Results 141 to 150 of about 3,038,089 (290)
Advanced Science, EarlyView.This study shows anti‐CEACAM5 CAR T‐cells are ineffective against colorectal cancer (CRC) because of CEACAM5 sequestration at intercellular junctions and the thick tumour cell glycocalyx. Enzymatic treatments of CRC cell monolayer/tissue section with trypsin or hyaluronidase restore CEACAM5 availability, enhance CAR T‐cell activation, increase ...
Debasis Banik +13 more
wiley +1 more source
Advanced Science, EarlyView.This study employs longitudinal fluorescence imaging in transgenic mice to map post‐craniotomy cortical recovery. We identify distinct neuroimmune recovery phases: microglial structural inflammation peaks at ∼10 days, neuronal structural intensity peaks at ∼14 days and correlates with microglial activity, and functional network modularity is most ...
Guihua Xiao +13 more
wiley +1 more source
Advanced Science, EarlyView.We present Diffusion‐MRI‐based Estimation of Cortical Architecture via Machine Learning (DECAM), a deep‐learning framework for estimating primate brain cortical architecture optimized with best response constraint and cortical label vectors. Trained using macaque brain high‐resolution multi‐shell dMRI and histology data, DECAM generates high‐fidelity ...
Tianjia Zhu +7 more
wiley +1 more source
A weighted sparse coding model on product Grassmann manifold for video-based human gesture recognition. [PDF]
PeerJ Comput Sci, 2022 Wang Y, Zhang J.
europepmc +1 more source
Online dictionary learning for sparse coding
International Conference on Machine Learning, 2009 J. Mairal, F. Bach, J. Ponce, G. Sapiro
semanticscholar +1 more source
, 2012 A fundamental understanding of the relationship between delay performance and complexity in network coding is instrumental towards its application in practical systems. The main argument against delay-optimal random linear network coding (RLNC) is its decoding complexity, which is O(n 3 ) for n original packets.
Feizi, Soheil +2 more
openaire +2 more sources
Advanced Science, EarlyView.Identifying disease‐causing genes in neurocognitive disorders remains challenging due to variants of uncertain significance. CLinNET employs dual‐branch neural networks integrating Reactome pathways and Gene Ontology terms to provide pathway‐level interpretability of genomic alterations.
Ivan Bakhshayeshi +5 more
wiley +1 more source
Anomaly detection in fundus images by self-adaptive decomposition via local and color based sparse coding. [PDF]
Biomed Opt Express, 2022 Du Y +7 more
europepmc +1 more source
MGM as a Large‐Scale Pretrained Foundation Model for Microbiome Analyses in Diverse Contexts
Advanced Science, EarlyView.We present the Microbial General Model (MGM), a transformer‐based foundation model pretrained on over 260,000 microbiome samples. MGM learns contextualized microbial representations via self‐supervised language modeling, enabling robust transfer learning, cross‐regional generalization, keystone taxa discovery, and prompt‐guided generation of realistic,
Haohong Zhang +5 more
wiley +1 more source