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2. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Author

Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L, Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, galassi, anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G, Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W, Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, and Gorgolewski, Krzysztof J.

Subjects
Quantitative Biology - Other Quantitative Biology
Abstract

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Published
2023
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5. Inter-individual and inter-regional variability of breast milk antibody reactivity to bacterial lipopolysaccharides

Author

Lisa Crone, Jens Sobek, Nicole Müller, Tanja Restin, Dirk Bassler, Daniela Paganini, Michael B. Zimmermann, Patricia Zarnovican, Françoise H. Routier, Tais Romero-Uruñuela, Luis Izquierdo, and Thierry Hennet

Subjects
glycan, O-antigen, lactation, infection, microarray, antigen mimicry, Immunologic diseases. Allergy, RC581-607
Abstract

Breast milk is a vital source of nutrients, prebiotics, probiotics, and protective factors, including antibodies, immune cells and antimicrobial proteins. Using bacterial lipopolysaccharide arrays, we investigated the reactivity and specificity of breast milk antibodies towards microbial antigens, comparing samples from rural Kenya and urban Switzerland. Results showed considerable variability in antibody reactivity both within and between these locations. Kenyan breast milk demonstrated broad reactivity to bacterial lipopolysaccharides, likely due to increased microbial exposure. Antibodies primarily recognized the O-antigens of lipopolysaccharides and showed strong binding to specific carbohydrate motifs. Notably, antibodies against specific Escherichia coli O-antigens showed cross-reactivity with parasitic pathogens like Leishmania major and Plasmodium falciparum, thus showing that antibodies reacting against lipopolysaccharide O-antigens can recognize a wide range of antigens beyond bacteria. The observed diversity in antigen recognition highlights the significance of breast milk in safeguarding infants from infections, particularly those prevalent in specific geographic regions. The findings also offer insights for potential immunobiotic strategies to augment natural antibody-mediated defense against diverse pathogens.

Published
2024
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6. Ensembling Voxel-Based and Box-Based Model Predictions for Robust Lesion Detection

Author

Debs, Noëlie, Routier, Alexandre, Abi-Nader, Clément, Marcoux, Arnaud, Bône, Alexandre, Rohé, Marc-Michel, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Wu, Shandong, editor, Shabestari, Behrouz, editor, and Xing, Lei, editor

Published
2024
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7. Two orthogonal differentiation gradients locally coordinate fruit morphogenesis

Author

Andrea Gómez-Felipe, Elvis Branchini, Binghan Wang, Marco Marconi, Hana Bertrand-Rakusová, Teodora Stan, Jérôme Burkiewicz, Stefan de Folter, Anne-Lise Routier-Kierzkowska, Krzysztof Wabnik, and Daniel Kierzkowski

Subjects
Science
Abstract

Abstract Morphogenesis requires the coordination of cellular behaviors along developmental axes. In plants, gradients of growth and differentiation are typically established along a single longitudinal primordium axis to control global organ shape. Yet, it remains unclear how these gradients are locally adjusted to regulate the formation of complex organs that consist of diverse tissue types. Here we combine quantitative live imaging at cellular resolution with genetics, and chemical treatments to understand the formation of Arabidopsis thaliana female reproductive organ (gynoecium). We show that, contrary to other aerial organs, gynoecium shape is determined by two orthogonal, time-shifted differentiation gradients. An early mediolateral gradient controls valve morphogenesis while a late, longitudinal gradient regulates style differentiation. Local, tissue-dependent action of these gradients serves to fine-tune the common developmental program governing organ morphogenesis to ensure the specialized function of the gynoecium.

Published
2024
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10. Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study

Author

Saha, Anindo, Bosma, Joeran S., Twilt, Jasper J., van Ginneken, Bram, Noordman, Constant R., Slootweg, Ivan, Roest, Christian, Fransen, Stefan J., Sunoqrot, Mohammed R.S., Bathen, Tone F., Rouw, Dennis, Immerzeel, Jos, Geerdink, Jeroen, van Run, Chris, Groeneveld, Miriam, Meakin, James, Karagöz, Ahmet, Bône, Alexandre, Routier, Alexandre, Marcoux, Arnaud, Abi-Nader, Clément, Li, Cynthia Xinran, Feng, Dagan, Alis, Deniz, Karaarslan, Ercan, Ahn, Euijoon, Nicolas, François, Sonn, Geoffrey A., Bhattacharya, Indrani, Kim, Jinman, Shi, Jun, Jahanandish, Hassan, An, Hong, Kan, Hongyu, Oksuz, Ilkay, Qiao, Liang, Rohé, Marc-Michel, Yergin, Mert, Khadra, Mohamed, Şeker, Mustafa E., Kartal, Mustafa S., Debs, Noëlie, Fan, Richard E., Saunders, Sara, Soerensen, Simon J.C., Moroianu, Stefania, Vesal, Sulaiman, Yuan, Yuan, Malakoti-Fard, Afsoun, Mačiūnien, Agnė, Kawashima, Akira, de Sousa Machadov, Ana M.M. de M.G., Moreira, Ana Sofia L., Ponsiglione, Andrea, Rappaport, Annelies, Stanzione, Arnaldo, Ciuvasovas, Arturas, Turkbey, Baris, de Keyzer, Bart, Pedersen, Bodil G., Eijlers, Bram, Chen, Christine, Riccardo, Ciabattoni, Courrech Staal, Ewout F.W., Jäderling, Fredrik, Langkilde, Fredrik, Aringhieri, Giacomo, Brembilla, Giorgio, Son, Hannah, Vanderlelij, Hans, Raat, Henricus P.J., Pikūnienė, Ingrida, Macova, Iva, Schoots, Ivo, Caglic, Iztok, Zawaideh, Jeries P., Wallström, Jonas, Bittencourt, Leonardo K., Khurram, Misbah, Choi, Moon H., Takahashi, Naoki, Tan, Nelly, Franco, Paolo N., Gutierrez, Patricia A., Thimansson, Per Erik, Hanus, Pieter, Puech, Philippe, Rau, Philipp R., de Visschere, Pieter, Guillaume, Ramette, Cuocolo, Renato, Falcão, Ricardo O., van Stiphout, Rogier S.A., Girometti, Rossano, Briediene, Ruta, Grigienė, Rūta, Gitau, Samuel, Withey, Samuel, Ghai, Sangeet, Penzkofer, Tobias, Barrett, Tristan, Tammisetti, Varaha S., Løgager, Vibeke B., Černý, Vladimír, Venderink, Wulphert, Law, Yan M., Lee, Young J., Bjartell, Anders, Padhani, Anwar R., Bonekamp, David, Villeirs, Geert, Salomon, Georg, Giannarini, Gianluca, Kalpathy-Cramer, Jayashree, Barentsz, Jelle, Maier-Hein, Klaus H., Rusu, Mirabela, Obuchowski, Nancy A., Rouvière, Olivier, van den Bergh, Roderick, Panebianco, Valeria, Kasivisvanathan, Veeru, Yakar, Derya, Elschot, Mattijs, Veltman, Jeroen, Fütterer, Jurgen J., de Rooij, Maarten, Huisman, Henkjan, Bosma, Joeran S, Twilt, Jasper J, Padhani, Anwar R, Maier-Hein, Klaus H, Obuchowski, Nancy A, and Fütterer, Jurgen J

Published
2024
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13. Immunovirological status in people with perinatal and adult-acquired HIV-1 infection: a multi-cohort analysis from FranceResearch in context

Author

Rémonie Seng, Pierre Frange, Albert Faye, Catherine Dollfus, Jérôme le Chenadec, Faroudy Boufassa, Asma Essat, Tessa Goetghebuer, Elisa Arezes, Véronique Avettand-Fènoël, Jean-Joël Bigna, Stéphane Blanche, Cécile Goujard, Laurence Meyer, Josiane Warszawski, Jean-Paul Viard, H. Aumaitre, E. Froguel, F. Caby, S. Dellion, L. Gerard, F. Lucht, C. Chirouze, M. Dupon, Jl Schmit, C. Goujard, T. Allegre, B. Cazenave, G. Hittinger, P. De Truchis, J. Cailhol, C. Duvivier, A. Canestri, O. Bouchaud, M. Karmochkine, D. Salmon-Ceron, D. Zucman, E. Mortier, R. Tubiana, P.M. Girard, C. Pintado, A. Cabie, V. Rabier, P. Morlat, D. Neau, C. Genet, D. Makhloufi, S Bregigeon Ronot, J. Ghosn, V. Reliquet, P. Perré, Jl Pellegrin, C. Arvieux, C. Cheneau, L. Bernard, P. Delobel, R. Verdon, C. Jacomet, L. Piroth, F. Ajana, S. Bevilacqua, Y. Debab, A.L. Lecapitaine, L. Cotte, S. Mokhtari, P. Mercie, P. Poubeau, V. Garrait, Ma Khuong, G. Beck-Wirth, L. Blum, S. Blanche, F. Boccara, T. Prazuck, C. Barbuat, J.P. Viard, S. Stegmann-Planchard, B. Martha, J.M. Treluyer, E. Dore, C. Gaud, M. Niault, E. Fernandes, H. Hitoto, A. Compagnucci, N. Elenga, A. Faye, C. Dollfus, A. Chace, M. Levine, S.A. Martha, C. Floch-Tudal, K. Kebaïli, N. Entz-Werle, J. Tricoire, F. Mazingue, P. Bolot, P. Brazille, T. Goetghebuer, A.F. Gennotte, D. Van Der Linden, V. Schmitz, M. Moutschen, C. Crenn-Hebert, F. Habibi, A. Coursol, E. Guesdon, P.F. Ceccaldi, M. Dehlinger – Paul, E. Pannier, V. Marcou, C. Elleau, M. Achkar, M.O. Vareil, S. Couderc, C. Routier, M.A. Bouldouyre, L. Selleret, A. Chabrol, C. Bellahcene, C. Pluchart, A. Yangui, D. Vignes, A. Alissa, A. Johnson, E. Lachassinne, A. Benbara, L. Karaoui, A. Bongain, B. Yakeu, J.L. Schmit, L. Cravello, C. Hubert, P. Faucher, D. Pinquier, C. Borie, D. Rocchi, C. Brunet-Cartier, C. Briandet, J. Brouard, A. Chalvon-Demersay, M. Rajguru, K. Billiemaz, A. Fresard, A. Moulin, P. Fialaire, L. Mesnard, E. Werner, E. Vintejoux, J. Marian, S. Ranaivojaona, F. Bissuel, M. Abdelhadi, Y. Hammou, C. Genet-Villeger, Y. Hatchuel, G. Bachelard, M. Medus, J. Dendale – Nguyen, T.S. Guimard, A. Martha, M. Rouha, P. Perfezou, L. De Saint Martin, S. Jaffuel, R. Buzele, M. Gousseff, C. Cudeville, V. Vitrat, C. Michau, G. Palenzuela, M. Driessen, B. Heller-Roussin, J.M. Labaune, B. Muanza, J. Massardier, M. Partisani, I. Hau, C. Runel-Belliard, C. Brehin, K. Kebaili, M. Lalande, M. Lagree, K. Lacombe, J.-M. Molina, J. Reynes, O. Robineau, F. Raffi, A. Becker, L. Weiss, T. Allègre, G. Pialoux, F. Souala, A. Rami, C. Katlama, A. Cabié, J.-P. Viard, F. Bastides, C. Michel, D. Salmon, J-D Le Lièvre, A. Sotto, E. Rouveix, A. Naqvi, S. Brégigeon, R. Rodet, A. Simon-Coutelier, J.-L. Esnault, R. Buzelé, A. Stein, C. Godin-Colet, G. Pichancourt, P. Caraux-Paz, M Mohseni Zadeh, L. Gérard, C. Lascaux-Cametz, L. Bodard, J.-L. Pellegrin, N. Ettahar, A. Uludag, E. Rosenthal, F. Prevoteau du Clary, S. Jaureguiberry, P. Philibert, A.-L. Lecapitaine, E. Chakvetadze, H. Champagne, V. Daneluzzi, J. Goupil de Bouillé, A. Leprêtre, I. Lamaury, I. Darasteanu, B. Abraham, D. Garipuy, J.-L. Berger, J.-L. Schmit, K. Diallo, F. Gourdon, O. Vaillant, V. Gaborieau, J. Doll, D. Quinsat, L. Geffray, J.-J. Girard, D. Houlbert, V. Perronne, E. Klement, O. Antioniotti, C. Rouzioux, V. Avettand-Fenoel, O. Lortholary, S. Boucly, A. Maignan, R. Thiebaut, L. Meyer, F. Boufassa, M.A. Charles, R. Dray-Spira, C. Legeai, V. Amon, N. Benammar, R. Seng, L. Slama, P. Bonnard, C. Chakvetadze, T. L’Yavanc, J. Capeau, C. Vigouroux, S. Fellahi, J.P. Bastard, E. Oksenhendler, J.F. Bourge, V. Bajzik, D. Sereni, C. Lascoux-Combe, O. Taulera, L.V. Dien, J. Delgado, J.M. Molina, T. Saint-Marc, S. Ferret, J. Pavie, J.F. Bergmann, M. Parrinello, BLefebvre, C. Boudraa, B. Diallo, C. Lupin, S. Herson, A. Simon, N. Edeb, L. Guillevin, T. Tahi, M.P. Pietri, D. Tisne-Dessus, C. Jalbert, P. Yeni, S. Matheron, G. Pahlavan, B. Phung, N. El-Alami Talbi, Z. Ramani, G. Catalano, C. Godard, F. Boue, V. Chambrin, D. Bornarel, H. Schoen, R. Carlier, B. Fantin, C. Poder, R. Dhote, M. Bentata, P. Honore, Xuan Tuyet, J.F. Delfraissy, F. Chaix, M.T. Rannou, Y. Levy, A. Sobel, C. Dumont, S. Abel, S. Pierre-François, V. Beaujolais, I. Poizot-Martin, O. Zaegel-Faucher, C. Debreux, J. Moreau, E. Van Der Gheynst, M.C. Thiebaut-Drobacheff, A. Foltzer, B. Hoen, J.F. Faucher, H. Gil, J.M. Ragnaud, I. Raymond, I. Louis, M. Hessamfar, V. Baillat, C Merle De Boever, C. Tramoni, A. Soufflet, P. Guadagnin, P. Choutet, O. Mounoury, D. Brosseau, H. Hue, T. May, S. Wassoumbou, M. Stenzel, M.P. Bouillon, Y. Yazdanpanah, T. Huleux, E. Aissi, S. Pavel, D. Rey, P. Fischer, G. Blaison, M. Martinot, A. Pachart, F. Jeanblanc, J.L. Touraine, C. Trepo, P. Miailhes, K. Kouadjo, V. Thoirain, C. Brochier, P. Perre, S. Leautez, J.L. Esnault, and I. Suaud

Subjects
Perinatal HIV infection, Cohort, Viral failure, Immunological outcome, Epidemiology, Public aspects of medicine, RA1-1270
Abstract

Summary: Background: No study has compared the virological and immunological status of young people with perinatally-acquired HIV infection (P-HIV) with that of people with HIV adulthood (A-HIV) having a similar duration of infection. Methods: 5 French cohorts of P-HIV and A-HIV patients with a known date of HIV-infection and receiving antiretroviral treatment (ART), were used to compare the following proportions of: virological failure (VF) defined as plasma HIV RNA ≥ 50 copies/mL, CD4 cell percentages and CD4:CD8 ratios, at the time of the most recent visit since 2012. The analysis was stratified on time since infection, and multivariate models were adjusted for demographics and treatment history. Findings: 310 P-HIV were compared to 1515 A-HIV (median current ages 20.9 [IQR:14.4–25.5] and 45.9 [IQR:37.9–53.5] respectively). VF at the time of the most recent evaluation was significantly higher among P-HIV (22.6%, 69/306) than A-HIV (3.3%, 50/1514); p ≤ 0.0001. The risk of VF was particularly high among the youngest children (2–5 years), adolescents (13–17 years) and young adults (18–24 years), compared to A-HIV with a similar duration of infection: adjusted Odds-Ratio (aOR) 7.0 [95% CI: 1.7; 30.0], 11.4 [4.2; 31.2] and 3.3 [1.0; 10.8] respectively. The level of CD4 cell percentages did not differ between P-HIV and A-HIV. P-HIV aged 6–12 and 13–17 were more likely than A-HIV to have a CD4:CD8 ratio ≥ 1: 84.1% vs. 58.8% (aOR = 3.5 [1.5; 8.3]), and 60.9% vs. 54.7% (aOR = 1.9 [0.9; 4.2]) respectively. Interpretation: P-HIV were at a higher risk of VF than A-HIV with a similar duration of infection, even after adjusting for treatment history, whereas they were not at a higher risk of immunological impairment. Exposure to viral replication among young patients living with HIV since birth or a very early age, probably because of lower adherence, could have an impact on health, raising major concerns about the selection of resistance mutations and the risk of HIV transmission. Funding: Inserm - ANRS MIE.

Published
2024
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15. Clinica: an open source software platform for reproducible clinical neuroscience studies

Author

Routier, Alexandre, Burgos, Ninon, Díaz, Mauricio, Bacci, Michael, Bottani, Simona, El-Rifai, Omar, Fontanella, Sabrina, Gori, Pietro, Guillon, Jérémy, Guyot, Alexis, Hassanaly, Ravi, Jacquemont, Thomas, Lu, Pascal, Marcoux, Arnaud, Moreau, Tristan, Samper-González, Jorge, Teichmann, Marc, Thibeau--Sutre, Elina, Vaillant, Ghislain, Wen, Junhao, Wild, Adam, Habert, Marie-Odile, Durrleman, Stanley, and Colliot, Olivier

Subjects
Quantitative Biology - Quantitative Methods
Abstract

We present Clinica (www.clinica.run), an open-source software platform designed to make clinical neuroscience studies easier and more reproducible. Clinica aims for researchers to i) spend less time on data management and processing, ii) perform reproducible evaluations of their methods, and iii) easily share data and results within their institution and with external collaborators. The core of Clinica is a set of automatic pipelines for processing and analysis of multimodal neuroimaging data (currently, T1-weighted MRI, diffusion MRI and PET data), as well as tools for statistics, machine learning and deep learning. It relies on the brain imaging data structure (BIDS) for the organization of raw neuroimaging datasets and on established tools written by the community to build its pipelines. It also provides converters of public neuroimaging datasets to BIDS (currently ADNI, AIBL, OASIS and NIFD). Processed data include image-valued scalar fields (e.g. tissue probability maps), meshes, surface-based scalar fields (e.g. cortical thickness maps) or scalar outputs (e.g. regional averages). These data follow the ClinicA Processed Structure (CAPS) format which shares the same philosophy as BIDS. Consistent organization of raw and processed neuroimaging files facilitates the execution of single pipelines and of sequences of pipelines, as well as the integration of processed data into statistics or machine learning frameworks. The target audience of Clinica is neuroscientists or clinicians conducting clinical neuroscience studies involving multimodal imaging, and researchers developing advanced machine learning algorithms applied to neuroimaging data.

Published
2021

16. Tetrahydropyridine LIMK inhibitors: Structure activity studies and biological characterization

Author

Champiré, Anthony, Berabez, Rayan, Braka, Abdennour, Cosson, Aurélie, Corret, Justine, Girardin, Caroline, Serrano, Amandine, Aci-Sèche, Samia, Bonnet, Pascal, Josselin, Béatrice, Brindeau, Pierre, Ruchaud, Sandrine, Leguevel, Rémy, Chatterjee, Deep, Mathea, Sebastian, Knapp, Stefan, Brion, Régis, Verrecchia, Franck, Vallée, Béatrice, Plé, Karen, Bénédetti, Hélène, and Routier, Sylvain

Published
2024
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17. Immunovirological status in people with perinatal and adult-acquired HIV-1 infection: a multi-cohort analysis from France

Author

Aumaitre, H., Froguel, E., Caby, F., Dellion, S., Gerard, L., Lucht, F., Chirouze, C., Dupon, M., Schmit, Jl, Goujard, C., Allegre, T., Cazenave, B., Hittinger, G., De Truchis, P., Cailhol, J., Duvivier, C., Canestri, A., Bouchaud, O., Karmochkine, M., Salmon-Ceron, D., Zucman, D., Mortier, E., Tubiana, R., Girard, P.M., Pintado, C., Cabie, A., Rabier, V., Morlat, P., Neau, D., Genet, C., Makhloufi, D., Ronot, S Bregigeon, Ghosn, J., Reliquet, V., Perré, P., Pellegrin, Jl, Arvieux, C., Cheneau, C., Bernard, L., Delobel, P., Verdon, R., Jacomet, C., Piroth, L., Ajana, F., Bevilacqua, S., Debab, Y., Lecapitaine, A.L., Cotte, L., Mokhtari, S., Mercie, P., Poubeau, P., Garrait, V., Khuong, Ma, Beck-Wirth, G., Blum, L., Blanche, S., Boccara, F., Prazuck, T., Barbuat, C., Viard, J.P., Stegmann-Planchard, S., Martha, B., Treluyer, J.M., Dore, E., Gaud, C., Niault, M., Fernandes, E., Hitoto, H., Compagnucci, A., Elenga, N., Faye, A., Dollfus, C., Chace, A., Levine, M., Martha, S.A., Floch-Tudal, C., Kebaïli, K., Entz-Werle, N., Tricoire, J., Mazingue, F., Bolot, P., Brazille, P., Goetghebuer, T., Gennotte, A.F., Van Der Linden, D., Schmitz, V., Moutschen, M., Crenn-Hebert, C., Habibi, F., Coursol, A., Guesdon, E., Ceccaldi, P.F., Dehlinger – Paul, M., Pannier, E., Marcou, V., Elleau, C., Achkar, M., Vareil, M.O., Couderc, S., Routier, C., Bouldouyre, M.A., Selleret, L., Chabrol, A., Bellahcene, C., Pluchart, C., Yangui, A., Vignes, D., Alissa, A., Johnson, A., Lachassinne, E., Benbara, A., Karaoui, L., Bongain, A., Yakeu, B., Schmit, J.L., Cravello, L., Hubert, C., Faucher, P., Pinquier, D., Borie, C., Rocchi, D., Brunet-Cartier, C., Briandet, C., Brouard, J., Chalvon-Demersay, A., Rajguru, M., Billiemaz, K., Fresard, A., Moulin, A., Fialaire, P., Mesnard, L., Werner, E., Vintejoux, E., Marian, J., Ranaivojaona, S., Bissuel, F., Abdelhadi, M., Hammou, Y., Genet-Villeger, C., Hatchuel, Y., Bachelard, G., Medus, M., Dendale – Nguyen, J., Guimard, T.S., Martha, A., Rouha, M., Perfezou, P., De Saint Martin, L., Jaffuel, S., Buzele, R., Gousseff, M., Cudeville, C., Vitrat, V., Michau, C., Palenzuela, G., Driessen, M., Heller-Roussin, B., Labaune, J.M., Muanza, B., Massardier, J., Partisani, M., Hau, I., Runel-Belliard, C., Brehin, C., Kebaili, K., Lalande, M., Lagree, M., Lacombe, K., Molina, J.-M., Reynes, J., Robineau, O., Raffi, F., Becker, A., Weiss, L., Allègre, T., Pialoux, G., Souala, F., Rami, A., Katlama, C., Cabié, A., Viard, J.-P., Bastides, F., Michel, C., Salmon, D., Lièvre, J-D Le, Sotto, A., Rouveix, E., Naqvi, A., Brégigeon, S., Rodet, R., Simon-Coutelier, A., Esnault, J.-L., Buzelé, R., Stein, A., Godin-Colet, C., Pichancourt, G., Caraux-Paz, P., Zadeh, M Mohseni, Gérard, L., Lascaux-Cametz, C., Bodard, L., Pellegrin, J.-L., Ettahar, N., Uludag, A., Rosenthal, E., Prevoteau du Clary, F., Jaureguiberry, S., Philibert, P., Lecapitaine, A.-L., Chakvetadze, E., Champagne, H., Daneluzzi, V., Goupil de Bouillé, J., Leprêtre, A., Lamaury, I., Darasteanu, I., Abraham, B., Garipuy, D., Berger, J.-L., Schmit, J.-L., Diallo, K., Gourdon, F., Vaillant, O., Gaborieau, V., Doll, J., Quinsat, D., Geffray, L., Girard, J.-J., Houlbert, D., Perronne, V., Klement, E., Antioniotti, O., Rouzioux, C., Avettand-Fenoel, V., Lortholary, O., Boucly, S., Maignan, A., Thiebaut, R., Meyer, L., Boufassa, F., Charles, M.A., Dray-Spira, R., Legeai, C., Amon, V., Benammar, N., Seng, R., Slama, L., Bonnard, P., Chakvetadze, C., L’Yavanc, T., Capeau, J., Vigouroux, C., Fellahi, S., Bastard, J.P., Oksenhendler, E., Bourge, J.F., Bajzik, V., Sereni, D., Lascoux-Combe, C., Taulera, O., Dien, L.V., Delgado, J., Molina, J.M., Saint-Marc, T., Ferret, S., Pavie, J., Bergmann, J.F., Parrinello, M., BLefebvre, Boudraa, C., Diallo, B., Lupin, C., Herson, S., Simon, A., Edeb, N., Guillevin, L., Tahi, T., Pietri, M.P., Tisne-Dessus, D., Jalbert, C., Yeni, P., Matheron, S., Pahlavan, G., Phung, B., El-Alami Talbi, N., Ramani, Z., Catalano, G., Godard, C., Boue, F., Chambrin, V., Bornarel, D., Schoen, H., Carlier, R., Fantin, B., Poder, C., Dhote, R., Bentata, M., Honore, P., Tuyet, Xuan, Delfraissy, J.F., Chaix, F., Rannou, M.T., Levy, Y., Sobel, A., Dumont, C., Abel, S., Pierre-François, S., Beaujolais, V., Poizot-Martin, I., Zaegel-Faucher, O., Debreux, C., Moreau, J., Van Der Gheynst, E., Thiebaut-Drobacheff, M.C., Foltzer, A., Hoen, B., Faucher, J.F., Gil, H., Ragnaud, J.M., Raymond, I., Louis, I., Hessamfar, M., Baillat, V., De Boever, C Merle, Tramoni, C., Soufflet, A., Guadagnin, P., Choutet, P., Mounoury, O., Brosseau, D., Hue, H., May, T., Wassoumbou, S., Stenzel, M., Bouillon, M.P., Yazdanpanah, Y., Huleux, T., Aissi, E., Pavel, S., Rey, D., Fischer, P., Blaison, G., Martinot, M., Pachart, A., Jeanblanc, F., Touraine, J.L., Trepo, C., Miailhes, P., Kouadjo, K., Thoirain, V., Brochier, C., Perre, P., Leautez, S., Esnault, J.L., Suaud, I., Seng, Rémonie, Frange, Pierre, Faye, Albert, Dollfus, Catherine, le Chenadec, Jérôme, Boufassa, Faroudy, Essat, Asma, Goetghebuer, Tessa, Arezes, Elisa, Avettand-Fènoël, Véronique, Bigna, Jean-Joël, Blanche, Stéphane, Goujard, Cécile, Meyer, Laurence, Warszawski, Josiane, and Viard, Jean-Paul

Published
2024
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21. Adaptive Consumption by Continuous Negotiation

Author

Beauprez, Ellie, Caron, Anne-Cécile, Morge, Maxime, Routier, Jean-Christophe, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Mathieu, Philippe, editor, Dignum, Frank, editor, Novais, Paulo, editor, and De la Prieta, Fernando, editor

Published
2023
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22. Automatic patient-level recognition of four Plasmodium species on thin blood smear by a real-time detection transformer (RT-DETR) object detection algorithm: a proof-of-concept and evaluation

Author

Emilie Guemas, Baptiste Routier, Théo Ghelfenstein-Ferreira, Camille Cordier, Sophie Hartuis, Bénédicte Marion, Sébastien Bertout, Emmanuelle Varlet-Marie, Damien Costa, and Grégoire Pasquier

Subjects
Plasmodium, artificial intelligence, deep learning, machine learning, object detection, YOLO, Microbiology, QR1-502
Abstract

ABSTRACTMalaria remains a global health problem, with 247 million cases and 619,000 deaths in 2021. Diagnosis of Plasmodium species is important for administering the appropriate treatment. The gold-standard diagnosis for accurate species identification remains the thin blood smear. Nevertheless, this method is time-consuming and requires highly skilled and trained microscopists. To overcome these issues, new diagnostic tools based on deep learning are emerging. This study aimed to evaluate the performances of a real-time detection transformer (RT-DETR) object detection algorithm to discriminate Plasmodium species on thin blood smear images. The algorithm was trained and validated on a data set consisting in 24,720 images from 475 thin blood smears corresponding to 2,002,597 labels. Performances were calculated with a test data set of 4,508 images from 170 smears corresponding to 358,825 labels coming from six French university hospitals. At the patient level, the RT-DETR algorithm exhibited an overall accuracy of 79.4% (135/170) with a recall of 74% (40/54) and 81.9% (95/116) for negative and positive smears, respectively. Among Plasmodium-positive smears, the global accuracy was 82.7% (91/110) with a recall of 90% (38/42), 81.8% (18/22), and 76.1% (35/46) for P. falciparum, P. malariae, and P. ovale/vivax, respectively. The RT-DETR model achieved a World Health Organization (WHO) competence level 2 for species identification. Besides, the RT-DETR algorithm may be run in real-time on low-cost devices such as a smartphone and could be suitable for deployment in low-resource setting areas lacking microscopy experts.IMPORTANCEMalaria remains a global health problem, with 247 million cases and 619,000 deaths in 2021. Diagnosis of Plasmodium species is important for administering the appropriate treatment. The gold-standard diagnosis for accurate species identification remains the thin blood smear. Nevertheless, this method is time-consuming and requires highly skilled and trained microscopists. To overcome these issues, new diagnostic tools based on deep learning are emerging. This study aimed to evaluate the performances of a real-time detection transformer (RT-DETR) object detection algorithm to discriminate Plasmodium species on thin blood smear images. Performances were calculated with a test data set of 4,508 images from 170 smears coming from six French university hospitals. The RT-DETR model achieved a World Health Organization (WHO) competence level 2 for species identification. Besides, the RT-DETR algorithm may be run in real-time on low-cost devices and could be suitable for deployment in low-resource setting areas.

Published
2024
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23. 'El héroe del otro'. Redes de interconocimiento y trayectos socioeducativos en cárceles del sur de la provincia de Santa Fe (Argentina)

Author

Maria Eva Routier

Subjects
itinerario de detención, trayectos socioeducativos, circuito penitenciario del centro-sur de Santa Fe, tácticas y estrategias, Education (General), L7-991, Special aspects of education, LC8-6691
Abstract

A partir de la elaboración de relatos biográficos, reconstruimos los trayectos socioeducativos de dos adultos privados de su libertad en instituciones penitenciarias de la provincia de Santa Fe. La noción de trayectos socioeducativos, articulada a un enfoque antropológico relacional, alude a la construcción de recorridos que, a nivel de lo vivido, incluyen tanto aspectos estructurales como la significación que estos asumen para los sujetos. Asimismo, recuperamos la categoría de trayectorias de Michel De Certeau (2007), para dar cuenta del cruce de movilidades y modalidades de acción (tácticas y estrategias) que incluyen estos itinerarios. Las dimensiones analíticas emergentes refieren a las conexiones entre las condiciones materiales, normativas, organizacionales y relacionales de los emplazamientos institucionales en los que se configuran las experiencias de los sujetos y los saberes y prácticas puestos en juego en el transcurrir de sus trayectos socioeducativos, en especial aquellos anclados en la generación de vínculos interpersonales.

Published
2024
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26. Tri-axial rubidium and helium optically pumped magnetometers for on-scalp magnetoencephalography recording of interictal epileptiform discharges: a case study

Author

Odile Feys, Pierre Corvilain, Etienne Labyt, Mahdi Mahmoudzadeh, Laura Routier, Claudine Sculier, Niall Holmes, Matthew Brookes, Serge Goldman, Rudy Romain, Sergey Mitryukovskiy, Agustin Palacios-Laloy, Denis Schwartz, Nacim Betrouni, Philippe Derambure, Fabrice Wallois, Vincent Wens, and Xavier De Tiège

Subjects
magnetoencephalography, optically pumped magnetometers, on-scalp magnetoencephalography, refractory epilepsy, focal epilepsy, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Cryogenic magnetoencephalography (MEG) enhances the presurgical assessment of refractory focal epilepsy (RFE). Optically pumped magnetometers (OPMs) are cryogen-free sensors that enable on-scalp MEG recordings. Here, we investigate the application of tri-axial OPMs [87Rb (Rb-OPM) and 4He gas (He-OPM)] for the detection of interictal epileptiform discharges (IEDs). IEDs were recorded simultaneously with 4 tri-axial Rb- and 4 tri-axial He-OPMs in a child with RFE. IEDs were identified visually, isolated from magnetic background noise using independent component analysis (ICA) and were studied following their optimal magnetic field orientation thanks to virtual sensors. Most IEDs (>1,000) were detectable by both He- and Rb-OPM recordings. IEDs were isolated by ICA and the resulting magnetic field oriented mostly tangential to the scalp in Rb-OPMs and radial in He-OPMs. Likely due to differences in sensor locations, the IED amplitude was higher with Rb-OPMs. This case study shows comparable ability of Rb-OPMs and He-OPMs to detect IEDs and the substantial benefits of triaxial OPMs to detect IEDs from different sensor locations. Tri-axial OPMs allow to maximize spatial brain sampling for IEDs detection with a limited number of sensors.

Published
2023
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27. Laboratorio Demostrativo de Energías Renovables

Author

Cecilia Dionisio, María Aneley Routier, Macarena Estefanía Saks, Luis Ignacio Silva, and Leila Luna

Subjects
comunicación de la ciencia, vocaciones científicas, brecha de género, transición energética, Communication. Mass media, P87-96, Social sciences (General), H1-99
Abstract

En este artículo se sistematiza la experiencia de un proyecto de comunicación pública de la ciencia que empleó un dispositivo desmontable: el Laboratorio Demostrativo de Energías Renovables (LaDER). El principal objetivo fue promover entre estudiantes de distintos niveles educativos las vocaciones científicas en carreras stem incorporando la perspectiva de género. Para esto, se realizaron 34 charlas en ciudades de distintas provincias argentinas de las que participaron 917 jóvenes.

Published
2023

28. Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation

Author

Wen, Junhao, Thibeau-Sutre, Elina, Diaz-Melo, Mauricio, Samper-Gonzalez, Jorge, Routier, Alexandre, Bottani, Simona, Dormont, Didier, Durrleman, Stanley, Burgos, Ninon, and Colliot, Olivier

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing, Statistics - Machine Learning
Abstract

Over 30 papers have proposed to use convolutional neural network (CNN) for AD classification from anatomical MRI. However, the classification performance is difficult to compare across studies due to variations in components such as participant selection, image preprocessing or validation procedure. Moreover, these studies are hardly reproducible because their frameworks are not publicly accessible and because implementation details are lacking. Lastly, some of these papers may report a biased performance due to inadequate or unclear validation or model selection procedures. In the present work, we aim to address these limitations through three main contributions. First, we performed a systematic literature review and found that more than half of the surveyed papers may have suffered from data leakage. Our second contribution is the extension of our open-source framework for classification of AD using CNN and T1-weighted MRI. Finally, we used this framework to rigorously compare different CNN architectures. The data was split into training/validation/test sets at the very beginning and only the training/validation sets were used for model selection. To avoid any overfitting, the test sets were left untouched until the end of the peer-review process. Overall, the different 3D approaches (3D-subject, 3D-ROI, 3D-patch) achieved similar performances while that of the 2D slice approach was lower. Of note, the different CNN approaches did not perform better than a SVM with voxel-based features. The different approaches generalized well to similar populations but not to datasets with different inclusion criteria or demographical characteristics.

Published
2019
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29. Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimers disease

Author

Wen, Junhao, Samper-Gonzalez, Jorge, Bottani, Simona, Routier, Alexandre, Burgos, Ninon, Jacquemont, Thomas, Fontanella, Sabrina, Durrleman, Stanley, Epelbaum, Stephane, Bertrand, Anne, and Colliot, Olivier

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing, Statistics - Machine Learning
Abstract

Diffusion MRI is the modality of choice to study alterations of white matter. In past years, various works have used diffusion MRI for automatic classification of AD. However, classification performance obtained with different approaches is difficult to compare and these studies are also difficult to reproduce. In the present paper, we first extend a previously proposed framework to diffusion MRI data for AD classification. Specifically, we add: conversion of diffusion MRI ADNI data into the BIDS standard and pipelines for diffusion MRI preprocessing and feature extraction. We then apply the framework to compare different components. First, FS has a positive impact on classification results: highest balanced accuracy (BA) improved from 0.76 to 0.82 for task CN vs AD. Secondly, voxel-wise features generally gives better performance than regional features. Fractional anisotropy (FA) and mean diffusivity (MD) provided comparable results for voxel-wise features. Moreover, we observe that the poor performance obtained in tasks involving MCI were potentially caused by the small data samples, rather than by the data imbalance. Furthermore, no extensive classification difference exists for different degree of smoothing and registration methods. Besides, we demonstrate that using non-nested validation of FS leads to unreliable and over-optimistic results: 0.05 up to 0.40 relative increase in BA. Lastly, with proper FR and FS, the performance of diffusion MRI features is comparable to that of T1w MRI. All the code of the framework and the experiments are publicly available: general-purpose tools have been integrated into the Clinica software package (www.clinica.run) and the paper-specific code is available at: https://github.com/aramis-lab/AD-ML., Comment: 51 pages, 5 figure and 6 tables

Published
2018

30. Design and biological evaluation of substituted 5,7-dihydro-6H-indolo[2,3-c]quinolin-6-one as novel selective Haspin inhibitors

Author

Sreenivas Avula, Xudan Peng, Xingfen Lang, Micky Tortorella, Béatrice Josselin, Stéphane Bach, Stephane Bourg, Pascal Bonnet, Frédéric Buron, Sandrine Ruchaud, Sylvain Routier, and Cleopatra Neagoie

Subjects
Indoloquinoline, Haspin kinase, docking, cell viability, Therapeutics. Pharmacology, RM1-950
Abstract

A library of substituted indolo[2,3-c]quinolone-6-ones was developed as simplified Lamellarin isosters. Synthesis was achieved from indole after a four-step pathway sequence involving iodination, a Suzuki-Miyaura cross-coupling reaction, and a reduction/lactamization sequence. The inhibitory activity of the 22 novel derivatives was assessed on Haspin kinase. Two of them possessed an IC50 of 1 and 2 nM with selectivity towards a panel of 10 other kinases including the parent kinases DYRK1A and CLK1. The most selective compound exerted additionally a very interesting cell effect on the osteosarcoma U-2 OS cell line.

Published
2022
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32. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Author

Poldrack, R, Markiewicz, C, Appelhoff, S, Ashar, Y, Auer, T, Baillet, S, Bansal, S, Beltrachini, L, Benar, C, Bertazzoli, G, Bhogawar, S, Blair, R, Bortoletto, M, Boudreau, M, Brooks, T, Calhoun, V, Castelli, F, Clement, P, Cohen, A, Cohen-Adad, J, D'Ambrosio, S, de Hollander, G, de la Iglesia-Vayá, M, de la Vega, A, Delorme, A, Devinsky, O, Draschkow, D, Duff, E, Dupre, E, Earl, E, Esteban, O, Feingold, F, Flandin, G, Galassi, A, Gallitto, G, Ganz, M, Gau, R, Gholam, J, Ghosh, S, Giacomel, A, Gillman, A, Gleeson, P, Gramfort, A, Guay, S, Guidali, G, Halchenko, Y, Handwerker, D, Hardcastle, N, Herholz, P, Hermes, D, Honey, C, Innis, R, Ioanas, H, Jahn, A, Karakuzu, A, Keator, D, Kiar, G, Kincses, B, Laird, A, Lau, J, Lazari, A, Legarreta, J, Li, A, Li, X, Love, B, Lu, H, Marcantoni, E, Maumet, C, Mazzamuto, G, Meisler, S, Mikkelsen, M, Mutsaerts, H, Nichols, T, Nikolaidis, A, Nilsonne, G, Niso, G, Norgaard, M, Okell, T, Oostenveld, R, Ort, E, Park, P, Pawlik, M, Pernet, C, Pestilli, F, Petr, J, Phillips, C, Poline, J, Pollonini, L, Raamana, P, Ritter, P, Rizzo, G, Robbins, K, Rockhill, A, Rogers, C, Rokem, A, Rorden, C, Routier, A, Saborit-Torres, J, Salo, T, Schirner, M, Smith, R, Spisak, T, Sprenger, J, Swann, N, Szinte, M, Takerkart, S, Thirion, B, Thomas, A, Torabian, S, Varoquaux, G, Voytek, B, Welzel, J, Wilson, M, Yarkoni, T, Gorgolewski, K, Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L., Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la Iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G., Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Marcantoni, Eleonora, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W., Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, Gorgolewski, Krzysztof J., Poldrack, R, Markiewicz, C, Appelhoff, S, Ashar, Y, Auer, T, Baillet, S, Bansal, S, Beltrachini, L, Benar, C, Bertazzoli, G, Bhogawar, S, Blair, R, Bortoletto, M, Boudreau, M, Brooks, T, Calhoun, V, Castelli, F, Clement, P, Cohen, A, Cohen-Adad, J, D'Ambrosio, S, de Hollander, G, de la Iglesia-Vayá, M, de la Vega, A, Delorme, A, Devinsky, O, Draschkow, D, Duff, E, Dupre, E, Earl, E, Esteban, O, Feingold, F, Flandin, G, Galassi, A, Gallitto, G, Ganz, M, Gau, R, Gholam, J, Ghosh, S, Giacomel, A, Gillman, A, Gleeson, P, Gramfort, A, Guay, S, Guidali, G, Halchenko, Y, Handwerker, D, Hardcastle, N, Herholz, P, Hermes, D, Honey, C, Innis, R, Ioanas, H, Jahn, A, Karakuzu, A, Keator, D, Kiar, G, Kincses, B, Laird, A, Lau, J, Lazari, A, Legarreta, J, Li, A, Li, X, Love, B, Lu, H, Marcantoni, E, Maumet, C, Mazzamuto, G, Meisler, S, Mikkelsen, M, Mutsaerts, H, Nichols, T, Nikolaidis, A, Nilsonne, G, Niso, G, Norgaard, M, Okell, T, Oostenveld, R, Ort, E, Park, P, Pawlik, M, Pernet, C, Pestilli, F, Petr, J, Phillips, C, Poline, J, Pollonini, L, Raamana, P, Ritter, P, Rizzo, G, Robbins, K, Rockhill, A, Rogers, C, Rokem, A, Rorden, C, Routier, A, Saborit-Torres, J, Salo, T, Schirner, M, Smith, R, Spisak, T, Sprenger, J, Swann, N, Szinte, M, Takerkart, S, Thirion, B, Thomas, A, Torabian, S, Varoquaux, G, Voytek, B, Welzel, J, Wilson, M, Yarkoni, T, Gorgolewski, K, Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L., Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la Iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G., Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Marcantoni, Eleonora, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W., Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, and Gorgolewski, Krzysztof J.

Abstract

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Published
2024

33. Two orthogonal differentiation gradients locally coordinate fruit morphogenesis

Author

Fonds de Recherche du Québec, Natural Sciences and Engineering Research Council of Canada, Comunidad de Madrid, Agencia Estatal de Investigación (España), Gómez-Felipe, Andrea [0000-0002-5647-0496], Branchini, Elvis [0000-0001-5826-7232], Wang, Binghan [0000-0003-0739-6741], Marconi, Marco [0000-0002-3457-1384], Stan, Teodora [0000-0001-6781-447X], Burkiewicz, Jérôme [0000-0001-6968-3506], de Folter, Stefan [0000-0003-4363-7274], Routier-Kierzkowska, Anne-Lise [0000-0003-0383-0811], Wabnik, Krzysztof [0000-0001-7263-0560], Kierzkowski, Daniel [0000-0002-1947-8691], Gómez-Felipe, Andrea, Branchini, Elvis, Wang, Binghan, Marconi, Marco, Bertrand-Rakusová, Hana, Stan, Teodora, Burkiewicz, Jérôme, de Folter, Stefan, Routier-Kierzkowska, Anne-Lise, Wabnik, Krzysztof, Kierzkowski, Daniel, Fonds de Recherche du Québec, Natural Sciences and Engineering Research Council of Canada, Comunidad de Madrid, Agencia Estatal de Investigación (España), Gómez-Felipe, Andrea [0000-0002-5647-0496], Branchini, Elvis [0000-0001-5826-7232], Wang, Binghan [0000-0003-0739-6741], Marconi, Marco [0000-0002-3457-1384], Stan, Teodora [0000-0001-6781-447X], Burkiewicz, Jérôme [0000-0001-6968-3506], de Folter, Stefan [0000-0003-4363-7274], Routier-Kierzkowska, Anne-Lise [0000-0003-0383-0811], Wabnik, Krzysztof [0000-0001-7263-0560], Kierzkowski, Daniel [0000-0002-1947-8691], Gómez-Felipe, Andrea, Branchini, Elvis, Wang, Binghan, Marconi, Marco, Bertrand-Rakusová, Hana, Stan, Teodora, Burkiewicz, Jérôme, de Folter, Stefan, Routier-Kierzkowska, Anne-Lise, Wabnik, Krzysztof, and Kierzkowski, Daniel

Abstract

Morphogenesis requires the coordination of cellular behaviors along developmental axes. In plants, gradients of growth and differentiation are typically established along a single longitudinal primordium axis to control global organ shape. Yet, it remains unclear how these gradients are locally adjusted to regulate the formation of complex organs that consist of diverse tissue types. Here we combine quantitative live imaging at cellular resolution with genetics, and chemical treatments to understand the formation of Arabidopsis thaliana female reproductive organ (gynoecium). We show that, contrary to other aerial organs, gynoecium shape is determined by two orthogonal, time-shifted differentiation gradients. An early mediolateral gradient controls valve morphogenesis while a late, longitudinal gradient regulates style differentiation. Local, tissue-dependent action of these gradients serves to fine-tune the common developmental program governing organ morphogenesis to ensure the specialized function of the gynoecium.

Published
2024

35. Task Bundle Delegation for Reducing the Flowtime

Author

Beauprez, Ellie, Caron, Anne Cécile, Morge, Maxime, Routier, Jean-Christophe, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Rocha, Ana Paula, editor, Steels, Luc, editor, and van den Herik, Jaap, editor

Published
2022
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36. Protective effect of obesity on survival in cancers treated with immunotherapy vanishes when controlling for type of cancer, weight loss and reduced skeletal muscle

Author

Antoun, Sami, Lanoy, Emilie, Ammari, Samy, Farhane, Siham, Martin, Lisa, Robert, Caroline, Planchard, David, Routier, Emilie, Voisin, Anne Laure, Messayke, Sabine, Champiat, Stephane, Michot, Jean Marie, Laghouati, Salim, Lambotte, Olivier, Marabelle, Aurélien, and Baracos, Vickie

Published
2023
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37. CryoEM analysis of the essential native UDP-glucose pyrophosphorylase from Aspergillus nidulans reveals key conformations for activity regulation and function

Author

Xu Han, Cecilia D'Angelo, Ainara Otamendi, Javier O. Cifuente, Elisa de Astigarraga, Borja Ochoa-Lizarralde, Martin Grininger, Francoise H. Routier, Marcelo E. Guerin, Jana Fuehring, Oier Etxebeste, and Sean R. Connell

Subjects
aspergillosis, cell wall biosynthesis, UDP-glucose pyrophosphorylases, enzyme mechanism, enzyme specificity, cryoEM, Microbiology, QR1-502
Abstract

ABSTRACT Invasive aspergillosis is one of the most serious clinical invasive fungal infections, resulting in a high case fatality rate among immunocompromised patients. The disease is caused by saprophytic molds in the genus Aspergillus, including Aspergillus fumigatus, the most significant pathogenic species. The fungal cell wall, an essential structure mainly composed of glucan, chitin, galactomannan, and galactosaminogalactan, represents an important target for the development of antifungal drugs. UDP (uridine diphosphate)-glucose pyrophosphorylase (UGP) is a central enzyme in the metabolism of carbohydrates that catalyzes the biosynthesis of UDP-glucose, a key precursor of fungal cell wall polysaccharides. Here, we demonstrate that the function of UGP is vital for Aspergillus nidulans (AnUGP). To understand the molecular basis of AnUGP function, we describe a cryoEM structure (global resolution of 3.5 Å for the locally refined subunit and 4 Å for the octameric complex) of a native AnUGP. The structure reveals an octameric architecture with each subunit comprising an N-terminal α-helical domain, a central catalytic glycosyltransferase A-like (GT-A-like) domain, and a C-terminal (CT) left-handed β-helix oligomerization domain. AnUGP displays unprecedented conformational variability between the CT oligomerization domain and the central GT-A-like catalytic domain. In combination with activity measurements and bioinformatics analysis, we unveil the molecular mechanism of substrate recognition and specificity for AnUGP. Altogether, our study not only contributes to understanding the molecular mechanism of catalysis/regulation of an important class of enzymes but also provides the genetic, biochemical, and structural groundwork for the future exploitation of UGP as a potential antifungal target. IMPORTANCE Fungi cause diverse diseases in humans, ranging from allergic syndromes to life-threatening invasive diseases, together affecting more than a billion people worldwide. Increasing drug resistance in Aspergillus species represents an emerging global health threat, making the design of antifungals with novel mechanisms of action a worldwide priority. The cryoEM structure of UDP (uridine diphosphate)-glucose pyrophosphorylase (UGP) from the filamentous fungus Aspergillus nidulans reveals an octameric architecture displaying unprecedented conformational variability between the C-terminal oligomerization domain and the central glycosyltransferase A-like catalytic domain in the individual protomers. While the active site and oligomerization interfaces are more highly conserved, these dynamic interfaces include motifs restricted to specific clades of filamentous fungi. Functional study of these motifs could lead to the definition of new targets for antifungals inhibiting UGP activity and, thus, the architecture of the cell wall of filamentous fungal pathogens.

Published
2023
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38. Reproducible evaluation of classification methods in Alzheimer's disease: framework and application to MRI and PET data

Author

Samper-González, Jorge, Burgos, Ninon, Bottani, Simona, Fontanella, Sabrina, Lu, Pascal, Marcoux, Arnaud, Routier, Alexandre, Guillon, Jérémy, Bacci, Michael, Wen, Junhao, Bertrand, Anne, Bertin, Hugo, Habert, Marie-Odile, Durrleman, Stanley, Evgeniou, Theodoros, and Colliot, Olivier

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

A large number of papers have introduced novel machine learning and feature extraction methods for automatic classification of AD. However, they are difficult to reproduce because key components of the validation are often not readily available. These components include selected participants and input data, image preprocessing and cross-validation procedures. The performance of the different approaches is also difficult to compare objectively. In particular, it is often difficult to assess which part of the method provides a real improvement, if any. We propose a framework for reproducible and objective classification experiments in AD using three publicly available datasets (ADNI, AIBL and OASIS). The framework comprises: i) automatic conversion of the three datasets into BIDS format, ii) a modular set of preprocessing pipelines, feature extraction and classification methods, together with an evaluation framework, that provide a baseline for benchmarking the different components. We demonstrate the use of the framework for a large-scale evaluation on 1960 participants using T1 MRI and FDG PET data. In this evaluation, we assess the influence of different modalities, preprocessing, feature types, classifiers, training set sizes and datasets. Performances were in line with the state-of-the-art. FDG PET outperformed T1 MRI for all classification tasks. No difference in performance was found for the use of different atlases, image smoothing, partial volume correction of FDG PET images, or feature type. Linear SVM and L2-logistic regression resulted in similar performance and both outperformed random forests. The classification performance increased along with the number of subjects used for training. Classifiers trained on ADNI generalized well to AIBL and OASIS. All the code of the framework and the experiments is publicly available at: https://gitlab.icm-institute.org/aramislab/AD-ML.

Published
2018
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39. Development and preclinical evaluation of [18F]FBVM as a new potent PET tracer for vesicular acetylcholine transporter

Author

Vercouillie, Johnny, Buron, Frédéric, Sérrière, Sophie, Rodrigues, Nuno, Gulhan, Zuhal, Chartier, Agnès, Chicheri, Gabrielle, Marzag, Hamid, Oury, Adeline, Percina, Nathalie, Bodard, Sylvie, Ben Othman, Rajah, Busson, Julie, Suzenet, Franck, Guilloteau, Denis, Marchivie, Mathieu, Emond, Patrick, Routier, Sylvain, and Chalon, Sylvie

Published
2022
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41. PET-BIDS, an extension to the brain imaging data structure for positron emission tomography

Author

Norgaard, Martin, Matheson, Granville J., Hansen, Hanne D., Thomas, Adam, Searle, Graham, Rizzo, Gaia, Veronese, Mattia, Giacomel, Alessio, Yaqub, Maqsood, Tonietto, Matteo, Funck, Thomas, Gillman, Ashley, Boniface, Hugo, Routier, Alexandre, Dalenberg, Jelle R., Betthauser, Tobey, Feingold, Franklin, Markiewicz, Christopher J., Gorgolewski, Krzysztof J., Blair, Ross W., Appelhoff, Stefan, Gau, Remi, Salo, Taylor, Niso, Guiomar, Pernet, Cyril, Phillips, Christophe, Oostenveld, Robert, Gallezot, Jean-Dominique, Carson, Richard E., Knudsen, Gitte M., Innis, Robert B., and Ganz, Melanie

Published
2022
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42. PET-BIDS, an extension to the brain imaging data structure for positron emission tomography

Author

Martin Norgaard, Granville J. Matheson, Hanne D. Hansen, Adam Thomas, Graham Searle, Gaia Rizzo, Mattia Veronese, Alessio Giacomel, Maqsood Yaqub, Matteo Tonietto, Thomas Funck, Ashley Gillman, Hugo Boniface, Alexandre Routier, Jelle R. Dalenberg, Tobey Betthauser, Franklin Feingold, Christopher J. Markiewicz, Krzysztof J. Gorgolewski, Ross W. Blair, Stefan Appelhoff, Remi Gau, Taylor Salo, Guiomar Niso, Cyril Pernet, Christophe Phillips, Robert Oostenveld, Jean-Dominique Gallezot, Richard E. Carson, Gitte M. Knudsen, Robert B. Innis, and Melanie Ganz

Subjects
Science
Abstract

The Brain Imaging Data Structure (BIDS) is a standard for organizing and describing neuroimaging datasets, serving not only to facilitate the process of data sharing and aggregation, but also to simplify the application and development of new methods and software for working with neuroimaging data. Here, we present an extension of BIDS to include positron emission tomography (PET) data, also known as PET-BIDS, and share several open-access datasets curated following PET-BIDS along with tools for conversion, validation and analysis of PET-BIDS datasets.

Published
2022
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43. Prediction of the progression of subcortical brain structures in Alzheimer's disease from baseline

Author

Bône, Alexandre, Louis, Maxime, Routier, Alexandre, Samper, Jorge, Bacci, Michael, Charlier, Benjamin, Colliot, Olivier, and Durrleman, Stanley

Subjects
Computer Science - Computer Vision and Pattern Recognition, Statistics - Machine Learning
Abstract

We propose a method to predict the subject-specific longitudinal progression of brain structures extracted from baseline MRI, and evaluate its performance on Alzheimer's disease data. The disease progression is modeled as a trajectory on a group of diffeomorphisms in the context of large deformation diffeomorphic metric mapping (LDDMM). We first exhibit the limited predictive abilities of geodesic regression extrapolation on this group. Building on the recent concept of parallel curves in shape manifolds, we then introduce a second predictive protocol which personalizes previously learned trajectories to new subjects, and investigate the relative performances of two parallel shifting paradigms. This design only requires the baseline imaging data. Finally, coefficients encoding the disease dynamics are obtained from longitudinal cognitive measurements for each subject, and exploited to refine our methodology which is demonstrated to successfully predict the follow-up visits.

Published
2017
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44. Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks

Author

Koval, Igor, Schiratti, Jean-Baptiste, Routier, Alexandre, Bacci, Michael, Colliot, Olivier, Allassonnière, Stéphanie, and Durrleman, Stanley

Subjects
Statistics - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Quantitative Biology - Neurons and Cognition, Quantitative Biology - Quantitative Methods
Abstract

We introduce a mixed-effects model to learn spatiotempo-ral patterns on a network by considering longitudinal measures distributed on a fixed graph. The data come from repeated observations of subjects at different time points which take the form of measurement maps distributed on a graph such as an image or a mesh. The model learns a typical group-average trajectory characterizing the propagation of measurement changes across the graph nodes. The subject-specific trajectories are defined via spatial and temporal transformations of the group-average scenario, thus estimating the variability of spatiotemporal patterns within the group. To estimate population and individual model parameters, we adapted a stochastic version of the Expectation-Maximization algorithm, the MCMC-SAEM. The model is used to describe the propagation of cortical atrophy during the course of Alzheimer's Disease. Model parameters show the variability of this average pattern of atrophy in terms of trajectories across brain regions, age at disease onset and pace of propagation. We show that the personalization of this model yields accurate prediction of maps of cortical thickness in patients.

Published
2017
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46. Inter-individual and inter-regional variability of breast milk antibody reactivity to bacterial lipopolysaccharides.

Author

Crone, Lisa, Sobek, Jens, Müller, Nicole, Restin, Tanja, Bassler, Dirk, Paganini, Daniela, Zimmermann, Michael B., Zarnovican, Patricia, Routier, Françoise H., Romero-Uruñuela, Tais, Izquierdo, Luis, and Hennet, Thierry

Subjects
MOLECULAR mimicry, BREAST milk, BACTERIAL antibodies, IMMUNE recognition, LEISHMANIA major
Abstract

Breast milk is a vital source of nutrients, prebiotics, probiotics, and protective factors, including antibodies, immune cells and antimicrobial proteins. Using bacterial lipopolysaccharide arrays, we investigated the reactivity and specificity of breast milk antibodies towards microbial antigens, comparing samples from rural Kenya and urban Switzerland. Results showed considerable variability in antibody reactivity both within and between these locations. Kenyan breast milk demonstrated broad reactivity to bacterial lipopolysaccharides, likely due to increased microbial exposure. Antibodies primarily recognized the O-antigens of lipopolysaccharides and showed strong binding to specific carbohydrate motifs. Notably, antibodies against specific Escherichia coli O-antigens showed cross-reactivity with parasitic pathogens like Leishmania major and Plasmodium falciparum, thus showing that antibodies reacting against lipopolysaccharide Oantigens can recognize a wide range of antigens beyond bacteria. The observed diversity in antigen recognition highlights the significance of breast milk in safeguarding infants from infections, particularly those prevalent in specific geographic regions. The findings also offer insights for potential immunobiotic strategies to augment natural antibody-mediated defense against diverse pathogens. [ABSTRACT FROM AUTHOR]

Published
2024
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