Results 171 to 180 of about 22,853,467 (283)
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
HVD-Net: low-light image enhancement in HSV space via continuous hue encoding and dual-branch restoration. [PDF]
Zhang W +5 more
europepmc +1 more source
Cyclic Generative Attention-Adversarial Network for Low-Light Image Enhancement. [PDF]
Zhen T, Peng D, Li Z.
europepmc +1 more source
ABSTRACT Objectives We aimed to determine the frequency of subclinical optic nerve (ON) lesions using MRI, optical coherence tomography (OCT), and visual evoked potentials (VEP) in radiologically isolated syndrome (RIS), and to assess their diagnostic and prognostic significance.
Christine Lebrun‐Frenay +13 more
wiley +1 more source
PGT-Net: A Physics-Guided Transformer-CNN Hybrid Network for Low-Light Image Enhancement and Object Detection in Traffic Scenes. [PDF]
Chen B, Qiao J, Li B, Liu S, She W.
europepmc +1 more source
A Zero-Shot Low Light Image Enhancement Method Integrating Gating Mechanism. [PDF]
Tian J, Zhang J.
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
Multi-Scale Interactive Network with Color Attention for Low-Light Image Enhancement. [PDF]
Lu H, Qian C, Wang Z, Liu Z.
europepmc +1 more source
Unsupervised Low-Light Image Enhancement Based on Generative Adversarial Network. [PDF]
Yu W, Zhao L, Zhong T.
europepmc +1 more source
Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source

