Association between vitamin B2 intake and prostate-specific antigen in American men: 2003-2010 National Health and Nutrition Examination Survey.

BACKGROUND: Accumulating evidence suggests a pivotal role of vitamin B2 in the pathogenesis and progression of prostate cancer (PCa). Vitamin B2 intake has been postulated to modulate the screening rate for PCa by altering the concentration of prostate-specific antigen(PSA). However, the relationship between vitamin B2 and PSA remains indeterminate. Hence, we conducted a comprehensive evaluation of the association between vitamin B2 intake and PSA levels, utilizing data from the National Health and Nutrition Examination Survey (NHANES) database. METHODS: From a pool of 20,371 participants in the NHANES survey conducted between 2003 and 2010, a cohort of 2,323 participants was selected for the present study. The male participants were classified into four distinct groups based on their levels of vitamin B2 intake. We employed a multiple linear regression model and a non-parametric regression method to investigate the relationship between vitamin B2 and PSA levels. RESULTS: The study cohort comprised of 2,323 participants with a mean age of 54.95 years (± 11.73). Our findings revealed a statistically significant inverse correlation between vitamin B2 intake (mg) and PSA levels, with a reduction of 0.13 ng/ml PSA concentration for every unit increase in vitamin B2 intake. Furthermore, we employed a fully adjusted model to construct a smooth curve to explore the possible linear relationship between vitamin B2 intake and PSA concentration. CONCLUSIONS: Our study in American men has unveiled a notable inverse association between vitamin B2 intake and PSA levels, potentially posing a challenge for the identification of asymptomatic prostate cancer. Specifically, our findings suggest that individuals with higher vitamin B2 intake may be at a greater risk of being diagnosed with advanced prostate cancer in the future, possibly indicating a detection bias. These results may offer a novel explanation for the observed positive correlation between vitamin B2 intake and prostate cancer.

Association of dietary live microbe intake with various cognitive domains in US adults aged 60 years or older.

The purpose of this study was to explore whether dietary live microbe intake is associated with various cognitive domains using data from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2014. And the specific relationship between low, medium and high dietary live microbe intake groups and cognitive ability of the elderly. Dietary live microbe intake was calculated from 24-h diet recall interviews. Cognitive function was assessed using the number symbol substitution test (DSST, which measures processing speed), the animal fluency test (AFT, which measures executive function), the Alzheimer's Registry sub-test (CERAD, which measures memory), and the Composite Z-score, which adds the Z-values of individual tests. Multiple linear regression models and restricted cubic bar graphs were used to investigate the relationship between live microbe intake and cognitive performance. A total of 2,450 participants aged 60 or older were included. Live microbe intake was positively correlated with cognitive ability on the whole. Specifically, when the intake of low, medium and high live microbe was > 2640 g, > 39 g and > 0 g respectively, the CERAD, DSST, AFT and compositive-Z score of the subjects increased with the increase of microbial intake (P < 0.05). In American adults age 60 or older, higher intakes of live microbes were associated with better cognitive performance, especially after a certain amount was reached.

Assessing volatile organic compounds exposure and chronic obstructive pulmonary diseases in US adults.

Background: Volatile organic compounds (VOCs) are a large group of chemicals widely used in People's Daily life. There is increasing evidence of the cumulative toxicity of VOCs. However, the association between VOCs and the risk of COPD has not been reported. Objective: We comprehensively evaluated the association between VOCs and COPD. Methods: Our study included a total of 1,477 subjects from the National Health and Nutrition Examination Survey, including VOCs, COPD, and other variables in the average US population. Multiple regression models and smooth-curve fitting (penalty splines) were constructed to examine potential associations, and stratified analyses were used to identify high-risk groups. Results: We found a positive association between blood benzene and blood o-xylene concentrations and COPD risk and identified a concentration relationship between the two. That is, when the blood benzene and O-xylene concentrations reached 0.28 ng/mL and 0.08 ng/mL, respectively, the risk of COPD was the highest. In addition, we found that gender, age, and MET influence the relationship, especially in women, young people, and people with low MET. Significance: This study revealed that blood benzene and blood o-xylene were independently and positively correlated with COPD risk, suggesting that long-term exposure to benzene and O-xylene may cause pulmonary diseases, and providing a new standard of related blood VOCs concentration for the prevention of COPD.

Effect of SARS-CoV-2 infection on asthma patients.

Background: SARS-CoV-2 causes coronavirus disease 2019 (COVID-19), a new coronavirus pneumonia, and containing such an international pandemic catastrophe remains exceedingly difficult. Asthma is a severe chronic inflammatory airway disease that is becoming more common around the world. However, the link between asthma and COVID-19 remains unknown. Through bioinformatics analysis, this study attempted to understand the molecular pathways and discover potential medicines for treating COVID-19 and asthma. Methods: To investigate the relationship between SARS-CoV-2 and asthma patients, a transcriptome analysis was used to discover shared pathways and molecular signatures in asthma and COVID-19. Here, two RNA-seq data (GSE147507 and GSE74986) from the Gene Expression Omnibus were used to detect differentially expressed genes (DEGs) in asthma and COVID-19 patients to find the shared pathways and the potential drug candidates. Results: There were 66 DEGs in all that were classified as common DEGs. Using a protein-protein interaction (PPI) network created using various bioinformatics techniques, five hub genes were found. We found that asthma has some shared links with the progression of COVID-19. Additionally, protein-drug interactions with common DEGs were also identified in the datasets. Conclusion: We investigated possible links between COVID-19 and asthma using bioinformatics databases, which might be useful in treating COVID-19 patients. More studies on populations affected by these diseases are needed to elucidate the molecular mechanism behind their association.

Clinical Implications of Necroptosis Genes Expression for Cancer Immunity and Prognosis: A Pan-Cancer Analysis.

Background: Necroptosis, a form of programmed cell death, is increasingly being investigated for its controversial role in tumorigenesis and progression. Necroptosis suppresses tumor formation and tumor development by killing tumor cells; however, the necrotic cells also promote tumor formation and tumor development via the immunosuppressive effect of necroptosis and inflammatory response caused by cytokine release. Thus, the exact mechanism of necroptosis in pan-cancer remains unknown. Methods: The data of 11,057 cancer samples were downloaded from the TCGA database, along with clinical information, tumor mutation burden, and microsatellite instability information of the corresponding patients. We used the TCGA data in a pan-cancer analysis to identify differences in mRNA level as well as single nucleotide variants, copy number variants, methylation profiles, and genomic signatures of miRNA-mRNA interactions. Two drug datasets (from GDSC, CTRP) were used to evaluate drug sensitivity and resistance against necroptosis genes. Results: Necroptosis genes were aberrantly expressed in various cancers. The frequency of necroptosis gene mutations was highest in lung squamous cell carcinoma. Furthermore, the correlation between necroptosis gene expression in the tumor microenvironment and immune cell infiltration varied for different cancers. High necroptosis gene expression was found to correlate with NK, Tfh, Th1, CD8_T, and DC cells. These can therefore be used as biomarkers to predict prognosis. By matching gene targets with drugs, we identified potential candidate drugs. Conclusion: Our study showed the genomic alterations and clinical features of necroptosis genes in 33 cancers. This may help clarify the link between necroptosis and tumorigenesis. Our findings may also provide new approaches for the clinical treatment of cancer.

m7G Methylation-Related Genes as Biomarkers for Predicting Overall Survival Outcomes for Hepatocellular Carcinoma.

Aim: The search for prognostic biomarkers and the construction of a prognostic risk model for hepatocellular carcinoma (HCC) based on N7-methyladenosine (m7G) methylation regulators. Methods: HCC transcriptomic data and clinical data were obtained from The Cancer Genome Atlas database and Shanghai Ninth People's Hospital, respectively. m7G methylation regulators were extracted, differential expression analysis was performed using the R software "limma" package, and one-way Cox regression analysis was used to screen for prognostic associations of m7G regulators. Using multi-factor Cox regression analysis, a prognostic risk model for HCC was constructed. Each patient's risk score was calculated using the model, and patients were divided into high- and low-risk groups according to the median risk score. Cox regression analysis was used to verify the validity of the model in the prognostic assessment of HCC in conjunction with clinicopathological characteristics. Results: The prognostic model was built using the seven genes, namely, CYFIP1, EIF4E2, EIF4G3, GEMIN5, NCBP2, NUDT10, and WDR4. The Kaplan-Meier survival analysis showed poorer 5-years overall survival in the high-risk group compared with the low-risk group, and the receiver-operating characteristic (ROC) curve suggested good model prediction (area under the curve AUC = 0.775, 0.820, and 0.839 at 1, 3, and 5 years). The Cox regression analysis included model risk scores and clinicopathological characteristics, and the results showed that a high-risk score was the only independent risk factor for the prognosis of patients with HCC. Conclusions: The developed bioinformatics-based prognostic risk model for HCC was found to have good predictive power.