Several types of arthritis share the common feature that the generation of inflammatory mediators leads to joint cartilage degradation. However, the shared mechanism is largely unknown. H2BK120ub1 was reportedly involved in various inflammatory diseases but its role in the shared mechanism in inflammatory joint conditions remains elusive. The present study demonstrated that levels of cartilage degradation, H2BK120ub1, and its regulator WW domain-containing adapter protein with coiled-coil (WAC) were increased in cartilage in human rheumatoid arthritis (RA) and osteoarthritis (OA) patients as well as in experimental RA and OA mice. By regulating H2BK120ub1 and H3K27me3, WAC regulated the secretion of inflammatory and cartilage-degrading factors. WAC influenced the level of H3K27me3 by regulating nuclear entry of the H3K27 demethylase KDM6B, and acted as a key factor of the crosstalk between H2BK120ub1 and H3K27me3. The cartilage-specific knockout of WAC demonstrated the ability to alleviate cartilage degradation in collagen-induced arthritis (CIA) and collagenase-induced osteoarthritis (CIOA) mice. Through molecular docking and dynamic simulation, doxercalciferol was found to inhibit WAC and the development of cartilage degradation in the CIA and CIOA models. Our study demonstrated that WAC is a key factor of cartilage degradation in arthritis, and targeting WAC by doxercalciferol could be a viable therapeutic strategy for treating cartilage destruction in several types of arthritis.

Objective:To assess the efficacy of silicone earplugs in protecting workers exposed to noise in a typical manufacturing environment, and to provide training interventions for workers who do not achieve the anticipated noise reduction levels, as well as examining the spectral characteristics of earplug attenuation.Methods:From June to August 2022, a total of 294 noise-exposed workers in two manufacturing enterprises equipped with the same type of earplug were studied by cluster sampling method, by conducting questionnaire surveys, collecting data, fitting tests, and providing trainings, the current noise exposure levels of workers in the industry as well as the perception about the earplug were understood. Additionally, the attenuation before and after intervention in workplace were measured, the spectral characteristics of noise reduction were were described and compared.Results:The percentage of workers with Personal Attenuation Rating (PAR) of 0 is 32.7% (96/294), and the baseline pass rates are all below 60%. There were no significant differences in pass rates based on gender, age, noise exposure, education level, or cognition of earplug effectiveness. After adjusting the way that earplugs are worn or changing the type of earplugs, all workers were able to meet their noise reduction requirements. The median PAR improvement for both companies is above 10 dB. The noise attenuation of the earplug vary with frequency, with lower attenuation at 4 000 Hz and higher attenuation at 8 000 Hz, showing some deviation from the nominal values.Conclusion:The difference between the actual sound attenuation value of earplugs and the nominal value is related to the noise frequency. When using silicone earplugs, attention should be paid to the spectral composition of the noise in the workplace.

Effective albumin refers to serum albumin with intact structure and function.In the course of chronic liver disease,some serum albumin loses its functional integrity through different post-translational modifications such as oxidation and glycosylation.Level of effective albumin is lower in patients with decompensated cirrhosis and is significantly correlated with patient survival,underscoring that they are more sensitive than total serum al-bumin in reflecting the actual state of liver function.In addition,effective albumin not only serves as a predictor,but also plays a key role in the treatment of chronic liver disease by improving albumin preparations and develo-ping new therapeutics.

Objective:To analyze the types and functions of CD34 + cells in full-thickness skin defect wounds of normal mice and diabetic mice by single-cell RNA sequencing. Methods:This study was an experimental study. The CD34 + cell lineage tracing mouse was produced, and the visualization of CD34 + cells under the fluorescent condition was realized. Six male CD34 + cell lineage tracing mice aged 7-8 weeks (designated as diabetic group) were intraperitoneally injected with streptozotocin to establish a diabetic model, and full-thickness skin defect wounds were prepared on their backs when they reached 13 weeks old. Another 6 male CD34 + cell lineage tracing mice aged 13 weeks (designated as control group) were also subjected to full-thickness skin defect wounds on their backs. On post-injury day (PID) 4, wound tissue was collected from 3 mice in control group and 2 mice in diabetic group, and digested to prepare single-cell suspensions. CD34 + cells were screened using fluorescence-activated cell sorting, followed by single-cell RNA sequencing. The Seurat 4.0.2 program in the R programming language was utilized for dimensionality reduction, visualization, and cell clustering analysis of CD34 + cell types, and to screen and annotate the marker genes for each CD34 + cell subpopulation. Kyoto encyclopedia of genes and genomes (KEGG) and gene ontology (GO) enrichment analysis was performed to analyze the differentially expressed genes (DEGs) of CD34 + fibroblasts (Fbs), smooth muscle cells (SMCs), keratinocytes (KCs), and chondrocyte-like cells (CLCs) in the wound tissue of two groups of mice for exploring cellular functions. Results:On PID 4, CD34 + cells in the wound tissue of both groups of mice were consisted of 7 cell types, specifically endothelial cells, Fbs, KCs, macrophages, T cells, SMCs, and CLCs. Among these, Fbs were further classified into 5 subpopulations. Compared with those in control group, the proportions of CD34 + endothelial cells, Fbs subpopulation 1, Fbs subpopulation 4, KCs, and CLCs in the wound tissue of mice were increased in diabetic group, while the proportions of CD34 + Fbs subpopulation 2, Fbs subpopulation 3, and SMCs were decreased. The marker genes for annotating CD34 + CLCs, endothelial cells, Fbs subpopulation 1, Fbs subpopulation 2, Fbs subpopulation 3, Fbs subpopulation 4, Fbs subpopulation 5, KCs, macrophages, SMCs, and T cells were respectively metastasis-associated lung adenocarcinoma transcript 1, fatty acid binding protein 4, Gremlin 1, complement component 4B, H19 imprinted maternally expressed transcript, Dickkopf Wnt signaling pathway inhibitor 2, fibromodulin, keratin 5, CD74 molecule, regulator of G protein signaling 5, and inducible T-cell co-stimulator molecule. KEGG and GO enrichment analysis revealed that, compared with those in control group, DEGs with significant differential expression (SDE) in CD34 + Fbs from the wound tissue of mice in diabetic group on PID 4 were significantly enriched in terms related to inflammatory response, extracellular matrix (ECM) organization, regulation of cell proliferation, and aging (with Pvalues all <0.05), DEGs with SDE in CD34 + SMCs were significantly enriched in terms related to cell migration, apoptotic process, positive regulation of transcription, and phagosome (with P values all <0.05), DEGs with SDE in CD34 + KCs were significantly enriched in terms related to mitochondrial function, transcription, and neurodegenerative diseases (with P values all <0.05), and DEGs with SDE in CD34 + CLCs were significantly enriched in terms related to rhythm regulation, ECM, and viral infection (with P values all <0.05). Conclusions:CD34 + cells display high heterogeneity in the healing process of full-thickness skin defect wounds in both normal mice and diabetic mice. The significantly enriched functions of DEGs with SDE in CD34 + cell subpopulations in the wound tissue of the two mouse groups are closely related to the wound healing process.

Objective To investigate the image quality,radiation dose and contrast medium(CM)intake in coronary computed tomography angiography(CCTA)of overweight patients based on wide-detector using different tube voltages and CM of different concentrations.Methods A total of 150 overweight patients[body mass index(BMI)≥ 25 kg/m2]who underwent CCTA were divided into three groups according to scan protocols:group A(120 kVp,370 mg I/mL CM),group B(100 kVp,350 mg I/mL CM),and group C(80 kVp,320 mg I/mL CM),with each group had 50 patients.The mean CT value,mean signal-to-noise ratio(SNR),mean contrast-to-noise ratio(CNR),figure of merit(FOM)of all images were measured and calculated.Images were assessed using a 5-point scale by two radiologists.The volume CT dose index(CTDIvol)and dose length product(DLP)of each patient were recorded and the effective dose(ED)was calculated.The total iodine intake values of patients in three groups were calculated.The above data were statistically analyzed by one-way ANOVA.Results The mean CT value,mean SNR,mean CNR,and mean subjective score of groups B and C were significantly higher than those of group A(P＜0.001),but there was no significant difference between groups B and C(P＞0.05).The FOM value of groups B and C was significantly higher than that of group A(P＜0.001),and the FOM value of group B was significantly lower than that of group C(P＜0.001).The total iodine intake values of groups B and C was significantly lower than that of group A(P＜0.001).The ED and total iodine intake values in groups B and C were 30.34％,68.53％and 10.22％,16.85％lower than those in group A,respectively(P＜0.001).Conclusion Under the premise of ensuring image quality,the lower tube voltage and lower concentration of CM based on wide-detector allows for significant reduction in radiation dose and total iodine intake in CCTA for overweight patients compared to routine scan protocols.

Objective:To investigate the mechanism of Wenjing Decoction in the treatment of hepatic fibrosis through network pharmacological methods, and conducting animal experiments to verify the core targets.Methods:The TCMSP database platform was used to screen the active components and related targets of Wenjing Decoction, and the Uniprot database was used to obtain the target genes corresponding to the active components of Wenjing Decoction. The network diagram of "Chinese materia medica-compound-target" was constructed in Cytoscape 3.7.2, and the GeneCards database was used to search liver fibrosis related targets. String database was used to construct a protein interaction network (PPI) to screen the core components and key targets of liver fibrosis, and GO analysis and KEGG pathway enrichment were performed. Animal experiments were conducted to verify the results of the analysis. 10 mice were selected as the blank group, and the remaining 45 rats were induced with carbon tetrachloride induced liver fibrosis model. After modeling, 40 successfully modeled rats were divided into model group and Wenjing Decoction high, medium-, and low-dosage groups using a random number table method, with 10 rats in each group. Wenjing Decoction high, medium-, and low-dosage groups were orally administered with 1.5×3.18, 3.18, and 0.5×3.18 g/kg Wenjing Decoction, respectively. The blank group was orally administered with equal volume distilled water once a day for 8 consecutive weeks. HE staining was used to observe the histopathological and morphological changes in the liver of rats. The serum GPT and GOT levels of rats were detected using a fully automated biochemical analyzer, and the expressions of TNF, AKT, and IL-6 proteins in rat liver tissue was detected using Western Blot.Results:A total of 188 active components of Wenjing Decoction were obtained, and the active components with higher degree values were β-sitosterol, quercetin, naringenin, etc. 799 liver fibrosis gene targets were collected, and the core target genes of the PPI network were TNF, AKT, IL6, etc. The key anti-hepatic fibrosis related pathways were obtained by GO function and KEGG analysis, including pathway in cancer, TNF, PI3K-Akt and other signalling pathways. Results of animal experiments showed that there were obvious inflammatory infiltration, collagen fibre and pseudo lobe generation in the liver tissue of rats in the model group, and the levels of inflammation and fibrosis in the liver tissue of rats in the Wenjing Decoction high, medium-, and low-dosage groups were improved to different degrees compared with that of the model group; compared with the model group, the levels of serum GPT and GOT decreased ( P<0.05); the protein expressions of TNF, AKT and IL6 in the Wenjing Decoction high, medium-, and low-dosage groups decreased ( P<0.05). Conclusion:Wenjing Decoction may exert anti-liver fibrosis effects by intervening in TNF, AKT, IL6 targets, regulating cancer pathways, TNF, PI3K Akt and other signaling pathways.

ObjectiveTo analyze the results of fit testing and its influencing factors on half-mask respirator among workers exposed to organic solvents. Methods A total of 84 workers exposed to organic solvents were selected as the research subjects using a convenience sampling method. The qualitative fit test apparatus of respiratory protection was tested after the workers had put on the half-mask respirats, and 11 facial indicators of the subjects were measured. Results The overall pass rate of the respirator fit testing was 71.4% (60/84). The lowest pass rate was 63.1% (53/84), which occurred during bending movements of workers. The head width, minimum forehead width, face length, nose length, nose depth, head circumference and head length were higher in workers who passed respirator fit testing, compared with those in the failing group (all P<0.05). The result of binary logistic regression analysis showed that gender and face width were influencing factors of the respirator fit testing (both P<0.05). Female workers had a lower pass rate of the fit testing than male workers, and workers with larger face width had a lower pass rate in the fit testing. Conclusion Drastic movement may lead to a decrease in the seal of half-mask respirator of workers exposed to organic solvents. When providing half-mask respirator to workers exposed to organic solvents, employers need to pay attention to the fit of respirators of female works and those with larger face width to ensure the effectiveness of respiratory protection for workers.

ObjectiveTo explore the protective effect of hearing protectors worn by noise-exposed workers and its influencing factors. Methods A total of 329 occupational noise-exposed workers were selected as the research subjects by judgment sampling method. A questionnaire survey on the use of ear protectors and individual suitability tests was conducted. Intervention was carried out for those whose personal attenuation rating (PAR) did not pass the baseline standard. Results The median (M) and the 25th and 75th percentiles of baseline PAR were 17.0 (5.0, 22.5) dB. The baseline PAR of the workers who were male, aged 25-<35 years, with a working experience of 5-<15 years, with a college degree or above, wearing ear protectors for 5-<15 years, knowing the right way to wear ear protectors, and workers who wore ear protectors correctly during work was relatively high (all P<0.01). The unqualified rate of baseline PAR of the study subjects was 32.8%. The unqualified rate of baseline PAR of workers in automobile manufacturing enterprises was lower than that of workers in plastic enterprises and textile enterprises (9.2% vs 43.6%, and 9.2% vs 50.0%, both P<0.01). The M of the 108 unqualified worker on baseline PAR was improved after intervention (22.0 vs 1.0 dB, P<0.01). The rates of knowing the right way to wear ear protectors, wearing ear protectors correctly during work, and receiving training on wearing ear protectors correctly for the research subjects were 88.1%, 84.8%, and 86.6%, respectively. Workers in automobile manufacturing enterprises and plastic enterprises had higher rates of knowing the right way to wear ear protectors, wearing ear protectors correctly during work, and receiving training on wearing ear protectors correctly than those in textile enterprises (all P<0.01). Conclusion Gender, age, working experience, education level, duration of wearing ear protectors, knowledge and use of ear protectors correctly are influencing factors of the protective effect of ear protectors for noise-exposed workers.

Objective To verify the genetic characteristics associated with gastric cancer,and to propose a hybrid feature selection method for identifying target genes,further analyzing their significance and establishing a new diagnostic prediction model.Methods Analysis of variance in bioinformatics was performed on the original gastric cancer data,and then machine learning methods such as random forest,recursive feature elimination of support vector machine,and LASSO algorithm were used to screen gastric cancer associated genes,and the intersection of results was taken as the key gene set.The key genes were identified and verified through enrichment analysis.The diagnosis and prediction models based on 8 kinds of machine learning classification algorithms such as multi-layer perceptron,logistic regression and decision tree,were constructed using the key genes.Results The key genes selected by the hybrid feature selection method were closely related to the tumorigenesis and development.Eight key genes(TXNDC5,BMP8A,ONECUT2,COL10A1,JCHAIN,INHBA,LCTL and TRIM59)were identified as potential markers of good diagnostic efficacy in gastric cancer.The ROC curve and accuracy results demonstrated that among the 8 classification models,MLP is the best gastric cancer prediction model,with an accuracy of 97.77%,which was 3.83%higher than that of Xgboost gastric cancer prediction model.Conclusion The study identifies 8 key genes for the diagnosis and prevention of gastric cancer,and establishes the optimal prognosis model.

Tumors are serious diseases threatening human health,and the early diagnosis is essential to improve treatment success and patient survival.The study of tumor gene expression data has become a major tool for revealing tumor disease mechanisms,in which artificial intelligence plays an important role.The potential advantages of supervised learning,unsupervised learning and deep learning in tumor prediction and classification are explored from the perspective of machine learning methods.Special attention is paid to the impact of feature selection algorithms on gene screening and their importance in high-dimensional gene expression data.By providing a comprehensive overview of the application and development of artificial intelligence in the analysis of tumor gene expression data,the study aims to provide an outlook for future research directions and promote further development.