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.

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.

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.

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.

ObjectiveTo propose an X-Gait motor rehabilitation assessment system based on a perception-cognition decoupling architecture to jointly achieve high-accuracy gait recognition and clinical interpretability for low clinical credibility and opaque decision-making workflows in existing intelligent gait assessment models. MethodsIn the perception layer, YOLOv11-Pose and PoseFormerV2 were integrated for 2D-to-3D human pose reconstruction. A long short-term memory network was adopted for temporal classification of normal, abnormal and pathological gaits. The layer-wise relevance propagation algorithm was used to identify discriminative joints and automatically quantify biomechanical indices including trunk forward inclination angle, stance phase percentage and stride symmetry. In the cognition layer, rehabilitation-oriented prompt engineering and prior knowledge graphs were combined to drive large language models, converting quantitative biomechanical measurements into clinically reasonable structured reports. Eight subjects were enrolled for bedside clinical validation to evaluate classification performance and clinical consistency. ResultsThe overall gait classification accuracy of X-Gait reached 94.1%. The 2D pose detection achieved 100% valid detection rate with an average confidence of 0.819. The mean per-joint position error of 3D pose reconstruction was 105.97 mm. In clinical validation of eight cases, outputs generated by explainable artificial intelligence combined with large language models showed high consistency with manual assessments from experienced rehabilitation physicians. ConclusionThe proposed X-Gait system based on perception-cognition decoupling realizes high-precision gait identification and clinically interpretable outputs.

Background Chronic non-communicable diseases, including hypertension, have become major threats to urban public health. The built environment has been linked to blood pressure. Objective To examine joint exposure patterns of built environment factors in relation to residents' blood pressure status and to identify environmental profiles of neighborhoods that may be favorable or unfavorable to hypertension prevention. Methods (1) A cross-sectional study was conducted among 1910 residents in Longzihu District, Bengbu City. Demographic characteristics, clinical indicators (including blood pressure), and lifestyle behavioral data were collected. Nine built environment indicators were derived within a 500-meter buffer zone surrounding each participant's residential address. (2) Using elevated blood pressure status as a binary outcome (all residents) and grade of elevated blood pressure as an ordinal multi-class outcome (residents with elevated blood pressure), the predictive performance of four binary classification models and nine multi-class classification models was compared, respectively. Feature importance was ranked based on the best-performing model. Multi-variable logistic regression with stepwise adjustment was then used to identify key environmental factors. (3) Using partial dependence plots, a joint exposure analysis was conducted in the target population of residents with elevated blood pressure (high-normal blood pressure and hypertension grades 1–3), with the 25th and 75th percentiles of key environmental factors as the low- and high-level thresholds, respectively. The 95% confidence intervals were estimated using the Bootstrap method. Results (1) Among the study participants, 863 had elevated blood pressure: 349 (40.4%) had high-normal blood pressure, and 398 (46.1%), 93 (10.8%), and 23 (2.7%) had hypertension grades 1, 2, and 3, respectively. (2) Logistic regression showed the best performance in analyzing the association between built environment factors and elevated blood pressure status (n=1910), whereas random forest showed the best performance in analyzing the association between built environment factors and grade of elevated blood pressure (n=863). Road density, bus stop density, and hospital/clinic density were key environmental factors. (3) Pairwise joint exposure patterns were observed among the three key environmental factors: When any two were both below the low-level thresholds (road ≤0.54 km·km⁻², bus stop ≤0.51 points·km⁻², hospital ≤5.99 points·km⁻²), the risk of a higher grade of elevated blood pressure was greater than the overall sample average (relative predicted odds 1.29–1.31, 95% confidence interval lower bound >1); when any two were both above the high-level thresholds (road ≥0.75 km·km⁻², bus stop ≥1.25 points·km⁻², hospital ≥15.00 points·km⁻²), the risk was lower than the overall sample average (relative predicted odds 0.54–0.61, 95% confidence interval upper bound <1); low-high and high-low combinations did not differ significantly from the overall sample average (P > 0.05). Conclusion Joint exposure profiles characterized by road density, bus stop density, and hospital/clinic density are associated with elevated blood pressure among residents: Simultaneously low levels of any two of these environmental indicators are associated with a higher predicted risk of a more severe grade, whereas simultaneously high levels are associated with a lower predicted risk. These findings suggest that coordinated configurations of road networks, public transit accessibility, and medical service facilities may represent important environmental feature of neighborhoods favorable to hypertension prevention and control.

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.

ObjectiveTo explore the therapeutic mechanism of Buchong Tiaojing prescription for rats with diminished ovarian reserve （DOR） from the perspectives of nucleotide-binding oligomerization domain （NOD）-like receptor protein 3 （NLRP3） inflammasome and ferroptosis. MethodsA total of 48 female SD rats were randomly divided into a normal group， a model group， low， medium， and high dose groups of Buchong Tiaojing prescription， and an MCC950 group， with eight rats in each group. Except the normal group， all the other groups were injected subcutaneously on the back of the neck with D-galactose to prepare the DOR rat model. From the 15th day of modeling， the rats in the low， medium， and high dose groups of Buchong Tiaojing prescription were subjected to gavage daily at doses of 14.4， 28.8， 57.6 g·kg^-1， respectively. Rats in the MCC950 group were injected intraperitoneally with MCC950 at a dose of 10 mg·kg^-1， once every other day. The interventions of all the groups lasted for 4 weeks. The estrous cycle of the rats was observed with vaginal exfoliated cell smear. Hematoxylin-eosin （HE） staining was performed to observe the development of follicles and corpus luteum in the ovary. Enzyme-linked immunosorbent assay （ELISA） was performed to detect the levels of serum sex hormones and interleukin-1β （IL-1β）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot assay were performed to detect the mRNA and protein expression of NLRP3 inflammasome， acyl-CoA synthetase long-chain family member 4 （ACSL4）， transferrin receptor 1 （TFR1）， and glutathione peroxidase 4 （GPX4）， and oxidative stress kits were used to detect ovarian superoxide dismutase （SOD） and malondialdehyde （MDA） levels. ResultsDuring the experiment， one rat died in the high dose group of Buchong Tiaojing prescription， and a total of 47 rats were finally included in the index tests and statistics. Compared with those in the normal group， rats in the model group had significantly disturbed estrous cycles， increased number of atretic follicles， and significant disorder of serum sex hormones. The mRNA and protein expression of NLRP3 inflammasome， ACSL4， and TFR1 in ovarian tissue was up-regulated （P<0.01）， while that of GPX4 was significantly down-regulated （P<0.01）. The SOD content in the ovary was decreased significantly， while the MDA level was increased （P<0.01）. After drug intervention， the estrous cycle of rats was basically resumed， and the follicles at all levels were more structurally intact and significantly increased in number. Additionally， the levels of serum sex hormones and IL-1β were significantly improved. The mRNA and protein expression of NLRP3 inflammasome， ACSL4， and TFR1 were down-regulated， while that of GPX4 was significantly up-regulated， and the ovarian oxidative stress was alleviated （P<0.05， P<0.01）， especially in the high dose group of Buchong Tiaojing prescription and the MCC950 group. ConclusionInflammatory injury and ferroptosis occur in the ovaries of DOR rats， and the Buchong Tiaojing prescription is able to inhibit ovarian NLRP3 inflammasome， alleviate the degree of ovarian ferroptosis， and improve ovarian reserve.

Objective To investigate the effects and regulatory mechanisms of carboxyamidotriazole orotate(CTO)on the metabolism and inflammatory mediators of glioma-associated microglia(GAM).Methods Tumor volume was regularly monitored by in vivo imaging,and histological examination was performed to detect the extent of tumor in-filtration;non-targeted metabolomics analysis was used to detect the level of tricarboxylic acid cycle metabolites in cells;seahorse cell energy measurement method was used to detect the oxygen consumption rate(OCR)and extra-cellular acidification rate(ECAR)of cells;immunofluorescence was used to detect the degree of hypoxia in cells;quantitative PCR was used to detect the mRNA level of pro-cancer mediators M1/M2 in cells;Western blot was used to detect the protein level of hypoxia-inducible factor-1α(HIF-1α)and programmed death receptor-ligand 1(PD-L1).Results CTO inhibited the tumor progression in mice,and down-regulated the oxidative phosphorylation level and improved cell hypoxia in vitro(P＜0.01).It also downregulated the expression of pro-oncogenic mediators iNos,Arg-1,Il-10,and Irf4 in GAM(P＜0.01).When combined with lactate dehydrogenase inhibitor stiripentol(STP),CTO-induced enhancement of glycolysis and upregulation of PD-L1 expression in GAM was attenuated(P＜0.01),and the expressions of Arg-1 and Il-10 was further downregulated(P＜0.000 1).Conclusions CTO down-regulates the expression of several oncogenic genes in GAM and inhibits tumor progression in mice.Combined use of lactate dehydrogenase inhibitors can weaken the adverse effect of CTO and reduce the transcriptional level of GAM oncogenic mediators.