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Caspases

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Myricitrin inhibits vascular endothelial growth factor-induced angiogenesis of human umbilical vein endothelial cells and mice.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
In the present study, the protective effects of myricitrin against vascular endothelial growth factor (VEGF)-induced angiogenesis of vascular endothelial cells were characterized. Cells were induced with 50 ng/mL VEGF in the presence or absence of va...

Anticancer activity of biologically synthesized silver and gold nanoparticles on mouse myoblast cancer cells and their toxicity against embryonic zebrafish.

Materials science & engineering. C, Materials for biological applications
The aim of this study was to evaluate the anticancer activity of bioinspired silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs) against mouse myoblast cancer cells (CC). Both AgNPs and AuNPs were biologically synthesized using Spinacia olera...

AI-based Apoptosis Cell Classification Using Phase-contrast Images of K562 Cells.

Anticancer research
BACKGROUND/AIM: This study aimed to automate the classification of cells, particularly in identifying apoptosis, using artificial intelligence (AI) in conjunction with phase-contrast microscopy. The objective was to reduce reliance on manual observat...

ZoomQA: residue-level protein model accuracy estimation with machine learning on sequential and 3D structural features.

Briefings in bioinformatics
MOTIVATION: The Estimation of Model Accuracy problem is a cornerstone problem in the field of Bioinformatics. As of CASP14, there are 79 global QA methods, and a minority of 39 residue-level QA methods with very few of them working on protein complex...

Protein model accuracy estimation empowered by deep learning and inter-residue distance prediction in CASP14.

Scientific reports
The inter-residue contact prediction and deep learning showed the promise to improve the estimation of protein model accuracy (EMA) in the 13th Critical Assessment of Protein Structure Prediction (CASP13). To further leverage the improved inter-resid...

CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction.

Nature communications
Residue co-evolution has become the primary principle for estimating inter-residue distances of a protein, which are crucially important for predicting protein structure. Most existing approaches adopt an indirect strategy, i.e., inferring residue co...

Analyzing effect of quadruple multiple sequence alignments on deep learning based protein inter-residue distance prediction.

Scientific reports
Protein 3D structure prediction has advanced significantly in recent years due to improving contact prediction accuracy. This improvement has been largely due to deep learning approaches that predict inter-residue contacts and, more recently, distanc...

Improved protein structure refinement guided by deep learning based accuracy estimation.

Nature communications
We develop a deep learning framework (DeepAccNet) that estimates per-residue accuracy and residue-residue distance signed error in protein models and uses these predictions to guide Rosetta protein structure refinement. The network uses 3D convolutio...