Stroke is the leading cause of death and disability among adults in China， and its common complications include digestive system abnormalities， cognitive impairment， depression， stroke-associated pneumonia， and hemiplegia. The combination of traditional Chinese and Western medicine has great potential in treating post-stroke complications. Xinglou Chengqitang （XLCQT） is a representative prescription of alleviating the disease in the upper part by treating the lower part. It has definite therapeutic effect and high safety. Clinically， XLCQT is often used to treat stroke and its complications. However， the quantity and quality of clinical trials of XLCQT in treating post-stroke complications need to be improved. Additionally， since the basic research is weak， the material basis and multi-target mechanism for the efficacy of this prescription are unknown. This article reviews XLCQT in terms of the pharmacodynamic basis， medicinal properties， safety evaluation， and progress in clinical research and mechanisms in treating post-stroke complications. This article summarizes 22 key active ingredients of XLCQT in treating acute stroke complicated with syndrome of phlegm heat and fu-organ excess. Among these key active ingredients， resveratrol， kaempferol， luteolin， chrysoeriol， apigenin， （+）-catechin， and adenosine have good pharmacokinetic properties and high bioavailability. The mechanisms of XLCQT in treating post-stroke complications are complex， including inflammatory response， brain-gut axis， hypothalamic-pituitary-adrenal （HPA） axis， intestinal flora， neurotrophic factors， autophagy， oxidative stress， and free radical damage. This review helps to deeply understand the pharmacodynamic basis and mechanisms of XLCQT in treating post-stroke complications and provides a theoretical basis for the clinical application of XLCQT against post-stroke complications and the development of drugs.

ObjectiveTo explore the visual attention distribution across different lateral facial profiles and analyze the influence of observer gender and professional background on aesthetic evaluation， providing an aesthetic basis for the design of clinical orthodontic treatment. MethodsEye-tracking technology was employed to record the gaze paths of 136 subjects （orthodontists， non-orthodontic dentists， and non-medical professionals） when evaluating three types of male and female lateral profiles （convex， straight， and concave）. A questionnaire survey was conducted using a visual analog scale （VAS）. Data differences and the consistency between eye-tracking and questionnaire results were analyzed through t-tests， analysis of variance （ANOVA）， and Kappa coefficient analysis. ResultsThe questionnaire scores for straight profiles were significantly higher than those for convex and concave profiles （P<0.05）. Eye-tracking revealed that subjects primarily focused on the eye and nasal regions （P<0.001）， followed by the mouth. However， orthodontists showed no significant difference in attention between the mouth and eye-nasal areas （P>0.05）. Additionally， gender differences were notable. Female observers prioritized the mouth （P<0.05）， while male observers paid later attention to the oral-buccal region. The forehead and chin rapidly attracted attention during the initial evaluation phase， particularly in female concave profiles （P<0.05）. Eye-tracking data demonstrated high consistency with questionnaire results （κ=0.868）. ConclusionThis study， utilizing eye-tracking technology， finds that the eye and nasal regions are the core focus areas for aesthetic evaluation of lateral profiles. Gender differences result in distinct gaze preferences （males emphasize the nose， while females emphasize the eyes）， whereas orthodontists focus more on the lips and forehead. As aesthetic baselines， the forehead and chin， with their profile characteristics， should be prioritized in treatment. This research provides a basis for developing personalized orthodontic plans and establishing aesthetic consensus between clinicians and patients.

ObjectiveTo investigate the effects of atorvastatin （ATV） on the proliferation and differentiation of rat bone marrow mesenchymal stem cells （BMSCs）， periodontal ligament stem cells （PDLSCs）， and dental pulp stem cells （DPSCs） in vitro， and to validate the regulatory effect of ATV on periodontal bone formation and tooth movement using a rat orthodontic tooth movement （OTM） model. MethodsThe effects of ATV on the proliferation and osteogenic/odontogenic differentiation of rat BMSCs， PDLSCs， and DPSCs were assessed in vitro. CCK-8 assay was used to detect the proliferation of the three types of cells. Alkaline phosphatase （ALP） staining and Alizarin Red staining were employed to evaluate osteogenic differentiation capacity. Western blot was used to detect the expression of osteogenesis-related proteins ［collagen type I （COL-I）， Runt-related transcription factor 2 （Runx2）， bone morphogenetic protein-2 （BMP-2）， osteocalcin （OCN）］ and the odontogenesis-related protein dentin sialophosphoprotein （DSPP） in BMSCs， PDLSCs and DPSCs. An OTM rat model was established， with rats randomly assigned to an ATV gavage group and a control group. The ATV gavage group received daily oral administration of ATV at a dose of 20 mg/kg， while the control group received an equal volume of solvent by gavage. Tooth movement distance was measured via Micro-CT on days 7， 14， and 21. Histomorphology of periodontal tissues was observed using Hematoxylin and Eosin （HE） staining and Masson staining. The gene and protein expression levels of osteogenic markers （BMP-2， Runx2， OCN） on the tension side of the first molar were detected by qRT-PCR and immunohistochemistry， respectively. ResultsATV at concentrations of 1×10⁻⁶ mol/L and 1×10⁻⁷ mol/L significantly promoted the proliferation and osteogenic/odontogenic differentiation of BMSCs， PDLSCs， and DPSCs， manifested as enhanced ALP activity， increased mineralized nodule formation， and up-regulated expression of osteogenic/odontogenic proteins COL-I， Runx2， BMP-2， OCN， and DSPP （P<0.001）. In the OTM model， compared with the control group， the ATV gavage group showed a significant reduction in tooth movement distance （P<0.05）， enhanced osteogenic activity in periodontal tissues， and significantly increased gene （P<0.001） and protein （P<0.05） expression of BMP-2， Runx2， and OCN on the tension side of the first molar. ConclusionATV enhances periodontal osteogenesis by promoting osteogenic/dentinogenic differentiation， thus inhibiting tooth movement.

Background Long working hours, as a common risk factor for occupational stress, is closely related to the occurrence of depressive symptoms. Understanding how long working hours affect occupational stress and depressive symptoms will inform occupational health interventions. Objective To quantify the impact of long working hours exposure on occupational stress and depressive symptoms among Internet industry employees, translate black-box outputs into actionable insights, and demonstrate the value of interpretable machine learning for early-warning occupational-health surveillance. Methods A dataset was derived from a cross-sectional survey involving 2866 internet industry employees in China. This survey was part of the project Risk Assessment Of Long Working Hour Exposure And Its Adverse Health Effects, conducted by the National Institute for Occupational Health and Poisoning Control, Chinese Center for Disease Control and Prevention, from 2021 to 2023. Working hours, occupational stress and depressive symptoms were quantified with a set of structured questionnaires including the Core Occupational Stress Scale and the Patient Health Questionnaire. Pairwise associations were screened by Mantel tests and variance-inflation factors. Key predictors identified through feature selection were fed into six machine-learning risk-prediction models. Visual interpretation was provided by feature importance, Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME), while directed causal effects and intervention impacts of prolonged working hours exposure on occupational stress and depressive symptoms were dissected with causal explanation of features techniques. Results The positive rates of occupational stress and depressive symptoms among internet employees were 12.9% and 77.8% respectively. Twelve core features for occupational stress and nine for depressive symptoms were retained after selection. After these features were supplied to six predictive algorithms and evaluated on five metrics, the Light Gradient Boosting Machine (LGBM) achieved the highest accuracy—0.89 for occupational stress and 0.79 for depressive symptoms on the hold-out test set. The feature-importance rankings converged on fatigue accumulation and life satisfaction as dominant drivers for both outcomes, whereas weekly working hours and daily overtime emerged as the principal exposure-related predictors. The SHAP summary plots revealed that longer weekly hours and daily overtime systematically elevated the probability of occupational stress. The causal feature explanation further quantified that ascending one category in weekly working hours increased the probability of occupational stress by 7.04%. Conclusion Exposure to long working hours is associated with both occupational stress and depressive symptoms among internet industry employees. Interpretable machine-learning frameworks translate these associations into transparent, defensible drivers, enabling precise identification of the pivotal factors and their interplay. This evidence base equips occupational-health practitioners with actionable insights for designing targeted prevention and intervention strategies.

Background Occupational stress has emerged as a critical public health concern affecting the physical and mental well-being of workers in the manufacturing sector. However, researchers typically evaluate its core driver—cumulative fatigue—using a crude binary “present/absent” variable, thereby overlooking the high-dimensional complexity and heterogeneity inherent in fatigue characteristics. This oversimplification constrains both the precision and predictive performance of occupational stress risk assessment model. Objective Leveraging a data-driven approach, to survey data on cumulative fatigue among manufacturing employees, and then use this new classification to develop and validate an occupational stress prediction model, with an ultimate aim of enhancing the accuracy and effectiveness of occupational stress assessment. Methods A set of cross-sectional survey data on 3871 manufacturing employees in 2021 were derived from the “Long working hours exposure and its adverse health effect risk assessment” program of the National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention. Occupational stress was assessed using the Core Occupational Stress Measurement Scale, while cumulative fatigue was evaluated via the Worker’s Self-Diagnostic Questionnaire for Fatigue Accumulation. Boruta method was applied to screen core variables from 20 occupational stress influencing factors. Dimensionality reduction of cumulative fatigue features was performed using a Bayesian sparse autoencoder (BASE), followed by comparison and application of clustering methods to achieve multi-class classification of the reduced features. Six machine learning classification models were then selected including logistic regression, support vector machine, decision tree, random forest, adaptive boosting, and lightweight gradient boosting machine (LightGBM) to construct and compare two occupational stress prediction models involving cumulative fatigue combined with ten other core variables: one utilizing the original binary cumulative fatigue label as a core variable, and another employing the novel fatigue classification proposed herein as a core variable. Results The positive rate of occupational stress among the manufacturing employees was 38.9%. The Boruta method identified 11 core variables of occupational stress: depressive symptoms, cumulative fatigue, age, length of service, tenure in current position, average weekly working hours, average daily overtime hours, average monthly income, low levels of exercise, life satisfaction, and sleep quality. The BSAE reduced the original cumulative fatigue factors to 12 dimensions, while the K-means clustering grouped the reduced fatigue features into three categories: no fatigue, moderate fatigue, and sever fatigue. Six occupational stress prediction models were constructed using the three-category labels of cumulative fatigue and ten additional factors. The results indicated that the LightGBM model performed best, achieving an area under the curve (AUC) of 0.78, an accuracy of 0.77, and an F1 score of 0.72. Compared with the model incorporating the traditional binary labels for cumulative fatigue, the best prediction AUC (0.72), accuracy (0.66), and F1 score (0.65) improved by 6%, 11%, and 7%, respectively. Conclusion Cumulative fatigue is a significant predictor of occupational stress among manufacturing employees. Applying data dimensionality reduction combined with three-class cluster analysis to characterize cumulative fatigue improves the performance of occupational stress prediction models. From a data-driven perspective, machine learning methods demonstrate strengths in processing complex datasets, capturing nonlinear relationships, and generating predictions based on key variables. This study therefore confirms that refined processing of core factors substantially enhances the predictive capability of machine learning models in assessing occupational stress risk in the manufacturing workforce.

Objective·To investigate the effect of Th17 cell-specific Stat3 knockout on anxiety-and depressive-like behaviors.Methods·Mice with specific Stat3 knockout in Th17 cells(Stat3fl/fl;Il17a-CreERT2),named Stat3△Il17a,and wild-type mice(Stat3fl/fl,WT)were generated through the Cre/LoxP system,and Stat3 knockout was induced by intraperitoneal injection of tamoxifen.CD4+T cells were isolated using magnetic-activated cell sorting and induced to differentiate into Th17 cells.Reverse transcription polymerase chain reaction and Western blotting were used to verify Stat3 knockout efficiency.Mice were assigned into 4 groups:WT-C group,Stat3△Il17a-C group,WT-P group,and Stat3△Il17a-P group.The periodontitis model was established in the WT-P group and the Stat3△Il17a-P group by injection of Porphyromonas gingivalis-lipopolysaccharide(P.gingivalis-LPS)into the gingival sulcus.Behavioral tests,including the open field test,elevated zero maze,and forced swimming test,were conducted to evaluate changes in anxiety-and depressive-like behaviors.Micro-computed tomography was used to observe destruction of alveolar bone.Neuronal injury was observed by H-E staining,and the level of brain-derived neurotrophic factor(BDNF)was detected by enzyme-linked immunosorbent assay.Results·mRNA expression and protein levels of Stat3 in Stat3△Il17a mice were inhibited compared to WT mice(P<0.05).Experimental periodontitis model was successfully established in the WT-P group and the Stat3△Il17a-P group.The degree of alveolar bone destruction was reduced in the Stat3△Il17a-P group compared to the WT-P group.In the WT-P group,decreased residence time in the central area and in the open area was observed in the open field test and elevated zero maze respectively,and increased immortal time was recorded in the forced swimming test(P<0.05).Moreover,neuronal injury was detected and significantly decreased expression levels of BDNF in the brain were measured in the WT-P group compared with the WT-C group(P<0.05).The degree of abnormal behaviors and neuronal injury was reduced in the Stat3△Il17a-P group compared to the WT-P group(P<0.05).Moreover,the level of BDNF in the Stat3△Il17a-P was higher than that in the WT-P group(P<0.05).Conclusion·Periodontitis may contribute to anxiety-and depressive-like behaviors and neuronal damage in mice,while Th17-specific conditional knockout of Stat3 could significantly alleviate pathological behaviors and neuronal damage.Stat3-mediated-Th17 cell immune responses may play a crucial role in the correlation between periodontitis and anxiety and depression.

Objective:Treat-to-target strategies for psoriatic arthritis (PsA) have been proposed for several years, however, the status of target and goal achievement in China is unknown. Therefore, we aimed to investigate the target achievement of PsA patients, and differences of treatment goals were further analyzed.Methods:A total of 360 PsA patients from Peking University First Hospital PsA patient cohort (PKUPsA) between January 2016 and March 2024 were included. We retrospectively analyzed the disease activity of patients at their enrollment. Minimal disease activity (MDA), disease activity index for PsA (DAPSA), clinical DAPSA (cDAPSA) and disease activity score based on 28 joint counts (DAS28) were evaluated. Interclass correlation coefficient (ICC) was used to test the consistency of all these assessments.Results:Three hundred and sixty patients were included in this study, with 149 females (41.4%), median age 47 (36, 57) years and duration of PsA for 2.0(1.0, 6.8) years. 129 (35.8%) patients reported family history of PsO. The most common comorbidities were hyperlipidemia (101, 28.1%) and hypertension (78, 21.7%). There were 217 (60.3%), 75 (20.8%) and 18 (5.0%) patients treated with conventional synthetic DMARDs, biologics and JAK inhibitors respectively. Forty-nine (13.6%) patients ever received intra-articular injection of glucocorticoid. Based on the different definitions, the rates of target achievement were 33.9% (MDA), 56.1% (DAPSA), 60.8% (DAS28-ESR), 63.9% (DAS28-CRP) and 64.2% (cDAPSA). The main limiting factors for MDA attainment among those who had achieved DAPSA or DAS-defined targets were pain VAS, Psoriasis Area and Severity Index (PASI), tender/swollen joint count, patient global assessment, HAQ, and number of enthesitis, based on leeds Enthesitis Index(LEI). The ICCs of these evaluation methods were 0.489~0.819 ( P<0.001). The consistency was the best between DAPSA and cDAPSA, medium between DAS28-CRP and DAS28-ESR, and worst between MDA and DAS28-CRP. Moreover, DAPSA was more consistent with DAS28 than cDASPA. MDA showed moderate consistency with all other assessments. Conclusion:33.9%~64.2% of PsA patients achieved targets based on different definitions. MDA was the most stringent target, while cDAPSA was the most loose one. In general, MDA was not well consistent with other assessments.

Objective To analyze the risk of bias during the experimental process and the shortcomings of the research report by evaluating the methodological and reporting quality of animal experimental studies on the prevention and treatment of precancerous lesions of gastric cancer(PLGC)using TCM compounds.To provide reference for improving the quality of animal experimental research on the prevention and treatment of PLGC with TCM compounds.Methods Experimental literature about the prevention and treatment of PLGC with TCM compounds was retrieved from CNKI,Wanfang Data,VIP,CBM,PubMed,Cochrane Library,Web of science and Embase from January 1,2014 to February 23,2024.SYRCLE assessment tool and ARRIVE 2.0 guideline were used to score the included literature and calculate the"low-risk"compliance rate for each item.Results Totally 213 articles were finally included,including 189 Chinese articles and 24 English articles.The SYRCLE tool score was(12.86±1.29)points,and the"low risk"compliance rate was 32.79％.The score of the necessary items of the ARRIVE 2.0 guideline was(24.15±2.80)points,and the"low risk"compliance rate was 49.08％;the score of the recommended items was(11.28±3.40)points,and the"low risk"compliance rate was 30.27％.In the SYRCLE tool evaluation,144(67.61％)studies did not elaborate on the method of generating the allocation sequence.All studies did not describe the adequacy of allocation concealment and the blinding method in the implementation of bias.Only 51 studies(23.94％)explicitly proposed the success criteria for PLGC modeling,only 66 studies(30.96％)provided detailed information on the statistical methods used,29 studies(13.62％)provided complete ethical statements,and 22 studies(10.33％)reported conflicts of interest.Conclusion There are many problems in the methodological quality and reporting quality of animal experimental literature on the prevention and treatment of PLGC with TCM compounds published from 2014 to 2024,especially the implementation of the random blinding strategy during the experimental process,the calculation details of the sample size,and the reporting of inclusion and exclusion criteria,etc.There are many deficiencies in this aspect.It is recommended to refer to the SYRCLE evaluation tool and the ARRIVE 2.0 guideline list to design and report the research plan,thereby improving the credibility and standardization of the PLGC animal experimental research results.

Objective:To evaluate the effect of trans-nasal humidified rapid insufflation ventilatory exchange (THRIVE) on the early postoperative atelectasis in patients undergoing prolonged non-intubated intravenous anesthesia for gastrointestinal endoscopic procedures.Methods:In this randomized double-blind controlled trial, 150 patients of either sex, aged 18-80 yr, with American Society of Anesthesiologists Physical Status classification Ⅰ or Ⅱ and body mass index of 18-30 kg/m 2, scheduled for endoscopic mucosal resection of multiple colorectal polyps at Northern Jiangsu People′s Hospital Affiliated to Yangzhou University from February 18 to June 15, 2024, were divided into 2 groups ( n=75 each) using simple random allocation: THRIVE group (group T) and conventional oxygen therapy group (group C). In group T, the oxygen flow rate was 10 L/min before anesthesia induction and increased to 50 L/min after induction until the end of operation, and the inhaled oxygen concentration was 100%. Group C used conventional mask oxygen inhalation, with an oxygen flow rate of 10 L/min during anesthesia induction and maintenance. Lung ultrasonography was performed immediately before anesthesia induction and after the end of surgery, and the modified lung ultrasound score and diaphragm mobility during quiet breathing were recorded to assess the occurrence of atelectasis and diaphragmatic dysfunction. The lowest intraoperative SpO 2 value, adverse events during surgery and in the postanesthesia care unit (PACU), duration of PACU stay, adverse events within 7 days after operation, hospitalization duration, and satisfaction scores of both patients and endoscopists were recorded. Results:Compared with group C, the postoperative modified lung ultrasound score and incidence of atelectasis and diaphragmatic dysfunction were significantly decreased, the lowest intraoperative SpO 2 value was increased, the incidence of hypoxemia was decreased, the duration of PACU stay was shortened, and endoscopists′ satisfaction scores were increased ( P<0.05), and no statistically significant changes were observed in diaphragm mobility, incidence of other intraoperative adverse events, incidence of adverse events during PACU stay and within 7 days after operation, or patients′ satisfaction scores in group T ( P>0.05). Conclusions:THRIVE can reduce the risk of early postoperative atelectasis and intraoperative hypoxemia, thereby promoting postoperative recovery of patients undergoing gastrointestinal endoscopy under long-term non-intubated anesthesia.

Neuroendocrine carcinoma (NEC) represents a category of malignant tumors originating from neuroendocrine cells. Given that NEC cells exhibit characteristics of both neural and endocrine cells, they can hijack neuronal signaling pathways and dynamically regulate the expression of neuronal lineage markers during tumor metastasis, thereby constructing a microenvironment conducive to tumor growth and metastasis. Conversely, alterations in the tumor microenvironment can enhance the interactions between neurons and tumor cells, ultimately synergistically promoting the metastasis of NEC. This review highlights recent advancements in the field of cancer neuroscience, uncovering neuronal lineage markers in NEC that facilitate tumor dissemination through mediating crosstalk, bidirectional communication, and synergistic interactions between tumor cells and the nervous system. Consequently, the latest findings in tumor neuroscience have enriched our understanding of the biological mechanisms underlying tumor metastasis, opening new research avenues for a deeper comprehension of the complex biological processes involved in tumor metastasis, particularly brain metastasis. This review provides a comprehensive review of the crosstalk between tumor cells and neural signaling in the metastasis of NEC.
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Humans ; Carcinoma, Neuroendocrine/metabolism* ; Signal Transduction ; Animals ; Neoplasm Metastasis ; Neurons/pathology* ; Tumor Microenvironment ; Cell Communication