Results 231 to 240 of about 93,309 (296)
Three charge assignment approaches (one quantum chemistry method‐based, the other two machine‐learning (ML) model‐based) are employed to investigate acetylene separation performances of experimental covalent‐organic frameworks. Partial Atomic Charge Predicter for Porous Materials based on Graph Convolutional Neural Network (PACMAN) ML model‐based ...
Hakan Demir, Ilknur Erucar
wiley +1 more source
The effect of salidroside in promoting endogenous neural regeneration after cerebral ischemia/reperfusion involves notch signaling pathway and neurotrophic factors. [PDF]
Zheng J, Zhang J, Han J, Zhao Z, Lin K.
europepmc +1 more source
This study explores machine learning‐driven prediction of fiber length characteristics in sustainable yarn blends made from recycled cotton and Lyocell. By analyzing empirical data through models like Random Forest and Gradient Boosting, and interpreting results with SHAP, key fiber length features from the Staple Diagram and Fibrogram are identified ...
Tuser Tirtha Biswas+2 more
wiley +1 more source
In vivo neural regeneration via AAV-NeuroD1 gene delivery to astrocytes in neonatal hypoxic-ischemic brain injury. [PDF]
Kim M+10 more
europepmc +1 more source
Vertebrate Neural Stem Cells: Development, Plasticity, and Regeneration
Takuya Shimazaki
openalex +2 more sources
Current preclinical studies of AAV‐mediated gene therapy explore different strategies based on the characteristics of inner ear diseases. For genetic hearing loss, approaches include the replacement of a “good gene,” removal of a “bad gene,” or direct correction of mutations through base editing.
Fan Wu+7 more
wiley +1 more source
Neural regeneration in the human central nervous system-from understanding the underlying mechanisms to developing treatments. Where do we stand today? [PDF]
Kvistad CE+3 more
europepmc +1 more source
Self-assembling peptides for neural regeneration
Ratcliffe Julian+4 more
openalex +1 more source