Objective To investigate the expression levels of selenoprotein genes in the patients with coronavirus disease 2019(COVID-19)and the possible regulatory mechanisms.Methods The dataset GSE177477 was obtained from the Gene Expression Omnibus,consisting of a symptomatic group(n=11),an asymptomatic group(n=18),and a healthy control group(n=18).The dataset was preprocessed to screen the differentially expressed genes(DEG)related to COVID-19,and gene ontology functional annotation and Kyoto encyclopedia of genes and genomes enrichment analysis were performed for the DEGs.The protein-protein interaction network of DEGs was established,and multivariate Logistic regression was employed to analyze the effects of selenoprotein genes on the presence/absence of symptoms in the patients with COVID-19.Results Compared with the healthy control,the symptomatic COVID-19 patients presented up-regulated expression of GPX1,GPX4,GPX6,DIO2,TXNRD1,SELENOF,SELENOK,SELENOS,SELENOT,and SELENOW and down-regulated ex-pression of TXNRD2 and SELENON(all P＜0.05).The asymptomatic patients showcased up-regulated expres-sion of GPX2,SELENOI,SELENOO,SELENOS,SELENOT,and SELENOW and down-regulated expression of SELP(all P＜0.05).The results of multivariate Logistic regression analysis showed that the abnormally high expression of GPX1(OR=0.067,95％CI=0.005-0.904,P=0.042)and SELENON(OR=56.663,95％CI=3.114-856.999,P=0.006)was the risk factor for symptomatic COVID-19,and the abnormally high expres-sion of SELP was a risk factor for asymptomatic COVID-19(OR=15.000,95％CI=2.537-88.701,P=0.003).Conclusions Selenoprotein genes with differential expression are involved in the regulation of COVID-19 development.The findings provide a new reference for the prevention and treatment of COVID-19.

Objective To explore the effect of UBE2I and FCGR1A gene expressions on the incidence of acquired immune deficiency syndrome(AIDS)combined with active pulmonary tuberculosis(APTB),so as to provide basis for disease monitoring.Methods A total of 98 AIDS patients combined with APTB and 84 AIDS patients combined with latent tuberculosis infection(LTBI)were selected from the validated whole genome transcriptome dataset(GSE37250).The top 30 differentially expressed genes(DEGs)in the two groups of patients were screened.We established the PPI interaction network,transcription factor-differentially expressed gene(TF-DEG),DEG-miRNA,and environmental chemical regulation network of the top 30 DEGs.Receiver operating characteristic(ROC)curves of 11 key DEGs were plotted and Logistic regression analysis was performed.Results There were 6 054 DEGs in the two groups of patients,and UBE2I was an important core node of the PPI interaction network.FCGR1A had the best predictive and indicative ability for AIDS combined with APTB.Univariate Logistic regression showed that high expressions of UBE2I and FCGR1A were risk factors for AIDS combined with APTB(P＜0.05).The regulatory network showed that VEGFB was a key gene in the TF-DEG network,participating in regulation with transcription factors such as SEPT9 and SMAD5.It targeted miRNAs such as hsa-mir-17-5p and hsa-mir-20a-5p,and was affected by environmental chemicals such as valproic acid and copper sulfate.Conclusion VEGFB plays an important role in the pathogenesis of AIDS combined with APTB.The abnormally high expressions of UBE2I and FCGR1A are associated with the disease progression of AIDS combined with APTB.The disease condition can be monitored by detecting the expression level of UBE2I and FCGR1A.

Objective:To investigate the relationship between glutathione peroxidases (GPXs) gene expression in colorectal cancer tissues and survival prognosis, and to construct and evaluate a nomogram prediction model of GPXs for survival prognosis of colorectal cancer patients.Methods:The GPXs gene expresion data and other clinical data of 620 patients with colorectal cancer (455 cases of colon cancer and 165 cases of rectal cancer) were downloaded from The Cancer Genome Atlas (TCGA) database, and the GPXs gene expression data of 820 normal people were downloaded as controls, preprocessed by R language, and the gene expression data were analyzed for differential expression. Spearman rank correlation was used to analyze the correlation between GPXs gene expression and tumor mutation burden (TMB) in colorectal cancer tissues. Cox risk regression model was used to analyze the influencing factors of survival and prognosis of colorectal cancer patients. Nomogram models were constructed to predict overall survival (OS) of colon cancer and rectal cancer patients, and its predictive performance was evaluated by calibration curve.Results:In the GPXs family, there were statistically significant differences in the mRNA expressions of GPX1, GPX2, GPX3, GPX4, GPX5, GPX7 and GPX8 between colon cancer patients and normal population, and the mRNA expressions of GPX1, GPX2, GPX4 and GPX8 in colon cancer patients were higher than those in normal population (all P<0.05) . There were statistically significant differences in the mRNA expressions of GPX1, GPX2, GPX3, GPX4, GPX7 and GPX8 between rectal cancer patients and normal population, and the mRNA expressions of GPX1, GPX2, GPX4, GPX7 and GPX8 in rectal cancer patients were higher than those in normal population (all P<0.05) . Spearman rank correlation analysis showed that GPX2 ( r s=-0.27, P<0.001) and GPX7 ( r s=-0.11, P=0.043) expressions were negatively correlated with TMB in colon cancer. There were no significant correlations between GPXs genes expressions and TMB in rectal cancer tissues (all P>0.05) . In colon cancer, univariate analysis showed that GPX3 ( HR=1.22, 95% CI: 1.05-1.43, P=0.012) , GPX4 ( HR=1.39, 95% CI: 1.01-1.92, P=0.045) , age ( HR=1.02, 95% CI: 1.01-1.04, P=0.010) and pTNM-stage ( HR=1.78, 95% CI: 1.43-2.21, P<0.001) were the influencing factors of OS. Multivariate analysis showed that GPX4 ( HR=1.96, 95% CI: 1.09-3.51, P=0.024) , age ( HR=1.02, 95% CI: 1.00-1.04, P=0.042) and pTNM-stage ( HR=1.61, 95% CI: 1.21-2.15, P=0.001) were the independent risk factors of OS. In rectal cancer, univariate analysis showed that age ( HR=1.08, 95% CI: 1.04-1.13, P<0.001) was the influencing factor of OS. Multivariate analysis showed that GPX7 ( HR=0.44, 95% CI: 0.22-0.88, P=0.020) , GPX8 ( HR=3.17, 95% CI: 1.63-6.17, P=0.001) and age ( HR=1.10, 95% CI: 1.04-1.16, P=0.001) were the independent influencing factors of OS. The consistency index (C-index) of the nomogram model for predicting OS in patients with colon cancer and rectal cancer were 0.71 (95% CI: 0.63-0.79) and 0.88 (95% CI: 0.82-0.94) respectively. The calibration curve showed that the prediction curve of the two models had a good fit with the real curve. Conclusion:GPX4 is an independent risk factor affecting the prognosis of colon cancer patients. Patients with high GPX4 expression have a poor prognosis. GPX7 and GPX8 are independent prognostic factors for rectal cancer patients, and the rectal cancer patients with low GPX7 expression and high GPX8 expression have poor prognosis. The nomogram constructed based on the above factors can better predict the prognosis of patients with colon cancer and rectal cancer.

Objective Iodothyronine deiodinases (DIOs) are important selenoproteins that play a key role in the bone and joint diseases. Osteoarthritis (OA) is the most prevalent joint disease especially in elders. This bioinformatic analysis was performed to explore the role of DIOs in OA pathogenesis. Methods The biological functions of selenoprotein DIOs were analyzed by bioinformatic techniques, including GenCLip 3.0, Database for Annotation, Visualization and Integrated Discovery (DAVID), STRING, Cytoscape, and Network Analyst. The expression of DIOs in the healthy individuals and OA patients was determined by mining OA-related microarray data in the gene expression omnibus (GEO) database of National Center for Biotechnology Information and performing a Meta-analysis of the data with Review Manager 5.3. Results Cluster analysis revealed that the function of the DIOs was associated with thyroid hormone receptor and iodothyronine; GO analysis showed that DIOs were mainly involved in biological processes, such as ethanol metabolism and phenol-containing compound metabolism and primarily involved in the cytochrome P450 metabolism of exogenous organisms and thyroid hormone signaling; SULT1A1 was the core node of the PPI network; miRNAs and thyroid hormones had some iterations with DIO1 and DIO2; Meta-analysis showed that DIO3 expression was significantly up-regulated in OA patients (SMD = 0.31, 95％CI: 0.03, 0.59, P = 0.03). Conclusions The main biological functions of DIOs were closely associated with the regulation of thyroid hormone. And the up-regulated expression of DIO3 may have crucial impact on the occurrence of OA.

Objective:To analyze the incidence and epidemiological characteristics of traumatic spinal cord injury in China in 2018.Methods:Multi-stage stratified cluster sampling was used to randomly select hospitals capable of treating patients with spinal cord injury from 3 regions，9 provinces and 27 cities in China to retrospectively investigate eligible patients with traumatic spinal cord injury admitted in 2018. National and regional incidence rates were calculated. The data of cause of injury，injury level，severity of injury，segment and type of fracture，complications，death and other data were collected by medical record questionnaire，and analyzed according to geographical region，age and gender.Results:Medical records of 4，134 patients were included in this study，with a male-to-female ratio of 2.99∶1. The incidence of traumatic spinal cord injury in China in 2018 was 50.484 / 1 million （95% CI 50.122-50.846）. The highest incidence in the Eastern region was 53.791 / 1 million （95% CI 53.217-54.365）. In the whole country，the main causes of injury were high falls （29.58%），as well as in the Western region （40.68%），while the main causes of injury in the Eastern and Central regions were traffic injuries （31.22%，30.10%）. The main injury level was cervical spinal cord in the whole country （64.49%），and the proportion of cervical spinal cord injury in the Central region was the highest （74.68%），and the proportion of lumbosacral spinal cord injury in the Western region was the highest （32.30%）. The highest proportion of degree of injury was incomplete quadriplegia （55.20%），and the distribution pattern was the same in each region. A total of 65.87% of the patients were complicated with fracture or dislocation，77.95% in the Western region and only 54.77% in the Central region. In the whole country，the head was the main combined injury （37.87%），as well as in the Eastern and Central regions，while the proportion of chest combined injury in the Western region was the highest （38.57%）. A total of 32.90% of the patients were complicated with respiratory complications. There were 23 patients （0.56%） died in hospital，of which 17（73.91%） died of respiratory dysfunction. Conclusions:The Eastern region of China has a high incidence of traumatic spinal cord injury. Other epidemiological features include high fall as the main cause of injury cervical spinal cord injury as the main injury level，incomplete quadriplegia as the main degree of injury，head as the main combined injury，and respiratory complications as the main complication.

OBJECTIVES: Coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 can damage the myocardium directly, or activate the immune system, trigger a cytokine storm, and cause inflammatory cells to infiltrate the myocardial tissue and damage the myocardium. This study is based on the sequencing data to analyze the changes in gene expression of cardiomyocytes and macrophages after SARS-CoV-2 infection, and explore the potential effects of SARS-CoV-2 on the heart and immune system. METHODS: The public data set GSE151879 was retrieved. The online software Network Analyst was used to preprocess the data, and the differentially expressed genes (DEGs) [log RESULTS: After data standardization, the data quality was excellent and it can ensure reliable results. Myocardial cell infection with SARS-CoV-2 and gene expression spectrum were changed significantly, including a total of 484 DEGs in adult cardiomyoblasts, a total of 667 DEGs in macrophages, and a total of 1 483 DEGs in human embryo source of cardiomyopathy. The Stum, mechanosensory transduction mediator homolog (STUM), dehydrogenase/reductase 9 (DHRS9), calcium/calmodulin dependent protein kinase II beta (CAMK2B), claudin 1(CLDN1), C-C motif chemokine ligand 2 (CCL2), TNFAIP3 interacting protein 3 (TNIP3), G protein-coupled receptor 84 (GPR84), and C-X-C motif chemokine ligand 1 (CXCL1) were identical in expression patterns in 3 types of cells. The protein-protein interaction suggested that CAMK2B proteins may play a key role in the antiviral process in 3 types of cells; and silicon dioxide (SiO CONCLUSIONS CAMK2B, CLDN1, CCL2, and DHRS9 genes play important roles in the immune response of cardiomyocytes against SARS-CoV-2. SiO
COVID-19 ; Humans ; Macrophages ; Myocytes, Cardiac ; SARS-CoV-2 ; Silicon Dioxide ; Transcriptome

【Objective】 Based on the high-throughput sequencing data of the whole genome， genomics and bioinformatics analyses were made to analyze the gene expression changes in the epithelial cells of the lung tissue from patients with coronavirus disease 2019 （COVID-19）， and explore the effects of the new coronavirus SARS-CoV-2 on human lungs. This study can provide a theoretical basis for the exploration of SARS-CoV-2 on the pathogenesis of lung tissue. 【Methods】 The public data set GSE160435 was retrieved. The data were analyzed by Network analyst， Cytoscape 3.7.2， String 11.0， and other software. The differentially expressed genes were screened， gene function （Gene Ontology， GO） and signal pathway KEGG （Kyoto Encyclopedia of Genes and Genomes） enrichment analysis were carried out. We established the Protein-protein Interactions Network （PPI）， PPI of lung tissue-specific DEGs， DEG microRNA regulatory network， Transcription Factor （TF）-DEG regulatory network， and environmental chemicals DEGs regulatory network. 【Results】 We found 324 DEGs in the lung epithelial cells of patients with COVID-19， of which 112 （34.57%） were upregulated and 212 （65.43%） were downregulated. Enrichment analysis showed that DEGs were mainly involved in biological processes such as virus-related defense response， mainly involved in protein digestion and absorption， anti-human papillomavirus infection and other signaling pathways. Specific PPI network closely related to DEGs and lung tissue showed that PDGFRB and KIT were core proteins； hsa-mir-340 had targeted interaction with DEGs. It indicated that HOXB4， ISG15 and other related genes were regulated by transcription factors； DEGs interacted with environmental chemicals such as nickel and estradiol. 【Conclusion】 The gene expression pattern of lung epithelial cells in lung tissue of COVID-19 patients has changed significantly. Proteins or genes such as PDGFRB， MMP9 and KIT may play a vital role in the defense immunity of lung tissue. Micro-RNA， TF， signaling pathway molecules， environmental chemicals， and lung tissue-specific genes also play a role in the above-mentioned process. This study provides new ideas for exploring the pathogenic mechanism of SARS-CoV-2 on lung tissue and formulating clinical prevention， diagnosis and treatment measures.

OBJECTIVES: To study the gene expression of adipose tissue CD14 METHODS: The data of GSE54350 were obtained from the public database of gene expression profiling. The data were pre-processed by Network Analyst, String 11.0, Cytoscape 3.7.1, and other analytical software. The differentially expressed genes were analyzed by gene ontology biological function and kyoto encycopedia of genes and genomes (KEGG) signaling pathway to establish differential gene protein interaction network, transcription factor-gene regulatory network, microRNA-gene regulatory network, environmental factors-gene regulatory network, and other interaction systems. RESULTS: The gene expression pattern of CD14 CONCLUSIONS The gene expression of adipose tissue CD14
Adipose Tissue ; Computational Biology ; DNA-Binding Proteins ; Diabetes Mellitus, Type 2/genetics* ; Gene Expression ; Gene Expression Profiling ; Gene Regulatory Networks ; Humans ; MicroRNAs/genetics* ; Muscle Proteins

Objective    To explore the value of artificial intelligence (AI) diagnostic imaging system and three dimensional computed tomographic bronchoangiography (3D-CTBA) surgical planning system in the management of multiple primary lung cancer (MPLC). Methods    The clinical data of 53 patients with MPLC treated surgically in our hospital from January 2018 to August 2020 were retrospectively analyzed, including 16 males and 37 females, with a median age of 60 (39-75) years. The patients' preoperative CT was analyzed by AI and manually, and the data of patients who underwent 3D-CTBA were compiled to evaluate the value of AI and 3D-CTBA in the diagnosis and treatment of MPLC, respectively. Results     The sensitivity of AI screening for MPLC was 84.91%. The sensitivity (91.90% vs. 83.78%) and accuracy (85.60% vs. 84.00%) of AI diagnosis of high-risk MPLC infiltrative lesions were better than those of manual diagnosis. 3D-CTBA was used for planning the surgery in 12 patients, and the intraoperative situation was generally consistent with the reconstructed results. Conclusion    AI is of high value in identifying infiltrative lesions of MPLC. 3D-CTBA reconstruction of anatomical structures is accurate and can guide preoperative planning.

Objective: To explore the influence of heat and noise exposure on the risk of hypertension in workers,and to provide evidence for prevention of hypertension in occupational population. Methods: Cluster sampling method was used to recruit 2 130 steel workers from four factories（north iron-making,long steel,cold steel and power department）of some steel company. A cross-sectional study was conducted to collect physical examination results,heat and noise exposure. Logistic regression models were used to analyze the effects of noise,heat and their interaction on hypertension. Results: Totally 1 971 valid questionnaires were collected,and the response rate was 92.54%. There were 654 workers suffering from hypertension,with a prevalence rate of 33.18%. There were 1 006 workers exposed to noise,accounting for 51.04%;and 853 workers exposed to heat,accounting for 43.28%. The prevalence rates of hypertension in workers exposed to noise and heat were higher than those in workers without the above exposure（P<0.05）. The prevalence rates of hypertension increased with the increase of age and working years（P<0.05）. The results of multivariate logistic regression analysis showed that noise（OR=1.711,95%CI：1.380-2.121）,heat（OR=1.721,95%CI：1.394-2.125）were risk factors for hypertension;the interaction between noise and heat on hypertension was not statistically significant（P>0.05）,while the interaction between noise and age（OR=1.086,95%CI：1.057-1.115）,between heat and age（OR=1.087,95%CI：1.059-1.115）both increased the risk of hypertension. Conclusion Occupational exposure to heat and noise are risk factors for hypertension. These two occupational hazards also interact with age,which can increase the risk of hypertension in workers.