Author: "Karmakar C" / Language: english - Searchworks@Jio Institute Digital Library Search Results

110 results on '"Karmakar C"'

1. DarpanX: A python package for modeling X-ray reflectivity of multilayer mirrors

Author: Mondal, B., Vadawale, S.V., Mithun, N.P.S., Vaishnava, C.S., Tiwari, N.K., Goyal, S.K., Panini, S.S., Navalkar, V., Karmakar, C., Patel, M.R., and Upadhyay, R.B.
Published: 2021
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2. Temporal dynamics of the circadian heart rate following low and high volume exercise training in sedentary male subjects

Author: Jelinek, Herbert F., Karmakar, C., Kiviniemi, A. M., Hautala, A. J., Tulppo, M. P., Mäkikallio, T. H., Huikuri, H. V., Khandoker, A. H., and Palaniswami, M.
Published: 2015
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3. Effect of ECG-derived respiration (EDR) on modeling ventricular repolarization dynamics in different physiological and psychological conditions

Author: Imam, M. H., Karmakar, C. K., Khandoker, A. H., and Palaniswami, M.
Published: 2014
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4. Investigating Relative Respiratory Effort Signals During Mixed Sleep Apnea Using Photoplethysmogram

Author: Khandoker, A. H., Karmakar, C. K., Penzel, T., Glos, M., and Palaniswami, M.
Published: 2013
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5. Risk stratification of cardiac autonomic neuropathy based on multi-lag Tone–Entropy

Author: Karmakar, C. K., Khandoker, A. H., Jelinek, H. F., and Palaniswami, M.
Published: 2013
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6. Poster presentations

Author: Olds, T., Blunden, S., Petkov, J., Forchino, F., Teng, A., Bartle, A., Sadeh, A., Mindell, J., Thompson, K., Richdale, A., Schreck, K., Gibson, R., Gander, P., Elder, D., Levendowski, D., Rosen, C., Berka, C., Zavora, T., Olmstead, R., Popovic, D., Westbrook, P., Piteo, A., Roberts, R., Nettelbeck, T., Lushington, K., Van Den Heuvel, C., Kohler, M., Martin, J., Kennedy, D., Jackman, A., Davey, M., Nixon, G., Hope, S., Catroppa, C., O’Driscoll, D., Anderson, V., Trinder, J., Horne, R., Milte, C., Sinn, N., Quach, J., Hiscock, H., Wake, M., Fulton, M., Sciberras, E., Efron, D., Oberklaid, F., Jay, S., Eng, A., ’t Mannetje, A., Cheng, S., Douwes, J., Ellison-Loschmann, L., Mclean, D., Pearce, N., Zhou, X., Sargent, C., Darwent, D., Ferguson, S., Paech, G., Mattews, R., Williams, L., Roach, G., Martin, D., Lastella, A., Matthews, R., Wilsmore, N., Galante, R., Lee, J., Barnes, M., Kennedy, G., Howard, M., Smith, S., Doye, G., Mangie, J., Signal, L., Phipps-Nelson, J., Redman, J., Rajaratnam, S., Lamond, N., Dorrian, J., Whitwell, B., Rogers, N., Sutherland, K., Chan, A. S. L., Deane, S. A., Zeng, B., Lee, R. W. W., Darendeliler, M. A., Cistulli, P. A., Spong, J., Brown, D., Berlowitz, D., Keihani, S. M., Hillman, D., Collins, A., Jackson, M., Pierce, R., O’Donoghue, F., Bignold, J., Mercer, J., Gorman, M., Mcevoy, D., Antic, N., Catcheside, P., Verma, M., Wheatley, J., Amis, T., Marshall, N., Grunstein, R., Peltonen, M., Carlson, L., Hedner, J., Stenlof, K., Sjostrom, L., Williams, S., Kennerson, M., Liu, P., Little, C., Watson, A., Dunn, N., Beevers, A., Douglas, J., Ruehland, W., Singh, P., Thornton, A., Copland, J., Rochford, P., Perri, R., Ward, K., Palmer, L., Mukherjee, S., Cooper, M., Love, G., Fedson, A., Simpson, L., Edwards, C., Szegner, B., Wong, K., Cistulli, P., Marks, G., Zwar, N., Norman, M., Middleton, S., Sullivan, C., Terrill, P., Mason, D., Parsley, C., Dakin, C., Wilson, S., Khandoker, A., Palaniswami, M., Karunajeewa, A., Abeyratne, U., Hukins, C., Lee, S., Borodzicz, J., Amatoury, J., Robinson, T., Ip, T., Mackenzie, J., Scott, E., Hickie, I., Lovato, N., Lack, L., Wright, H., Muller, D., van Den Berg, M., van Dongen, H. P. A., Miller, B., Orr, R., O’Connor, H., Chow, C. M., Litchfield, C., Glozier, N., Ogeil, R., Broadbear, J., Bakar, R. A., Denotti, A., Rae, C., Bartlett, D. J., Wong, K. K. H., Yang, Q., Walton, D., Sachinwalla, T., Grunstein, R. R., Dang, D., Cunnington, D., Swieca, J., Chen, Y., Young, A., Jakobson, A., Fitzgerald, P., Conduit, R., Smith, D., Jorgensen, G., Lee, H. L., Simpson, G., Ferns, J., Shepherd, K., James, A., Musk, A., Hunter, M., Eastwood, P., Duce, B., Al-Abri, M., Al-Hashmi, K., Jaju, D., Al-Rawas, O., Hassan, M., Ngan, A., Marshall, M. J., Dawson, A. D. G., Bucks, R. S., Walker, A., Hensley, R., Machaalani, R., Waters, K., Harrison, H., Tai, A., Raju, S., Williamson, B., Richardson, H. L., Walker, A. M., Horne, R. S. C., Yuill, M., Harris, M. A., Griffiths, A., Trang, L., Paramalingam, N., Davis, E., Jones, T., Stick, S., Wilson, A., Suresh, S., Cooper, D., Walsh, J., Maddison, K., Hoegh, T., Daulatzai, M., Karmakar, C., Khan, N., Bei, B., Nicholas, C., Worsnop, C., Jordan, A., Saboisky, J., White, D., Malhotra, A., Stadler, D., Mcevoy, R. D., Paul, D., Bradley, J., Maclean, J., Fitzgerald, D., Witcombe, N., Yiallourou, S., Sands, S., Ratnavadivel, R., George, K., Ryan, M., Thompson, C., Catcheside, P. G., Harmer, L., Deacon, N., Wang, D., Piper, A., Yee, B., Mihai, R., Davey, M. J., Nixon, G. M., Tyler, L., Vidal, A., Lambert, S., Tolson, J., Henderson, M., Maree, B., Campbell, A., Neill, A., Heraganahally, S., Bowden, J., Carney, S., Robinson, S., Sajkov, D., Bakker, J., Rixon, K., Hanssen, K., Chia, C., Sather, T., Keir, G., Chikazaza, M., Shirlaw, T., Jones, D., West, J., Dooney, N., Teo, M. Y., Falland, K., Phung, S., Cullen, S., Kevin, G., Mcardle, N., Joosten, S., Turton, A., Hamilton, G., Lavercombe, M., Hocking, V., Clarence, M., Thien, F., Senin, S. R., Ong, T. H., Ong, G., Roebuck, T., Ho, S., Langan-Fox, J., Davis, S., Van, E., Paul, E., Naughton, M., Iqbal, S. M., Gray, P., Urquhart, D., Williams, G., Verginis, N., Boynton, A., Gradinger, F., Partinen, M., Stucki, G., Cooper, P., Biggs, S., Dollman, J., Sweeney, B., Jones, L., Milgrom, J., Ericksen, J., Parry, B., Meliska, C., Sorenson, D., Lopez, A., Martinez, F., Nowakowski, S., Hauger, R., Elliott, J., Kripke, D., Duncan, S., Larsson, E., Fuller, J., Krass, I., Saini, B., and Junge, M.
Published: 2009
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7. Poster Presentations

Author: Maclean, J., Fitzgerald, D., Fitzsimons, D., Hayward, P., Waters, K., Chu, J., Richdale, A., Elder, D., Campbell, A., Larsen, P., Galletly, D., Cranage, S., Walter, L., Foster, A., Patterson, R., Nixon, G., Davey, M., Anderson, V., Trinder, J., Walker, A., Horne, R., Tan, S., Seton, C., Sandford, D., Dorrian, J., Blunden, S., Kohler, M., Thormaehlen, S., Kennedy, D., van den Heuvel, C., Lushington, K., Martin, J., Yorkston, S., Southwell, K., O’Driscoll, D., Gillman, A., Roebuck, T., van Braak, E., Naughton, M., Blake, J., Smith, S., Douglas, J., Sellers, R., Lee, R., Petocz, P., Prvan, T., Chan, A., Grunstein, R., Cistulli, P., Hiramatsu, R., Kasai, T., Maeno, K.-I., Tomo, Y., Kato, M., Kawana, F., Narui, K., Copland, J., Ho, M., Duggan, T., Harris, K., Vakulin, A., Antic, N., Catcheside, P., Mcevoy, D., Litchfield, C., Baulk, S., Neill, A., Wu, P., Amis, T., Lee, S., Verma, M., Wheatley, J., Sands, S., Edwards, B., Berger, P., Wilkinson, M., Wilkinson, V., Malhotra, A., Nicholas, C., Worsnop, C., Jordan, A., Butler, J., Saboisky, J., Gandevia, S., White, D., Ratnavadivel, R., Stadler, D., Windler, S., Bradley, J., Paul, D., Maddison, K., Walsh, J., Mclaughlin, R., Becker, S., Armstrong, J., Sampson, D., Hillman, D., Eastwood, P., Piper, A., Hollier, C., Flunt, D., Mendadue, C., Fiene, A., Robinson, P., Jorgensen, G., Sather, T., Hukins, C., Jackson, M., Radford, L., Kennedy, G., Swann, P., Pierce, R., Howard, M., Jay, S., Thomas, M., Weissenfeld, A., Dawson, D., Ferguson, S., Sletten, T., Revell, V., Middleton, B., Lederle, K., Skene, D., Segal, A., Redman, J., Lockley, S., Rajaratnam, S., Lovato, N., Lack, L., Wright, H., Bambrick, C., Swann, C., Yelland, G., Roach, G., Darwent, D., O’Keeffe, K., Gander, P., Scott, G., Scott, H., Coussens, S., Baumert, M., Pamula, Y., Saint, D., Terrill, P., Wilson, S., Dakin, C., Suresh, S., Cooper, D., Michell, B., Salvini, A., Gulliver, T., Longley, J., Heussler, H., Parsley, C., Wawruszak, M., Verginis, N., Yang, J., Gyulay, S., Pretto, J., Hensley, M., Marshall, N., Wong, K., Phillips, C., Liu, P., Knuiman, M., Liaw, H. S., Veale, A., Homan, S., Wilson, D., Ellett, L., Crowe, S., Barnes, M., Spong, J., Riley, D., Brown, D., Berlowitz, D., Lee, J., Fedson, A., Simpson, L., Ward, K., Love, G., Cooper, M., Singh, B., Palmer, L., Mukherjee, S., Grant, K., Robillard, R., Boissonneault, M., Martin, N., Filipini, D., Prince, F., Carrier, J., Sukovic, A., Sweeney, B., Signal, L., Ellison-Loschmann, L., Shekleton, J., Parcell, D., Phipps-Nelson, J. O., Ponsford, J., Ho, S., Conduit, R., Stuart, K., Bei, B., Milgrom, J., Ericksen, J., Bakker, J., Turton, A., Kumagai, T., Kasagi, S., Ishiwata, S., Burgess, K., Havryk, A., Whitelaw, W. A., Mikel, M., Newing, G., Newton, S., Rixon, K., Cheney, L., Chikazaza, M., Clarke, P., Duce, B., Hanssen, K., Milosavljevic, J., Popovich, J., Saarinen, K., Shirlaw, T., Khandoker, A., Gubbi, J., Karmakar, C., Palaniswami, M., Keir, G., Rochford, P., Ruehland, W., Thornton, A., Potts, A., Warman, G., Anderson, B., Wanklyn, C., Biggs, S., Blecher, G., Evans, C., Wilson, A., Nadasan, M., Nguyen, K., Dollman, J., Herbert, A., Delima, J., Collins, J., Tang, J., Goh, A., Teoh, O. H., Chay, O. M., Tan, C. H., Gibson, R., Cheng, S., Brogan, S.-B., Duckett, H., Douwes, J., Kabir, M., Dimitri, H., Sanders, P., Abbott, D., Roy, A., Antic, R., Young, T., Anson, M., Bergman, N., O’Donoghue, F., Teuwen, P., Morrison, S., Allen, R., Silburn, P., Mcwhae, S., Rose, A., Harmer, L., Yeo, A., Jurisevic, M., Mercer, J., Muller, D., van den Berg, M., Garden, A., Cvetkovic, D., Cosic, I., Zhou, X., Matthews, R., Croucher, N., Weng, T., Williams, L., Sargent, C., Halson, S., Tokley, M., Ball, M., Bruck, D., Sutherland, K., Schwab, R., Zeng, B., Darendeliler, M. A., Rowland, S., Hennessy, C., Tang, T., Song, P., Rahim, S. A., Ong, T. H., Noakes, M., Southcott, A. M., Smith, B., Woods, M., Mclean, N., Godde, K., Kirkness, J., and Daulatzai, M.
Published: 2008
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8. Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Author: Brown, P. Zhou, Y. Tan, A.-C. El-Esawi, M.A. Liehr, T. Blanck, O. Gladue, D.P. Almeida, G.M.F. Cernava, T. Sorzano, C.O. Yeung, A.W.K. Engel, M.S. Chandrasekaran, A.R. Muth, T. Staege, M.S. Daulatabad, S.V. Widera, D. Zhang, J. Meule, A. Honjo, K. Pourret, O. Yin, C.-C. Zhang, Z. Cascella, M. Flegel, W.A. Goodyear, C.S. van Raaij, M.J. Bukowy-Bieryllo, Z. Campana, L.G. Kurniawan, N.A. Lalaouna, D. Hüttner, F.J. Ammerman, B.A. Ehret, F. Cobine, P.A. Tan, E.-C. Han, H. Xia, W. McCrum, C. Dings, R.P.M. Marinello, F. Nilsson, H. Nixon, B. Voskarides, K. Yang, L. Costa, V.D. Bengtsson-Palme, J. Bradshaw, W. Grimm, D.G. Kumar, N. Martis, E. Prieto, D. Sabnis, S.C. Amer, S.E.D.R. Liew, A.W.C. Perco, P. Rahimi, F. Riva, G. Zhang, C. Devkota, H.P. Ogami, K. Basharat, Z. Fierz, W. Siebers, R. Tan, K.H. Boehme, K.A. Brenneisen, P. Brown, J.A.L. Dalrymple, B.P. Harvey, D.J. Ng, G. Werten, S. Bleackley, M. Dai, Z. Dhariwal, R. Gelfer, Y. Hartmann, M.D. Miotla, P. Tamaian, R. Govender, P. Gurney-Champion, O.J. Kauppila, J.H. Zhang, X. Echeverría, N. Subhash, S. Sallmon, H. Tofani, M. Bae, T. Bosch, O. Cuív, P.O. Danchin, A. Diouf, B. Eerola, T. Evangelou, E. Filipp, F. Klump, H. Kurgan, L. Smith, S.S. Terrier, O. Tuttle, N. Ascher, D.B. Janga, S.C. Schulte, L.N. Becker, D. Browngardt, C. Bush, S.J. Gaullier, G. Ide, K. Meseko, C. Werner, G.D.A. Zaucha, J. Al-Farha, A.A. Greenwald, N.F. Popoola, S.I. Rahman, S. Xu, J. Yang, S.Y. Hiroi, N. Alper, O.M. Baker, C.I. Bitzer, M. Chacko, G. Debrabant, B. Dixon, R. Forano, E. Gilliham, M. Kelly, S. Klempnauer, K.-H. Lidbury, B.A. Lin, M.Z. Lynch, I. Ma, W. Maibach, E.W. Mather, D.E. Nandakumar, K.S. Ohgami, R.S. Parchi, P. Tressoldi, P. Xue, Y. Armitage, C. Barraud, P. Chatzitheochari, S. Coelho, L.P. Diao, J. Doxey, A.C. Gobet, A. Hu, P. Kaiser, S. Mitchell, K.M. Salama, M.F. Shabalin, I.G. Song, H. Stevanovic, D. Yadollahpour, A. Zeng, E. Zinke, K. Alimba, C.G. Beyene, T.J. Cao, Z. Chan, S.S. Gatchell, M. Kleppe, A. Piotrowski, M. Torga, G. Woldesemayat, A.A. Cosacak, M.I. Haston, S. Ross, S.A. Williams, R. Wong, A. Abramowitz, M.K. Effiong, A. Lee, S. Abid, M.B. Agarabi, C. Alaux, C. Albrecht, D.R. Atkins, G.J. Beck, C.R. Bonvin, A.M.J.J. Bourke, E. Brand, T. Braun, R.J. Bull, J.A. Cardoso, P. Carter, D. Delahay, R.M. Ducommun, B. Duijf, P.H.G. Epp, T. Eskelinen, E.-L. Fallah, M. Farber, D.B. Fernandez-Triana, J. Feyerabend, F. Florio, T. Friebe, M. Furuta, S. Gabrielsen, M. Gruber, J. Grybos, M. Han, Q. Heinrich, M. Helanterä, H. Huber, M. Jeltsch, A. Jiang, F. Josse, C. Jurman, G. Kamiya, H. de Keersmaecker, K. Kristiansson, E. de Leeuw, F.-E. Li, J. Liang, S. Lopez-Escamez, J.A. Lopez-Ruiz, F.J. Marchbank, K.J. Marschalek, R. Martín, C.S. Miele, A.E. Montagutelli, X. Morcillo, E. Nicoletti, R. Niehof, M. O'Toole, R. Ohtomo, T. Oster, H. Palma, J.-A. Paterson, R. Peifer, M. Portilla, M. Portillo, M.C. Pritchard, A.L. Pusch, S. Raghava, G.P.S. Roberts, N.J. Ross, K. Schuele, B. Sergeant, K. Shen, J. Stella, A. Sukocheva, O. Uversky, V.N. Vanneste, S. Villet, M.H. Viveiros, M. Vorholt, J.A. Weinstock, C. Yamato, M. Zabetakis, I. Zhao, X. Ziegler, A. Aizat, W.M. Atlas, L. Bridges, K.M. Chakraborty, S. Deschodt, M. Domingues, H.S. Esfahlani, S.S. Falk, S. Guisado, J.L. Kane, N.C. Kueberuwa, G. Lau, C.L. Liang, D. Liu, E. Luu, A.M. Ma, C. Ma, L. Moyer, R. Norris, A.D. Panthee, S. Parsons, J.R. Peng, Y. Pinto, I.M. Reschke, C.R. Sillanpää, E. Stewart, C.J. Uhle, F. Yang, H. Zhou, K. Zhu, S. Ashry, M. Bergsland, N. Berthold, M. Chen, C.-E. Colella, V. Cuypers, M. Eskew, E.A. Fan, X. Gajda, M. Gonzálezlez-Prendes, R. Goodin, A. Graham, E.B. Groen, E.J.N. Gutiérrez-Sacristán, A. Habes, M. Heffler, E. Higginbottom, D.B. Janzen, T. Jayaraman, J. Jibb, L.A. Jongen, S. Kinyanjui, T. Koleva-Kolarova, R.G. Li, Z. Liu, Y.-P. Lund, B.A. Lussier, A.A. Ma, L. Mier, P. Moore, M.D. Nagler, K. Orme, M.W. Pearson, J.A. Prajapati, A.S. Saito, Y. Tröder, S.E. Uchendu, F. Verloh, N. Voutchkova, D.D. Abu-Zaid, A. Bakkach, J. Baumert, P. Dono, M. Hanson, J. Herbelet, S. Hobbs, E. Kulkarni, A. Kumar, N. Liu, S. Loft, N.D. Reddan, T. Senghore, T. Vindin, H. Xu, H. Bannon, R. Chen, B. Cheung, J.T.K. Cooper, J. Esnakula, A.K. Feghali, K.A. Ghelardi, E. Gnasso, A. Horbar, J. Lai, H.M. Li, J. Ma, L. Ma, R. Pan, Z. Peres, M.A. Pranata, R. Seow, E. Sydes, M. Testoni, I. Westermair, A.L. Yang, Y. Afnan, M. Albiol, J. Albuquerque, L.G. Amir, S. Amiya, E. Amorim, R.M. An, Q. Andersen, S.U. Aplin, J.D. Argyropoulos, C. Asmann, Y.W. Assaeed, A.M. Atanasov, A.G. Atchison, D.A. Avery, S.V. Avillach, P. Baade, P.D. Backman, L. Badie, C. Baldi, A. Ball, E. Bardot, O. Barnett, A.G. Basner, M. Batra, J. Bazanova, O.M. Beale, A. Beddoe, T. Bell, M.L. Berezikov, E. Berners-Price, S. Bernhardt, P. Berry, E. Bessa, T.B. Billington, C. Birch, J. Blakely, R.D. Blaskovich, M.A.T. Blum, R. Boelaert, M. Bogdanos, D. Bosch, C. Bourgoin, T. Bouvard, D. Boykin, L.M. Bradley, G. Braun, D. Brownlie, J. Brühl, A. Burt, A. Butler, L.M. Byrareddy, S.N. Byrne, H.J. Cabantous, S. Calatayud, S. Candal, E. Carlson, K. Casillas, S. Castelvetro, V. Caswell, P.T. Cavalli, G. Cerovsky, V. Chagoyen, M. Chen, C.-S. Chen, D.F. Chen, H. Chen, H. Chen, J.-T. Chen, Y. Cheng, C. Cheng, J. Chinapaw, M. Chinopoulos, C. Cho, W.C.S. Chong, L. Chowdhury, D. Chwalibog, A. Ciresi, A. Cockcroft, S. Conesa, A. Cook, P.A. Cooper, D.N. Coqueret, O. Corea, E.M. Costa, A. Costa, E. Coupland, C. Crawford, S.Y. Cruz, A.D. Cui, H. Cui, Q. Culver, D.C. D'Angiulli, A. Dahms, T.E.S. Daigle, F. Dalgleish, R. Danielsen, H.E. Darras, S. Davidson, S.M. Day, D.A. Degirmenci, V. Demaison, L. Devriendt, K. Ding, J. Dogan, Y. Dong, X.C. Donner, C.F. Dressick, W. Drevon, C.A. Duan, H. Ducho, C. Dumaz, N. Dwarakanath, B.S. Ebell, M.H. Eisenhardt, S. Elkum, N. Engel, N. Erickson, T.B. Fairhead, M. Faville, M.J. Fejzo, M.S. Festa, F. Feteira, A. Flood-Page, P. Forsayeth, J. Fox, S.A. Franks, S.J. Frentiu, F.D. Frilander, M.J. Fu, X. Fujita, S. Galea, I. Galluzzi, L. Gani, F. Ganpule, A.P. García-Alix, A. Gedye, K. Giordano, M. Giunta, C. Gleeson, P.A. Goarant, C. Gong, H. Gora, D. Gough, M.J. Goyal, R. Graham, K.E. Grande-Pérez, A. Graves, P.M. Greidanus, H. Grice, D. Grunau, C. Gumulya, Y. Guo, Y. Gurevich, V.V. Gusev, O. Hacker, E. Hage, S.R. Hagen, G. Hahn, S. Haller, D.M. Hammerschmidt, S. Han, J. Han, R. Handfield, M. Hapuarachchi, H.C. Harder, T. Hardingham, J.E. Heck, M. Heers, M. Hew, K.F. Higuchi, Y. Hilaire, C.St. Hilton, R. Hodzic, E. Hone, A. Hongoh, Y. Hu, G. Huber, H.P. Hueso, L.E. Huirne, J. Hurt, L. Idborg, H. Ikeo, K. Ingley, E. Jakeman, P.M. Jensen, A. Jia, H. Jia, H. Jia, S. Jiang, J. Jiang, X. Jin, Y. Jo, D. Johnson, A.M. Johnston, M. Jonscher, K.R. Jorens, P.G. Jorgensen, J.O.L. Joubert, J.W. Jung, S.-H. Junior, A.M. Kahan, T. Kamboj, S.K. Kang, Y.-K. Karamanos, Y. Karp, N.A. Kelly, R. Kenna, R. Kennedy, J. Kersten, B. Khalaf, R.A. Khalid, J.M. Khatlani, T. Khider, T. Kijanka, G.S. King, S.R.B. Kluz, T. Knox, P. Kobayashi, T. Koch, K.-W. Kohonen-Corish, M.R.J. Kong, X. Konkle-Parker, D. Korpela, K.M. Kostrikis, L.G. Kraiczy, P. Kratz, H. Krause, G. Krebsbach, P.H. Kristensen, S.R. Kumari, P. Kunimatsu, A. Kurdak, H. Kwon, Y.D. Lachat, C. Lagisz, M. Laky, B. Lammerding, J. Lange, M. Larrosa, M. Laslett, A.L. Laverman, G.D. Leclair, E.E. Lee, K.-W. Lee, M.-Y. Lee, M.-S. Li, G. Li, J. Lieb, K. Lim, Y.Y. Lindsey, M.L. Line, P.-D. Liu, D. Liu, F. Liu, H. Liu, H. Lloyd, V.K. Lo, T.-W. Locci, E. Loidl, J. Lorenzen, J. Lorkowski, S. Lovell, N.H. Lu, H. Lu, W. Lu, Z. Luengo, G.S. Lundh, L.-G. Lysy, P.A. Mabb, A. Mack, H.G. Mackey, D.A. Mahdavi, S.R. Maher, P. Maher, T. Maity, S.N. Malgrange, B. Mamoulakis, C. Mangoni, A.A. Manke, T. Manstead, A.S.R. Mantalaris, A. Marsal, J. Marschall, H.-U. Martin, F.L. Martinez-Raga, J. Martinez-Salas, E. Mathieu, D. Matsui, Y. Maza, E. McCutcheon, J.E. McKay, G.J. McMillan, B. McMillan, N. Meads, C. Medina, L. 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Pheko, M. Pinto, K.A. Piovesan, A. Pluess, M. Podolsky, I.M. Prescott, J. Qi, D. Qi, X. Raikou, V.D. Ranft, A. Rhodes, J. Rotge, J.-Y. Rowe, A.D. Saggar, M. Schuon, R.A. Shahid, S. Shalchyan, V. Shirvalkar, P. Shiryayev, O. Singh, J. Smout, M.J. Soares, A. Song, C. Srivastava, K. Srivastava, R.K. Sun, J. Szabo, A. Szymanski, W. Tai, C.N.P. Takeuchi, H. Tanadini-Lang, S. Tang, F. Tao, W. Theron, G. Tian, C.F. Tian, Y.-S. Tuttle, L.M. Valenti, A. Verlot, P. Walker, M. Wang, J. Welter, D. Winslade, M. Wu, D. Wu, Y.-R. Xiao, H. Xu, B. Xu, J. Xu, Z. Yang, D. Yang, M. Yankilevich, P. You, Y. Yu, C. Zhan, J. Zhang, G. Zhang, K. Zhang, T. Zhang, Y. Zhao, G. Zhao, J. Zhou, X. Zhu, Z. Ajani, P.A. Anazodo, U.C. Bagloee, S.A. Bail, K. Bar, I. Bathelt, J. Benkeser, D. Bernier, M.L. Blanchard, A.M. Boakye, D.W. Bonatsos, V. Boon, M.H. Bouboulis, G. Bromfield, E. Brown, J. Bul, K.C.M. Burton, K.J. Butkowski, E.G. Carroll, G. Chao, F. Charrier, E.E. Chen, X. Chen, Y.-C. Chenguang Choi, J.R. Christoffersen, T. Comel, J.C. Cosse, C. Cui, Y. van Dessel, P. Dhaval Diodato, D. Duffey, M. Dutt, A. Egea, L.G. El-Said, M. Faye, M. Fernandez-Fernandez, B. Foley, K.G. Founou, L.L. Fu, F. Gadelkareem, R.A. Galimov, E. Garip, G. Gemmill, A. Gouil, Q. Grey, J. Gridneva, Z. Grothe, M.J. Grébert, T. Guerrero, F. Guignard, L. Haenssgen, M.J. Hasler, D. Holgate, J.Y. Huang, A. Hulse-Kemp, A.M. Jean-Quartier, C. Jeon, S.-M. Jia, Y. Jutzeler, C. Kalatzis, P. Karim, M. Karsay, K. Keitel, A. Kempe, A. Keown, J.R. Khoo, C.M. Khwaja, N. Kievit, R.A. Kosanic, S. Koutoukidis, D.A. Kramer, P. Kumar, D. Kiraǧ, N. Lanza, G. Le, T.D. Leem, J.W. Leightley, D. Leite, A. Lercher, L. Li, Y. Lim, R. Lima, L.R.A. Lin, L. Ling, T. Liu, Y. Liu, Z. Lu, Y. Lum, F.M. Luo, H. Machhi, J. Macleod, A. Macwan, I. Madala, H.R. Madani, N. de Maio, N. Makowiecki, K. Mallinson, D.J. Margelyte, R. Maria, C. Markonis, Y. Marsili, L. Mavoa, S. McWilliams, L. Megersa, M. Souto-Maior, C. Menichetti, J. Mercieca-Bebber, R. Miller, J.J. Minde, D.-P.M. Minges, A. Mishra, E. Mishra, V.R. Moores, C. Morrice, N. Moskalensky, A.E. Navarin, N. Negera, E. Nolet, P. Nordberg, A. Nordén, R. Nowicki, J.P. Olova, N. Olszewski, P. Onzima, R. Pan, C.-L. Park, C. Park, D.I. Park, S. Patil, C.D. Pedro, S.A. Perry, S.R. Peter, J. Peterson, B.M. Pezzuolo, A. Pozdnyakov, I. Qian, S. Qin, L. Rafe, A. Raote, I. Raza, A. Rebl, H. Refai, O. Regan, T. Richa, T. Richardson, M.F. Robinson, K.R. Rossoni, L. Rouet, R. Safaei, S. Schneeberger, P.H.H. Schwotzer, D. Sebastian, A. Selinski, J. Seltmann, S. Sha, F. Shalev, N. Shang, J.-L. Singer, J. Singh, M. Smith, T. Solomon-Moore, E. Song, L. Soraggi, S. Stanley, R. Steckhan, N. Strobl, F. Subissi, L. Supriyanto, I. Surve, C.R. Suzuki, T. Syme, C. Sörelius, K. Tang, Y. Tantawy, M. Tennakoon, S. Teseo, S. Toelzer, C. Tomov, N. Tovar, M. Tran, L. Tripathi, S. Tuladhar, A.M. Ukubuiwe, A.C. Ung, C.O.L. Valgepea, K. Vatanparast, H. Vidal, A. Wang, F. Wang, Q. Watari, R. Webster, R. Webster, R. Wei, J. Wibowo, D. Wingenbach, T.S.H. Xavier, R.M. Xiao, S. Xiong, P. Xu, S. Xu, S. Yao, R. Yao, W. Yin, Q. Yu, Y. Zaitsu, M. Zeineb, Z. Zhan, X.-Y. Zhang, J. Zhang, R. Zhang, W. Zhang, X. Zheng, S. Zhou, B. Zhou, X. Ahmad, H. Akinwumi, S.A. Albery, G.F. Alhowimel, A. Ali, J. Alshehri, M. Alsuhaibani, M. Anikin, A. Azubuike, S.O. Bach-Mortensen, A. Baltiansky, L. Bartas, M. Belachew, K.Y. Bhardwaj, V. Binder, K. Bland, N.S. Boah, M. Bullen, B. Calabrò, G.E. Callahan, T.J. Cao, B. Chalmers, K. Chang, W. Che, Z. Chen, A.T.Y. Chen, H. Chen, H. Chen, Y. Chen, Z. Choi, Y. Chowdhury, M.A.K. Christensen, M.R. Cooke, R.S.C. Cottini, M. Covington, N.V. Cunningham, C. Delarocque, J. Devos, L. Dhar, A.R. Ding, K.-F. Dong, K. Dong, Z. Dreyer, N. Ekstrand, C. Fardet, T. Feleke, B.E. Feurer, T. Freitas, A. Gao, T. Gebremedhin Giganti, F. Grabowski, P. Guerra-Mora, J.R. Guo, C. Guo, X. Gupta, H. He, S. Heijne, M. Heinemann, S. Hogrebe, A. Huang, Z. Iskander-Rizk, S. Iyer, L.M. Jahan, Y. James, A.S. Joel, E. Joffroy, B. Jégousse, C. Kambondo, G. Karnati, P. Kaya, C. Ke, A. Kelly, D. Kickert, R. Kidibule, P.E. Kieselmann, J.P. Kim, H.J. Kitazawa, T. Lamberts, A. Li, Y. Liang, H. Linn, S.N. Litfin, T. Liusuo, W. Lygirou, V. Mahato, A.K. Mai, Z.-M. Major, R.W. Mali, S. Mallis, P. Mao, W. Marvin-Dowle, K. Mason, L.D. Merideth, B. Merino-Plaza, M.J. Merlaen, B. Messina, R. Mishra, A.K. Muhammad, J. Musinguzi, C. Nanou, A. Naqash, A. Nguyen, J.T. Nguyen, T.T.H. Ni, D. Nida Notcovich, S. Ohst, B. Ollivier, Q.R. Osses, D.F. Peng, X. Plantinga, A. Pulia, M. Rafiq, M. Raman, A. Raucher-Chéné Rawski, R. Ray, A. Razak, L.A. Rudolf, K. Rusch, P. Sadoine, M.L. Schmidt, A. Schurr, R. Searles, S. Sharma, S. Sheehan, B. Shi, C. Shohayeb, B. Sommerlad, A. Strehlow, J. Sun, X. Sundar, R. Taherzadeh, G. Tahir, N.D.M. Tang, J. Testa, J. Tian, Z. Tingting, Q. Verheijen, G.P. Vickstrom, C. Wang, T. Wang, X. Wang, Z. Wei, P. Wilson, A. Wyart Yassine, A.-A. Yousefzadeh, A. Zare, A. Zeng, Z. Zhang, C. Zhang, H. Zhang, L. Zhang, T. Zhang, W. Zhang, Z. Zhou, J. Zhu, D. Adamo, V. Adeyemo, A.A. Aggelidou, M. Al-Owaifeer, A.M. Al-Riyami, A.Z. Alzghari, S.K. Andersen, V. Angus, K. Asaduzzaman, M. Asady, H. Ato, D. Bai, X. Baines, R.L. Ballantyne, M. Ban, B. Beck, J. Ben-Nafa, W. Black, E. Blancher, A. Blankstein, R. Bodagh, N. Borges, P. Brooks, A. Brox-Ponce, J. Brunetti, A. Canham, C.D. Carninci, P. Carvajal, R. Chang, S.C. Chao, J. Chatterjee, P. Chen, H. Chen, L. Chen, Y.-C. Chhatriwalla, A.K. Chikowe, I. Chuang, T.-J. Collevatti, R.G. Cornejo, D.A.V. Cuenda, A. Dao, M. Dauga, D. Deng, Z. Devkota, K. Doan, L.V. Elewa, Y.H.A. Fan, D. Faruk, M. Feifei, S. Ferguson, T.S. Fleres, F. Foster, E.J. Foster, S. Furer, T. Gao, Y. Garcia-Rivera, E.J. Gazdar, A. George, R.B. Ghosh, S. Gianchecchi, E. Gleason, J.M. Hackshaw, A. Hall, A. Hall, R. Harper, P. Hogg, W.E. Huang, G. Hunter, K.E. Ijzerman, A.P. Jesus, C. Jian, G. Lewis, J.S., Jr. Kanj, S.S. Kaur, H. Kelly, S. Kheir, F. Kichatova, V.S. Kiyani, M. Klein, R. Kovesi, T. Kraschnewski, J.L. Kumar, A.P. Labutin, D. Lazo-Langner, A. Leclercq, G. Li, M. Li, Q. Li, T. Li, Y. Liao, W.-T. Liao, Z.-Y. Lin, J. Lizer, J. Lobreglio, G. Lowies, C. Lu, C. Majeed, H. Martin, A. Martinez-Sobrido, L. Meresh, E. Middelveen, M. Mohebbi, A. Mota, J. Mozaheb, Z. Muyaya, L. Nandhakumar, A. Ng, S.H.X. Obeidat, M. Oh, D.-H. Owais, M. Pace-Asciak, P. Panwar, A. Park, C. Patterson, C. Penagos-Tabaree, F. Pianosi, P.T. Pinzi, V. Pridans, C. Psaroulaki, A. Pujala, R.K. Pulido-Arjona, L. Qi, P.-F. Rahman, P. Rai, N.K. Rassaf, T. Refardt, J. Ricciardi, W. Riess, O. Rovas, A. Sacks, F.M. Saleh, S. Sampson, C. Schmutz, A. Sepanski, R. Sharma, N. Singh, M. Spearman, P. Subramaniapillai, M. Swali, R. Tan, C.M. Tellechea, J.I. Thomas, L.-M. Tong, X. Vavvas, D.G. Veys, R. Vitriol, V. Wang, H.-D. Wang, J. Wang, J. Waugh, J. Webb, S.A. Williams, B.A. Workman, A.D. Xiang, T. Xie, L.-X. Xu, J. Xu, T. Yang, C. Yoon, J.G. Yuan, C.M. Zaritsky, A. Zhang, Y. Zhao, H. Zuckerman, H. Lyu, R. Pullan, W. RELISH Consortium
Abstract: Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press.
Published: 2019

9. Forewarning of incidence of Spodoptera litura (Tobacco caterpillar) in soybean and cotton using statistical and synoptic approach.

Author: CHATTOPADHYAY, N., BALASUBRAMANIAM, R., ATTRI, S. D., RAY, KAMALJEET, JOHN, GRACY, KHEDIKAR, S., and KARMAKAR, C.
Subjects: SPODOPTERA littoralis, SOYBEAN, WEATHER forecasting, COTTON, HUMIDITY, PHEROMONE traps
Abstract: A study on the effect of weather parameters on the the population dynamics of Spodoptera litura (S.litura) in soybean and cotton during kharif season using six years pest data (pheromone trap catches) at Niphad and Rahuri in Maharashtra showed that rainfall two weeks prior, Tmax and Tmin during the week of incidence signifiantly contributed towards the occurrence of S.litura in soybean. Maximum temperature and morning humidity during the week and one week prior were found to be favourable for the incidence of S. litura in cotton. Temperature (maximum: 26-27°C & minimum: 21-22°C), morning relative humidity (above 90%) and rainfall during one week prior were found to be congenial weather parameters for the outbreak of the pest in soybean. Similarly, maximum temperature around 32-33°C, minimum temperature around 22-23°C, morning relative humidity around 90 per cent, sunshine hours about 4 hrs day-1 and rainfall during the previous 2 weeks favoured heavy incidence of S.litura in cotton crop during flowering to boll formation stages. It is also shown how the incidence of S.litura in soybean and cotton can be predicted well in advance using the observed relationship of the pest with weather parameters as well as weather forecast. [ABSTRACT FROM AUTHOR]
Published: 2019

10. Changes in heart rate circadian rhythm following exercise in middle-aged men.

Author: Jelinek, HF, Karmakar, C, Kiviniemi, AM, Tulppo, MP, Makikallio, TH, Hautala, AL, Huikuri, HV, Khandoker, AF, and Palaniswami, M
Published: 2015
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11. Drusen quantification for early identification of age related macular degeneration (AMD) using color fundus imaging.

Author: Bhuiyan, Alauddin, Karmakar, C., Xiao, Di, Ramamohanarao, Kotagiri, and Kanagasingam, Yogi
Published: 2013
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12. Heart rate asymmetry in altered parasympathetic nervous system activity.

Author: Karmakar, C., Khandoker, A., and Palaniswami, M.
Published: 2010

13. Perturbation in parasympathetic nervous system activity affects temporal structure of Poincaré plot.

Author: Karmakar, C., Khandoker, A., and Palaniswami, M.
Published: 2010

14. Unravelling unique qualitative and quantitative characteristics of the surface submentalis EMG in OSA polysomnograms.

Author: Daulatzai, M., Karmakar, C., Khan, N., Khandoker, A., and Palaniswami, M.
Published: 2010
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15. Lateral decubitus posture during sleep: Sub-groups of obstructive sleep apnea patients — therapeutic value of vertical position in OSA.

Author: Daulatzai, M.A., Khan, N., Karmakar, C., Khandoker, A., and Palaniswami, M.
Published: 2009
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16. Phylogeny Inference Using a Multi-objective Evolutionary Algorithm with Indirect Representation.

Author: Hassan, Md. Rafiul, Hossain, M. Maruf, Karmakar, C. K., and Kirley, Michael
Abstract: The inference of phylogenetic trees is one of the most important tasks in computational biology. In this paper, we propose an extension to multi-objective evolutionary algorithms to address this problem. Here, we adopt an enhanced indirect encoding for a tree using the corresponding Prüfer code represented in Newick format. The algorithm generates a range of non-dominated trees given alternative fitness measures such as statistical likelihood and maximum parsimony. A key feature of this approach is the preservation of the evolutionary hierarchy between species. Preliminary experimental results indicate that our model is capable of generating a set of optimized phylogenetic trees for given species data and the results are comparable with other techniques. [ABSTRACT FROM AUTHOR]
Published: 2008
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17. Sensitivity of temporal heart rate variability in Poincaré plot to changes in parasympathetic nervous system activity

Author: Voss Andreas, Khandoker Ahsan H, Karmakar Chandan K, and Palaniswami Marimuthu
Subjects: Medical technology, R855-855.5
Abstract: Abstract Background A novel descriptor (Complex Correlation Measure (CCM)) for measuring the variability in the temporal structure of Poincaré plot has been developed to characterize or distinguish between Poincaré plots with similar shapes. Methods This study was designed to assess the changes in temporal structure of the Poincaré plot using CCM during atropine infusion, 70° head-up tilt and scopolamine administration in healthy human subjects. CCM quantifies the point-to-point variation of the signal rather than gross description of the Poincaré plot. The physiological relevance of CCM was demonstrated by comparing the changes in CCM values with autonomic perturbation during all phases of the experiment. The sensitivities of short term variability (SD1), long term variability (SD2) and variability in temporal structure (CCM) were analyzed by changing the temporal structure by shuffling the sequences of points of the Poincaré plot. Surrogate analysis was used to show CCM as a measure of changes in temporal structure rather than random noise and sensitivity of CCM with changes in parasympathetic activity. Results CCM was found to be most sensitive to changes in temporal structure of the Poincaré plot as compared to SD1 and SD2. The values of all descriptors decreased with decrease in parasympathetic activity during atropine infusion and 70° head-up tilt phase. In contrast, values of all descriptors increased with increase in parasympathetic activity during scopolamine administration. Conclusions The concordant reduction and enhancement in CCM values with parasympathetic activity indicates that the temporal variability of Poincaré plot is modulated by the parasympathetic activity which correlates with changes in CCM values. CCM is more sensitive than SD1 and SD2 to changes of parasympathetic activity.
Published: 2011
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18. Toe clearance and velocity profiles of young and elderly during walking on sloped surfaces

Author: Begg Rezaul K, Karmakar Chandan K, Lynch Kate, Khandoker Ahsan H, and Palaniswami Marimuthu
Subjects: Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Abstract Background Most falls in older adults are reported during locomotion and tripping has been identified as a major cause of falls. Challenging environments (e.g., walking on slopes) are potential interventions for maintaining balance and gait skills. The aims of this study were: 1) to investigate whether or not distributions of two important gait variables [minimum toe clearance (MTC) and foot velocity at MTC (VelMTC)] and locomotor control strategies are altered during walking on sloped surfaces, and 2) if altered, are they maintained at two groups (young and elderly female groups). Methods MTC and VelMTC data during walking on a treadmill at sloped surfaces (+3°, 0° and -3°) were analysed for 9 young (Y) and 8 elderly (E) female subjects. Results MTC distributions were found to be positively skewed whereas VelMTC distributions were negatively skewed for both groups on all slopes. Median MTC values increased (Y = 33%, E = 7%) at negative slope but decreased (Y = 25%, E = 15%) while walking on the positive slope surface compared to their MTC values at the flat surface (0°). Analysis of VelMTC distributions also indicated significantly (p < 0.05) lower minimum and 25th percentile (Q1) values in the elderly at all slopes. Conclusion The young displayed a strong positive correlation between MTC median changes and IQR (interquartile range) changes due to walking on both slopes; however, such correlation was weak in the older adults suggesting differences in control strategies being employed to minimize the risk of tripping.
Published: 2010
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19. Complex Correlation Measure: a novel descriptor for Poincaré plot

Author: Gubbi Jayavardhana, Khandoker Ahsan H, Karmakar Chandan K, and Palaniswami Marimuthu
Subjects: Medical technology, R855-855.5
Abstract: Abstract Background Poincaré plot is one of the important techniques used for visually representing the heart rate variability. It is valuable due to its ability to display nonlinear aspects of the data sequence. However, the problem lies in capturing temporal information of the plot quantitatively. The standard descriptors used in quantifying the Poincaré plot (SD1, SD2) measure the gross variability of the time series data. Determination of advanced methods for capturing temporal properties pose a significant challenge. In this paper, we propose a novel descriptor "Complex Correlation Measure (CCM)" to quantify the temporal aspect of the Poincaré plot. In contrast to SD1 and SD2, the CCM incorporates point-to-point variation of the signal. Methods First, we have derived expressions for CCM. Then the sensitivity of descriptors has been shown by measuring all descriptors before and after surrogation of the signal. For each case study, lag-1 Poincaré plots were constructed for three groups of subjects (Arrhythmia, Congestive Heart Failure (CHF) and those with Normal Sinus Rhythm (NSR)), and the new measure CCM was computed along with SD1 and SD2. ANOVA analysis distribution was used to define the level of significance of mean and variance of SD1, SD2 and CCM for different groups of subjects. Results CCM is defined based on the autocorrelation at different lags of the time series, hence giving an in depth measurement of the correlation structure of the Poincaré plot. A surrogate analysis was performed, and the sensitivity of the proposed descriptor was found to be higher as compared to the standard descriptors. Two case studies were conducted for recognizing arrhythmia and congestive heart failure (CHF) subjects from those with NSR, using the Physionet database and demonstrated the usefulness of the proposed descriptors in biomedical applications. CCM was found to be a more significant (p = 6.28E-18) parameter than SD1 and SD2 in discriminating arrhythmia from NSR subjects. In case of assessing CHF subjects also against NSR, CCM was again found to be the most significant (p = 9.07E-14). Conclusion Hence, CCM can be used as an additional Poincaré plot descriptor to detect pathology.
Published: 2009
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20. Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Author: Zeineb, Zian, Brown, Peter, Tan, Aik-Choon, El-Esawi, Mohamed A., Liehr, Thomas, Blanck, Oliver, Gladue, Douglas P., Almeida, Gabriel M. F., Cernava, Tomislav, Sorzano, Carlos O., Yeung, Andy W. K., Engel, Michael S., Chandrasekaran, Arun Richard, Muth, Thilo, Staege, Martin S., Daulatabad, Swapna V., Widera, Darius, Zhang, Junpeng, Meule, Adrian, Honjo, Ken, Pourret, Olivier, Yin, Cong-Cong, Zhang, Zhongheng, Cascella, Marco, Flegel, Willy A., Goodyear, Carl S., Raaij, Mark J. van, Bukowy-Bieryllo, Zuzanna, Campana, Luca G., Kurniawan, Nicholas A., Lalaouna, David, Hüttner, Felix J., Ammerman, Brooke A., Ehret, Felix, Cobine, Paul A., Tan, Ene-Choo, Han, Hyemin, Xia, Wenfeng, McCrum, Christopher, Dings, Ruud P. M., Marinello, Francesco, Nilsson, Henrik, Nixon, Brett, Voskarides, Konstantinos, Yang, Long, Costa, Vincent D., Bengtsson-Palme, Johan, Bradshaw, William, Grimm, Dominik G., Kumar, Nitin, Martis, Elvis, Prieto, Daniel, Sabnis, Sandeep C., Amer, Said E. D. R., Liew, Alan W. C., Perco, Paul, Rahimi, Farid, Riva, Giuseppe, Zhang, Chongxing, Devkota, Hari P., Ogami, Koichi, Basharat, Zarrin, Fierz, Walter, Siebers, Robert, Tan, Kok-Hian, Boehme, Karen A., Brenneisen, Peter, Brown, James A. L., Dalrymple, Brian P., Harvey, David J., Ng, Grace, Werten, Sebastiaan, Bleackley, Mark, Dai, Zhanwu, Dhariwal, Raman, Gelfer, Yael, Hartmann, Marcus D., Miotla, Pawel, Tamaian, Radu, Govender, Pragashnie, Gurney-Champion, Oliver J., Kauppila, Joonas H., Zhang, Xiaolei, Echeverría, Natalia, Subhash, Santhilal, Sallmon, Hannes, Tofani, Marco, Bae, Taeok, Bosch, Oliver, Cuív, Páraic O., Danchin, Antoine, Diouf, Barthelemy, Eerola, Tuomas, Evangelou, Evangelos, Filipp, Fabian V., Klump, Hannes, Kurgan, Lukasz, Smith, Simon S., Terrier, Olivier, Tuttle, Neil, Ascher, David B., Janga, Sarath C., Schulte, Leon N., Becker, Daniel, Browngardt, Christopher, Bush, Stephen J., Gaullier, Guillaume, Ide, Kazuki, Meseko, Clement, Werner, Gijsbert D. A., Zaucha, Jan, Al-Farha, Abd A., Greenwald, Noah F., Popoola, Segun I., Rahman, Md Shaifur, Xu, Jialin, Yang, Sunny Y., Hiroi, Noboru, Alper, Ozgul M., Baker, Chris I., Bitzer, Michael, Chacko, George, Debrabant, Birgit, Dixon, Ray, Forano, Evelyne, Gilliham, Matthew, Kelly, Sarah, Klempnauer, Karl-Heinz, Lidbury, Brett A., Lin, Michael Z., Lynch, Iseult, Ma, Wujun, Maibach, Edward W., Mather, Diane E., Nandakumar, Kutty S., Ohgami, Robert S., Parchi, Piero, Tressoldi, Patrizio, Xue, Yu, Armitage, Charles, Barraud, Pierre, Chatzitheochari, Stella, Coelho, Luis P., Diao, Jiajie, Doxey, Andrew C., Hu, Pingzhao, Kaiser, Stefan, Mitchell, Kate M., Salama, Mohamed F., Shabalin, Ivan G., Song, Haijun, Stevanovic, Dejan, Yadollahpour, Ali, Zeng, Erliang, Zinke, Katharina, Alimba, C. G., Beyene, Tariku J., Cao, Zehong, Chan, Sherwin S., Gatchell, Michael, Kleppe, Andreas, Piotrowski, Marcin, Torga, Gonzalo, Woldesemayat, Adugna A., Cosacak, Mehmet I., Haston, Scott, Ross, Stephanie A., Williams, Richard, Wong, Alvin, Abramowitz, Matthew K., Effiong, Andem, Lee, Senhong, Abid, Muhammad Bilal, Agarabi, Cyrus, Alaux, Cedric, Albrecht, Dirk R., Atkins, Gerald J., Beck, Charles R., Bonvin, A. M. J. J., Bourke, Emer, Brand, Thomas, Braun, Ralf J., Bull, James A., Cardoso, Pedro, Carter, Dee, Delahay, Robin M., Ducommun, Bernard, Duijf, Pascal H. G., Epp, Trevor, Eskelinen, Eeva-Liisa, Fallah, Mazyar, Farber, Debora B., Fernandez-Triana, Jose, Feyerabend, Frank, Florio, Tullio, Friebe, Michael, Furuta, Saori, Gabrielsen, Mads, Gruber, Jens, Grybos, Malgorzata, Han, Qian, Heinrich, Michael, Helanterä, Heikki, Huber, Michael, Jeltsch, Albert, Jiang, Fan, Josse, Claire, Jurman, Giuseppe, Kamiya, Haruyuki, Keersmaecker, Kim de, Kristiansson, Erik, Leeuw, Frank-Erik de, Li, Jiuyong, Liang, Shide, Lopez-Escamez, Jose A., Lopez-Ruiz, Francisco J., Marchbank, Kevin J., Marschalek, Rolf, Martín, Carmen S., Miele, Adriana E., Montagutelli, Xavier, Morcillo, Esteban, Nicoletti, Rosario, Niehof, Monika, O’Toole, Ronan, Ohtomo, Toshihiko, Oster, Henrik, Palma, Jose-Alberto, Paterson, Russell, Peifer, Mark, Portilla, Maribel, Portillo, M. C., Pritchard, Antonia L., Pusch, Stefan, Raghava, Gajendra P. S., Roberts, Nicola J., Ross, Kehinde, Schuele, Birgitt, Sergeant, Kjell, Shen, Jun, Stella, Alessandro, Sukocheva, Olga, Uversky, Vladimir N., Vanneste, Sven, Villet, Martin H., Viveiros, Miguel, Vorholt, Julia A., Weinstock, Christof, Yamato, Masayuki, Zabetakis, Ioannis, Zhao, Xin, Ziegler, Andreas, Aizat, Wan M., Atlas, Lauren, Bridges, Kristina M., Chakraborty, Sayan, Deschodt, Mieke, Domingues, Helena S., Esfahlani, Shabnam S., Falk, Sebastian, Guisado, J. L., Kane, Nolan C., Kueberuwa, Gray, Lau, Colleen L., Liang, Dai, Liu, Enwu, Luu, Andreas M., Ma, Chuang, Ma, Lisong, Moyer, Robert, Norris, Adam D., Panthee, Suresh, Parsons, Jerod R., Peng, Yousong, Pinto, Inês Mendes, Reschke, Cristina R., Sillanpää, Elina, Stewart, Christopher J., Uhle, Florian, Yang, Hui, Zhou, Kai, Zhu, Shu, Ashry, Mohamed, Bergsland, Niels, Berthold, Maximilian, Chen, Chang-Er, Colella, Vito, Cuypers, Maarten, Eskew, Evan A., Fan, Xiao, Gajda, Maksymilian, Gonzálezlez-Prendes, Rayner, Goodin, Amie, Graham, Emily B., Groen, Ewout J. N., Gutiérrez-Sacristán, Alba, Habes, Mohamad, Heffler, Enrico, Higginbottom, Daniel B., Janzen, Thijs, Jayaraman, Jayakumar, Jibb, Lindsay A., Jongen, Stefan, Kinyanjui, Timothy, Koleva-Kolarova, Rositsa G., Li, Zhixiu, Liu, Yu-Peng, Lund, Bjarte A., Lussier, Alexandre A., Ma, Liping, Mier, Pablo, Moore, Matthew D., Nagler, Katja, Orme, Mark W., Pearson, James A., Prajapati, Anilkumar S., Saito, Yu, Tröder, Simon E., Uchendu, Florence, Verloh, Niklas, Voutchkova, Denitza D., Abu-Zaid, Ahmed, Bakkach, Joaira, Baumert, Philipp, Dono, Marcos, Hanson, Jack, Herbelet, Sandrine, Hobbs, Emma, Kulkarni, Ameya, Kumar, Narendra, Liu, Siqi, Loft, Nikolai D., Reddan, Tristan, Senghore, Thomas, Vindin, Howard, Xu, Haotian, Bannon, Ross, Chen, Branson, Cheung, Johnny T. K., Cooper, Jeffrey, Esnakula, Ashwini K., Feghali, Karine A., Ghelardi, Emilia, Gnasso, Agostino, Horbar, Jeffrey, Lai, Hei M., Li, Jian, Ma, Lan, Ma, Ruiyan, Pan, Zihang, Peres, Marco A., Pranata, Raymond, Seow, Esmond, Sydes, Matthew, Testoni, Ines, Westermair, Anna L., Yang, Yongliang, Afnan, Masoud, Albiol, Joan, Albuquerque, Lucia G., Amiya, Eisuke, Amorim, Rogerio M., An, Qianli, Andersen, Stig U., Aplin, John D., Argyropoulos, Christos, Asmann, Yan W., Assaeed, Abdulaziz M., Atanasov, Atanas G., Atchison, David A., Avery, Simon V., Avillach, Paul, Baade, Peter D., Backman, Lars, Badie, Christophe, Baldi, Alfonso, Ball, Elizabeth, Bardot, Olivier, Barnett, Adrian G., Basner, Mathias, Batra, Jyotsna, Bazanova, O. M., Beale, Andrew, Beddoe, Travis, Bell, Melanie L., Berezikov, Eugene, Berners-Price, Sue, Bernhardt, Peter, Berry, Edward, Bessa, Theolis B., Billington, Craig, Birch, John, Blakely, Randy D., Blaskovich, Mark A. T., Blum, Robert, Boelaert, Marleen, Bogdanos, Dimitrios, Bosch, Carles, Bourgoin, Thierry, Bouvard, Daniel, Boykin, Laura M., Bradley, Graeme, Braun, Daniel, Brownlie, Jeremy, Brühl, Albert, Burt, Austin, Butler, Lisa M., Byrareddy, Siddappa N., Byrne, Hugh J., Cabantous, Stephanie, Calatayud, Sara, Candal, Eva, Carlson, Kimberly, Casillas, Sònia, Castelvetro, Valter, Caswell, Patrick T., Cavalli, Giacomo, Cerovsky, Vaclav, Chagoyen, Monica, Chen, Chang-Shi, Chen, Dong F., Chen, Hao, Chen, Hui, Chen, Jui-Tung, Chen, Yinglong, Cheng, Changxiu, Cheng, Jianlin, Chinapaw, Mai, Chinopoulos, Christos, Cho, William C. S., Chong, Lillian, Chowdhury, Debashish, Chwalibog, Andre, Ciresi, A., Cockcroft, Shamshad, Conesa, Ana, Cook, Penny A., Cooper, David N., Coqueret, Olivier, Corea, Enoka M., Costa, Elisio, Coupland, Carol, Crawford, Stephanie Y., Cruz, Aparecido D., Cui, Huijuan, Cui, Qiang, Culver, David C., D’Angiulli, Amedeo, Dahms, Tanya E. S., Daigle, France, Dalgleish, Raymond, Danielsen, Håvard E., Darras, Sébastien, Davidson, Sean M., Day, David A., Degirmenci, Volkan, Demaison, Luc, Devriendt, Koenraad, Ding, Jiandong, Dogan, Yunus, Dong, X. C., Donner, Claudio F., Dressick, Walter, Drevon, Christian A., Duan, Huiling, Ducho, Christian, Dumaz, Nicolas, Dwarakanath, Bilikere S., Ebell, Mark H., Eisenhardt, Steffen, Elkum, Naser, Engel, Nadja, Erickson, Timothy B., Fairhead, Michael, Faville, Marty J., Fejzo, Marlena S., Festa, Fernanda, Feteira, Antonio, Flood-Page, Patrick, Forsayeth, John, Fox, Simon A., Franks, Steven J., Frentiu, Francesca D., Frilander, Mikko J., Fu, Xinmiao, Fujita, Satoshi, Galea, Ian, Galluzzi, Luca, Gani, Federica, Ganpule, Arvind P., García-Alix, Antonio, Gedye, Kristene, Giordano, Maurizio, Giunta, Cecilia, Gleeson, Paul A., Goarant, Cyrille, Gong, Haipeng, Gora, Diop, Gough, Michael J., Goyal, Ravinder, Graham, Kathryn E., Grande-Pérez, Ana, Graves, Patricia M., Greidanus, Harm, Grice, Darren, Grunau, Christoph, Gumulya, Yosephine, Guo, Yabin, Gurevich, Vsevolod V., Gusev, Oleg, Hacker, Elke, Hage, Steffen R., Hagen, Guy, Hahn, Steven, Haller, Dagmar M., Hammerschmidt, Sven, Han, Jianwei, Han, Renzhi, Handfield, Martin, Hapuarachchi, Hapuarachchige C., Harder, Timm, Hardingham, Jennifer E., Heck, Michelle, Heers, Marcel, Hew, Khe F., Higuchi, Yohei, Hilaire, Cynthia St, Hilton, Rachel, Hodzic, Enisa, Hone, Andrew, Hongoh, Yuichi, Hu, Guoku, Huber, Heinz P., Hueso, Luis E., Huirne, Judith, Hurt, Lisa, Idborg, Helena, Ikeo, Kazuho, Ingley, Evan, Jakeman, Philip M., Jensen, Arne, Jia, Hong, Jia, Husen, Jia, Shuqin, Jiang, Jianping, Jiang, Xingyu, Jin, Yi, Jo, Daehyun, Johnson, Andrew M., Johnston, Marie, Jonscher, Karen R., Jorens, Philippe G., Jorgensen, Jens O. L., Joubert, Johan W., Jung, Sin-Ho, Junior, Antonio M., Kahan, Thomas, Kamboj, Sunjeev K., Kang, Yong-Kook, Karamanos, Yannis, Karp, Natasha A., Kelly, Ryan, Kenna, Ralph, Kennedy, Jonathan, Kersten, Birgit, Khalaf, Roy A., Khalid, Javaria M., Khatlani, T., Khider, Tarig, Kijanka, Gregor S., King, Sarah R. B., Kluz, Tomasz, Knox, Paul, Kobayashi, Tatsuya, Koch, Karl-Wilhelm, Kohonen-Corish, Maija R. J., Kong, Xiangpeng, Konkle-Parker, Deborah, Korpela, Kalevi M., Kostrikis, Leondios G., Kraiczy, Peter, Kratz, Harald, Krause, Günter, Krebsbach, Paul H., Kristensen, Søren R., Kumari, Prerna, Kunimatsu, Akira, Kurdak, Hatice, Kwon, Young D., Lachat, Carl, Lagisz, Malgorzata, Laky, Brenda, Lammerding, Jan, Lange, Matthias, Larrosa, Mar, Laslett, Andrew L., LeClair, Elizabeth E., Lee, Kyung-Woo, Lee, Ming-Yih, Lee, Moon-Soo, Li, Genyuan, Li, Jiansheng, Lieb, Klaus, Lim, Yau Y., Lindsey, Merry L., Line, Paul-Dag, Liu, Dengcai, Liu, Fengbin, Liu, Haiyan, Liu, Hongde, Lloyd, Vett K., Lo, Te-Wen, Locci, Emanuela, Loidl, Josef, Lorenzen, Johan, Lorkowski, Stefan, Lovell, Nigel H., Lu, Hua, Lu, Wei, Lu, Zhiyong, Luengo, Gustavo S., Lundh, Lars-Gunnar, Lysy, Philippe A., Mabb, Angela, Mack, Heather G., Mackey, David A., Mahdavi, S. R., Maher, Pamela, Maher, Toby, Maity, Sankar N., Malgrange, Brigitte, Mamoulakis, Charalampos, Mangoni, Arduino A., Manke, Thomas, Manstead, Antony S. R., Mantalaris, Athanasios, Marsal, Jan, Marschall, Hanns-Ulrich, Martin, Francis L., Martinez-Raga, Jose, Martinez-Salas, Encarnacion, Mathieu, Daniel, Matsui, Yoichi, Maza, Elie, McCutcheon, James E., McKay, Gareth J., McMillan, Brian, McMillan, Nigel, Meads, Catherine, Medina, Loreta, Merrick, B. Alex, Metzger, Dennis W., Meunier, Frederic A., Michaelis, Martin, Micheau, Olivier, Mihara, Hisaaki, Mintz, Eric M., Mizukami, Takuo, Moalic, Yann, Mohapatra, D. P., Monteiro, Antonia, Montes, Matthieu, Moran, John V., Morozov, Sergey Y., Mort, Matthew, Murai, Noriyuki, Murphy, Denis J., Murphy, Susan K., Murray, Shauna A., Naganawa, Shinji, Nammi, Srinivas, Nasios, Grigorios, Natoli, Roman M., Nguyen, Frederique, Nicol, Christine, Nieuwerburgh, Filip van, Nilsen, Erlend B., Nobile, Clarissa J., O’Mahony, Margaret, Ohlsson, Sophie, Olatunbosun, Oluremi, Olofsson, Per, Ortiz, Alberto, Ostrikov, Kostya, Otto, Siegmar, Outeiro, Tiago F., Ouyang, Songying, Paganoni, Sabrina, Page, Andrew, Palm, Christoph, Paradies, Yin, Parsons, Michael H., Parsons, Nick, Pascal, Pigny, Paul, Elisabeth, Peckham, Michelle, Pedemonte, Nicoletta, Pellizzon, Michael A., Petrelli, M., Pichugin, Alexander, Pinto, Carlos J. C., Plevris, John N., Pollesello, Piero, Polz, Martin, Ponti, Giovanna, Porcelli, Piero, Prince, Martin, Quinn, Gwendolyn P., Quinn, Terence J., Ramula, Satu, Rappsilber, Juri, Rehfeldt, Florian, Reiling, Jan H., Remacle, Claire, Rezaei, Mohsen, Riddick, Eric W., Ritter, Uwe, Roach, Neil W., Roberts, David D., Robles, Guillermo, Rodrigues, Tiago, Rodriguez, Cesar, Roislien, Jo, Roobol, Monique J., Rowe, J. Alexandra, Ruepp, Andreas, Ruitenbeek, Jan van, Rust, Petra, Saad, Sonia, Sack, George H., Santos, Manuela, Saudemont, Aurore, Sava, Gianni, Schrading, Simone, Schramm, Alexander, Schreiber, Martin, Schuler, Sidney, Schymkowitz, Joost, Sczyrba, Alexander, Seib, Kate L., Shi, Han-Ping, Shimada, Tomohiro, Shin, Jeon-Soo, Shortt, Colette, Silveyra, Patricia, Skinner, Debra, Small, Ian, Smeets, Paul A. 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W., Xu, Jianping, Xue, Bin, Yalcin, Suayib, Yan, Hong, Yang, En-Cheng, Yang, Shiqi, Yang, Wei, Ye, Yuzhen, Ye, Zhi-Qiang, Yli-Kauhaluoma, Jari, Yoneyama, Hiroshi, Yu, Ying, Yuan, Guo-Cheng, Yuh, Chiou-Hwa, Zaccolo, Manuela, Zeng, Chen, Zevnik, Branko, Zhang, Chi, Zhang, Li, Zhang, Yingkai, Zhang, Yusen, Zhang, Zhiyong, Zhang, Zhong-Yin, Zhao, Yuan, Zhou, Min, Zuberbier, Torsten, Aanei, Carmen M., Ahmad, Rafi, Al-Lawama, Manar, Alanio, Alexandre, Allardyce, Judith, Alonso-Caneiro, David, Atack, John M., Baier, Dirk, Bansal, Abhisheka, Benezeth, Yannick, Berbesque, Colette, Berrevoet, Frederik, Biedermann, Peter H. W., Bijleveld, Erik, Bittner, Florian, Blombach, Fabian, Bos, Wouter van den, Boudreau, Shellie A., Bramoweth, Adam D., Braubach, Oliver, Cai, Yufeng, Campbell, Matthew, Cao, Zanxia, Catry, Thibault, Chen, Xin, Cheng, Shuiqin, Chung, Hee-Jung, Chávez-Fumagalli, Miguel A., Conway, Aaron, Costa, Bruno M., Cyr, Normand, Dean, Lorraine T., Denzel, Martin S., Dlamini, S. V., Dudley, Kevin J., Dufies, Maeva, Ecke, Thorsten, Eckweiler, Denitsa, Eixarch, Elisenda, El-Adawy, Hosny, Emmrich, Julius V., Eustace, Alex J., Falter-Wagner, Christine M., Fuss, Johannes, Gao, Jianzhao, Gill, Martin R., Gloyn, Liz, Goggs, Robert, Govinden, Usha, Greene, Garrett, Greiff, Victor, Grundle, D. S., Grüneberg, Patrick, Gumede, Nicksy, Haore, Gbaguidi, Harrison, Pille, Hoenner, Xavier, Hojsgaard, Diego, Hori, Hikaru, Ikonomopoulou, Maria P., Jeurissen, Patrick, Johnson, Daniel M., Kabra, Dhiraj, Kamagata, Koji, Karmakar, Chandan, Kasian, Olga, Kaye, Linda K., Khan, Murad M., Kim, Yong-Min, Kish, J. K., Kobold, Sebastian, Kohanbash, Gary, Kohls, Gregor, Kugler, Jan-Michael, Kumar, Gyanendra, Lacy-Colson, Jon, Latif, Asam, Lauschke, Volker M., Li, Bingling, Lim, Chinten J., Liu, Fang, Liu, Xiaodong, Lu, Jin-Jian, Lu, Qiang, Mahavadi, Poornima, Marzocchi, Ugo, McGarrigle, Christine A., Meerten, Tom van, Min, Rogier, Moal, Iain, Molari, Massimiliano, Molleman, Lucas, Mondal, Saiful R., Mortel, Thea van de, Moss, W. N., Moultos, Othonas A., Mukherjee, Maheswari, Nakayama, Kazuhiko, Narayan, Edward, Navaratnarajah, Neumann, Philipp-Alexander, Nie, Jiyun, Nie, Yingjiu, Niemeyer, Frank, Nolan, Fiona, Nwaiwu, Ogueri, Oldenmenger, Wendy H., Olumayede, Emmanuel, Ou, Jianhong, Pallebage-Gamarallage, Menuka, Pearce, Simon P., Pelkonen, Tuula, Pelleri, Maria C., Pereira, Joana L., Pheko, Mpho, Pinto, Karina A., Piovesan, Allison, Pluess, Michael, Podolsky, Illya M., Prescott, Julie, Qi, Dongchen, Qi, Xingshun, Raikou, Vaia D., Ranft, Andreas, Rhodes, Johanna, Rotge, Jean-Yves, Rowe, Anna D., Saggar, Manish, Schuon, Robert A., Shahid, Shaouli, Shalchyan, Vahid, Shirvalkar, Prasad, Shiryayev, Oleg, Singh, Jugpreet, Smout, Michael J., Soares, António, Song, Chunjiao, Srivastava, Kshitij, Srivastava, Rupesh K., Sun, Jim, Szabo, Attila, Szymanski, Wiktor, Tai, Chan N. P., Takeuchi, Hisashi, Tanadini-Lang, S., Tang, Fei, Tao, Wanyin, Theron, G., Tian, Chang F., Tian, Yu-Shi, Tuttle, Lisa M., Valenti, Anna, Verlot, Pierre, Walker, Mirella, Wang, Jun, Welter, Danielle, Winslade, Matthew, Wu, Dalei, Wu, Yi-Rui, Xiao, Han, Xu, Beisi, Xu, Juan, Xu, Ziyue, Yang, Dongdong, Yang, Mingjun, Yankilevich, Patricio, You, Yuyi, Yu, Chenglong, Zhan, Jian, Zhang, Gong, Zhang, Kai, Zhang, Tuo, Zhang, Yi, Zhao, Guoyan, Zhao, Jing, Zhou, Xiaofan, Zhu, Zhenxing, Ajani, Penelope A., Anazodo, Udunna C., Bagloee, Saeed A., Bail, Kasia, Bar, Ido, Bathelt, Joe, Benkeser, David, Bernier, Meghan L., Blanchard, Adam M., Boakye, Dominic W., Bonatsos, Vasileios, Boon, Michele H., Bouboulis, George, Bromfield, Elizabeth, Brown, Joshua, Bul, Kim C. 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A., Lin, Li, Ling, Tong, Liu, Yuchen, Liu, Zhonghua, Lu, Yao, Lum, Fok M., Luo, Hang, Machhi, Jatin, Macleod, Angus, Macwan, Isaac, Madala, Hanumantha R., Madani, Nima, Maio, Nicola de, Makowiecki, Kalina, Mallinson, Daniel J., Margelyte, Ruta, Maria, Caracausi, Markonis, Y., Marsili, Luca, Mavoa, Suzanne, McWilliams, Lorna, Megersa, Moa, Mendes, Caetano S. M., Menichetti, Julia, Mercieca-Bebber, Rebecca, Miller, Jack J., Minde, David-Paul M., Minges, Alexander, Mishra, Eleanor, Mishra, Virendra R., Moores, Carly, Morrice, Nicola, Moskalensky, Alexander E., Navarin, Nicolò, Negera, Edessa, Nolet, Philippe, Nordberg, Ana, Nordén, Rickard, Nowicki, Jessica P., Olova, Nelly, Olszewski, Paweł, Onzima, Robert, Pan, Chih-Long, Park, Charny, Park, Dong Ik, Park, Seyoung, Patil, Chandrashekhar D., Pedro, Sansoa A., Perry, Samuel R., Peter, Jessica, Peterson, Brent M., Pezzuolo, Andrea, Pozdnyakov, Ilya, Qian, Siyu, Qin, Lei, Rafe, Ali, Raote, Ishier, Raza, Ali, Rebl, Henrike, Refai, Osama, Regan, Tim, Richa, Tambi, Richardson, Mark F., Robinson, K. R., Rossoni, Luca, Rouet, Romain, Safaei, Soroush, Schneeberger, Pierre H. H., Schwotzer, Daniela, Sebastian, Agata, Selinski, Jennifer, Seltmann, Stefanie, Sha, Feng, Shalev, Nir, Shang, Jin-Long, Singer, Josef, Singh, Mandeep, Smith, Taylor, Solomon-Moore, Emma, Song, Lijuan, Soraggi, Samuele, Stanley, Ryan, Steckhan, Nico, Strobl, Frederic, Subissi, Lorenzo, Supriyanto, Irwan, Surve, Chinmay R., Suzuki, Tomo, Syme, Caitlin, Sörelius, Karl, Tang, Young, Tantawy, Marwa, Tennakoon, Sumudu, Teseo, Serafino, Toelzer, Christine, Tomov, Nikola, Tovar, Miguel, Tran, Linh, Tripathi, Sushil, Tuladhar, Anil M., Ukubuiwe, Azubuike C., Ung, Carolina O. L., Valgepea, Kaspar, Vatanparast, Hamid, Vidal, Arnau, Wang, Fang, Wang, Qing, Watari, Ricky, Webster, Rebecca, Webster, Ruth, Wei, Junnian, Wibowo, David, Wingenbach, Tanja S. H., Xavier, Rose M., Xiao, Shumin, Xiong, Peng, Xu, Shicai, Xu, Shilin, Yao, Ruifeng, Yao, Wen, Yin, Qinan, Yu, Yongbo, Zaitsu, Masayoshi, Zhan, Xiao-Yong, Zhang, Jilei, Zhang, Rongqiang, Zhang, Wei, Zhang, Xianglilan, Zheng, Shan, Zhou, Bailing, Zhou, Xiaoyan, Ahmad, Haroon, Akinwumi, Sayo A., Albery, Gregory F., Alhowimel, Ahmed, Ali, Junaid, Alshehri, Mansour, Alsuhaibani, Mohammed, Anikin, Andrey, Azubuike, Samuel O., Bach-Mortensen, Anders, Baltiansky, Lior, Bartas, Martin, Belachew, Kiflemariam Y., Bhardwaj, Vivek, Binder, Karin, Bland, Nicholas S., Boah, Michael, Bullen, Benjamin, Calabrò, Giovanna E., Callahan, Tiffany J., Cao, Bing, Chalmers, Kelsey, Chang, Wei, Che, Zhengping, Chen, Andrew T. Y., Chen, Haimin, Chen, Huaming, Chen, Youning, Chen, Zhao, Choi, YoungRok, Chowdhury, Mohiuddin A. K., Christensen, Martin R., Cooke, Robert S. 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A., Williams, Brendan A., Workman, Alan D., Xiang, Tingxiu, Xie, Li-Xin, Xu, Jun, Xu, Taosheng, Yang, Chongjun, Yoon, Jihoon G., Yuan, Christina M., Zaritsky, Arno, Zhang, Yao, Zhao, Haochen, Zuckerman, Hannah, Lyu, Ran, Pullan, Wayne, Zhou, Yaoqi, Gobet, Angélique, Sadoine, Margaux L., Ontwikkelingspsychologie (Psychologie, FMG), British Lung Foundation, Brown, P, Zhou, Y, Tan, A, El-Esawi, M, Liehr, T, Blanck, O, Gladue, D, Almeida, G, Cernava, T, Sorzano, C, Yeung, A, Engel, M, Chandrasekaran, A, Muth, T, Staege, M, Daulatabad, S, Widera, D, Zhang, J, Meule, A, Honjo, K, Pourret, O, Yin, C, Zhang, Z, Cascella, M, Flegel, W, Goodyear, C, van Raaij, M, Bukowy-Bieryllo, Z, Campana, L, Kurniawan, N, Lalaouna, D, Huttner, F, Ammerman, B, Ehret, F, Cobine, P, Tan, E, Han, H, Xia, W, Mccrum, C, Dings, R, Marinello, F, Nilsson, H, Nixon, B, Voskarides, K, Yang, L, Costa, V, Bengtsson-Palme, J, Bradshaw, W, Grimm, D, Kumar, N, Martis, E, Prieto, D, Sabnis, S, Amer, S, Liew, A, Perco, P, Rahimi, F, Riva, G, Zhang, C, Devkota, H, Ogami, K, Basharat, Z, Fierz, W, Siebers, R, Tan, K, Boehme, K, Brenneisen, P, Brown, J, Dalrymple, B, Harvey, D, Ng, G, Werten, S, Bleackley, M, Dai, Z, Dhariwal, R, Gelfer, Y, Hartmann, M, Miotla, P, Tamaian, R, Govender, P, Gurney-Champion, O, Kauppila, J, Zhang, X, Echeverria, N, Subhash, S, Sallmon, H, Tofani, M, Bae, T, Bosch, O, Cuiv, P, Danchin, A, Diouf, B, Eerola, T, Evangelou, E, Filipp, F, Klump, H, Kurgan, L, Smith, S, Terrier, O, Tuttle, N, Ascher, D, Janga, S, Schulte, L, Becker, D, Browngardt, C, Bush, S, Gaullier, G, Ide, K, Meseko, C, Werner, G, Zaucha, J, Al-Farha, A, Greenwald, N, Popoola, S, Rahman, S, Xu, J, Yang, S, Hiroi, N, Alper, O, Baker, C, Bitzer, M, Chacko, G, Debrabant, B, Dixon, R, Forano, E, Gilliham, M, Kelly, S, Klempnauer, K, Lidbury, B, Lin, M, Lynch, I, Ma, W, Maibach, E, Mather, D, Nandakumar, K, Ohgami, R, Parchi, P, Tressoldi, P, Xue, Y, Armitage, C, Barraud, P, Chatzitheochari, S, Coelho, L, Diao, J, 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Subjects: Technology and Engineering, SCIENTIFIC SEARCH, Expert-curated database, Biokemia, solu- ja molekyylibiologia - Biochemistry, cell and molecular biology, Databases, RElevant LIterature SearcH consortium, Medicine and Health Sciences, Biomedical research, benchmarking, Biology, GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries), Settore MED/42 - IGIENE GENERALE E APPLICATA, database, Computer. Automation, Science & Technology, 0804 Data Format, relisch, Scientific research in health sciences, Mathematics and Statistics, litearture search, relisch , database, biomedical research, Biomedical literature, Original Article, RELISH, Mathematical & Computational Biology, RECOMMENDER-SYSTEMS, Life Sciences & Biomedicine, Mathematics, 0807 Library and Information Studies
Abstract: Made available in DSpace on 2020-12-11T01:57:28Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-10-29 Griffith University Gowonda HPC Cluster Queensland Cyber Infrastructure Foundation Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research. Griffith Univ, Sch Informat & Commun Technol, Gold Coast, Qld 4222, Australia Griffith Univ, Inst Glyc, Gold Coast, Qld 4222, Australia Univ Colorado, Dept Med Med Oncol, Anschutz Med Campus, Denver, CO USA Tanta Univ, Fac Sci, Bot Dept, Tanta, Egypt Friedrich Schiller Univ, Jena Univ Hosp, Inst Human Genet, Jena, Germany Univ Med Ctr Schleswig Holstein, Dept Radiat Oncol, Campus Kiel, Kiel, Germany ARS, USDA, Plum Isl Anim Dis Ctr, Greenport, NY 11944 USA Univ Jyvaskyla, Dept Biol & Environm Sci, Jyvaskyla, Finland Graz Univ Technol, Inst Environm Biotechnol, Graz, Austria CSIC, CNB, Natl Biotechnol Ctr, Dept Macromol Struct, Madrid, Spain Univ Hong Kong, Fac Dent, Oral & Maxillofacial Radiol Appl Oral Sci & Commu, Hong Kong, Peoples R China Univ Kansas, Div Entomol, Biodivers Inst, Lawrence, KS 66045 USA SUNY Albany, RNA Inst, Albany, NY 12222 USA Robert Koch Inst, Dept Methods Dev & Res Infrastruct, Berlin, Germany Martin Luther Univ Halle Wittenberg, Dept Surg & Conservat Pediat & Adolescent Med, Halle, Germany Indiana Univ Purdue Univ, IU Sch Informat & Comp, Dept BioHlth Informat, Indianapolis, IN 46202 USA Univ Reading, Sch Pharm Stem Cell Biol & Regenerat Med, Reading, Berks, England Dali Univ, Sch Engn, Dali City, Yunnan, Peoples R China Univ Hosp Munich LMU, Dept Psychiat & Psychotherapy, Munich, Germany Univ Tsukuba, Fac Life & Environm Sci, Ibaraki, Japan UniLaSalle, Aghyle, Beauvais, France Henry Ford Hlth Syst, Dept Immunol, Detroit, MI USA Zhejiang Univ, Sch Med, Sir Run Run Shaw Hosp, Dept Emergency, Hangzhou 310016, Zhejiang, Peoples R China Ist Nazl Tumori Fdn Pascale IRCCS, Anesthesia & Pain Med, Naples, Italy NIH, Dept Transfus Med, Bethesda, MD USA Univ Glasgow, Inst Infect Immun & Inflammat, Glasgow, Lanark, Scotland Polish Acad Sci, Inst Human Genet, Poznan, Poland Univ Padua, Dept Surg Oncol & Gastroenterol DISCOG, Padua, Italy Eindhoven Univ Technol, Biomed Engn, Eindhoven, Netherlands Univ Strasbourg, IBMC, Strasbourg, France Heidelberg Univ, Dept Gen Visceral & Transplantat Surg, Heidelberg, Germany Univ Notre Dame, Psychol, Notre Dame, IN 46556 USA Harvard Med Sch, Massachusetts Gen Hosp, Radiol & Pathol, Boston, MA 02115 USA Auburn Univ, Dept Biol Sci, Auburn, AL 36849 USA KK Womens & Childrens Hosp, KK Res Ctr, Singapore, Singapore Univ Alabama, Educ Psychol, Tuscaloosa, AL USA UCL, Wellcome EPSRC Ctr Intervent & Surg Sci, London, England Maastricht Univ, Dept Nutr & Movement Sci, Maastricht, Netherlands Univ Arkansas Med Sci, Dept Radiat Oncol, Little Rock, AR 72205 USA Univ Padua, Dept Land Environm Agr & Forestry, Padua, Italy Univ Gothenburg, Dept Biol & Environm Sci, Gothenburg, Sweden Univ Newcastle, Prior Res Ctr Reprod Sci, Callaghan, NSW, Australia Univ Cyprus, Med Sch, Nicosia, Cyprus Shandong Agr Univ, Coll Plant Protect, Agr Big Data Res Ctr, Tai An, Shandong, Peoples R China NIMH, Neuropsychol Lab, Bldg 9, Bethesda, MD 20892 USA Univ Wisconsin, Wisconsin Inst Discovery, Madison, WI USA Univ Oxford, Struct Genom Consortium, Oxford, England Weihenstephan Triesdorf Univ Appl Sci, TUM Campus Straubing Biotechnol & Sustainabil, Bioinformat, Straubing, Germany Univ Michigan, Cardiovasc Res, Ann Arbor, MI 48109 USA Bombay Coll Pharm, Pharmaceut Chem, Mumbai, Maharashtra, India Inst Invest Biol Clemente Estable, Dev Neurobiol, Montevideo, Uruguay Gem Hosp & Res Ctr, Surg Gastroenterol & HPB Surg, Coimbatore, Tamil Nadu, India Kafr El Sheikh Univ, Fac Sci, Dept Zool, Kafr Al Sheikh, Egypt Med Univ Innsbruck, Dept Internal Med 4, Innsbruck, Austria Australian Natl Univ, Div Biomed Sci & Biochem, Canberra, ACT, Australia Univ Cattolica Sacro Cuore, Appl Technol Neuropsychol Lab, Milan, Italy Shandong Inst Parasit Dis, Med Entomol, Jinan, Shandong, Peoples R China Kumamoto Univ, Sch Pharm, Kumamoto, Japan Nagoya City Univ, Grad Sch Pharmaceut Sci, Dept Biol Chem, Nagoya, Aichi, Japan Univ Karachi, ICCBS, PCMD, Jamil ur Rahman Ctr Genome Res, Karachi 75270, Pakistan Labormed Zentrum Dr Risch, Vaduz, Liechtenstein Univ Otago, Med, Dunedin, New Zealand KK Womens & Childrens Hosp, Maternal Fetal Med, Singapore, Singapore Albert Ludwigs Univ Freiburg, GERN Tissue Replacement Regenerat & Neogenesis, Dept Orthoped & Trauma Surg, Med Ctr,Fac Med, Freiburg, Germany Heinrich Heine Univ, Inst Biochem & Mol Biol, Dusseldorf, Germany Natl Univ Ireland Galway, Surg, Galway, Ireland Univ Western Australia, Inst Agr, Perth, WA, Australia Univ Oxford, Nuffield Dept Med, Oxford, England SingHlth Polyclin, Punggol Polyclin, Singapore, Singapore Med Univ Innsbruck, Bioctr, Div Biol Chem, Innsbruck, Austria La Trobe Univ, La Trobe Inst Mol Sci, Biochem & Genet, Melbourne, Vic, Australia Univ Bordeaux, INRA, Bordeaux, France Agr & Agri Food Canada, Lethbridge Res & Dev Ctr, Lethbridge, AB, Canada St George Hosp, Trauma & Orthopaed, London, England Max Planck Inst Dev Biol, Dept Prot Evolut, Tubingen, Germany Med Univ Lublin, Dept Gynaecol 2, Lublin, Poland ICIT, ICSI Analyt Natl Res & Dev, Ramnicu Valcea, VL, Romania Univ KwaZulu Natal, Occupat Therapy, Westville Campus, Durban, South Africa Inst Canc Res, Joint Dept Phys, London, England Karolinska Inst, Dept Mol Med & Surg, Solna, Sweden Wenzhou Med Univ, Affiliated Hosp 2, Orthopaed, Wenzhou, Zhejiang, Peoples R China Univ Republica, Fac Ciencias, Ctr Invest Nucl, Lab Virol Mol, Montevideo, Uruguay Univ Gothenburg, Dept Med Biochem & Cell Biol, Gothenburg, Sweden Charite Med Univ Berlin, Pediat Cardiol, Berlin, Germany Bambino Gesu Pediat Hosp, Dept Neurosci & Neurorehabil, Neurorehabil Unit, Rome, Italy Indiana Univ Sch Med Northwest, Microbiol & Immunol, Gary, IN USA Univ Regensburg, Dept Behav & Mol Neurobiol, Regensburg, Germany Univ Queensland, Diamantina Inst, Brisbane, Qld, Australia Translat Res Inst, Brisbane, Qld, Australia Univ Hong Kong, Sch Biomed Sci, Hong Kong, Peoples R China St Jude Childrens Res Hosp, Pharmaceut Sci Dept, 332 N Lauderdale St, Memphis, TN 38105 USA Univ Durham, Mus, Durham, England Univ Ioannina, Med Sch, Dept Hyg & Epidemiol, Ioannina, Greece Tech Univ Munich, Sch Life Sci Weihenstephan, Maximus von Imhof Forum 3, D-85354 Freising Weihenstephan, Germany Univ Hosp Essen, Inst Transfus Med, Essen, Germany Virginia Commonwealth Univ, Comp Sci, Richmond, VA USA Univ Queensland, Inst Social Sci Res, Brisbane, Qld, Australia Univ Lyon, Ctr Int Rech Infectiol, Lyon, France Griffith Univ, Sch Allied Hlth Sci, Gold Coast, Qld, Australia Univ Melbourne, Dept Biochem & Mol Biol, Parkville, Vic, Australia Indiana Univ Purdue Univ, Dept Biohlth Informat, Sch Informat & Comp, Indianapolis, IN 46202 USA Philipps Univ Marburg, Inst Lung Res, Marburg, Germany Indiana Univ, Dept Biol, Bloomington, IN USA Univ Florida, Oral Biol, Gainesville, FL USA Univ Colorado, Dept Biochem, Boulder, CO 80309 USA Kyoto Univ, Ctr Promot Interdisciplinary Educ & Res, Kyoto, Japan Friedrich Loeffler Inst, Inst Virus Diagnost, Greifswald, Germany Univ Oxford, Dept Zool, Oxford, England Tech Univ Munich, Dept Bioinformat, Munich, Germany Univ Adelaide, Sch Anim & Vet Sci, Adelaide, SA, Australia Stanford Univ, Canc Biol, Palo Alto, CA 94304 USA Covenant Univ, Dept Elect & Informat Engn, Ota, Nigeria Heinrich Heine Univ, Inst Stem Cell Res & Regenerat Med, Dusseldorf, Germany Univ British Columbia, Fac Pharmaceut Sci, Vancouver, BC, Canada Albert Einstein Coll Med, Psychiat, New York, NY USA Akdeniz Univ, Med Biol & Genet, Antalya, Turkey NIMH, NIH, Bethesda, MD 20892 USA Med Univ Hosp, Internal Med 1, Tubingen, Germany NET ESolut, Netelabs, Mclean, VA USA Univ Southern Denmark, Inst Publ Hlth, Odense, Denmark John Innes Ctr, Mol Microbiol, Norwich, Norfolk, England Univ Adelaide, Waite Res Precinct, Australian Res Council, Ctr Excellence Plant Energy Biol, Adelaide, SA, Australia Univ Cambridge, Cambridge Inst Publ Hlth, Cambridge, England Univ Munster, Inst Biochem, Munster, Germany Australian Natl Univ, Natl Ctr Epidemiol & Populat Hlth RSPH, Canberra, ACT, Australia Stanford Univ, Neurobiol & Bioengn, Palo Alto, CA 94304 USA Univ Birmingham, Geog Earth & Environm Sci, Birmingham, W Midlands, England Murdoch Univ, Sch Vet & Life Sci, Perth, WA, Australia George Mason Univ, Ctr Climate Change Commun, Fairfax, VA 22030 USA Univ Adelaide, Sch Agr Food & Wine, Adelaide, SA, Australia Southern Med Univ, Sch Pharmaceut Sci, Guangzhou, Guangdong, Peoples R China Stanford Univ, Pathol, Palo Alto, CA 94304 USA Univ Bologna, Dept Expt Diagnost & Specialty Med, Bologna, Italy Univ Padua, Dept Gen Psychol, Padua, Italy Huazhong Univ Sci & Technol, Coll Life Sci & Technol, Dept Bioinformat & Syst Biol, Key Lab Mol Biophys,Minist Educ, Wuhan, Hubei, Peoples R China Huazhong Univ Sci & Technol, Collaborat Innovat Ctr Biomed Engn, Wuhan, Hubei, Peoples R China Queensland Univ Technol, Sch Biomed Sci, Brisbane, Qld, Australia French Natl Ctr Sci Res, CNRS, Inst Biol Physicochim, Paris, France Univ Warwick, Dept Sociol, Coventry, W Midlands, England European Mol Biol Lab, Struct & Computat Biol, Heidelberg, Germany Univ Cincinnati, Coll Med, Canc Biol, Cincinnati, OH USA Univ Waterloo, Biol, Waterloo, ON, Canada Sorbonne Univ, CNRS, Integrat Biol Marine Models LBI2M, SBR, Roscoff, France Univ Manitoba, Biochem & Med Genet, Winnipeg, MB, Canada Max Planck Inst Solid State Res, Ultrafast Solid State Spect, Stuttgart, Germany Imperial Coll London, Sch Publ Hlth, Dept Infect Dis Epidemiol, London, England Mansoura Univ, Fac Vet Med, Biochem, Mansoura, Egypt Univ Virginia, Mol Physiol & Biol Phys, Charlottesville, VA USA China Univ Geosci, State Key Lab Biogeol & Environm Geol, Wuhan, Hubei, Peoples R China Clin Neurol & Psychiat Children & Youth, Child Psychiat, Belgrade, Serbia Ahvaz Jundishapur Univ Med Sci, Med Phys, Ahwaz, Iran Univ Iowa City, Coll Dent, Div Biostat & Computat Biol, Dept Prevent & Community Dent, Iowa City, IA USA Univ Iowa City, Coll Dent, Div Biostat & Computat Biol, Dept Biomed Engn, Iowa City, IA USA Univ Iowa City, Coll Dent, Div Biostat & Computat Biol, Dept Biostat, Iowa City, IA USA Univ Tubingen, Inst Med Psychol & Behav Neurobiol, Tubingen, Germany Univ Ibadan, Dept Zool, Ibadan, Nigeria Kansas State Univ, Coll Vet Med, Manhattan, KS 66506 USA Univ Tasmania, Sch Technol Environm & Design, Discipline ICT, Hobart, Tas, Australia Childrens Mercy Hosp, Radiol, Kansas City, MO 64108 USA Stockholm Univ, Dept Phys, Stockholm, Sweden Oslo Univ Hosp, Inst Canc Genet & Informat, Oslo, Norway CSIRO, CSIRO Mfg, Pullenvale, Qld, Australia Johns Hopkins Sch Med, Urol, Baltimore, MD USA Univ South Africa, Life & Consumer Sci, Johannesburg, South Africa German Ctr Neurodegenerat Dis, Mech Induced Plast Brain, Bonn, Germany UCL, Inst Child Hlth, Dev Biol & Canc, London, England Simon Fraser Univ, Biomed Physiol & Kinesiol, Burnaby, BC, Canada Univ Manchester, Ctr Hlth Informat, Manchester, Lancs, England Univ Queensland, Sch Human Movement & Nutr Sci, Brisbane, Qld, Australia Albert Einstein Coll Med, Dept Med, New York, NY USA Georgetown Univ, Kennedy Inst Eth, Washington, DC 20057 USA Dermatol Skin & Canc Fdn, Carlton, Vic, Australia Med Coll Wisconsin, Div Hematol, Milwaukee, WI 53226 USA Med Coll Wisconsin, Div Oncol, Milwaukee, WI 53226 USA Med Coll Wisconsin, Div Infect Dis, Milwaukee, WI 53226 USA US FDA, Off Biotechnol Prod, Washington, DC 20204 USA Worcester Polytech Inst, Biomed Engn, Worcester, MA 01609 USA Univ Adelaide, Ctr Orthopaed & Trauma Res, Adelaide, SA, Australia Publ Hlth England, Natl Infect Serv, Bristol, Avon, England Univ Utrecht, Fac Sci Chem, Utrecht, Netherlands Natl Univ Ireland Galway, Pathol, Galway, Ireland Imperial Coll London, NHLI, London, England Danube Private Univ, Neurodegenerat, Krems Donau, Austria Imperial Coll London, Dept Chem, London, England Univ Helsinki, Finnish Museum Nat Hist, Helsinki, Finland Univ Sydney, Sch Life & Environm Sci, Sydney, NSW, Australia Univ Nottingham, Nottingham Digest Dis Ctr, Nottingham, England Univ Toulouse, CNRS, ITAV, USR3505, Toulouse, France ASCR, Inst Mol Genet, CZ Openscreen, Prague, Czech Republic Univ Turku, Inst Biomed, Turku, Finland York Univ, Sch Kinesiol & Hlth Sci, Toronto, ON, Canada Univ Calif Los Angeles, Stein Eye Inst, Ophthalmol, Los Angeles, CA USA Agr & Agri Food Canada, Ottawa Res & Dev Ctr, Ottawa, ON, Canada Helmholtz Zentrum Geesthacht, Mat Design & Characterizat, Geesthacht, Germany Unvers Genova, Internal Med, Genoa, Italy Otto von Guericke Univ, Intelligent Catheter INKS, Magdeburg, Germany Univ Toledo, Canc Biol, 2801 W Bancroft St,Hlth Sci Campus, Toledo, OH 43606 USA CRUK Beatson Inst, Struct Biol, Glasgow, Lanark, Scotland Leibniz Inst Primate Res, Med RNA Biol, Gottingen, Germany Univ Limoges, PEIRENE, EA 7500, Limoges, France Hainan Univ, Vet Med, Haikou, Hainan, Peoples R China UCL, Sch Pharam, Pharmacognosy & Phytotherapy, London, England Univ Oulu, Ecol & Genet Res Unit, Oulu, Finland Rhein Westfal TH Aachen, Inst Biochem & Mol Immunol, Aachen, Germany Univ Stuttgart, Inst Biochem & Tech Biochem, Stuttgart, Germany Peking Univ, Shenzhen Grad Sch, Sch Chem Biol & Biotechnol, Shenzhen, Peoples R China GIGA Res Inst, Med Oncol, Liege, Belgium CHULiege, Liege, Belgium Fdn Bruno Kessler, MPBA, Trento, Italy Hokkaido Univ, Grad Sch Med, Dept Neurobiol, Sapporo, Hokkaido, Japan Univ Leuven, Oncol, Leuven, Belgium Chalmers Univ Technol, Dept Math Sci, Gothenburg, Sweden Radboud Univ Nijmegen, Med Ctr, Dept Neurol, Nijmegen, Netherlands Univ South Australia, Sch Informat Technol & Math Sci, Adelaide, SA, Australia Bio Thera Solut Ltd, Dept Computat Biol, Guangzhou, Guangdong, Peoples R China Inst Invest Biosanitario Granada IBS, Otolaryngol, Granada, Spain Curtin Univ, Sch Mol & Life Sci, Perth, WA, Australia Newcastle Univ, Inst Cellular Med, Newcastle Upon Tyne, Tyne & Wear, England Goethe Univ, Biol DCAL, Inst Pharm, Frankfurt, Germany Univ Lyon, ICBMS, UMR 5246, Lyon, France Inst Pasteur, Dept Genomes & Genet, Paris, France Univ Valencia, Pharmacol, Valencia, Spain Council Agr Res & Econ, Res Ctr Olive Citrus & Tree Fruit, Caserta, Italy Fraunhofer Inst Toxicol & Expt Med ITEM, Preclin Pharmacol & Vitro Toxicol, Hannover, Germany Univ Tasmania, Sch Med, Hobart, Tas, Australia Chugai Pharmaceut Co Ltd, Oncol Lifecycle Management Dept, Tokyo, Japan Univ Lubeck, Inst Neurobiol, Lubeck, Germany NYU, Sch Med, Neurol, New York, NY USA Univ Putra Malaysia, Dept Plant Pathol, Seri Kembangan, Malaysia Univ N Carolina, Biol, Chapel Hill, NC 27515 USA Univ Southampton, Fac Hlth Sci, Southampton, Hants, England Univ Highlands & Islands, Genet & Immunol Res Grp, Inverness, Scotland Heidelberg Univ, Inst Pathol, Heidelberg, Germany Indraprastha Inst Informat Technol, Dept Computat Biol, New Delhi, India Glasgow Caledonian Univ, Sch Hlth & Life Sci, Glasgow, Lanark, Scotland Liverpool John Moores Univ, Pharm & Biomol Sci, Liverpool, Merseyside, England Parkinsons Inst & Clin Ctr, Basic Res, Sunnyvale, CA USA Luxembourg Inst Sci & Technol, Environm Res & 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Kansas, Med Ctr, Family Med Res Div, Kansas City, KS 66103 USA ASTAR, Inst Mol & Cell Biol, Multimodal Mol Biol, Singapore, Singapore Univ Leuven, Dept Chron Dis Metab & Ageing, Leuven, Belgium Int Iberian Nanotechnol Lab INL, Braga, Portugal Anglia Ruskin, Comp & Technol, Cambridge, England Max Planck Inst Biochem, Struct Cell Biol, Planegg, Germany Univ Seville, Dept Comp Architecture & Technol, Seville, Spain Univ Colorado, EBIO, Boulder, CO 80309 USA Univ Manchester, Canc Sci, Manchester, Lancs, England Australian Natl Univ, Res Sch Populat Hlth, Canberra, ACT, Australia Singapore MIT Alliance Res & Technol, Biosyst, Singapore, Singapore Australian Catholic Univ, Mary MacKillop Inst Hlth Res, Musculoskeletal Hlth & Ageing Res Program, Melbourne, Vic, Australia Ruhr Univ Bochum, Gen Surg, St Josef Hosp, Bochum, Germany Northwest A&F Univ, Coll Life Sci, Xianyang, Shaanxi, Peoples R China Australian Natl Univ, Res Sch Biol, Div Plant Sci, Canberra, ACT, Australia Battelle Mem Inst, Clin & Nonclin Res, Columbus, OH USA Southern Methodist Univ, Biol Sci, Dallas, TX 75275 USA Teikyo Univ, Inst Med Mycol, Tokyo, Japan Tempus Labs, Bioinformat, Chicago, IL USA Hunan Univ, Coll Biol, Changsha, Hunan, Peoples R China Inst Cochin, Dept Infect Immun & Inflammat, Paris, France Royal Coll Surgeons Ireland, FutureNeuro Res Ctr Physiol & Med Phys, Dublin, Ireland Univ Jyvaskyla, Gerontol Res Ctr, Jyvaskyla, Finland Heidelberg Univ, Dept Anesthesiol, Heidelberg, Germany Penn State Univ, Biol, University Pk, PA 16802 USA Chinese Acad Sci, Inst Microbiol, State Key Lab Microbial Resources, Beijing, Peoples R China Univ Sci & Technol China, Sch Life Sci, Hefei, Anhui, Peoples R China Michigan State Univ, Anim Sci, E Lansing, MI 48824 USA SUNY Buffalo, Jacobs Sch Med & Biomed Sci, Dept Neurol, Buffalo Neuroimaging Anal Ctr, New York, NY USA Univ Rostock, Inst Biol Sci, Rostock, Germany South China Normal Univ, Sch Environm, Environm Res Inst, Guangzhou, Guangdong, Peoples R China Univ Bari, Dept Vet Med, Bari, Italy Radboud Univ Nijmegen, Med Ctr, Primary & Community Care, Nijmegen, Netherlands EcoHlth Alliance, New York, NY USA Mayo Clin, Cardiovasc Dept, Rochester, MN USA Med Univ Silesia, Sch Med Katowice, Dept Epidemiol, Katowice, Poland Univ Lleida, Anim Sci, Lleida, Spain Univ Florida, Coll Pharm, Pharmaceut Outcomes & Policy, Gainesville, FL USA Pacific Northwest Natl Lab, Earth & Biol Sci Directorate, Richland, WA 99352 USA Univ Edinburgh, Ctr Discovery Brain Sci, Edinburgh, Midlothian, Scotland Harvard Med Sch, Dept Biomed Informat, Boston, MA 02115 USA Univ Penn, Radiol, Philadelphia, PA 19104 USA Humanitas Univ & Res Hosp, Asthma & Allergy Unit, Biomed Sci Personalized Med, Rozzano, Italy Australian Natl Univ, Dept Quantum Sci, Canberra, ACT, Australia Carl von Ossietzky Univ Oldenburg, Ecol Genom, Oldenburg, Germany Int Med Univ, Paediat Dent & Orthodont, Kuala Lumpur, Malaysia Univ Ottawa, Sch Nursing, Ottawa, ON, Canada Maastricht Univ, Dept Educ Support, Maastricht, Netherlands Univ Manchester, Math, Manchester, Lancs, England Kings Coll London, Fac Life Sci & Med, Sch Populat Hlth Sci, London, England Queensland Univ Technol, Inst Hlth & Biomed Innovat, Brisbane, Qld, Australia Harbin Med Univ, Publ Hlth Sch, Epidemiol, Harbin, Heilongjiang, Peoples R China UiT Arctic Univ Norway, Dept Chem, Tromso, Norway Cornell Univ, Biol Stat & Computat Biol, Ithaca, NY USA East China Normal Univ, Sch Ecol & Environm Sci, Shanghai Key Lab Urban Ecol Proc & Ecorestorat, Shanghai, Peoples R China Johannes Gutenberg Univ Mainz, Fac Biol, Mainz, Germany Univ Massachusetts, Food Sci, Amherst, MA 01003 USA Max Planck Inst Terr Microbiol, Complex Adapt Traits Res Grp, Marburg, Germany NIHR Biomed Res Ctr Resp, Ctr Exercise & Rehabil Sci, Leicester, Leics, England Yale Univ, Dept Internal Med, Sect Endocrinol, New Haven, CT USA Sardar Patel Univ, Dept Biosci, Anand, Gujarat, India Univ Tokyo, Dept Appl Phys, Tokyo, Japan Univ Cologne, Vivo Res Facil ivRF, Cologne Excellence Cluster Cellular Stress Respon, Cologne, Germany Natl Open Univ Nigeria, Dept Publ Hlth Sci, Lagos, Nigeria Univ Hosp Regensburg, Dept Radiol, Regensburg, Germany Natl Univ Singapore, Geog, Singapore, Singapore Alfaisal Univ, Coll Med, Riyadh, Saudi Arabia Abdelmalek Essaadi Univ, Fac Sci & Techn Tangier, Biomed Genom & Oncogenet Res Lab, Tetouan, Morocco Tech Univ Munich, Fac Sport & Hlth Sci, Exercise Biol Grp, Munich, Germany Univ Santiago de Compostela, Dept Psicoloxia Social Basica & Metodoloxia, Galiza, Spain Griffith Univ, Signal Proc Lab, Brisbane, Qld, Australia Univ Ghent, Dept Neurol, Ghent, Belgium Ghent Univ Hosp, Ghent, Belgium Univ Ghent, Fac Vet Med, Merelbeke, Belgium Albert Einstein Coll Med, Inst Clin & Translat Res, New York, NY USA Anglia Ruskin Univ, Fac Med Sci, Cambridge, England Peking Univ, Coll Chem & Mol Engn, Beijing, Peoples R China Herlev & Gentofte Hosp, Dept Dermatol & Allergy, Hellerup, Denmark Lady Cilento Childrens Hosp, Med Imaging & Nucl Med, Brisbane, Qld, Australia Univ Gambia, Sch Med & Allied Hlth Sci, Nursing & Reprod Hlth, Brikama, Gambia Univ Sydney, Woolcock Inst Med Res, Sydney, NSW, Australia Wayne State Univ, Comp Sci, Detroit, MI USA Aberdeen Royal Infirm, Otolaryngol, Aberdeen, Scotland Univ Toronto, Lab Med & Pathobiol, Toronto, ON, Canada Chinese Univ Hong Kong, Inst Ageing, Hong Kong, Peoples R China Univ Nebraska Med Ctr, Emergency Med, Omaha, NE USA Univ Florida, Coll Med, Pathol, Gainesville, FL USA Univ Texas MD Anderson Canc Ctr, Radiat Oncol, Houston, TX 77030 USA Univ Pisa, Translat Res NTMS, Pisa, Italy Magna Grecia Univ, Clin & Expt Med, Catanzaro, Italy Univ Vermont, Larner Coll Med, Pediat, Burlington, VT USA Sun Yat Sen Univ, Canc Ctr, Diagnost & Intervent Ultrasound, Guangzhou, Guangdong, Peoples R China Fudan Univ, Inst Brain Sci, Shanghai, Peoples R China Shanxi Agr Univ, Coll Agron, Jinzhong, Shanxi, Peoples R China Univ Toronto, Inst Med Sci, Toronto, ON, Canada Univ Adelaide, ARCPOH, Adelaide, SA, Australia Pelita Harapan Univ, Fac Med, Cardiol & Vasc Med, Tangerang, Indonesia Inst Mental Hlth, Res Div, Singapore, Singapore UCL, MRC Clin Trials Unit, London, England Univ Padua, Dept Philosophy Sociol Educ & Appl Psychol FISPPA, Padua, Italy Univ Lubeck, Dept Psychiat & Psychotherapy, Lubeck, Germany Dalian Univ Technol, Ctr Mol Med, Dalian, Liaoning, Peoples R China Tianjin United Family Healthcare, Reprod Med, Tianjin, Peoples R China Univ Autonoma Barcelona, Dept Engn Quim Biol & Ambiental, Barcelona, Spain Sao Paulo State Univ UNESP, Dept Anim Sci, Sao Paulo, Brazil Helmholtz Zentrum Munchen, Inst Computat Biol, Canc Syst Biol, Ingolstadter Land Str 1, D-85764 Munich, Germany Univ Tokyo, Dept Cardiovasc Med, Tokyo, Japan Sao Paulo State Univ, Vet Clin, Sao Paulo, Brazil Zhejiang Univ, Inst Biotechnol, Hangzhou, Zhejiang, Peoples R China Aarhus Univ, Dept Mol Biol & Genet, Aarhus, Denmark Univ Manchester, St Marys Hosp, Maternal & Fetal Hlth, Manchester, Lancs, England Univ New Mexico, Internal Med, Albuquerque, NM 87131 USA Mayo Clin, Div Biomed Stat & Informat, Jacksonville, FL 32224 USA King Saud Univ, Plant Prod, Riyadh, Saudi Arabia Polish Acad Sci, Inst Genet & Anim Breeding, Dept Mol Biol, Warsaw, Poland Queensland Univ Technol, Optometry & Vis Sci, Brisbane, Qld, Australia Univ Nottingham, Sch Life Sci, Nottingham, England Canc Council Queensland, Canc Res Ctr, Brisbane, Qld, Australia Umea Univ, Dept Chem, Umea, Sweden Publ Hlth England, Ctr Radiat Chem & Environm Hazards, Bristol, Avon, England Univ Campania L Vanvitelli, DISTABIF, Caserta, Italy Bartshealth, Obstet & Gyanecol, London, England Univ Clermont Auvergne, GReD Lab, Clermont Ferrand, France INRA Abeilles & Environm, Avignon, France Queensland Univ Technol, Sch Publ Hlth & Social Work, Brisbane, Qld, Australia Univ Penn, Psychiat, Philadelphia, PA 19104 USA Novosibirsk State Univ, Res Inst Physiol & Basic Med, Novosibirsk, Russia UCL, Dept Chem, London, England La Trobe Univ, Anim Plant & Soil Sci, Melbourne, Vic, Australia Univ Arizona, Epidemiol & Biostat, Tucson, AZ USA Univ Groningen, Univ Med Ctr Groningen, ERIBA, Groningen, Netherlands Univ Gothenburg, Inst Clin Sci, Dept Radiat Phys, Gothenburg, Sweden SUNY Upstate Med Univ, Biochem & Mol Biol, Syracuse, NY 13210 USA Fundacao Oswaldo Cruz, Ctr Pesquisas Goncalo Moniz, Salvador, Bahia, Brazil Inst Environm Sci & Res ESR, Food Water & Environm Microbiol, Christchurch, New Zealand Univ Otago, Food Sci, Dunedin, New Zealand Florida Atlantic Univ, Biomed Sci, Boca Raton, FL 33431 USA Univ Queensland, Inst Mol Biosci, Brisbane, Qld, Australia Univ Hosp Wurzburg, Inst Clin Neurobiol, Wurzburg, Germany Inst Trop Med, Publ Hlth, Antwerp, Belgium Univ Thessaly, Sch Hlth Sci, Fac Med, Dept Rheumatol & Clin Immunol, Larisa, Greece Univ Basel, UZB Univ Ctr Dent Med, Dept Orthodont & Pediat Dent, Basel, Switzerland Sorbonne Univ, Museum Natl Hist Nat, Inst Systemat Evolut Biodiversite ISYEB, MNHN,CNRS,UMR 7205,EPHE, Paris, France CNRS, Inst Adv Biosci, Paris, France Univ Western Australia, Sch Mol Sci, Perth, WA, Australia Univ Ft Hare, Biochem & Microbiol, Alice, South Africa Univ Tubingen, Phys, Tubingen, Germany Griffith Univ, Sch Environm & Sci, Brisbane, Qld, Australia Philosoph Theol Hsch Vallendar, Stat & Standardised Methods, Vallendar, Germany Imperial Coll London, Life Sci, London, England Univ Adelaide, Adelaide Med Sch, Adelaide, SA, Australia Univ Nebraska Med Ctr, Dept Pharmacol & Expt Neurosci, Omaha, NE USA Technol Univ Dublin, FOCAS Res Inst, Dublin, Ireland INSERM, Natl Inst Hlth & Med Res, Canc Res Ctr Toulouse, Paris, France Univ Santiago de Compostela, Dept Bioloxia Func, Grp BRAINSHARK, Galiza, Spain Univ Nebraska, Biol, Kearney, NE USA Univ Autonoma Barcelona, Dept Genet & Microbiol, Barcelona, Spain Univ Pisa, Chem & Ind Chem, Pisa, Italy Univ Manchester, Wellcome Trust Ctr Cell Matrix Res, Manchester, Lancs, England Univ Montpellier, CNRS, Inst Human Genet, Montpellier, France Czech Acad Sci, Inst Organ Chem & Biochem, Prague, Czech Republic CSIC, Natl Ctr Biotechnol CNB, Computat Syst Biol Grp, Madrid, Spain Natl Cheng Kung Univ, Dept Biochem & Mol Biol, Tainan, Taiwan Harvard Med Sch, Schepens Eye Res Inst, Ophthalmol, Boston, MA 02115 USA Lanzhou Univ, Hosp 2, Dept Gen Surg, Lanzhou, Gansu, Peoples R China Univ Technol Sydney, Sch Life Sci, Sydney, NSW, Australia JT Chen Clin, Gynecol, Tokyo, Japan Univ Western Australia, Sch Agr & Environm, Perth, WA, Australia Beijing Normal Univ, Fac Geog Sci, Beijing, Peoples R China Univ Missouri, Elect Engn & Comp Sci, Columbia, MO USA Vrije Univ Amsterdam Med Ctr, Amsterdam Publ Hlth Res Inst, Dept Publ & Occupat Hlth, Amsterdam, Netherlands Semmelweis Univ, Med Biochem, Budapest, Hungary Queen Elizabeth Hosp, Dept Clin Oncol, Hong Kong, Peoples R China Univ Pittsburgh, Chem, Pittsburgh, PA USA GB Pant Inst Post Grad Med Educ & Res, Neurol, New Delhi, India Univ Copenhagen, Vet & Anim Sci, Copenhagen, Denmark Univ Palermo, Biomed Dept Internal & Specialist Med DIBIMIS, Sect Endocrinol, Palermo, Italy UCL, NPP, London, England Univ Florida, Microbiol & Cell Sci, Gainesville, FL USA Univ Salford, Sch Hlth Sci, Manchester, Lancs, England Cardiff Univ, Inst Med Genet, Cardiff, S Glam, Wales INSERM, ICO Canc Ctr, Angers, France Univ Colombo, Fac Med, Microbiol, Colombo, Sri Lanka Beijing Univ Chinese Med, Sch Chinese Mat Med, Beijing, Peoples R China Univ Porto, Fac Pharm, Porto, Portugal Univ Nottingham, Div Primary Care, Nottingham, England Univ Illinois, Pharm Syst Outcomes & Policy, Chicago, IL USA Pontificia Univ Catolica Goias, Escola Ciencias Agr & Biol, Goiania, Go, Brazil China Japan Friendship Hosp, Dept Oncol, Beijing, Peoples R China Boston Univ, Chem, Boston, MA 02215 USA Amer Univ, Environm Sci, Washington, DC 20016 USA Carleton Univ, Neurosci, Ottawa, ON, Canada Univ Regina, Chem & Biochem, Regina, SK, Canada Univ Montreal, Microbiolgy, Montreal, PQ, Canada Univ Leicester, Dept Genet & Genome Biol, Leicester, Leics, England Univ Queensland, Sch Agr & Food Sci, Gatton, Qld, Australia CNRS, BIOM, Paris, France UCL, Hatter Cardiovasc Inst, London, England Flinders Univ S Australia, Sci & Engn, Adelaide, SA, Australia Univ Warwick, Engn, Coventry, W Midlands, England Katholieke Univ Leuven, Ctr Human Genet, Leuven, Belgium Fudan Univ, Dept Macromol Sci, Shanghai, Peoples R China Dokuz Eylul Univ, Biol Educ, Izmir, Turkey Indiana Univ Sch Med, Dept Biochem & Mol Biol, Indianapolis, IN 46202 USA Mondo Med, Pulm Dis, Borgomanero, Italy US Naval, Res Lab, Ctr Bio Mol Sci & Engn, Washington, DC USA Univ Oslo, Inst Basic Med Sci, Dept Nutr, Oslo, Norway Peking Univ, Dept Mech & Engn Sci, Beijing, Peoples R China Saarland Univ, Dept Pharm Pharmaceut & Med Chem, Saarbrucken, Germany INSERM, Natl Inst Hlth & Med Res, Skin Res Inst, Paris, France Shanghai Proton & Heavy Ion Ctr, Res & Dev, Shanghai, Peoples R China Univ Georgia, Epidemiol, Athens, GA 30602 USA Univ Freiburg, Med Ctr, Dept Plast & Hand Surg, Freiburg, Germany Sidra Med, Res, Doha, Qatar Rostock Univ, Med Ctr, Dept Oral Maxillofacial & Plast Surg, Rostock, Germany Harvard Med Sch, Brigham & Womens Hosp, Emergency Med, Boston, MA 02115 USA AgResearch, Forage Sci, Palmerston North, New Zealand Univ Calif Los Angeles, Med, Los Angeles, CA USA Arizona State Univ, Biodesign Inst, Virginia G Piper Ctr Personalized Diagnost, Tempe, AZ USA Sheffield Hallam Univ, Res Inst, Mat & Engn, Sheffield, S Yorkshire, England Aneurin Bevan Univ Healthboard, Resp Med, Newport, Shrops, England Univ Calif San Francisco, Neurol Surg, San Francisco, CA 94143 USA Univ Western Australia, UWA Dent Sch, Perth, WA, Australia Fordham Univ, Biol Sci, Bronx, NY 10458 USA Univ Helsinki, Inst Biotechnol, Helsinki, Finland Fujian Normal Univ, Coll Life Sci, Fuzhou, Fujian, Peoples R China Univ Fukui, Dept Frontier Fiber Technol & Sci, Fukui, Japan Univ Southampton, Fac Med, Clin & Expt Sci, Southampton, Hants, England Univ Urbino, Dept Biomol Sci, Urbino, Italy Osped San Luigi, Allergol Unit, Turin, Italy Muljibhai Patel Urol Hosp, Dept Urol, Nadiad, Gujarat, India Univ Granada, Stratig & Paleontol, Granada, Spain Massey Univ, Sch Vet Sci, Auckland, New Zealand CNR, High Performance Comp & Networking Inst, Naples, Italy Univ Childrens Hosp Zurich, Div Metab, Zurich, Switzerland Univ Childrens Hosp Zurich, Childrens Res Ctr, Zurich, Switzerland Univ Melbourne, Biochem & Mol Biol, Parkville, Vic, Australia Inst Pasteur, Leptospirosis Res & Expertise Unit, Noumea, New Caledonia Tsinghua Univ, Sch Life Sci, Beijing, Peoples R China Cheikh Anta Diop Univ UCAD, Sci Fac, Biol Anim Dept, Dakar, Senegal Providence Portland Med Ctr, Earle A Chiles Res Inst, Portland, OR USA Agr & Agri Food Canada, Lacombe Res & Dev Ctr, Lacombe, AB, Canada Alberta Innovates, Performance Management & Evaluat, Edmonton, AB, Canada Univ Malaga, CSIC, Inst Hortofruticultura Subtrop Mediterranea La Ma, IHSM,UMA, Malaga, Spain James Cook Univ, Coll Publ Hlth Med & Vet Sci, Cairns, Qld, Australia European Commiss, Joint Res Ctr, Ispra, Italy Univ Montpellier, Montpellier, France CSIRO, Floreat, WA, Australia Sun Yat Sen Univ, Sun Yat Sen Mem Hosp, Guangzhou, Guangdong, Peoples R China Vanderbilt Univ, Pharmacol, 221 Kirkland Hall, Nashville, TN 37235 USA RIKEN, KFU RIKEN Translat Genom Unit, Yokohama, Kanagawa, Japan Univ Tubingen, Neurobiol Vocal Commun, Tubingen, Germany Univ Colorado, UCCS Ctr Biofrontiers Inst, Colorado Springs, CO 80907 USA Fred Hutchinson Canc Ctr, Div Basic Sci, Seattle, WA USA Univ Geneva, Fac Med, Primary Care Unit, Geneva, Switzerland Ernst Moritz Arndt Univ Greifswald, Dept Mol Genet & Infect Biol, Greifswald, Germany East China Univ Sci & Technol, Dept Fine Chem, Shanghai, Peoples R China Ohio State Univ, Surg, Columbus, OH 43210 USA Oragenics, R&D, Tampa, FL USA Natl Environm Agcy, Environm Hlth Inst, Singapore, Singapore Friedrich Loeffler Inst, Inst Diagnost Virol, Greifswald, Germany Queen Elizabeth Hosp, Oncol, Woodville, SA, Australia USDA, Emerging Pests & Pathogens Res Unit, Ithaca, NY USA Univ Freiburg, Med Ctr, Dept Neurosurg, Epilepsy Ctr, Freiburg, Germany Univ Hong Kong, Fac Educ, Informat & Technol Studies, Hong Kong, Peoples R China Univ Tokyo, Grad Sch Agr & life Sci, Agr & Environm Biol, Tokyo, Japan Univ Pittsburgh, Dept Med, Pittsburgh Heart Lung & Blood Vasc Med Inst, Pittsburgh, PA USA Guys & St Thomas NHS Fdn Trust, Directorate Transplant Renal & Urol, London, England Univ Sarajevo, Clin Ctr, Clin Heart Blood Vessel & Rheumat Dis, Sarajevo, Bosnia & Herceg Univ Kent, Sch Math Stat & Actuarial Sci, Canterbury, Kent, England Tokyo Inst Technol, Dept Life Sci & Technol, Tokyo, Japan Univ Appl Sci Munich, Laser Ctr Dept Appl Sci & Mechatron, Munich, Germany CIC NanoGUNE, Nanodevices, San Sebastian, Spain Vrije Univ Amsterdam Med Ctr, Gynaecol, Amsterdam, Netherlands Cardiff Univ, Med Sch, Div Populat Med, Cardiff, S Glam, Wales Karolinska Inst, Dept Med, Solna, Sweden Natl Inst Genet, Ctr Informat Biol, Mishima, Shizuoka, Japan Murdoch Univ, Harry Perkins Inst Med Res, Perth, WA, Australia Univ Limerick, Phys Educ & Sport Sci, Limerick, Ireland Ruhr Univ Bochum, Campus Clin Gynecol, Univ Str, Bochum, Germany Southwest Med Univ, Sch Publ Hlth, Epidemiol & Biostat, Luzhou, Sichuan, Peoples R China Beijing Canc Hosp, Minist Educ Beijing, Key Lab Carcinogenesis & Translat Res, Ctr Mol Diagnost, Beijing, Peoples R China Chinese Acad Sci, Chengdu Inst Biol, Herpetol Dept, Chengdu, Sichuan, Peoples R China Key Lab Nano Biol Effects & Safety, Beijing, Peoples R China NIBR, PK Sci, Basel, Switzerland Daejeon St Marys Hosp, Pain Ctr, Daejeon, South Korea Univ Western Ontario, Sch Hlth Studies, London, ON, Canada Univ Aberdeen, Hlth Psychol Grp, Aberdeen, Scotland Univ Colorado, Anesthesiol, Anschutz Med Campus, Boulder, CO 80309 USA Univ Antwerp, UZA Antwerp Univ Hosp, Crit 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Res Ctr, Stem Cell & Regenerat Med, Riyadh, Saudi Arabia Univ Bahri, Ind Pulp & Paper, Khartoum, Sudan Univ Queensland, Mater Med Res Inst, Mater Res Inst, Brisbane, Qld, Australia Colorado State Univ, NREL, Ft Collins, CO 80523 USA Rzeszow Univ Hosp, Ob Gyn Dept, Rzeszow, Poland Univ Leeds, Fac Biol Sci, Leeds, W Yorkshire, England Massachusetts Gen Hosp, Endocrine Unit, Boston, MA 02114 USA Carl von Ossietzky Univ Oldenburg, Neurosci, Oldenburg, Germany UNSW, St George & Sutherland Clin Sch, Microbiome Res Ctr, Sydney, NSW, Australia NYU, Sch Med, Dept Biochem, New York, NY 10016 USA NYU, Sch Med, Dept Mol Pharmacol, New York, NY USA Univ Mississippi, Med Ctr, Med Infect Dis, Jackson, MS 39216 USA Tampere Univ, Fac Social Sci Psychol, Tampere, Finland Univ Cyprus, Dept Biol Sci, Nicosia, Cyprus Goethe Univ, Inst Med Microbiol & Infect Control, Frankfurt, Germany Charite Med Univ Berlin, Inst Radiol, Berlin, Germany Univ Cologne, Univ Hosp Cologne, Internal Med 1, Cologne, Germany Univ Calif Los Angeles, Sch Dent, Sect Periodont, Los Angeles, CA 90024 USA Aalborg Univ Hosp, Dept Clin Biochem, Aalborg, Denmark Manipal Acad Higher Educ, Pharm Practice, Manipal, Karnataka, India Univ Tokyo, Inst Med Sci, Dept Radiol, Tokyo, Japan Cukurova Univ, Family Med, Fac Med, Adana, Turkey Catholic Univ Korea, Coll Med, Dept Humanities & Social Med, Seoul, South Korea Univ Ghent, Food Technol Safety & Hlth, Ghent, Belgium UNSW Sydney, Sch Biol Earth & Environm Sci BEES, Sydney, NSW, Australia St Vincent Shoulder & Sports Clin, Res Unit, Vienna, Austria Cornell Univ, Biomed Engn, Ithaca, NY USA Leibniz Inst Plant Genet & Crop Plant Res IPK, Res Grp Bioinformat & Informat Technol, Gatersleben, Germany Univ Europea Madrid, Sch Doctoral Studies, Madrid, Spain CSIRO Mfg, Biomed Mfg, Melbourne, Vic, Australia Depaul Univ, Biol Sci, Chicago, IL 60604 USA Konkuk Univ, Dept Anim Sci & Technol, Seoul, South Korea Chang Gung Univ, Grad Inst Med Mechatron, Taoyuan, Taiwan Korea Univ, 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Biochem & Mol Biol, 1430 Tulane Ave, New Orleans, LA 70112 USA NINDS, NIH, Bldg 36,Rm 4D04, Bethesda, MD 20892 USA NIH, NCBI, Natl Lib Med, Bldg 10, Bethesda, MD 20892 USA LOreal Res & Innovat, Aulnay Sous Bois, France Lund Univ, Dept Psychol, Malmo, Sweden Catholic Univ Louvain, Inst Rech Expt & Clin, Brussels, Belgium Georgia State Univ, Neurosci Inst, Atlanta, GA 30303 USA Univ Melbourne, Ophthalmol, Surg, Parkville, Vic, Australia Univ Western Australia, Ctr Ophthalmol & Visual Sci, Perth, WA, Australia Iran Univ Med Sci, Med Phys, Fac Med, Tehran, Iran Salk Inst Biol Studies, Cellular Neurobiol, La Jolla, CA USA Imperial Coll London, Fibrosis Res Grp, London, England Univ Texas MD Anderson Canc Ctr, Genitourinary Med Oncol, Houston, TX 77030 USA Univ Liege, GIGA Neurosci, Liege, Belgium Univ Crete, Sch Med, Urol, Iraklion, Greece Flinders Univ S Australia, Flinders Med Ctr, Dept Clin Pharmacol, Adelaide, SA, Australia Max Planck Inst Immunobiol & Epigenet, Bioinformat, Breisgau, Germany Cardiff Univ, Sch Psychol, Cardiff, S Glam, Wales Imperial Coll London, Chem Engn, London, England Lund Univ, Skane Univ Hosp, Clin Sci, Malmo, Sweden Sahlgrens Acad, Inst Clin Sci, Dept Mol & Clin Med, Gothenburg, Sweden Univ Cent Lancashire, Sch Pharm & Biomed Sci, Preston, Lancs, England Hosp Univ Doctor Peset, Psychiat & Clin Psychol, Valencia, Spain Ctr Biol Mol Severo Ochoa, Genome Dynam & Funct, Madrid, Spain Unvivers Hosp Lille, Dept Intens Care, Lille, France Kansai Med Univ, Surg, Osaka, Japan Univ Toulouse, Inst Natl Polytech Toulouse, Ecole Natl Super Agron Toulouse, Lab Genom & Biotechnol Fruit, Toulouse, France UiT Arctic Univ Norway, Inst Psychol, Tromsto, Norway Queens Univ, Ctr Publ Hlth, Belfast, Antrim, North Ireland Univ Manchester, Ctr Primary Care & Hlth Serv Res, Manchester, Lancs, England Griffith Univ, Menzies Hlth Inst, Gold Coast, Qld, Australia Anglia Ruskin Univ, FHSCE, Cambridge, England Univ Lleida, Dept Expt Med, Lleida, Spain NIEHS, Biomol Screening Branch, Div Natl Toxicol Program, POB 12233, Res Triangle Pk, NC 27709 USA Albany Med Coll, Immunol & Microbial Dis, Albany, NY 12208 USA Univ Queensland, Queensland Brain Inst, Brisbane, Qld, Australia Univ Kent, Sch Biosci, Canterbury, Kent, England Univ Bourgogne Franche Comte, INSERM, LNC, UMR 1231, Besancon, France Ritsumeikan Univ, Coll Life Sci, Dept Biotechnol, Shiga, Japan Kent State Univ, Biol Sci, Kent, OH 44242 USA Natl Inst Infect Dis, Dept Safety Res Blood & Biol Prod, Tokyo, Japan European Inst Marine Studies, Lab Microbiol Extreme Environm, Plouzane, France Univ Iowa, Dept Pharmacol, Roy J & Lucille A Carver Coll Med, Iowa City, IA 52242 USA Natl Univ Singapore, Biol Sci, Singapore, Singapore Conservatoire Natl Arts & Metiers, Lab GBA, EA4627, Paris, France Univ Michigan, Dept Human Genet, Ann Arbor, MI 48109 USA Lomonosov Moscow State Univ, Belozersky Inst Physicochem Biol, Moscow, Russia Jikei Univ, Sch Med, Dept Mol Biol, Tokyo, Japan Univ South Wales, Genom & Computat Biol, Treforest, Wales Duke Univ, Med Ctr, Obstet & Gynecol, Durham, NC USA Univ Technol Sydney, Climate Change Cluster, Sydney, NSW, Australia Nagoya Univ, Grad Sch Med, Dept Radiol, Nagoya, Aichi, Japan Western Sydney Univ, Sch Sci & Hlth, Sydney, NSW, Australia TEI Epirus, Dept Speech & Language Therapy, Ioannina, Greece Indiana Univ Purdue Univ, Orthopaed Surg, Indianapolis, IN 46202 USA Oniris, Vet Pathol, Nantes, France Royal Vet Coll, Pathobiol & Populat Sci, Hatfield, Herts, England Univ Ghent, Lab Pharmaceut Biotechnol, Ghent, Belgium Norwegian Inst Nat Res, Terr Ecol, Trondheim, Norway Univ Calif Merced, Mol & Cell Biol, Merced, CA USA Univ Dublin, Trinity Coll Dublin, Sch Engn, Ctr Transport Res, Dublin, Ireland Lund Univ, Inst Clin Sci, Nephrol, Malmo, Sweden Univ Birmingham, Mech Engn, Birmingham, W Midlands, England Lund Univ, Inst Clin Sci, OB GYN, Lund, Sweden Fdn Jimenez Diaz Hosp, Nephrol & Hypertens, Madrid, Spain Queensland Univ Technol, Sch Chem Phys & Mech Engn, Brisbane, Qld, Australia Otto von Guericke Univ, Psychol, Magdeburg, Germany Univ Med Ctr Gottingen, Dept Expt Neurodegenerat, Gottingen, Germany Harvard Med Sch, Spaulding Rehabil Hosp, Phys Med & Rehabil, Boston, MA 02115 USA Quadram Inst Biosci, Sci Operat, Norwich, Norfolk, England Ostbayer Tech Hsch Regensburg OTH Regensburg, Regensburg Med Image Comp ReMIC, Regensburg, Germany Deakin Univ, Fac Arts & Educ, Melbourne, Vic, Australia Univ Warwick, Warwick Med Sch, Coventry, W Midlands, England INSERM, Natl Inst Hlth & Med Res, Biochem & Mol Biol, Paris, France Univ Liege, Tax Inst, Liege, Belgium Univ Leeds, Sch Mol & Cellular Biol, Leeds, W Yorkshire, England IRCCS Ist Giannina Gaslini, UOC Genet Med, Genoa, Italy Res Diets Inc, Sci, New Brunswick, NJ USA Univ Perugia, Dept Phys & Geol, Perugia, Italy Walter Reed Natl Mil Med Ctr, Cellular Immunol, Bethesda, MD USA Univ Fed Santa Catarina, Biol Sci Ctr, Microbiol Immunol & Parasitol Dept, Florianopolis, SC, Brazil Univ Edinburgh, Royal Infirm, Ctr Liver & Digest Disorders, Edinburgh, Midlothian, Scotland Orion Pharma, Crit Care Proprietary Prod Div, Espoo, Finland MIT, Dept Civil & Environm Engn, 77 Massachusetts Ave, Cambridge, MA 02139 USA Univ Turin, Dept Vet Sci, Turin, Italy Univ G dAnnunzio, Dept Psychol Hlth & Territorial Sci, Chieti, Italy NYU, Sch Med, OB GYN, New York, NY USA Univ Glasgow, Inst Cardiovasc & Med Sci, Glasgow, Lanark, Scotland Univ Turku, Dept Biol, Turku, Finland Tech Univ Berlin, Bioanalyt, Berlin, Germany Univ Goettingen, Inst Phys Biophys 3, Gottingen, Germany Univ Texas MD Anderson Canc Ctr, Inst Appl Canc Sci, Translat Res Adv Therapeut & Innovat Oncol TRACTI, Houston, TX 77030 USA Univ Liege, Life Sci, Liege, Belgium Tarbiat Modares Univ, Fac Med Sci, Dept Toxicol, Tehran, Iran ARS, USDA, Stoneville, MS USA Univ Regensburg, RCI Regensburg Ctr Intervent Immunol, Regensburg, Germany Univ Nottingham, Sch Psychol, Nottingham, England NIH, Pathol Lab, Bethesda, MD 20892 USA Univ Carlos III Madrid, Elect Engn, Madrid, Spain Inst Med Mol, Chem Biol, Lisbon, Portugal Univ Costa Rica, CIET, San Jose, Costa Rica Univ Stavanger, Fac Hlth Sci, Stavanger, Norway Erasmus MC, Urol, Rotterdam, Netherlands Univ Edinburgh, Sch Biol Sci, Edinburgh, Midlothian, Scotland German Res Ctr Environm Hlth GmbH, Helmholtz Zentrum Munchen, Inst Bioinformat & Syst Biol IBIS, Ingolstadter Landstr 1, D-85764 Neuherberg, Germany Leiden Univ, Huygens Kamerlingh Onnes Lab, Leiden, Netherlands Univ Vienna, Nutr Sci, Vienna, Austria Kolling Inst Med Res, Med, St Leonards, NSW, Australia Johns Hopkins Sch Med, Biol Chem, Baltimore, MD USA Univ Montreal, Med Nutr & Microbiome Lab, Montreal, PQ, Canada GlaxoSmithKline, Cell & Gene Therapy, Stevenage, Herts, England Univ Trieste, Life Sci, Trieste, Italy Rhein Westfal TH Aachen, Dept Radiol, Aachen, Germany Univ Duisburg Essen, Univ Hosp Essen, West German Canc Ctr, Dept Med Oncol, Essen, Germany Med Univ Vienna, Obstet & Gynecol, Vienna, Austria FHI 360, Social & Behav Hlth Sci Div, Washington, DC USA KU Leuven VIB, Switch Lab, Leuven, Belgium Bielefeld Univ, Fac Technol, Bielefeld, Germany Capital Med Univ, Beijing Shijitan Hosp, Dept Clin Nutr, Dept Gastrointestinal Surg, Beijing, Peoples R China Meiji Univ, Dept Agr Chem, Kawasaki, Japan Yonsei Univ, Coll Med, Microbiol, Seoul, South Korea Johnson & Johnson EAME, Maidenhead, Berks, England Penn State Coll Med, Pediat, Hershey, PA USA Univ N Carolina, Dept Social Med, Chapel Hill, NC 27515 USA Univ Western Australia, ARC CoE Plant Energy Biol, Perth, WA, Australia Wageningen Univ, Div Human Nutr & Hlth, Wageningen, Netherlands Kings Coll London, Dept Neuroimaging, London, England Univ Murcia, Biochem & Mol Biol, Murcia, Spain Old Dominion Univ, Dept Biol Sci, Norfolk, VA 23529 USA Monash Univ, Biochem & Mol Biol, Melbourne, Vic, Australia Chinese Acad Sci, Inst Genet & Dev Biol, Beijing, Peoples R China Univ Pittsburgh, Pharmacol & Chem Biol, Pittsburgh, PA USA Univ Lausanne, Ctr Integrat Genom, Lausanne, Switzerland Univ Queensland, Sch Pharm, Brisbane, Qld, Australia Leibniz Inst Plant Genet & Crop Plant Res IPK Gat, Genebank, Gatersleben, Germany Piramal Imaging, Res & Dev, Berlin, Germany Univ Leeds, Civil Engn, Leeds, W Yorkshire, England Univ Missouri, Chem & Biochem, St Louis, MO 63121 USA US Geol Survey, Coastal & Marine Geol Program, Pacific Coastal & Marine Sci Ctr, Santa Cruz, CA USA Ajinomoto Genet Res Inst, Moscow, Russia Jagiellonian Univ, Fac Biochem Biophys & Biotechnol, Dept Plant Biotechnol, Krakow, Poland Univ Puerto Rico, Engn Sci & Mat, Mayaguez, PR USA Univ Regina, Dept Chem & Biochem, Regina, SK, Canada Argonne Natl Lab, Ctr Nanoscale Mat, 9700 S Cass Ave, Argonne, IL 60439 USA Univ Sunshine Coast, Sunshine Coast Mind & Neurosci Thompson Inst, Sippy Downs, Qld, Australia Chinese Peoples Liberat Army Gen Hosp, Dept Gastroenterol & Hepatol, Beijing, Peoples R China Griffith Univ, Griffith Ctr Social & Cultural Res, Gold Coast, Qld, Australia Tohoku Univ, Inst Dev Aging Canc, Dept Mol Oncol, Sendai, Miyagi, Japan Indiana Univ, Comp Sci, Bloomington, IN USA Fukushima Med Univ, Sch Med, Dept Pulm Med, Fukushima, Japan MEDIVIR AB, Biol, Huddinge, Sweden Western Sydney Univ, Neuroimmunol, Sydney, NSW, Australia Univ Jordan, Nutr & Food Technol, Amman, Jordan Thunen Inst Forest Genet, Fed Res Ctr Rura Areas Forestry & Fisheries, Inst Biodivers, Grosshansdorf, Germany Univ Edinburgh, Inst Cell Biol, Edinburgh, Midlothian, Scotland Univ Edinburgh, Ctr Integrat Physiol, Edinburgh, Midlothian, Scotland Univ Toronto, Struct Genom Consortium, Toronto, ON, Canada Canadian Mem Chiropract Coll, Grad Educ & Res, Toronto, ON, Canada Agilent Technol, R&D, Leuven, Belgium Univ British Columbia, Sch Nursing, Vancouver, BC, Canada Monash Univ, Monash Hlth, Sch Clin Sci, Stroke & Ageing Res,Dept Med, Melbourne, Vic, Australia French Natl Canc Inst, Innovat, Transfer, Biol, Boulogne, France Ludwig Maximilians Univ Munchen, Phys Chem, NanoBioSci, Munich, Germany Bandung Inst Technol, Sch Pharm, Med Chem, Bandung, Indonesia Univ Luxembourg, Life Sci Res Unit, Luxembourg, Luxembourg Lund Univ, Skane Univ Hosp, Dept Gastroenterol, Malmo, Sweden Millennium Hlth, Translat Genet, San Diego, CA USA Aristotle Univ Thessaloniki, Med Dept 2, Clin Res & Evidence Based Med Unit, Thessaloniki, Greece Jan Kochanowski Univ Humanities & Sci, Piotrkow Trybunalski Branch, Dept Psychol, Kielce, Poland McMaster Univ, Engn Phys, Hamilton, ON, Canada Marche Polytech Univ, Dept Agr Food & Environm Sci, Ancona, Italy Kuwait Univ, Fac Med, Microbiol, Kuwait, Kuwait Fujita Hlth Univ, Dept Breast Surg, Toyoake, Aich, Japan North West Reg Spinal Injuries Ctr, Spinal Injuries Ctr, Southport, Merseyside, England Luxembourg Inst Hlth, Competence Ctr Methodol & Stat, Luxembourg, Luxembourg Nestle Inst Hlth Sci SA, Metab Hlth, Ecublens, Vaud, Switzerland Ctr Inflammat Res VIB, Ghent, Belgium Univ Ghent, Dept Biomed Mol Biol, Ghent, Belgium Univ Lisbon, Inst Educ, Curriculo Formacao Prof & Tecnol, Lisbon, Portugal Univ Edinburgh, Ctr Inflammat Res, Edinburgh, Midlothian, Scotland Univ Melbourne, Sch BioSci, Parkville, Vic, Australia Northumbria Univ, Comp & Informat Sci, Newcastle Upon Tyne, Tyne & Wear, England Univ Valencia, Endocrinol, Valencia, Spain INRS, Inst Armand Frappier, Laval, PQ, Canada Univ Laval, INAF, Sch Nutr, Quebec City, PQ, Canada Univ Konstanz, Dept Biol, Constance, Germany Univ Cote dAzur, LAMHESS, Nice, France Scion, Syst Ecol, Christchurch, New Zealand CUNY, Grad Sch Publ Hlth & Hlth Policy, Epidemiol & Biostat, New York, NY 10021 USA Univ Queensland, Sch Dent, Brisbane, Qld, Australia George Inst Global Hlth, Renal & Metab Div, Sydney, NSW, Australia Wuhan Univ, Coll Chem & Mol Sci, Wuhan, Hubei, Peoples R China Griffith Univ, Sch Environm & Sci, Gold Coast, Qld, Australia Univ Minnesota, Radiat Oncol, Minneapolis, MN USA Goethe Univ, Fac Med, Frankfurt, Germany Natl Yunlin Univ Sci & Technol, Dept & Grad Sch Safety & Environm Engn, Touliu, Yunlin, Taiwan Massey Univ, Sch Sport Exercise & Nutr, Auckland, New Zealand Univ Florida, Wildlife Ecol & Conservat, Gainesville, FL USA Bournemouth Univ, Dept Psychol, Poole, Dorset, England Robert Koch Inst, Project Grp P2, Berlin, Germany Univ Edinburgh, MRC Inst Genet & Mol Med, Edinburgh, Midlothian, Scotland Univ Basel, Biozentrum, Basel, Switzerland Univ Wollongong, Sch Med, Wollongong, NSW, Australia Univ Cologne, Inst Human Genet, Cologne, Germany Rural Econ Branch, Econ Res Serv, Washington, DC USA Uivers Bordeaux, CNRS, Inst Neurosci Cognit & Integrat Aquitaine, Bordeaux, France Univ Calif Riverside, Dept Chem & Environm Engn, Riverside, CA 92521 USA Univ Calif Riverside, Mat Sci & Engn Program, Riverside, CA 92521 USA Mackay Med Coll, Dept Med, New Taipei, Taiwan Univ Bern, Div Anim Welf, Bern, Switzerland Oregon Hlth & Sci Univ, Dept Physiol & Pharmacol, Portland, OR 97201 USA Shanghai Univ Tradit Chinese Med, Inst Interdisciplinary Med Sci, Shanghai, Peoples R China McMaster Univ, Biol, Hamilton, ON, Canada Univ S Florida, Dept Cell Biol Microbiol & Mol Biol, Tampa, FL USA Hacettepe Univ, Inst Canc, Med Oncol, Ankara, Turkey City Univ Hong Kong, Dept Elect Engn, Hong Kong, Peoples R China Natl Taiwan Univ, Dept Entomol, Taipei, Taiwan Chinese Acad Agr Sci, Inst Environm & Sustainable Dev Agr, Ecol Secur, Beijing, Peoples R China Florida State Univ, Inst Mol Biophys, Chem & Biochem, Tallahassee, FL USA Peking Univ, Shenzhen Grad Sch, State Key Lab Chem Oncogen, Lab Computat Chem & Drug Design, Shenzhen, Peoples R China Univ Helsinki, Fac Pharm, Div Pharmaceut Chem & Technol, Drug Res Program, Helsinki, Finland Tohoku Univ, Microbial Biotechnol, Sendai, Miyagi, Japan Tianjin Med Univ, Sch Basical Med Sci, Dept Pharmacol, Tianjin, Peoples R China Dana Farber Canc Inst, Biostat & Computat Biol, Boston, MA 02115 USA Natl Hlth Res Inst, Inst Mol & Genom Med, Zhunan, Taiwan Univ Oxford, Physiol Anat & Genet, Oxford, England George Washington Univ, Phys, Washington, DC USA Univ Nebraska, Sch Biol Sci, Lincoln, NE USA Toronto Gen Hosp, Res Inst, Dept Lab Med & Pathobiol, Toronto, ON, Canada Univ Texas Dallas, Biol Sci, Richardson, TX 75083 USA NYU, Dept Chem, New York, NY USA Shandong Univ, Sch Math & Stat, Jinan, Shandong, Peoples R China Univ Sci & Technol China, Hefei Natl Lab Phys Sci Microscale, Hefei, Anhui, Peoples R China Purdue Univ, Med Chem & Mol Pharmacol, W Lafayette, IN 47907 USA NIBSC, Adv Therapies, Ridge, Herts, England Shanghai Jiao Tong Univ, Ruijin Hosp, Dept Pulm & Crit Care Med, Shanghai, Peoples R China Charite Med Univ Berlin, Dermatol & Allergy, Berlin, Germany Univ Hosp St Etienne, Hematol, St Etienne, France Inland Norway Univ Appl Sci, Inst Biotechnol, Elverum, Norway Univ Jordan, Pediat, Amman, Jordan Inst Pasteur, Mol Mycol Unit, Paris, France Cardiff Univ, Sch Med, Inst Psychol Med & Clin Neurosci, Med Res Council Ctr Neuropsychiat Genet & Genom, Cardiff, S Glam, Wales Zurich Univ Appl Sci, Social Work, Zurich, Switzerland Jawaharlal Nehru Univ, Sch Life Sci, New Delhi, India Univ Burgundy Franche Comte, LE2I, Dijon, France Univ Roehampton, Life Sci, London, England Ghent Univ Hosp, Gen & HPB Surg, Ghent, Belgium Univ Wurzburg, Insect Fungus Symbiosis Lab, Wurzburg, Germany Radboud Univ Nijmegen, Behav Sci Inst, Nijmegen, Netherlands Fraunhofer WKI, Applicat Ctr HOFZET, Hannover, Germany UCL, Struct & Mol Biol, London, England Univ Amsterdam, Dev Psychol, Amsterdam, Netherlands Aalborg Univ, Hlth Sci & Technol, CNAP, SMI, Aalborg, Denmark VA Pittsburgh Healthcare Syst, Ctr Hlth Equity Res & Promot, Pittsburgh, PA USA Cedars Sinai Med Ctr, Neurosurg, Los Angeles, CA 90048 USA Sun Yat Sen Univ, Sch Data & Comp Sci, Guangzhou, Guangdong, Peoples R China Dezhou Univ, Shandong Prov Key Lab Biophys, Guangzhou, Guangdong, Peoples R China Maison Teledetection, Inst Rech Dev, UMR Espace DEv, Montpellier, France Xiamen Univ, Sch Life Sci, Xiamen, Fujian, Peoples R China Nanjing Univ, Sch Med, Jinling Hosp, Natl Clin Res Ctr Kidney Dis,Dept Med Imaging, Nanjing, Jiangsu, Peoples R China Univ Kent, Sch Social Policy Sociol & Social Res, Canterbury, Kent, England Univ Fed Minas Gerais, Infect Dis & Trop Med, Belo Horizonte, MG, Brazil Univ Minho, Sch Med, Life & Hlth Sci Res Inst ICVS, Braga, Portugal Univ Montreal, Biochim & Med Mol, Montreal, PQ, Canada Johns Hopkins Bloomberg Sch Publ Hlth, Epidemiol, Baltimore, MD USA Max Planck Inst Biol Ageing, Metab & Genet Regulat Ageing, Cologne, Germany Univ Swaziland, Hlth Sci, Kwaluseni, Eswatini Queensland Univ Technol, Inst Future Environm, Brisbane, Qld, Australia Ctr Sci Monaco, Dept Biol Med, Monaco, Monaco HELIOS Hosp, Urol, Bad Saarow Pieskow, Germany Tech Univ Carolo Wilhelmina Braunschweig, Inst Microbiol, Braunschweig, Germany Univ Barcelona, Barcelona Ctr Maternal Fetal & Neonatal Med, Fetal i D Fetal Med Res Ctr, IDIBAPS BCNatal,Hosp Clin, Barcelona, Spain Univ Barcelona, Hosp St Joan de Deu, Barcelona, Spain Friedrich Loeffler Inst, Inst Bacterial Infect & Zoonoses, Jena, Germany Charite Med Univ Berlin, Neurol, Berlin, Germany Dublin City Univ, Natl Inst Cellular Biotechnol, Mol Therapeut Canc Ireland, Dublin, Ireland Schoen Clin Roseneck, Prien Am Chiemsee, Germany Univ Med Ctr Hamburg Eppendorf, Inst Sex Res & Forens Psychiat, Hamburg, Germany Nankai Univ, Sch Math Sci, Tianjin, Peoples R China Nankai Univ, LPMC, Tianjin, Peoples R China Univ Oxford, Oncol, Oxford, England Royal Holloway Univ London, Class, Egham, Surrey, England Cornell Univ, Clin Sci, Ithaca, NY USA Univ KwaZulu Natal, Pharmaceut Chem, Westville Campus, Durban, South Africa Royal Coll Surgeons Ireland, Med, Dublin, Ireland Univ Oslo, Dept Immunol, Oslo, Norway Bermuda Inst Ocean Sci, Marine Nitrogen Cycling Lab, St Georges, Bermuda Kanazawa Univ, Inst Liberal Arts & Sci, Kanazawa, Ishikawa, Japan World Hlth Org Reg Off Africa, Brazzaville, Rep Congo Univ Hosp BesanCon, Infect Control Dept, Besancon, France Galapagos NV, Clin Dev, Mechelen, Belgium Univ Tasmania, Integrated Marine Observing Syst, Hobart, Tas, Australia Georg August Univ Gottingen, Albrecht von Haller Inst Plant Sci, Dept Systemat Biodivers & Evolut Plants, Gottingen, Germany Univ Occupat & Environm Hlth, Dept Psychiat, Fukuoka, Fukuoka, Japan IMDEA Food, Program Precis Nutr & Aging, Madrid, Spain Radboud Univ Nijmegen, Med Sch, IQHealthcare, Nijmegen, Netherlands Maastricht Univ, Dept Cardiovasc Surg, Maastricht, Netherlands German Diabet Ctr, Inst Clin Biochem & Pathobiochem, Dusseldorf, Germany Juntendo Univ, Grad Sch Med, Dept Radiol, Tokyo, Japan Deakin Univ, Sch Informat Technol, Melbourne, Vic, Australia Max Planck Inst Eusenforschung, Dept Interface Chem & Surface Sci, Dusseldorf, Germany Edge Hill Univ, Dept Psychol, Ormskirk, England Aga Khan Univ, Psychiat, Karachi, Pakistan KRIBB, Korean Bioinformat Ctr, Seoul, South Korea Cardinal Hlth Specialty Solut, Hlth Econ & Outcomes Res, Dallas, TX USA Klinikum Univ Munchen, Div Clin Pharmacol, Munich, Germany Univ Pittsburgh, Neurol Surg, Pittsburgh, PA USA Rhein Westfal TH Aachen, Dept Child & Adolescent Psychiat Psychosomat & Ps, Aachen, Germany Univ Copenhagen, Inst Mol & Cellular Biol, Copenhagen, Denmark St Jude Childrens Res Hosp, Struct Biol, 332 N Lauderdale St, Memphis, TN 38105 USA Royal Shrewsbury Hosp, Colorectal Surg, Shrewsbury, Salop, England Univ Nottingham, Fac Med & Hlth Sci, Nottingham, England Karolinska Inst, Dept Physiol & Pharmacol, Solna, Sweden Chinese Acad Sci, Changchun Inst Appl Chem, State Key Lab Electroanalyt Chem, Jilin, Jilin, Peoples R China Univ British Columbia, Pediat, Vancouver, BC, Canada Chinese Acad Agr Sci, State Key Lab Cotton Biol, Res Base Anyang Inst Technol, Cotton Germplasm Resources,Inst Cotton Res, Beijing, Peoples R China Chinese Univ Hong Kong, Anaesthesia & Intens Care, Hong Kong, Peoples R China Univ Macau, ICMS, Zhuhai, Guangdong, Peoples R China North China Elect Power Univ, Sch Renewable Energy, Beijing, Peoples R China Justus Liegbig Univ, Dept Internal Med, Giessen, Germany Aarhus Univ, Biosci, Aarhus, Denmark Univ Dublin, Trinity Coll Dublin, Irish Longitudinal Study Ageing TILDA, Dublin, Ireland Univ Groningen, Univ Med Ctr Groningen, Hematol, Groningen, Netherlands Vrije Univ Amsterdam Med Ctr, Child Neurol, Amsterdam, Netherlands EBI, EMBL, Cambridge, England Max Planck Inst Marine Microbiol, HGF MPG Joint Res Grp Deep Sea Ecol & Technol, Bremen, Germany Max Planck Inst Human Dev, Ctr Adapt Rat, Berlin, Germany King Faisal Univ, Math, Al Hufuf, Saudi Arabia Griffith Univ, Sch Nursing & Midwifery, Gold Coast, Qld, Australia Iowa State Univ, Roy J Carver Dept Biochemsitry Biophys & Mol Biol, Ames, IA USA Delft Univ Technol, Fac Mech Maritime & Mat Engn, Engn Thermodynam Proc & Energy Dept, Leeghwaterstr 39, NL-2628 CB Delft, Netherlands Univ Nebraska Med Ctr, Coll Allied Hlth Profess, Cytotechnol Educ, Omaha, NE USA Shinko Mem Hosp, Dept Cardiovasc Med, Kobe, Hyogo, Japan Imperial Coll London, Mat, London, England Tech Univ Munich, Dept Surg, Munich, Germany Chinese Acad Agr Sci, Res Inst Pomol, Minist Agr, Lab Qual & Safety Risk Assessment Fruit Xingcheng, Shenyang, Liaoning, Peoples R China James Madison Univ, Commun Sci & Disorders, Harrisonburg, VA 22807 USA Univ Hosp Ulm, Inst Orthopaed Res & Biomech, Ulm, Germany Univ Essex, Sch Hlth & Social Care, Colchester, Essex, England Alpha Altis, Res Serv, Nottingham, England Erasmus MC, Med Oncol, Rotterdam, Netherlands Fed Univ Oye, Dept Ind Chem, Ekiti, Nigeria Duke Univ, Med Ctr, Cell Biol, Durham, NC USA Univ Oxford, Nuffield Dept Clin Neurosci, Oxford, England Univ Manchester, Canc Res UK Manchester Inst, Manchester, Lancs, England Helsinki Univ Hosp, Childrens Hosp, Helsinki, Finland Univ Aveiro, CESAM Ctr Environm & Marine Studies, Dept Biol, Aveiro, Portugal Univ Botswana, Psychol, Gaborone, Botswana Univ Fed Bahia, Nursing Sch, Salvador, BA, Brazil Queen Mary Univ London, Biol & Expt Psychol, London, England Natl Univ Pharm, Med Chem Dept, Kharkov, Ukraine Univ Bolton, Dept Educ & Psychol, Bolton, England La Trobe Univ, Dept Chem & Phys, Melbourne, Vic, Australia Gen Hosp Northern Theater Command, Dept Gastroenterol, Shenyang, Liaoning, Peoples R China Doctors Hosp, Dept Nephrol, Athens, Greece Univ Hosp Essen, Pediat 3, Essen, Germany Imperial Coll London, Infect Dis Epidemiol, London, England Sorbonne Univ, Dept Psychiat, Paris, France UNSW Sydney, Educ, Sydney, NSW, Australia Stanford Univ, Dept Psychiat & Behav Sci, Palo Alto, CA 94304 USA Hannover Med Sch, Clin Laryngol Rhinol & Otol, Hannover, Germany Curtin Univ, Ctr Aboriginal Studies, Perth, WA, Australia Iran Univ Sci & Technol, Biomed Engn Dept, Tehran, Iran Univ Calif San Francisco, Anesthesiol, San Francisco, CA 94143 USA Khalifa Univ Sci & Technol, Mech Engn, Abu Dhabi, U Arab Emirates Univ Florida, Hort Sci, Gainesville, FL USA James Cook Univ, Australian Inst Trop Hlth & Med, Ctr Biodiscovery & Mol Dev Therapeut, Cairns, Qld, Australia Univ Porto, Fac Med, CINTESIS, Porto, Portugal Shaoxing Peoples Hosp, Med Res Ctr, Shaoxing, Zhejiang, Peoples R China NIH, Dept Transfus Med, Bethesda, MD 20892 USA AIIMS, Dept Biotechnol, New Delhi, India Univ Ottawa, Biochem Microbiol & Immunol, Ottawa, ON, Canada Univ Oslo, Inst Clin Med, Div Mental Hlth & Addict, Oslo, Norway Univ Groningen, Univ Med Ctr Groningen, Dept Radiol, Groningen, Netherlands Univ Hong Kong, Sch Nursing, Hong Kong, Peoples R China Tokyo Med Univ, Ibaraki Med Ctr, Urol, Tokyo, Japan Univ Hosp Zurich, Dept Radiat Oncol, Zurich, Switzerland Univ Maryland, Inst Human Virol, Div Immunotherapy, Baltimore, MD 21201 USA Univ Maryland, Dept Surg, Baltimore, MD 21201 USA Stellenbosch Univ, Fac Med & Hlth Sci, Div Mol Biol & Human Genet, Stellenbosch, South Africa China Agr Univ, Coll Biol Sci, Beijing, Peoples R China Osaka Univ, Grad Sch Pharmaceut Sci, Suita, Osaka, Japan Univ Washington, Biochem, Seattle, WA 98195 USA Natl Res Council Italy, Inst Biosci & BioResources, Naples, Italy Univ Lyon, Phys, Lyon, France Univ Basel, Fac Psychol, Ctr Social Psychol, Basel, Switzerland Queen Mary Univ London, Barts Canc Inst, Ctr Mol Oncol, London, England EBI, EMBL, Samples Phenotypes & Ontol Team, Cambridge, England Charles Sturt Univ, Fac Arts & Educ, Bathurst, NSW, Australia Shandong Univ, Helmholtz Inst Biotechnol, Sch Life Sci, State Key Lab Microbial Technol, Jinan, Shandong, Peoples R China Shantou Univ, Dept Biol, Shantou, Guangdong, Peoples R China Shanxi Univ, Inst Biomed Sci, Taiyuan, Shanxi, Peoples R China St Jude Childrens Res Hosp, Computat Biol, 332 N Lauderdale St, Memphis, TN 38105 USA Harbin Med Univ, Coll Bioinformat Sci & Technol, Harbin, Heilongjiang, Peoples R China NIH, Radiol & Imaging Sci, Bldg 10, Bethesda, MD 20892 USA Georgia Inst Technol, Dept Biol Sci, Atlanta, GA 30332 USA XtalPi Inc, Cambridge, MA USA Consejo Nacl Invest Cient & Tecn, Partner Inst Max Planck Soc, Inst Invest Biomed Buenos Aires IBioBA, Bioinformat, Buenos Aires, DF, Argentina Univ Sydney, Save Sight Inst, Sydney, NSW, Australia Univ South Australia, Canc Res Inst, Australian Ctr Precis Hlth, Adelaide, SA, Australia Jinan Univ, Inst Life & Hlth Engn, Guangdong Higher Educ Inst, Key Lab Funct Prot Res, Guangzhou, Guangdong, Peoples R China Univ Texas Hlth Sci Ctr Houston, Epidemiol Human Genet & Environm Sci, Houston, TX 77030 USA Weill Cornell Med, Dept Microbiol & Immunol, New York, NY USA Guangdong Inst Appl Biol Resources, Biotechnol Lab, Guangzhou, Guangdong, Peoples R China Shandong Normal Univ, Coll Life Sci, Jinan, Shandong, Peoples R China Shandong Univ, Life Sci Dept, Jinan, Shandong, Peoples R China South China Agr Univ, Integrat Microbiol Res Ctr, Guangzhou, Guangdong, Peoples R China Liaoning Acad Agr Sci, Crop Mol Improving Lab, Shenyang, Liaoning, Peoples R China Lawson Hlth Res Inst, Med Biophys, London, ON, Canada Univ Melbourne, Infrastruct Engn, Parkville, Vic, Australia Univ Canberra, Fac Hlth, Canberra, ACT, Australia Univ Cambridge, MRC Cognit & Brain Sci Unit, Cambridge, England Emory Univ, Biostat & Bioinformat, Atlanta, GA 30322 USA Johns Hopkins Sch Med, Anesthesiol & Crit Care Med, Baltimore, MD USA Nottingham Trent Univ, Sch Anim Rural & Environm Sci, Nottingham, England Univ Exeter, Biosci, Exeter, Devon, England Hillingdon Hosp NHS Fdn Trust, London, England Univ Glasgow, MRC CSO Social & Publ Hlth Sci Unit, Glasgow, Lanark, Scotland Natl & Kapodistrian Univ Athens, Evaggelismos Athens Hosp, ICU, Athens, Greece Univ Newcastle, Biol Sci, Callaghan, NSW, Australia Coventry Univ, Fac Hlth & Life Sci, Ctr Innovat Res Life Course, Coventry, W Midlands, England Lausanne Univ Hosp, Serv Endocrinol Diabet & Metab, Lausanne, Switzerland Charles Sturt Univ, Sch Community Hlth, Bathurst, NSW, Australia Queens Univ Belfast, Inst Global Food Secur, Belfast, Antrim, North Ireland Natl Univ Singapore, Inst Policy Studies, Singapore, Singapore Univ Penn, Intitute Med & Engn, Philadelphia, PA 19104 USA Cold Spring Harbor Lab, POB 100, Cold Spring Harbor, NY 11724 USA Univ Michigan, EECS, Ann Arbor, MI 48109 USA Univ British Columbia, Ctr Blood Res, Vancouver, BC, Canada UiT Arctic Univ Norway, Dept Hlth & Care Sci, Fac Hlth Sci, Tromso, Norway Hosp Clin Porto Alegre, Physiotherapy, Porto Alegre, RS, Brazil Univ Paris 05, Med Sch, Paris, France Chinese Acad Agr Sci, Inst Crop Sci, Natl Key Facil Crop Gene Resources & Genet Improv, Beijing, Peoples R China Univ Ghent, Expt Clin & Hlth Psychol, Ghent, Belgium Indian Inst Adv Res, Bioinformat & Struct Biol, Gandhinagar, Gujart, India Bambino Ges Childrens Res Hosp, Lab Mol Med, Rome, Italy Heidelberg Univ, Ctr Infect Dis Parasitol, Heidelberg, Germany Stanford Univ, Elect Engn, Palo Alto, CA 94304 USA Univ Cadiz, Biol, Andalucia, Spain Mansoura Univ Hosp, Gen Surg, Mansoura, Egypt Inst Pasteur, Virol Pole, Dakar, Senegal Cardiff Univ, Div Canc & Genet, Cardiff, S Glam, Wales Ctr Expertise & Biol Diagnost Cameroon, Food Safety & Environm Microbiol, Yaounde, Cameroon Swiss Fed Labs Mat Sci & Technol, Lab Thin Films & Photovolta, Dubendorf, Switzerland Assiut Univ, Assiut Urol & Nephrol Hosp, Fac Med, Assiut, Egypt UCL, GEE, London, England UCL, IHA, London, England Univ Derby, Univ Derby Online Learning, Derby, England SUNY Stony Brook, Family Populat & Prevent Med, Stony Brook, NY 11794 USA Walter & Eliza Hall Inst Med Res, Mol Med Div, Melbourne, Vic, Australia Newcastle Univ, Northern Inst Canc Res, Newcastle Upon Tyne, Tyne & Wear, England German Ctr Neurodegenerat Dis, Clin Dementia Res, Bonn, Germany Sorbonne Univ, CNRS, UMR 7144, Stn Biol, Paris, France Univ Barcelona, Odontoestomatol, Barcelona, Spain Janelia Res Campus, Comp Sci, Ashburn, VA USA Univ Oxford, Ctr Trop Med & Global Hlth, Oxford, England Univ Bern, ARTORG Ctr Biomed Engn Res, Bern, Switzerland Australian Natl Univ, Eccles Inst Neurosci, John Curtain Sch Med Res, Canberra, ACT, Australia John Innes Ctr, Metab Biol, Norwich, Norfolk, England USDA ARS, Genom & Bioinformat Res Unit, Raleigh, NC 27695 USA Med Univ Graz, Inst Med Informat Stat & Documentat, Holzinger Grp, Graz, Austria Ajou Univ, Pharm, Suwon, South Korea City Univ Hong Kong, Sch Energy & Environm, Hong Kong, Peoples R China Univ British Columbia, Sch Kinseiol, Vancouver, BC, Canada Univ Copenhagen, Marine Biol Sect, Dept Biol, Copenhagen, Denmark Univ Vienna, Dept Commun, Vienna, Austria Univ Dundee, Sch Social Sci, Dundee, Scotland Tech Univ Dresden, Inst Bot, Dresden, Germany Univ Oxford, Div Struct Biol, Oxford, England Natl Univ Hlth Syst, Med, Singapore, Singapore Univ Canterbury, Sch Biol Sci, Christchurch, New Zealand Univ Hosp Southern Denmark, Focused Res Unit Mol Diagnost & Clin Res, Odense, Denmark Univ Oxford, Primary Care Hlth Sci, Oxford, England Baylor Coll Med, Verna & Marrs McLean Dept Biochem & Mol Biol, Houston, TX 77030 USA Adnan Menderes Univ Aydin, Fac Nursing, Dept Publ Hlth Nursing, Aydin, Turkey Oasi Res Inst IRCCS, Dept Neurol IC, Troina, Italy Purdue Univ, Weldon Sch Biomed Engn, W Lafayette, IN 47907 USA Kings Coll London, Kings Ctr Mil Hlth Res, London, England LSHTM, Dept Infect Dis Epidemiol, London, England Leibniz Univ Hannover, BMWZ Organ Chem, Hannover, Germany Xi An Jiao Tong Univ, Sch Basic Med Sci, Dept Physiol & Pathophysiol, Xian, Shaanxi, Peoples R China Univ South Australia, Sch Pharm & Med Sci, Adelaide, SA, Australia Univ Fed Santa Catarina, Dept Phys Educ, Florianopolis, SC, Brazil Southern Med Univ, Nanfang Hosp, Dept Oncol, Guangzhou, Guangdong, Peoples R China Stanford Univ, Hansen Expt Phys Lab, Palo Alto, CA 94304 USA Shenzhen Univ, Affiliated Hosp 1, Shenzhen Peoples Hosp 2, Inst Translat Med, Shenzhen, Guangdong, Peoples R China Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Peoples R China UCL, Dept Mech Engn, London, England ASTAR, Singapore Immunol Network, Lab Microbial Immun, Singapore, Singapore Cent South Univ, State Key Lab Powder Met, Changsha, Hunan, Peoples R China Univ Aberdeen, Inst Appl Hlth Sci, Aberdeen, Scotland Univ Bridgeport, Biomed Engn, Bridgeport, CT 06601 USA Texas Tech Univ, Hlth Sci Ctr, Pharmaceut Sci, Lubbock, TX 79430 USA Univ Montana, Ecosyst & Conservat Sci, Missoula, MT 59812 USA Univ Goettingen, Dept Syst Neurosci, Gottingen, Germany NHLBI, Lab Syst Genet, Bldg 10, Bethesda, MD 20892 USA Cleveland Clin, Lou Ruvo Ctr Brain Hlth, Imaging, Las Vegas, NV USA Flinders Univ S Australia, Coll Nursing & Hlth Sci, Nutr & Dietet, Adelaide, SA, Australia Univ Padua, Dept Math, Padua, Italy Lund Univ, Fac Law, Lund, Sweden Univ Gothenburg, Dept Microbiol & Immunol, Gothenburg, Sweden NARO, Kachwekano Zardi, Entebbe, Uganda Natl Yunlin Univ Sci & Technol, Bachelor Program Interdisciplinary Studies, Touliu, Yunlin, Taiwan Aarhus Univ, Dept Biomed, Danish Res Inst Translat Neurosci DANDRITE, Aarhus, Denmark Eduardo Mondlane Univ, Math & Comp Sci, Maputo, Mozambique Univ Bern, Dept Old Age Psychiat & Psychotherapy, Bern, Switzerland RAS, Inst Cytol, Lab Cytol Unicellular Organisms, St Petersburg, Russia Beijing Inst Technol, Sch Chem & Chem Engn, Beijing, Peoples R China Univ Queensland, Queensland Alliance Agr & Food Innovat, Brisbane, Qld, Australia Fraunhofer Inst Toxicol & Expt Med ITEM, Inhalat Toxicol, Hannover, Germany Univ Hong Kong, Publ Hlth, Hong Kong, Peoples R China Univ Hlth Network, Anesthesia & Pain Med, Toronto, ON, Canada Univ Toronto, Toronto, ON, Canada Univ Bath, Dept Hlth, Bath, Avon, England Univ Copenhagen, Computat & RNA Biol, Copenhagen, Denmark Fisheries & Oceans Canada, Bedford Inst Oceanog, Dartmouth, NS, Canada Goethe Univ, CEF MC, BMLS, Phys Biol, Frankfurt, Germany Albert Einstein Coll Med, Anat & Struct Biol, New York, NY USA Queensland Govt, Dept Environm & Sci, Brisbane, Qld, Australia Uppsala Univ, Vasc Surg Sect, Dept Surg Sci, Uppsala, Sweden Childrens Canc Hosp, Res, Cairo, Egypt Leibniz Inst Nat Prod Res & Infect Biol, Bio Pilot Plant, Jena, Germany Duy Tan Univ, Inst Res & Dev, Da Nang, Vietnam Univ Helsinki, Helsinki Inst Life Sci HiLIFE, Helsinki, Finland Univ Queensland, Australian Inst Bioengn & Nanotechnol, Brisbane, Qld, Australia George Inst Global Hlth, Sydney, NSW, Australia Griffith Univ, Griffith Inst Drug Discovery, Brisbane, Qld, Australia Dezhou Univ, Coll Phys & Elect Informat, Shandong Prov Key Lab Biophys, Dezhou, Peoples R China Henan Agr Univ, Coll Life Sci, Zhengzhou, Henan, Peoples R China Univ Tokyo, Publ Hlth, Tokyo, Japan Sun Yat Sen Univ, Affiliated Hosp 1, Guangzhou, Guangdong, Peoples R China Univ Illinois, Dept Med, Chicago, IL USA Beijing Inst Microbiol & Epidemiol, State Key Lab Pathogen & Biosecur, Beijing, Peoples R China Minist Hlth, Key Lab Neonatal Dis, Shanghai, Peoples R China Covenant Univ, Dept Phys, Ota, Nigeria Prince Sattam Bin Abdulaziz Univ, Dept Phys Therapy & Hlth Rehabil, Al Kharj, Saudi Arabia Lund Univ, Cognit Sci, Malmo, Sweden Natl Open Univ Nigeria, Dept Publ & Environm Hlth, Abuja, Nigeria Peking Univ, Sch Publ Hlth, Dept Lab Sci & Technol, Beijing, Peoples R China Univ Sydney, Sch Publ Hlth, Menzies Ctr Hlth Policy, Sydney, NSW, Australia Univ Auckland, Dept Elect & Comp Engn, Auckland, New Zealand Beijing Univ Chinese Med, Res Ctr TCM Informat Engn, Beijing, Peoples R China Osped Niguarda Ca Granda, Cardiac Surg, Milan, Italy Univ Vet Med, Clin Horses, Hannover, Germany Harbin Med Univ, Lab Med Genet, Harbin, Heilongjiang, Peoples R China Univ Saskatchewan, Dept Psychol, Saskatoon, SK, Canada Univ Coimbra, Ctr Studies Geog & Spatial Planning CEGOT, Coimbra, Portugal Univ Groningen, Univ Med Ctr Groningen, Epidemiol, Groningen, Netherlands South Cent High Specialty Hosp, Dept Neurol & Neurosurg, Pemex, Mexico Shandong Agr Univ, Coll Informat Sci & Engn, Tai An, Shandong, Peoples R China Curtin Univ, Natl Drug Res Inst, Perth, WA, Australia Wageningen Bioveterinary Res, Bacteriol & Epidemiol, Lelystad, Netherlands Guangdong Second Prov Gen Hosp, Dept Rheumatol & Immunol, Guangzhou, Guangdong, Peoples R China Erasmus MC, Biomed Rngineering, Rotterdam, Netherlands Hiroshima Univ, Grad Sch Biomed & Hlth Sci, Hiroshima, Japan Univ Iceland, Sch Hlth Sci, Reykjavik, Iceland Ohio State Univ, Mat Sci & Engn, Columbus, OH 43210 USA Kathmandu Univ, Sch Med Sci, Dept Physiotherapy, Dhulikhel, Nepal Univ Queensland, Sch Biomed Sci, Brisbane, Qld, Australia Fraunhofer MEVIS, Image Guided Therapies, Bremen, Germany Natl Univ Hlth Syst, Haematol Oncol, Singapore, Singapore Sun Yat Sen Univ, Canc Ctr, Breast Oncol, Guangzhou, Guangdong, Peoples R China Med Coll Wisconsin, Pharmacol & Toxicol, Wauwatosa, WI USA Queensland Univ Technol, Sci & Engn Fac, Sch Chem Phys & Mech Engn, Brisbane, Qld, Australia Univ Turin, Dept Mol Biotechnol & Hlth Sci, Turin, Italy Univ Tehran Med Sci, Sch Rehabil, Physiotherapy Dept, Tehran, Iran Univ Helsinki, Dept Forest Sci, Helsinki, Finland Univ Messina, Human Pathol, Messina, Italy AO Papardo Hosp Messina, Messina, Italy Univ Ibadan, Coll Med, Inst Child Hlth, Ibadan, Nigeria King Faisal Univ, Coll Med, Fac Ophthalmol, Al Hasa, Saudi Arabia Univ Stirling, Inst Social Mkt, Stirling, Scotland Saveh Univ Med Sci, Social Determinants Hlth Res Ctr, Saveh, Iran Gakujutsu Shien Co Ltd, Tokyo, Japan Chinese Acad Sci, Inst Geochem, Guiyang, Guizhou, Peoples R China Univ Plymouth, Med Sch, Plymouth, Devon, England CHU Toulouse, Immunol, Toulouse, France Azorean Biodivers Grp, Ctr Ecol Evolut & Environm Changes, Azores, Portugal Univ Acores, Azores, Portugal RIKEN, Ctr Integrat Med Sci, Yokohama, Kanagawa, Japan Peking Univ, Sch Publ Hlth, Dept Global Hlth, Beijing, Peoples R China Chang Gung Univ, Chang Gung Mem Hosp, Dept Neurol, Linkou Med Ctr, Taoyuan, Taiwan Chang Gung Univ, Coll Med, Taoyuan, Taiwan Univ Malawi, Coll Med, Biomed Sci Dept, Blantyre, Malawi Univ Malawi, Coll Med, Pharm Dept, Blantyre, Malawi Bioself Commun, Biocurat, Marseille, France Peking Univ, Hosp 3, Dept Neurol, Beijing, Peoples R China Ahmadu Bello Univ, Fac Basic Clin Sci, Coll Hlth Sci, Dept Pathol, Zaria, Nigeria Dalhousie Univ, Dept Anesthesia Pain Management & Perioperat Med, Halifax, NS, Canada VisMederi Srl, Siena, Italy UCL, Canc Res UK, London, England UCL, UCL Canc Trials Ctr, London, England Univ Ottawa, Family Med, Ottawa, ON, Canada China Agr Univ, Coll Engn, Beijing, Peoples R China Leiden Univ, Leiden Acad Ctr Drug Res, Div Drug Discovery & Safety, Leiden, Netherlands Sun Yat Sen Univ, Affiliated Hosp 1, Dept Intervent Radiol, Guangzhou, Guangdong, Peoples R China Amer Univ Beirut, Med Ctr, Infect Dis, Beirut, Lebanon Sheffield Hallam Univ, Dept Social Work Social Care & Community Studies, Sheffield, S Yorkshire, England Mechnikov Res Inst Vaccines & Sera, Viral Hepatitis, Moscow, Russia Univ Ottawa, Pediat, Ottawa, ON, Canada Vreden Russian Res Inst Traumatol & Orthopaed, Dept Wound Infect Treatment & Prevent, St Petersburg, Russia Hangzhou Ctr Dis Control & Prevent, Dept TB Control & Prevent, Hangzhou, Zhejiang, Peoples R China Kaohsiung Med Univ, Dept Biotechnol, Kaohsiung, Taiwan Zoetis, Diagnost, Kalamazoo, MI USA Aintree Univ Hosp NHS Fdn Trust, Head & Neck Oncol Res, Liverpool, Merseyside, England Wrightington Hosp, Trauma & Orthopaed, Manchester, Lancs, England Loyola Univ, Med Ctr, Dept Psychiat, 2160 S 1st Ave, Maywood, IL 60153 USA Atkins Vet Serv, Microbiol, Calgary, AB, Canada Univ Porto, FADEUP, CIAFEL, Porto, Portugal Natl Univ Singapore, Saw Swee Hock Sch Publ Hlth, Singapore, Singapore Kangwon Natl Univ, Coll Biotechnol & Biosci, Dept Food Sci & Biotechnol, Chunchon, South Korea Kakatiya Med Coll, Internal Med, Warangal, Telangana, India Univ Antioquia, Vet Med Sch, CIBAV Res Grp, Medellin, Colombia IISER, Dept Phys, Soft & Act Matter Grp, Tirupati 517507, Andhra Pradesh, India Univ Rosario, Sch Med & Hlth, Ctr Studies Phys Activ Measurements, Bogota, Colombia Univ Hosp Essen, Cardiol & Vasc Med, Essen, Germany Univ Hosp Basel, Endocrinol, Basel, Switzerland Univ Tubingen, Inst Med Genet & Appl Genom, Tubingen, Germany Univ Hosp Munster, Div Gen Internal Med Nephrol & Rheumatolog, Dept Med D, Munster, Germany Univ Kentucky, Dept Nephrol, Lexington, KY USA Univ Freiburg, Dept Anaesthesiol & Crit Care, Med Ctr, Freiburg, Germany Univ Calif Irvine, Dept Med, Orange, CA 92668 USA Univ Hosp Leuven, Dept Urol, Leuven, Belgium Chinese Acad Sci, Coll Life Sci, Beijing, Peoples R China Univ Florida, Orthopaed & Rehabil, Gainesville, FL USA Chongqing Med Univ, Affiliated Hosp 1, Chongqing Key Lab Mol Oncol & Epigenet, Chongqing, Peoples R China Tsinghua Univ, Dept Chem Engn, Beijing, Peoples R China Yonsei Univ, Coll Med, Dept Pharmacol, Seoul, South Korea Childrens Hosp Kings Daughters, Eastern Virginia Med Sch, Dept Pediat, Norfolk, VA USA China Three Gorges Univ, Coll Sci, Dept Math, Yichang, Peoples R China Xiangtan Univ, Coll Informat Engn, Xiangtan, Hunan, Peoples R China Univ Hlth Network, Mood Disorders & Psychopharmacol, Toronto, ON, Canada Sao Paulo State Univ UNESP, Dept Anim Sci, Sao Paulo, Brazil Sao Paulo State Univ, Vet Clin, Sao Paulo, Brazil
Published: 2019
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21. Photoplethysmography as a noninvasive surrogate for microneurography in measuring stress-induced sympathetic nervous activation - A machine learning approach.

Author: Rahman S, Udhayakumar R, Kaplan D, McCarthy B, Dawood T, Mellor N, Senior A, Macefield VG, Buxi D, and Karmakar C
Abstract: The sympathetic nervous system (SNS) is essential for the body's immediate response to stress, initiating physiological changes that can be measured through sympathetic nerve activity (SNA). While microneurography (MNG) is the gold standard for direct SNA measurement, its invasive nature limits its practical use in clinical settings. This study investigates the use of multi-wavelength photoplethysmography (PPG) as a non-invasive alternative for SNA measurement. Key features are extracted from the pulsatile components of red and green PPG signals to train a linear regression machine learning (ML) model to predict R-wave-triggered spike count (SPR), a biomarker derived from MNG. The study correlates PPG-derived features with ground truth SPR to develop a predictive model capable of detecting SNA during induced physical stress (isometric handgrip and cold pressor) and cognitive stress (mental arithmetic and Stroop test). Unlike previous research that relies on subjective stress indicators, our work utilizes MNG-derived SPR as an objective ground truth for validation. Our findings demonstrate strong agreement between PPG-predicted SPR values and those obtained via MNG, with red PPG showing a higher correlation. The green wavelength PPG exhibits greater sensitivity in detecting stress-induced SNA, particularly during stress onset, where it outperforms the MNG method in capturing immediate responses to stressors such as mental arithmetic and the cold pressor task. To the best of our knowledge, this is the first study to directly compare PPG-derived SNA estimates with MNG, offering a promising pathway for developing wearable, non-invasive tools for continuous stress monitoring and sympathetic arousal detection., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)
Published: 2024
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22. Exploration of an intrinsically explainable self-attention based model for prototype generation on single-channel EEG sleep stage classification.

Author: Adey B, Habib A, and Karmakar C
Subjects: Humans, Adult, Male, Female, Signal Processing, Computer-Assisted, Deep Learning, Young Adult, Electroencephalography methods, Sleep Stages physiology
Abstract: Prototype-based methods in deep learning offer interpretable explanations for decisions by comparing inputs to typical representatives in the data. This study explores the adaptation of SESM, a self-attention-based prototype method successful in electrocardiogram (ECG) tasks, for electroencephalogram (EEG) signals. The architecture is evaluated on sleep stage classification, exploring its efficacy in predicting stages with single-channel EEG. The model achieves comparable test accuracy compared to EEGNet, a state-of-the-art black-box architecture for EEG classification. The generated prototypical components are exaimed qualitatively and using the area over the perterbation curve (AOPC) indicate some alignment with expected bio-markers for different sleep stages such as alpha spindles and slow waves in non-REM sleep, but the results are severely limited by the model's ability to only extract and present information in the time-domain. Ablation studies are used to explore the impact of kernel size, number of heads, and diversity threshold on model performance and explainability. This study represents the first application of a self-attention based prototype method to EEG data and provides a step forward in explainable AI for EEG data analysis., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)
Published: 2024
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23. Designing a practical fatigue detection system: A review on recent developments and challenges.

Author: Imran MAA, Nasirzadeh F, and Karmakar C
Subjects: Humans, Wearable Electronic Devices, Machine Learning, Monitoring, Physiologic instrumentation, Monitoring, Physiologic methods, Fatigue diagnosis
Abstract: Introduction: Fatigue is considered to have a life-threatening effect on human health and it has been an active field of research in different sectors. Deploying wearable physiological sensors helps to detect the level of fatigue objectively without any concern of bias in subjective assessment and interfering with work., Methods: This paper provides an in-depth review of fatigue detection approaches using physiological signals to pinpoint their main achievements, identify research gaps, and recommend avenues for future research. The review results are presented under three headings, including: signal modality, experimental environments, and fatigue detection models. Fatigue detection studies are first divided based on signal modality into uni-modal and multi-modal approaches. Then, the experimental environments utilized for fatigue data collection are critically analyzed. At the end, the machine learning models used for the classification of fatigue state are reviewed., Practical Applications: The directions for future research are provided based on critical analysis of past studies. Finally, the challenges of objective fatigue detection in the real-world scenario are discussed., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
Published: 2024
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24. Robustness of Deep Learning models in electrocardiogram noise detection and classification.

Author: Rahman S, Pal S, Yearwood J, and Karmakar C
Subjects: Humans, Algorithms, Signal-To-Noise Ratio, Electrocardiography methods, Deep Learning, Neural Networks, Computer, Signal Processing, Computer-Assisted
Abstract: Background and Objective: Automatic electrocardiogram (ECG) signal analysis for heart disease detection has gained significant attention due to busy lifestyles. However, ECG signals are susceptible to noise, which adversely affects the performance of ECG signal analysers. Traditional blind filtering methods use predefined noise frequency and filter order, but they alter ECG biomarkers. Several Deep Learning-based ECG noise detection and classification methods exist, but no study compares recurrent neural network (RNN) and convolutional neural network (CNN) architectures and their complexity., Methods: This paper introduces a knowledge-based ECG filtering system using Deep Learning to classify ECG noise types and compare popular computer vision model architectures in a practical Internet of Medical Things (IoMT) framework. Experimental results demonstrate that the CNN-based ECG noise classifier outperforms the RNN-based model in terms of performance and training time., Results: The study shows that AlexNet, visual geometry group (VGG), and residual network (ResNet) achieved over 70% accuracy, specificity, sensitivity, and F1 score across six datasets. VGG and ResNet performances were comparable, but VGG was more complex than ResNet, with only a 4.57% less F1 score., Conclusions: This paper introduces a Deep Learning (DL) based ECG noise classifier for a knowledge-driven ECG filtering system, offering selective filtering to reduce signal distortion. Evaluation of various CNN and RNN-based models reveals VGG and Resnet outperform. Further, the VGG model is superior in terms of performance. But Resnet performs comparably to VGG with less model complexity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)
Published: 2024
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25. MDDBranchNet: A Deep Learning Model for Detecting Major Depressive Disorder Using ECG Signal.

Author: Habib A, Vaniya SN, Khandoker A, and Karmakar C
Subjects: Humans, Algorithms, Adult, Male, Deep Learning, Electrocardiography methods, Depressive Disorder, Major physiopathology, Depressive Disorder, Major diagnosis, Signal Processing, Computer-Assisted
Abstract: Major depressive disorder (MDD) is a chronic mental illness which affects people's well-being and is often detected at a later stage of depression with a likelihood of suicidal ideation. Early detection of MDD is thus necessary to reduce the impact, however, it requires monitoring vitals in daily living conditions. EEG is generally multi-channel and due to difficulty in signal acquisition, it is unsuitable for home-based monitoring, whereas, wearable sensors can collect single-channel ECG. Classical machine-learning based MDD detection studies commonly use various heart rate variability features. Feature generation, which requires domain knowledge, is often challenging, and requires computation power, often unsuitable for real time processing, MDDBranchNet is a proposed parallel-branch deep learning model for MDD binary classification from a single channel ECG which uses additional ECG-derived signals such as R-R signal and degree distribution time series of horizontal visibility graph. The use of derived branches was able to increase the model's accuracy by around 7%. An optimal 20-second overlapped segmentation of ECG recording was found to be beneficial with a 70% prediction threshold for maximum MDD detection with a minimum false positive rate. The proposed model evaluated MDD prediction from signal excerpts, irrespective of location (first, middle or last one-third of the recording), instead of considering the entire ECG signal with minimal performance variation stressing the idea that MDD phenomena are likely to manifest uniformly throughout the recording.
Published: 2024
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26. Epileptic seizure detection using CHB-MIT dataset: The overlooked perspectives.

Author: Ali E, Angelova M, and Karmakar C
Abstract: Epilepsy is a life-threatening neurological condition. Manual detection of epileptic seizures (ES) is laborious and burdensome. Machine learning techniques applied to electroencephalography (EEG) signals are widely used for automatic seizure detection. Some key factors are worth considering for the real-world applicability of such systems: (i) continuous EEG data typically has a higher class imbalance; (ii) higher variability across subjects is present in physiological signals such as EEG; and (iii) seizure event detection is more practical than random segment detection. Most prior studies failed to address these crucial factors altogether for seizure detection. In this study, we intend to investigate a generalized cross-subject seizure event detection system using the continuous EEG signals from the CHB-MIT dataset that considers all these overlooked aspects. A 5-second non-overlapping window is used to extract 92 features from 22 EEG channels; however, the most significant 32 features from each channel are used in experimentation. Seizure classification is done using a Random Forest (RF) classifier for segment detection, followed by a post-processing method used for event detection. Adopting all the above-mentioned essential aspects, the proposed event detection system achieved 72.63% and 75.34% sensitivity for subject-wise 5-fold and leave-one-out analyses, respectively. This study presents the real-world scenario for ES event detectors and furthers the understanding of such detection systems., Competing Interests: We declare we have no competing interests., (© 2024 The Authors.)
Published: 2024
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27. Continuous monitoring of body temperature for objective detection of health and safety risks in construction sites: An analysis of the accuracy and comfort of off-the-shelf wearable sensors.

Author: Nasirzadeh F, Karmakar C, Habib A, Benny Neelangal K, Mir M, Lee S, and Arnel T
Abstract: Recent studies have shown the potential of wearable sensors for objective detection of health and safety risks in construction workers through their collected physiological data. Body temperature, as the focus of the current study, is one of the most important physiological parameters that can help to detect various health and safety risks such as heat stress, physical fatigue, and infectious diseases. This study aims to assess the applicability and performance of off-the-shelf wearable sensor devices to monitor workers' body temperature in construction sites by evaluating the accuracy of temperature measurements as well as the comfort of the devices. A total of nine off-the-shelf wearable sensor devices available on the market were initially trialed in the laboratory, and three devices were shortlisted considering a set of selection criteria for further assessment. Over three weeks, the shortlisted wearable sensors were tested on 26 workers in two large construction sites in Australia. The reliability/validity of the selected wearable sensors in measuring body temperature was investigated using Bland-Altman analysis. Human factors were also investigated in terms of the comfort of the devices, their impact on workers' performance, and the acceptability of being worn for an extended period (i.e., 8 h or more). It was found that all selected devices measured body temperature with a bias of less than one indicating a slight difference in measurements compared to the reference hospital-grade thermometers. Two devices out of the three were also comfortable. The achieved results indicate that it is feasible to develop a continuous temperature monitoring platform using off-the-shelf wearable sensors to detect a range of significant health and safety risks in construction sites objectively. Considering the rapid advancements in manufacturing wearable sensors, future research can adopt a similar approach to include the newly introduced off-the-shelf temperature sensors and select the most appropriate device., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Farnad Nasirzadeh reports financial support was provided by Incolink. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2024 Published by Elsevier Ltd.)
Published: 2024
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28. Association of Chest Pain with Rate Pressure Product and ST-segment Changes after Sub Arachnoid Block in Caesarean Section.

Author: Mariom ML, Banik D, Mondol MK, Kader MA, Hassan M, Tushar SM, Karmakar CS, Hossain MS, Azad AK, Haque MM, Reza R, Morshed MM, Hasanuzzaman M, Masud M, and Sultana N
Subjects: Humans, Female, Pregnancy, Young Adult, Adult, Cesarean Section adverse effects, Bangladesh, Chest Pain diagnosis, Chest Pain etiology, Myocardial Ischemia, Anesthesia, Spinal
Abstract: When healthy women undergo caesarean section (CS) under sub arachnoid anaesthesia, transient electrocardiographic changes, such as ST-segment depression and T-wave abnormalities, are observed. During an elective caesarean section under sub arachnoid anaesthesia, about one-third of healthy parturient experience chest pain and ECG changes suggestive of myocardial ischemia. To assess the ST-segment and Rate Pressure Product changes with chest pain in patients with elective caesarean section under subarachnoid block. The Department of Anesthesia, Analgesia and Intensive Care Medicine at Bangabandhu Sheikh Mujib Medical University (BSMMU), Bangladesh was the site of this prospective observational study. The study included 86 healthy women between the ages of 20 and 35 who needed an elective caesarean section under a single shot sub arachnoid block and who visited the Department of Anesthesia, Analgesia, and Intensive Care Medicine at BSMMU in Shahbagh, Dhaka from January 2019 to June 2019. In comparison to the no chest pain group, ST-segment changes among the chest pain group at delivery, 5 minute, 10 minute after delivery and at the end of the surgery were highly significant (p=0.001). Comparatively, Rate Pressure Product changes were found to be significantly higher in the group with chest pain than in the group without chest pain (p=0.001). It is concluded that there is a substantial association of chest pain with rate pressure product and ST-segment changes after subarachroid block in caesarean section.
Published: 2023

29. Measurement of stress-induced sympathetic nervous activity using multi-wavelength PPG.

Author: Udhayakumar R, Rahman S, Buxi D, Macefield VG, Dawood T, Mellor N, and Karmakar C
Abstract: The onset of stress triggers sympathetic arousal (SA), which causes detectable changes to physiological parameters such as heart rate, blood pressure, dilation of the pupils and sweat release. The objective quantification of SA has tremendous potential to prevent and manage psychological disorders. Photoplethysmography (PPG), a non-invasive method to measure skin blood flow changes, has been used to estimate SA indirectly. However, the impact of various wavelengths of the PPG signal has not been investigated for estimating SA. In this study, we explore the feasibility of using various statistical and nonlinear features derived from peak-to-peak (AC) values of PPG signals of different wavelengths (green, blue, infrared and red) to estimate stress-induced changes in SA and compare their performances. The impact of two physical stressors: and Hand Grip are studied on 32 healthy individuals. Linear (Mean, s.d.) and nonlinear (Katz, Petrosian, Higuchi, SampEn, TotalSampEn) features are extracted from the PPG signal's AC amplitudes to identify the onset, continuation and recovery phases of those stressors. The results show that the nonlinear features are the most promising in detecting stress-induced sympathetic activity. TotalSampEn feature was capable of detecting stress-induced changes in SA for all wavelengths, whereas other features (Petrosian, AvgSampEn) are significant (AUC ≥ 0.8) only for IR and Red wavelengths. The outcomes of this study can be used to make device design decisions as well as develop stress detection algorithms., Competing Interests: Philia Labs is jointly developing the technology with the co-authors to compute sympathetic arousal from wearable data., (© 2023 The Authors.)
Published: 2023
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30. Individual and Conjoint Factors Associated With Beliefs About the Harmfulness of Nicotine Replacement Therapies Relative to Combustible Cigarettes Among People Who Smoke: Findings From the 2020 ITC Four Country Smoking and Vaping Survey.

Author: Yong HH, Karmakar C, Motin MA, Borland R, Cummings KM, Gravely S, and Fong GT
Subjects: Adult, Humans, United States epidemiology, Nicotine adverse effects, Tobacco Use Cessation Devices, Surveys and Questionnaires, Smoking Cessation, Vaping adverse effects, Tobacco Products adverse effects, Electronic Nicotine Delivery Systems
Abstract: Introduction: This study examined individual and conjoint factors associated with beliefs about the harmfulness of nicotine replacement therapies (NRTs) relative to combustible cigarettes (CCs)., Aims and Methods: Data analyzed came from 8642 adults (≥18 years) who smoked daily/weekly and participated in the 2020 ITC Four Country Smoking and Vaping Survey in Australia (n = 1213), Canada (n = 2633), England (n = 3057), and United States (n = 1739). Respondents were asked: "Compared to smoking cigarettes, how harmful do you think nicotine replacement products are?" Responses were dichotomized into "much less" versus otherwise for analysis using multivariable logistic regression models, complemented by decision-tree analysis to identify conjoint factors., Results: Percentages believing that NRTs are much less harmful than CCs were 29.7% (95% CI = 26.2% to 33.5%) in Australia, 27.4% (95% CI = 25.1% to 29.8%) in England, 26.4% (95% CI = 24.4% to 28.4%) in Canada, and 21.7% (95% CI = 19.2% to 24.3%) in the United States. Across all countries, believing nicotine is not at all/slightly harmful to health (aOR = 1.53-2.27), endorsing nicotine vaping products (NVPs) as less harmful than CCs (much less harmful: aOR = 7.24-14.27; somewhat less harmful: aOR = 1.97-3.23), and possessing higher knowledge of smoking harms (aOR = 1.23-1.88) were individual factors associated with increased odds of believing NRTs are much less harmful than CCs. With some country variations, these nicotine-related measures also interacted with each other and sociodemographic variables to serve as conjoint factors associated with the likelihood of accurate NRT relative harm belief., Conclusions: Many people who regularly smoke cigarettes are unaware that NRTs are much less harmful than cigarettes. Additionally, beliefs about NRTs relative harmfulness appear to be influenced by both individual and conjoint factors., Implications: This study demonstrates that despite past efforts to educate people who smoke about the harms of NRTs relative to CCs, misperceptions around the relative harmfulness of NRTs remain substantial. In all four studied countries, subgroups of people who smoke regularly who are misinformed about the relative harmfulness of NRTs, and who may be reluctant to use NRTs for smoking cessation can be reliably identified for corrective interventions based on their understanding of the harms related to nicotine, NVPs and smoking along with sociodemographic markers. The identified subgroup information can be used to prioritize and inform the development of effective interventions to specifically address the gaps in knowledge and understanding of the various subgroups identified. Our results suggest these may need to be tailored for each country., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.)
Published: 2023
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31. Domain Agnostic Post-Processing for QRS Detection Using Recurrent Neural Network.

Author: Habib A, Karmakar C, and Yearwood J
Subjects: Signal Processing, Computer-Assisted, Algorithms, Neural Networks, Computer
Abstract: Deep-learning-based QRS-detection algorithms often require essential post-processing to refine the output prediction-stream for R-peak localisation. The post-processing involves basic signal-processing tasks including the removal of random noise in the model's prediction stream using a basic Salt and Pepper filter, as well as, tasks that use domain-specific thresholds, including a minimum QRS size, and a minimum or maximum R-R distance. These thresholds were found to vary among QRS-detection studies and empirically determined for the target dataset, which may have implications if the target dataset differs such as the drop of performance in unknown test datasets. Moreover, these studies, in general, fail to identify the relative strengths of deep-learning models and the post-processing to weigh them appropriately. This study identifies the domain-specific post-processing, as found in the QRS-detection literature, as three steps based on the required domain knowledge. It was found that the use of minimal domain-specific post-processing is often sufficient for most of the cases and the use of additional domain-specific refinement ensures superior performance, however, it makes the process biased towards the training data and lacks generalisability. As a remedy, a domain-agnostic automated post-processing is introduced where a separate recurrent neural network (RNN)-based model learns required post-processing from the output generated from a QRS-segmenting deep learning model, which is, to the best of our knowledge, the first of its kind. The RNN-based post-processing shows superiority over the domain-specific post-processing for most of the cases (with shallow variants of the QRS-segmenting model and datasets like TWADB) and lags behind for others but with a small margin ( ≤ 2%). The consistency of the RNN-based post-processor is an important characteristic which can be utilised in designing a stable and domain agnostic QRS detector.
Published: 2023
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32. Impact of synthetic noise signature and physiologic ECG signal on designing ML-based ECG noise detection framework.

Author: Rahman S, Habib A, Karmakar C, and Yearwood J
Subjects: Humans, Machine Learning, Support Vector Machine, Artificial Intelligence, Electrocardiography
Abstract: Automatic signal analysis using artificial intelligence is getting popular in digital healthcare, such as ECG rhythm analysis, where ECG signals are collected from traditional ECG machines or wearable ECG sensors. However, the risk of using an automated system for ECG analysis when noise is present can lead to incorrect diagnosis or treatment decisions. A noise detector is crucial to minimise the risk of incorrect diagnosis. Machine learning (ML) models are used in ECG noise detection before clinical decision-making systems to mitigate false alarms. However, it is essential to prove the generalisation capability of the ML model in different situations. ML models performance is 50% lesser when the model is trained with synthetic and tested with physiologic ECG datasets compared to trained and tested with physiologic ECG datasets. This suggests that the ML model must be trained with physiologic ECG datasets rather than synthetic ones or add more various types of noise in synthetic ECG datasets that can mimic physiologic ECG.Clinical relevance- ML model trained with synthetic noisy ECG can increase the 50% misclassification rate in ECG noise detection compared to training with physiologic ECG datasets. The wrong classification of noise-free and noisy ECG will lead to misdiagnosis regarding the patient's condition, which could be a cause of death.
Published: 2023
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33. Nonlinear Features from Multi-Modal Signals for Continuous Stress Monitoring.

Author: Udhayakumar R, Rahman S, Gopakumar S, and Karmakar C
Subjects: Adult, Humans, Wakefulness, Machine Learning, Heart Rate, Electroencephalography, Mental Disorders
Abstract: Continuous monitoring of stress in individuals during their daily activities has become an inevitable need in present times. Unattended stress is a silent killer and may lead to fatal physical and mental disorders if left unidentified. Stress identification based on individual judgement often leads to under-diagnosis and delayed treatment possibilities. EEG-based stress monitoring is quite popular in this context, but impractical to use for continuous remote monitoring.Continuous remote monitoring of stress using signals acquired from everyday wearables like smart watches is the best alternative here. Non-EEG data such as heart rate and ectodermal activity can also act as indicators of physiological stress. In this work, we have explored the possibility of using nonlinear features from non-EEG data such as (a) heart rate, (b) ectodermal activity, (c) body temperature (d) SpO2 and (e) acceleration in detecting four different types of neurological states; namely (1) Relaxed state, (2) State of Physical stress, (3) State of Cognitive stress and (4) State of Emotional stress. Physiological data of 20 healthy adults have been used from the noneeg database of PhysioNet.Results: We used two machine learning models; a linear logistic regression and a nonlinear random forest to detect (a) stress from relaxed state and (4) the four different neurological states. We trained the models using linear and nonlinear features separately. For the 2-class and 4-class problems, using nonlinear features increased the accuracy of the models. Moreover, it is also proved in this study that by using nonlinear features, we can avoid the use of complex machine learning models.
Published: 2023
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34. Performance of a Convolutional Neural Network Derived From PPG Signal in Classifying Sleep Stages.

Author: Habib A, Motin MA, Penzel T, Palaniswami M, Yearwood J, and Karmakar C
Subjects: Sleep, Polysomnography, Electroencephalography, Sleep Stages physiology, Neural Networks, Computer
Abstract: Automatic sleep stage classification is vital for evaluating the quality of sleep. Conventionally, sleep is monitored using multiple physiological sensors that are uncomfortable for long-term monitoring and require expert intervention. In this study, we propose an automatic technique for multi-stage sleep classification using photoplethysmographic (PPG) signal. We have proposed a convolutional neural network (CNN) that learns directly from the PPG signal and classifies multiple sleep stages. We developed models for two- (Wake-Sleep), three- (Wake-NREM-REM) and four- (Wake-Light sleep-Deep sleep-REM) stages of sleep classification. Our proposed approach shows an average classification accuracy of 94.4%, 94.2%, and 92.9% for two, three, and four stages, respectively. Experimental results show that the proposed CNN model outperforms existing state-of-the-art models (classical and deep learning) in the literature.
Published: 2023
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35. Multi-stage sleep classification using photoplethysmographic sensor.

Author: Motin MA, Karmakar C, Palaniswami M, Penzel T, and Kumar D
Abstract: The conventional approach to monitoring sleep stages requires placing multiple sensors on patients, which is inconvenient for long-term monitoring and requires expert support. We propose a single-sensor photoplethysmographic (PPG)-based automated multi-stage sleep classification. This experimental study recorded the PPG during the entire night's sleep of 10 patients. Data analysis was performed to obtain 79 features from the recordings, which were then classified according to sleep stages. The classification results using support vector machine (SVM) with the polynomial kernel yielded an overall accuracy of 84.66%, 79.62% and 72.23% for two-, three- and four-stage sleep classification. These results show that it is possible to conduct sleep stage monitoring using only PPG. These findings open the opportunities for PPG-based wearable solutions for home-based automated sleep monitoring., Competing Interests: We have no competing interests., (© 2023 The Authors.)
Published: 2023
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36. Interpretability and Optimisation of Convolutional Neural Networks Based on Sinc-Convolution.

Author: Habib A, Karmakar C, and Yearwood J
Subjects: Humans, Machine Learning, Neural Networks, Computer, Algorithms
Abstract: Interpretability often seeks domain-specific facts, which is understandable to human, from deep-learning (DL) or other machine-learning (ML) models of black-box nature. This is particularly important to establish transparency in ML model's inner-working and decision-making, so that a certain level of trust is achieved when a model is deployed in a sensitive and mission-critical context, such as health-care. Model-level transparency can be achieved when its components are transparent and are capable of explaining reason of a decision, for a given input, which can be linked to domain-knowledge. This article used convolutional neural network (CNN), with sinc-convolution as its constrained first-layer, to explore if such a model's decision-making can be explained, for a given task, by observing the sinc-convolution's sinc-kernels. These kernels work like band-pass filters, having only two parameters per kernel - lower and upper cutoff frequencies, and optimised through back-propagation. The optimised frequency-bands of sinc-kernels may provide domain-specific insights for a given task. For a given input instance, the effects of sinc-kernels was visualised by means of explanation vector, which may help to identify comparatively significant frequency-bands, that may provide domain-specific interpretation, for the given task. In addition, a CNN model was further optimised by considering the identified subset of prominent sinc frequency-bands as the constrained first-layer, which yielded comparable or better performance, as compared to its all sinc-bands counterpart, as well as, a classical CNN. A minimal CNN structure, achieved through such an optimisation process, may help design task-specific interpretable models. To the best of our knowledge, the idea of sinc-convolution layer's task-specific significant sinc-kernel-based network optimisation is the first of its kind. Additionally, the idea of explanation-vector-based joint time-frequency representation to analyse time-series signals is rare in the literature. The above concept was validated for two tasks, ECG beat-classification (five-class classification task), and R-peak localisation (sample-wise segmentation task).
Published: 2023
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37. Design and development of a smartphone app for hypertension management: An intervention mapping approach.

Author: Lobo EH, Karmakar C, Abdelrazek M, Abawajy J, Chow CK, Zhang Y, Kabir MA, Daryabeygi R, Maddison R, and Islam SMS
Subjects: Humans, Health Behavior, Mobile Applications, Hypertension therapy, Self-Management, Smoking Cessation
Abstract: Background: Several research studies have demonstrated the potential of mobile health apps in supporting health management. However, the design and development process of these apps are rarely presented., Objective: We present the design and development of a smartphone-based lifestyle app integrating a wearable device for hypertension management., Methods: We used an intervention mapping approach for the development of theory- and evidence-based intervention in hypertension management. This consisted of six fundamental steps: needs assessment, matrices, theoretical methods and practical strategies, program design, adoption and implementation plan, and evaluation plan. To design the contents of the intervention, we performed a literature review to determine the preferences of people with hypertension (Step 1) and necessary objectives toward the promotion of self-management behaviors (Step 2). Based on these findings, we implemented theoretical and practical strategies in consultation with stakeholders and researchers (Steps 3), which was used to identify the functionality and develop an mHealth app (Step 4). The adoption (Step 5) and evaluation (Step 6) of the mHealth app will be conducted in a future study., Results: Through the needs analysis, we identified that people with hypertension preferred having education, medication or treatment adherence, lifestyle modification, alcohol and smoking cessation and blood pressure monitoring support. We utilized MoSCoW analysis to consider four key elements, i.e., education, medication or treatment adherence, lifestyle modification and blood pressure support based on past experiences, and its potential benefits in hypertension management. Theoretical models such as (i) the information, motivation, and behavior skills model, and (ii) the patient health engagement model was implemented in the intervention development to ensure positive engagement and health behavior. Our app provides health education to people with hypertension related to their condition, while utilizing wearable devices to promote lifestyle modification and blood pressure management. The app also contains a clinician portal with rules and medication lists titrated by the clinician to ensure treatment adherence, with regular push notifications to prompt behavioral change. In addition, the app data can be reviewed by patients and clinicians as needed., Conclusions: This is the first study describing the design and development of an app that integrates a wearable blood pressure device and provides lifestyle support and hypertension management. Our theory-driven intervention for hypertension management is founded on the critical needs of people with hypertension to ensure treatment adherence and supports medication review and titration by clinicians. The intervention will be clinically evaluated in future studies to determine its effectiveness and usability., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor SM declared a past co-authorship/collaboration (10.1016/S0140-6736(21)01207-1) with the author SI., (Copyright © 2023 Lobo, Karmakar, Abdelrazek, Abawajy, Chow, Zhang, Kabir, Daryabeygi, Maddison and Islam.)
Published: 2023
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38. Differentiating acute from chronic insomnia with machine learning from actigraphy time series data.

Author: Rani S, Shelyag S, Karmakar C, Zhu Y, Fossion R, Ellis JG, Drummond SPA, and Angelova M
Abstract: Acute and chronic insomnia have different causes and may require different treatments. They are investigated with multi-night nocturnal actigraphy data from two sleep studies. Two different wrist-worn actigraphy devices were used to measure physical activities. This required data pre-processing and transformations to smooth the differences between devices. Statistical, power spectrum, fractal and entropy analyses were used to derive features from the actigraphy data. Sleep parameters were also extracted from the signals. The features were then submitted to four machine learning algorithms. The best performing model was able to distinguish acute from chronic insomnia with an accuracy of 81%. The algorithms were then used to evaluate the acute and chronic groups compared to healthy sleepers. The differences between acute insomnia and healthy sleep were more prominent than between chronic insomnia and healthy sleep. This may be associated with the adaptation of the physiology to prolonged periods of disturbed sleep for individuals with chronic insomnia. The new model is a powerful addition to our suite of machine learning models aiming to pre-screen insomnia at home with wearable devices., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Rani, Shelyag, Karmakar, Zhu, Fossion, Ellis, Drummond and Angelova.)
Published: 2022
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39. Scalable Cluster Tendency Assessment for Streaming Activity Data using Recurring Shapelets.

Author: Datta S, Karmakar C, Rathore P, and Palaniswami M
Subjects: Cluster Analysis, Humans, Algorithms, Memory
Abstract: Automatic interpretation of cluster structure in rapidly arriving data streams is essential for timely detection of interesting events. Human activities often contain bursts of repeating patterns. In this paper, we propose a new relative of the Visual Assessment of Cluster Tendency (VAT) model, to interpret cluster evolution in streaming activity data where shapes of recurring patterns are important. Existing VAT algorithms are either suitable only for small batch data and unscalable to rapidly evolving streams, or cannot capture shape patterns. Our proposed incremental algorithm processes streaming data in chunks and identifies repeating patterns or shapelets from each chunk, creating a Dictionary-of-Shapes (DoS) that is updated on the fly. Each chunk is transformed into a lower dimensional representation based on it's distance from the shapelets in the current DoS. Then a small set of transformed chunks are sampled using an intelligent Maximin Random Sampling (MMRS) scheme, to create a scalable VAT image that is incrementally updated as the data stream progresses. Experiments on two upper limb activity datasets demonstrate that the proposed method can successfully and efficiently visualize clusters in long streams of data and can also identify anomalous movements.
Published: 2022
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40. Wearable cuffless blood pressure monitoring devices: a systematic review and meta-analysis.

Author: Islam SMS, Chow CK, Daryabeygikhotbehsara R, Subedi N, Rawstorn J, Tegegne T, Karmakar C, Siddiqui MU, Lambert G, and Maddison R
Abstract: Aims: High blood pressure (BP) is the commonest modifiable cardiovascular risk factor, yet its monitoring remains problematic. Wearable cuffless BP devices offer potential solutions; however, little is known about their validity and utility. We aimed to systematically review the validity, features and clinical use of wearable cuffless BP devices., Methods and Results: We searched MEDLINE, Embase, IEEE Xplore and the Cochrane Database till December 2019 for studies that reported validating cuffless BP devices. We extracted information about study characteristics, device features, validation processes, and clinical applications. Devices were classified according to their functions and features. We defined devices with a mean systolic BP (SBP) and diastolic BP (DBP) biases of <5 mmHg as valid as a consensus. Our definition of validity did not include assessment of device measurement precision, which is assessed by standard deviation of the mean difference-a critical component of ISO protocol validation criteria. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies version 2 tool. A random-effects model meta-analysis was performed to summarise the mean biases for SBP and DBP across studies. Of the 430 studies identified, 16 studies (15 devices, 974 participants) were selected. The majority of devices (81.3%) used photoplethysmography to estimate BP against a reference device; other technologies included tonometry, auscultation and electrocardiogram. In addition to BP and heart rate, some devices also measured night-time BP ( n = 5), sleep monitoring ( n = 3), oxygen saturation ( n = 3), temperature ( n = 2) and electrocardiogram ( n = 3). Eight devices showed mean biases of <5 mmHg for SBP and DBP compared with a reference device and three devices were commercially available. The meta-analysis showed no statistically significant differences between the wearable and reference devices for SBP (pooled mean difference = 3.42 mmHg, 95% CI: -2.17, 9.01, I 2 95.4%) and DBP (pooled mean = 1.16 mmHg, 95% CI: -1.26, 3.58, I 2 87.1%)., Conclusion: Several cuffless BP devices are currently available using different technologies, offering the potential for continuous BP monitoring. The variation in standards and validation protocols limited the comparability of findings across studies and the identification of the most accurate device. Challenges such as validation using standard protocols and in real-life settings must be overcome before they can be recommended for uptake into clinical practice., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.)
Published: 2022
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41. Robustness of electrocardiogram signal quality indices.

Author: Rahman S, Karmakar C, Natgunanathan I, Yearwood J, and Palaniswami M
Subjects: Electrocardiography, Humans, Reproducibility of Results, Signal-To-Noise Ratio, Algorithms, Signal Processing, Computer-Assisted
Abstract: Electrocardiogram (ECG) signal quality indices (SQIs) are essential for improving diagnostic accuracy and reliability of ECG analysis systems. In various practical applications, the ECG signals are corrupted by different types of noise. These corrupted ECG signals often provide insufficient and incorrect information regarding a patient's health. To solve this problem, signal quality measurements should be made before an ECG signal is used for decision-making. This paper investigates the robustness of existing popular statistical signal quality indices (SSQIs): relative power of QRS complex (SQI p ), skewness (SQI skew ), signal-to-noise ratio (SQI snr ), higher order statistics SQI (SQI hos ) and peakedness of kurtosis (SQI kur ). We analysed the robustness of these SSQIs against different window sizes across diverse datasets. Results showed that the performance of SSQIs considerably fluctuates against varying datasets, whereas the impact of varying window sizes was minimal. This fluctuation occurred due to the use of a static threshold value for classifying noise-free ECG signals from the raw ECG signals. Another drawback of these SSQIs is the bias towards noise-free ECG signals, that limits their usefulness in clinical settings. In summary, the fixed threshold-based SSQIs cannot be used as a robust noise detection system. In order to solve this fixed threshold problem, other techniques can be developed using adaptive thresholds and machine-learning mechanisms.
Published: 2022
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42. Detection of fetal arrhythmias in non-invasive fetal ECG recordings using data-driven entropy profiling.

Author: Keenan E, Karmakar C, Udhayakumar RK, Brownfoot FC, Lakhno I, Shulgin V, Behar JA, and Palaniswami M
Subjects: Algorithms, Arrhythmias, Cardiac diagnosis, Entropy, Female, Fetal Monitoring methods, Humans, Pregnancy, Prospective Studies, Signal Processing, Computer-Assisted, Electrocardiography methods, Heart Rate, Fetal physiology
Abstract: Objective. Fetal arrhythmias are a life-threatening disorder occurring in up to 2% of pregnancies. If identified, many fetal arrhythmias can be effectively treated using anti-arrhythmic therapies. In this paper, we present a novel method of detecting fetal arrhythmias in short length non-invasive fetal electrocardiography (NI-FECG) recordings. Approach. Our method consists of extracting a fetal heart rate time series from each NI-FECG recording and computing an entropy profile using a data-driven range of the entropy tolerance parameter r . To validate our approach, we apply our entropy profiling method to a large clinical data set of 318 NI-FECG recordings. Main Results. We demonstrate that our method ( TotalSampEn ) provides strong performance for classifying arrhythmic fetuses (AUC of 0.83) and outperforms entropy measures such as SampEn (AUC of 0.68) and FuzzyEn (AUC of 0.72). We also find that NI-FECG recordings incorrectly classified using the investigated entropy measures have significantly lower signal quality, and that excluding recordings of low signal quality (13.5% of recordings) increases the classification performance of TotalSampEn (AUC of 0.90). Significance. The superior performance of our approach enables automated detection of fetal arrhythmias and warrants further investigation in a prospective clinical trial., (© 2022 Institute of Physics and Engineering in Medicine.)
Published: 2022
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43. Performance Analysis of Entropy Methods in Detecting Epileptic Seizure from Surface Electroencephalograms.

Author: Ali E, Udhayakumar RK, Angelova M, and Karmakar C
Subjects: Electroencephalography, Entropy, Humans, Seizures diagnosis, Algorithms, Signal Processing, Computer-Assisted
Abstract: Physiological signals like Electrocardiography (ECG) and Electroencephalography (EEG) are complex and nonlinear in nature. To retrieve diagnostic information from these, we need the help of nonlinear methods of analysis. Entropy estimation is a very popular approach in the nonlinear category, where entropy estimates are used as features for signal classification and analysis. In this study, we analyze and compare the performances of four entropy methods; namely Distribution entropy (DistEn), Shannon entropy (ShanEn), Renyi entropy (RenEn) and LempelZiv complexity (LempelZiv) as classification features to detect epileptic seizure (ES) from surface Electroencephalography (sEEG) signal. Experiments were conducted on sEEG data from 23 subjects, obtained from the CHB-MIT database of PhysioNet. ShanEn, RenEn and LempelZiv entropy are found to be potential features for accurate and consistent detection of ES from sEEG, across multiple channels and subjects.
Published: 2021
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44. Measures of Bipedal Toe-Ground Clearance Asymmetry to Characterize Gait in Stroke Survivors.

Author: Datta S, Begg R, Rao AS, Karmakar C, Bajelan S, Said C, and Palaniswami M
Subjects: Accidental Falls, Humans, Survivors, Walking, Gait, Toes
Abstract: Post-stroke hemiparesis often impairs gait and increases the risks of falls. Low and variable Minimum Toe Clearance (MTC) from the ground during the swing phase of the gait cycle has been identified as a major cause of such falls. In this paper, we study MTC characteristics in 30 chronic stroke patients, extracted from gait patterns during treadmill walking, using infrared sensors and motion analysis camera units. We propose objective measures to quantify MTC asymmetry between the paretic and non-paretic limbs using Poincaré analysis. We show that these subject independent Gait Asymmetry Indices (GAIs) represent temporal variations of relative MTC differences between the two limbs and can distinguish between healthy and stroke participants. Compared to traditional measures of cross-correlation between the MTC of the two limbs, these measures are better suited to automate gait monitoring during stroke rehabilitation. Further, we explore possible clusters within the stroke data by analysing temporal dispersion of MTC features, which reveals that the proposed GAIs can also be potentially used to quantify the severity of lower limb hemiparesis in chronic stroke.
Published: 2021
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45. Evaluation of Mesh and Sensor Resolution for Finite Element Modeling of Non-Invasive Fetal ECG Signals.

Author: Keenan E, Karmakar C, Brownfoot FC, and Palaniswami M
Subjects: Female, Fetus, Finite Element Analysis, Humans, Pregnancy, Reproducibility of Results, Electrocardiography, Fetal Monitoring
Abstract: Non-invasive fetal electrocardiography (NI-FECG) is an emerging tool with novel diagnostic potential for monitoring fetal wellbeing using electrical signals acquired from the maternal abdomen. However, variations in the geometric structure and conductivity of maternal-fetal tissues have been shown to affect the reliability of NI-FECG signals. Previous studies have utilized detailed finite element models to simulate these impacts, however this approach is computationally expensive. In this study, we investigate a range of mesh and sensor resolutions to determine an optimal trade-off between computational cost and modeling accuracy for simulating NI-FECG signals. Our results demonstrate that an optimal refinement of mesh resolution provides comparable accuracy to a detailed reference solution while requiring approximately 12 times less computation time and one-third of the memory usage. Furthermore, positioning simulated sensors at a 20 mm grid spacing provides a sufficient representation of abdominal surface potentials. These findings represent default parameters to be used in future simulations of NI-FECG signals. Code for the model utilized in this work is available under an open-source GPL license as part of the fecgsyn toolbox.Clinical Relevance- Simulating NI-FECG signals provides the opportunity to study the effects of sensor placement and maternal-fetal anatomic variations in a controlled setting. This work has relevance in determining default parameters for efficiently performing these simulations.
Published: 2021
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46. A machine learning model for multi-night actigraphic detection of chronic insomnia: development and validation of a pre-screening tool.

Author: Kusmakar S, Karmakar C, Zhu Y, Shelyag S, Drummond SPA, Ellis JG, and Angelova M
Abstract: We propose a novel machine learning-based method for analysing multi-night actigraphy signals to objectively classify and differentiate nocturnal awakenings in individuals with chronic insomnia (CI) and their cohabiting healthy partners. We analysed nocturnal actigraphy signals from 40 cohabiting couples with one partner seeking treatment for insomnia. We extracted 12 time-domain dynamic and nonlinear features from the actigraphy signals to classify nocturnal awakenings in healthy individuals and those with CI. These features were then used to train two machine learning classifiers, random forest (RF) and support vector machine (SVM). An optimization algorithm that incorporated the predicted quality of each night for each individual was used to classify individuals into CI or healthy sleepers. Using the proposed actigraphic signal analysis technique, coupled with a rigorous leave-one-out validation approach, we achieved a classification accuracy of 80% (sensitivity: 76%, specificity: 82%) in classifying CI individuals and their healthy bed partners. The RF classifier (accuracy: 80%) showed a better performance than SVM (accuracy: 75%). Our approach to analysing the multi-night nocturnal actigraphy recordings provides a new method for screening individuals with CI, using wrist-actigraphy devices, facilitating home monitoring., (© 2021 The Authors.)
Published: 2021
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47. Detection of Coronary Artery Disease Using Multi-Domain Feature Fusion of Multi-Channel Heart Sound Signals.

Author: Liu T, Li P, Liu Y, Zhang H, Li Y, Jiao Y, Liu C, Karmakar C, Liang X, Ren M, and Wang X
Abstract: Heart sound signals reflect valuable information about heart condition. Previous studies have suggested that the information contained in single-channel heart sound signals can be used to detect coronary artery disease (CAD). But accuracy based on single-channel heart sound signal is not satisfactory. This paper proposed a method based on multi-domain feature fusion of multi-channel heart sound signals, in which entropy features and cross entropy features are also included. A total of 36 subjects enrolled in the data collection, including 21 CAD patients and 15 non-CAD subjects. For each subject, five-channel heart sound signals were recorded synchronously for 5 min. After data segmentation and quality evaluation, 553 samples were left in the CAD group and 438 samples in the non-CAD group. The time-domain, frequency-domain, entropy, and cross entropy features were extracted. After feature selection, the optimal feature set was fed into the support vector machine for classification. The results showed that from single-channel to multi-channel, the classification accuracy has increased from 78.75% to 86.70%. After adding entropy features and cross entropy features, the classification accuracy continued to increase to 90.92%. The study indicated that the method based on multi-domain feature fusion of multi-channel heart sound signals could provide more information for CAD detection, and entropy features and cross entropy features played an important role in it., Competing Interests: The authors declare no conflict of interest.
Published: 2021
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48. Identifying factors that conjointly influence nicotine vaping product relative harm perception among smokers and recent ex-smokers: Findings from the 2016 ITC Four Country Smoking and Vaping Survey.

Author: Yong HH, Karmakar C, Motin MA, Borland R, Elton-Marshall T, Cummings KM, Fong GT, and Thompson ME
Subjects: Adult, Australia, Canada, Electronic Nicotine Delivery Systems, England, Ex-Smokers, Female, Health Surveys, Humans, Male, Middle Aged, Perception, Smokers, Smoking, Smoking Cessation statistics & numerical data, Surveys and Questionnaires, Tobacco Smoking, Tobacco Use Cessation Devices, Nicotine, Tobacco Use psychology, Vaping
Abstract: Background: Use of nicotine vaping products (NVPs) to replace smoking is often influenced by perceived harmfulness of these products relative to smoking. This study aimed to identify factors that conjointly influenced NVP relative harm perception among smokers and ex-smokers., Methods: Data (n = 11,838) from adult smokers and ex-smokers (quit < 2 years) who participated in the 2016 ITC 4 Country Smoking and Vaping Surveys in Australia, Canada, England and the US were analyzed. Decision tree models were used to classify respondents into those who perceived vaping as less harmful than smoking ("correct" perception) versus otherwise ("incorrect" perception) based on their socio-demographic, smoking and vaping related variables., Results: Decision tree analysis identified nicotine replacement therapy (NRT) harmfulness perceptions relative to smoking, perceived vaping portrayal in the media and other sources as positive, negative or balanced, recency of seeking online vaping information, and age as the key variables that interacted conjointly to classify respondents into those with "correct" versus "incorrect" harm perceptions of vaping relative to smoking (model performance accuracy = 0.70-0.74). In all countries, NRT relative harmfulness perception and vaping portrayal perception were consistently the two most important classifying variables, with other variables showing some country differences., Conclusions: In all four countries, perception of NVP relative harmfulness among smokers and recent ex-smokers is strongly influenced by a combination of NRT relative harmfulness perception and vaping portrayal in the media and other sources. These conjoint factors can serve as useful markers for identifying subgroups more vulnerable to misperception about NVP relative harmfulness to benefit from corrective intervention., (Copyright © 2020 Elsevier B.V. All rights reserved.)
Published: 2021
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49. Bivariate Entropy Analysis of Electrocardiographic RR-QT Time Series.

Author: Shi B, Motin MA, Wang X, Karmakar C, and Li P
Abstract: QT interval variability (QTV) and heart rate variability (HRV) are both accepted biomarkers for cardiovascular events. QTV characterizes the variations in ventricular depolarization and repolarization. It is a predominant element of HRV. However, QTV is also believed to accept direct inputs from upstream control system. How QTV varies along with HRV is yet to be elucidated. We studied the dynamic relationship of QTV and HRV during different physiological conditions from resting, to cycling, and to recovering. We applied several entropy-based measures to examine their bivariate relationships, including cross sample entropy (XSampEn), cross fuzzy entropy (XFuzzyEn), cross conditional entropy (XCE), and joint distribution entropy (JDistEn). Results showed no statistically significant differences in XSampEn, XFuzzyEn, and XCE across different physiological states. Interestingly, JDistEn demonstrated significant decreases during cycling as compared with that during the resting state. Besides, JDistEn also showed a progressively recovering trend from cycling to the first 3 min during recovering, and further to the second 3 min during recovering. It appeared to be fully recovered to its level in the resting state during the second 3 min during the recovering phase. The results suggest that there is certain nonlinear temporal relationship between QTV and HRV, and that the JDistEn could help unravel this nuanced property.
Published: 2020
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50. Entropy Profiling: A Reduced-Parametric Measure of Kolmogorov-Sinai Entropy from Short-Term HRV Signal.

Author: Karmakar C, Udhayakumar R, and Palaniswami M
Abstract: Entropy profiling is a recently introduced approach that reduces parametric dependence in traditional Kolmogorov-Sinai (KS) entropy measurement algorithms. The choice of the threshold parameter r of vector distances in traditional entropy computations is crucial in deciding the accuracy of signal irregularity information retrieved by these methods. In addition to making parametric choices completely data-driven, entropy profiling generates a complete profile of entropy information as against a single entropy estimate (seen in traditional algorithms). The benefits of using "profiling" instead of "estimation" are: (a) precursory methods such as approximate and sample entropy that have had the limitation of handling short-term signals (less than 1000 samples) are now made capable of the same; (b) the entropy measure can capture complexity information from short and long-term signals without multi-scaling; and (c) this new approach facilitates enhanced information retrieval from short-term HRV signals. The novel concept of entropy profiling has greatly equipped traditional algorithms to overcome existing limitations and broaden applicability in the field of short-term signal analysis. In this work, we present a review of KS-entropy methods and their limitations in the context of short-term heart rate variability analysis and elucidate the benefits of using entropy profiling as an alternative for the same.
Published: 2020
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