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.

OBJECTIVE: To observe the clinical efficacy of different acupuncture methods in the treatment of ankylosing spondylitis (AS) at different stages. METHODS: Thirty-two patients with AS were treated with acupuncture at ashi points (tendon focus), triple acupuncture method was used in the acute phase, accompanied needling method was used in the remission phase, once a day, 5 times a week for 4 weeks. The Bath ankylosing spondylitis disease activity index (BASDAI) score, Bath ankylosing spondylitis functional index (BASFI) score and TCM symptom grade quantitative standard score before and after treatment were observed, and the efficacy was evaluated. RESULTS: After treatment, the BASDAI score, BASFI score and TCM symptom grade quantitative standard score were reduced compared with those before treatment (P<0.01), the effective rate was 96.9% (31/32). CONCLUSION Different acupuncture methods in the treatment of AS at different stages could improve signs and symptoms, such as pain, activity limitation and morning stiffness.
Humans ; Spondylitis, Ankylosing/physiopathology* ; Acupuncture Therapy/methods* ; Male ; Female ; Adult ; Middle Aged ; Young Adult ; Acupuncture Points ; Treatment Outcome

This study aims to investigate the in vitro mechanisms underlying the beneficial effects of puerarin on hepatic insulin resistance(IR) based on the carbohydrate response element-binding protein(ChREBP)/peroxisome proliferator-activated receptor(PPAR)α/PPARγ axis involved in glucose and lipid metabolism. An IR-HepG2 cell model was established by treating cells with dexamethasone for 48 h, and the cells were then treated with 10, 20, and 40 μmol·L~(-1) puerarin for 24 h. Glucose levels and output in the extracellular fluid were measured by the glucose oxidase method, while cell viability was assessed by the cell counting kit-8(CCK-8) assay. The adenosine triphosphate(ATP) content and glycogen synthesis were evaluated through chemiluminescence and periodic acid-Schiff staining, respectively. Western blot was employed to quantify the protein levels of forkhead box protein O1(FoxO1), phosphorylated forkhead box protein O1 [p-FoxO1(Ser256)], glucagon, phosphofructokinase, liver type(PFKL), pyruvate kinase L-R(PKLR), pyruvate dehydrogenase complex 1(PDHA1), insulin receptor substrate 2(IRS2), phosphatidylinositol 3-kinase p85(PI3KR1), phosphorylated protein kinase B [p-Akt(Thr308)], glycogen synthase(GYS), glycogen phosphorylase, liver type(PYGL), adiponectin(ADPN), ChREBP, PPARα, and PPARγ. Additionally, the protein levels of acetyl-CoA carboxylase 1(ACC1), phosphorylated ATP citrate lyase [p-ACLY(Ser455)], sterol regulatory element binding protein 1c(SREBP-1c), peroxisome proliferator-activated receptor gamma coactivator 1α(PGC1α), carnitine palmitoyltransferase 1α(CPT1α), and glucagon receptor(GCGR) were also determined. Immunofluorescence was employed to visualize the expression and nuclear location of ChREBP/PPARα/PPARγ. Furthermore, quantitative PCR with the antagonists GW6471 and GW9662 was employed to assess Pparα, Pparγ, and Chrebp. The findings indicated that puerarin effectively reduced both the glucose level and glucose output in the extracellular fluid of IR-HepG2 cells without obvious effect on the cell viability, and it increased intracellular glycogen and ATP levels. Puerarin down-regulated the protein levels of FoxO1 and glucagon while up-regulating the protein levels of p-FoxO1(Ser256), PFKL, PKLR, PDHA1, IRS2, PI3KR1, p-Akt(Thr308), GYS, PYGL, ADPN, ACC1, SREBP-1c, p-ACLY(Ser455), PGC1α, CPT1α, and GCGR in IR-HepG2 cells. Furthermore, puerarin up-regulated both the mRNA and protein levels of ChREBP, PPARα, and PPARγ and promoted the translocation into the nucleus. GW6471 was observed to down-regulate the expression of Pparα while up-regulating the expression of Chrebp and Pparγ. GW9662 down-regulated the expression of Pparγ while up-regulating the expression of Pparα, with no significant effect on Chrebp. In summary, puerarin activated the hepatic ChREBP/PPARα/PPARγ axis, thereby coordinating the glucose and lipid metabolism, promoting the conversion of glucose to lipids to exert the blood glucose-lowering effect.
Isoflavones/pharmacology* ; Humans ; PPAR gamma/genetics* ; Hep G2 Cells ; Glucose/metabolism* ; Lipid Metabolism/drug effects* ; PPAR alpha/genetics* ; Liver/drug effects* ; Basic Helix-Loop-Helix Leucine Zipper Transcription Factors/genetics* ; Insulin Resistance

This paper aims to investigate the hypoglycemic effect and mechanism of berberine in improving energy metabolism based on the multi-pathway regulation of brain and muscle aromatic hydrocarbon receptor nuclear translocal protein 1(BMAL1): cyclin kaput complex of day-night spontaneous output cyclin kaput(CLOCK). The dexamethasone-induced hepatic insulin resistance(IR) HepG2 cell model was used; 0.5, 1, 5, 10, 20 μmol·L~(-1) berberine were administered at 15, 18, 21, 24, 30, 36 h. The time-dose effect of glucose content in extracellular fluid was detected by glucose oxidase method. The optimal dosage and time of berberine were determined for the follow-up study. Glucose oxidase method and chemiluminescence method were respectively performed to detect hepatic glucose output and relative content of ATP in cells; Ca~(2+), reactive oxygen species(ROS), mitochondrial structure and membrane potential were detected by fluorescent probes. Moreover, ultraviolet colorimetry method was used to detect the liver type of pyruvate kinase(L-PK) and phosphoenol pyruvate carboxykinase(PEPCK). In addition, pyruvate dehydrogenase E1 subunit α1(PDHA1), phosphate fructocrine-liver type(PFKL), forkhead box protein O1(FoxO1), peroxisome proliferator-activated receptor gamma co-activator 1α(PGC1α), glucose-6-phosphatase(G6Pase), glucagon, phosphorylated nuclear factor-red blood cell 2-related factor 2(p-Nrf2)(Ser40), heme oxygenase 1(HO-1), NAD(P)H quinone oxidoreductase 1(NQO1), fibroblast growth factor 21(FGF21), uncoupled protein(UCP) 1 and UCP2 were detected by Western blot. BMAL1:CLOCK complex was detected by immunofluorescence double-staining method, combined with small molecule inhibitor CLK8. Western blot was used to detect PDHA1, PFKL, FoxO1, PGC1α, G6Pase, glucagon, Nrf2, HO-1, NQO1, FGF21, UCP1 and UCP2 in the CLK8 group. The results showed that berberine downregulated the glucose content in extracellular fluid in IR-HepG2 cells in a time-and dose-dependent manner. Moreover, berberine inhibited hepatic glucose output and reduced intracellular Ca~(2+) and ROS whereas elevated JC-1 membrane potential and improved mitochondrial structure to enhance ATP production. In addition, berberine upregulated the rate-limiting enzymes such as PFKL, L-PK and PDHA1 to promote glycolysis and aerobic oxidation but also downregulated PGC1α, FoxO1, G6Pase, PEPCK and glucagon to inhibit hepatic gluconeogenesis. Berberine not only upregulated p-Nrf2(Ser40), HO-1 and NQO1 to enhance antioxidant capacity but also upregulated FGF21, UCP1 and UCP2 to promote energy metabolism. Moreover, berberine increased BMAL1, CLOCK and nuclear BMAL1:CLOCK complex whereas CLK8 reduced the nuclear BMAL1:CLOCK complex. Finally, CLK8 decreased PDHA1, PFKL, Nrf2, HO-1, NQO1, FGF21, UCP1, UCP2 and increased FoxO1, PGC1α, G6Pase and glucagon compared with the 20 μmol·L~(-1) berberine group. BMAL1:CLOCK complex inhibited gluconeogenesis, promoted glycolysis and glucose aerobic oxidation pathways, improved the reduction status within mitochondria, protected mitochondrial structure and function, increased ATP energy storage and promoted energy consumption in IR-HepG2 cells. These results suggested that berberine mediated BMAL1:CLOCK complex to coordinate the regulation of hepatic IR cells to improve energy metabolism in vitro.
Humans ; Berberine/pharmacology* ; Gluconeogenesis/drug effects* ; Hep G2 Cells ; Glucose/metabolism* ; Liver/drug effects* ; Energy Metabolism/drug effects* ; Hypoglycemic Agents/pharmacology* ; ARNTL Transcription Factors/genetics* ; Glycolysis/drug effects* ; Oxidation-Reduction/drug effects*