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.

Novel classification for simple peripheral arteriovenous malformations based on anatomic localization: Prevalence data from the tertiary referral center in China.

Background: In absence of the large-sample study of simple peripheral arteriovenous malfomations (pAVM), we aimed to perform the epidemiological analysis of over 1,000 simple pAVM patients from our center in the past 5 years, and establish a novel classification based on the anatomical localization of the primary lesion. Results: Between March 27, 2016, and March 31, 2021, Chinese patients who were diagnosed with simple pAVM were taken into account. Those who suffered from simple arteriovenous malformations of the central nervous system (cnsAVM), combined types of AVM, and syndromes, such as CLOVES syndrome, etc. were all excluded from this study. A total of 1,070 simple pAVM patients were screened out. All of the simple pAVM patients were diagnosed by clinical manifestations and imaging examinations. Demographic data were obtained from the National Bureau of Statistics of China. The 5-year prevalence of simple pAVM was about (2.15-6.60) /1,000,000 population. The male-female ratio was approximately 1.22:1. The pAVM inpatients that were included in the age group of 21~30 years old had the highest constituent ratio (P = 0.01). The classification included four groups: Type I (primarily occurring in soft tissue); Type II (primarily occurring in bone); Type III (primarily occurring in the viscus) and Type IV (simple pAVM coexisting with CNS lesions). There were two subtypes of Type I: the A subtype (involving one major anatomical region) and the B subtype (involving two or more major anatomical regions); two subtypes of Type II: the A subtype (the cortex was intact) and the B subtype (the lesion had broken through the cortex). Generally, 657 patients were classified as Type IA (61.4%), 232 patients were Type IB (21.7%), 82 patients were Type IIA (7.7%) and 79 were categorized as Type IIB (7.4%); the number of patients who had Type III and Type IV pAVM were 9 (0.8%) and 11 (1.0%), respectively. The clinical manifestations and diagnostic standards for each type were also systematically summarized. Conclusions: Prevalence data for simple pAVM were analyzed, and a novel classification was proposed based on the anatomy of the lesions. The present work was expected to facilitate the diagnosis of simple pAVM in clinical works.

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.

Construction and Validation of a m7G-Related Gene-Based Prognostic Model for Gastric Cancer.

Background: Gastric cancer (GC) is one of the most common malignant tumors of the digestive system. Chinese cases of GC account for about 40% of the global rate, with approximately 1.66 million people succumbing to the disease each year. Despite the progress made in the treatment of GC, most patients are diagnosed at an advanced stage due to the lack of obvious clinical symptoms in the early stages of GC, and their prognosis is still very poor. The m7G modification is one of the most common forms of base modification in post-transcriptional regulation, and it is widely distributed in the 5' cap region of tRNA, rRNA, and eukaryotic mRNA. Methods: RNA sequencing data of GC were downloaded from The Cancer Genome Atlas. The differentially expressed m7G-related genes in normal and tumour tissues were determined, and the expression and prognostic value of m7G-related genes were systematically analysed. We then built models using the selected m7G-related genes with the help of machine learning methods.The model was then validated for prognostic value by combining the receiver operating characteristic curve (ROC) and forest plots. The model was then validated on an external dataset. Finally, quantitative real-time PCR (qPCR) was performed to detect gene expression levels in clinical gastric cancer and paraneoplastic tissue. Results: The model is able to determine the prognosis of GC samples quantitatively and accurately. The ROC analysis of model has an AUC of 0.761 and 0.714 for the 3-year overall survival (OS) in the training and validation sets, respectively. We determined a correlation between risk scores and immune cell infiltration and concluded that immune cell infiltration affects the prognosis of GC patients. NUDT10, METTL1, NUDT4, GEMIN5, EIF4E1B, and DCPS were identified as prognostic hub genes and potential therapeutic agents were identified based on these genes. Conclusion: The m7G-related gene-based prognostic model showed good prognostic discrimination. Understanding how m7G modification affect the infiltration of the tumor microenvironment (TME) cells will enable us to better understand the TME's anti-tumor immune response, and hopefully guide more effective immunotherapy methods.

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.

A Novel Model Based on Necroptosis-Related Genes for Predicting Prognosis of Patients With Prostate Adenocarcinoma.

Background: Necroptosis is a newly recognized form of cell death. Here, we applied bioinformatics tools to identify necroptosis-related genes using a dataset from The Cancer Genome Atlas (TCGA) database, then constructed a model for prognosis of patients with prostate cancer. Methods: RNA sequence (RNA-seq) data and clinical information for Prostate adenocarcinoma (PRAD) patients were obtained from the TCGA portal (http://tcga-data.nci.nih.gov/tcga/). We performed comprehensive bioinformatics analyses to identify hub genes as potential prognostic biomarkers in PRAD u followed by establishment and validation of a prognostic model. Next, we assessed the overall prediction performance of the model using receiver operating characteristic (ROC) curves and the area under curve (AUC) of the ROC. Results: A total of 5 necroptosis-related genes, namely ALOX15, BCL2, IFNA1, PYGL and TLR3, were used to construct a survival prognostic model. The model exhibited excellent performance in the TCGA cohort and validation group and had good prediction accuracy in screening out high-risk prostate cancer patients. Conclusion: We successfully identified necroptosis-related genes and constructed a prognostic model that can accurately predict 1- 3-and 5-years overall survival (OS) rates of PRAD patients. Our riskscore model has provided novel strategy for the prediction of PRAD patients' prognosis.

SOX5 promotes cell invasion and metastasis via activation of Twist-mediated epithelial-mesenchymal transition in gastric cancer.

BACKGROUND: Sex-determining region Y-box protein 5 (SOX5) has been demonstrated to be implicated in oncogenic function in various types of cancers. However, the role of SOX5 in gastric cancer (GC) remains poorly elucidated. Herein, we investigated the role and the underlying mechanism of SOX5 in GC progression. METHODS: SOX5 mRNA and protein expression were detected by quantitative real-time PCR (qRT-PCR), Western blot and immunohistochemistry in human GC specimens, and their clinical significance was evaluated. The effects of SOX5 knockdown or overexpression on GC cell behavior were determined by proliferation, wound-healing and transwell assays in vitro, and metastasis assays in vivo; and epithelial-mesenchymal transition (EMT)-related markers were detected by qRT-PCR, Western blot and immunofluorescence staining. RESULTS: The up-regulated expression of SOX5 in GC specimens was significantly correlated with clinical metastasis and poor prognosis for patients with GC. Besides, SOX5 promoted GC cell migration and invasion in vitro, as well as GC cell metastasis in vivo. Mechanically, Twist-mediated EMT was likely involved in SOX5-facilitated GC cell behavior. CONCLUSION: SOX5 has an important function in GC progression. In addition, SOX5 promotes GC cell invasion and metastasis via activation of Twist-mediated EMT, thus providing a potential therapeutic target for GC metastasis.

Investigation of gender difference in human response to temperature step changes.

The purpose of this study was to examine gender difference in human response to temperature step changes. A total of three step-change conditions (S5: 32 °C-37 °C-32 °C, S11: 26 °C-37 °C-26 °C, and S15: 22 °C-37 °C-22 °C) were designed and a laboratory experiment with 12 males and 12 females was performed. Results of this study support our hypothesis that females differ from males in human response to sudden temperature changes from the perspectives of psychology, physiology and biomarkers. Females are more prone to show thermal dissatisfaction to cool environments while males are more likely to feel thermal discomfort in warm environments. It is logical that men have a stronger thermoregulation ability than women as male skin temperature change amplitude is smaller while the time to be stable for skin temperature is shorter than that of females after both up-steps and down-steps. In S15, males witnessed a more intensive decrease in RMSSD while females underwent a remarkable instant reduce in oral temperatures after the up-step. Marginal significance was observed in male IL-6 before and after the up-step in S15 while female IL-6 prominently increased after the down-step in S15.