Vitamin E Reduces Hypobaric Hypoxia-Induced Immune Responses in Male Rats

Global Metabolomics of Fireflies (Coleoptera: Lampyridae) Explore Metabolic Adaptation to Fresh Water in Insects

Aquatic insects are well-adapted to freshwater environments, but metabolic mechanisms of such adaptations, particularly to primary environmental factors (e.g., hypoxia, water pressure, dark light, and abundant microbes), are poorly known. Most firefly species (Coleoptera: Lampyridae) are terrestrial, but the larvae of a few species are aquatic. We generated 24 global metabolomic profiles of larvae and adults of Aquatica leii (freshwater) and Lychnuris praetexta (terrestrial) to identify freshwater adaptation-related metabolites (AARMs). We identified 110 differentially abundant metabolites (DAMs) in A. leii (adults vs. aquatic larvae) and 183 DAMs in L. praetexta (adults vs. terrestrial larvae). Furthermore, 100 DAMs specific to aquatic A. leii larvae were screened as AARMs via interspecific comparisons (A. leii vs. L. praetexta), which were primarily involved in antioxidant activity, immune response, energy production and metabolism, and chitin biosynthesis. They were assigned to six categories/superclasses (e.g., lipids and lipid-like molecules, organic acids and derivatives, and organoheterocyclic compound). Finally, ten metabolic pathways shared between KEGG terms specific to aquatic fireflies and enriched by AARMs were screened as aquatic adaptation-related pathways (AARPs). These AARPs were primarily involved in energy metabolism, xenobiotic biodegradation, protection of oxidative/immune damage, oxidative stress response, and sense function (e.g., glycine, serine and threonine metabolism, drug metabolism-cytochrome P450, and taste transduction), and certain aspects of morphology (e.g., steroid hormone biosynthesis). These results provide evidence suggesting that abundance changes in metabolomes contribute to freshwater adaptation of fireflies. The metabolites identified here may be vital targets for future work to determine the mechanism of freshwater adaptation in insects.

Exposure to hypoxia causes stress erythropoiesis and downregulates immune response genes in spleen of mice

BACKGROUND

The spleen is the largest secondary lymphoid organ and the main site where stress erythropoiesis occurs. It is known that hypoxia triggers the expansion of erythroid progenitors; however, its effects on splenic gene expression are still unclear. Here, we examined splenic global gene expression patterns by time-series RNA-seq after exposing mice to hypoxia for 0, 1, 3, 5, 7 and 13 days.

RESULTS

Morphological analysis showed that on the 3rd day there was a significant increase in the spleen index and in the proliferation of erythroid progenitors. RNA-sequencing analysis revealed that the overall expression of genes decreased with increased hypoxic exposure. Compared with the control group, 1380, 3430, 4396, 3026, and 1636 genes were differentially expressed on days 1, 3, 5, 7 and 13, respectively. Clustering analysis of the intersection of differentially expressed genes pointed to 739 genes, 628 of which were upregulated, and GO analysis revealed a significant enrichment for cell proliferation. Enriched GO terms of downregulated genes were associated with immune cell activation. Expression of Gata1, Tal1 and Klf1 was significantly altered during stress erythropoiesis. Furthermore, expression of genes involved in the immune response was inhibited, and NK cells decreased.

CONCLUSIONS

The spleen of mice conquer hypoxia exposure in two ways. Stress erythropoiesis regulated by three transcription factors and genes in immune response were downregulated. These findings expand our knowledge of splenic transcriptional changes during hypoxia.

Antioxidants and Exercise Performance: With a Focus on Vitamin E and C Supplementation

Antioxidant supplementation, including vitamin E and C supplementation, has recently received recognition among athletes as a possible method for enhancing athletic performance. Increased oxidative stress during exercise results in the production of free radicals, which leads to muscle damage, fatigue, and impaired performance. Despite their negative effects on performance, free radicals may act as signaling molecules enhancing protection against greater physical stress. Current evidence suggests that antioxidant supplementation may impair these adaptations. Apart from athletes training at altitude and those looking for an immediate, short-term performance enhancement, supplementation with vitamin E does not appear to be beneficial. Moreover, the effectiveness of vitamin E and C alone and/or combined on muscle mass and strength have been inconsistent. Given that antioxidant supplements (e.g., vitamin E and C) tend to block anabolic signaling pathways, and thus, impair adaptations to resistance training, special caution should be taken with these supplements. It is recommended that athletes consume a diet rich in fruits and vegetables, which provides vitamins, minerals phytochemicals, and other bioactive compounds to meet the recommended intakes of vitamin E and C.

Prediction of the Rehabilitation Duration and Risk Management for Mild-Moderate COVID-19

Objectives:

More than 80% of coronavirus disease 2019 (COVID-19) cases are mild or moderate. In this study, a risk model was developed for predicting rehabilitation duration (the time from hospital admission to discharge) of the mild-moderate COVID-19 cases and was used to conduct refined risk management for different risk populations.

Methods:

A total of 90 consecutive patients with mild-moderate COVID-19 were enrolled. Large-scale datasets were extracted from clinical practices. Through the multivariable linear regression analysis, the model was based on significant risk factors and was developed for predicting the rehabilitation duration of mild-moderate cases of COVID-19. To assess the local epidemic situation, risk management was conducted by weighing the risk of populations at different risk.

Results:

Ten risk factors from 44 high-dimensional clinical datasets were significantly correlated to rehabilitation duration (P < 0.05). Among these factors, 5 risk predictors were incorporated into a risk model. Individual rehabilitation durations were effectively calculated. Weighing the local epidemic situation, threshold probability was classified for low risk, intermediate risk, and high risk. Using this classification, risk management was based on a treatment flowchart tailored for clinical decision-making.

Conclusions:

The proposed novel model is a useful tool for individualized risk management of mild-moderate COVID-19 cases, and it may readily facilitate dynamic clinical decision-making for different risk populations.