AIMC Topic: Cell Line, Tumor
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A novel CAF-cancer cell crosstalk-related gene prognostic index based on machine learning: prognostic significance and prediction of therapeutic response in head and neck squamous cell carcinoma.
Journal of translational medicine
Jul 9, 2024
BACKGROUND: Cancer-associated fibroblast (CAF)-cancer cell crosstalk (CCCT) plays an important role in tumor microenvironment shaping and immunotherapy response. Current prognostic indexes are insufficient to accurately assess immunotherapy response ...
Synthesis, Docking, and Machine Learning Studies of Some Novel Quinolinesulfonamides-Triazole Hybrids with Anticancer Activity.
Molecules (Basel, Switzerland)
Jul 2, 2024
In the presented work, a series of 22 hybrids of 8-quinolinesulfonamide and 1,4-disubstituted triazole with antiproliferative activity were designed and synthesised. The title compounds were designed using molecular modelling techniques. For this pur...
A high hydrophobic moment arginine-rich peptide screened by a machine learning algorithm enhanced ADC antitumor activity.
Journal of peptide science : an official publication of the European Peptide Society
Jul 1, 2024
Cell-penetrating peptides (CPPs) with better biomolecule delivery properties will expand their clinical applications. Using the MLCPP2.0 machine algorithm, we screened multiple candidate sequences with potential cellular uptake ability from the nucle...
A DNA robotic switch with regulated autonomous display of cytotoxic ligand nanopatterns.
Nature nanotechnology
Jul 1, 2024
The clustering of death receptors (DRs) at the membrane leads to apoptosis. With the goal of treating tumours, multivalent molecular tools that initiate this mechanism have been developed. However, DRs are also ubiquitously expressed in healthy tissu...
Immune Cell-Based Microrobots for Remote Magnetic Actuation, Antitumor Activity, and Medical Imaging.
Advanced healthcare materials
Jun 25, 2024
Translating medical microrobots into clinics requires tracking, localization, and performing assigned medical tasks at target locations, which can only happen when appropriate design, actuation mechanisms, and medical imaging systems are integrated i...
Machine learning identifies activation of RUNX/AP-1 as drivers of mesenchymal and fibrotic regulatory programs in gastric cancer.
Genome research
Jun 25, 2024
Gastric cancer (GC) is the fifth most common cancer worldwide and is a heterogeneous disease. Among GC subtypes, the mesenchymal phenotype (Mes-like) is more invasive than the epithelial phenotype (Epi-like). Although gene expression of the epithelia...
Machine learning assisted microfluidics dual fluorescence flow cytometry for detecting bladder tumor cells based on morphological characteristic parameters.
Analytica chimica acta
Jun 22, 2024
BACKGROUND: Bladder cancer (BC) is the most common malignant tumor and has become a major public health problem, leading the causes of death worldwide. The detection of BC cells is of great significance for clinical diagnosis and disease treatment. U...
From Deep Learning to the Discovery of Promising VEGFR-2 Inhibitors.
ChemMedChem
Jun 20, 2024
Vascular endothelial growth factor receptor 2 (VEGFR-2) stands as a prominent therapeutic target in oncology, playing a critical role in angiogenesis, tumor growth, and metastasis. FDA-approved VEGFR-2 inhibitors are associated with diverse side effe...
Vascular Endothelial Growth Factor Receptor-2
Protein Kinase Inhibitors
Drug Screening Assays, Antitumor
Structure-Activity Relationship
Molecular Structure
Molecular Docking Simulation
Drug Discovery
Antineoplastic Agents
Cell Proliferation
Dose-Response Relationship, Drug
Deep Learning
Cell Line, Tumor
Humans
Deep learning unlocks label-free viability assessment of cancer spheroids in microfluidics.
Lab on a chip
Jun 11, 2024
Despite recent advances in cancer treatment, refining therapeutic agents remains a critical task for oncologists. Precise evaluation of drug effectiveness necessitates the use of 3D cell culture instead of traditional 2D monolayers. Microfluidic plat...
D-MAINS: A Deep-Learning Model for the Label-Free Detection of Mitosis, Apoptosis, Interphase, Necrosis, and Senescence in Cancer Cells.
Cells
Jun 8, 2024
BACKGROUND: Identifying cells engaged in fundamental cellular processes, such as proliferation or living/death statuses, is pivotal across numerous research fields. However, prevailing methods relying on molecular biomarkers are constrained by high c...
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