Results 221 to 230 of about 8,194,451 (253)

Predictive Value of Composite Inflammatory Markers for Stroke Prognosis: A Prospective Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Novel composite inflammatory markers' role in stroke prognosis is understudied, and the best predictor is unclear, requiring further exploration. Objectives This study aimed to systematically evaluate the associations of 6 novel composite inflammatory markers on stroke prognosis.
Bing Wu, Jie‐Jie Li, Jing Jing, Jin‐Xi Lin, Xia Meng, Yong Jiang, Yong‐Jun Wang, Hong‐Qiu Gu   +7 more
wiley   +1 more source

Enhancing drug repositioning: A multi-class ensemble model for drug-target interaction prediction with action type categorization. [PDF]

PLoS One
Jafari Khouzani L, Sardari S, Jafari Khouzani S, Pérez-Sánchez H, Ghasemi F.   +4 more
europepmc   +1 more source

Natural Frequencies of Levodopa‐Induced Dyskinesia in Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Abnormal involuntary movements, known as dyskinesias, are common complications of levodopa treatment in patients with Parkinson's disease and can significantly impair quality of life. The underlying pathophysiology remains unclear, and current therapeutic options are limited.
Ioannis U. Isaias, Federica Avantaggiato, Gianni Pezzoli, Andrea Canessa   +3 more
wiley   +1 more source

AI-powered IC50 prediction for p53 inhibitors drug-target interaction via hybrid graph neural networks. [PDF]

J Comput Aided Mol Des
El-Masry WH, Monem S, Darwish NR, Hassanein AE.   +3 more
europepmc   +1 more source

Integrated PANoptosis Profiling Identifies Immunosuppressive Subtypes and a Prognostic Signature With Functional Validation of MLKL in Glioblastoma

Annals of Clinical and Translational Neurology, EarlyView.
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, Minghui Zhao, Yuanbo Hu, Kaiyue Wang, Haiguang Liu, Zetong Bai, Kebin Zheng   +6 more
wiley   +1 more source

BiMA-DTI: a bidirectional Mamba-Attention hybrid framework for enhanced drug-target interaction prediction. [PDF]

BMC Biol
Shui Y, Ge X, Cao C, Wang J, Hu J, Liu Y.   +5 more
europepmc   +1 more source

Validation of a Cellular Imaging‐Based Method as a Potential Biomarker for SPG4 Hereditary Spastic Paraplegia

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Hereditary Spastic Paraplegia (HSP) comprises a group of rare genetic diseases characterized by length‐dependent axonal degeneration of the corticospinal tracts and dorsal columns, whose main clinical feature is spastic gait. Pathogenic variants in the SPG4 gene cause Spastic Paraplegia Type 4 (SPG4‐HSP), the most common form of HSP.
Gaia Fattorini, Valerio Licursi, Gianmarco Dalla Zanna, Flavio Dal Canto, Melissa Barghigiani, Nunzio Setola, Salvatore Rossi, Antonio Funcis, Filippo M. Santorelli, Gabriella Silvestri, Carlo Casali, Francesca Sardina, Cinzia Rinaldo   +12 more
wiley   +1 more source

SaeGraphDTI: drug-target interaction prediction based on sequence attribute extraction and graph neural network. [PDF]

BMC Bioinformatics
Zhang Q, Sun Z, Zhong Z, Yang H, Wei Y, Xu J.   +5 more
europepmc   +1 more source

SP-DTI: subpocket-informed transformer for drug-target interaction prediction. [PDF]

Bioinformatics
Liu S, Liu Y, Xu H, Xia J, Li SZ.
europepmc   +1 more source

NASNet-DTI: accurate drug-target interaction prediction using heterogeneous graphs and node adaptation. [PDF]

Brief Bioinform
Zhong N, Du Z.
europepmc   +1 more source