AIMC Topic: Cell Proliferation

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Machine learning-based construction of Immunogenic cell death-related score for improving prognosis and personalized treatment in glioma.

Scientific reports
Immunogenic cell death (ICD) is capable of activating both innate and adaptive immune responses. In this study, we aimed to develop an ICD-related signature in glioma patients and facilitate the assessment of their prognosis and drug sensitivity. Con...

Identification of prognostic genes related to T cell proliferation in papillary thyroid cancer based on single-cell RNA sequencing and bulk RNA sequencing data.

Clinical and experimental medicine
Papillary thyroid carcinoma (PTC) is the main pathological subtype of thyroid cancer. Given the strong association between T cells and PTC, this study focused on the prognostic value and potential molecular mechanisms of T cell proliferation-related ...

Data-Driven Sustainable Campaigns to Decipher Invasive Breast Cancer Features.

ACS biomaterials science & engineering
The intrinsic complexity of biological processes often hides the role of dynamic microenvironmental cues in the development of pathological states. Microphysiological systems (MPSs) are emerging technological platforms that model dynamics of tissue-...

Noninvasive real-time monitoring of cellular spatiotemporal dynamics via machine learning-enhanced electrical impedance spectroscopy.

Science advances
Monitoring cellular spatiotemporal dynamics is essential for understanding complex biological processes such as organ development and cancer progression. Using live-cell fluorescence microscopy to track cellular dynamics is often limited by dye-induc...

SPP1 promotes malignant characteristics and drug resistance in hepatocellular carcinoma by activating fatty acid metabolic pathway.

Functional & integrative genomics
Hepatocellular carcinoma (HCC) progression and prognosis are influenced by various molecular markers. This study aimed to identify the hub gene associated with HCC clinical characteristics and its role in HCC progression. Differentially expressed gen...

Artificial intelligence-driven discovery of YH395A: A novel TGFβR1 inhibitor with potent anti-tumor activity against triple-negative breast cancer.

Cell communication and signaling : CCS
Characterized by high malignancy and limited treatment efficacy, triple-negative breast cancer (TNBC) remains a clinically challenging subtype within breast cancer classifications, marked by rapid progression and high mortality. Abnormal activation o...

Combining the NanaPPI Toolbox and AI-Driven Virtual Inhibitor Screening for the p53-MDM2 Interaction.

Analytical chemistry
High-throughput screening for inhibitors of protein-protein interactions (PPIs) provides vital information for therapeutic intervention in diseases driven by aberrant PPIs. Traditionally, the discovery of PPI inhibitors involves sequential steps: in ...

Identification of proliferating neural progenitors in the adult human hippocampus.

Science (New York, N.Y.)
Continuous adult hippocampal neurogenesis is involved in memory formation and mood regulation but is challenging to study in humans. Difficulties finding proliferating progenitor cells called into question whether and how new neurons may be generated...

Optimization of biological activities of Agaricus species: an artificial intelligence-assisted approach.

Scientific reports
This study aims to determine the optimum extraction conditions that maximize the biological activities of Agaricus campestris and Agaricus bisporus species. In the study, a total of 64 extraction experiments were carried out at different temperatures...

Deep learning-driven drug response prediction and mechanistic insights in cancer genomics.

Scientific reports
In the field of cancer therapy, the diversity and heterogeneity of cancer genomes in clinical patients complicate and challenge the effective use of non-targeted drugs, as these drugs often fail to address specific genetic events. Recent advancements...