Now showing items 1-6 of 6
A hybrid mathematical modeling approach of the metabolic fate of a fluorescent sphingolipid analogue to predict cancer chemosensitivity
Sphingolipid (SL) metabolism is a complex biological system that produces and transforms ceramides and other molecules able to modulate other cellular processes, including survival or death pathways key to cell fate ...
Clinical profiles at the time of diagnosis of COVID-19 in Costa Rica during the pre-vaccination period using a machine learning approach
Background: The clinical manifestations of COVID-19 disease, caused by the SARS-CoV-2 virus, define a large spectrum of symptoms that are mainly dependent on the human host conditions. In Costa Rica, almost 319 000 cases ...
Predicting Cancer Chemosensitivity Based on Intensity/Distribution Profiles of Cells Loaded with a Fluorescent Sphingolipid Analogue
Cancer is a group of heterogeneous and complex diseases, with limited therapeutic options due to the recurrent emergence of drug resistance. Sphingolipids are bioactive molecules that participate in signaling of cell ...
Hybrid mathematical modeling decodes the complexity of sphingolipid pathway to predict chemosensitivity
Sphingolipid (SL) signaling pathway is a complex biological system able to integrate different types of cellular stress signals related to induction of cell death pathways with special interest in cancer. This makes of ...
Characterization of heterogeneous response to chemotherapy by perturbation-based modeling of fluorescent sphingolipid metabolism in cancer cell subpopulations
Cancer treatments options are limited by the generation of therapy resistance, which is due by intratumoral heterogeneity in cell response. The study of resistance requires biosensors able to report the response at the ...