ObjectiveTo investigate the role of Ras-GTPase-activating protein SH3 domain-binding protein 2 （G3BP2） in regulating the activation， proliferation， and migration of hepatic stellate cells （HSCs）. MethodsThe mouse HSCs （JS-1 cell line） were treated with 5 μg/L transforming growth factor-beta 1（TGF-β1） for 24 hours to establish an HSC activation and proliferation model. A G3BP2 knockdown system was constructed using siRNA interference technology. The experiment was divided into four groups： Control， TGF-β1 treatment， TGF-β1+si-NC， and TGF-β1+ G3BP2-siRNA. The expression levels of key fibrosis indicators， including type I collagen （Collagen I）， α-smooth muscle actin （α-SMA）， and G3BP2， were detected by Western blot and RT-qPCR. Cell proliferation activity was assessed using the CCK-8 proliferation assay kit and EdU fluorescence labeling technology. Cell migration ability was analyzed by scratch wound healing assay and Transwell migration assay. The formation level of stress granules was quantified by immunofluorescence microscopy to investigate the effects of G3BP2 on stress granule formation in activated HSCs. ResultsStimulation with TGF-β1 upregulated the expression of G3BP2 in JS-1 cells （RT-qPCR： P0.000 1； Western blot： P0.000 1）， while a downward trend in its expression was observed in the G3BP2‑silenced group （RT-qPCR： P0.01； Western blot： P0.000 1）. Compared with the control group， the TGF-β1 group exhibited increased protein expression levels of α-SMA and Collagen I （RT-qPCR： both P0.01； Western blot： P0.01 and P0.05， respectively）， concomitant with an increased number of stress granules and enhanced cell proliferation and migration capacity （all P0.001）. The experimental results demonstrated that G3BP2 knockout effectively reversed the aforementioned phenotypes， with the G3BP2-silenced group showing reduced expression of fibrotic markers （all P0.01）， decreased stress granule formation （P0.01）， and reduced cell proliferation and migration capacity （all P0.05）， compared to the negative control group. ConclusionG3BP2 enhances the activation， proliferation， and migration of HSCs by promoting the formation of stress granules， thereby accelerating the pathological progression of liver fibrosis. This suggests that stress granules may serve as important regulators in controlling the activation， proliferation， and migration of HSCs.

Objective To analyze the effect of residual cholesterol (RC) on hearing loss in noise-exposed workers. Methods A total of 3 412 workers engaged in noise operation work in an underground railway enterprise were selected as the research subjects using the judgment sampling method. Their occupational health examination data were collected to analyze the relationship between RC and hearing loss. Results The noise intensity of workplace in the underground rail enterprise was 80.0-85.0 (81.4±3.2) dB(A). The detection rate of hearing loss was 20.2% (691/3 412). The rates of abnormal total cholesterol, triacylglycerol, high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol were 35.6%, 25.7%, 9.5% and 42.4%, respectively. The median and the 25th and 75th percentiles [M(P₂₅,P₇₅)] of RC level were 0.24 (0.15, 0.37) mmol/L. The levels of total cholesterol, triacylglycerol and RC of workers in hearing loss group were higher than those in normal hearing group [M(P₂₅,P₇₅): 4.91(4.37, 5.58) vs 4.84(4.30, 5.46) mmol/L, 1.29(0.91, 1.93) vs 1.16(0.82, 1.67) mmol/L, 0.26(0.16, 0.41) vs 0.24(0.14, 0.37) mmol/L, all P<0.05]. The detection rate of hearing loss in abnormal triglyceride group was higher than that in normal triglyceride group (24.8% vs 18.7%, P<0.01), and the detection rate of hearing loss in abnormal HDL-C group was higher than that in normal HDL-C group (25.0% vs 19.8%, P<0.05). The higher the serum RC level, the higher the detection rate of hearing loss (P<0.01). Multivariate logistic regression result showed that individual with older age, longer work time and higher serum RC level had higher risk of hearing abnormality (all P<0.05), and the risk of hearing abnormality was higher in patients with abnormal fasting blood glucose than patients with normal faseing blood glucose (P<0.05) after controlling for confounding factors such as gender, alcohol consumption, body mass index, and elevated blood pressure. However, abnormal triacylglycerol and HDL-C levels were not significantly related to the risk of hearing abnormality (both P>0.05). Conclusion Serum RC levels are an independent risk factor for hearing loss among noise-exposed workers exposed to noise level of 80.0-85.0 dB(A) in the workplace.

Subtype classification of age-related macular degeneration (AMD) based on optical coherence tomography (OCT) images serves as an effective auxiliary tool for clinicians in diagnosing disease progression and formulating treatment plans. To improve the classification accuracy of AMD subtypes, this study proposes a keypoint-based, attention-enhanced residual network (KPA-ResNet). The proposed architecture adopts a 50-layer residual network (ResNet-50) as the backbone, preceded by a keypoint localization module based on heatmap regression to outline critical lesion regions. A two-dimensional relative self-attention mechanism is incorporated into convolutional layers to enhance the representation of key lesion areas. Furthermore, the network depth is appropriately increased and an improved residual module, ConvNeXt, is introduced to enable comprehensive extraction of high-dimensional features and enrich the detail of lesion boundary contours, ultimately achieving higher classification accuracy of AMD subtypes. Experimental results demonstrate that KPA-ResNet achieves significant improvements in overall classification accuracy compared with conventional convolutional neural networks. Specifically, for the wet AMD subtypes, the classification accuracies for inactive choroidal neovascularization (CNV) and active CNV reach 92.8% and 95.2%, respectively, representing substantial improvement over ResNet-50. These findings validate the superior performance of KPA-ResNet in AMD subtype classification tasks. This work provides a high-accuracy, generalizable network architecture for OCT-based AMD subtype classification and offers new insights into integrating attention mechanisms with convolutional neural networks in ophthalmic image analysis.
Tomography, Optical Coherence/methods* ; Humans ; Macular Degeneration/diagnostic imaging* ; Neural Networks, Computer

OBJECTIVES: Depression is a common negative emotion that can significantly impact physical and mental health. Due to their occupational characteristics, medical staff are more susceptible to depression compared to the general population. This study aims to explore the influence of future-oriented coping on depression among medical staff and the mediating roles of psychological resilience and perceived stress, providing theoretical guidance for depression intervention strategies in this group. METHODS: A cross-sectional survey was conducted among medical staff at a tertiary hospital using convenience sampling. Data were collected via the "Wenjuanxing" platform. A total of 754 questionnaires were distributed; after excluding invalid responses (e.g., duplicate IPs or insufficient completion time), 655 valid questionnaires were retained (valid response rate: 86.87%). Instruments included a demographic questionnaire, the Future-Oriented Coping Scale, the Connor-Davidson Resilience Scale, the Perceived Stress Scale, and the Self-Rating Depression Scale. All scales demonstrated high internal consistency (Cronbach's α>0.88) and validity. SPSS 27.0 was used for descriptive analysis, and PROCESS macro (Model 6) was used to test the chain mediation model. Harman's one-factor test was applied to control for common method bias. RESULTS: Descriptive analyses showed that future-oriented coping was positively correlated with psychological resilience and negatively correlated with perceived stress and depression. Mediation analysis revealed that future-oriented coping significantly predicted lower depression levels among medical staff (β=-0.283, P<0.001). Psychological resilience partially mediated the relationship (effect size=-0.329, accounting for 34.13% of the total effect), as did perceived stress (effect size=-0.099, 10.27%). A significant chain mediation path was identified: "future-oriented coping → psychological resilience → perceived stress → depression" (effect size=-0.253, 26.24%). The total indirect effect accounted for 70.64% of the overall effect, highlighting the substantial role of the mediating pathways. CONCLUSIONS Future-oriented coping can reduce depressive symptoms in medical staff, with psychological resilience and perceived stress serving as key mediators in a chain structure. These findings suggest that enhancing future-oriented coping strategies and psychological resilience may improve stress adaptation and reduce depression levels in this population.
Humans ; Adaptation, Psychological ; Resilience, Psychological ; Cross-Sectional Studies ; Depression/psychology* ; Surveys and Questionnaires ; Stress, Psychological/psychology* ; Male ; Female ; Adult ; Middle Aged ; Medical Staff/psychology* ; Occupational Stress/psychology*

Allergen-specific Immunotherapy (AIT) is currently the only allopathic treatment capable of modifying the natural course of immunoglobulin E (IgE)-mediated allergic diseases. Currently, there is a lack of recognized clinical markers for evaluating and predicting the efficacy of AIT, and some biological markers may have some potential for application. This article will summarize the currently known indicators for evaluating and predicting the therapeutic effects of AIT, with the aim of providing assistance in evaluating and monitoring the efficacy of AIT.

BACKGROUND:Cervical instability is a common orthopedic disease in young and middle-aged people,and is the early manifestation of cervical spondylosis,which has a great impact on the quality of life of patients.Therefore,early diagnosis of cervical instability to implement early intervention has positive clinical and social significance.OBJECTIVE:The clinical prediction model of cervical instability in young and middle-aged people was constructed based on machine learning to realize early screening of cervical instability in young and middle-aged people before X-ray examination.METHODS:From September 2022 to October 2023,155 young and middle-aged adults with cervical instability and 88 with non-cervical instability recruited through recruitment advertisements and spinal department outpatient of Wangjing Hospital,China Academy of Chinese Medical Sciences were selected as research subjects.The research subjects'general information,living and working habits,discomfort symptoms,visual analog scale score,Neck Disability Index,and 36-ltem Short Form Health Survey were collected on site based on questionnaires.The above information was used as predictive factors.After screening,six machine learning algorithms of Support Vector Machine,LightGBM,RandomForest,Logistic,AdaBoost,and XGBClassifier were used to train the model by ten-fold cross-validation method,and the clinical prediction model of cervical instability was constructed.Area under the curve was used as the main evaluation index.Univariate analysis was performed on the predictors,and SHAP method was used to rank the importance of the predictors.Correlation heat maps were used to show the degree of linear correlation between the predictors and the cervical instability.RESULTS AND CONCLUSION:(1)Among the six machine learning models,RandomForest model was chosen as the final prediction model,including nine predictors,such as age,body mass index,neck circumference/neck length,visual analog scale score,Neck Disability Index,bodily pain,general health,vitality,and mental health,area under the curve=0.725 4,and the calibration degree was good.It could be used as a reference tool for early screening of cervical instability in young and middle-aged people.(2)There were significant differences in age,visual analog scale score,Neck Disability Index,bodily pain,general health,and vitality between the two groups(P＜0.05).(3)The order of importance of predictors was age,Neck Disability Index,visual analog scale score,general health,body mass index,vitality,bodily pain,neck circumference/neck length,mental health,among which age,visual analog scale score,Neck Disability Index were positively correlated with cervical instability,while general health,body mass index,vitality,bodily pain,neck circumference/neck length,and mental health were negatively correlated with cervical instability.

Female reproductive system diseases,such as premature ovarian insufficiency(POI),premature ovarian failure(POF),polycystic ovary syndrome(PCOS),intrauterine adhesions(IUA),ulterus scar diverticulum,salpingitis,and tubal obstruction,may induce infertility,severely impacting patients'physical and mental health and quality of life.Currently,the umbilical cord mesenchymal stem cells(UCMSCs)have emerged as a research focus in gynecological and obstetric fields,demonstrating significant therapeutic potential for female reproductive system disorders.UCMSCs secrete various cytokines,activate relevant signaling pathways and key molecules,reduce inflammation mediators and oxidative stress,and prevent excessive cellular damage and apoptosis,thereby achieving therapeutic effects.In recent years,extensive studies have explored the therapeutic effects of UCMSCs on female reproductive system diseases.This article review the current in vitro and in vivo research progress in UCMSCs for treating female reproductive system diseases,aiming to provide the novel strategies and directions for future research and clinical applications.

Objective:To establish the quality standard of Galla Turcica standard decoction; To provide a reference for the quality evaluation of its decoction granules.Methods:The moisture, total ash, acid-insoluble ash, and extract of Galla Turcica were assessed according to the guidelines specified in the Chinese Pharmacopoeia (Volume Ⅳ); high-performance liquid chromatography (HPLC) was employed to quantify the gallic acid content in sixteen batches of Galla Turcica and standard decoction, from which the transfer rate was calculated; the paste rate, moisture, and extract yield were quantitatively analyzed, establishing the comprehensive fingerprint of Galla Turcica standard decoction. The quantitative value transfer rules of common peaks from medicinal materials to standard decoction were studied through similarity evaluation and stoichiometric analysis. Results:The gallic acid content of the sixteen batches of Galla Turcica standard decoction ranged from 76.79 mg/g to 115.04 mg/g, the range of transfer rate was 24.02% to 47.82%, the extraction rate was 34.04% to 63.23%, the moisture was 1.11% to 2.06%, and the extract was 94.44% to 101.75%. A total of nine characteristic peaks were identified in the fingerprints of the sixteen batches of Galla Turcica and standard decoction, and four characteristic peaks were identified: gallic acid (GA), 1, 2, 3, 6 - tetragalloylglucose (TeGG), ellagic acid (EA) and 1, 2, 3, 4, 6, - pentagalloylglucose (PGG). Clustering analysis revealed that at a measurement distance of fifteen, the sixteen batches could be grouped into two categories. Principal component analysis (PCA) showed that three principal components were extracted with a cumulative variance contribution rate of 84.204%, which could represent most of the information of the samples.Conclusions:The standard decoction preparation process developed in this study adheres to the requirements of traditional decoction methods and has proven to be both effective and feasible. This method can be used for the research and quality evaluation of standard decoction of Galla Turcica, and provide a basis for subsequent formulation granules and related research.

Allergen-specific Immunotherapy (AIT) is currently the only allopathic treatment capable of modifying the natural course of immunoglobulin E (IgE)-mediated allergic diseases. Currently, there is a lack of recognized clinical markers for evaluating and predicting the efficacy of AIT, and some biological markers may have some potential for application. This article will summarize the currently known indicators for evaluating and predicting the therapeutic effects of AIT, with the aim of providing assistance in evaluating and monitoring the efficacy of AIT.

The prevalence of allergic diseases is on the rise,posing a significant global health challenge.Allergen specific immunotherapy(AIT)is the only treatment capable of altering the natural course of allergic diseases,offering long-term efficacy and the potential to prevent disease progression.However,its widespread application is hindered by factors such as lengthy treatment duration,adverse reactions,and patient compliance issues.In recent years,biologics targeting type 2 inflammatory pathways have played a crucial role at various stages of different allergic diseases.Research indicates that for patients with moderate to severe allergic diseases,using biologics during or prior to AIT can significantly enhance the safety of AIT,reduce the time required to reach maintenance doses,and markedly improve symptom scores.This article elucidates the synergistic mechanisms and recent advancements in the combined application of biologics and AIT in the treatment of allergic diseases.The aim is to provide a reference for the standardized treatment of allergic diseases.