Results 161 to 170 of about 481,445 (263)
ABSTRACT Objective Variants in SLC6A1, encoding the GABA transporter 1 (GAT‐1), cause epilepsy, autism spectrum disorder, and developmental delay via loss of GABA uptake, impaired trafficking, and ER retention. We previously found that 4‐Phenylbutyrate (PBA), an FDA‐approved drug, restores GABA uptake and reduces seizures in SLC6A1‐related disorders ...
Melissa B. DeLeeuw +5 more
wiley +1 more source
Enhancing property and activity prediction and interpretation using multiple molecular graph representations with MMGX. [PDF]
Kengkanna A, Ohue M.
europepmc +1 more source
Efficient learning of non-autoregressive graph variational autoencoders for molecular graph generation. [PDF]
Kwon Y +5 more
europepmc +1 more source
ABSTRACT Objective Facioscapulohumeral muscular dystrophy (FSHD) is one of the most debilitating and common muscular dystrophies. Despite its severity, no approved therapy exists for FSHD patients. However, several therapeutic candidates are currently under development, and some have recently entered clinical trials, marking the need for reliable ...
Mustafa Bilal Bayazit +11 more
wiley +1 more source
Multimodal fused deep learning for drug property prediction: Integrating chemical language and molecular graph. [PDF]
Lu X, Xie L, Xu L, Mao R, Xu X, Chang S.
europepmc +1 more source
Chemi-Net: A Molecular Graph Convolutional Network for Accurate Drug Property Prediction. [PDF]
Liu K +9 more
europepmc +1 more source
ABSTRACT Objective To evaluate the expression of nine blood RNA biomarkers in a clinical trial based on genes previously identified in an experimental monkey model of stroke for diagnosis feasibility and prognostication. Methods IBIS‐CT1 was a prospective longitudinal study enrolling patients with ischemic stroke (IS) or intracerebral hemorrhage (ICH ...
Salomé Retailleau +11 more
wiley +1 more source
Performance and robustness of small molecule retention time prediction with molecular graph neural networks in industrial drug discovery campaigns. [PDF]
Vik D +4 more
europepmc +1 more source
Molecular graph convolutions: moving beyond fingerprints. [PDF]
Kearnes S +4 more
europepmc +1 more source
ABSTRACT Objective The prognosis of glioblastoma (GBM) remains highly unfavorable, largely due to high tumor heterogeneity and an immunosuppressive microenvironment. However, the functional role of PANoptosis in this context is poorly understood. Methods Patients were stratified via K‐means clustering. A risk score model was constructed using prognosis‐
Langfei Tian +6 more
wiley +1 more source

