AIMC Topic: Cell Line, Tumor
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Machine learning based intratumor heterogeneity related signature for prognosis and drug sensitivity in breast cancer.
Scientific reports
Mar 28, 2025
Intratumor heterogeneity (ITH) is involved in tumor evolution and drug resistance. Drug sensitivity shows discrepancy in different breast cancer (BRCA) patients due to ITH. The genes mediating ITH in BRCA and their role in predicting prognosis and dr...
Cancer Cell Line Classification Using Raman Spectroscopy of Cancer-Derived Exosomes and Machine Learning.
Analytical chemistry
Mar 27, 2025
Liquid biopsies are an emerging, noninvasive tool for cancer diagnostics, utilizing biological fluids for molecular profiling. Nevertheless, the current methods often lack the sensitivity and specificity necessary for early detection and real-time mo...
Aggregation induced emission luminogen bacteria hybrid bionic robot for multimodal phototheranostics and immunotherapy.
Nature communications
Mar 16, 2025
Multimodal phototheranostics utilizing single molecules offer a "one-and-done" approach, presenting a convenient and effective strategy for cancer therapy. However, therapies based on conventional photosensitizers often suffer from limitations such a...
Light scattering imaging modal expansion cytometry for label-free single-cell analysis with deep learning.
Computer methods and programs in biomedicine
Mar 15, 2025
BACKGROUND AND OBJECTIVE: Single-cell imaging plays a key role in various fields, including drug development, disease diagnosis, and personalized medicine. To obtain multi-modal information from a single-cell image, especially for label-free cells, t...
Cancer Drug Sensitivity Prediction Based on Deep Transfer Learning.
International journal of molecular sciences
Mar 10, 2025
In recent years, many approved drugs have been discovered using phenotypic screening, which elaborates the exact mechanisms of action or molecular targets of drugs. Drug susceptibility prediction is an important type of phenotypic screening. Large-sc...
AEGNN-M:A 3D Graph-Spatial Co-Representation Model for Molecular Property Prediction.
IEEE journal of biomedical and health informatics
Mar 6, 2025
Improving the drug development process can expedite the introduction of more novel drugs that cater to the demands of precision medicine. Accurately predicting molecular properties remains a fundamental challenge in drug discovery and development. Cu...
Decoding Drug Response With Structurized Gridding Map-Based Cell Representation.
IEEE journal of biomedical and health informatics
Mar 6, 2025
A thorough understanding of cell-line drug response mechanisms is crucial for drug development, repurposing, and resistance reversal. While targeted anticancer therapies have shown promise, not all cancers have well-established biomarkers to stratify...
DRExplainer: Quantifiable interpretability in drug response prediction with directed graph convolutional network.
Artificial intelligence in medicine
Mar 4, 2025
Predicting the response of a cancer cell line to a therapeutic drug is pivotal for personalized medicine. Despite numerous deep learning methods that have been developed for drug response prediction, integrating diverse information about biological e...
GALR1 and PENK serve as potential biomarkers in invasive non-functional pituitary neuroendocrine tumours.
Gene
Feb 28, 2025
BACKGROUND: Some nonfunctioning pituitary neuroendocrine tumor (NFPitNET) can show invasive growth, which increases the difficulty of surgery and indicates a poor prognosis. However, the molecular mechanism related to invasiveness remains to be furth...
Living Microalgae-Based Magnetic Microrobots for Calcium Overload and Photodynamic Synergetic Cancer Therapy.
Advanced healthcare materials
Feb 27, 2025
The combination of Ca overload and reactive oxygen species (ROS) production for cancer therapy offers a superior solution to the lack of specificity in traditional antitumor strategies. However, current therapeutic platforms for this strategy are pri...
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