BackgroundAnxiety disorder is a common mental disorder， with its prevalence showing a continuous upward trend， significantly affecting the quality of life and social function of patients. Due to the lack of objective and reliable biomarkers in clinical practice， the early identification and treatment of anxiety disorder have been somewhat limited. Plasma proteins have the potential to serve as biomarkers for mental diseases， however， the causal relationship between them and anxiety disorder remains unclear. ObjectiveTo identify the plasma proteins that have a causal relationship with anxiety disorders， and to elucidate the associated biological pathways， in order to provide references for the search for biomarkers of anxiety disorders and the exploration of potential therapeutic targets. MethodsBased on the protein quantitative trait locus （pQTL） data of 4 907 plasma proteins covering 35 559 Icelandic individuals from the deCODE database， and the genome-wide association studies （GWAS） data of 50 486 patients with anxiety disorders and 330 460 healthy controls， the inverse-variance weighted （IVW） method was used as the main analysis method， supplemented by MR-Egger method， weighted median method， simple model method， and weighted model method for bidirectional Mendelian randomization analysis. Enrichment analysis of gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathways was conducted for the related proteins. Sensitivity analysis was performed using Cochran's Q test， MR-Egger intercept test， MR-PRESSO test， and leave-one-out analysis to evaluate the robustness of the results. ResultsA total of 10 plasma proteins were identified as significantly associated with anxiety disorders. Among these， SPATA9 （OR=0.856， 95% CI： 0.784–0.934， P<0.01） and PDE5A （OR=0.911， 95% CI： 0.864–0.961， P<0.01） were identified as protective factors， while CRYGD （OR=1.209， 95% CI： 1.095–1.334， P<0.01）， BTN3A3 （OR=1.045， 95% CI： 1.018–1.073， P<0.01）， SERPINB13 （OR=1.102， 95% CI： 1.040–1.168， P<0.01）， ERBB4 （OR=1.283， 95% CI： 1.109–1.484， P<0.01）， LSAMP （OR=1.096， 95% CI： 1.037–1.158， P<0.01）， ICOSLG （OR=1.283， 95% CI： 1.104–1.490， P<0.01）， DNAJB11 （OR=1.172， 95% CI： 1.076–1.277， P<0.01）， and TREML1 （OR=1.115， 95% CI： 1.054–1.179， P<0.01） were identified as risk factors. The sensitivity analysis showed that the results were robust， with no heterogeneity （Cochran's Q test P>0.05） or pleiotropy （MR-Egger intercept test P>0.05）. Enrichment analysis indicated that these plasma proteins were enriched in biological processes such as T-cell signal transduction， lymphocyte proliferation， cell membrane structure and synaptic function， as well as the intestinal immune network that produces IgA and the ErbB signaling pathway. ConclusionThis study identified 10 plasma proteins associated with anxiety disorders. The functions of these plasma proteins involve multiple biological processes such as neural development and immune regulation.

Chronic eczema has a high prevalence in China， significantly impacting patients’ quality of life. Leveraging the unique advantages of pattern identification/syndrome differentiation and treatment， along with a holistic approach， traditional Chinese medicine （TCM）， which integrates internal and external therapies， has been widely applied in the management of chronic eczema. It has demonstrated significant efficacy and distinctive strengths in alleviating symptoms， reducing recurrence rates， maintaining disease stability， and enhancing patients’ quality of life. Oral administration of TCM（e.g. modified Longdan xiegan decoction） can improve patients’ clinical symptoms through systemic regulation. External use of TCM can directly act on the skin lesion with the help of steaming and washing， hydropathic compress， ointment and other forms. At the same time， it can effectively relieve the clinical symptoms of chronic eczema by combining with non-drug therapies such as acupuncture， moxibustion， acupoint catgut embedding， blood-letting puncture and cupping. In addition， characteristic therapies such as oral administration of TCM combined with external treatment， a combination of various external treatments and a combination of Chinese and Western medicine have also demonstrated certain advantages in regulating immune function， alleviating skin lesions， and relieving itching symptoms. These therapies cooperate with each other， creating a synergistic effect that treats both the symptoms and the root cause simultaneously. It is suggested that more high-quality， large-scale clinical research should be conducted in the future to systematically confirm the therapeutic advantages of TCM and further explore the specific molecular mechanism of action.

Objective To construct a prediction model for the progression of knee osteoarthritis(KOA)based on ultrasound score,magnetic resonance imaging(MRI)score,and serum levels of transforming growth factor-β1(TGF-β1)and cathepsin D(Cat D).Methods Clinical data from 270 patients with KOA in Hengshui People's hospital from December 2022 to June 2024 were retrospec-tively analyzed.The patients were randomly divided into a modeling set(n=189)and validation set(n=81)at a ratio of 7∶3.The patients in the modeling set were categorized into mild-to-moderate and severe groups based on the degree of disease progression.Mul-tivariate logistic regression analysis was used to identify factors influencing KOA progression,and a prediction model was constructed using R software.Results Multivariate logistic regression analysis showed that body mass index,knee injury history,ultrasound score,WORMS score,TGF-β1,and Cat D were significant predictors of KOA progression(P＜0.05).A nomogram-based prediction model was developed using these variables.The areas under the curve(AUC)of the nomograms for predicting disease progression in the modeling and validation sets were 0.889 and 0.860,respectively.The calibration curves showed that the predicted probability was in good agreement with the actual probability.Conclusion The prediction model developed in this study is effective in identifying patients at high-risk of KOA progression and may servce as a valuable tool for clinical assessment and decision making.

Purpose To explore the value of gray-scale ultrasound and contrast-enhanced ultrasound of carotid plaques combined with clinical factors in predicting the recurrence risk of ischemic stroke(IS)in patients with mild to moderate carotid stenosis.Materials and Methods A total of 101 patients with mild to moderate carotid artery stenosis who were initially diagnosed with IS in the First Medical Center of the Chinese PLA General Hospital were prospectively collected from May 2022 to August 2023.After one year of follow-up,patients were divided into recurrent group(n=33)and non-recurrent group(n=68)according to whether new IS occurred.The characteristics of plaque ultrasound and the clinical information of patients were compared between the two groups.A multivariate Logistic prediction model was established and its efficacy was evaluated.Results The results of multivariate analysis showed that low-density lipoprotein cholesterol(OR=2.116,P=0.046),C-reactive protein(OR=3.707,P=0.008),plaque internal echo(OR=7.410,P=0.029)and intraplaque neovascularization grading 3(OR=17.155,P=0.030)were independent risk factors for the recurrence of IS.The area under the curve of the model established using the above indicators was 0.825,the sensitivity and specificity were 87.50%and 65.15%,respectively.Conclusion The ultrasound features of carotid plaque are closely related to recurrent IS,which can provide an important basis for the clinical treatment of patients with mild-moderate carotid artery stenosis complicated with IS.

ObjectiveTo analyze the distribution of traditional Chinese medicine （TCM） syndrome elements in patients with immune-related adverse events （irAEs） associated with malignant tumor immunotherapy and to explore the influencing factors for the occurrence of irAEs. MethodsClinical data were retrospectively collected from malignant tumor patients treated with programmed death-1 （PD-1） inhibitors， including demographic information， tumor history， duration of immunotherapy， occurrence of irAEs， types and grades of irAEs （G1-G5）， and TCM four-diagnostic information. Patients were divided into irAEs group and the non-irAEs group based on the occurrence of irAEs. Propensity score matching （PSM） at a 1∶2 ratio was performed to balance baseline characteristics between groups. Syndrome elements before treatment and cumulative contributions of syndrome elements before and after irAEs onset were evaluated using the "Syndrome Elements Differentiation Scale". Logistic regression analysis was conducted to identify factors associated with the occurrence of irAEs. The use of glucocorticoids in the irAEs group was also analyzed. ResultsAfter 1∶2 matching， 59 patients were included in the irAEs group and 118 were in the non-irAEs group. No statistically significant differences were found between groups in terms of age， gender， primary tumor site， pathological type， or tumor stage （P＞0.05）. Patients in the non-irAEs group were more likely to have received targeted therapy， while the irAEs group had a longer duration of immunotherapy and a higher rate of positive programmed death-ligand 1 （PD-L1） expression （P＜0.05）. In total， 72 irAEs events occurred among 59 patients， with an overall incidence rate of 19.4% （59/304） and a grade 3~5 incidence rate of 6.8% （4/59）， mainly presenting as cardiotoxicity， nephrotoxicity， and pneumotoxicity.Before immunotherapy， the top three syndrome elements in the irAEs group were spleen （71.2%， 42/59）， kidney （42.4%， 25/59）， and lung （39.0%， 23/59）. For the pathogenic nature elements， yin deficiency （52.5%， 31/59）， phlegm （40.7%， 24/59）， and dampness （35.6%， 21/59） ranked highest. Compared to the non-irAEs group， the distribution of spleen， kidney， liver， yin deficiency， and qi deficiency elements showed significant differences in the irAEs group （P＜0.05）. After the occurrence of irAEs， the cumulative contributions of spleen， lung， stomach， heart， yin deficiency， qi deficiency， and yang hyperactivity elements increased significantly （P＜0.05）. Multivariate Logistic regression analysis indicated that duration of immunotherapy， spleen syndrome element， kidney syndrome element， liver syndrome element， yin deficiency element， and qi deficiency element were independent risk factors for irAEs （P＜0.05 or P＜0.01）. Among the irAEs patients， 15 received glucocorticoid combined with TCM treatment， while 6 received glucocorticoid therapy alone. Patients receiving combined treatment required lower doses and shorter courses of glucocorticoids compared to those treated with glucocorticoids alone （P＜0.05）. ConclusionIn malignant tumor patients， spleen， kidney， lung， yin deficiency， phlegm， dampness， and qi deficiency are the predominant syndrome elements before and after the occurrence of irAEs. However， elements such as heat and qi stagnation significantly increase after irAEs onset. Duration of immunotherapy， spleen， kidney， liver syndrome elements， yin deficiency， and qi deficiency are independent risk factors for the development of irAEs.

Objective To construct a prediction model for the progression of knee osteoarthritis(KOA)based on ultrasound score,magnetic resonance imaging(MRI)score,and serum levels of transforming growth factor-β1(TGF-β1)and cathepsin D(Cat D).Methods Clinical data from 270 patients with KOA in Hengshui People's hospital from December 2022 to June 2024 were retrospec-tively analyzed.The patients were randomly divided into a modeling set(n=189)and validation set(n=81)at a ratio of 7∶3.The patients in the modeling set were categorized into mild-to-moderate and severe groups based on the degree of disease progression.Mul-tivariate logistic regression analysis was used to identify factors influencing KOA progression,and a prediction model was constructed using R software.Results Multivariate logistic regression analysis showed that body mass index,knee injury history,ultrasound score,WORMS score,TGF-β1,and Cat D were significant predictors of KOA progression(P＜0.05).A nomogram-based prediction model was developed using these variables.The areas under the curve(AUC)of the nomograms for predicting disease progression in the modeling and validation sets were 0.889 and 0.860,respectively.The calibration curves showed that the predicted probability was in good agreement with the actual probability.Conclusion The prediction model developed in this study is effective in identifying patients at high-risk of KOA progression and may servce as a valuable tool for clinical assessment and decision making.

Aromatherapy refers to the method of using the aromatic components of plants in appropriate forms to act on the entire body or a specific area to prevent and treat diseases. Essential oils used in aromatherapy are hydrophobic liquids containing volatile aromatic molecules， such as limonene， linalool， linalool acetate， geraniol， and citronellol. These chemicals have been extensively studied and shown to have a variety of functions， including reducing anxiety， relieving depression， promoting sleep， and providing pain relief. Terpenoids are a class of organic molecules with relatively low lipid solubility. After being inhaled， they can pass through the nasal mucosa for transfer or penetrate the skin and enter the bloodstream upon local application. Some of these substances also have the ability to cross the blood-brain barrier， thereby exerting effects on the central nervous system. Currently， the academic community generally agrees that products such as essential oils and aromatherapy from aromatic plants have certain health benefits. However， the process of extracting a single component from it and successfully developing it into a drug still faces many challenges. Its safety and efficacy still need to be further verified through more rigorous and systematic experiments. This article systematically elaborated on the efficacy of aromatic substances， including plant extracts and natural small molecule compounds， in antibacterial and antiviral fields and the regulation of nervous system activity. As a result， a deeper understanding of aromatherapy was achieved. At the same time， the potential of these aromatic substances for drug development was thoroughly explored， providing important references and insights for possible future drug research and application.

BackgroundGenetic factor plays an important role in the pathogenesis of panic disorder. Previous studies have revealed that immune system dysregulation is closely related to mental disorders such as panic disorder， while the relationship between panic disorder and immune-related gene expression remains unclear. ObjectiveTo explore the relationship between the expression of CXCL8， IL6R， JUN， PTGS2， TGFBR1， TLR2， CCR4 genes and panic disorder， providing references for the diagnosis and treatment of panic disorder. MethodsA total of 52 patients who met the diagnostic criteria for panic disorder according to the Diagnosed and Statistical Manual of Mental Disorders， fourth edition （DSM-IV） were enrolled at the Psychosomatic Medicine Center of Sichuan Provincial People's Hospital from January 2020 to March 2021. Another 72 healthy individuals matched for age and gender from Chengdu were concurrently recruited as control group. The Panic Disorder Severity Scale （PDSS） was used to assess the severity of symptoms in panic disorder patients. Quantitative real-time polymerase chain reaction （PCR） was used to detect gene expression levels in two groups. Spearman correlation analysis was adopted to determine the correlation between PDSS score and immune-related gene expression in research group. ResultsThe expression of the JUN， PTGS2 and TGFBR1 genes were significant higher in panic disorder patients than those in control group （Z=-4.172， -2.086， -3.018， P<0.05 or 0.01）. After false discovery rate （FDR） correction for multiple testing， the differential expression of JUN and TGFBR1 genes remained statistically significant between two groups （P<0.05）. There was no significant difference in the expression of CCR4， CXCL8， IL6R and TLR2 genes between two groups （P>0.05）. Correlation analysis revealed that the expression of the JUN gene in panic disorder patients was positively correlated with PDSS score （r=0.360， P<0.01）， while the CCR4， CXCL8， IL6R， PTGS2， TGFBR1 and TLR2 genes showed no statistically significant correlation with the PDSS score （P>0.05）. ConclusionThe expression of the JUN and TGFBR1 genes may be associated with panic disorder， and the expression of the JUN gene correlated with the severity of panic disorder. ［Funded by Science and Technology Plan Project of Sichuan Provincial Department of Science and Technology （number， 2021YJ0440）］

ObjectiveTo evaluate the efficacy and safety of transcutaneous electrical acupoint stimulation (TEAS) for muscle atrophy in patients with immobilization after surgical fixation of foot and ankle fractures.MethodsThis was a two-arm randomized controlled trial wherein 80 patients were recruited and divided into control (n = 40) and intervention (n = 40) groups. The control group received conventional orthopedic treatment, whereas the intervention group received TEAS and conventional treatment. The intervention group received TEAS 3 times a week for 30 min each time for 8 weeks. The primary outcomes were muscle thickness (MT) and cross-sectional area (CSA) of the rectus femoris and gastrocnemius muscles, whereas the secondary outcome measure was echo intensity (EI). Data were collected before the fixation operations (baseline assessment) and 4 and 8 weeks after intervention.ResultsCompared with baseline, the MT and CSA were reduced in both groups by the end of treatment, whereas EI increased in both groups. At week 4, the reduction in the rectus femoris CSA in the intervention group was significantly lower than that in the control group (P = .02); however, the between-group differences in the MT and EI (all P .05) were not significant. No serious adverse events were observed in either group.ConclusionOur study showed that TEAS can improve muscle atrophy by attenuating the decline in the muscle CSA. Because this was only a pilot trial, subsequent studies will need longer follow-ups and larger sample sizes.

BACKGROUND: The mechanisms distinguishing metabolically healthy from unhealthy phenotypes within the same BMI categories remain unclear. This study aimed to investigate the associations between regional fat distribution and metabolically unhealthy phenotypes in Chinese adults across different BMI categories. METHODS: This cross-sectional study involving 11833 Chinese adults aged 20 years and older. Covariance analysis, adjusted for age, compared the percentage of regional fat (trunk, leg, or arm fat divided by whole-body fat) between metabolically healthy and unhealthy participants. Trends in regional fat percentage with the number of metabolic abnormalities were assessed by the Jonckheere-Terpstra test. Odds ratios (ORs) and their 95% confidence intervals (CIs) were estimated by logistic regression models. All analyses were performed separately by sex. RESULTS: In non-obese individuals, metabolically unhealthy participants exhibited higher percent trunk fat and lower percent leg fat compared to healthy participants. Additionally, percent trunk fat increased and percent leg fat decreased with the number of metabolic abnormalities. After adjustment for demographic and lifestyle factors, as well as BMI, higher percent trunk fat was associated with increased odds of being metabolically unhealthy [highest vs. lowest quartile: ORs (95%CI) of 1.64 (1.35, 2.00) for men and 2.00 (1.63, 2.46) for women]. Conversely, compared with the lowest quartile, the ORs (95%CI) of metabolically unhealthy phenotype in the highest quartile for percent arm and leg fat were 0.64 (0.53, 0.78) and 0.60 (0.49, 0.74) for men, and 0.72 (0.56, 0.93) and 0.46 (0.36, 0.59) for women, respectively. Significant interactions between BMI and percentage of trunk and leg fat were observed in both sexes, with stronger associations found in individuals with normal weight and overweight. CONCLUSIONS Trunk fat is associated with a higher risk of metabolically unhealthy phenotype, while leg and arm fat are protective factors. Regional fat distribution assessments are crucial for identifying metabolically unhealthy phenotypes, particularly in non-obese individuals.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Young Adult ; Adipose Tissue ; Body Fat Distribution ; Body Mass Index ; China/epidemiology* ; Cross-Sectional Studies ; Health Surveys ; Phenotype