AIMC Topic: Cell Survival

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Degradable Magnetic Composites for Minimally Invasive Interventions: Device Fabrication, Targeted Drug Delivery, and Cytotoxicity Tests.

Advanced materials (Deerfield Beach, Fla.) Nov 25, 2015
Superparamagnetic nanoparticles and a functional, degradable polymer matrix based on poly(ethylene glycol) are combined to enable fully degradable magnetic microdevices for minimally invasive biomedical applications. A bioinspired helical microrobot ...
Magnets Propylene Glycols Polyethylene Glycols Materials Testing 3T3 Cells Acrylates Drug Carriers Robotics Equipment Design Animals Mice Cell Survival
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Application of artificial neural network to investigate the effects of 5-fluorouracil on ribonucleotides and deoxyribonucleotides in HepG2 cells.

Scientific reports Nov 18, 2015
Endogenous ribonucleotides and deoxyribonucleotides are essential metabolites that play important roles in a broad range of key cellular functions. Their intracellular levels could also reflect the action of nucleoside analogues. We investigated the ...
Tandem Mass Spectrometry Inhibitory Concentration 50 Adenine Nucleotides Cytosine Nucleotides Metabolic Networks and Pathways Models, Biological Fluorouracil Uracil Nucleotides Deoxyribonucleotides Guanine Nucleotides Ribonucleotides Thymine Nucleotides Humans Neural Networks, Computer Hep G2 Cells Cell Survival Chromatography, Liquid
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Effect of earthworm active protein on fibroblast proliferation and its mechanism.

Pharmaceutical biology Oct 7, 2015
CONTEXT: Earthworms have been used as a traditional medicine in China from thousands of years. In recent years, research has demonstrated that earthworm extracts might promote wound healing; however, its mechanism is still unknown.
Dose-Response Relationship, Drug Cell Survival NIH 3T3 Cells Biological Factors Mice Oligochaeta Animals Cell Proliferation Fibroblasts
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Cytotoxicity of chitosan/streptokinase nanoparticles as a function of size: An artificial neural networks study.

Nanomedicine : nanotechnology, biology, and medicine Sep 25, 2015
Predicting the size and toxicity of chitosan/streptokinase nanoparticles at various values of processing parameters was the aim of this study. For the first time, a comprehensive model could be developed to determine the cytotoxicity of the nanoparti...
Neural Networks, Computer Algorithms Reproducibility of Results Drug Evaluation, Preclinical Nanocomposites Streptokinase Chitosan Pattern Recognition, Automated Sensitivity and Specificity Particle Size Toxicity Tests Dose-Response Relationship, Drug Structure-Activity Relationship Cell Survival Hydrogen-Ion Concentration
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Quantitative analysis of mitochondrial morphology and membrane potential in living cells using high-content imaging, machine learning, and morphological binning.

Biochimica et biophysica acta Nov 13, 2014
Understanding the processes of mitochondrial dynamics (fission, fusion, biogenesis, and mitophagy) has been hampered by the lack of automated, deterministic methods to measure mitochondrial morphology from microscopic images. A method to quantify mit...
Electron Transport tert-Butylhydroperoxide Carbonyl Cyanide m-Chlorophenyl Hydrazone Cell Respiration Mitochondria Sodium-Potassium-Exchanging ATPase Stress, Physiological Animals Cell Membrane Imaging, Three-Dimensional Cell Survival Mice Membrane Potential, Mitochondrial Cell Line Artificial Intelligence Oxidants Phenotype
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Machine learning-driven nanoparticle toxicity.

Ecotoxicology and environmental safety Jul 1, 2025
This study presents a comprehensive machine learning-driven analysis to understand and predict the toxicity of nanoparticles (NPs), a crucial aspect in ensuring the safe application of nanotechnology in medicine, pharmaceuticals, biotechnology, and v...
Machine Learning Nanoparticles Cell Survival Toxicity Tests Humans
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Machine-Learning Framework to Predict the Performance of Lipid Nanoparticles for Nucleic Acid Delivery.

ACS applied bio materials May 19, 2025
Lipid nanoparticles (LNPs) are highly effective carriers for gene therapies, including mRNA and siRNA delivery, due to their ability to transport nucleic acids across biological membranes, low cytotoxicity, improved pharmacokinetics, and scalability....
Particle Size Lipids Materials Testing Biocompatible Materials Machine Learning Nanoparticles Cell Survival Humans Surface Properties Nucleic Acids Quantitative Structure-Activity Relationship
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A comprehensive evaluation of regression-based drug responsiveness prediction models, using cell viability inhibitory concentrations (IC50 values).

Bioinformatics (Oxford, England) May 13, 2022
MOTIVATION: Predicting drug response is critical for precision medicine. Diverse methods have predicted drug responsiveness, as measured by the half-maximal drug inhibitory concentration (IC50), in cultured cells. Although IC50s are continuous, tradi...
Neural Networks, Computer Precision Medicine Machine Learning Cell Survival Inhibitory Concentration 50
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Cytotoxicity and molecular docking analysis of racemolactone I, a new sesquiterpene lactone isolated from .

Pharmaceutical biology Dec 1, 2021
CONTEXT: Traditionally, Hook. f. (Asteraceae) has been reported to be effective in cancer treatment which motivated the authors to explore the plant for novel anticancer compounds.
Plant Roots Humans Inula Apoptosis Membrane Potential, Mitochondrial Lactones Molecular Docking Simulation HeLa Cells Cell Survival Sesquiterpenes Cell Line, Tumor Antineoplastic Agents, Phytogenic A549 Cells
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Deep learning identifies synergistic drug combinations for treating COVID-19.

Proceedings of the National Academy of Sciences of the United States of America Sep 28, 2021
Effective treatments for COVID-19 are urgently needed. However, discovering single-agent therapies with activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been challenging. Combination therapies play an important role i...
Humans SARS-CoV-2 Deep Learning Adenosine Monophosphate Drug Interactions COVID-19 Drug Treatment Drug Synergism Alanine Antiviral Agents Drug Combinations Cell Survival
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