Esports players,got muscle? Competitive video game players’ physical activity,body fat,bone mineral content,and muscle mass in comparison to matched controls

BackgroundEsports players, like traditional athletes, practice for long hours and, thus, are vulnerable to the negative health effects of prolonged sitting. There is a lack of research on the physical activity and the health ramifications of prolonged sitting by competitive players. The purpose of this study was to investigate activity levels, body mass index (BMI), and body composition in collegiate esports players as compared to age-matched controls.MethodsTwenty-four male collegiate esports players and non-esports players between 18 and 25 years of age signed a written consent to participate. Physical activity was examined using daily activity (step count) with a wrist-worn activity tracker. A questionnaire assessing physical activity was also administered. Secondary outcomes included body-fat percentage, lean-body mass, BMI, and bone mineral content measured using dual X-ray absorptiometry.ResultsThe step count in the esports players was significantly lower than the age-matched controls (6040.2 ± 3028.6 vs. 12843.8 ± 5661.1; p = 0.004). Esports players exhibited greater body-fat percentage (p = 0.05), less lean body mass (p = 0.003), and less bone mineral content (p = 0.03), despite no difference in BMI between the esports and non-esports players.ConclusionAs compared to non-esports players, collegiate esports players were significantly less active and had a higher body-fat percentage, with lower lean body mass and bone mineral content. The BMIs showed no difference between the 2 groups. Esports athletes displayed significantly less activity and poor body composition, which are all correlated with potential health issues and risk of injury. BMI did not capture this difference and should not be considered as an accurate measure of health in competitive esports players.     

A CRISPR/Cas12a-empowered surface plasmon resonance platform for rapid and specific diagnosis of the Omicron variant of SARS-CoV-2

The outbreak of the COVID-19 pandemic was partially due to the challenge of identifying asymptomatic and presymptomatic carriers of the virus, and thus highlights a strong motivation for diagnostics with high sensitivity that can be rapidly deployed. On the other hand, several concerning SARS-CoV-2 variants, including Omicron, are required to be identified as soon as the samples are identified as ‘positive’. Unfortunately, a traditional PCR test does not allow their specific identification. Herein, for the first time, we have developed MOPCS (Methodologies of Photonic CRISPR Sensing), which combines an optical sensing technology-surface plasmon resonance (SPR) with the ‘gene scissors’ clustered regularly interspaced short palindromic repeat (CRISPR) technique to achieve both high sensitivity and specificity when it comes to measurement of viral variants. MOPCS is a low-cost, CRISPR/Cas12a-system-empowered SPR gene-detecting platform that can analyze viral RNA, without the need for amplification, within 38 min from sample input to results output, and achieve a limit of detection of 15 fM. MOPCS achieves a highly sensitive analysis of SARS-CoV-2, and mutations appear in variants B.1.617.2 (Delta), B.1.1.529 (Omicron) and BA.1 (a subtype of Omicron). This platform was also used to analyze some recently collected patient samples from a local outbreak in China, identified by the Centers for Disease Control and Prevention. This innovative CRISPR-empowered SPR platform will further contribute to the fast, sensitive and accurate detection of target nucleic acid sequences with single-base mutations.