AIMC Topic: Cell Proliferation
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Bioactivity of Juglans regia kernel extracts optimized using response surface method and artificial neural Network-Genetic algorithm integration.
Scientific reports
Mar 15, 2025
In this study, the biological activities of the extracts obtained under optimum extraction conditions of the kernel part of Juglans regia L. were determined. Two different methods, Response Surface Method (RSM) and Artificial Neural Network-Genetic A...
Machine learning analysis identified NNMT as a potential therapeutic target for hepatocellular carcinoma based on PCD-related genes.
Scientific reports
Mar 3, 2025
Programmed cell death (PCD) plays a critical role in cancer biology, influencing tumor progression and treatment response. This study aims to investigate the role of PCD-related genes in hepatocellular carcinoma (HCC), identifying potential prognosti...
Big data analysis and machine learning of the role of cuproptosis-related long non-coding RNAs (CuLncs) in the prognosis and immune landscape of ovarian cancer.
Frontiers in immunology
Feb 25, 2025
BACKGROUND: Ovarian cancer (OC) is a severe malignant tumor with a significant threat to women's health, characterized by a high mortality rate and poor prognosis despite conventional treatments such as cytoreductive surgery and platinum-based chemot...
G2M-checkpoint related immune barrier structure and signature for prognosis and immunotherapy response in hepatocellular carcinoma: insights from spatial transcriptome and machine learning.
Journal of translational medicine
Feb 18, 2025
BACKGROUND: Hepatocellular carcinoma (HCC) treatment remains challenging, particularly for immune checkpoint inhibitors (ICIs) non-response patients. Spatial transcriptome (ST) data and machine learning algorithms offer new insights into understandin...
Machine learning-based lactate-related genes signature predicts clinical outcomes and unveils novel therapeutic targets in esophageal squamous cell carcinoma.
Cancer letters
Jan 27, 2025
Esophageal squamous cell carcinoma (ESCC), a predominant subtype of esophageal cancer, typically presents with poor prognosis. Lactate is a crucial metabolite in cancer and significantly impacts tumor biology. Here, we aimed to construct a lactate-re...
Opioid growth factor receptor overexpression exerts anti-hepatocellular carcinoma effects by activating P16 and P21 to inhibit proliferation and migration of HepG2 cells.
Folia histochemica et cytobiologica
Jan 13, 2025
INTRODUCTION: Hepatocellular carcinoma (HCC) is the sixth most common type of cancer and the second leading cause of cancer death worldwide [19]. Opioid growth factor (OGF) has been shown to exhibit antitumour potential, binding to OGF receptor (OGFr...
Glycosylation profiling of triple-negative breast cancer: clinical and immune correlations and identification of LMAN1L as a biomarker and therapeutic target.
Frontiers in immunology
Jan 10, 2025
INTRODUCTION: Breast cancer (BC) is the most prevalent malignant tumor in women, with triple-negative breast cancer (TNBC) showing the poorest prognosis among all subtypes. Glycosylation is increasingly recognized as a critical biomarker in the tumor...
PRAF2 as a novel biomarker for breast cancer with machine learning and experimentation validation.
BMC cancer
Jan 8, 2025
BACKGROUND: Breast cancer (BC) is the most prevalent malignancy in women. Potential therapeutic targets for BC are of great significance. In our previous study, we found that prenylated rab acceptor 1 domain family member 2 (PRAF2) is an oncogene in ...
Robot-Assisted Synthesis of Structure-Controlled Star-Cluster Hydrogels with Targeted Mechanophysical Properties for Biomedical Applications.
Biomacromolecules
Dec 23, 2024
Advancements in polymer chemistry have enabled the design of macromolecular structures with tailored properties for diverse applications. Reversible addition-fragmentation chain-transfer (RAFT) polymerization is a controlled technique for precise pol...
Integration of Graph Neural Networks and multi-omics analysis identify the predictive factor and key gene for immunotherapy response and prognosis of bladder cancer.
Journal of translational medicine
Dec 23, 2024
OBJECTIVE: The evaluation of the efficacy of immunotherapy is of great value for the clinical treatment of bladder cancer. Graph Neural Networks (GNNs), pathway analysis and multi-omics analysis have shown great potential in the field of cancer diagn...
Cell Movement
Apoptosis
Proteasome Endopeptidase Complex
Prognosis
Reproducibility of Results
Tumor Microenvironment
Gene Expression Regulation, Neoplastic
Cell Line, Tumor
Humans
Cell Proliferation
Neural Networks, Computer
Single-Cell Analysis
Treatment Outcome
Computational Biology
Urinary Bladder Neoplasms
Immunotherapy
Multiomics
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