Transfer learning on structural brain age models to decode cognition in MS: a federated learning approach

Autor: Stijn Denissen, Matthias Grothe, Manuela Vaněčková, Tomáš Uher, Jorne Laton, Matěj Kudrna, Dana Horáková, Michael Kirsch, Jiří Motýl, Maarten De Vos, Oliver Y. Chén, Jeroen Van Schependom, Diana Maria Sima, Guy Nagels

IntroductionClassical deep learning research requires lots of centralised data. However, data sets are often stored at different clinical centers, and sharing sensitive patient data such as brain images is difficult. In this manuscript, we investigat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::097bbcf8ff14d8e21e3de992702e54d6
https://doi.org/10.1101/2023.04.22.23288741

Clinical exome analysis and targeted gene repair of the c.1354dupT variant in iPSC lines from patients with PROM1-related retinopathies exhibiting diverse phenotypes

Autor: Kevin Puertas-Neyra, Rosa M. Coco-Martin, Leticia A. Hernandez-Rodriguez, Dino Gobelli, Yenisey Garcia-Ferrer, Raicel Palma-Vecino, Juan José Tellería, Maria Simarro, Miguel A. de la Fuente, Ivan Fernandez-Bueno

Publikováno v: Stem Cell Research & Therapy, Vol 15, Iss 1, Pp 1-24 (2024)

Abstract Background Inherited retinal dystrophies (IRD) are one of the main causes of incurable blindness worldwide. IRD are caused by mutations in genes that encode essential proteins for the retina, leading to photoreceptor degeneration and loss of

Externí odkaz: https://doaj.org/article/dda4a69b160541f4adba672a7f7cb41d

Towards Multimodal Machine Learning Prediction of Individual Cognitive Evolution in Multiple Sclerosis

Autor: Stijn Denissen, Oliver Y. Chén, Johan De Mey, Maarten De Vos, Jeroen Van Schependom, Diana Maria Sima, Guy Nagels

Publikováno v: Journal of Personalized Medicine, Vol 11, Iss 1349, p 1349 (2021)
Journal of Personalized Medicine

Multiple sclerosis (MS) manifests heterogeneously among persons suffering from it, making its disease course highly challenging to predict. At present, prognosis mostly relies on biomarkers that are unable to predict disease course on an individual l

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6e7d6c7ec20b994116fd6b4c8240b58
https://doi.org/10.3390/jpm11121349

The mitochondrial succinate dehydrogenase complex controls the STAT3-IL-10 pathway in inflammatory macrophages

Autor: Dino Gobelli, Pablo Serrano-Lorenzo, María J. Esteban-Amo, Julia Serna, M. Teresa Pérez-García, Antonio Orduña, Alexis A. Jourdain, Miguel Á. Martín-Casanueva, Miguel Á. de la Fuente, María Simarro

Publikováno v: iScience, Vol 26, Iss 8, Pp 107473- (2023)

Summary: The functions of macrophages are tightly regulated by their metabolic state. However, the role of the mitochondrial electron transport chain (ETC) in macrophage functions remains understudied. Here, we provide evidence that the succinate deh

Externí odkaz: https://doaj.org/article/58252a7893af4fcebcf8be541d458110

Quantifying brain tumor tissue abundance in HR-MAS spectra using non-negative blind source separation techniques

Autor: Croitor Sava, Anca Ramona, Marie Martinez-Bisbal, Carmen, Maria Sima, Diana, Calvar, Jorge, Esteve, Vicente, Celda, Bernardo, Himmelreich, Uwe, Van Huffel, Sabine

Publikováno v: Journal of Chemometrics; Vol 26
JOURNAL OF CHEMOMETRICS
r-IIS La Fe. Repositorio Institucional de Producción Científica del Instituto de Investigación Sanitaria La Fe
instname

Given high-resolution magic angle spinning (HR-MAS) spectra from several glial tumor subjects, our goal is to differentiate between tumor tissue types by separating the different sources that contribute to the profile of each spectrum. Blind source s

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::82508e98f5303e906fffd2ee4d41658e