Dynamic associations between the respiratory tract and gut antibiotic resistome of patients with COVID-19 and its prediction power for disease severity.

The antibiotic resistome is the collection of all antibiotic resistance genes (ARGs) present in an individual. Whether an individual's susceptibility to infection and the eventual severity of coronavirus disease 2019 (COVID-19) is influenced by their respiratory tract antibiotic resistome is unknown. Additionally, whether a relationship exists between the respiratory tract and gut ARGs composition has not been fully explored. We recruited 66 patients with COVID-19 at three disease stages (admission, progression, and recovery) and conducted a metagenome sequencing analysis of 143 sputum and 97 fecal samples obtained from them. Respiratory tract, gut metagenomes, and peripheral blood mononuclear cell (PBMC) transcriptomes are analyzed to compare the gut and respiratory tract ARGs of intensive care unit (ICU) and non-ICU (nICU) patients and determine relationships between ARGs and immune response. Among the respiratory tract ARGs, we found that Aminoglycoside, Multidrug, and Vancomycin are increased in ICU patients compared with nICU patients. In the gut, we found that Multidrug, Vancomycin, and Fosmidomycin were increased in ICU patients. We discovered that the relative abundances of Multidrug were significantly correlated with clinical indices, and there was a significantly positive correlation between ARGs and microbiota in the respiratory tract and gut. We found that immune-related pathways in PBMC were enhanced, and they were correlated with Multidrug, Vancomycin, and Tetracycline ARGs. Based on the ARG types, we built a respiratory tract-gut ARG combined random-forest classifier to distinguish ICU COVID-19 patients from nICU patients with an AUC of 0.969. Cumulatively, our findings provide some of the first insights into the dynamic alterations of respiratory tract and gut antibiotic resistome in the progression of COVID-19 and disease severity. They also provide a better understanding of how this disease affects different cohorts of patients. As such, these findings should contribute to better diagnosis and treatment scenarios.

Driving mechanism of farmers' green production behavior under normalization of COVID-19 prevention and control: A case study in China

China's public health emergency COVID-19 has brought great challenges to food safety. Among them, the quality and safety of agricultural products under the normalization of the COVID-19 prevention and control has become a hot issue of general concern. This study attempts to reveal the driving factors and mechanisms of farmers' green production behavior. The empirical research by collecting 673 sample data shows that: individual characteristics of farmers, government guiding factors, an industrial organization promoting factors, and market adjustment factors have a positive driving effect on farmers' green production behavior. And farmers' green production behavior has a positive influence on the quality and safety of agricultural products. Farmers' green production behavior plays an intermediary role between the quality and safety of agricultural products and individual characteristics of farmers, government guidance factors, industrial organization promotion factors, and market regulation factors. The results of the study have guiding significance for ensuring the quality and safety of agricultural products, promoting ecological environmental protection, and sustainable agricultural development under the normalization of COVID-19 prevention and control.

Dynamic Alterations in the Respiratory Tract Microbiota of Patients with COVID-19 and its Association with Microbiota in the Gut.

The role of respiratory tract microbes and the relationship between respiratory tract and gut microbiomes in coronavirus disease 2019 (COVID-19) remain uncertain. Here, the metagenomes of sputum and fecal samples from 66 patients with COVID-19 at three stages of disease progression are sequenced. Respiratory tract, gut microbiome, and peripheral blood mononuclear cell (PBMC) samples are analyzed to compare the gut and respiratory tract microbiota of intensive care unit (ICU) and non-ICU (nICU) patients and determine relationships between respiratory tract microbiome and immune response. In the respiratory tract, significantly fewer Streptococcus, Actinomyces, Atopobium, and Bacteroides are found in ICU than in nICU patients, while Enterococcus and Candida increase. In the gut, significantly fewer Bacteroides are found in ICU patients, while Enterococcus increases. Significant positive correlations exist between relative microbiota abundances in the respiratory tract and gut. Defensin-related pathways in PBMCs are enhanced, and respiratory tract Streptococcus is reduced in patients with COVID-19. A respiratory tract-gut microbiota model identifies respiratory tract Streptococcus and Atopobium as the most prominent biomarkers distinguishing between ICU and nICU patients. The findings provide insight into the respiratory tract and gut microbial dynamics during COVID-19 progression, considering disease severity, potentially contributing to diagnosis, and treatment strategies.

Decision-Making Behaviour Evolution Among Pork Supply and Demand Subjects Under Normalisation of COVID-19 Prevention and Control: A Case Study in China.

Affected by the coronavirus disease 2019 (COVID-19), there were short-term uncertainties in China's live pig industry supply chain. Due to the insufficient supply of pork, the price of pork rose from 33.21 yuan/kg at the end of 2019 to 37.46 yuan/kg in mid-February and fell to 26.41 yuan/kg in mid-May. To restore pig supply and stabilise prices, China issued relevant policies. Given the current effective control of COVID-19 in China, this paper constructed an evolutionary game model of China's pork supply and demand stakeholders under normalisation of COVID-19 prevention and control, analysed the behavioural strategies of consumers, government, and pig farmers, used MATLAB software for data simulation, and expounded on the evolution path and the characteristic rule of tripartite decision-making behaviours. The results showed that government supervision costs, evaluation of government by consumers and pig farmers, government subsidies to pig farmers and consumers, and the proportion of stakeholder behaviours affected the formation of tripartite relationships. The results provide a useful reference for the government to formulate effective policies, increase pig supply, and stabilise pork prices.

Serum level of testosterone predicts disease severity of male COVID-19 patients and is related to T-cell immune modulation by transcriptome analysis.

BACKGROUND: Severe disease of COVID-19 and mortality occur more frequently in male patients than that in female patients may be related to testosterone level. However, the diagnostic value of changes in the level of testosterone in predicting severe disease of male COVID-19 patients has not been determined yet. METHODS: Sixty-one male COVID-19 patients admitted to the First Affiliated Hospital of Zhejiang University School of Medicine were enrolled. Serum samples at different stages of the patients after admission were collected and testosterone levels were detected to analyze the correlation between testosterone level and disease severity. Transcriptome analysis of PBMC was performed in 34 patients. RESULTS: Testosterone levels at admission in male non-ICU COVID-19 patients (3.7 nmol/L, IQR: 1.5 âˆ¼ 4.7) were significantly lower than those in male ICU COVID-19 patients (6.7 nmol/L, IQR: 4.2 âˆ¼ 8.7). Testosterone levels in the non-ICU group increased gradually during the progression of the disease, while those in the ICU group remained low. In addition, testosterone level of enrolled patients in the second week after onset was significantly correlated with the severity of pneumonia, and ROC curve showed that testosterone level in the second week after onset was highly effective in predicting the severity of COVID-19. Transcriptome studies have found that testosterone levels of COVID-19 patients were associated with immune response, including T cell activation and regulation of lymphocyte activation. In addition, CD28 and Inositol Polyphosphate-4-Phosphatase Type II B (INPP4B) were found positively correlated with testosterone. CONCLUSIONS: Serum testosterone is an independent risk factor for predicting the severity of COVID-19 in male patients, and the level of serum testosterone in the second week after onset is valuable for evaluating the severity of COVID-19. Testosterone level is associated with T cell immune activation. The monitoring of serum testosterone should be highlighted in clinical treatment and the related mechanism should be further studied.

Hock-a-loogie saliva as a diagnostic specimen for SARS-CoV-2 by a PCR-based assay: A diagnostic validity study.

To clarify the effect of different respiratory sample types on SARS-CoV-2 detection, we collected throat swabs, nasal swabs and hock-a-loogie saliva or sputum, and compared their detection rates and viral loads. The detection rates of sputum (95.65%, 22/23) and hock-a-loogie saliva (88.09%, 37/42) were significantly higher than those in throat swabs (41.54%, 27/65) and nasal swabs (72.31%, 47/65) (P < 0.001). The Ct Values of sputum, hock-a-loogie saliva and nasal swabs were significantly higher than that in throat swabs, whereas no significant difference was observed between sputum and saliva samples. Hock-a-loogie saliva are reliable sample types that can be used to detect SARS-CoV-2, and worthy of clinical promotion.

Plant-derived exosomal microRNAs inhibit lung inflammation induced by exosomes SARS-CoV-2 Nsp12.

Lung inflammation is a hallmark of coronavirus disease 2019 (COVID-19). In this study, we show that mice develop inflamed lung tissue after being administered exosomes released from the lung epithelial cells exposed to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Nsp12 and Nsp13 (exosomesNsp12Nsp13). Mechanistically, we show that exosomesNsp12Nsp13 are taken up by lung macrophages, leading to activation of nuclear factor κB (NF-κB) and the subsequent induction of an array of inflammatory cytokines. Induction of tumor necrosis factor (TNF)-α, interleukin (IL)-6, and IL-1ß from exosomesNsp12Nsp13-activated lung macrophages contributes to inducing apoptosis in lung epithelial cells. Induction of exosomesNsp12Nsp13-mediated lung inflammation was abolished with ginger exosome-like nanoparticle (GELN) microRNA (miRNA aly-miR396a-5p. The role of GELNs in inhibition of the SARS-CoV-2-induced cytopathic effect (CPE) was further demonstrated via GELN aly-miR396a-5p- and rlcv-miR-rL1-28-3p-mediated inhibition of expression of Nsp12 and spike genes, respectively. Taken together, our results reveal exosomesNsp12Nsp13 as potentially important contributors to the development of lung inflammation, and GELNs are a potential therapeutic agent to treat COVID-19.