Optimizing intervertebral disc cell metabolic phenotyping with machine learning and artificial neural networks.

ABSTRACT: Biological phenotyping of cellular metabolism is essential for deciphering health and disease states. The Seahorse XF analyzer enables direct measurement of oxygen consumption rate (OCR) and extracellular acidification rate (ECAR), providing insight into mitochondrial function and glycolytic activity in living cells. Accurate phenotyping requires meticulous preparation, including forming a uniform cell monolayer and carefully titrating critical reagents such as the uncoupler carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone (FCCP), to ensure precise and reproducible bioenergetic measurements. Artificial neural networks (ANN) and machine learning (ML) algorithms serve as powerful tools for analyzing experimental findings, enhancing the accuracy of result predictions, and reducing the num

SUBMITTER: Bahar ME 

PROVIDER: S-EPMC12722773 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature