Background The positive rate of work-related musculoskeletal disorders (WMSDs) among coal mine workers remains high, which seriously affects the quality of life of the workers. Objective To estimate the prevalence of WMSDs among coal miners in Shanxi Province and analyze their influencing factors. Methods From May to December 2023, 2315 coal miners from a coal mine enterprise inShanxi Province were selected by convenience sampling, and the self-administered Basic Situation Survey Scale, Musculoskeletal Disorders Questionnaire, Effort-Reward Imbalance Questionnaire, and Pittsburgh Sleep Quality Scale were used to evaluate general demographic characteristics, work organization characteristics, living habits, sleep quality, occupational stress, and occurrence of WMSDs symptoms and the corresponding absences (sickness absence) in past 1 year. The positive rate and absenteeism rate of WMSDs were caculated, and Pearson's chi-square test was used for identify influencing factors of WMSDs, and finally a binary logistic regression method was used to further studying the factors. Results A total of 2577 questionnaires were distributed in this survey, and 2315 valid questionnaires were recovered, with an effective recovery rate of 89.9%. The positive rate of WMSDs symptoms was 48.7% (1127/2315), the absenteeism rate due to WMSDs was 22.6% (523/2315), and the waist (17.5%), neck (11.7%), and knee (9.0%) were the most common areas presenting WMSDs symptoms. The results of logistic regression showed that compared with ≤10 years of service, the risk of WMSDs was higher for those with > 20 years of service (OR=2.167, 95%CI: 1.419, 3.311). Compared with the daily working time of ≤8 h, the risk of WMSDs was higher for those >8 h daily working time (OR=1.463, 95%CI: 1.211, 1.767). A higher risk of WMSDs was reported in workers with moderate labor intensity (OR=1.247, 95%CI: 1.009, 1.542) or heavy labor intensity (OR=1.570, 95%CI: 1.215, 2.027) than those with light labor intensity. The higher the education level (OR _{high school and technical secondary school}=1.866, 95%CI: 1.435, 2.425; OR _{junior college/bachelor degree or above}=1.953, 95%CI: 1.445, 2.639), the higher the risk of WMSDs. The risk of WMSDs was higher in workers reporting smoking (OR=1.225, 95%CI: 1.021, 1.470) or alcohol consumption (OR=1.345, 95%CI: 1.122, 1.612). The risk of WMSDs in coal miners with high occupational stress (OR=1.229, 95%CI:1.030, 1.466) or those with sleep disorders (OR=3.616, 95%CI:2.824, 4.629) was higher than that in workers with low occupational stress or no sleep disorders respectively. Conclusion The positive rate of WMSDs among coal mine personnel in Shanxi Province is high, and education level, length of service, daily working hours, smoking, alcohol consumption, labor intensity, sleep disorders, and occupational stress are influencing factors for WMSDs.

Background Exposure to polycyclic aromatic hydrocarbons (PAHs) is associated with the development of metabolic syndrome (MS). However, the role of amino acids in PAH-induced MS remains unclear. Objective To explore the impact of PAHs exposure on the incidence of MS among coking workers, and to determine potential modifying effect of amino acid on this relationship. Methods Unmatched nested case-control design was adopted and the baseline surveys of coking workers were conducted in two plants in Taiyuan in 2017 and 2019, followed by a 4-year follow-up. The cohort comprised 667 coking workers. A total of 362 participants were included in the study, with 84 newly diagnosed cases of MS identified as the case group and 278 as the control group. Urinary levels of 11 PAH metabolites and plasma levels of 17 amino acids were measured by ultrasensitive performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Logistic regression was used to estimate the association between individual PAH metabolites and MS. Stratified by the median concentration of amino acids, Bayesian kernel machine regression (BKMR) model was employed to assess the mixed effects of PAHs on MS. Due to the skewed data distribution, all PAH metabolites and amino acids in the analysis were converted by natural logarithm ln (expressed as lnv). Results The median age of the 362 participants was 37 years, and 83.2% were male. Compared to the control group, the case group exhibited higher concentrations of urinary 2-hydroxyphenanthrene (2-OHPhe), 9-hydroxyphenanthrene (9-OHPhe), and hydroxyphenanthrene (OHPhe) (P=0.005, P=0.049, and P=0.004, respectively), as well as elevated levels of plasma branched chain amino acid (BCAA) and aromatic amino acid (AAA) (P<0.05). After being adjusted for confounding factors, for every unit increase in lnv_2-OHPhe in urine, the OR (95%CI) of MS was 1.57 (1.11, 2.26), and for every unit increase in lnv_OHPhe, the OR (95%CI) of MS was 1.82 (1.16, 2.90). Tyrosine, leucine, and AAA all presented a significant nonlinear correlation with MS. At low levels, tyrosine, leucine, and AAA did not significantly increase the risk of MS, but at high levels, they increased the risk of MS. In the low amino acid concentration group, as well as in the low BCAA and low AAA concentration groups, it was found that compared to the PAH metabolite levels at the 50th percentile (P₅₀), the log-odds of MS when the PAH metabolite levels was at the 75th percentile (P₇₅) were 0.158 (95%CI: 0.150, 0.166), 0.218 (95%CI: 0.209, 0.227), and 0.262 (95% CI: 0.241, 0.282), respectively, However, no correlation between PAHs and MS was found in the high amino acid concentration group. Conclusion Amino acids modify the effect of PAHs exposure on the incidence of MS. In individuals with low plasma amino acid levels, the risk of developing MS increases with higher concentrations of mixed PAH exposure. This effect is partly due to the low concentrations of BCAA and AAA.

Background Thyroid hormones are crucial for development and proper functioning of human physiological systems. Current research on the thyroid mainly focuses on the impacts of lifestyle factors on thyroid dysfunction, while less attention is paid to the factors affecting thyroid hormone levels, especially occupational hazards, which warrants further investigation. Objective To investigate the associations between occupational hazard exposure and thyroid-stimulating hormone (TSH) and thyroid hormone levels in male coal mine workers. Methods A cross-sectional study design was adopted. A total of 12564 workers who participated in the occupational health check-ups at the Xishan Coal Electricity (Group) Corporation Occupational Disease Prevention and Control Institute in 2023 and met the inclusion and exclusion criteria were selected as research subjects. A self-designed electronic questionnaire was used to collect basic information, occupational history, and lifestyle habits of all study subjects. Height, weight, thyroid function test results, and occupational hazard exposure of the study subjects were obtained through occupational health examinations and routine workplace occupational hazard detection records. Generalized linear regression was used to analyze the associations between occupational hazard exposure and the levels of TSH and thyroid hormones. Results The median (P₂₅, P₇₅) levels of triiodothyronine (T3), thyroxine (T4), free triiodothyronine (FT3), free thyroxine (FT4), and TSH in the included 12564 male coal mine workers were 1.16 (1.03, 1.29) ng·mL⁻¹, 7.70 (6.70, 8.90) μg·dL⁻¹, 3.63 (3.40, 3.84) pg·mL⁻¹, 1.19 (1.08, 1.30) ng·dL⁻¹, and 1.93 (1.36, 2.78) μIU·mL⁻¹, respectively. The overall abnormality rate of thyroid hormones was 2.83%, with the highest rate for subclinical hypothyroidism (1.83%), followed by hyperthyroidism (0.37%), hypothyroidism (0.32%), and subclinical hyperthyroidism (0.31%). After adjustment for confounding factors, the generalized linear regression model showed that long working hours were associated with higher levels of T3 and FT3, with β (95%CI) values of 0.011 (0.003, 0.019) and 0.038 (0.019, 0.057) respectively. Night shift work was linked to increased TSH levels and decreased FT4 levels, with β (95%CI) values of 0.171 (0.016, 0.326) and −0.012 (−0.019, −0.006) respectively. Coal dust exposure was associated with decreased levels of T3 and T4, with β (95%CI) values of −0.022 (−0.037, −0.008) and −0.320 (−0.434, −0.207) respectively. Noise exposure was related to decreased levels of T4 and FT4, with β (95%CI) values of −0.102 (−0.166, −0.038) and −0.020 (−0.027, −0.013) respectively. Conclusion The TSH and thyroid hormone levels of coal miners are mostly within the normal reference ranges, with a low abnormality rate. Long work hours, night shift work, coal dust, and noise are associated with the levels of TSH and thyroid hormone levels in the male miners. Coal companies should reasonably arrange working hours, optimize the night shift scheduling system, and enhance protection against coal dust and noise to promote occupational health and safeguard the physical health of miners.

Background Coal workers' pneumoconiosis is a serious occupational disease in China. Exhaled volatile organic compounds (VOCs) can serve as the "breath fingerprint" of internal pathological processes, which provides a theoretical basis for exhaled VOCs to be used as potential non-invasive biomarkers for early diagnosis of coal workers' pneumoconiosis. Objective To screen out the characteristic VOCs and important characteristic VOCs of exhaled air in patients with coal workers' pneumoconiosis, and to explore the potential of these VOCs as biomarkers for early non-invasive diagnosis of the disease. Methods In this study, 27 VOCs in the exhaled breath of 22 patients with stage I coal workers' pneumoconiosis, 77 workers exposed to dust, and 92 healthy controls were quantitatively detected by thermal desorption gas chromatography-mass spectrometry (TD-GC-MS). Substances with P<0.05 in univariate analysis and variable importance projection (VIP) >1 in supervised orthogonal partial least squares discriminant analysis (OPLS-DA) model were selected as the characteristic VOCs for early diagnosis of coal workers' pneumoconiosis. Age was included in the LASSO regression model as a covariate to screen out important characteristic VOCs, and the diagnostic performance was evaluated by receiver operating characteristic (ROC) curve. Spearman correlation was further used to explore the correlation between important characteristic VOCs and clinical lung function indicators. Results Through univariate analysis and OPLS-DA modeling, 8 VOCs were selected, including 2-methylpentane, 3-methylpentane, n-hexane, methylcyclopentane, n-heptane, methylcyclohexane, 4-methyl-2-pentanone, and 2-hexanone, in exhaled breath of patients with coal workers' pneumoconiosis. The concentrations of 4 VOCs, including 3-methylpentane, n-hexane, 4-methyl-2-pentanone, and 2-hexanone, showed a decreasing trend with the increase of dust exposure years. By LASSO regression, the important characteristic VOCs of the coal workers' pneumoconiosis group and the dust exposure group were n-hexane, methylcyclohexane and 4-methyl-2-pentanone, and the important characteristic VOCs of the coal workers' pneumoconiosis group and the healthy group were 2-methyl-pentane and 4-methyl-2-pentanone. The ROC analysis showed that the area under the curve (AUC) of n-hexane, methylcyclohexane, and 4-methyl-2-pentanone were 0.969, 0.909, and 0.956, respectively, and the AUC of combined diagnosis was 0.988 and its Youden index was 0.961, suggesting that these results can serve as a valuable reference for further research on early diagnosis. The Correlation analysis found that there was a positive correlation between n-hexane and lung function indicators in the important characteristic VOCs, indicating that it could indirectly reflect the obstruction of lung function ventilation, further proving that important characteristic VOCs have the potential to monitor lung function decline. Conclusion Three important characteristic VOCs selected in this study have the potential to be used as non-invasive biomarkers for early diagnosis and disease monitoring of coal workers' pneumoconiosis, and are worthy of further study and verification.

Objective To report the diagnosis of a canine distemper virus outbreak among a colony of cynomolgus monkeys at an experimental monkey farm in 2019. MethodsA total of 46 samples were collected from 21 diseased cynomolgus monkeys (exhibiting symptoms such as facial rash, skin scurf, runny nose, and diarrhea) and from one deceased monkey at an experimental monkey breeding farm in South China in late 2019, including serum, skin rash swabs, and anticoagulated whole blood, liver, lung, and skin tissues were submitted for testing. All submitted samples were tested for canine distemper virus gene fragments using real-time quantitative PCR, while immunohistochemical staining was performed to detect canine distemper virus nucleoprotein in lung tissues. The skin tissue of the deceased monkey was ground and sieved. The filtrate was inoculated into a monolayer MDCK cell line for virus isolation. Then, whole-genome sequencing was performed to identify the isolated virus. The Clustal Omega tool was used to align and analyze the homology of different Asian canine distemper virus isolates. A phylogenetic tree was constructed, followed by genetic evolutionary analysis. ResultsClinical retrospective analysis revealed that the diseased cynomolgus monkeys exhibited symptoms similar to those observed in cynomolgus monkeys infected with measles virus. Necropsy findings showed red lesions in the lungs and significant hemorrhage in the colonic mucosa. Real-time quantitative PCR detected canine distemper virus nucleic acid in the serum, skin rash swabs of the infected monkeys, and various tissue samples of the deceased monkey, all of which tested positive. Calculation based on the standard curve formula indicated the viral load was highest in the skin tissue. Immunohistochemical staining of the deceased monkey's lung tissue demonstrated aggregation of CDV nucleoprotein in alveolar epithelial cells, bronchi, and bronchioles. A CDV strain was isolated from the skin tissue of the deceased monkey. Phylogenetic analysis indicated that this strain shares the closest relationship (98.86%) with the Asian-1 type canine distemper virus strain CDV/dog/HCM/33/140816, previously identified in dogs in Vietnam. ConclusionBased on comprehensive analysis of clinical symptoms, nucleic acid detection, viral protein immunohistochemistry, and whole-genome sequencing results, the diagnosis confirms that the cynomolgus monkeys in this facility are infected with canine distemper virus. It is recommended to include canine distemper virus as a routine surveillance target in captive monkey populations. Additionally, this study provides a foundation for further research on the molecular biological characteristics of canine distemper virus.

Objective To report the diagnosis of a canine distemper virus outbreak among a colony of cynomolgus monkeys at an experimental monkey farm in 2019. MethodsA total of 46 samples were collected from 21 diseased cynomolgus monkeys (exhibiting symptoms such as facial rash, skin scurf, runny nose, and diarrhea) and from one deceased monkey at an experimental monkey breeding farm in South China in late 2019, including serum, skin rash swabs, and anticoagulated whole blood, liver, lung, and skin tissues were submitted for testing. All submitted samples were tested for canine distemper virus gene fragments using real-time quantitative PCR, while immunohistochemical staining was performed to detect canine distemper virus nucleoprotein in lung tissues. The skin tissue of the deceased monkey was ground and sieved. The filtrate was inoculated into a monolayer MDCK cell line for virus isolation. Then, whole-genome sequencing was performed to identify the isolated virus. The Clustal Omega tool was used to align and analyze the homology of different Asian canine distemper virus isolates. A phylogenetic tree was constructed, followed by genetic evolutionary analysis. ResultsClinical retrospective analysis revealed that the diseased cynomolgus monkeys exhibited symptoms similar to those observed in cynomolgus monkeys infected with measles virus. Necropsy findings showed red lesions in the lungs and significant hemorrhage in the colonic mucosa. Real-time quantitative PCR detected canine distemper virus nucleic acid in the serum, skin rash swabs of the infected monkeys, and various tissue samples of the deceased monkey, all of which tested positive. Calculation based on the standard curve formula indicated the viral load was highest in the skin tissue. Immunohistochemical staining of the deceased monkey's lung tissue demonstrated aggregation of CDV nucleoprotein in alveolar epithelial cells, bronchi, and bronchioles. A CDV strain was isolated from the skin tissue of the deceased monkey. Phylogenetic analysis indicated that this strain shares the closest relationship (98.86%) with the Asian-1 type canine distemper virus strain CDV/dog/HCM/33/140816, previously identified in dogs in Vietnam. ConclusionBased on comprehensive analysis of clinical symptoms, nucleic acid detection, viral protein immunohistochemistry, and whole-genome sequencing results, the diagnosis confirms that the cynomolgus monkeys in this facility are infected with canine distemper virus. It is recommended to include canine distemper virus as a routine surveillance target in captive monkey populations. Additionally, this study provides a foundation for further research on the molecular biological characteristics of canine distemper virus.

BACKGROUND: It is inaccurate to reflect the level of dust exposure through working years. Furthermore, identifying a predictive indicator for lung function decline is significant for coal miners. The study aimed to explored whether club cell secretory protein (CC16) levels can reflect early lung function changes. METHODS: The cumulative respiratory dust exposure (CDE) levels of 1,461 coal miners were retrospectively assessed by constructed a job-exposure matrix to replace working years. Important factors affecting lung function and CC16 were selected by establishing random forest models. Subsequently, the potential of CC16 to reflect lung injury was explored from multiple perspectives. First, restricted cubic spline (RCS) models were used to compare the trends of changes in lung function indicators and plasma CC16 levels after dust exposure. Then mediating analysis was performed to investigate the role of CC16 in the association between dust exposure and lung function decline. Finally, the association between baseline CC16 levels and follow-up lung function was explored. RESULTS: The median CDE were 35.13 mg/m³-years. RCS models revealed a rapid decline in forced vital capacity (FVC), forced expiratory volume in the first second (FEV₁), and their percentages of predicted values when CDE exceeded 25 mg/m³-years. The dust exposure level (<5 mg/m³-years) causing significant changes in CC16 was much lower than the level (25 mg/m³-years) that caused changes in lung function indicators. CC16 mediated 11.1% to 26.0% of dust-related lung function decline. Additionally, workers with low baseline CC16 levels experienced greater reductions in lung function in the future. CONCLUSIONS CC16 levels are more sensitive than lung indicators in reflecting early lung function injury and plays mediating role in lung function decline induced by dust exposure. Low baseline CC16 levels predict poor future lung function.
Uteroglobin/blood* ; Humans ; Dust/analysis* ; Occupational Exposure/analysis* ; Male ; Middle Aged ; Adult ; Retrospective Studies ; Lung Injury/chemically induced* ; Coal Mining ; Biomarkers/blood* ; China/epidemiology* ; Air Pollutants, Occupational ; Female

Objective: To investigate the relationship of polycyclic aromatic hydrocarbons (PAHs) exposure, S-adenosylhomocysteine hydrolase (SAHH) activity and long noncoding RNA H19 gene expression in the urine of coke oven workers. Methods: In September 2019, in a coking plant in Taiyuan City, 146 male workers who had worked in coke oven operations for one year were selected through a completely random sampling method, and their basic personal information was collected by questionnaire survey, and blood and urine samples were collected. The levels of 4 PAHs metabolites 2-hydroxfluorene (2-FLU), 2- hydroxynaphthalene (2-NAP), 9-hydroxyphenanthren (9-PHE), and 1-hydroxypyrene (1-OHP) in urine were detected by high performance liquid chromatography (HPLC) -fluorescence detection method. HPLC-UV detection method was used to detect the content of S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) in plasma, and the SAHH activity value was obtained by calculating the ratio. Reverse transcription PCR method was used to determine the H19 gene expression level. Urine levels of 2-FLU, 2-NAP, 9-PHE, and 1-OHP were divided into Q(1), Q(2), Q(3), and Q(4) groups according to quartiles (P(25), P(50), P(75)). Regression, trend test and restricted cubic splines were used to analyze the relationship among PAHs metabolites, SAHH activity, H19 gene expression and their dose-response. Results: The median age of coke oven workers was 39.60 years old, the median length of service was 20.38 years, and the urinary levels of 2-FLU, 2-NAP, 9- PHE, and 1-OHP were 0.29, 0.74, 0.09, and 0.06 μg/mmol Cr, respectively. The levels of 2-FLU, 2-NAP and 9-PHE in the urine of workers were significantly different between groups with different 1-OHP levels (P<0.05). After adjusting for age, length of service, smoking, drinking, and levels of 2-FLU, 2-NAP and 9-PHE, SAHH activity decreased with the increase of urinary 1-OHP level (OR=0.63, 95%CI: 0.41-0.98, P=0.038), showing a nonlinear relationship (P(nonlinear)= 0.030). H19 gene expression increased with the increase of urinary 1- OHP level (OR=1.51, 95%CI: 1.03-2.19, P=0.033), there was a linear relationship (P(trend)= 0.058). The relationship between the other three metabolites in urine and SAHH activity and H19 gene expression was not statistically significant (P>0.05) . Conclusion: Urinary 1-OHP level may be a risk factor for decreased SAHH activity and increased H19 gene expression in coke oven workers.
Humans ; Adult ; Coke/analysis* ; Polycyclic Aromatic Hydrocarbons/analysis* ; Occupational Exposure/analysis* ; Pyrenes/analysis* ; Smoking/urine*

The incidence of early-onset colorectal cancer is increasing year by year, and it occupies an important position in colorectal cancer. Most of the characteristics of patients with early-onset colorectal cancer are different from those with late-onset colorectal cancer, the patients are diagnosed in a late stage, and their pathological manifestations show a type of poor prognosis. At present, there is a lack of consensus and guideline for the diagnosis, treatment and screening of early-onset colorectal cancer. A full understanding of the characteristics of early-onset colorectal cancer helps to understand its pathogenesis and guide screening and treatment to reduce the incidence and mortality of colorectal cancer. This article reviews the clinicopathological characteristics, molecular pathological mechanisms, diagnosis and treatment, and prognosis of early-onset colorectal cancer, in order to provide references for elucidating its etiology and formulating scientific and standardized screening strategies.

Objective: To investigate the diagnostic value of serum levels of aquaporin-4 (AQP4) and matrix metalloproteinase-9 (MMP-9) in predicting malignant cerebral infarction in patients with cerebral infarction. Methods: The clinical data about 66 patients with hemisphere massive cerebral infarction were collected. According to clinical symptoms and brain computed tomography (CT) findings, the patients were divided into malignant cerebral infarction group (MCI) and non-MCI group. The serum levels of AQP4 and MMP-9 were detected 1, 4, 7 days. The diagnostic value of AQP4 and MMP-9 in predicting occurrence of MCI was analysed by receiver operating characteristic (ROC) curve. Results: The serum levels of AQP4 and MMP-9 in MCI group were significantly higher than those in non-MCI group in the fourth day (P<0.05). In MCI group, AQP4 and MMP-9 in the fourth day were significant higher than other two time points (P<0.05). But in non-MCI group, AQP4 and MMP-9 in different time points have no differences (P>0.05). ROC curve analysis showed that the aera under curve for the serum levels of AQP4 was 0.654 (95% CI: 0.516-0.792). When the serum AQP4=23.49 μg/L, the sensitivity and specificity were 0.57, 0.74, respectively. Conclusions Serum AQP4 and MMP-9 levels were increased in patients with MCI. Combined detection of serum AQP4 and MMP-9 is helpful for early differential diagnosis of MCI.