Background Pneumoconiosis remains a critical occupational disease in China. As a major industrial province, Hebei historically faced severe challenges regarding this condition. The 1986 national epidemiological survey ranked Hebei sixth in reported pneumoconiosis cases nationwide. Objective To analyze 76 years of pneumoconiosis data (1949–2024) in Hebei Province to provide evidence-based support for prevention and control strategies. Methods Occupational pneumoconiosis cases diagnosed in Hebei from 1949 to 2024 were included. Five-year intervals were used to analyze incidence composition, dust exposure duration, age at first diagnosis, and age at death. A hybrid model, integrating autoregressive integrated moving average (ARIMA) with generalized regression neural network (GRNN), was employed to predict case numbers for the 2025−2030 period. Results A total of 36107 cases of pneumoconiosis were recorded (2.10% female) in Hebei from 1949 to 2024. Stages I, II, and III accounted for 77.35%, 16.45%, and 6.20%, respectively. Silicosis (55.60%), coal workers’ pneumoconiosis (27.24%), and pottery workers’ pneumoconiosis (8.88%) were the predominant types. Observed trends included a shortened dust exposure duration [silicosis: (12.78±7.063) years in 2020–2024] and an increasing age at first diagnosis [(54.01±7.499) years in 2020–2024]. The case-fatality rate was 14.84%, with a rising age at death [(82.26±9.632) years in 2015–2019]. Three incidence peaks (1963, 1984, and 2014) correlated with national policies and industrialization phases. The number of pneumoconiosis cases showed a decreasing trend from 2015 to 2024. Chengde and Tangshan were identified as current high-risk areas. The ARIMA-GRNN model projected annual cases between 416 and 429 during 2025–2030. Conclusion In the past decade，the number of pneumoconiosis cases in Hebei Province had shown a decreasing trend, it is projected to plateau with no significant decline over the next five years. Furthermore, challenges such as the proportion of silicosis remaining high and shortened dust exposure duration remain severe. It is recommended to focus on key regions like Chengde (ore mining) and Tangshan (ceramics industry). A comprehensive strategy integrating stricter regulation, technological controls, model innovation, and targeted interventions should be implemented to achieve a further substantial reduction in pneumoconiosis incidence.

Background Pneumoconiosis remains a critical occupational disease in China. As a major industrial province, Hebei historically faced severe challenges regarding this condition. The 1986 national epidemiological survey ranked Hebei sixth in reported pneumoconiosis cases nationwide. Objective To analyze 76 years of pneumoconiosis data (1949–2024) in Hebei Province to provide evidence-based support for prevention and control strategies. Methods Occupational pneumoconiosis cases diagnosed in Hebei from 1949 to 2024 were included. Five-year intervals were used to analyze incidence composition, dust exposure duration, age at first diagnosis, and age at death. A hybrid model, integrating autoregressive integrated moving average (ARIMA) with generalized regression neural network (GRNN), was employed to predict case numbers for the 2025−2030 period. Results A total of 36107 cases of pneumoconiosis were recorded (2.10% female) in Hebei from 1949 to 2024. Stages I, II, and III accounted for 77.35%, 16.45%, and 6.20%, respectively. Silicosis (55.60%), coal workers’ pneumoconiosis (27.24%), and pottery workers’ pneumoconiosis (8.88%) were the predominant types. Observed trends included a shortened dust exposure duration [silicosis: (12.78±7.063) years in 2020–2024] and an increasing age at first diagnosis [(54.01±7.499) years in 2020–2024]. The case-fatality rate was 14.84%, with a rising age at death [(82.26±9.632) years in 2015–2019]. Three incidence peaks (1963, 1984, and 2014) correlated with national policies and industrialization phases. The number of pneumoconiosis cases showed a decreasing trend from 2015 to 2024. Chengde and Tangshan were identified as current high-risk areas. The ARIMA-GRNN model projected annual cases between 416 and 429 during 2025–2030. Conclusion In the past decade，the number of pneumoconiosis cases in Hebei Province had shown a decreasing trend, it is projected to plateau with no significant decline over the next five years. Furthermore, challenges such as the proportion of silicosis remaining high and shortened dust exposure duration remain severe. It is recommended to focus on key regions like Chengde (ore mining) and Tangshan (ceramics industry). A comprehensive strategy integrating stricter regulation, technological controls, model innovation, and targeted interventions should be implemented to achieve a further substantial reduction in pneumoconiosis incidence.

BACKGROUND:Knee finite element modelling can provide insight into knee mechanics,but its complex image segmentation is more difficult for researchers.With the development of deep learning techniques,deep learning techniques have been widely used in knee joint finite element modelling.OBJECTIVE:To replace the manual segmentation step in finite element modelling of the knee joint by using 3D Swin UNETR in combination with a semi-automatic segmentation technique for statistical shape models.METHODS:Manual(artificial)knee joint finite element model was developed based on MR and semi-automatic knee joint finite element model was developed based on 3D Swin UNETR+statistical shape model segmentation.The same loads and boundary conditions were applied to both models.Validation was performed by calculating the Dice similarity coefficient,mean distance,and comparing the peak equivalent stresses,maximum principal stresses,and maximum shear stresses of the two models.RESULTS AND CONCLUSION:(1)The Dice similarity coefficients of the manual and semi-automatic segmented femur and tibia were more than 98％,and the average distances were less than or equal to(0.35±0.08)mm.(2)With the longitudinal load of 750 N and 10 Nm internal overturning moment applied to the femur tip of both manual and semi-automatic finite element models,the peak equivalent stress,maximum principal stress,and maximum shear stresses of meniscus in manual finite element model were 14.12,18.54,and 7.35 MPa;peak equivalent force,maximum principal stress,and maximum shear stress of femoral cartilage were 2.22,2.15,and 1.18 MPa;peak equivalent force,maximum principal stress,and maximum shear stress of tibial cartilage were 2.50,1.91,and 1.41 MPa;semi-automatic finite element model of meniscus:peak equivalent force,maximum principal stress,and maximum shear stress were 14.93,18.53,and 7.75 MPa.The peak equivalent force,maximum principal stress,and maximum shear stress of femoral cartilage were 2.26,2.18,and 1.20 MPa;the peak equivalent stress,maximum principal stress,and maximum shear stress of tibial cartilage were 2.60,1.91,and 1.46 MPa.The peak equivalent stress,maximum principal stress,and maximum shear stress of manual and semi-automatic finite element models were basically consistent,with no significant difference(P＞0.05).(3)The semi-automatic segmentation technique proposed in this study can replace manual segmentation in creating accurate finite element models of the knee joint.

Objective:To explore the application and clinical significance of pathological diagnostic criteria for medically refractory epilepsy in children.Methods:Cross-sectional study.A retrospective analysis was conducted on 490 children(pathology involved) with medically refractory epilepsy treated continuously in the Pediatric Epilepsy Center of Peking University First Hospital from January 2019 to May 2022.The distribution of different pathological types was observed, and the differences in clinical characteristics among different pathological types were analyzed through Kruskal-Wallis or χ2 tests.The impact of clinical and pathological features on patient prognosis was evaluated through regression analysis. Results:Focal cortical dysplasia (FCD) was the predominant lesion (49.59%, 243/490).The electroencephalograms ( χ2=6.720, P=0.035) and clinical seizure characteristics ( χ2=26.370, P<0.001) in FCDⅡ were more focal than those in FCD Ⅰ and Ⅲ.Moreover, the proportions of focal resection in surgery ( χ2=24.286, P<0.001) and central involvement ( χ2=22.849, P<0.001) in FCDⅡ were higher than those in FCD Ⅰ and Ⅲ.Univariate and multivariate regression analyses revealed that FCD Ⅱ had a better prognosis than other dysplastic patients among the 375 cases of dysplasia ( P=0.049).Next-generation sequencing was performed on 35 cases of cortical malformations with such morphological characteristics as increased numbers of neurons in the white matter and Olig2-positive glial cell hyperplasia, and SLC35A2 mutations were detected in 2 cases (5.71%). Conclusions:Pathology of refractory epilepsy is specialized and continuously evolving.Standardized specimen processing and the accumulation of morphological, immunohistochemical, and molecular genetic data provide the foundation for clarifying the neuropathological nature of epilepsy, improving integrated classification, and advancing prognosis prediction and targeted therapy.

Psoriasis is an incurable chronic inflammatory disease that requires new interventions. Here, we found that fibroblasts exacerbate psoriasis progression by promoting macrophage recruitment via CCL2 secretion by single-cell multi-omics analysis. The natural small molecule celastrol was screened to interfere with the secretion of CCL2 by fibroblasts and improve the psoriasis-like symptoms in both murine and cynomolgus monkey models. Mechanistically, celastrol directly bound to the low-density lipoprotein receptor-related protein 1 (LRP1) β-chain and abolished its binding to the transcription factor c-Jun in the nucleus, which in turn inhibited CCL2 production by skin fibroblasts, blocked fibroblast-macrophage crosstalk, and ameliorated psoriasis progression. Notably, fibroblast-specific LRP1 knockout mice exhibited a significant reduction in psoriasis like inflammation. Taken together, from clinical samples and combined with various mouse models, we revealed the pathogenesis of psoriasis from the perspective of fibroblast-macrophage crosstalk, and provided a foundation for LRP1 as a novel potential target for psoriasis treatment.

BACKGROUND:Knee finite element modelling can provide insight into knee mechanics,but its complex image segmentation is more difficult for researchers.With the development of deep learning techniques,deep learning techniques have been widely used in knee joint finite element modelling.OBJECTIVE:To replace the manual segmentation step in finite element modelling of the knee joint by using 3D Swin UNETR in combination with a semi-automatic segmentation technique for statistical shape models.METHODS:Manual(artificial)knee joint finite element model was developed based on MR and semi-automatic knee joint finite element model was developed based on 3D Swin UNETR+statistical shape model segmentation.The same loads and boundary conditions were applied to both models.Validation was performed by calculating the Dice similarity coefficient,mean distance,and comparing the peak equivalent stresses,maximum principal stresses,and maximum shear stresses of the two models.RESULTS AND CONCLUSION:(1)The Dice similarity coefficients of the manual and semi-automatic segmented femur and tibia were more than 98％,and the average distances were less than or equal to(0.35±0.08)mm.(2)With the longitudinal load of 750 N and 10 Nm internal overturning moment applied to the femur tip of both manual and semi-automatic finite element models,the peak equivalent stress,maximum principal stress,and maximum shear stresses of meniscus in manual finite element model were 14.12,18.54,and 7.35 MPa;peak equivalent force,maximum principal stress,and maximum shear stress of femoral cartilage were 2.22,2.15,and 1.18 MPa;peak equivalent force,maximum principal stress,and maximum shear stress of tibial cartilage were 2.50,1.91,and 1.41 MPa;semi-automatic finite element model of meniscus:peak equivalent force,maximum principal stress,and maximum shear stress were 14.93,18.53,and 7.75 MPa.The peak equivalent force,maximum principal stress,and maximum shear stress of femoral cartilage were 2.26,2.18,and 1.20 MPa;the peak equivalent stress,maximum principal stress,and maximum shear stress of tibial cartilage were 2.60,1.91,and 1.46 MPa.The peak equivalent stress,maximum principal stress,and maximum shear stress of manual and semi-automatic finite element models were basically consistent,with no significant difference(P＞0.05).(3)The semi-automatic segmentation technique proposed in this study can replace manual segmentation in creating accurate finite element models of the knee joint.

Gelsemium elegans (G. elegans) is an extremely poisonous plant that is widely distributed in southern China and southeastern Asia. G. elegans poisoning events occur frequently in southern China, and are therefore an urgent public health problem requiring multidisciplinary action. However, the toxic components and toxicological mechanisms remain unclear. Here, we describe a systematic investigation on the toxic components of G. elegans, resulting in the isolation and identification of 120 alkaloids. Based on acute toxicity screening, the structure-toxicity relationship of Gelsemium alkaloids was proposed for the first time. Moreover, gelsedine- and humantenine-type alkaloids were detected in the clinical blood sample, and were confirmed to be causative in the poisoning. The most toxic compound, gelsenicine (1), had selective inhibitory effects toward ventral respiratory group (VRG) neurons in the medulla, which is the main brain region controlling respiration in the central nervous system. Gelsenicine (1) strongly inhibited the firing of action potentials in VRG neurons through its ability to stimulate GABA_A receptors, the main receptors involved in inhibitory neurotransmission. Application of GABA_A receptor antagonists successively reversed action potential firing in gelsenicine (1)-treated VRG neurons. Importantly, the GABA_A receptor antagonists securinine and flumazenil significantly increased the survival of poisoned animals. Our findings provide insight into the components and mechanisms of G. elegans toxicity, and should assist the development of effective emergency treatments for G. elegans poisoning.

This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations. Observationally, a history of gallstones without cholecystectomy was associated with a high risk of stomach cancer (adjusted odds ratio (aOR)=2.54, 95% confidence interval (CI) 1.50-4.28), liver and bile duct cancer (aOR=2.46, 95% CI 1.17-5.16), kidney cancer (aOR=2.04, 95% CI 1.05-3.94), and bladder cancer (aOR=2.23, 95% CI 1.01-5.13) in the general population, as well as cervical cancer (aOR=1.69, 95% CI 1.12-2.56) in women. Moreover, cholecystectomy was associated with high odds of stomach cancer (aOR=2.41, 95% CI 1.29-4.49), colorectal cancer (aOR=1.83, 95% CI 1.18-2.85), and cancer of liver and bile duct (aOR=2.58, 95% CI 1.11-6.02). MR analysis only supported the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer. This study added evidence to the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer, highlighting the importance of cancer screening in individuals with gallstones.
Humans ; Mendelian Randomization Analysis ; Gallstones/complications* ; Female ; Male ; Cholecystectomy/statistics & numerical data* ; Middle Aged ; Risk Factors ; Aged ; Adult ; Neoplasms/etiology* ; Stomach Neoplasms/epidemiology*

Objective:To explore the application and clinical significance of pathological diagnostic criteria for medically refractory epilepsy in children.Methods:Cross-sectional study.A retrospective analysis was conducted on 490 children(pathology involved) with medically refractory epilepsy treated continuously in the Pediatric Epilepsy Center of Peking University First Hospital from January 2019 to May 2022.The distribution of different pathological types was observed, and the differences in clinical characteristics among different pathological types were analyzed through Kruskal-Wallis or χ2 tests.The impact of clinical and pathological features on patient prognosis was evaluated through regression analysis. Results:Focal cortical dysplasia (FCD) was the predominant lesion (49.59%, 243/490).The electroencephalograms ( χ2=6.720, P=0.035) and clinical seizure characteristics ( χ2=26.370, P<0.001) in FCDⅡ were more focal than those in FCD Ⅰ and Ⅲ.Moreover, the proportions of focal resection in surgery ( χ2=24.286, P<0.001) and central involvement ( χ2=22.849, P<0.001) in FCDⅡ were higher than those in FCD Ⅰ and Ⅲ.Univariate and multivariate regression analyses revealed that FCD Ⅱ had a better prognosis than other dysplastic patients among the 375 cases of dysplasia ( P=0.049).Next-generation sequencing was performed on 35 cases of cortical malformations with such morphological characteristics as increased numbers of neurons in the white matter and Olig2-positive glial cell hyperplasia, and SLC35A2 mutations were detected in 2 cases (5.71%). Conclusions:Pathology of refractory epilepsy is specialized and continuously evolving.Standardized specimen processing and the accumulation of morphological, immunohistochemical, and molecular genetic data provide the foundation for clarifying the neuropathological nature of epilepsy, improving integrated classification, and advancing prognosis prediction and targeted therapy.

Background::Thoracic aortic aneurysm (TAA) is a fatal cardiovascular disease, the pathogenesis of which has not yet been clarified. This study aimed to identify and validate the diagnostic markers of TAA to provide a strong theoretical basis for developing new methods to prevent and treat this disease.Methods::Gene expression profiles of the GSE9106, GSE26155, and GSE155468 datasets were acquired from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the "limma" package in R. Least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), random forest, and binary logistic regression analyses were used to screen the diagnostic marker genes. Single-sample gene set enrichment analysis (ssGSEA) was used to estimate immune cell infiltration in TAA.Results::A total of 16 DEGs were identified. The enrichment and functional correlation analyses showed that DEGs were mainly associated with inflammatory response pathways and collagen-related diseases. Collagen type I alpha 1 chain ( COL1A1) and synaptotagmin like 2 ( SYTL2) were identified as diagnostic marker genes with a high diagnostic value for TAA. The expression of COL1A1 and SYTL2 was considerably higher in TAA vascular wall tissues than in the corresponding normal tissues, and there were significant differences in the infiltration of immune cells between TAA and normal vascular wall tissues. Additionally, COL1A1 and SYTL2 expression were associated with the infiltration of immune cells in the vascular wall tissue. Single-cell analysis showed that COL1A1 in TAA was mainly derived from fibroblasts and SYTL2 mainly from cluster of differentiation (CD)8 + T cells. In addition, single-cell analysis indicated that fibroblasts and CD8 + T cells in TAA were significantly higher than those in normal arterial wall tissue. Conclusions::COL1A1 and SYTL2 may serve as diagnostic marker genes for TAA. The upregulation of SYTL2 and COL1A1 may be involved in the inflammatory infiltration of the vessel wall and poor extracellular matrix remodeling, promoting the progression of TAA.