Background The adverse effects of long working hours, shift rotation, and job stress on the physical and mental health of occupational populations require urgent attention. Objective To investigate and compare the positive rates of WMSDs between different industries, analyze the exposure status of long working hours, shift rotation, and job stress among key occupational groups, and evaluate the impacts of these factors on WMSDs in the manufacturing and service industries. Methods The study subjects were derived from key occupational populations in Yunnan Province, recruited by the Chinese National Occupational Health Literacy Monitoring Survey in 2022. A cross-sectional design was used for this survey. The key occupational populations were recruited from the secondary industry (manufacturing industry, metal mining and beneficiation industry, and non-metal mining and beneficiation industry) by stratified random sampling and from the tertiary industry (medical and healthcare industry, education industry, environmental sanitation industry, transportation industry, and express/takeaway delivery industry) by proportional probability sampling, and 12014 front-line workers were finally included as survey participants. General information, work-related factors (shift rotation, weekly working hours, job stress, etc.) and WMSDs assessment results were obtained through a web-based self-reported questionnaire, and the associations of long working hours, shift rotation, and job stress with WMSDs were analyzed using χ² test and logistic regression. Results The average positive rate of WMSDs among the key occupational groups in Yunnan Province was 77.2%. The positive rate of WMSDs in the secondary industry group was 69.4%, while it was 81.6% in the tertiary industry group, with a statistically significant difference (P<0.001). Among the eight surveyed sectors, the education sector had the highest positive rate of WMSDs (94.2%). The single-site WMSDs mainly involved the neck, shoulders, and low back. In the secondary industry, WMSDs was reported in 1−2 body parts, while in the tertiary industry, WMSDs was mainly reported in multiple (≥5) body parts. Long working hours (OR: 1.119, 1.165, 1.163, respectively), shift rotation (OR: 1.094, 1.199, 1.230, respectively), and job stress (OR: 1.795, 1.854, 2.006, respectively) were risk factors for WMSDs in the neck, shoulder, or low back, and all three were also risk factors for multi-site WMSDs. Moreover, as the number of involved body parts increased, the effects of long working hours and job stress became more pronounced. For 1-2, 3-4, and 5 or more body parts compared to no pain reported, their OR values were 0.971 (95%CI: 0.871, 1.082), 1.133 (95%CI: 1.004, 1.279), and 1.285 (95%CI: 1.155, 1.429) for long working hours, respectively, and the OR values were 1.009 (95%CI: 0.878, 1.160), 1.360 (95%CI: 1.174, 1.575), and 2.797 (95%CI: 2.471, 3.166) for job stress, respectively. Conclusion The positive rate of WMSDs is higher in the tertiary industry than that in the secondary industry among the key occupational groups in Yunnan Province. Long working hours, rotating shift work, and job stress could significantly increase the risk of WMSDs.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

AIM: To evaluate the diagnostic value of serum Th1-type cytokine levels and extraocular muscle-related parameters in thyroid-associated ophthalmopathy(TAO).METHODS: A retrospective study was conducted on 45 patients diagnosed with TAO in our hospital from January 2023 to December 2024, and 20 normal volunteers during the same period as controls. Venous blood samples of the patients were collected to detect the concentrations of Th1-type cytokines [interferon-γ(IFN-γ), tumor necrosis factor-α(TNF-α), interleukin-2(IL-2), and interleukin-12(IL-12)] in the serum. Additionally, the end diastolic velocity(Ved), velocity maximum(Vmax), resistance index(RI)of the central retinal artery, as well as the thickness and left-right diameter of the medial rectus muscle were measured. Logistic regression model was used to analyze the risk factors of TAO, and receiver operating characteristic curve(ROC)was adopted to evaluate the diagnostic efficacy of each index for the occurrence of TAO.RESULTS: The general information of the two groups was comparable. Compared with the normal control group, the serum concentrations of IFN-γ and TNF-α in TAO patients were significantly increased, Ved and Vmax were lower than those in the control group, and RI and the thickness of the medial rectus muscle were higher than those in the control group(all P<0.05). Logistic regression analysis showed that serum IFN-γ concentration, Ved, Vmax, and the thickness of the medial rectus muscle were all risk factors for TAO. ROC curve analysis indicated that the AUCs of serum IFN-γ concentration, Ved, Vmax, and the thickness of the medial rectus muscle for the diagnostic efficacy of TAO were 0.756, 0.769, 0.732, and 0.642, respectively. The combined detection of IFN-γ, Ved, Vmax, and the thickness of the medial rectus muscle had an AUC of 0.840 and a Youden index of 0.59, which was superior to the detection of a single indicator.CONCLUSION: The levels of serum Th1-type cytokines and extraocular muscle-related ultrasound indicators have certain value in the diagnosis of TAO. The combination of IFN-γ, Ved, Vmax, and the thickness of the medial rectus muscle has better diagnosis efficiency in TAO, which can provide a certain reference for the early diagnosis of TAO.

The effect of porcine SIRT5 on replication of foot and mouth disease virus type O(FMDV-O)and the underlying regulatory mechanism were investigated.Western blot and RT-qPCR analyses were employed to monitor expression of endoge-nous SIRT5 in PK-15 cells infected with FMDV-O.Three pairs of SIRT5-specific siRNAs were synthesized.Changes to SIRT5 and FMDV-O protein and transcript levels,in addition to virus copy numbers,were measured by western blot and RT-qPCR analyses.PK-15 cells were transfected with a eukaryotic SIRT5 expression plasmid.Western blot and RT-qPCR analyses were used to explore the impact of SIRT5 overexpression on FMDV-O replication.Meanwhile,RT-qPCR analysis was used to detect the effect of SIRT5 overexpression on the mRNA expression levels of type I interferon-stimulated genes induced by SeV and FMDV-O.The results showed that expression of SIRT5 was up-regulated in PK-15 cells infected with FMDV-O and siRNA interfered with SIRT5 to inhibit FMDV-O replication.SIRT5 overexpression promoted FMDV-O replication.SIRT5 over-expression decreased mRNA expression levels of interferon-stimulated genes induced by SeV and FMDV-O.These results suggest that FMDV-O infection stimulated expression of SIRT5 in PK-15 cells,while SIRT5 promoted FMDV-O rep-lication by inhibiting production of type I interferon-stimula-ted genes.These findings provide a reference to further ex-plore the mechanism underlying the ability of porcine SIRT5 to promote FMDV-O replication.

This study was aimed at understanding the detection rate,drug resistance characteristics,virulence characteris-tics,multi-locus sequence typing,and other molecular epidemic and pathogenic characteristics of Campylobacter jejuni and Campylobacter coli in children in Guangdong Province from 2020 to 2022.Anal swabs or stool samples of suspected infection cases in children from 2020 to 2022 were collected from two hospitals in Guangzhou,Guangdong Province.Campylobacter was isolated and cultured through the filtration method,and identified with a microbial mass spectrometry system;antibiotic resist-ance was analyzed with the agar dilution method;bacterial genome nucleic acids were extracted,and whole-genome sequencing was conducted;and drug resistance genes,virulence genes,multi-locus sequence typing,and phylogenetic analysis based on whole-genome single nucleotide polymorphisms were analyzed from whole-genome sequencing results.First,53 strains of Campy-lobacter were detected through continuous routine monitoring in this study,with a positive detection rate of 2.94％.Among them,Campylobacter jejuni accounted for 81.13％(43/53)and Campylobacter coli accounted for 18.87％(10/53).In addition,16 strains of Campylobacter were screened through multi-pathogen surveillance,including 11 strains of Campylobacter jejuni and 5 strains of Campylobacter coli.Drug resistance ex-periments and whole genome sequencing were conducted on 46 Campylobacter isolates,including 33 isolates of Campylobacter jejuni and 13 isolates of Campylobacter coli.The resistance rate of Campylobacter to erythromycin,a widely used clinical treatment,was21.73％(10/46);that to tetracycline was 80.43％(37/46);those to the quinolone antibiotics nalidixic acid and ciprofloxacin were 76.08％(35/46)and 71.73％(33/46)respectively;and that to chloramphenicol was lowest,at 2.17％(1/46).The drug resistance rate was generally higher for Campylobacter coli than Campylobacter jejuni,and the differences in the indicators of erythromycin,gentamicin,streptomycin,telithromycin,and clindamycin were statistically significant.A total of 30 isolates of multidrug-resistant Campylobacter were detected,including nine multidrug-resistant phenotypes.Whole-ge-nome sequence analysis indicated that 46 Campylobacter isolates carried antibiotic resistance genes for antibiotics such as quino-lones,tetracyclines,β-lactams,and aminoglycosides,and carried 128 virulence factor genes in five categories.All 46 isolates of Campylobacter were identified as 35 ST type through MLST typing,and phylogenetic analysis indicated no obvious dominant ST type.Campylobacter coli had more SNPs than Campylobacter jejuni.In conclusion,the positive detection rate of Campy-lobacter in Guangzhou City,Guangdong Province stabilized from 2020 to 2022,and the detection rate of Campylobacter jejuni was higher than that of Campylobacter coli.Campylobacter isolates were resistant to tetracyclines and quinolone,and showed a wide spectrum of multi-drug resistance,which was relatively severe among Campylobacter coli.Resistance genes and drug-resistant phenotypes were correlated and had predictive significance.The virulence genes of Campylobacter jejuni were more a-bundant than those of Campylobacter coli,possibly because of the higher detection rate and pathogenicity of Campylobacter jejuni.The phylogenetic tree showed clear branches with high genetic diversity and no clearly dominant clonal group.

Background: Triglyceride glucose (TyG) and TyG-body mass index (TyG-BMI) are reliable surrogate indices of insulin resistance and used for risk stratification and outcome prediction in patients with atherosclerotic cardiovascular disease (ASCVD). Here, we inserted estimated average glucose (eAG) into the TyG (TyAG) and TyG-BMI (TyAG-BMI) as derived parameters and explored their clinical significance in cardiovascular risk prediction. Methods: This was a population-based cohort study of 9,944 Chinese patients with ASCVD. The baseline admission fasting glucose and A1C-derived eAG values were recorded. Cardiovascular events (CVEs) that occurred during an average of 38.5 months of follow-up were recorded. We stratified the patients into four groups by quartiles of the parameters. Baseline data and outcomes were analyzed. Results: Distribution of the TyAG and TyAG-BMI indices shifted slightly toward higher values (the right side) compared with TyG and TyG-BMI, respectively. The baseline levels of cardiovascular risk factors and coronary severity increased with quartile of TyG, TyAG, TyG-BMI, and TyAG-BMI (all P<0.001). The multivariate-adjusted hazard ratios for CVEs when the highest and lowest quartiles were compared from low to high were 1.02 (95% confidence interval [CI], 0.77 to 1.36; TyG), 1.29 (95% CI, 0.97 to 1.73; TyAG), 1.59 (95% CI, 1.01 to 2.58; TyG-BMI), and 1.91 (95% CI, 1.16 to 3.15; TyAG-BMI). The latter two showed statistical significance. Conclusion This study suggests that TyAG and TyAG-BMI exhibit more information than TyG and TyG-BMI in disease progression among patients with ASCVD. The TyAG-BMI index provided better predictive performance for CVEs than other parameters.