Microbial Signatures in COVID-19: Distinguishing Mild and Severe Disease via Gut Microbiota.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has significantly impacted global healthcare, underscoring the importance of exploring the virus's effects on infected individuals beyond treatments and vaccines. Notably, recent findings suggest that SARS-CoV-2 can infect the gut, thereby altering the gut microbiota. This study aimed to analyze the gut microbiota composition differences between COVID-19 patients experiencing mild and severe symptoms. We conducted 16S rRNA metagenomic sequencing on fecal samples from 49 mild and 43 severe COVID-19 cases upon hospital admission. Our analysis identified a differential abundance of specific bacterial species associated with the severity of the disease. Severely affected patients showed an association with Enterococcus faecium, Akkermansia muciniphila, and others, while milder cases were linked to Faecalibacterium prausnitzii, Alistipes putredinis, Blautia faecis, and additional species. Furthermore, a network analysis using SPIEC-EASI indicated keystone taxa and highlighted structural differences in bacterial connectivity, with a notable disruption in the severe group. Our study highlights the diverse impacts of SARS-CoV-2 on the gut microbiome among both mild and severe COVID-19 patients, showcasing a spectrum of microbial responses to the virus. Importantly, these findings align, to some extent, with observations from other studies on COVID-19 gut microbiomes, despite variations in methodologies. The findings from this study, based on retrospective data, establish a foundation for future prospective research to confirm the role of the gut microbiome as a predictive biomarker for the severity of COVID-19.

Evaluation of serum and urine biomarkers for severe COVID-19.

Introduction: The new coronavirus disease, COVID-19, poses complex challenges exacerbated by several factors, with respiratory tissue lesions being notably significant among them. Consequently, there is a pressing need to identify informative biological markers that can indicate the severity of the disease. Several studies have highlighted the involvement of proteins such as APOA1, XPNPEP2, ORP150, CUBN, HCII, and CREB3L3 in these respiratory tissue lesions. However, there is a lack of information regarding antibodies to these proteins in the human body, which could potentially serve as valuable diagnostic markers for COVID-19. Simultaneously, it is relevant to select biological fluids that can be obtained without invasive procedures. Urine is one such fluid, but its effect on clinical laboratory analysis is not yet fully understood due to lack of study on its composition. Methods: Methods used in this study are as follows: total serum protein analysis; ELISA on moderate and severe COVID-19 patients' serum and urine; bioinformatic methods: ROC analysis, PCA, SVM. Results and discussion: The levels of antiAPOA1, antiXPNPEP2, antiORP150, antiCUBN, antiHCII, and antiCREB3L3 exhibit gradual fluctuations ranging from moderate to severe in both the serum and urine of COVID-19 patients. However, the diagnostic value of individual anti-protein antibodies is low, in both blood serum and urine. On the contrary, joint detection of these antibodies in patients' serum significantly increases the diagnostic value as demonstrated by the results of principal component analysis (PCA) and support vector machine (SVM). The non-linear regression model achieved an accuracy of 0.833. Furthermore, PCA aided in identifying serum protein markers that have the greatest impact on patient group discrimination. The study revealed that serum serves as a superior analyte for describing protein quantification due to its consistent composition and lack of organic salts and drug residues, which can otherwise affect protein stability.

Risk Factors for Heart Disease in Working Railwaymen.

Heart diseases are the most common non-communicable diseases worldwide. We examined the prevalence of risk factors for heart disease among a sub-population of working men. In total, 11,059 railway crew workers of the Russian Railways Company were included in the study. We also asked participants to answer several questions based on the WHO STEPwise approach to surveillance (STEPS) translated into Russian. Only 30% of drivers had normal body mass index (BMI), whereas 70% were overweight or obese. In 12% of subjects, total cholesterol was higher than 5 mmol/L. In 15% of participants, glucose level was higher than 5.5 mmol/L. 38% of drivers reported smoking. Physical inactivity was registered in 54% of persons. Only 29% ate according to the key principles of good diet quality. 24% of respondents had a family history of heart disease. MANOVA demonstrated that BMI was determined by age, profession, smoking, physical inactivity, and diet quality. As age increased, the number of people with normal cholesterol levels decreased. It was demonstrated that a correlation existed between glucose levels and BMI. In the total group, the correlation was 0.46 (p < .05). The correlation between those parameters increased due to age, from 0.33 in the <30 years of age group up to 0.52 in the >50 years of age group. This study demonstrated that there is a high prevalence of risk factors for heart disease in train drivers in the Russian Federation.

Prevalence and Risk of Dental Erosion in Patients with Gastroesophageal Reflux Disease: A Meta-Analysis.

AIM: The present paper aims to systematize data concerning the prevalence and risk of dental erosion (DE) in adult patients with gastroesophageal reflux disease (GERD) compared to controls. MATERIALS AND METHODS: Core electronic databases, i.e., MEDLINE/PubMed, EMBASE, Cochrane, Google Scholar, and the Russian Science Citation Index (RSCI), were searched for studies assessing the prevalence and risk of DE in adult GERD patients with publication dates ranging from 1 January 1985 to 20 January 2022. Publications with detailed descriptive statistics (the total sample size of patients with GERD, the total sample size of controls (if available), the number of patients with DE in the sample of GERD patients, the number of patients with DE in the controls (if available)) were selected for the final analysis. RESULTS: The final analysis included 28 studies involving 4379 people (2309 GERD patients and 2070 control subjects). The pooled prevalence of DE was 51.524% (95 CI: 39.742-63.221) in GERD patients and 21.351% (95 CI: 9.234-36.807) in controls. An association was found between the presence of DE and GERD using the random-effects model (OR 5.000, 95% CI: 2.995-8.345; I2 = 79.78%) compared with controls. When analyzing studies that only used validated instrumental methods for diagnosing GERD, alongside validated DE criteria (studies that did not specify the methodologies used were excluded), a significant association between the presence of DE and GERD was revealed (OR 5.586, 95% CI: 2.311-13.503; I2 = 85.14%). CONCLUSION: The meta-analysis demonstrated that DE is quite often associated with GERD and is observed in about half of patients with this extremely common disease of the upper gastrointestinal tract.

Risk Factors for Locomotive Crew Members Depending on Their Place of Work.

PURPOSE: The purpose of this study is to examine the prevalence of workplace exposure, behavior, and individual health conditions, along with resulting medical activity among locomotive crew members depending on their place of work. PATIENTS AND METHODS: Participants included 5585 train drivers and 3723 train drivers' assistants (7% of the total train operators in the Russian Federation). Measured height and weight were used to calculate body mass index (BMI), and waist circumference, pulse rate, and blood pressure were also measured. The risk assessment was conducted using the STEPS tool. The level of commitment to a Healthy Lifestyle was assessed based on World Health Organization recommendations. Occupational risk factors were surveyed. Morbidity was analyzed over the past year. RESULTS: The lowest frequency of work exposure risk factors was found for employees of the Trans-Baikal railway; the highest was among Krasnoyarsk, North, and South-East. The participants from the Far East and October Railways had the lowest self-reported frequency of behavioral risk factors. The participants from the Eastern Siberian, October, and Southern Urals railways had the lowest occurrence of individual health conditions. The participants from the East Siberian, Far East, Kuibyshev, and Sverdlovsk railways were the least likely to visit their doctor, take temporary disability leave, or be hospitalized. The total assessed Healthy Lifestyle commitment index was higher for participants from the Far Eastern and Southern Urals railways. The participants from the Moscow and October railways were the least committed to a Healthy Lifestyle. CONCLUSIONS: Significant differences exist between risk factors and Healthy Lifestyle commitment between railways. Future research should examine changes due to a new corporate health program introduced in 2020.