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2. Prevalence of Poor Sleep Quality and Associated Factors Among the Elderly in Amirkola City, Iran

Author

Seyed Reza Hosseini, Mostafa Dezhalon, Reza Ghadimi, Ali Bijani, and Ali Zabihi

Subjects
Health Policy, Public Health, Environmental and Occupational Health
Abstract

Background & Aims: One of the problems affecting elderly people's quality of life is sleep problems which has an adverse impact on their social, occupational and other activities. This study was conducted aiming to determine the prevalence of poor sleep quality among the elderly in …, northern Iran. Methods: This cross-sectional study is part of the second phase of … Health and Ageing Project (…HAP) which is a cohort study that has been conducted on all elderly people aged 60 and over in … city, north of Iran since 2011. The sleep quality and its related factors were assessed through Pittsburgh Sleep Quality Index (PSQI-P) and interviews, respectively. Results: Of the 1675 elderly people, 914 (54.6%) were male and 761 (45.4%) were female, among them 714 (42.6%) had poor sleep quality. The prevalence of poor sleep quality in women and men was 56.9% and 30.7%, respectively (p

Published
2023
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4. Hemodynamic Changes after Continuing or Omitting Regular Angiotensin Converting Enzyme Inhibitors before Cataract Surgery: A Comparative Study

Author

Sedigheh Ahmadi, Saeed Khademi, Reza Jouybar, Naeimehossadat Asmarian, Maryam Ghadimi, Mehrdad Salari, and Soodabeh Emami

Subjects
Internal Medicine
Abstract

Aims: In this study, we aimed to appraise the effects of interrupting (discontinuing) vs. continuing Angiotensin receptor blockers (ARBs) and Angiotensin-Converting Enzyme Inhibitors (ACEIs) on the hemodynamic changes of patients during and after cataract surgery. Methods and Materials: Patients aged 40-70 years, American society of anesthesiologist (ASA) class II, taking ACEI/ARB medications, who were admitted to Khalili hospital (Shiraz, south of Iran) for cataract surgery, were enrolled in the study. Patients were randomly divided into two groups for continuing or withdrawing the use of ACEI/ARBs. Group 1 included the patients who continued ACEI/ARB administration, and group 2 included those who discontinued them before surgery. In the operating room, relevant demographic information was collected in addition to the data on patients’ basic clinical status, including heart rate and blood pressure, before induction of anesthesia, during, and after that. The collected data were analyzed using SPSS 21, and p-values < 0.05 were considered statistically significant. Results: Any significant differences were not revealed in demographic variables (age, sex, diabetes, hypertension, Myocardial infarction, Smoking, and duration of drug therapy) between the two groups. Time effect was significant (p Conclusion: It seems that in some minor surgeries, such as cataract surgery, withdrawal or continuation of ACEIs/ARBs have no significant effect on the hypotension and heart rate of patients during orafter an operation. Clinical Trial Registration Number: The study has been registered in the Iranian registry for clinical trials (IRCT20141009019470N78).

Published
2023
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8. Spermatogenesis regeneration by transfected spermatogonial stem cells in infertile roosters through testicular transplantation

Author

Kazem Rasouli-Gharehsaghal, Malak Shakeri, Mahdi Zhandi, Hamid-Reza Amini, Fereshteh Ghadimi, Afsaneh Golkar-Narenji, and Paul Edward Mozdziak

Subjects
Food Animals, Equine, Animal Science and Zoology, Small Animals
Abstract

Investigations pertaining to spermatogonial stem cells (SSCs) have led to the use of these cells in a variety of fields including infertility treatments, production of transgenic animals, and genome editing. The aim of the present study was to investigate the plausibility of regenerating spermatogenesis in infertile roosters by transplanting transfected SSCs into testes. Spermatogonial stem cells were isolated and cultured for seven days. Afterward, pDB2, a plasmid vector carrying a reporter gene, GFP, was transfected into the SSCs. Transfected SSCs were transplanted into the left testis of infertile roosters. Tissue samples from the recipients' testes were obtained six weeks after the transplantation and transplanted SSCs were observed in the basement membrane. After eight weeks, GFP-positive spermatozoa were observed in collected semen from the recipient roosters and GFP gene in spermatozoa was confirmed using PCR. The recipient roosters were mated with hens. Hatchlings were visually checked and their tissue samples were tested by PCR to identify transgenesis but both of them were negative. Overall, it seems that regeneration of spermatogenesis in roosters via transfected SSCs is possible but more studies are need to produce recombinant proteins by this way.

Published
2023
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9. A Psychosocial Risk Assessment Tool to Predict Postnatal Depression in Women with Complicated Pregnancy

Author

Mahbobeh Faramarzi, Angela Hamidia, Farzan Kheirkhah, Zahra Basirat, Reza Ghadimi, Mohammad Chehrazi, Shahnaz Barat, Pim Cuijpers, Elizabeth O'Connor, Seyyedeh Mahboubeh Mirtabar, Clinical Psychology, APH - Global Health, APH - Mental Health, and World Health Organization (WHO) Collaborating Center

Subjects
Complicated pregnancy, Psychiatry and Mental health, SDG 3 - Good Health and Well-being, depression, women, antenatal risk question-naire, psychosocial assessment, mental disorders
Abstract

Introduction: Few studies have reported the role of psychosocial risk factors by a validated scale in predicting mental disorders in women with complicated pregnancy. This study investigated the role of a psychosocial risk assessment tool in the prediction of postnatal depression in women with complicated pregnancy. Methods: A prospective study was performed on pregnant women with complicated pregnancy from December 2019 to June 2020. A total of 125 pregnant women filled the Antenatal Risk Questionnaire (ANRQ), Edinburgh Postnatal Depression Scale (EPDS) and Brief Symptom Inventory 53-items (BSI-53). Also, the patients completed EPDS during 6-weeks of postpartum. An expert mental specialist conducted the interviews based on the DSM-5. Results: More than half of the women with complicated pregnancy were diagnosed to have at least one mental disorder. The mean risk scores of ANRQ including the childhood social support from the respondent’s mother, history of mental illness, perceived level of support available postpartum, significant life events in the past 12 months, and personality traits with high anxiety were higher in women with mental disorders than those without mental disorders. The results emphasized that the total score of ANRQ was the strongest positive predictor for postnatal depression score of EPDS (β = 0.569, p= Conclusion: The study proposes that the use of a validated psychosocial risk assessment tool alongside a screening psychological tool, like EPDS, is reliable for prediction of mental disorders and help women with complicated pregnancy at risk for prevention of depression at antenatal visits.

Published
2023
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10. An analysis of barriers for successful implementation of municipal solid waste management in Beijing: an integrated DEMATEL-MMDE-ISM approach

Author

Chao Wang, Yongkang Sun, Ming K. Lim, Pezhman Ghadimi, and Amir Hossein Azadnia

Subjects
Strategy and Management, Industrial relations, Industrial and Manufacturing Engineering, Computer Science Applications, Management Information Systems
Abstract

PurposeWith rapid industrialization and urbanization, municipal solid waste (MSW) management has become a serious challenge worldwide, especially in developing countries. The Beijing Municipality is a representative example of many local governments in China that are facing MSW management issues. Although there have been studies in the area of MSW management in the literature, less attention has been devoted to developing a structured framework that identifies and interprets the barriers to MSW management in megacities, especially in Beijing. Therefore, this study focuses on identifying a comprehensive list of barriers affecting the successful implementation of MSW management in Beijing.Design/methodology/approachThrough an extensive review of related literature, 12 barriers are identified and classified into five categories: government, waste, knowledge dissemination, MSW management process and market. Using an integrated approach including the decision-making trial and evaluation laboratory (DEMATEL), maximum mean de-entropy algorithm (MMDE) and interpretive structural modeling (ISM), a conceptual structural model of MSW implementation barriers is constructed to provide insights for industrial decision-makers and policymakers.FindingsThe results show that a lack of economic support from the government, imperfect MSW-related laws and regulations, the low education of residents and the lack of publicity of waste recycling knowledge are the main barriers to MSW management in Beijing. Combined with expert opinions, the paper provides suggestions and guidance to municipal authorities and industry practitioners to guide the successful implementation of MSW management.Practical implicationsThe findings of this study can provide a reference for MSW management in other metropolises in China and other developing countries.Originality/valueThis study proposes a hybrid DEMATEL-MMDE-ISM approach to resolve the subjectivity issues of the traditional ISM approach and it analyzes the barriers that hinder MSW management practices in Beijing.

Published
2023
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14. The Effect of Rainbow Trout ( Oncorhynchus mykiss ) Collagen Incorporated with Exo‐Polysaccharides Derived from Rhodotorula mucilaginosa sp. on Burn Healing

Author

Tayyeb Ghadimi, Soheila Naderi Gharahgheshlagh, Noorahmad Latifi, Ahmad Hivechi, Vahid Hosseinpour Sarmadi, Siamak Farokh Forghani, Naser Amini, Peiman B. Milan, Fatemeh Latifi, Masoud Hamidi, Ghazaleh Larijani, Seyed Mohammad Amin Haramshahi, Motahareh Abdollahi, Fatemeh Ghadimi, and Saeed Nezari

Subjects
Biomaterials, Polymers and Plastics, Materials Chemistry, Bioengineering, Biotechnology
Published
2023
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15. Association of country income level with the characteristics and outcomes of critically ill patients hospitalized with acute kidney injury and COVID-19

Author

Wainstein, Marina, Spyrison, Nicholas, Dai, Danyang, Ghadimi, Moji, Chavez-Iniquez, Jonathan Samuel, Rizo Topete, Lilia María, Citarella, Barbara Wanjiru, Merson, Laura, Pole, Jason, Claure-Del Granado, Rolando, Johnson, David W., Shrapnel, Sally, Abdukahil, heryl Ann, Abdulkadir, Nurul Najmee, Abe, Ryuzo, Abel, Laurent, Abrous, Amal, Absil, Lara, Acker, Andrew, Adachi, Shingo, Adrião, Diana, Al Ageel, Saleh, Ahmed, Shakeel, Ainscough, Kate, Airlangga, Eka, Aisa, Tharwat, Hssain, Ali Ait, Tamlihat, Younes Ait, Akimoto, Takako, Akmal, Ernita, Akwani, Chika, Al Qasim, Eman, Alalqam, Razi, Alberti, Angela, Al-dabbous, Tala, Alegesan, Senthilkumar, Alessi, Marta, Alex, Beatrice, Alexandre, Kévin, Al-Fares, Abdulrahman, Alfoudri, Huda, Ali, Imran, Alidjnou, Kazali Enagnon, Aliudin, Jeffrey, Alkhafajee, Qabas, Allavena, Clotilde, Allou, Nathalie, Alves, João, Alves, Rita, Alves, João Melo, Cabrita, Joana Alves, Amaral, Maria, Amira, Nur, Ampaw, Phoebe, Andini, Roberto, Andréjak, Claire, Angheben, Andrea, Angoulvant, François, Ansart, Séverine, Anthonidass, Sivanesen, Antonelli, Massimo, Antunes de Brito, Carlos Alexandre, Apriyana, Ardiyan, Arabi, Yaseen, Aragao, Irene, Arancibia, Francisco, Araujo, Carolline, Arcadipane, Antonio, Archambault, Patrick, Arenz, Lukas, Arlet, Jean-Benoît, Arnold-Day, Christel, Arora, Lovkesh, Arora, Rakesh, Artaud-Macari, Elise, Aryal, Diptesh, Asensio, Angel, Ashraf, Muhammad, Assie, Jean Baptiste, Asyraf, Amirul, Atif, Minahel, Atique, Anika, Auchabie, Johann, Aumaitre, Hugues, Auvet, Adrien, Azemar, Laurène, Azoulay, Cecile, Bach, Benjamin, Bachelet, Delphine, Badr, Claudine, Baillie, J. Kenneth, Baird, J Kevin, Bak, Erica, Bakakos, Agamemnon, Bakar, Nazreen Abu, Bal, Andriy, Balakrishnan, Mohanaprasanth, Balan, Valeria, Bani-Sadr, Firouzé, Barbalho, Renata, Barbosa, Nicholas Yuri, Barclay, Wendy S., Barnett, Saef Umar, Barnikel, Michaela, Barrelet, Audrey, Barrigoto, Cleide, Bartoli, Marie, Baruch, Joaquín, Basmaci, Romain, Hassin Basri, Muhammad Fadhli, Battaglini, Denise, Bauer, Jules, Bautista Rincon, Diego Fernando, Beane, Abigail, Bedossa, Alexandra, Bee, Ker Hong, Begum, Husna, Behilill, Sylvie, Beishuizen, Albertus, Beljantsev, Aleksandr, Bellemare, David, Beltrame, Anna, Beltrão, Beatriz Amorim, Beluze, Marine, Benech, Nicolas, Benjiman, Lionel Eric, Benkerrou, Dehbia, Bennett, Suzanne, Benny, Binny, Bento, Luís, Berdal, Jan-Erik, Bergeaud, Delphine, Bergin, Hazel, Bernal Sobrino, José Luis, Bertoli, Giulia, Bertolino, Lorenzo, Bessis, Simon, Bevilcaqua, Sybille, Bezulier, Karine, Bhatt, Amar, Bhavsar, Krishna, Bianco, Claudia, Bidin, Farah Nadiah, Singh, Moirangthem Bikram, Humaid, Felwa Bin, Bin Kamarudin, Mohd Nazlin, Bisoffi, Zeno, Bissuel, François, Biston, Patrick, Bitker, Laurent, Bitton, Jonathan, Blanco-Schweizer, Pablo, Blier, Catherine, Bloos, Frank, Blot, Mathieu, Blumberg, Lucille, Boccia, Filomena, Bodenes, Laetitia, Bogaert, Debby, Boivin, Anne-Hélène, Bolaños, Isabela, Bolze, Pierre-Adrien, Bompart, François, Borges, Diogo, Borie, Raphaël, Botelho-Nevers, Elisabeth, Bouadma, Lila, Bouchaud, Olivier, Bouchez, Sabelline, Bouhmani, Dounia, Bouhour, Damien, Bouiller, Kévin, Bouillet, Laurence, Bouisse, Camile, Boureau, Anne-Sophie, Bourke, John, Bouscambert, Maude, Bousquet, Aurore, Bouziotis, Jason, Boxma, Bianca, Boyer-Besseyre, Marielle, Boylan, Maria, Bozza, Fernando Augusto, Braconnier, Axelle, Braga, Cynthia, Monteiro, Filipa Brás, Brazzi, Luca, Breen, Patrick, Breen, Dorothy, Brewster, David, Brickell, Kathy, Browne, Shaunagh, Brusse-Keizer, Marjolein, Bryda, Petra, Buchtele, Nina, Bugaeva, Polina, Buisson, Marielle, Burhan, Erlina, Burrell, Aidan, Bustos, Ingrid G., Butnaru, Denis, Cabie, André, Cabral, Susana, Caceres, Eder, Cadoz, Cyril, Garcês, Rui Caetano, Calligy, Kate, Calvache, Jose Andres, Camões, João, Campana, Valentine, Campbell, Paul, Campisi, Josie, Cantero, Mireia, Caraux-Paz, Pauline, Cardellino, Chiara Simona, Cardoso, Sofia, Cardoso, Filipe, Cardoso, Filipa, Cardoso, Nelson, Carelli, Simone, Carlier, Nicolas, Carmoi, Thierry, Carney, Gayle, Carqueja, Inês, Carret, Marie-Christine, Carrier, François Martin, Carroll, Ida, Carson, Gail, Casanova, Maire-Laure, Cascão, Mariana, Casey, Siobhan, Casimiro, José, Cassandra, Bailey, Castanheira, Nidyanara, Castor-Alexandre, Guylaine, Castro, Ivo, Catarino, Ana, Catherine, François-Xavier, Cattaneo, Paolo, Cavalin, Roberta, Cavayas, Alexandros, Cervantes-Gonzalez, Minerva, Chair, Anissa, Chakveatze, Catherine, Chan, Adrienne, Chand, Meera, Chantalat Auger, Christelle, Chapplain, Jean-Marc, Charpentier, Charlotte, Chas, Julie, Chávez Iñiguez, Jonathan Samuel, Chen, Anjellica, Chen, Yih-Sharng, Chenard, Léo, Cheng, Matthew Pellan, Cheret, Antoine, Chiarabini, Thibault, Chica, Julian, Chidambaram, Suresh Kumar, Tho, Leong Chin, Chirouze, Catherine, Chiumello, Davide, Cho, Sung-Min, Cholley, Bernard, Chopin, Marie-Charlotte, Chow, Ting Soo, Chow, Yock Ping, Chua, Hiu Jian, Chua, Jonathan, Cidade, Jose Pedro, Ciullo, Anna, Clarke, Jennifer, Clohisey, Sara, Cobb, Perren J., Codan, Cassidy, Cody, Caitriona, Coelho, Alexandra, Coles, Megan, Coles, Jennifer, Colin, Gwenhaël, Collins, Michael, Colombo, Sebastiano Maria, Combs, Pamela, Connolly, Jennifer, Connor, Marie, Conrad, Anne, Conway, Elaine, Cooke, Graham S., Copland, Mary, Cordel, Hugues, Corley, Amanda, Cornelis, Sabine, Cornet, Alexander Daniel, Corpuz, Arianne Joy, Cortegiani, Andrea, Corvaisier, Grégory, Couffignal, Camille, Couffin-Cadiergues, Sandrine, Courtois, Roxane, Cousse, Stéphanie, Croonen, Sabine, Crowl, Gloria, Crump, Jonathan, Cruz, Claudina, Cruz Bermúdez, Juan Luis, Rojo, Jaime Cruz, Csete, Marc, Cullen, Ailbhe, Curley, Gerard, Curlier, Elodie, Curran, Colleen, Custodio, Paula, da Silva Filipe, Ana, Da Silveira, Charlene, Dabaliz, Al-Awwab, Dagens, Andrew, Dahly, Darren, Dalton, Heidi, Dalton, Jo, Daly, Seamus, Damas, Juliana, Daneman, Nick, Daniel, Corinne, Dankwa, Emmanuelle A., Dantas, Jorge, de Loughry, Gillian, De Montmollin, Etienne, Freitas de Oliveira França, Rafael, De Rosa, Rosanna, de Silva, Thushan, de Vries, Peter, Dean, David, Debard, Alexa, DeBenedictis, Bianca, Debray, Marie-Pierre, DeCastro, Nathalie, Dechert, William, Deconninck, Lauren, Decours, Romain, Defous, Eve, Delacroix, Isabelle, Delaveuve, Eric, Delavigne, Karen, Dell'Amore, Andrea, Delmas, Christelle, Delobel, Pierre, Delsing, Corine, Demonchy, Elisa, Denis, Emmanuelle, Deplanque, Dominique, Depuydt, Pieter, Desai, Mehul, Descamps, Diane, Desvallées, Mathilde, Dewayanti, Santi, Dhanger, Pathik, Diallo, Alpha, Diamantis, Sylvain, Da Silva, Fernanda Dias, Diaz, Juan Jose, Diaz, Rodrigo, Didier, Kévin, Diehl, Jean-Luc, Dieperink, Wim, Dimet, Jérôme, Dinot, Vincent, Diop, Fara, Diouf, Alphonsine, Dishon, Yael, Djossou, Félix, Docherty, Annemarie B., Doherty, Helen, Donnelly, Maria, Donnelly, Christl A., Donohue, Sean, Donohue, Yoann, Donohue, Chloe, Doran, Peter, Dorival, Céline, D'Ortenzio, Eric, Douglas, James Joshua, Dournon, Nathalie, Downer, Triona, Downey, Joanne, Downing, Mark, Drake, Tom, Driscoll, Aoife, Dryden, Murray, Fonseca, Claudio Duarte, Dubee, Vincent, Dubos, François, Ducancelle, Alexandre, Duculan, Toni, Dudman, Susanne, Duggal, Abhijit, Dunand, Paul, Dunning, Jake, Duplaix, Mathilde, Durante-Mangoni, Emanuele, Durham, Lucian, Dussol, Bertrand, Duthoit, Juliette, Duval, Xavier, Dyrhol-Riise, Anne Margarita, Ean, Sim Choon, Echeverria-Villalobos, Marco, Edwards, Eleanor, Egan, Siobhan, El Sanharawi, Mohammed, Elapavaluru, Subbarao, Elharrar, Brigitte, Eloy, Philippine, Elshazly, Tarek, Enderle, Isabelle, Endo, Tomoyuki, Eng, Chan Chee, Engelmann, Ilka, Enouf, Vincent, Epaulard, Olivier, Escher, Martina, Esperatti, Mariano, Esperou, Hélène, Santo, Catarina Espírito, Esposito-Farese, Marina, Estevão, João, Etienne, Manuel, Ettalhaoui, Nadia, Everding, Anna Greti, Evers, Mirjam, Fabre, Marc, Fabre, Isabelle, Faheem, Amna, Fahy, Arabella, Fairfield, Cameron J., Faria, Pedro, Fateena, Hanan, Fatoni, Arie Zainul, Faure, Karine, Favory, Raphaël, Fayed, Mohamed, Feely, Niamh, Feeney, Laura, Fernandes, Jorge, Fernandes, Marília Andreia, Fernandes, Susana, Ferrand, François-Xavier, Devouge, Eglantine Ferrand, Ferrão, Joana, Ferraz, Mário, Ferreira, Sílvia, Ferreira, Bernardo, Ferreira, Benigno, Ferriere, Nicolas, Ficko, Céline, Figueiredo-Mello, Claudia, Fiorda, Juan, Flament, Thomas, Flanagan, Emily, Flateau, Clara, Fletcher, Tom, Florence, Aline-Marie, Florio, Letizia Lucia, Flynn, Deirdre, Foley, Jean, Fomin, Victor, Fonseca, Tatiana, Forsyth, Simon, Foster, Denise, Foti, Giuseppe, Fourn, Erwan, Fowler, Robert A., Fraher, Marianne, Franch-Llasat, Diego, Fraser, John F., Fraser, Christophe, Freire, Marcela Vieira, Ribeiro, Ana Freitas, Friedrich, Caren, Fritz, Ricardo, Fry, Stéphanie, Fuentes, Nora, Fukuda, Masahiro, G, Argin, Gaborieau, Valérie, Gaci, Rostane, Gagliardi, Massimo, Gagnard, Jean-Charles, Gagneux-Brunon, Amandine, Gaião, Sérgio, Skeie, Linda Gail, Gallagher, Phil, Gamble, Carrol, Gani, Yasmin, Garan, Arthur, Garcia, Rebekha, Barrio, Noelia García, Garcia-Gallo, Esteban, Garot, Denis, Garrait, Valérie, Gault, Nathalie, Gavin, Aisling, Gavrylov, Anatoliy, Gaymard, Alexandre, Gebauer, Johannes, Geraud, Eva, Morlaes, Louis Gerbaud, Germano, Nuno, Ghosn, Jade, Giani, Marco, Gibson, Jess, Gigante, Tristan, Gilg, Morgane, Gilroy, Elaine, Giordano, Guillermo, Girvan, Michelle, Gissot, Valérie, Glikman, Daniel, Glybochko, Petr, Gnall, Eric, Goehringer, François, Goffard, Jean-Christophe, Goh, Jin Yi, Golob, Jonathan, Gominet, Marie, Gonzalez, Alicia, Gordon, Patricia, Gorenne, Isabelle, Gormley, Conor, Goubert, Laure, Goujard, Cécile, Goulenok, Tiphaine, Grable, Margarite, Grandin, Edward Wilson, Granier, Pascal, Grasselli, Giacomo, Green, Christopher A., Greenhalf, William, Greffe, Segolène, Grieco, Domenico Luca, Griffee, Matthew, Griffiths, Fiona, Grigoras, Ioana, Groenendijk, Albert, Gruner, Heidi, Gu, Yusing, Guedj, Jérémie, Guego, Martin, Guellec, Dewi, Guerreiro, Daniela, Guery, Romain, Guillaumot, Anne, Guilleminault, Laurent, Guimarães de Castro, Maisa, Guimard, Thomas, Haalboom, Marieke, Haber, Daniel, Habraken, Hannah, Hachemi, Ali, Hadri, Nadir, Hakak, Sheeba, Hall, Adam, Hall, Matthew, Halpin, Sophie, Hamer, Ansley, Hamers, Raph L., Hamidfar, Rebecca, Hammond, Terese, Hammond, Naomi, Han, Lim Yuen, Hao, Kok Wei, Hardwick, Hayley, Harrison, Ewen M., Harrison, Janet, Hartman, Alan, Hashmi, Junaid, Hayes, Ailbhe, Hays, Leanne, Heerman, Jan, Heggelund, Lars, Hendry, Ross, Hennessy, Martina, Hentzien, Maxime, Hernandez, Diana, Hershey, Andrew, Hesstvedt, Liv, Higgins, Eibhlin, Higgins, Dawn, Higgins, Rupert, Hinchion, Rita, Hinton, Samuel, Hiraiwa, Hiroaki, Hitoto, Hikombo, Ho, Antonia, Ho, Yi Bin, Hoctin, Alexandre, Hoffmann, Isabelle, Hoh, Wei Han, Hoiting, Oscar, Holt, Rebecca, Holter, Jan Cato, Horby, Peter, Hoshino, Kota, Houas, Ikram, Hough, Catherine L., Houltham, Stuart, Ming-Yang Hsu, Jimmy, Hulot, Jean-Sébastien, Hurd, Abby, Ijaz, Samreen, Ikram, M. Arfan, Illes, Hajnal-Gabriela, Imbert, Patrick, Inácio, Hugo, Ing, Yun Sii, Ippolito, Mariachiara, Isgett, Sarah, Isidoro, Tiago, Ismail, Nadiah, Isnard, Margaux, Itai, Junji, Ivulich, Daniel, Jaafar, Danielle, Jaafoura, Salma, Jabot, Julien, Jackson, Clare, Jaquet, Pierre, Jassat, Waasila, Jaud-Fischer, Coline, Jaureguiberry, Stéphane, Jego, Florence, Jelani, Anilawati Mat, Jenum, Synne, Joe, Ong Yiaw, Jorge García, Ruth N., Joseph, Mark, Joseph, Cédric, Jourdain, Mercé, Jouvet, Philippe, Jung, Anna, Juzar, Dafsah, Kafif, Ouifiya, Kaguelidou, Florentia, Kaisbain, Neerusha, Kaleesvran, Thavamany, Kali, Sabina, Kalomoiri, Smaragdi, Ayadi Kamaluddin, Muhammad Aisar, Che Kamaruddin, Zul Amali, Kamarudin, Nadiah, Kandamby, Darshana Hewa, Kandel, Chris, Kang, Kong Yeow, Karpayah, Pratap, Kartsonaki, Christiana, Kasugai, Daisuke, Kataria, Anant, Katz, Kevin, Kaur, Aasmine, Kay, Christy, Kayyali, Lamees, Keating, Seán, Kelly, Claire, Kelly, Yvelynne, Kelly, Andrea, Kelly, Niamh, Kelly, Aoife, Kelly, Sadie, Kelsey, Maeve, Kennedy, Ryan, Kennon, Kalynn, Kernan, Maeve, Kerroumi, Younes, Keshav, Sharma, Khalid, Imrana, Khalil, Antoine, Khan, Coralie, Khan, Irfan, Kho, Michelle E., Khoo, Saye, Khoo, Ryan, Khoo, Denisa, Kiat, Khor How, Kida, Yuri, Kiiza, Peter, Granerud, Beathe Kiland, Kildal, Anders Benjamin, Kim, Jae Burm, Kimmoun, Antoine, Kitamura, Nobuya, Klenerman, Paul, Klont, Rob, Bekken, Gry Kloumann, Knight, Stephen R., Komatsu, Mamoru, Korten, Volkan, Kpangon, Arsène, Krawczyk, Karolina, Krishnan, Sudhir, Krishnan, Vinothini, Kruglova, Oksana, Kumar, Deepali, Kumar, Ganesh, Tirupakuzhi Vijayaraghavan, Bharath Kumar, Vecham, Pavan Kumar, Kuriakose, Dinesh, Kurtzman, Ethan, Kutsogiannis, Demetrios, Kutsyna, Galyna, Kyriakoulis, Konstantinos, Lachatre, Marie, Lacoste, Marie, Laffey, John G., Lafhej, Nadhem, Lagrange, Marie, Laine, Fabrice, Lairez, Olivier, Lalueza, Antonio, Lambert, Marc, Langelot-Richard, Marie, Langlois, Vincent, Lantang, Eka Yudha, Lanza, Marina, Laouénan, Cédric, Laribi, Samira, Lariviere, Delphine, Lasry, Stéphane, Launay, Odile, Laureillard, Didier, Lavie-Badie, Yoan, Law, Andy, Lawrence, Teresa, Lawrence, Cassie, Le, Minh, Le Bihan, Clément, Le Bris, Cyril, Le Falher, Georges, Le Fevre, Lucie, Le Hingrat, Quentin, Le Maréchal, Marion, Le Mestre, Soizic, Le Moal, Gwenaël, Le Moing, Vincent, Le Nagard, Hervé, Le Turnier, Paul, Lee, Todd C., Lee, Su Hwan, Lee, James, Lee, Jennifer, Lee, Heng Gee, Lee, Biing Horng, Lee, Yi Lin, Leeming, Gary, Lefebvre, Laurent, Lefebvre, Bénédicte, Lefèvre, Benjamin, LeGac, Sylvie, Lelievre, Jean-Daniel, Lellouche, François, Lemaignen, Adrien, Lemee, Véronique, Lemeur, Anthony, Lemmink, Gretchen, Lene, Ha Sha, Leone, Michela, Leone, Marc, Lepiller, Quentin, Lescure, François-Xavier, Lesens, Olivier, Lesouhaitier, Mathieu, Lester-Grant, Amy, Letrou, Sophie, Levy, Yves, Levy, Bruno, Levy-Marchal, Claire, L'Her, Erwan, Bassi, Gianluigi Li, Liang, Janet, Liegeon, Geoffrey, Lim, Wei Shen, Lim, Kah Chuan, Lima, Chantre, Lina, Bruno, Lina, Lim, Lind, Andreas, Lingas, Guillaume, Lion-Daolio, Sylvie, Liu, Keibun, Livrozet, Marine, Lizotte, Patricia, Lolong, Navy, Loon, Leong Chee, Lopes, Diogo, Lopez-Colon, Dalia, Loschner, Anthony L., Loubet, Paul, Loufti, Bouchra, Louis, Guillame, Lourenco, Silvia, Low, Lee, Lowik, Marije, Loy, Jia Shyi, Lucet, Jean Christophe, Bermejo, Carlos Lumbreras, Luna, Carlos M., Lungu, Olguta, Lunn, Miles, Luong, Liem, Luque, Nestor, Luton, Dominique, Lyons, Ruth, Maasikas, Olavi, Mabiala, Oryane, Machado, Sara, Machado, Moïse, Macheda, Gabriel, Madiha, Hashmi, Maestro de la Calle, Guillermo, Mahieu, Rafael, Mahy, Sophie, Maier, Lars S., Maillet, Mylène, Maitre, Thomas, Malfertheiner, Maximilian, Malik, Nadia, Mallon, Paddy, Malvy, Denis, Manda, Victoria, Mandelbrot, Laurent, Manetta, Frank, Mankikian, Julie, Manning, Edmund, Manuel, Aldric, Sant`Ana Malaque, Ceila Maria, Marino, Flávio, Markowicz, Samuel, Marques, Ana, Marsh, Brian, Marsh, Laura, Marshal, Megan, Marshall, John, Martelli, Celina Turchi, Martin, Emily, Martin-Blondel, Guillaume, Martinez, F. Eduardo, Martin-Loeches, Ignacio, Martinot, Martin, Martins, João, Martins, Ana, Rego, Caroline Martins, Martucci, Gennaro, Martynenko, Olga, Marwali, Eva Miranda, Marzukie, Marsilla, Maslove, David, Mason, Sabina, Mat Nor, Mohd Basri, Matan, Moshe, Mathieu, Daniel, Mattei, Mathieu, Maulin, Laurence, Maxwell, Michael, Mazzoni, Thierry, Sweeney, Lisa Mc, McArthur, Colin, McCanny, Peter, McCarthy, Anne, McCarthy, Aine, McCloskey, Colin, McConnochie, Rachael, McDermott, Sherry, McDonald, Sarah E., McElroy, Aine, McElwee, Samuel, McEneany, Victoria, McEvoy, Natalie, McGeer, Allison, McKay, Chris, McKeown, Johnny, McLean, Kenneth A., McNicholas, Bairbre, McPartlan, Elaine, Meaney, Edel, Mear-Passard, Cécile, Mechlin, Maggie, Mehkri, Omar, Mele, Ferruccio, Menon, Kusum, Mentré, France, Mentzer, Alexander J., Mercier, Noémie, Mercier, Emmanuelle, Merckx, Antoine, Mergeay-Fabre, Mayka, Mergler, Blake, Mesquita, António, Metwally, Osama, Meybeck, Agnès, Meyer, Dan, Meynert, Alison M., Meysonnier, Vanina, Meziane, Amina, Mezidi, Mehdi, Michelanglei, Céline, Michelet, Isabelle, Mihelis, Efstathia, Mihnovit, Vladislav, Miller, Jennene, Misnan, Nor Arisah, Mohamed, Tahira Jamal, Eliza Mohamed, Nik Nur, Moin, Asma, Molinos, Elena, Molloy, Brenda, Monahan, Sinead, Mone, Mary, Monteiro, Agostinho, Montes, Claudia, Montrucchio, Giorgia, Moore, Shona C., Moore, Sarah, Cely, Lina Morales, Moro, Lucia, Motherway, Catherine, Motos, Ana, Mouquet, Hugo, Perrot, Clara Mouton, Moyet, Julien, Mudara, Caroline, Muh, Ng Yong, Muhamad, Dzawani, Mullaert, Jimmy, Müller, Fredrik, Müller, Karl Erik, Munblit, Daniel, Murphy, Aisling, Murphy, Lorna, Murray, Patrick, Murris, Marlène, Murthy, Srinivas, Musaab, Himed, Muyandy, Gugapriyaa, Myrodia, Dimitra Melia, Nagpal, Dave, Nagrebetsky, Alex, Narasimhan, Mangala, Narayanan, Nageswaran, Neant, Nadège, Necsoi, Coca, Nekliudov, Nikita, Neto, Raul, Neumann, Emily, Ng, Pauline Yeung, Ng, Wing Yiu, Nghi, Anthony, Nguyen, Duc, Choileain, Orna Ni, Leathlobhair, Niamh Ni, Nichol, Alistair D., Nitayavardhana, Prompak, Nonas, Stephanie, Mohd Noordin, Nurul Amani, Noret, Marion, Izzati Norharizam, Nurul Faten, Norman, Lisa, Notari, Alessandra, Noursadeghi, Mahdad, Nseir, Saad, Nusantara, Dwi Utomo, Nyamankolly, Elsa, Brien, Fionnuala O., Callaghan, Annmarie O., O'Callaghan, Annmarie, Occhipinti, Giovanna, OConnor, Derbrenn, Ogura, Takayuki, O'Halloran, Sophie, O'Hearn, Katie, Ohshimo, Shinichiro, Oliveira, João, Olliaro, Piero L., O'Neil, Conar, Ong, David S. Y., Ong, Jee Yan, Oosthuyzen, Wilna, Opavsky, Anne, Openshaw, Peter, Orozco-Chamorro, Claudia Milena, Ortoleva, Jamel, Osatnik, Javier, O'Shea, Linda, O'Sullivan, Miriam, Othman, Siti Zubaidah, Ouamara, Nadia, Ouissa, Rachida, Oziol, Eric, Pagadoy, Maïder, Pages, Justine, Palmarini, Massimo, Panarello, Giovanna, Panda, Prasan Kumar, Pang, Lai Hui, Panigada, Mauro, Pansu, Nathalie, Papadopoulos, Aurélie, Parke, Rachael, Pasquier, Jérémie, Pastene, Bruno, Patauner, Fabian, Pathmanathan, Mohan Dass, Patricio, Patricia, Patrier, Juliette, Patterson, Lisa, Paul, Mical, Paul, Christelle, Paulos, Jorge, Paxton, William A., Payen, Jean-François, Peake, Sandra L., Peariasamy, Kalaiarasu, Jiménez, Miguel Pedrera, Peek, Giles J., Peelman, Florent, Peiffer-Smadja, Nathan, Peigne, Vincent, Pejkovska, Mare, Pelosi, Paolo, Peltan, Ithan D., Pereira, Rui, Perez, Daniel, Periel, Luis, Perpoint, Thomas, Pesenti, Antonio, Pestre, Vincent, Petrou, Lenka, Petrovic, Michele, Petrov-Sanchez, Ventzislava, Pettersen, Frank Olav, Peytavin, Gilles, Pharand, Scott, Piagnerelli, Michael, Picard, Walter, Picone, Olivier, Pierobon, Carola, Piersma, Djura, Pimentel, Carlos, Piquard, Valentine, Pires, Catarina, Pironneau, Isabelle, Piroth, Lionel, Pitaloka, Ayodhia, Piubelli, Chiara, Pius, Riinu, Plantier, Laurent, Png, Hon Shen, Poissy, Julien, Pokeerbux, Ryadh, Poli, Sergio, Pollakis, Georgios, Ponscarme, Diane, Porto, Diego Bastos, Post, Andra-Maris, Postma, Douwe F., Povoa, Pedro, Póvoas, Diana, Powis, Jeff, Prapa, Sofia, Preau, Sébastien, Prebensen, Christian, Preiser, Jean-Charles, Prinssen, Anton, Proença, Lucia, Pudota, Sravya, Puéchal, Oriane, Semedi, Bambang Pujo, Purcell, Gregory, Quesada, Luisa, González, Víctor Quirós, Quist-Paulsen, Else, Quraishi, Mohammed, Qutishat, Fadi, Rabaud, Christian, Rafael, Aldo, Rafiq, Marie, Rahardjani, Mutia, Rahimi, Amir Kamel, Rahman, Rozanah Abd, Haji Ab Rahman, Ahmad Kashfi, Rainieri, Fernando, Rajahram, Giri Shan, Ramakrishnan, Nagarajan, Ramalho, José, Ramli, Ahmad Afiq, Rammaert, Blandine, Ramos, Grazielle Viana, Ranjan, Ritika, Rapp, Christophe, Rasmin, Menaldi, Rätsep, Indrek, Ravi, Tharmini, Real, Andre, Rebaudet, Stanislas, Redl, Sarah, Reeve, Brenda, Reid, Liadain, Reikvam, Dag Henrik, Reis, Renato, Remy, Martine, Ren, Hongru, Resseguier, Anne-Sophie, Revest, Matthieu, Rewa, Oleksa, Reyes, Tiago, Reyes, Luis Felipe, Ribeiro, Maria Ines, Richardson, David, Richardson, Denise, Richier, Laurent, Atikah Ahmad Ridzuan, Siti Nurul, Rios, Ana L., Rishu, Asgar, Rispal, Patrick, Risso, Karine, Rizer, Nicholas, Robba, Chiara, Roberto, André, Roberts, Stephanie, Robertson, David L., Robineau, Olivier, Roche-Campo, Ferran, Rodari, Paola, Rodeia, Simão, Roessler, Bernhard, Roger, Pierre-Marie, Rojek, Amanda, Romaru, Juliette, Roncon-Albuquerque, Roberto, Roriz, Mélanie, Rosa-Calatrava, Manuel, Rose, Michael, Rosenberger, Dorothea, Rossanese, Andrea, Rossetti, Matteo, Rossignol, Bénédicte, Rossignol, Patrick, Rousset, Stella, Roy, Carine, Roze, Benoît, Russell, Clark D., Ryan, Maria, Ryan, Maeve, Ryckaert, Steffi, Holten, Aleksander Rygh, Saba, Isabela, Sadat, Musharaf, Sahraei, Valla, Saint-Gilles, Maximilien, Sakiyalak, Pranya, Salazar, Leonardo, Sales, Gabriele, Sallaberry, Stéphane, Gandonniere, Charlotte Salmon, Salvator, Hélène, Sanchez, Emely, Sanchez, Olivier, Sanchez-Miralles, Angel, Sancho-Shimizu, Vanessa, Sandhu, Gyan, Sandhu, Zulfiqar, Sandrine, Pierre-François, Sandulescu, Oana, Santos, Marlene, Sarfo-Mensah, Shirley, Sarmiento, Iam Claire E., Sarton, Benjamine, Satyapriya, Sree, Satyawati, Rumaisah, Saviciute, Egle, Saw, Yen Tsen, Schaffer, Justin, Schermer, Tjard, Scherpereel, Arnaud, Schneider, Marion, Schroll, Stephan, Schwameis, Michael, Scott, Janet T., Scott-Brown, James, Sedillot, Nicholas, Seitz, Tamara, Selvarajoo, Mageswari, Semaille, Caroline, Semple, Malcolm G., Senian, Rasidah Bt, Senneville, Eric, Sepulveda, Claudia, Sequeira, Filipa, Sequeira, Tânia, Neto, Ary Serpa, Balazote, Pablo Serrano, Shadowitz, Ellen, Shahidan, Syamin Asyraf, Shamsah, Mohammad, Shankar, Anuraj, Sharjeel, Shaikh, Sharma, Pratima, Shaw, Catherine A., Shaw, Victoria, Sheenan, John Robert, Shi, Haixia, Shime, Nobuaki, Shimizu, Hiroaki, Shimizu, Keiki, Shum, Hoi Ping, Mohammed, Nassima Si, Siang, Ng Yong, Sibiude, Jeanne, Siddiqui, Atif, Sigfrid, Louise, Sillaots, Piret, Silva, Catarina, Silva, Rogério, Silva, Maria Joao, Lim Heng, Benedict Sim, Sin, Wai Ching, Singh, Punam, Singh, Budha Charan, Sitompul, Pompini Agustina, Sivam, Karisha, Skogen, Vegard, Smith, Sue, Smood, Benjamin, Smyth, Coilin, Smyth, Michelle, Snacken, Morgane, So, Dominic, Soh, Tze Vee, Solomon, Joshua, Solomon, Tom, Somers, Emily, Sommet, Agnès, Song, Rima, Song, Myung Jin, Song, Tae, Chia, Jack Song, Sotto, Albert, Soum, Edouard, Sousa, Marta, Sousa, Ana Chora, Uva, Maria Sousa, Souza-Dantas, Vicente, Sperry, Alexandra, Spinuzza, Elisabetta, Sriskandan, Shiranee, Stabler, Sarah, Staudinger, Thomas, Stecher, Stephanie-Susanne, Steinsvik, Trude, Stienstra, Ymkje, Stiksrud, Birgitte, Stolz, Eva, Stone, Amy, Streinu-Cercel, Adrian, Streinu-Cercel, Anca, Stuart, Ami, Stuart, David, Su, Richa, Subekti, Decy, Suen, Gabriel, Suen, Jacky Y., Sukumar, Prasanth, Sultana, Asfia, Summers, Charlotte, Supic, Dubravka, Suppiah, Deepashankari, Surovcová, Magdalena, Svistunov, Suwarti, Andrey, Syahrin, Sarah, Syrigos, Konstantinos, Sztajnbok, Jaques, Szuldrzynski, Konstanty, Tabrizi, Shirin, Taccone, Fabio S., Tagherset, Lysa, Taib, Shahdattul Mawarni, Taleb, Sara, Talsma, Jelmer, Tampubolon, Maria Lawrensia, Tan, Kim Keat, Tan, Yan Chyi, Tanaka, Hiroyuki, Tanaka, Taku, Taniguchi, Hayato, Tardivon, Coralie, Tattevin, Pierre, Taufik, M Azhari, Tawfik, Hassan, Tedder, Richard S., Tee, Tze Yuan, Teixeira, João, Tellier, Marie-Capucine, Teoh, Sze Kye, Teotonio, Vanessa, Téoulé, François, Terpstra, Pleun, Terrier, Olivier, Terzi, Nicolas, Tessier-Grenier, Hubert, Tey, Adrian, Mohd Thabit, Alif Adlan, Tham, Zhang Duan, Thangavelu, Suvintheran, Theron, Elmi, Thibault, Vincent, Thiberville, Simon-Djamel, Thill, Benoît, Thirumanickam, Jananee, Thompson, Shaun, Thomson, David, Thomson, Emma C., Thorpe, Mathew, Thanga Thurai, Surain Raaj, Thwaites, Ryan S., Tierney, Paul, Tieroshyn, Vadim, Timashev, Peter S., Timsit, Jean-François, Tissot, Noémie, Toal, Fiona, Yang Toh, Jordan Zhien, Toki, Maria, Tonby, Kristian, Tonnii, Sia Loong, Torre, Marta, Torres, Antoni, Torres-Zevallos, Hernando, Towers, Michael, Trapani, Tony, Tromeur, Cécile, Trontzas, Ioannis, Trouillon, Tiffany, Truong, Jeanne, Tual, Christelle, Tubiana, Sarah, Tuite, Helen, Turgeon, Alexis F., Turmel, Jean-Marie, Turtle, Lance C. W., Tveita, Anders, Twardowski, Pawel, Udy, Andrew, Ullrich, Roman, Uribe, Alberto, Usman, Asad, Uyeki, Timothy M., Vajdovics, Cristinava, Val-Flores, Luís, Valran, Amélie, Van de Velde, Stijn, van den Berge, Marcel, van der Palen, Job, van der Valk, Paul, Van Der Vekens, Nicky, Van der Voort, Peter, Van Der Werf, Sylvie, van Gulik, Laura, Van Hattem, Jarne, van Netten, Carolien, van Veen, Ilonka, Vanel, Noémie, Vanoverschelde, Henk, Varghese, Pooja, Varrone, Michael, Vasudayan, Shoban Raj, Vauchy, Charline, Veeran, Shaminee, Veislinger, Aurélie, Vencken, Sebastian, Ventura, Sara, Verbon, Annelies, Vidal, José Ernesto, Vieira, César, Villanueva, Joy Ann, Villoldo, Andrea, Visseaux, Benoit, Vitiello, Chiara, Vonkeman, Harald, Vuotto, Fanny, Wahab, Noor Hidayu, Wahab, Suhaila Abdul, Wahid, Nadirah Abdul, Walsh, Laura, Wang, Chih-Hsien, Webb, Steve, Wei, Jia, Wen, Tan Pei, Wesselius, Sanne, Wham, Murray, Whelan, Bryan, White, Nicole, Wicky, Paul Henri, Wiedemann, Aurélie, Wijaya, Surya Otto, Wille, Keith, Willems, Sue, Williams, Bailey, Williams, Virginie, Williams, Patricia J., Wils, Evert-Jan, Wittman, Jessica, Wong, Calvin, Wong, Xin Ci, Wong, Yew Sing, Wong, Teck Fung, Xian, Gan Ee, Xian, Lim Saio, Kuan, Pei Xuan, Xynogalas, Ioannis, Binti Mohd Yakop, Siti Rohani, Yamazaki, Masaki, Yarad, Elizabeth, Yazdanpanah, Yazdan, Liang Hing, Nicholas Yee, Yelnik, Cécile, Yeoh, Chian Hui, Yerkovich, Stephanie, Yokoyama, Toshiki, Yonis, Hodane, Yousif, Obada, Zaaqoq, Akram, Zabbe, Marion, Zahid, Masliza, Zahran, Maram, Binti Zaidan, Nor Zaila, Zambon, Maria, Zambrano, Miguel, Zanella, Alberto, Zaynah, Nurul, Zayyad, Hiba, Zoufaly, Alexander, Zucman, David, Wainstein, Marina, Spyrison, Nichola, Dai, Danyang, Ghadimi, Moji, Chavez-Iniquez, Jonathan Samuel, Rizo Topete, Lilia María, Citarella, Barbara Wanjiru, Merson, Laura, Pole, Jason, Claure-Del Granado, Rolando, Johnson, David W., Shrapnel, Sally, Abdukahil, heryl Ann, Abdulkadir, Nurul Najmee, Abe, Ryuzo, Abel, Laurent, Abrous, Amal, Absil, Lara, Acker, Andrew, Adachi, Shingo, Adrião, Diana, Al Ageel, Saleh, Ahmed, Shakeel, Ainscough, Kate, Airlangga, Eka, Aisa, Tharwat, Hssain, Ali Ait, Tamlihat, Younes Ait, Akimoto, Takako, Akmal, Ernita, Akwani, Chika, Al Qasim, Eman, Alalqam, Razi, Alberti, Angela, Al-dabbous, Tala, Alegesan, Senthilkumar, Alessi, Marta, Alex, Beatrice, Alexandre, Kévin, Al-Fares, Abdulrahman, Alfoudri, Huda, Ali, Imran, Alidjnou, Kazali Enagnon, Aliudin, Jeffrey, Alkhafajee, Qaba, Allavena, Clotilde, Allou, Nathalie, Alves, João, Alves, Rita, Alves, João Melo, Cabrita, Joana Alve, Amaral, Maria, Amira, Nur, Ampaw, Phoebe, Andini, Roberto, Andréjak, Claire, Angheben, Andrea, Angoulvant, Françoi, Ansart, Séverine, Anthonidass, Sivanesen, Antonelli, Massimo, Antunes de Brito, Carlos Alexandre, Apriyana, Ardiyan, Arabi, Yaseen, Aragao, Irene, Arancibia, Francisco, Araujo, Carolline, Arcadipane, Antonio, Archambault, Patrick, Arenz, Luka, Arlet, Jean-Benoît, Arnold-Day, Christel, Arora, Lovkesh, Arora, Rakesh, Artaud-Macari, Elise, Aryal, Diptesh, Asensio, Angel, Ashraf, Muhammad, Assie, Jean Baptiste, Asyraf, Amirul, Atif, Minahel, Atique, Anika, Auchabie, Johann, Aumaitre, Hugue, Auvet, Adrien, Azemar, Laurène, Azoulay, Cecile, Bach, Benjamin, Bachelet, Delphine, Badr, Claudine, Baillie, J. Kenneth, Baird, J Kevin, Bak, Erica, Bakakos, Agamemnon, Bakar, Nazreen Abu, Bal, Andriy, Balakrishnan, Mohanaprasanth, Balan, Valeria, Bani-Sadr, Firouzé, Barbalho, Renata, Barbosa, Nicholas Yuri, Barclay, Wendy S., Barnett, Saef Umar, Barnikel, Michaela, Barrelet, Audrey, Barrigoto, Cleide, Bartoli, Marie, Baruch, Joaquín, Basmaci, Romain, Hassin Basri, Muhammad Fadhli, Battaglini, Denise, Bauer, Jule, Bautista Rincon, Diego Fernando, Beane, Abigail, Bedossa, Alexandra, Bee, Ker Hong, Begum, Husna, Behilill, Sylvie, Beishuizen, Albertu, Beljantsev, Aleksandr, Bellemare, David, Beltrame, Anna, Beltrão, Beatriz Amorim, Beluze, Marine, Benech, Nicola, Benjiman, Lionel Eric, Benkerrou, Dehbia, Bennett, Suzanne, Benny, Binny, Bento, Luí, Berdal, Jan-Erik, Bergeaud, Delphine, Bergin, Hazel, Bernal Sobrino, José Lui, Bertoli, Giulia, Bertolino, Lorenzo, Bessis, Simon, Bevilcaqua, Sybille, Bezulier, Karine, Bhatt, Amar, Bhavsar, Krishna, Bianco, Claudia, Bidin, Farah Nadiah, Singh, Moirangthem Bikram, Humaid, Felwa Bin, Bin Kamarudin, Mohd Nazlin, Bisoffi, Zeno, Bissuel, Françoi, Biston, Patrick, Bitker, Laurent, Bitton, Jonathan, Blanco-Schweizer, Pablo, Blier, Catherine, Bloos, Frank, Blot, Mathieu, Blumberg, Lucille, Boccia, Filomena, Bodenes, Laetitia, Bogaert, Debby, Boivin, Anne-Hélène, Bolaños, Isabela, Bolze, Pierre-Adrien, Bompart, Françoi, Borges, Diogo, Borie, Raphaël, Botelho-Nevers, Elisabeth, Bouadma, Lila, Bouchaud, Olivier, Bouchez, Sabelline, Bouhmani, Dounia, Bouhour, Damien, Bouiller, Kévin, Bouillet, Laurence, Bouisse, Camile, Boureau, Anne-Sophie, Bourke, John, Bouscambert, Maude, Bousquet, Aurore, Bouziotis, Jason, Boxma, Bianca, Boyer-Besseyre, Marielle, Boylan, Maria, Bozza, Fernando Augusto, Braconnier, Axelle, Braga, Cynthia, Monteiro, Filipa Brá, Brazzi, Luca, Breen, Patrick, Breen, Dorothy, Brewster, David, Brickell, Kathy, Browne, Shaunagh, Brusse-Keizer, Marjolein, Bryda, Petra, Buchtele, Nina, Bugaeva, Polina, Buisson, Marielle, Burhan, Erlina, Burrell, Aidan, Bustos, Ingrid G., Butnaru, Deni, Cabie, André, Cabral, Susana, Caceres, Eder, Cadoz, Cyril, Garcês, Rui Caetano, Calligy, Kate, Calvache, Jose Andre, Camões, João, Campana, Valentine, Campbell, Paul, Campisi, Josie, Cantero, Mireia, Caraux-Paz, Pauline, Cardellino, Chiara Simona, Cardoso, Sofia, Cardoso, Filipe, Cardoso, Filipa, Cardoso, Nelson, Carelli, Simone, Carlier, Nicola, Carmoi, Thierry, Carney, Gayle, Carqueja, Inê, Carret, Marie-Christine, Carrier, François Martin, Carroll, Ida, Carson, Gail, Casanova, Maire-Laure, Cascão, Mariana, Casey, Siobhan, Casimiro, José, Cassandra, Bailey, Castanheira, Nidyanara, Castor-Alexandre, Guylaine, Castro, Ivo, Catarino, Ana, Catherine, François-Xavier, Cattaneo, Paolo, Cavalin, Roberta, Cavayas, Alexandro, Cervantes-Gonzalez, Minerva, Chair, Anissa, Chakveatze, Catherine, Chan, Adrienne, Chand, Meera, Chantalat Auger, Christelle, Chapplain, Jean-Marc, Charpentier, Charlotte, Chas, Julie, Chávez Iñiguez, Jonathan Samuel, Chen, Anjellica, Chen, Yih-Sharng, Chenard, Léo, Cheng, Matthew Pellan, Cheret, Antoine, Chiarabini, Thibault, Chica, Julian, Chidambaram, Suresh Kumar, Tho, Leong Chin, Chirouze, Catherine, Chiumello, Davide, Cho, Sung-Min, Cholley, Bernard, Chopin, Marie-Charlotte, Chow, Ting Soo, Chow, Yock Ping, Chua, Hiu Jian, Chua, Jonathan, Cidade, Jose Pedro, Ciullo, Anna, Clarke, Jennifer, Clohisey, Sara, Cobb, Perren J., Codan, Cassidy, Cody, Caitriona, Coelho, Alexandra, Coles, Megan, Coles, Jennifer, Colin, Gwenhaël, Collins, Michael, Colombo, Sebastiano Maria, Combs, Pamela, Connolly, Jennifer, Connor, Marie, Conrad, Anne, Conway, Elaine, Cooke, Graham S., Copland, Mary, Cordel, Hugue, Corley, Amanda, Cornelis, Sabine, Cornet, Alexander Daniel, Corpuz, Arianne Joy, Cortegiani, Andrea, Corvaisier, Grégory, Couffignal, Camille, Couffin-Cadiergues, Sandrine, Courtois, Roxane, Cousse, Stéphanie, Croonen, Sabine, Crowl, Gloria, Crump, Jonathan, Cruz, Claudina, Cruz Bermúdez, Juan Lui, Rojo, Jaime Cruz, Csete, Marc, Cullen, Ailbhe, Curley, Gerard, Curlier, Elodie, Curran, Colleen, Custodio, Paula, da Silva Filipe, Ana, Da Silveira, Charlene, Dabaliz, Al-Awwab, Dagens, Andrew, Dahly, Darren, Dalton, Heidi, Dalton, Jo, Daly, Seamu, Damas, Juliana, Daneman, Nick, Daniel, Corinne, Dankwa, Emmanuelle A., Dantas, Jorge, de Loughry, Gillian, De Montmollin, Etienne, Freitas de Oliveira França, Rafael, De Rosa, Rosanna, de Silva, Thushan, de Vries, Peter, Dean, David, Debard, Alexa, DeBenedictis, Bianca, Debray, Marie-Pierre, DeCastro, Nathalie, Dechert, William, Deconninck, Lauren, Decours, Romain, Defous, Eve, Delacroix, Isabelle, Delaveuve, Eric, Delavigne, Karen, Dell'Amore, Andrea, Delmas, Christelle, Delobel, Pierre, Delsing, Corine, Demonchy, Elisa, Denis, Emmanuelle, Deplanque, Dominique, Depuydt, Pieter, Desai, Mehul, Descamps, Diane, Desvallées, Mathilde, Dewayanti, Santi, Dhanger, Pathik, Diallo, Alpha, Diamantis, Sylvain, Da Silva, Fernanda Dia, Diaz, Juan Jose, Diaz, Rodrigo, Didier, Kévin, Diehl, Jean-Luc, Dieperink, Wim, Dimet, Jérôme, Dinot, Vincent, Diop, Fara, Diouf, Alphonsine, Dishon, Yael, Djossou, Félix, Docherty, Annemarie B., Doherty, Helen, Donnelly, Maria, Donnelly, Christl A., Donohue, Sean, Donohue, Yoann, Donohue, Chloe, Doran, Peter, Dorival, Céline, D'Ortenzio, Eric, Douglas, James Joshua, Dournon, Nathalie, Downer, Triona, Downey, Joanne, Downing, Mark, Drake, Tom, Driscoll, Aoife, Dryden, Murray, Fonseca, Claudio Duarte, Dubee, Vincent, Dubos, Françoi, Ducancelle, Alexandre, Duculan, Toni, Dudman, Susanne, Duggal, Abhijit, Dunand, Paul, Dunning, Jake, Duplaix, Mathilde, Durante-Mangoni, Emanuele, Durham, Lucian, Dussol, Bertrand, Duthoit, Juliette, Duval, Xavier, Dyrhol-Riise, Anne Margarita, Ean, Sim Choon, Echeverria-Villalobos, Marco, Edwards, Eleanor, Egan, Siobhan, El Sanharawi, Mohammed, Elapavaluru, Subbarao, Elharrar, Brigitte, Eloy, Philippine, Elshazly, Tarek, Enderle, Isabelle, Endo, Tomoyuki, Eng, Chan Chee, Engelmann, Ilka, Enouf, Vincent, Epaulard, Olivier, Escher, Martina, Esperatti, Mariano, Esperou, Hélène, Santo, Catarina Espírito, Esposito-Farese, Marina, Estevão, João, Etienne, Manuel, Ettalhaoui, Nadia, Everding, Anna Greti, Evers, Mirjam, Fabre, Marc, Fabre, Isabelle, Faheem, Amna, Fahy, Arabella, Fairfield, Cameron J., Faria, Pedro, Fateena, Hanan, Fatoni, Arie Zainul, Faure, Karine, Favory, Raphaël, Fayed, Mohamed, Feely, Niamh, Feeney, Laura, Fernandes, Jorge, Fernandes, Marília Andreia, Fernandes, Susana, Ferrand, François-Xavier, Devouge, Eglantine Ferrand, Ferrão, Joana, Ferraz, Mário, Ferreira, Sílvia, Ferreira, Bernardo, Ferreira, Benigno, Ferriere, Nicola, Ficko, Céline, Figueiredo-Mello, Claudia, Fiorda, Juan, Flament, Thoma, Flanagan, Emily, Flateau, Clara, Fletcher, Tom, Florence, Aline-Marie, Florio, Letizia Lucia, Flynn, Deirdre, Foley, Jean, Fomin, Victor, Fonseca, Tatiana, Forsyth, Simon, Foster, Denise, Foti, Giuseppe, Fourn, Erwan, Fowler, Robert A., Fraher, Marianne, Franch-Llasat, Diego, Fraser, John F., Fraser, Christophe, Freire, Marcela Vieira, Ribeiro, Ana Freita, Friedrich, Caren, Fritz, Ricardo, Fry, Stéphanie, Fuentes, Nora, Fukuda, Masahiro, G, Argin, Gaborieau, Valérie, Gaci, Rostane, Gagliardi, Massimo, Gagnard, Jean-Charle, Gagneux-Brunon, Amandine, Gaião, Sérgio, Skeie, Linda Gail, Gallagher, Phil, Gamble, Carrol, Gani, Yasmin, Garan, Arthur, Garcia, Rebekha, Barrio, Noelia García, Garcia-Gallo, Esteban, Garot, Deni, Garrait, Valérie, Gault, Nathalie, Gavin, Aisling, Gavrylov, Anatoliy, Gaymard, Alexandre, Gebauer, Johanne, Geraud, Eva, Morlaes, Louis Gerbaud, Germano, Nuno, Ghosn, Jade, Giani, Marco, Gibson, Je, Gigante, Tristan, Gilg, Morgane, Gilroy, Elaine, Giordano, Guillermo, Girvan, Michelle, Gissot, Valérie, Glikman, Daniel, Glybochko, Petr, Gnall, Eric, Goehringer, Françoi, Goffard, Jean-Christophe, Goh, Jin Yi, Golob, Jonathan, Gominet, Marie, Gonzalez, Alicia, Gordon, Patricia, Gorenne, Isabelle, Gormley, Conor, Goubert, Laure, Goujard, Cécile, Goulenok, Tiphaine, Grable, Margarite, Grandin, Edward Wilson, Granier, Pascal, Grasselli, Giacomo, Green, Christopher A., Greenhalf, William, Greffe, Segolène, Grieco, Domenico Luca, Griffee, Matthew, Griffiths, Fiona, Grigoras, Ioana, Groenendijk, Albert, Gruner, Heidi, Gu, Yusing, Guedj, Jérémie, Guego, Martin, Guellec, Dewi, Guerreiro, Daniela, Guery, Romain, Guillaumot, Anne, Guilleminault, Laurent, Guimarães de Castro, Maisa, Guimard, Thoma, Haalboom, Marieke, Haber, Daniel, Habraken, Hannah, Hachemi, Ali, Hadri, Nadir, Hakak, Sheeba, Hall, Adam, Hall, Matthew, Halpin, Sophie, Hamer, Ansley, Hamers, Raph L., Hamidfar, Rebecca, Hammond, Terese, Hammond, Naomi, Han, Lim Yuen, Hao, Kok Wei, Hardwick, Hayley, Harrison, Ewen M., Harrison, Janet, Hartman, Alan, Hashmi, Junaid, Hayes, Ailbhe, Hays, Leanne, Heerman, Jan, Heggelund, Lar, Hendry, Ro, Hennessy, Martina, Hentzien, Maxime, Hernandez, Diana, Hershey, Andrew, Hesstvedt, Liv, Higgins, Eibhlin, Higgins, Dawn, Higgins, Rupert, Hinchion, Rita, Hinton, Samuel, Hiraiwa, Hiroaki, Hitoto, Hikombo, Ho, Antonia, Ho, Yi Bin, Hoctin, Alexandre, Hoffmann, Isabelle, Hoh, Wei Han, Hoiting, Oscar, Holt, Rebecca, Holter, Jan Cato, Horby, Peter, Hoshino, Kota, Houas, Ikram, Hough, Catherine L., Houltham, Stuart, Ming-Yang Hsu, Jimmy, Hulot, Jean-Sébastien, Hurd, Abby, Ijaz, Samreen, Ikram, M. Arfan, Illes, Hajnal-Gabriela, Imbert, Patrick, Inácio, Hugo, Ing, Yun Sii, Ippolito, Mariachiara, Isgett, Sarah, Isidoro, Tiago, Ismail, Nadiah, Isnard, Margaux, Itai, Junji, Ivulich, Daniel, Jaafar, Danielle, Jaafoura, Salma, Jabot, Julien, Jackson, Clare, Jaquet, Pierre, Jassat, Waasila, Jaud-Fischer, Coline, Jaureguiberry, Stéphane, Jego, Florence, Jelani, Anilawati Mat, Jenum, Synne, Joe, Ong Yiaw, Jorge García, Ruth N., Joseph, Mark, Joseph, Cédric, Jourdain, Mercé, Jouvet, Philippe, Jung, Anna, Juzar, Dafsah, Kafif, Ouifiya, Kaguelidou, Florentia, Kaisbain, Neerusha, Kaleesvran, Thavamany, Kali, Sabina, Kalomoiri, Smaragdi, Ayadi Kamaluddin, Muhammad Aisar, Che Kamaruddin, Zul Amali, Kamarudin, Nadiah, Kandamby, Darshana Hewa, Kandel, Chri, Kang, Kong Yeow, Karpayah, Pratap, Kartsonaki, Christiana, Kasugai, Daisuke, Kataria, Anant, Katz, Kevin, Kaur, Aasmine, Kay, Christy, Kayyali, Lamee, Keating, Seán, Kelly, Claire, Kelly, Yvelynne, Kelly, Andrea, Kelly, Niamh, Kelly, Aoife, Kelly, Sadie, Kelsey, Maeve, Kennedy, Ryan, Kennon, Kalynn, Kernan, Maeve, Kerroumi, Youne, Keshav, Sharma, Khalid, Imrana, Khalil, Antoine, Khan, Coralie, Khan, Irfan, Kho, Michelle E., Khoo, Saye, Khoo, Ryan, Khoo, Denisa, Kiat, Khor How, Kida, Yuri, Kiiza, Peter, Granerud, Beathe Kiland, Kildal, Anders Benjamin, Kim, Jae Burm, Kimmoun, Antoine, Kitamura, Nobuya, Klenerman, Paul, Klont, Rob, Bekken, Gry Kloumann, Knight, Stephen R., Komatsu, Mamoru, Korten, Volkan, Kpangon, Arsène, Krawczyk, Karolina, Krishnan, Sudhir, Krishnan, Vinothini, Kruglova, Oksana, Kumar, Deepali, Kumar, Ganesh, Tirupakuzhi Vijayaraghavan, Bharath Kumar, Vecham, Pavan Kumar, Kuriakose, Dinesh, Kurtzman, Ethan, Kutsogiannis, Demetrio, Kutsyna, Galyna, Kyriakoulis, Konstantino, Lachatre, Marie, Lacoste, Marie, Laffey, John G., Lafhej, Nadhem, Lagrange, Marie, Laine, Fabrice, Lairez, Olivier, Lalueza, Antonio, Lambert, Marc, Langelot-Richard, Marie, Langlois, Vincent, Lantang, Eka Yudha, Lanza, Marina, Laouénan, Cédric, Laribi, Samira, Lariviere, Delphine, Lasry, Stéphane, Launay, Odile, Laureillard, Didier, Lavie-Badie, Yoan, Law, Andy, Lawrence, Teresa, Lawrence, Cassie, Le, Minh, Le Bihan, Clément, Le Bris, Cyril, Le Falher, George, Le Fevre, Lucie, Le Hingrat, Quentin, Le Maréchal, Marion, Le Mestre, Soizic, Le Moal, Gwenaël, Le Moing, Vincent, Le Nagard, Hervé, Le Turnier, Paul, Lee, Todd C., Lee, Su Hwan, Lee, Jame, Lee, Jennifer, Lee, Heng Gee, Lee, Biing Horng, Lee, Yi Lin, Leeming, Gary, Lefebvre, Laurent, Lefebvre, Bénédicte, Lefèvre, Benjamin, LeGac, Sylvie, Lelievre, Jean-Daniel, Lellouche, Françoi, Lemaignen, Adrien, Lemee, Véronique, Lemeur, Anthony, Lemmink, Gretchen, Lene, Ha Sha, Leone, Michela, Leone, Marc, Lepiller, Quentin, Lescure, François-Xavier, Lesens, Olivier, Lesouhaitier, Mathieu, Lester-Grant, Amy, Letrou, Sophie, Levy, Yve, Levy, Bruno, Levy-Marchal, Claire, L'Her, Erwan, Bassi, Gianluigi Li, Liang, Janet, Liegeon, Geoffrey, Lim, Wei Shen, Lim, Kah Chuan, Lima, Chantre, Lina, Bruno, Lina, Lim, Lind, Andrea, Lingas, Guillaume, Lion-Daolio, Sylvie, Liu, Keibun, Livrozet, Marine, Lizotte, Patricia, Lolong, Navy, Loon, Leong Chee, Lopes, Diogo, Lopez-Colon, Dalia, Loschner, Anthony L., Loubet, Paul, Loufti, Bouchra, Louis, Guillame, Lourenco, Silvia, Low, Lee, Lowik, Marije, Loy, Jia Shyi, Lucet, Jean Christophe, Bermejo, Carlos Lumbrera, Luna, Carlos M., Lungu, Olguta, Lunn, Mile, Luong, Liem, Luque, Nestor, Luton, Dominique, Lyons, Ruth, Maasikas, Olavi, Mabiala, Oryane, Machado, Sara, Machado, Moïse, Macheda, Gabriel, Madiha, Hashmi, Maestro de la Calle, Guillermo, Mahieu, Rafael, Mahy, Sophie, Maier, Lars S., Maillet, Mylène, Maitre, Thoma, Malfertheiner, Maximilian, Malik, Nadia, Mallon, Paddy, Malvy, Deni, Manda, Victoria, Mandelbrot, Laurent, Manetta, Frank, Mankikian, Julie, Manning, Edmund, Manuel, Aldric, Sant`Ana Malaque, Ceila Maria, Marino, Flávio, Markowicz, Samuel, Marques, Ana, Marsh, Brian, Marsh, Laura, Marshal, Megan, Marshall, John, Martelli, Celina Turchi, Martin, Emily, Martin-Blondel, Guillaume, Martinez, F. Eduardo, Martin-Loeches, Ignacio, Martinot, Martin, Martins, João, Martins, Ana, Rego, Caroline Martin, Martucci, Gennaro, Martynenko, Olga, Marwali, Eva Miranda, Marzukie, Marsilla, Maslove, David, Mason, Sabina, Mat Nor, Mohd Basri, Matan, Moshe, Mathieu, Daniel, Mattei, Mathieu, Maulin, Laurence, Maxwell, Michael, Mazzoni, Thierry, Sweeney, Lisa Mc, McArthur, Colin, McCanny, Peter, McCarthy, Anne, McCarthy, Aine, McCloskey, Colin, McConnochie, Rachael, McDermott, Sherry, McDonald, Sarah E., McElroy, Aine, McElwee, Samuel, McEneany, Victoria, McEvoy, Natalie, McGeer, Allison, McKay, Chri, McKeown, Johnny, McLean, Kenneth A., McNicholas, Bairbre, McPartlan, Elaine, Meaney, Edel, Mear-Passard, Cécile, Mechlin, Maggie, Mehkri, Omar, Mele, Ferruccio, Menon, Kusum, Mentré, France, Mentzer, Alexander J., Mercier, Noémie, Mercier, Emmanuelle, Merckx, Antoine, Mergeay-Fabre, Mayka, Mergler, Blake, Mesquita, António, Metwally, Osama, Meybeck, Agnè, Meyer, Dan, Meynert, Alison M., Meysonnier, Vanina, Meziane, Amina, Mezidi, Mehdi, Michelanglei, Céline, Michelet, Isabelle, Mihelis, Efstathia, Mihnovit, Vladislav, Miller, Jennene, Misnan, Nor Arisah, Mohamed, Tahira Jamal, Eliza Mohamed, Nik Nur, Moin, Asma, Molinos, Elena, Molloy, Brenda, Monahan, Sinead, Mone, Mary, Monteiro, Agostinho, Montes, Claudia, Montrucchio, Giorgia, Moore, Shona C., Moore, Sarah, Cely, Lina Morale, Moro, Lucia, Motherway, Catherine, Motos, Ana, Mouquet, Hugo, Perrot, Clara Mouton, Moyet, Julien, Mudara, Caroline, Muh, Ng Yong, Muhamad, Dzawani, Mullaert, Jimmy, Müller, Fredrik, Müller, Karl Erik, Munblit, Daniel, Murphy, Aisling, Murphy, Lorna, Murray, Patrick, Murris, Marlène, Murthy, Sriniva, Musaab, Himed, Muyandy, Gugapriyaa, Myrodia, Dimitra Melia, Nagpal, Dave, Nagrebetsky, Alex, Narasimhan, Mangala, Narayanan, Nageswaran, Neant, Nadège, Necsoi, Coca, Nekliudov, Nikita, Neto, Raul, Neumann, Emily, Ng, Pauline Yeung, Ng, Wing Yiu, Nghi, Anthony, Nguyen, Duc, Choileain, Orna Ni, Leathlobhair, Niamh Ni, Nichol, Alistair D., Nitayavardhana, Prompak, Nonas, Stephanie, Mohd Noordin, Nurul Amani, Noret, Marion, Izzati Norharizam, Nurul Faten, Norman, Lisa, Notari, Alessandra, Noursadeghi, Mahdad, Nseir, Saad, Nusantara, Dwi Utomo, Nyamankolly, Elsa, Brien, Fionnuala O., Callaghan, Annmarie O., O'Callaghan, Annmarie, Occhipinti, Giovanna, OConnor, Derbrenn, Ogura, Takayuki, O'Halloran, Sophie, O'Hearn, Katie, Ohshimo, Shinichiro, Oliveira, João, Olliaro, Piero L., O'Neil, Conar, Ong, David S.Y., Ong, Jee Yan, Oosthuyzen, Wilna, Opavsky, Anne, Openshaw, Peter, Orozco-Chamorro, Claudia Milena, Ortoleva, Jamel, Osatnik, Javier, O'Shea, Linda, O'Sullivan, Miriam, Othman, Siti Zubaidah, Ouamara, Nadia, Ouissa, Rachida, Oziol, Eric, Pagadoy, Maïder, Pages, Justine, Palmarini, Massimo, Panarello, Giovanna, Panda, Prasan Kumar, Pang, Lai Hui, Panigada, Mauro, Pansu, Nathalie, Papadopoulos, Aurélie, Parke, Rachael, Pasquier, Jérémie, Pastene, Bruno, Patauner, Fabian, Pathmanathan, Mohan Da, Patricio, Patricia, Patrier, Juliette, Patterson, Lisa, Paul, Mical, Paul, Christelle, Paulos, Jorge, Paxton, William A., Payen, Jean-Françoi, Peake, Sandra L., Peariasamy, Kalaiarasu, Jiménez, Miguel Pedrera, Peek, Giles J., Peelman, Florent, Peiffer-Smadja, Nathan, Peigne, Vincent, Pejkovska, Mare, Pelosi, Paolo, Peltan, Ithan D., Pereira, Rui, Perez, Daniel, Periel, Lui, Perpoint, Thoma, Pesenti, Antonio, Pestre, Vincent, Petrou, Lenka, Petrovic, Michele, Petrov-Sanchez, Ventzislava, Pettersen, Frank Olav, Peytavin, Gille, Pharand, Scott, Piagnerelli, Michael, Picard, Walter, Picone, Olivier, Pierobon, Carola, Piersma, Djura, Pimentel, Carlo, Piquard, Valentine, Pires, Catarina, Pironneau, Isabelle, Piroth, Lionel, Pitaloka, Ayodhia, Piubelli, Chiara, Pius, Riinu, Plantier, Laurent, Png, Hon Shen, Poissy, Julien, Pokeerbux, Ryadh, Poli, Sergio, Pollakis, Georgio, Ponscarme, Diane, Porto, Diego Basto, Post, Andra-Mari, Postma, Douwe F., Povoa, Pedro, Póvoas, Diana, Powis, Jeff, Prapa, Sofia, Preau, Sébastien, Prebensen, Christian, Preiser, Jean-Charle, Prinssen, Anton, Proença, Lucia, Pudota, Sravya, Puéchal, Oriane, Semedi, Bambang Pujo, Purcell, Gregory, Quesada, Luisa, González, Víctor Quiró, Quist-Paulsen, Else, Quraishi, Mohammed, Qutishat, Fadi, Rabaud, Christian, Rafael, Aldo, Rafiq, Marie, Rahardjani, Mutia, Rahimi, Amir Kamel, Rahman, Rozanah Abd, Haji Ab Rahman, Ahmad Kashfi, Rainieri, Fernando, Rajahram, Giri Shan, Ramakrishnan, Nagarajan, Ramalho, José, Ramli, Ahmad Afiq, Rammaert, Blandine, Ramos, Grazielle Viana, Ranjan, Ritika, Rapp, Christophe, Rasmin, Menaldi, Rätsep, Indrek, Ravi, Tharmini, Real, Andre, Rebaudet, Stanisla, Redl, Sarah, Reeve, Brenda, Reid, Liadain, Reikvam, Dag Henrik, Reis, Renato, Remy, Martine, Ren, Hongru, Resseguier, Anne-Sophie, Revest, Matthieu, Rewa, Oleksa, Reyes, Tiago, Reyes, Luis Felipe, Ribeiro, Maria Ine, Richardson, David, Richardson, Denise, Richier, Laurent, Atikah Ahmad Ridzuan, Siti Nurul, Rios, Ana L., Rishu, Asgar, Rispal, Patrick, Risso, Karine, Rizer, Nichola, Robba, Chiara, Roberto, André, Roberts, Stephanie, Robertson, David L., Robineau, Olivier, Roche-Campo, Ferran, Rodari, Paola, Rodeia, Simão, Roessler, Bernhard, Roger, Pierre-Marie, Rojek, Amanda, Romaru, Juliette, Roncon-Albuquerque, Roberto, Roriz, Mélanie, Rosa-Calatrava, Manuel, Rose, Michael, Rosenberger, Dorothea, Rossanese, Andrea, Rossetti, Matteo, Rossignol, Bénédicte, Rossignol, Patrick, Rousset, Stella, Roy, Carine, Roze, Benoît, Russell, Clark D., Ryan, Maria, Ryan, Maeve, Ryckaert, Steffi, Holten, Aleksander Rygh, Saba, Isabela, Sadat, Musharaf, Sahraei, Valla, Saint-Gilles, Maximilien, Sakiyalak, Pranya, Salazar, Leonardo, Sales, Gabriele, Sallaberry, Stéphane, Gandonniere, Charlotte Salmon, Salvator, Hélène, Sanchez, Emely, Sanchez, Olivier, Sanchez-Miralles, Angel, Sancho-Shimizu, Vanessa, Sandhu, Gyan, Sandhu, Zulfiqar, Sandrine, Pierre-Françoi, Sandulescu, Oana, Santos, Marlene, Sarfo-Mensah, Shirley, Sarmiento, Iam Claire E., Sarton, Benjamine, Satyapriya, Sree, Satyawati, Rumaisah, Saviciute, Egle, Saw, Yen Tsen, Schaffer, Justin, Schermer, Tjard, Scherpereel, Arnaud, Schneider, Marion, Schroll, Stephan, Schwameis, Michael, Scott, Janet T., Scott-Brown, Jame, Sedillot, Nichola, Seitz, Tamara, Selvarajoo, Mageswari, Semaille, Caroline, Semple, Malcolm G., Senian, Rasidah Bt, Senneville, Eric, Sepulveda, Claudia, Sequeira, Filipa, Sequeira, Tânia, Neto, Ary Serpa, Balazote, Pablo Serrano, Shadowitz, Ellen, Shahidan, Syamin Asyraf, Shamsah, Mohammad, Shankar, Anuraj, Sharjeel, Shaikh, Sharma, Pratima, Shaw, Catherine A., Shaw, Victoria, Sheenan, John Robert, Shi, Haixia, Shime, Nobuaki, Shimizu, Hiroaki, Shimizu, Keiki, Shum, Hoi Ping, Mohammed, Nassima Si, Siang, Ng Yong, Sibiude, Jeanne, Siddiqui, Atif, Sigfrid, Louise, Sillaots, Piret, Silva, Catarina, Silva, Rogério, Silva, Maria Joao, Lim Heng, Benedict Sim, Sin, Wai Ching, Singh, Punam, Singh, Budha Charan, Sitompul, Pompini Agustina, Sivam, Karisha, Skogen, Vegard, Smith, Sue, Smood, Benjamin, Smyth, Coilin, Smyth, Michelle, Snacken, Morgane, So, Dominic, Soh, Tze Vee, Solomon, Joshua, Solomon, Tom, Somers, Emily, Sommet, Agnè, Song, Rima, Song, Myung Jin, Song, Tae, Chia, Jack Song, Sotto, Albert, Soum, Edouard, Sousa, Marta, Sousa, Ana Chora, Uva, Maria Sousa, Souza-Dantas, Vicente, Sperry, Alexandra, Spinuzza, Elisabetta, Sriskandan, Shiranee, Stabler, Sarah, Staudinger, Thoma, Stecher, Stephanie-Susanne, Steinsvik, Trude, Stienstra, Ymkje, Stiksrud, Birgitte, Stolz, Eva, Stone, Amy, Streinu-Cercel, Adrian, Streinu-Cercel, Anca, Stuart, Ami, Stuart, David, Su, Richa, Subekti, Decy, Suen, Gabriel, Suen, Jacky Y., Sukumar, Prasanth, Sultana, Asfia, Summers, Charlotte, Supic, Dubravka, Suppiah, Deepashankari, Surovcová, Magdalena, Svistunov, Suwarti, Andrey, Syahrin, Sarah, Syrigos, Konstantino, Sztajnbok, Jaque, Szuldrzynski, Konstanty, Tabrizi, Shirin, Taccone, Fabio S., Tagherset, Lysa, Taib, Shahdattul Mawarni, Taleb, Sara, Talsma, Jelmer, Tampubolon, Maria Lawrensia, Tan, Kim Keat, Tan, Yan Chyi, Tanaka, Hiroyuki, Tanaka, Taku, Taniguchi, Hayato, Tardivon, Coralie, Tattevin, Pierre, Taufik, M Azhari, Tawfik, Hassan, Tedder, Richard S., Tee, Tze Yuan, Teixeira, João, Tellier, Marie-Capucine, Teoh, Sze Kye, Teotonio, Vanessa, Téoulé, Françoi, Terpstra, Pleun, Terrier, Olivier, Terzi, Nicola, Tessier-Grenier, Hubert, Tey, Adrian, Mohd Thabit, Alif Adlan, Tham, Zhang Duan, Thangavelu, Suvintheran, Theron, Elmi, Thibault, Vincent, Thiberville, Simon-Djamel, Thill, Benoît, Thirumanickam, Jananee, Thompson, Shaun, Thomson, David, Thomson, Emma C., Thorpe, Mathew, Thanga Thurai, Surain Raaj, Thwaites, Ryan S., Tierney, Paul, Tieroshyn, Vadim, Timashev, Peter S., Timsit, Jean-Françoi, Tissot, Noémie, Toal, Fiona, Yang Toh, Jordan Zhien, Toki, Maria, Tonby, Kristian, Tonnii, Sia Loong, Torre, Marta, Torres, Antoni, Torres-Zevallos, Hernando, Towers, Michael, Trapani, Tony, Tromeur, Cécile, Trontzas, Ioanni, Trouillon, Tiffany, Truong, Jeanne, Tual, Christelle, Tubiana, Sarah, Tuite, Helen, Turgeon, Alexis F., Turmel, Jean-Marie, Turtle, Lance C.W., Tveita, Ander, Twardowski, Pawel, Udy, Andrew, Ullrich, Roman, Uribe, Alberto, Usman, Asad, Uyeki, Timothy M., Vajdovics, Cristinava, Val-Flores, Luí, Valran, Amélie, Van de Velde, Stijn, van den Berge, Marcel, van der Palen, Job, van der Valk, Paul, Van Der Vekens, Nicky, Van der Voort, Peter, Van Der Werf, Sylvie, van Gulik, Laura, Van Hattem, Jarne, van Netten, Carolien, van Veen, Ilonka, Vanel, Noémie, Vanoverschelde, Henk, Varghese, Pooja, Varrone, Michael, Vasudayan, Shoban Raj, Vauchy, Charline, Veeran, Shaminee, Veislinger, Aurélie, Vencken, Sebastian, Ventura, Sara, Verbon, Annelie, Vidal, José Ernesto, Vieira, César, Villanueva, Joy Ann, Villoldo, Andrea, Visseaux, Benoit, Vitiello, Chiara, Vonkeman, Harald, Vuotto, Fanny, Wahab, Noor Hidayu, Wahab, Suhaila Abdul, Wahid, Nadirah Abdul, Walsh, Laura, Wang, Chih-Hsien, Webb, Steve, Wei, Jia, Wen, Tan Pei, Wesselius, Sanne, Wham, Murray, Whelan, Bryan, White, Nicole, Wicky, Paul Henri, Wiedemann, Aurélie, Wijaya, Surya Otto, Wille, Keith, Willems, Sue, Williams, Bailey, Williams, Virginie, Williams, Patricia J., Wils, Evert-Jan, Wittman, Jessica, Wong, Calvin, Wong, Xin Ci, Wong, Yew Sing, Wong, Teck Fung, Xian, Gan Ee, Xian, Lim Saio, Kuan, Pei Xuan, Xynogalas, Ioanni, Binti Mohd Yakop, Siti Rohani, Yamazaki, Masaki, Yarad, Elizabeth, Yazdanpanah, Yazdan, Liang Hing, Nicholas Yee, Yelnik, Cécile, Yeoh, Chian Hui, Yerkovich, Stephanie, Yokoyama, Toshiki, Yonis, Hodane, Yousif, Obada, Zaaqoq, Akram, Zabbe, Marion, Zahid, Masliza, Zahran, Maram, Binti Zaidan, Nor Zaila, Zambon, Maria, Zambrano, Miguel, Zanella, Alberto, Zaynah, Nurul, Zayyad, Hiba, Zoufaly, Alexander, and Zucman, David

Subjects
acute kidney injury, covid-19, Nephrology
Abstract

Introduction Acute kidney injury (AKI) has been identified as one of the most common and significant problems in hospitalized patients with COVID-19. However, studies examining the relationship between COVID-19 and AKI in low- and low-middle income countries (LLMIC) are lacking. Given that AKI is known to carry a higher mortality rate in these countries, it is important to understand differences in this population. Methods This prospective, observational study examines the AKI incidence and characteristics of 32,210 patients with COVID-19 from 49 countries across all income levels who were admitted to an intensive care unit during their hospital stay. Results Among patients with COVID-19 admitted to the intensive care unit (ICU), AKI incidence was highest in patients in LLMIC, followed by patients in upper-middle income countries (UMIC) and high-income countries (HIC) (53%, 38%, and 30%, respectively), whereas dialysis rates were lowest among patients with AKI from LLMIC and highest among those from HIC (27% vs. 45%). Patients with AKI in LLMIC had the largest proportion of community-acquired AKI (CA-AKI) and highest rate of in-hospital death (79% vs. 54% in HIC and 66% in UMIC). The association between AKI, being from LLMIC and in-hospital death persisted even after adjusting for disease severity. Conclusions AKI is a particularly devastating complication of COVID-19 among patients from poorer nations where the gaps in accessibility and quality of healthcare delivery have a major impact on patient outcomes.

Published
2023
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20. Instruments assessing risk of bias of randomized trials frequently included items that are not addressing risk of bias issues

Author

Ying Wang, Maryam Ghadimi, Qi Wang, Liangying Hou, Dena Zeraatkar, Atiya Iqbal, Cameron Ho, Liang Yao, Malini Hu, Zhikang Ye, Rachel Couban, Susan Armijo-Olivo, Dirk Bassler, Matthias Briel, Lise Lotte Gluud, Paul Glasziou, Rod Jackson, Sheri A. Keitz, Luz M. Letelier, Philippe Ravaud, Kenneth F. Schulz, Reed A.C. Siemieniuk, Romina Brignardello-Petersen, and Gordon H. Guyatt

Subjects
Epidemiology
Abstract

To establish whether items included in instruments published in the last decade assessing risk of bias of randomized controlled trials (RCTs) are indeed addressing risk of bias.We searched Medline, Embase, Web of Science, and Scopus from 2010 to October 2021 for instruments assessing risk of bias of RCTs. By extracting items and summarizing their essential content, we generated an item list. Items that two reviewers agreed clearly did not address risk of bias were excluded. We included the remaining items in a survey in which 13 experts judged the issue each item is addressing: risk of bias, applicability, random error, reporting quality, or none of the above.Seventeen eligible instruments included 127 unique items. After excluding 61 items deemed as clearly not addressing risk of bias, the item classification survey included 66 items, of which the majority of respondents deemed 20 items (30.3%) as addressing risk of bias; the majority deemed 11 (16.7%) as not addressing risk of bias; and there proved substantial disagreement for 35 (53.0%) items.Existing risk of bias instruments frequently include items that do not address risk of bias. For many items, experts disagree on whether or not they are addressing risk of bias.

Published
2022
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23. Dysregulation of HNF1B/Clusterin axis enhances disease progression in a highly aggressive subset of pancreatic cancer patients

Author

Shouhui, Yang, Wei, Tang, Azadeh, Azizian, Jochen, Gaedcke, Philipp, Ströbel, Limin, Wang, Helen, Cawley, Yuuki, Ohara, Paloma, Valenzuela, Lin, Zhang, Trisha, Lal, Sanju, Sinha, Eythan, Rupin, Nader, Hanna, B Michael, Ghadimi, and S Perwez, Hussain

Subjects
Cancer Research, General Medicine
Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy and is largely refractory to available treatments. Identifying key pathways associated with disease aggressiveness and therapeutic resistance may characterize candidate targets to improve patient outcomes. We used a strategy of examining the tumors from a subset of PDAC patient cohorts with the worst survival to understand the underlying mechanisms of aggressive disease progression and to identify candidate molecular targets with potential therapeutic significance. Non-negative matrix factorization (NMF) clustering, using gene expression profile, revealed three patient subsets. A 142-gene signature specific to the subset with the worst patient survival, predicted prognosis and stratified patients with significantly different survival in the test and validation cohorts. Gene-network and pathway analysis of the 142-gene signature revealed dysregulation of Clusterin (CLU) in the most aggressive patient subset in our patient cohort. Hepatocyte nuclear factor 1 b (HNF1B) positively regulated CLU, and a lower expression of HNF1B and CLU was associated with poor patient survival. Mechanistic and functional analyses revealed that CLU inhibits proliferation, 3D spheroid growth, invasiveness and epithelial-to-mesenchymal transition (EMT) in pancreatic cancer cell lines. Mechanistically, CLU enhanced proteasomal degradation of EMT-regulator, ZEB1. In addition, orthotopic transplant of CLU-expressing pancreatic cancer cells reduced tumor growth in mice. Furthermore, CLU enhanced sensitivity of pancreatic cancer cells representing aggressive patient subset, to the chemotherapeutic drug gemcitabine. Taken together, HNF1B/CLU axis negatively regulates pancreatic cancer progression and may potentially be useful in designing novel strategies to attenuate disease progression in PDAC patients.

Published
2022
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29. The impact of race on utilization of durable left ventricular assist device therapy in patients with advanced heart failure

Author

Mandisa‐Maia Jones, Lisa M. McElroy, Manal Mirreh, Matthew Fuller, Rebecca Schroeder, Kamrouz Ghadimi, Adam DeVore, Chetan B. Patel, Eric Black‐Maier, Raquel Bartz, and Kevin Thomas

Subjects
Cohort Studies, Heart Failure, Pulmonary and Respiratory Medicine, Treatment Outcome, Humans, Stroke Volume, Surgery, Heart-Assist Devices, Cardiology and Cardiovascular Medicine, United States, Ventricular Function, Left, Retrospective Studies
Abstract

Heart failure affects6 million people in the United States alone and is most prevalent in Black patients who suffer the highest mortality risk. Yet prior studies have suggested that Black patients are less likely to receive advanced heart failure therapy. We hypothesized that Black patients would have decreased rates of durable left ventricular assist device (LVAD) implantation within our expansive heart failure program.A retrospective single-center cohort study was conducted at a single high-volume academic medical center. Patients between 18 and 85 years admitted with a diagnosis of cardiogenic shock or congestive heart failure between 1, 2013 and 12, 2017 with a left ventricular ejection fraction 30% and inotropic dependence or need for mechanical circulatory support were included. Patients with contraindications to durable LVAD were excluded. An adjusted logistic regression model for durable LVAD implantation within 90 days of the index admission was used to determine the effect of race on durable LVAD implantation.Among the 702 study patients (60.9% White, 34.1% Black), durable LVAD implantation was performed within 90 days of the index admission in 183 (26%) of the cohort. After multivariate analysis, Black patients were not found to have a statistically significant difference in durable LVAD implantation rates compared to White patients in our study (OR: 0.68 [95% confidence interval: 0.45-1.04; p: .074]).Black patients in our study did not have a statistically significant difference in the rate of durable LVAD implantation compared with White patients after adjustments were made for age, sex, socioeconomic, and clinical covariates. Larger prospective studies are needed to validate these findings.

Published
2022
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30. Design and Analysis of Novel Non-Reversible & Reversible Parity Generator and Detector in Quantum Cellular Automata using Feynman Gate

Author

Zhou Peng, Mehraeen Esmaeil, Jahangir Rahil, S. Kanwar Shamsher, Das Proteeti, Wei Yunlin, Wu Lijun, İlker Saygılı Eyüp, Faruk Hossen Md., Kudrat-E-Zahan Md., L. Roe Amy, Song Pengfei, Hangül Ceren, Berker Karaüzüm Sibel, Javaherian Mohammad, Lin Hao, Demir-Dora Devrim, Lv Hao, Gupta Shruti, Sobarzo-Sánchez Eduardo, Shang Junjie, Shahlaee Fatemeh, Ebrahimnejad Pedram, Rahimi Sajad, Ghadimi Maryam, Hoque Munshi Najmul, Sadeghi-Ghadi Zaynab, Ali Mahjoub Mohammad, Tripathi Neeraj, Hayati Bagher, Ebrahimi Pouneh, Qin Kunhao, Çetin Zafer, Shan Yan, Zhang Dongfang, Ma Yongkai, Maitra Subhasis, Sabatier Jean-Marc, Mudakir Fazili Mohammad, Evcili Gökhan, Najafi Zeinab, Küpeli Akkol Esra, Dao Fu-Ying, Zulfiqar Hasan, Ali Asraf Md., Dadras Omid, Ji Xiuling, Yang Hui, Cui Yinshan, Venkataraman Arvind, Zhu Jie, Chen Wei, Zakaria C. M., Wang Yi, and SeyedAlinaghi SeyedAhmad

Subjects
Physics, symbols.namesake, Design analysis, Generator (computer programming), Detector, Hardware_INTEGRATEDCIRCUITS, symbols, Feynman diagram, Parity (physics), Building and Construction, Topology, Hardware_LOGICDESIGN, Quantum cellular automaton
Abstract

Aim: A novel design for non-reversible as well as reversible parity generator and detector in Quantum-dot Cellular Automata (QCA) technology is presented in this research article. Parity generator and detector circuits are reliable error-checking components of a nano-communication system. Objective: The main focus of this research is to design an ultra-low-power fault-tolerant reversible gate implementation of the parity logic function in QCA. An efficient QCA design layout with minimal area, less latency and the least energy dissipation is desired. Methods: The proposed designs are developed using Quantum-dot Cellular Automata (QCA) technology. The circuits are optimized using majority gate reduction and clock zone reduction techniques. Also, the cell-cell interaction technique is employed to further optimize the QCA circuit. To increase the fault tolerance and ultra-low power operation, reversible QCA circuits are designed using cascaded Feynman gates. Results Conclusion: The efficiency of the parity generator and detector is calculated to be more than 25% compared to existing QCA layouts. It is demonstrated in this paper that the proposed circuits perform exceptionally well on every design parameter. The design parameters under consideration are cell count, cell area, complexity, crossover count, latency and energy dissipation. Conclusion: Using reversible logic, a fault-tolerant and defect-sensitive circuit are developed for parity generation and detection.

Published
2022
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31. Hemostatic efficacy of composite polysaccharide powder (starch-chitosan) for emergency bleeding control: An animal model study

Author

Mohsen Mardani, Hamid Reza Eftekharian, Mahmood Naseri, Seyed Mohammad Hashem Hosseini, Hamid Mohammadi, Hossein Danesteh, Niloofar Ghadimi, and Saeed Fazel

Subjects
Male, Chitosan, Hemostasis, Water, Hemorrhage, Starch, Iran, Hemostatics, Disease Models, Animal, Polysaccharides, Animals, Surgery, Rabbits, Powders
Abstract

Blood clot formation or hemostasis is vital to minimize blood loss and mitigate the risk of death from severe bleeding. This study investigates the characteristics of a novel hemostatic composite containing chemically modified chitosan and starch for emergency bleeding control. The performance of this novel hemostatic powder was compared with commercially available starch-based (Arista AH) and chitosan-based (Celox) hemostats.Hemostatic composite was prepared according to the patent registered by the authors (Patent No. 100865, Iranian Intellectual Property Organization) in Bani Zist Baspar Healda, Inc. (Shiraz, Iran). The properties of the product were surveyed by Fourier-transform infrared spectroscopy and compared with Arista-AH and Celox as commercial counterparts. The cytocompatibility, hemolysis, platelet and red blood cells (RBCs) adhesion, biocompatibility, and biodegradability attributes were evaluated in in vivo and in vitro studies. Hemostatic efficacy was evaluated in 24 healthy 6-month-old male New Zealand white rabbits in lethal and sublethal injuries of femoral artery and veins, respectively.Modification and composition led to a fundamental development in physicochemical characteristics including swelling properties, water absorption, and platelet and RBC adhesion due to improved electrostatic and hydrophilic attributes. The significant superiority in clotting efficiency was confirmed after the application of the composite in 2 models of venous and arterial injury in comparison with common commercial hemostats.Simultaneous use of water-absorbing compounds and introducing positively charged functional groups to hemostatic material led to a considerable control of femoral bleeding in emergency conditions. The introduced composite was biodegradable and biocompatible and prompts RBC aggregation and platelet adhesion.

Published
2022
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33. A sensor-less control and optimal energy management algorithm for a stand-alone photovoltaic system considering partial shading condition

Author

Amin Mirzaei, Sepehr Sheikhipour, and Ali Asghar Ghadimi

Subjects
Battery (electricity), Energy management, Computer science, Applied Mathematics, Reliability (computer networking), Photovoltaic system, Converters, Computer Science Applications, Power (physics), Reduction (complexity), Energy management system, Control and Systems Engineering, Electrical and Electronic Engineering, Instrumentation, Algorithm
Abstract

One of the most important part of a stand-alone photovoltaic system is energy management. This part uses several sensors to measure solar radiations, load power and battery energy to determine operation of the system components. Reduction the number of sensors and optimization of energy management system are two key steps to improve the efficiency and reliability of the system without additional cost. Hence, in this paper, a comprehensive energy management algorithm along with a complementary algorithm to estimate radiation under uniform and partial shading conditions is proposed. According to the system state, the energy management algorithm commands to activate/ deactivate a part or entire of photovoltaic system which can increase the system lifetime and thus increase the system reliability. Another feature of the proposed algorithm is a new mode in the absence of radiation for parallelizing and sharing the battery’s current to the load by unidirectional and bidirectional converters. Furthermore, a sensor-less complementary algorithm to determine the amount of radiation and also the partial shading condition is proposed. To prove the feasibility of the proposed algorithms, the system was simulated and constructed. The simulation and experimental results are found closely comparable and confirm the effectiveness of the proposed methods.

Published
2022
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36. Smile management: White esthetic, pink esthetic and facial attractiveness, a review of literature

Author

null Neda Tajbakhsh, null Farzaneh Delpisheh, null Nikoo Ghadimi, and null Shamim Ansari

Abstract

A smile determines whether an individual is happy, pleasant, or laughing. A delicate or pleasant smile can boost the introductory impression in socializing, which consequently increases the approval of a person in the community. Therefore, it is considered a way of communication. Smile aesthetics can be described by many factors, including teeth surrounded by upper and lower lips, the sculpting of the tissue or gums, and the total of gaps and extra spaces. The formation of a perfect smile requires the interaction of many elements with different degrees of significance. Knowledge of the concepts that describe the equilibrium betwixt the dental care provider's knowledge related to aesthetic smile and the individual's perception is necessary. The major aim of this study was to describe various esthetics and methods that contribute to the formation of a perfect smile.

Published
2022
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41. Experimental study of the effects of Vee-shaped steps on the hydrodynamic performance of planing hulls

Author

Parviz Ghadimi, Sayyed Mahdi Sajedi, and Mohammad Sheikholeslami

Subjects
Mechanical Engineering, Ocean Engineering
Abstract

Speed and stability are two essential criteria for assessment of planing hull performance. Accordingly, the effects of step shape on these vessels’ hydrodynamic performance and stability are experimentally investigated. Five different models are studied which are based on a high-speed recreational craft and are primarily the same in form and dimensions. One of these models does not have a step, two of them have transverse steps, and two other models have Vee-shaped steps. These five models all have a length of 2.64 m, a beam of 0.55 m, a deadrise angle of 24°, and weigh 86 kg. As the parent model, that is, the non-stepped model is unstable at high speeds, this study is aimed to figure out how different types of steps could prevent this kind of instability. The trim angle, resistance, and lengths of the wetted keel and wetted chine of all these models are reported at beam Froude numbers ranging from 0.43 to 3.44. First, the non-step model is investigated in towing tank tests. The optimum position for the center of gravity of this model is determined to be at a distance of 30% of the model’s length to the transom, which leads to the lowest resistance while the model still remains stable. The models with the aft-wise Vee type and fore-wise Vee type experience the lowest and highest resistance among all studied models, respectively. The steps’ performance appears to be directly related to the ventilation condition at the bottom of stepped models. It is also observed that aft-wise Vee-shaped step leads to the most severe flow separation, and the model with this type of step has the least wetted surface area compared to other studied models.

Published
2022
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42. Personalisierte Resektionsverfahren bei neuroendokrinen Neoplasien des Pankreas

Author

Florian Bösch, Michael Ghadimi, and Martin K. Angele

Subjects
Surgery
Abstract

ZusammenfassungNeuroendokrine Neoplasien des Pankreas (pNEN) haben eine steigende Inzidenz und erhalten klinisch dadurch eine immer höhere Relevanz. Neben den hormonell inaktiven pNEN gibt es die hormonproduzierenden Tumoren, und sowohl die inaktiven als auch die aktiven pNEN können entweder sporadisch oder hereditär vorkommen. Die Behandlung orientiert sich an tumorassoziierten Faktoren, aber auch an individuellen patienteneigenen Gegebenheiten. Für die Behandlung sind individuelle maßgeschneiderte Konzepte notwendig, welche die jeweiligen Faktoren und Gegebenheiten berücksichtigen.

Published
2022
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44. Predicting complicated appendicitis based on clinical findings: the role of Alvarado and Appendicitis Inflammatory Response scores

Author

F. Haak, O. Kollmar, A. Ioannidis, J. E. Slotta, M. B. Ghadimi, T. Glass, and M. von Strauss und Torney

Subjects
Cohort Studies, Acute Disease, Appendectomy, Humans, Surgery, Appendicitis, Sensitivity and Specificity, Retrospective Studies
Abstract

Purpose The pre-interventional differentiation between complicated and uncomplicated appendicitis is decisive for treatment. In the context of conservative therapy, the definitive diagnosis of uncomplicated appendicitis is mandatory. This study investigates the ability of clinical scoring systems and imaging to differentiate between the two entities. Methods This is a retrospective analysis of two cohorts from two tertiary referral centers in Switzerland and Germany. All consecutive patients underwent appendectomy between January 2008 and April 2013 (in the first cohort) or between January 2017 and June 2019 (the second cohort). Exclusion criteria did not apply as all patients found by the database search and received an appendectomy were included. Diagnostic testing and calculation of a receiver operating curve were performed to identify a cutoff for clinical scores that resulted in a minimum sensitivity of 90% to detect complicated appendicitis. The cutoff was combined with additional diagnostic imaging criteria to see if diagnostic properties could be improved. Results Nine hundred fifty-six patients were included in the analysis. Two hundred twenty patients (23%) had complicated appendicitis, and 736 patients (77%) had uncomplicated appendicitis or no inflammation. The complicated appendicitis cohort had a mean Alvarado score of 7.03 and a mean AIR of 5.21. This compared to a mean Alvarado of 6.53 and a mean AIR of 4.07 for the uncomplicated appendicitis cohort. The highest Alvarado score with a sensitivity of > 90% to detect complicated appendicitis was ≧ 5 (sensitivity = 95%, specificity 8.99%). The highest AIR score with a sensitivity of > 90% to detect complicated appendicitis was ≧ 3 (sensitivity 91.82%, specificity 18.53). The analysis showed that additional CT information did not improve the sensitivity of the proposed cut-offs. Conclusion AIR and Alvarado scores showed limited capability to distinguish between complicated and uncomplicated appendicitis even with additional imaging in this retrospective cohort. As conservative management of appendicitis needs to exclude patients with complicated disease reliably, appendectomy seems until now to remain the safest option to prevent undertreatment of this mostly benign disease.

Published
2022
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46. Unexpected recurrence and rapid progression of lacrimal gland adenoid cystic carcinoma during pregnancy: a case report

Author

Seyed Mohsen Rafizadeh, Hadi Ghadimi, Nasim Zarei Vesal, Zohreh Nozarian, and Mojgan Nikdel

Subjects
Ophthalmology
Abstract

Adenoid cystic carcinoma (ACC) is the most common malignant neoplasm involving the lacrimal glands, with high rates of recurrence and metastasis. During the pregnancy, reports of recurrence of ACC of the salivary glands and trachea have previously been published, but no lacrimal gland ACC recurrence has been reported. We present a 35-year-old woman with lacrimal gland ACC who was initially treated by surgical resection and adjunctive radiotherapy, but her cancer recurred during pregnancy, with rapid progression to cavernous sinuses and brain. Estrogen and progesterone receptors have been detected on lacrimal glands and ACCs of salivary glands. Thus, hormonal changes during pregnancy might contribute to the recurrence of ACC. However, the inherent invasive and recurrent nature of ACC could also account for the regrowth in this patient and further molecular studies can provide more accurate explanations.

Published
2022
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48. Improvement of sleep by resistant dextrin prebiotic in type 2 diabetic women coincides with attenuation of metabolic endotoxemia: involvement of gut–brain axis

Author

Sevda Saleh‐Ghadimi, Parvin Dehghan, Bahareh Sarmadi, and Parham Maleki

Subjects
Glycated Hemoglobin, Hypothalamo-Hypophyseal System, Nutrition and Dietetics, Hydrocortisone, Interleukin-6, Tumor Necrosis Factor-alpha, Interleukin-18, Pituitary-Adrenal System, Endotoxemia, Interleukin-10, Endotoxins, Prebiotics, Diabetes Mellitus, Type 2, Brain-Gut Axis, Dextrins, Quality of Life, Humans, Female, Obesity, Sleep, Agronomy and Crop Science, Biomarkers, Food Science, Biotechnology
Abstract

Resistant dextrin, as a prebiotic and functional food, may possess favorable effects in type 2 diabetes. This study was conducted to assess whether supplementation with resistant dextrin can improve sleep and quality of life in obese type 2 diabetic women.In this randomized controlled trial, female obese type 2 diabetic patients (n = 76) were randomly assigned into intervention group (n = 38) and placebo group (n = 38), and received 10 g dayIt is concluded that resistant dextrin improves sleep and QOL in obese women with type 2 diabetes. Its beneficial effects may be attributed in part to modulation of glycemia, metabolic endotoxemia and subsequently a decrease in biomarkers of inflammation and HPA axis activity. © 2022 Society of Chemical Industry.

Published
2022
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49. Effects of ad libitum Free-Choice Access to Freshly Squeezed Domestic White Asparagus Juice on Intestinal Microbiota Composition and Universal Bio-Markers of Immuno-Metabolic Homeostasis and General Health in Middle-Aged Female and Male C57BL/6 Mice

Author

Knut J. Heller, Regina Fölster-Holst, Sven Olaf Frahm, Christoph Röcken, Michael Ebsen, Wilhelm Bockelmann, Darab Ghadimi, and Andreas Schwiertz

Subjects
chemistry.chemical_classification, biology, Firmicutes, Endocrinology, Diabetes and Metabolism, Clostridium leptum, food and beverages, Butyrate, Gut flora, biology.organism_classification, medicine.disease, chemistry, medicine, Propionate, Immunology and Allergy, Asparagus, Liver function, Food science, Dysbiosis
Abstract

Background and purpose: Asparagus contains different bioactive and volatile components including pyrazines, sulphur-containing compounds, and polyphenols. Asparagus juice is a new low-calorie LAB-containing natural juice product, the usage of which is expanding. Pyrazines and sulphur-containing compounds are degraded by bacteria on one hand, but on the other hand, dietary polyphenols prevent human colorectal diseases as modulators of the composition and/or activity of gut microbiota. However, the utility of these asparagus compounds for reversal of age-associated microbial dysbiosis and the immunometabolic disorders that dysbiosis incites body inflammatory reactions was not much explored so far. Hence, using middle-aged mice, we conducted the current study to verify the effect of freshly squeezed domestic white asparagus juice on the biomarkers reflecting immuno-metabolic pathways linking age-related dysbiosis and metabolic events. Materials and Methods: Thirty-two conventional Harlan Laboratories C57BL/6 mice aged between 11-12 months were randomly divided into two groups (n=16). Mice in control group 1 received sterile tap water. Animals in group 2 had 60 days ad libitum free-choice access to sterile tap water supplemented with 5% (v/v) freshly squeezed domestic white asparagus juice. Clinical signs of general health, hydration, and inflammation were monitored daily. Caecal content samples were analysed by qPCR for microbial composition. Histology of relevant organs was carried out on day 60 after sacrificing the mice. Universal markers of metabolic- and liver function were determined in serum samples. Caecal SCFAs contents were measured using HPLC. Results: Overall, no significant differences in general health or clinical signs of inflammation between the two groups were observed. The liver to body weight ratio in asparagus juice-drank mice was lowered. The qPCR quantification showed that asparagus juice significantly decreased the caecal Clostridium coccoides group while causing an enhancement in Clostridium leptum, Firmicutes, and bifidobacterial groups as well as total caecal bacterial count. Asparagus juice significantly elevated the caecal contents of SCFAs. Enhanced SCFAs (acetate, butyrate, and propionate) in mice receiving asparagus juice, however, did coincide with altered lipid levels in plasma or changes in the abundance of relevant bacteria for acetate-, butyrate-, and propionate production. Discussion: To the best of our knowledge, this is the first study aiming at evaluating the effect of freshly squeezed German domestic white asparagus juice on universal markers of metabolic- and liver function in middle-aged mice and the role of gut microbiota in this regard. The effectiveness of asparagus juice to improve metabolism in middle-aged mice was associated with alterations in intestinal microbiota but maybe also due to uptake of higher amounts of SCFAs. Conclusion: Hence, the key signal pathways corresponding to improved immune-metabolic homeostasis will be an important research scheme in the future.

Published
2022
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50. StrainNet: Improved Myocardial Strain Analysis of Cine MRI by Deep Learning from DENSE

Author

Yu Wang, Changyu Sun, Sona Ghadimi, Daniel C. Auger, Pierre Croisille, Magalie Viallon, Kenneth Mangion, Colin Berry, Christopher M. Haggerty, Linyuan Jing, Brandon K. Fornwalt, J. Jane Cao, Joshua Cheng, Andrew D. Scott, Pedro F. Ferreira, John N. Oshinski, Daniel B. Ennis, Kenneth C. Bilchick, and Frederick H. Epstein

Subjects
Radiology, Nuclear Medicine and imaging, Original Research
Abstract

PURPOSE: To develop a three-dimensional (two dimensions + time) convolutional neural network trained with displacement encoding with stimulated echoes (DENSE) data for displacement and strain analysis of cine MRI. MATERIALS AND METHODS: In this retrospective multicenter study, a deep learning model (StrainNet) was developed to predict intramyocardial displacement from contour motion. Patients with various heart diseases and healthy controls underwent cardiac MRI examinations with DENSE between August 2008 and January 2022. Network training inputs were a time series of myocardial contours from DENSE magnitude images, and ground truth data were DENSE displacement measurements. Model performance was evaluated using pixelwise end-point error (EPE). For testing, StrainNet was applied to contour motion from cine MRI. Global and segmental circumferential strain (E(cc)) derived from commercial feature tracking (FT), StrainNet, and DENSE (reference) were compared using intraclass correlation coefficients (ICCs), Pearson correlations, Bland-Altman analyses, paired t tests, and linear mixed-effects models. RESULTS: The study included 161 patients (110 men; mean age, 61 years ± 14 [SD]), 99 healthy adults (44 men; mean age, 35 years ± 15), and 45 healthy children and adolescents (21 males; mean age, 12 years ± 3). StrainNet showed good agreement with DENSE for intramyocardial displacement, with an average EPE of 0.75 mm ± 0.35. The ICCs between StrainNet and DENSE and FT and DENSE were 0.87 and 0.72, respectively, for global E(cc) and 0.75 and 0.48, respectively, for segmental E(cc). Bland-Altman analysis showed that StrainNet had better agreement than FT with DENSE for global and segmental E(cc). CONCLUSION: StrainNet outperformed FT for global and segmental E(cc) analysis of cine MRI. Keywords: Image Postprocessing, MR Imaging, Cardiac, Heart, Pediatrics, Technical Aspects, Technology Assessment, Strain, Deep Learning, DENSE Supplemental material is available for this article. © RSNA, 2023

Published
2023
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