Objective To analyze the characteristics of work-related musculoskeletal disorders (WMSDs) among sonographers in Guangdong Province, and to explore the disease pattern of the cases. Methods A total of 512 sonographers from 31 hospitals in Guangdong Province were selected as the research subjects using stratified cluster sampling method. The prevalence of WMSDs in the past year was investigated using the Musculoskeletal Disorders Questionnaire, and the characteristics of WMSDs were analyzed. Latent class analysis was used to identify the disease pattern of WMSDs. Results The overall prevalence of WMSDs was 94.3%. The top five affected body parts were right shoulder, neck, right hand/wrist, lower back and right forearm/elbow, with the prevalence of 80.3%, 75.4%, 61.1%, 55.5% and 45.3%, respectively. The prevalence of WMSDs was higher on the right side for the shoulder, hand/wrist, forearm/elbow, hip/leg and knee compared with the left side (80.3% vs 31.3%, 61.1% vs 13.9%, 45.3% vs 10.0%, 17.4% vs 8.6%, 13.1% vs 8.4%, all P<0.05). The prevalence of WMSDs increased with work years, as well the prevalence of WMSDs in the top five affected body parts among the sonographers (all P<0.05). However, there were no statistical differences in prevalence of WMSDs between general hospitals and maternal and child health hospitals, tertiary hospitals and non-tertiary hospitals, Pearl River Delta hospitals and non-Pearl River Delta hospitals; there was also no statistical difference between different genders and age groups of the sonographers (all P>0.05). The best-fit latent disease pattern for sonographers WMSDs comprised three categories： symptom of neck-right shoulder, symptom of neck-lower back-right shoulder-right elbow-right hand/wrist, and symptom of multi-parts above the knees, with the latent probabilities of 0.438, 0.427 and 0.135, respectively. Conclusion The prevalence of WMSDs in sonographers is extremely high, with a dose-effect relationship with work years. The most common affected parts are neck, lower back and right shoulder, right hand/wrist, and right forearm/elbow. The prevalence of WMSDs in the right side of limb was higher than that in the left. WMSDs primarily occur in multiple parts simultaneously. The most common symptoms occur in the neck-right shoulder and neck-lower back-right shoulder-right elbow-right hand/wrist.

Background Occupational injuries, which can result in absenteeism, disability, or death, are closely related to poor working conditions. However, the improvement of operating conditions are often time-consuming and require significant economic inputs. Both occupational psychology and enterprise risk factors have been proved to be related to the occurrence of occupational injuries, but their roles in the influence path of adverse working conditions leading to occupational injuries remain unclear. Objective To explore the roles of occupational psychology and enterprise risk factors in the impact of adverse working conditions on occupational injury, so as to provide a scientific basis for enterprises with adverse working conditions to carry out targeted occupational injury intervention programs. Methods The survey data of 5997 manufacturing enterprises were obtained from the European Survey of Enterprises on New and Emerging Risks (ESENER) database. The data on enterprise risk characteristics, occupational injuries, working conditions, and occupational psychological factors were extracted and assigned. Occupational injury differences by enterprise categories were examined by chi-square test. Correlations between interest variables were evaluated by Spearman test. Path analysis with Bootstrap method was conducted using AMOS 26 software, and ratio of chi-square statistic to degree of freedom (χ²/ν), comparative fit index (CFI), Tucker-Lewis index (TLI), and root mean square error of approximation (RMSEA) were used to evaluate the path model candidates. The effect size and its proportion were calculated for variables (occupational psychological factors, enterprise risk factors, and adverse working conditions) included in the final model. Results The M (P₂₅, P₇₅) scores of occupational injuries, adverse working conditions, and occupational psychological factors were 40 (20, 50), 50 (30, 60), and 20 (10, 30), respectively. The enterprises that reported occupational injuries accounted for 25.5% (1550 enterprises) of the total enterprises. Proportions of the enterprises that reported occupational injuries varied significantly by company scale, branch companies, temporary employment, language barriers, and establishment time (P<0.05). The results of Spearman test showed that occupational injuries were positively correlated with working conditions (r_s=0.440), occupational psychological factors (r_s=0.205), company scale (r_s=0.307), temporary employment (r_s=0.282), and language barriers (r_s=0.158); but negatively correlated with branch companies (r_s=−0.180) and establishment time (r_s=−0.176) (P<0.05). In the path analysis, the fitness indexes of the final model were χ²/ν=2.85, CFI=0.997, TLI=0.993, and RMSEA=0.018 (90%CI: 0.011, 0.025). The indirect effect size values and constituent ratios of enterprise risk factors and occupational psychological factors in the effect of adverse working conditions on occupational injuries were 0.166 (30.01%) and 0.013 (3.13%) respectively. The indirect effect size value of occupational psychological factors in the effect of enterprise risk factors on occupational injuries and its constituent ratio were 0.022 and 6.85%. Conclusion Enterprises with adverse working conditions may control the risk of occupational injuries by offering better solutions to surmount language barriers and temporary employment, developing occupational psychological intervention and optimization programs such as improving working hours system. At the same time, large enterprises, enterprises without branches, or enterprises with a long history are the focus of occupational injury prevention and control.

Globally, manufacturing workers are one of the most vulnerable groups to occupational injuries. Occupational injuries can lead to absenteeism, disability or even death, and most of the inflicted workers involve young adults aged 18-40 years, suggesting a safety and health problem that needs close attention. In the working environment of manufacturing industry, there are a variety of occupational injury risk factors, involving individuals, equipment, environment, and management, which should be considered comprehensively. This study found comprehensive research coverage on the influencing factors of occupational injuries in manufacturing industry at individual, environmental, and management levels at home and abroad, and rich research results on the impacts of psychological factors on occupational injuries. However, factors associated with occupational injuries in equipment safety and engineering like man-machine environment need further research. Influencing factors at all levels should be comprehensively considered in the surveillance and intervention of occupational injuries in manufacturing industry to protect health and safety of workers.

OBJECTIVE: To analyze the differentially expressed genes (DEGs) between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) with bioinformatics analysis and search for potential biomarkers for clinical diagnosis of nonsmall cell lung cancer (NSCLC). METHODS: The gene expression profiling datasets of LUAD and LUSC were acquired. The transcriptome differences between LUAD and LUSC were identified using R language processing and t-test analysis. The differential expressions of the genes were shown by Venn diagram. The DEGs identified by GEO2R were analyzed with DAVID and Ingenuity Pathway Analysis (IPA) to identify the signaling pathways and biomarkers that could be used for differential diagnosis of LUAD and LUSC. The TCGA data and the biomarker expression data from clinical lung cancer samples were used to verify the differential expressions of the Osteoarthritis pathway and LXR/RXR between LUAD and LUSC. We further examined the differential expressions of miR-181 and its two target genes, and , in 23 clinical specimens of lung squamous cell carcinoma and the paired adjacent tissues. RESULTS: GEO data analysis identified 851 DEGs (including 276 up-regulated and 575 down-regulated genes) in LUAD and 885 DEGs (including 406 up-regulated and 479 down-regulated genes) in LUSC. DAVID and IPA analysis revealed that leukocyte migration and inflammatory responses were more abundant in LUAD than in LUSC. Osteoarthritis pathway was inhibited in LUAD and activated in LUSC. IPA analysis showed that transcription factors (GATA4, RELA, YBX1, TP63 and MBD2), cytokines (WNT5A and IL1A) and microRNAs (miR-34a, miR-181b and miR-15a) differed significantly between LUAD and LUSC. miR-34a with IL-1A, miR-15a with YBX1, and miR-181b with WNT5A and MBD2 could serve as the paired microRNA and mRNA targets for differential diagnosis of NSCLC subtypes. Analysis of the clinical samples showed an increased expression of miR-181b-5p and the down-regulation of WNT5A, which could be used as molecular markers for the diagnosis of LUSC. CONCLUSIONS Through transcriptome analysis, we identified candidate genes, paired microRNAs and pathways for differentiating LUAD and LUSC, and they can provide novel differential diagnosis and therapeutic strategies for LUAD and LUSC.
Adenocarcinoma of Lung ; Carcinoma, Non-Small-Cell Lung ; Carcinoma, Squamous Cell ; Humans ; Lung Neoplasms ; MicroRNAs ; Y-Box-Binding Protein 1