AIMC Topic: Cell Proliferation
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Exploring tumor microenvironment interactions and apoptosis pathways in NSCLC through spatial transcriptomics and machine learning.
Cellular oncology (Dordrecht, Netherlands)
Dec 19, 2024
BACKGROUND: The most common type of lung cancer is non-small cell lung cancer (NSCLC), accounting for 85% of all cases. Programmed cell death (PCD), an important regulatory mechanism for cell survival and homeostasis, has become increasingly prominen...
Cubosomes as Delivery System to Repositioning Nitrofurantoin in Breast Cancer Management.
Drug design, development and therapy
Dec 19, 2024
PURPOSE: Nitrofurantoin (NITRO), a long-standing antibiotic to treat urinary tract infections, is activated by Nitro reductases. This activation mechanism has led to its exploration for repositioning applications in controlling and treating breast ca...
Effects of aqueous and ethanolic extracts of Chinese propolis on dental pulp stem cell viability, migration and cytokine expression.
PeerJ
Dec 18, 2024
BACKGROUND: Propolis is a natural substance produced by honeybees that has various biological properties including, anti-inflammatory, antioxidant and antimicrobial properties. Although previous studies have evaluated the antimicrobial effects of pro...
Machine learning-based selection of immune cell markers in osteosarcoma: prognostic determination and validation of CLK1 in disease progression.
Frontiers in immunology
Dec 17, 2024
INTRODUCTION: Osteosarcoma (OS) is a malignancy of the bone that mainly afflicts younger individuals. Despite existing treatment approaches, patients with metastatic or recurrent disease generally face poor prognoses. A greater understanding of the t...
Cell Line, Tumor
Protein Serine-Threonine Kinases
Tumor Microenvironment
Gene Expression Regulation, Neoplastic
Osteosarcoma
Humans
Biomarkers, Tumor
Bone Neoplasms
Cell Proliferation
Machine Learning
Male
Protein-Tyrosine Kinases
Lymphocytes, Tumor-Infiltrating
Prognosis
Disease Progression
DNA Copy Number Variations
Female
Utilizing AI for the Identification and Validation of Novel Therapeutic Targets and Repurposed Drugs for Endometriosis.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Dec 12, 2024
Endometriosis affects over 190 million women globally, and effective therapies are urgently needed to address the burden of endometriosis on women's health. Using an artificial intelligence (AI)-driven target discovery platform, two unreported therap...
Prediction of gene expression-based breast cancer proliferation scores from histopathology whole slide images using deep learning.
BMC cancer
Dec 11, 2024
BACKGROUND: In breast cancer, several gene expression assays have been developed to provide a more personalised treatment. This study focuses on the prediction of two molecular proliferation signatures: an 11-gene proliferation score and the MKI67 pr...
Linsitinib inhibits proliferation and induces apoptosis of both IGF-1R and TSH-R expressing cells.
Frontiers in immunology
Dec 11, 2024
BACKGROUND: The insulin-like growth factor 1 receptor (IGF-1R) and the thyrotropin receptor (TSH-R) are expressed on orbital cells and thyrocytes. These receptors are targeted in autoimmune-induced thyroid eye disease (TED). Effective therapeutic tre...
Integrating necroptosis into pan-cancer immunotherapy: a new era of personalized treatment.
Frontiers in immunology
Dec 9, 2024
INTRODUCTION: Necroptosis has emerged as a promising biomarker for predicting immunotherapy responses across various cancer types. Its role in modulating immune activation and therapeutic outcomes offers potential for precision oncology.
Machine learning-aided discovery of T790M-mutant EGFR inhibitor CDDO-Me effectively suppresses non-small cell lung cancer growth.
Cell communication and signaling : CCS
Dec 5, 2024
BACKGROUND: Epidermal growth factor receptor (EGFR) T790M mutation often occurs during long durational erlotinib treatment of non-small cell lung cancer (NSCLC) patients, leading to drug resistance and disease progression. Identification of new selec...
A deep learning model based on the BERT pre-trained model to predict the antiproliferative activity of anti-cancer chemical compounds.
SAR and QSAR in environmental research
Nov 28, 2024
Identifying new compounds with minimal side effects to enhance patients' quality of life is the ultimate goal of drug discovery. Due to the expensive and time-consuming nature of experimental investigations and the scarcity of data in traditional QSA...
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