Background Work-related musculoskeletal disorders (WMSDs) are a major occupational health concern, particularly among workers exposed to adverse ergonomic conditions. Manganese production involves heavy physical demands, yet research on WMSDs among manganese workers remains limited. Objective To investigate the prevalence and influencing factors of WMSDs among manganese workers in a manganese enterprise in Guangxi. Methods A cross-sectional survey was conducted from May to June 2024 on workers at a manganese factory in Guangxi. The Chinese Musculoskeletal Disorders Questionnaire was used to collect information on demographic characteristics, distribution of musculoskeletal symptoms, and work-related exposures. χ² test was applied to compare differences in positive WMSDs rates across groups, and logistic regression analysis was performed to identify associated factors. Results A total of 1476 workers were enrolled in the study after pre-determined inclusion and exclusion criteria. The overall prevalence of WMSDs was 34.15%. The most commonly affected body regions were the lower back (17.28%), neck (16.67%), and shoulders (13.82%). The results of logistic regression analysis indicated that female, older age, and education level of college or above were associated with a higher risk of WMSDs (P<0.05). Awkward working postures were significantly associated with WMSDs in corresponding body regions; in particular, awkward postures of the neck, upper limbs, trunk, and lower limbs were related to an increased risk of WMSDs in multiple body sites (P<0.05). In addition, poor lighting conditions, high workplace temperature, frequent or sustained arm support during work, and high job demands were associated with an increased risk of overall or site-specific WMSDs (P<0.05). Conclusion The high prevalence of WMSDs among manganese workers is closely associated with demographic characteristics, working postures, and work environment and organizational factors. Targeted ergonomic interventions focusing on high-risk body regions and key ergonomic exposures are warranted to reduce the risk of WMSDs among manganese workers.

Neurological disorders such as post-stroke hemiplegia, spinal cord injury, and Parkinson disease represent a major global health burden. Brain-computer interface (BCI), which creates direct communication pathways between the nervous system and external devices, offers a promising strategy for functional restoration. The long-term efficacy of such BCI fundamentally depends on the performance of biomaterials at the neural interface. Ideal materials must concurrently satisfy biocompatibility, electrical conductivity, enduring chemical stability, and mechanical compatibility with brain tissue. This review systematically outlines the application of conductive polymers, inorganic nanomaterials, natural biomaterials, and composites in BCI, with a focus on how advanced designs, such as bionic and encapsulated electrodes, improve signal fidelity and surgical feasibility through structural innovation. It further summarizes key material-modification techniques and analyzes the complex foreign-body response orchestrated by microglia, astrocytes, and peripheral immune cells. Finally, it provides insights into future research directions and clinical translation of BCI-based neurorehabilitation, while highlighting critical challenges including long-term biosafety and the establishment of standardized evaluation frameworks, aiming to bridge the gap between laboratory innovation and effective clinical deployment.

Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

Depression is a common mental disorder that falls under the category of "stagnation syndrome" in traditional Chinese medicine （TCM）. Its complex pathogenesis poses challenges for the development of novel therapeutic agents. Currently， clinically used antidepressants are often accompanied by significant side effects， and statistics show that about one-third of patients do not respond to these medications. TCM demonstrates advantages in the treatment of depression through multi-target， multi-pathway and multi-mechanistic approaches. Pinelliae Rhizoma， a phlegm-resolving herb， exhibits effects such as drying dampness and resolving phlegm， as well as eliminating stuffiness and reducing masses. The characteristics of harmonizing Yin and Yang and resolving stagnation in the middle energizer align precisely with the pathogenesis of depression syndrome， demonstrating therapeutic efficacy in affected patients. Literature studies have found that the active ingredients of Pinelliae Rhizoma， such as cavidine， baicalein， β-sitosterol， as well as Pinelliae Rhizoma herb pairs， such as Pinelliae Rhizoma-Magnoliae Officinalis Cortex， Pinelliae Rhizoma-husked sorghum， Pinelliae Rhizoma-Prunellae Spica， exhibit significant antidepressant effects. Furthermore， TCM formulas containing Pinelliae Rhizoma as the principal therapeutic agent， such as Banxia Xiexin Tang， Banxia Houpo Tang， and Wendan Tang， as well as formulas incorporating Pinelliae Rhizoma like compound Xiaochaihu Tang， Chaihu Jia Longgu Muli Tang， and Erchen Tang， have also demonstrated favorable antidepressant efficacy. The antidepressant mechanism of these agents may involve modulation of 5-hydroxytryptamine （5-HT） and dopamine （DA） levels， up-regulation of brain-derived neurotrophic factor （BDNF） expression， regulation of the hypothalamus-pituitary-adrenal （HPA） axis， reduction of oxidative stress， modulation of nuclear transcription factor-κB （NF-κB） signaling pathway， and inhibition of microglia-mediated inflammatory responses. This review summarized the antidepressant mechanisms and clinical applications of the active components， herb pairs， and TCM formulas containing Pinelliae Rhizoma， aiming to provide a reference for modern research on the use of Pinelliae Rhizoma in antidepressant therapy.

OBJECTIVE To confirm trigger items for adverse drug reaction （ADR） induced by bevacizumab， to identify and analyze the occurrence of related ADR， and to establish a predictive model for severe adverse reaction （SAR） caused by this drug. METHODS Based on the global trigger tool （GTT） theory， and referencing the GTT White Paper， drug package inserts and relevant literature， trigger items for bevacizumab-related ADR were confirmed using a single-round Delphi method. Utilizing these established items， electronic medical records of relevant patients at Guilin People’s Hospital from January 2020 to September 2024 were actively screened via the China Hospital Pharmacovigilance System. Pharmacists then identified and tallied the occurrence of bevacizumab-induced ADR. Data from patients with any positive trigger item served as the study subjects （divided into training and test sets at a ratio of 7∶3）， candidate feature variables were selected from 39 related variables using the Boruta algorithm， and the multivariable Logistic regression analysis was performed with the occurrence of SAR as the dependent variable. Based on these candidate features， Logistic Regression， Extreme Gradient Boosting， Light Gradient Boosting Machine， Random Forest， and Categorical Boosting models were constructed. Model performance was evaluated using metrics including the area under the curve （AUC） of receiver operating characteristic curve and recall rate. The Shapley Additive exPlanations （SHAP） method was applied to analyze and interpret the contribution of each variable. A nomogram was constructed based on the optimal model. RESULTS A total of 38 trigger items for active monitoring of bevacizumab-related ADR were determined， comprising 17 laboratory indicators， 13 clinical manifestations， and 8 intervention measures. In total， 483 patients with positive trigger items were included， and 318 patients with bevacizumab-induced ADR were identified， including 83 SARs. The positive predictive values for the trigger items and cases were 43.57% （708/1 625） and 63.84% （318/483）， respectively. Bevacizumab-induced ADR involved 7 systems/organs， with the hematological system being the most frequently involved （64.15%）. The Boruta algorithm selected 7 vari ables： serum potassium， hematocrit， albumin-to-globulin ratio， prealbumin， hypertension history， age and red blood cell count. Multivariable Logistic regression showed that elevated serum potassium levels were associated with a decreased risk of bevacizumab-induced SAR （OR＝0.234， P ＝0.002）， while a history of hypertension （OR＝2.642， P ＝0.006） and increased age （OR＝1.040， P ＝0.025） were associated with an increased risk. The Logistic Regression model demonstrated superior performance with higher AUC， F1 score and recall rate （0.761， 0.447， 0.607）， compared to other models. SHAP evaluation results indicated that variables such as serum potassium， hematocrit， and age ranked highest in importance. CONCLUSIONS Totally 38 trigger entries have been successfully identified for active screening of bevacizumab-related ADR. Elevated serum potassium levels are a protective factor against bevacizumab-induced SAR， whereas the hypertension history and increased age are risk factors. The Logistic Regression model is the optimal predictive model.

This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans ; Nasal Cavity/surgery* ; Nasal Surgical Procedures ; China ; Consensus ; Sinusitis/surgery* ; Dermal Fillers

Allergen-specific immunotherapy（AIT） remains the only therapeutic approach with the potential to modify the natural course of allergic rhinitis（AR）. Nevertheless, considerable inter-individual variability exists in patients'responses to AIT. To facilitate more reliable assessment of treatment efficacy, the China Rhinopathy Research Cooperation Group（CRRCG） convened young and middle-aged nasal experts in China to formulate the present consensus. The recommended subjective outcome measures for AIT comprise symptom scores, medication scores, combined symptom and medication scores, quality-of-life assessments, evaluation of disease control, and assessment of comorbidities. Objective indicators may supplement these measures. Currently available objective approaches include skin prick testing, nasal provocation testing, and allergen exposure chambers. However, these methods remain constrained by practical limitations and are not yet appropriate for routine implementation in clinical efficacy evaluation. In addition, several biomarkers, including sIgE and the sIgE/tIgE ratio, sIgG4, serum IgE-blocking activity, IgA, cytokines and chemokines, as well as immune cell surface molecules and their functional activity, have been shown to have associations with AIT outcomes. While these biomarkers may complement subjective assessments, they are subject to significant limitations. Consequently, large-scale multicenter trials and real-world evidence are required to strengthen the evidence base. The present consensus underscores the necessity of integrating patients'subjective experiences with objective testing throughout the treatment process, thereby providing a more comprehensive and accurate framework for efficacy evaluation. Looking forward, future investigations should prioritize the incorporation of multi-omics data and artificial intelligence methodologies, which hold promise for overcoming current limitations in assessment strategies and for advancing both the standardization and personalization of AIT.
Humans ; Allergens/immunology* ; China ; Consensus ; Desensitization, Immunologic ; Immunoglobulin E ; Quality of Life ; Rhinitis, Allergic/therapy* ; Treatment Outcome ; East Asian People

OBJECTIVES: To investigate the associations between Tau protein deposition and brain biochemical metabolites detected by proton magnetic resonance spectroscopy (¹H-MRS) in patients with advanced Alzheimer's disease (AD). METHODS: From April, 2022 to December, 2024, 64 Tau-positive AD patients and 29 healthy individuals underwent ¹⁸F-APN-1607 PET/MR and simultaneously acquired multi-voxel ¹H-MRS in the Department of Nuclear Medicine, Nanjing First Hospital. Visual analysis and voxel-based analysis of PET/MR data were performed to investigate the Tau protein deposition patterns in AD patients. Valid voxels within the ¹H-MRS field of view were selected, and their standardized uptake value ratio (SUVr) in PET and metabolite levels of N-acetylaspartate (NAA), choline (Cho), creatine (Cr), NAA/Cr, and Cho/Cr were recorded. The Tau-positive (Tau⁺) voxels and Tau-negative (Tau^-) voxels of the AD patients were compared for PET and ¹H-MRS parameters, and the correlations between the metabolites and Tau PET SUVr within Tau⁺ voxels were analyzed. RESULTS: Significant Tau protein deposition were observed in the AD patients, involving mainly the bilateral frontal lobes (30.07%), parietal lobes (29.96%), temporal lobes (21.07%), and occipital lobes (15.89%). A total of 1422 valid voxels in AD group (including 994 Tau⁺ and 428 Tau^- voxels) and 814 voxels in the control group were selected. The AD patients showed significantly decreased NAA level and increased SUVr compared with the control group (P<0.05). Subgroup analyses revealed that Tau⁺ voxels had higher SUVr and lower Cr and Cho/Cr than Tau^- voxels (P<0.05). Compared with the control group, Tau⁺ voxels exhibited higher SUVr and lower Cr (P<0.05), while Tau^- voxels showed lower NAA (P=0.004). No significant differences were found in Cho or NAA/Cr among the subgroups (P>0.05). Within Tau⁺ voxels, NAA, Cho, and Cr were negatively correlated with SUVr (P<0.001). CONCLUSIONS The patients with progressive AD have significant Tau protein deposition in the brain, which is correlated with alterations in metabolite levels. Decreased NAA is more prominent in early or pre-tau deposition stages, while Cr changes is more significant in the regions with Tau protein deposition, suggesting the potential of NAA and Cr as biomarkers for Tau protein deposition in AD for disease monitoring and treatment evaluation.
Humans ; Alzheimer Disease/diagnostic imaging* ; Aspartic Acid/metabolism* ; tau Proteins/metabolism* ; Creatine/metabolism* ; Brain/metabolism* ; Biomarkers/metabolism* ; Positron-Emission Tomography ; Male ; Female ; Proton Magnetic Resonance Spectroscopy ; Choline/metabolism* ; Aged ; Middle Aged

Objective To analyze the influencing factors of postoperative hypoxemia after whole lung lavage (WLL) in patients with pneumoconiosis and to evaluate the predictive value of lung ultrasound scores. Methods A total of 757 patients with pneumoconiosis who underwent unilateral large-volume WLL were selected as the research subjects by continuous sampling method. The patients with hypoxemia after large-volume WLL were assigned to the observation group (82 cases), and those without hypoxemia were assigned to the control group (675 cases). Patients′ basic information and clinical data of the two groups were collected using a retrospective investigation method. The binary logistic regression analysis was used to analyze the influencing factors of hypoxemia after large-volume WLL in patients with pneumoconiosis, and receiver operating characteristic (ROC) curve analysis was conducted to assess the predictive value of ultrasound indicators. Results The combined rate of postoperative hypoxemia in the patients was 10.8% (82/757). The multivariate logistic regression analysis showed that the risk of hypoxemia in patients aged ≥65 years was higher than that in patients aged <65 years (P<0.05). The risk of hypoxemia was higher in patients with increased pre-extubation lung ultrasound score than those with lower pre-extubation lung ultrasound score (P<0.01). Patients with a higher partial pressure of carbon dioxide in arterial blood (PaCO₂) had a higher risk of concurrent hypoxemia than those with a lower pressure (P<0.01), while patients with lower arterial partial pressure of oxygen (PaO₂) had a higher risk of concurrent hypoxemia than those with higher PaO₂ (P<0.01). Pearson correlation analysis showed that lung ultrasound scores were negatively correlated with PaO₂ and positively correlated with PaCO₂ (both P<0.01). The ROC curve analysis showed that the area under the curve was 0.855, the 95% confidence interval was 0.828 to 0.879, the diagnostic sensitivity was 84.2%, and the specificity was 75.1%. Conclusion Age, pre-extubation lung ultrasound score, and PaCO₂ are risk factors for hypoxemia after WLL in patients with pneumoconiosis, while PaO₂ is a protective factor. Pre-extubation lung ultrasound scoring demonstrates good accuracy in predicting postoperative hypoxemia among pneumoconiosis patients after WLL.

Depression is a high-incidence mental disorder with complex causes and multifaceted pathogenic mechanisms. Its pathogenesis has not yet been fully elucidated， which has hindered the development of novel and highly effective antidepressant drugs. This condition severely affects human physical and mental health while imposing a significant socio-economic burden. At present， several hypotheses exist regarding the pathogenesis of depression， including monoamine neurotransmitter imbalances， neurotrophic factor deficiencies， neural plasticity impairments， glutamate dysregulation， neuroinflammatory disorders， gut microbiota imbalances， and mitochondrial autophagy dysfunction. Currently， most clinical antidepressants are monoamine neurotransmitter reuptake inhibitors. Although they exhibit certain therapeutic effects， they are associated with significant drawbacks， such as severe adverse reactions and poor patient compliance. In contrast， traditional Chinese medicine （TCM）， characterized by its multi-targeted effects， mild efficacy， and minimal side effects， has demonstrated significant advantages in the treatment of depression. Chinese medicine Polygalae Radix possesses the functions of calming the mind， enhancing cognitive functions， harmonizing the heart and kidneys， and dispelling phlegm to open orifices. It is often included in compound prescriptions for the clinical treatment of depression. Based on current hypotheses regarding the pathogenesis of depression， this paper systematically reviews research progress on the antidepressant mechanisms of Polygalae Radix from multiple perspectives， including its active components， its use in herbal pairings， and its inclusion in TCM compound prescriptions. This review aims to provide a scientific basis for the clinical application of Polygalae Radix in antidepressant therapy and to serve as a reference for the modernization of its antidepressant research.