A generalized equation for predicting peak oxygen consumption during treadmill exercise testing: mitigating the bias from total body mass scaling.

Background: Indexing peak oxygen uptake (VOpeak) to total body mass can underestimate cardiorespiratory fitness (CRF) in women, older adults, and individuals with obesity. The primary objective of this multicenter study was to derive and validate a body size-independent scaling metric for VOpeak. This metric was termed exercise body mass (EBM).

Integrating Metabolomics Domain Knowledge with Explainable Machine Learning in Atherosclerotic Cardiovascular Disease Classification.

Metabolomic data often present challenges due to high dimensionality, collinearity, and variability in metabolite concentrations. Machine learning (ML) application in metabolomic analyses is enabling the extraction of meaningful information from complex data. Bringing together domain-specific knowledge from metabolomics with explainable ML methods can refine the predictive performance and interpretability of models used in atherosclerosis research.

The development of an analytical procedure for the determination of microplastics in freshwater ecosystems.

Microplastics raise growing concerns regarding their ubiquity and possible negative impact on human health; therefore, the need for comparable, standardized methods is urgent. Modern instrumental analytical techniques, such as IR and Raman spectroscopy, pyrolysis-gas chromatography-mass spectrometry and electron microscopy, are fundamental for the analysis of microplastics in environmental and biological objects. The quality of the samples prepared is a determining factor in the validity of the results obtained.