Tracing contacts to evaluate the transmission of COVID-19 from highly exposed individuals in public transportation.

We investigate, through a data-driven contact tracing model, the transmission of COVID-19 inside buses during distinct phases of the pandemic in a large Brazilian city. From this microscopic approach, we recover the networks of close contacts within consecutive time windows. A longitudinal comparison is then performed by upscaling the traced contacts with the transmission computed from a mean-field compartmental model for the entire city. Our results show that the effective reproduction numbers inside the buses, [Formula: see text], and in the city, [Formula: see text], followed a compatible behavior during the first wave of the local outbreak. Moreover, by distinguishing the close contacts of healthcare workers in the buses, we discovered that their transmission, [Formula: see text], during the same period, was systematically higher than [Formula: see text]. This result reinforces the need for special public transportation policies for highly exposed groups of people.

Different Signatures of High Cardiorespiratory Capacity Revealed With Metabolomic Profiling in Elite Athletes.

PURPOSE: High cardiorespiratory capacity is a key determinant of human performance and life expectancy; however, the underlying mechanisms are not fully understood. The objective of this pilot study was to investigate biochemical signatures of endurance-performance athletes using high-resolution nontargeted metabolomics. METHODS: Elite long-distance runners with similar training and anthropometrical records were studied. After athletes' maximal oxygen consumption (V˙O2max) was measured, they were divided into 2 groups: low V˙O2max (<65 mL·kg-1·min-1, n = 7) and high V˙O2max (>75 mL·kg-1·min-1, n = 7). Plasma was collected under basal conditions after 12 hours of fasting and after a maximal exercise test (nonfasted) and analyzed by high-resolution LC-MS. Multivariate and univariate statistics were applied. RESULTS: A total of 167 compounds were putatively identified with an LC-MS-based metabolomics pipeline. Partial least-squares discriminant analysis showed a clear separation between groups. Significant variations in metabolites highlighted group differences in diverse metabolic pathways, including lipids, vitamins, amino acids, purine, histidine, xenobiotics, and others, either under basal condition or after the maximal exercise test. CONCLUSIONS: Taken together, the metabolic alterations revealed in the study affect cellular energy use and availability, oxidative stress management, muscle damage, central nervous system signaling metabolites, nutrients, and compound bioavailability, providing new insights into metabolic alterations associated with exercise and cardiorespiratory fitness levels in trained athletes.