Down syndrome and DYRK1A overexpression: relationships and future therapeutic directions

Autor: Aidan J. Murphy, Steve D. Wilton, May T. Aung-Htut, Craig S. McIntosh

Publikováno v: Frontiers in Molecular Neuroscience, Vol 17 (2024)

Down syndrome is a genetic-based disorder that results from the triplication of chromosome 21, leading to an overexpression of many triplicated genes, including the gene encoding Dual-Specificity Tyrosine Phosphorylation-Regulated Kinase 1A (DYRK1A).

Externí odkaz: https://doaj.org/article/7bd9e0f2f9304a299516f800d438406f

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

Autor: 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, Viard, Jean-Paul

Publikováno v: In The Lancet Regional Health - Europe May 2024 40

Adaptive Coordination Offsets for Signalized Arterial Intersections using Deep Reinforcement Learning

Autor: Diaz, Keith Anshilo, Dailisan, Damian, Sharaf, Umang, Santos, Carissa, Gan, Qijian, Uy, Francis Aldrine, Lim, May T., Bayen, Alexandre M.

Coordinating intersections in arterial networks is critical to the performance of urban transportation systems. Deep reinforcement learning (RL) has gained traction in traffic control research along with data-driven approaches for traffic control sys

Externí odkaz: http://arxiv.org/abs/2008.02691

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