AIMC Topic: Cell Proliferation

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Machine learning-powered discovery of a novel berberine derivative inducing SCD-dependent ferroptosis in osteosarcoma.

Journal of translational medicine
BACKGROUND: Despite decades of therapeutic development, osteosarcoma survival remains poor. Although berberine (BBR) shows anti-tumor activity, its efficacy is limited. We addressed this through structural modification and machine learning-guided dis...

Macrophage mitophagy-related genes predict prognosis and therapeutic response in lung adenocarcinoma.

Scientific reports
Mitochondrial autophagy (mitophagy) in macrophages is crucial yet poorly understood within the lung adenocarcinoma (LUAD) tumor microenvironment. This study aimed to identify key macrophage mitophagy-related genes and develop a robust prognostic mode...

Construction and validation of gene signature for prognosis and drug sensitivity in cholangiocarcinoma based on cellular senescence related genes.

Scientific reports
Cholangiocarcinoma is a very deadly epithelial cell cancer with poor clinical outcome. Cellular senescence plays a vital role in the oncogenesis and the aggressiveness of cholangiocarcinoma. Integrative machine learning procedure including 10 methods...

Automated quantification of Ki-67 expression in breast cancer from H&E-stained slides using a transformer-based regression model.

Breast cancer research : BCR
BACKGROUND: Accurate quantification of the Ki-67 proliferation index is essential for breast cancer prognosis and treatment planning. Current automated methods, including classical and deep learning approaches based on cell detection or segmentation,...

Targeted inhibition of gastric adenocarcinoma by nano-curcumin liposomes: Insights from combined machine learning and experimental analyses into the mechanisms of cuproptosis and metabolic reprogramming.

International journal of pharmaceutics
PURPOSE: Gastric adenocarcinoma is a highly aggressive malignancy characterized by a complex tumor microenvironment. Nano-curcumin liposomes hold great potential in inhibiting tumor growth and survival, as well as inducing cuproptosis and oxidative s...

Synergistic approach utilizing bioinformatics, machine learning, and traditional screening for the identification of novel CSK inhibitors targeting hepatocellular carcinoma.

Journal of computer-aided molecular design
The overexpression or activation of C-terminal Src kinase (CSK) has been recognized as a pivotal factor in the progression of hepatocellular carcinoma (HCC), positioning CSK as a promising therapeutic target. Despite this potential, no CSK-specific i...

Drug repurposing identifies novel Wee1 kinase inhibitors for triple negative breast cancer therapeutics.

European journal of medicinal chemistry
Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited treatment options. Wee1 kinase, a critical regulator of the G2/M checkpoint and DNA replication, is a promising therapeutic target. However, dose dependent as...

Evaluation of (Z)-endoxifen as a potential therapy for glioblastoma multiforme through computational and experimental analyses.

Scientific reports
(Z)-endoxifen (endoxifen) is the active metabolite of tamoxifen. Endoxifen is a potent antiestrogen that binds and blocks estrogen receptor alpha (ERα) and estrogen receptor beta (ERβ). Early-phase clinical trials have shown that endoxifen has promis...

Evaluation of antioxidant, anticholinesterase and antiproliferative potential of Artemisia herba-alba by artificial intelligence-assisted extraction optimization.

Scientific reports
In this study, in order to maximize the biological activity of Artemisia herba-alba Asso, extraction conditions were optimized by two different methods: Response Surface Methodology (RSM) and Artificial Neural Network-Genetic Algorithm (ANN-GA). A to...

Predicted peptide scaffolds for drug screening in endometrial cancer organoids.

Scientific reports
AlphaFold, a deep learning-based platform widely used to predict protein and peptide structures, was employed in this study to model the self-assembling peptide RFC, which demonstrated a stable α-helical structure with high confidence. This structura...