Background As common public facilities essential to daily life, hair and beauty salons frequently contain various airborne toxic and hazardous pollutants potentially leading to adverse health effects for salon practitioners. Objective To characterize the indoor air pollution profiles of common contaminants in hair and beauty salons in Shanghai and to evaluate the associated health risks for practitioners, in order to provide a scientific basis for strengthening the public health management in Shanghai and protecting the health of practitioners. Methods The air quality monitoring data of hair and beauty salons in Shanghai from 2016 to 2024 were obtained from the “Health Hazard Factors Monitoring Program for Public Places” of the National Institute of Environmental Health, Chinese Center for Disease Control and Prevention. Monitoring indicators included particulate matter ≤10 μm in aerodynamic diameter (PM₁₀), particulate matter ≤2.5 μm in aerodynamic diameter (PM_2.5), formaldehyde, ammonia, benzene, toluene, and xylene. Indicator compliance rates were calculated across various years in accordance with GB 9666-1996 Hygienic standard for barber shop and beauty shop and GB 37488-2019 Hygiene indicators and limit for public places; specifically, PM_2.5 was assessed against the limits stipulated in GB/T 18883-2022 Standards for indoor air quality. A questionnaire survey was conducted among salon practitioners to collect weekly working days and daily working hours. The non-carcinogenic risks associated with inhalation exposure to formaldehyde, ammonia, benzene, toluene, and xylene as well as the carcinogenic risks posed by formaldehyde and benzene were evaluated following WS/T 777-2021 Technical guide for environmental health risk assessment of chemical exposure and the U.S. Environmental Protection Agency inhalation risk model. Results The overall compliance rates of PM₁₀, formaldehyde, ammonia, benzene, and toluene in the air of hair and beauty salons in Shanghai from 2016 to 2024 were 92.13%, 96.59%, 96.15%, 94.93%, and 94.97%, respectively; the overall compliance rate of xylene was a little lower (85.92%), and the overall compliance rate of PM_2.5 was 57.18%. The P₅₀ concentrations of PM₁₀, PM_2.5, formaldehyde, ammonia, benzene, toluene, and xylene did not exceed the corresponding limits. The P₅₀ of non-carcinogenic risk indicator (hazard quotient, HQ) for formaldehyde, ammonia, benzene, toluene, and xylene were <1. The probabilities of non-carcinogenic risk HQ >1 for formaldehyde and xylene were 41.4% and 10.9%, respectively, which were higher than that of other pollutants. The P₅₀ of carcinogenic risk (CR) for formaldehyde and benzene were between 1.0×10⁻⁶ and 1.0×10⁻⁴, while the probabilities of CR >1.0×10⁻⁴ were 16.9% and 14.0%, respectively. Conclusion The overall compliance rate of common pollutant concentrations in the air of hair and beauty salons in Shanghai is high, and the hygienic condition meets the requirements of national standards. The non-carcinogenic health risks posed by formaldehyde and xylene to employees (with formaldehyde being more prominent), as well as the carcinogenic risks associated with formaldehyde and benzene, deserve heightened attention in future health supervision.

BACKGROUND:Rheumatoid arthritis is widely prevalent worldwide,with its high incidence and universality that considerably affects patients' quality of life.Previous studies have focused on a few immune cells or cytokines,whereas this study comprehensively provides a more complete view of the immune mechanisms in rheumatoid arthritis.OBJECTIVE:To explore the causal relationship between 731 immune cell phenotypes and rheumatoid arthritis using the Mendelian randomization method,thereby providing evidence of causality.METHODS:The 731 immune cell phenotypes used in this study were sourced from the GWAScatalog database,jointly developed by the National Human Genome Research Institute(NHGRI)and the European Bioinformatics Institute(EBI).The rheumatoid arthritis data were from the Finngen database,developed by the Finnish Institute for Molecular Medicine(FIMM).The inverse variance weighting method was employed as the primary analytical approach.Additionally,multiple analytical methods,including MR-Egger,weighted mode,simple mode,and weighted median,were concurrently utilized to complement the final results.Sensitivity analyses(Cochran's Q test,MR-Egger regression,and MR-presso analysis)were also conducted to verify the stability and feasibility of the data.RESULTS AND CONCLUSION:(1)After excluding results through heterogeneity testing,the inverse variance weighting analysis indicated that 10 absolute cell counts,15 median fluorescence intensities of surface antigen levels,1 morphological characteristic,and 9 relative cell counts had a causal relationship with the occurrence of rheumatoid arthritis.(2)According to cell classification,this study found that seven types of B cells,seven types of classical dendritic cells,six types of mature T cells,four types of monocytes,three types of myeloid cells,three types of TBNK cells(lymphocyte subset T cells,B cells and natural killer cells),and five types of Tregs had a causal association with the occurrence of rheumatoid arthritis.(3)Through comprehensive bidirectional two-sample MR analysis,we demonstrated the complex causal relationships between multiple immune phenotypes and rheumatoid arthritis,highlighting the intricate interaction patterns between the immune system and rheumatoid arthritis.These results provide new biomarkers for the early screening and diagnosis of rheumatoid arthritis in China,and help to improve the diagnostic accuracy and sensitivity.

BACKGROUND:Rheumatoid arthritis is widely prevalent worldwide,with its high incidence and universality that considerably affects patients' quality of life.Previous studies have focused on a few immune cells or cytokines,whereas this study comprehensively provides a more complete view of the immune mechanisms in rheumatoid arthritis.OBJECTIVE:To explore the causal relationship between 731 immune cell phenotypes and rheumatoid arthritis using the Mendelian randomization method,thereby providing evidence of causality.METHODS:The 731 immune cell phenotypes used in this study were sourced from the GWAScatalog database,jointly developed by the National Human Genome Research Institute(NHGRI)and the European Bioinformatics Institute(EBI).The rheumatoid arthritis data were from the Finngen database,developed by the Finnish Institute for Molecular Medicine(FIMM).The inverse variance weighting method was employed as the primary analytical approach.Additionally,multiple analytical methods,including MR-Egger,weighted mode,simple mode,and weighted median,were concurrently utilized to complement the final results.Sensitivity analyses(Cochran's Q test,MR-Egger regression,and MR-presso analysis)were also conducted to verify the stability and feasibility of the data.RESULTS AND CONCLUSION:(1)After excluding results through heterogeneity testing,the inverse variance weighting analysis indicated that 10 absolute cell counts,15 median fluorescence intensities of surface antigen levels,1 morphological characteristic,and 9 relative cell counts had a causal relationship with the occurrence of rheumatoid arthritis.(2)According to cell classification,this study found that seven types of B cells,seven types of classical dendritic cells,six types of mature T cells,four types of monocytes,three types of myeloid cells,three types of TBNK cells(lymphocyte subset T cells,B cells and natural killer cells),and five types of Tregs had a causal association with the occurrence of rheumatoid arthritis.(3)Through comprehensive bidirectional two-sample MR analysis,we demonstrated the complex causal relationships between multiple immune phenotypes and rheumatoid arthritis,highlighting the intricate interaction patterns between the immune system and rheumatoid arthritis.These results provide new biomarkers for the early screening and diagnosis of rheumatoid arthritis in China,and help to improve the diagnostic accuracy and sensitivity.

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Objective:This multicenter retrospective study aimed to analyze the clinicopathological features of duodenal adenocarcinoma (DA) and identify prognostic factors for postoperative survival.Methods:Demographic characteristics, clinicopathological features, treatment outcomes and survival of DA patients undergoing surgical treatment at 18 Chinese medical centers from January 2012 to December 2023 were retrospectively analyzed.Results:Among the 2 056 DA patients included, 46.8% (963) had extra-ampullary DA (EA-DA), and 53.2% (1 093) had peri-ampullary DA (PA-DA). The 1-, 3-, and 5-year overall survival (OS) rates for patients who underwent radical surgery were 93.2%, 71.0%, and 57.2%, respectively. The median overall survival was 76 months, and the median progression-free survival (PFS) was 65 months. No differences in survival were observed between the laparotomy group and minimally invasive surgery (MIS) group either before or after propensity score matching (OS: 76 vs. 75 months before PSM, P=0.986; OS: 75 vs. 75 months after PSM, P=0.602). Furthermore, there were no significant differences between-group in operation time and postoperative complications ( P＞0.05). The MIS group experienced less intraoperative blood loss and shorter hospital stays. The multivariate Cox regression analysis revealed that advanced age ( HR=1.43,95% CI:1.18-1.73), elevated carbohydrate antigen 19-9 levels ( HR=1.24,95% CI:1.02-1.51), perineural invasion ( HR=1.44,95% CI:1.14-1.81), vascular invasion ( HR=1.35,95% CI:1.07-1.71), advanced T stage (T3-4 vs. T1-2: HR=1.86,95% CI:1.49-2.31), regional lymph node metastasis ( HR=1.93,95% CI:1.58-2.36), preoperative biliary drainage ( HR=1.26,95% CI:1.04-1.53), intraoperative blood loss ( HR=1.34,95% CI:1.11-1.62), clinically significant postoperative pancreatic fistulas ( HR=1.53,95% CI:1.12-2.09), and postoperative hemorrhage ( HR=1.62,95% CI:1.14-2.29) were independent risk factors for poor prognosis after surgery (all P＜0.05). Conclusions:Radical surgery is associated with favorable overall survival among DA patients, and no difference in survival is observed between EA-DA and PA-DA patients. MIS is a reliable alternative for DA treatment.

Objective:To predict mechanical complications (MC) following spinal deformity surgery for adult spine deformity (ASD) using machine learning models, identify key risk factors, and develop a visualizable tool for individualized risk assessment.Methods:Clinical and radiological data from 525 patients with ASD who underwent surgery in our hospital between January 2017 and December 2021 were collected. Patients were randomly assigned to a training set (70%) and a test set (30%) for model development. The cohort included 88 males and 437 females, with a mean age of 42.2±18.1 years. Variables included demographic data, comorbidities, local and systemic radiological parameters, paraspinal muscle fat infiltration (FI), and vertebral bone quality (VBQ) scores. Multiple machine learning algorithms: Random Forest (RF), Gaussian Naive Bayes (GNB), Light GBM, Support Vector Machine (SVM), XGBoost (XGB), and Logistic Regression (LR) were trained and evaluated. Model performance was compared using the receiver operating characteristic curve (ROC) and precision-recall curve (PRC). SHAP (Shapley Additive Explanations) was used to rank risk factors, while LIME (Local Interpretable Model-Agnostic Explanations) was applied to visualize MC risk in individual cases.Results:Of the 525 patients, 135 (25.7%) developed postoperative MC. Among these, 80 (59.3%) experienced proximal junction kyphosis or failure (PJK/PJF), 7 (5.2%) had distal junction kyphosis or failure (DJK/DJF), 28 (20.7%) sustained rod fractures, and 29 (21.5%) showed significant loss of correction. In the validation cohort, the RF model achieved the highest area under the curve (AUC=0.80), followed by GNB (0.77), XGB (0.76), LR (0.74), LightGBM (0.73), and SVM (0.66). The RF model also demonstrated the best PRC value (0.58), highest sensitivity (0.65), and lowest Brier score (0.20). GNB, Light GBM, and LR models achieved the highest accuracy (0.78 each), while LightGBM exhibited the highest specificity (0.93). SHAP analysis identified higher preoperative VBQ scores, larger T 1 pelvic angle (TPA), and higher paraspinal muscle FI as the main risk factors for MC. Based on the RF model, a LIME-based tool was successfully constructed for individualized MC risk estimation. Conclusion:The RF model demonstrated the best overall predictive performance for MC. A machine learning-based prediction model has the potential to provide valuable guidance for surgical decision-making in ASD patients.

Drug addiction is a chronic disease that causes serious physical and psychological harm to the individual,as well as damage to society.Biomarkers are indicators that differ significantly between healthy people and patients and are important for the diagnosis and treatment of diseases.The increasing incidence of drug addiction in recent years and the wider variety and number of new drugs has led to an increase in the study of biomarkers of drug addiction and their analysis in different biological samples.This paper reviews biomarkers of drug addiction in hair,blood,urine,and feces,to help to explore the biological signatures of drug addiction and facilitate its clinical diagnosis and treatment.

Objective:This multicenter retrospective study aimed to analyze the clinicopathological features of duodenal adenocarcinoma (DA) and identify prognostic factors for postoperative survival.Methods:Demographic characteristics, clinicopathological features, treatment outcomes and survival of DA patients undergoing surgical treatment at 18 Chinese medical centers from January 2012 to December 2023 were retrospectively analyzed.Results:Among the 2 056 DA patients included, 46.8% (963) had extra-ampullary DA (EA-DA), and 53.2% (1 093) had peri-ampullary DA (PA-DA). The 1-, 3-, and 5-year overall survival (OS) rates for patients who underwent radical surgery were 93.2%, 71.0%, and 57.2%, respectively. The median overall survival was 76 months, and the median progression-free survival (PFS) was 65 months. No differences in survival were observed between the laparotomy group and minimally invasive surgery (MIS) group either before or after propensity score matching (OS: 76 vs. 75 months before PSM, P=0.986; OS: 75 vs. 75 months after PSM, P=0.602). Furthermore, there were no significant differences between-group in operation time and postoperative complications ( P＞0.05). The MIS group experienced less intraoperative blood loss and shorter hospital stays. The multivariate Cox regression analysis revealed that advanced age ( HR=1.43,95% CI:1.18-1.73), elevated carbohydrate antigen 19-9 levels ( HR=1.24,95% CI:1.02-1.51), perineural invasion ( HR=1.44,95% CI:1.14-1.81), vascular invasion ( HR=1.35,95% CI:1.07-1.71), advanced T stage (T3-4 vs. T1-2: HR=1.86,95% CI:1.49-2.31), regional lymph node metastasis ( HR=1.93,95% CI:1.58-2.36), preoperative biliary drainage ( HR=1.26,95% CI:1.04-1.53), intraoperative blood loss ( HR=1.34,95% CI:1.11-1.62), clinically significant postoperative pancreatic fistulas ( HR=1.53,95% CI:1.12-2.09), and postoperative hemorrhage ( HR=1.62,95% CI:1.14-2.29) were independent risk factors for poor prognosis after surgery (all P＜0.05). Conclusions:Radical surgery is associated with favorable overall survival among DA patients, and no difference in survival is observed between EA-DA and PA-DA patients. MIS is a reliable alternative for DA treatment.

Pancreatic cancer is a severe malignant tumor that poses a significant threat to human health worldwide, with its incidence and mortality rates increasing annually, especially in economically developed regions. The progress of surgical treatment is of great significance in improving the prognosis of pancreatic cancer patients. This article reviews the recent progress in surgical treatment strategies for pancreatic cancer, with a particular emphasis on the multidisciplinary team (MDT) approach, neoadjuvant therapy, conversion therapy, and the assessment of the effectiveness of neoadjuvant/conversion therapy. The MDT approach, by integrating the strengths of multiple disciplines, provides personalized treatment plans for patients, improving the resection rate and survival rate of patients with pancreatic cancer. Neoadjuvant and conversion therapy provide surgical opportunities for patients with advanced pancreatic cancer, improving their prognosis. Additionally, accurate assessment of treatment effects is crucial for determining the timing and method of surgery.

Objective:To construct a patient-derived organoid model and clarify its predictive value for the sensitivity of pancreatic cancer chemotherapy drugs.Methods:A total of 42 tissue samples from patients with pancreatic ductal adenocarcinoma who underwent surgery or percutaneous biopsy at Peking University First Hospital from 2020 to 2023 were collected. Pancreatic cancer organoid models were constructed through in vitro culture. These organoid models were treated with five most commonly used pancreatic cancer chemotherapy drugs, namely Gemcitabine, nab-Paclitaxel, 5-Fluorouracil, Oxaliplatin, and Irinotecan, to determine the IC 50. The consistency between the organoid drug sensitivity test results and the patients' chemotherapy sensitivity was determined. Results:Patient-derived pancreatic cancer organoid models achieved an establishment success rate of 73.33%. The organoid model could reproduce the pathological features of the patients' tumor tissues; there were individual differences in the sensitivity to the same chemotherapy drug among organoid models derived from different patients. The sensitivity of patient derived organoids was highly consistent with the actual treatment effect of the corresponding patients was 81%.Conclusion:The drug susceptibility test results were significantly correlated with the actual medication response of patients, suggesting that the drug susceptibility test technology based on patient derived organoids has the potential to guide individualized chemotherapy for pancreatic cancer.