The inflammatory microenvironment is closely associated with the initiation and progression of osteoarthritis （OA）， specifically manifesting as macrophage activation， dysregulation of inflammatory cytokines， and redox imbalance. Following an overview of the pathological characteristics of the OA inflammatory microenvironment， this paper reviews the research progress on the mechanism of traditional Chinese medicine （TCM） intervening in OA by modulating the inflammatory microenvironment. It has been found that TCM monomers/active ingredients （such as total alkaloids from Strychnos nux-vomica ， quercetin， triptolide， etc.）， herb pairs （e.g. Angelica pubescens - Gentiana macrophylla ， Carthami Flos-Lycopodii Herba）， and TCM formulas （such as Zhuanggu jianxi formula， Duhuo jisheng decoction and Rongjin niantong formula， etc.） can inhibit macrophage activation， reduce the release of proinflammatory cytokines and the generation of reactive oxygen species by inhibiting multiple signaling pathways， including nuclear factor-κB， Wnt/ β -catenin， and mitogen-activated protein kinase， thereby alleviating the articular inflammatory microenvironment， restoring local joint homeostasis， and slowing the progression of OA.

ObjectiveTo identify the pathogen species responsible for the wilt disease of Tetradium ruticarpum in Chongqing， investigate there biological characteristics， and screen effective fungicides， so as to provide a theoretical basis for disease control in production. MethodsThe pathogen was isolated via the tissue culture method. Pathogenicity was verified according to Koch's postulates. The pathogen was identified based on morphological characteristics and multi-gene phylogenetic analysis. The mycelial growth rate method was used for biological characterization of the pathogen and fungicide screening. ResultsThe pathogen colonies were nearly circular with irregular edges， white， short， velvety aerial hyphae， and pale purple undersides. Macroconidia were colorless， sickle-shaped， with 3-5 septa， while microconidia were transparent， elliptical， aseptate or with 1-2 septa. Multi-gene phylogenetic analysis showed that the pathogen clustered in the same clade as Fusarium fujikuroi with 100% support， which， combined with morphological characteristics， identified the pathogen causing wilt of T. ruticarpum in Chongqing as F. fujikuroi. The optimal conditions for the mycelial growth of F. fujikuroi were mung bean agar （MBA） with glucose as the carbon source， beef extract and yeast powder as nitrogen sources， 28 ℃， pH 7.0， and alternating light/dark conditions. The optimal conditions for sporulation were potato dextrose agar （PDA） with glucose as the carbon source， beef extract as the nitrogen source， 28 ℃， pH 7.0， and complete darkness. Among chemical fungicides， phenazine-1-carboxylic acid exhibited the strongest inhibitory effect on F. fujikuroi. Shenqinmycin and tetramycin were the most effective bio-fungicides. ConclusionThis study is the first to report F. fujikuroi as the causal agent of wilt disease in T. rutaecarpa. The chemical fungicide phenazine-1-carboxylic acid and the bio-fungicides shenqinmycin and tetramycin showed strong inhibitory effects against F. fujikuroi.

ObjectiveTo address the challenges of unstructured classical Chinese expressions， nested entity relationships， and limited annotated data in famous traditional Chinese medicine（TCM） case records， this study proposes a joint relation extraction framework that integrates data augmentation and entity mapping， aiming to support the construction of TCM diagnostic knowledge graphs and clinical pattern mining. MethodsWe developed an annotation structure for entities and their relationships in TCM case texts and applied a data augmentation strategy by incorporating multiple ancient texts to expand the relation extraction dataset. A cascade binary tagging framework for relation triple extraction（CasRel） model for TCM semantics was designed， integrating a pre-trained bidirectional encoder representations from transformers（BERT） layer for classical TCM texts to enhance semantic representation， and using a head entity-relation-tail entity mapping mechanism to address entity nesting and relation overlapping issues. ResultsExperimental results showed that the CasRel model， combining data augmentation and entity mapping， outperformed the pipeline-based Bert-Radical-Lexicon（BRL）-bidirectional long short-term memory（BiLSTM）-Attention model. The overall precision， recall， and F₁-score across 12 relation types reached 65.73%， 64.03%， and 64.87%， which represent improvements of 14.26%， 7.98%， and 11.21% compared to the BRL-BiLSTM-Attention model， respectively. Notably， the F₁-score for tongue syndrome relations increased by 22.68%（69.32%）， and the prescription-syndrome relations performed the best with the F₁-score of 70.10%. ConclusionThe proposed framework significantly improves the semantic representation and complex dependencies in TCM texts， offering a reusable technical framework for structured mining of TCM case records. The constructed knowledge graph can support clinical syndrome differentiation， prescription optimization， and drug compatibility， providing a methodological reference for TCM artificial intelligence research.

OBJECTIVE:It has been confirmed that neuromodulation technology can improve the clinical symptoms of patients with Parkinson's disease,and there are differences in the efficacy of different neuromodulation stimulation methods.Herein,a network meta-analysis was used to evaluate the efficacy of different neuromodulation stimulation modalities in improving non-motor symptoms such as sleep disorders and depression and anxiety in patients with Parkinson's disease,thereby exploring the optimal neuromodulation stimulation regimen.METHODS:The Chinese Biomedical Literature Database,WanFang Database,VIP Database,CNKI Database,Web of Science,PubMed,The Cochrane Library,and EMbase databases were searched for randomized controlled trials on neuromodulation techniques to improve sleep disorders,depression and anxiety in patients with Parkinson's disease.The control group was treated with conventional treatments(drugs,conventional rehabilitation therapy,etc.)or sham stimulation,and the experimental group was supplemented with neuromodulation technology on the basis of the control group.The quality of the included studies was evaluated using the PEDro scale and the deviation risk assessment tool recommended by the Cochrane Collaboration.RevMan 5.4 and Stata 17.0 were used for network meta-analysis of the four outcomes(sleep disorders,anxiety symptoms,depressive symptoms,and quality of life).RESULTS:(1)Twenty-nine randomized controlled trials involving six neuromodulation stimulation modalities were included.These modalities were transcranial direct current stimulation,high-frequency repetitive transcranial magnetic stimulation,low-frequency repetitive transcranial magnetic stimulation,deep brain stimulation of the subthalamic nucleus,deep brain stimulation of the globus pallidus,multi-target deep brain stimulation.(2)The results of network meta-analysis showed that compared with conventional treatment,transcranial direct current stimulation[standardized mean difference(SMD)=-2.57,95％confidence interval(CI)=-4.52 to-0.63,P＜0.05)had the best effect in improving sleep disorders in patients with Parkinson's disease.In terms of improving depressive symptoms,deep brain stimulation of the globus pallidus(SMD=-1.00,95％CI=-1.87 to-0.14,P＜0.05)had the best effect,followed by low-frequency repetitive transcranial magnetic stimulation(SMD=-0.91,95％CI=-1.60 to-0.23,P＜0.05),deep brain stimulation of the subthalamic nucleus(SMD=-0.82,95％CI=-1.56 to-0.08,P＜0.05),and high-frequency repetitive transcranial magnetic stimulation(SMD=-0.75,95％CI=-0.97 to-0.53,P＜0.05).In terms of improving anxiety symptoms,high-frequency repetitive transcranial magnetic stimulation(SMD=-0.86,95％CI=-1.54 to-0.18,P＜0.05)had the best effect.In terms of improving the quality of life,deep brain stimulation of the globus pallidus(SMD=-0.79,95％CI=-1.55 to-0.04,P＜0.05)had the best efficacy,followed by high-frequency repetitive transcranial magnetic stimulation(SMD=-0.63,95％CI=-0.90 to-0.36,P＜0.05)and transcranial direct current stimulation(SMD=-0.50,95％CI=-0.80 to-0.19,P＜0.05).CONCLUSION:Neuromodulation technology has significant efficacy in improving non-motor symptoms in patients with Parkinson's disease.Transcranial direct current stimulation has the best efficacy in improving sleep disorders,deep electrical stimulation of the medial cerebral part of the globus pallidus has the best efficacy in improving depressive symptoms,high-frequency repetitive transcranial magnetic stimulation has the best efficacy in improving anxiety symptoms,and deep electrical stimulation of the globus pallidus has the best efficacy in improving quality of life.

OBJECTIVE:It has been confirmed that neuromodulation technology can improve the clinical symptoms of patients with Parkinson's disease,and there are differences in the efficacy of different neuromodulation stimulation methods.Herein,a network meta-analysis was used to evaluate the efficacy of different neuromodulation stimulation modalities in improving non-motor symptoms such as sleep disorders and depression and anxiety in patients with Parkinson's disease,thereby exploring the optimal neuromodulation stimulation regimen.METHODS:The Chinese Biomedical Literature Database,WanFang Database,VIP Database,CNKI Database,Web of Science,PubMed,The Cochrane Library,and EMbase databases were searched for randomized controlled trials on neuromodulation techniques to improve sleep disorders,depression and anxiety in patients with Parkinson's disease.The control group was treated with conventional treatments(drugs,conventional rehabilitation therapy,etc.)or sham stimulation,and the experimental group was supplemented with neuromodulation technology on the basis of the control group.The quality of the included studies was evaluated using the PEDro scale and the deviation risk assessment tool recommended by the Cochrane Collaboration.RevMan 5.4 and Stata 17.0 were used for network meta-analysis of the four outcomes(sleep disorders,anxiety symptoms,depressive symptoms,and quality of life).RESULTS:(1)Twenty-nine randomized controlled trials involving six neuromodulation stimulation modalities were included.These modalities were transcranial direct current stimulation,high-frequency repetitive transcranial magnetic stimulation,low-frequency repetitive transcranial magnetic stimulation,deep brain stimulation of the subthalamic nucleus,deep brain stimulation of the globus pallidus,multi-target deep brain stimulation.(2)The results of network meta-analysis showed that compared with conventional treatment,transcranial direct current stimulation[standardized mean difference(SMD)=-2.57,95％confidence interval(CI)=-4.52 to-0.63,P＜0.05)had the best effect in improving sleep disorders in patients with Parkinson's disease.In terms of improving depressive symptoms,deep brain stimulation of the globus pallidus(SMD=-1.00,95％CI=-1.87 to-0.14,P＜0.05)had the best effect,followed by low-frequency repetitive transcranial magnetic stimulation(SMD=-0.91,95％CI=-1.60 to-0.23,P＜0.05),deep brain stimulation of the subthalamic nucleus(SMD=-0.82,95％CI=-1.56 to-0.08,P＜0.05),and high-frequency repetitive transcranial magnetic stimulation(SMD=-0.75,95％CI=-0.97 to-0.53,P＜0.05).In terms of improving anxiety symptoms,high-frequency repetitive transcranial magnetic stimulation(SMD=-0.86,95％CI=-1.54 to-0.18,P＜0.05)had the best effect.In terms of improving the quality of life,deep brain stimulation of the globus pallidus(SMD=-0.79,95％CI=-1.55 to-0.04,P＜0.05)had the best efficacy,followed by high-frequency repetitive transcranial magnetic stimulation(SMD=-0.63,95％CI=-0.90 to-0.36,P＜0.05)and transcranial direct current stimulation(SMD=-0.50,95％CI=-0.80 to-0.19,P＜0.05).CONCLUSION:Neuromodulation technology has significant efficacy in improving non-motor symptoms in patients with Parkinson's disease.Transcranial direct current stimulation has the best efficacy in improving sleep disorders,deep electrical stimulation of the medial cerebral part of the globus pallidus has the best efficacy in improving depressive symptoms,high-frequency repetitive transcranial magnetic stimulation has the best efficacy in improving anxiety symptoms,and deep electrical stimulation of the globus pallidus has the best efficacy in improving quality of life.

OBJECTIVES: Intracranial aneurysm (IA) has an insidious onset, and once ruptured, it carries high rates of mortality and disability. Cardiometabolic factors may be associated with the formation and rupture of IA. This study aims to summarize the application of Mendelian randomization (MR) methods in research on cardiometabolic factors and IA, providing insights for further elucidation of IA etiology and pathogenesis. METHODS: Literature about MR-based IA studies published up to February 21, 2024, was retrieved from PubMed, Embase, Web of Science, CNKI, and Wanfang. Two researchers independently performed literature screening, data extraction, and quality assessment. A narrative synthesis approach was used to conduct a qualitative systematic review of the included studies. RESULTS: A total of 11 MR-based studies on IA published between 2017 to 2024 were included, of which 4 were rated as high quality. These studies investigated the associations between blood pressure, blood lipids, blood glucose, obesity-related indicators, and inflammatory cytokines with IA and its subtypes, though issues of duplication were noted. Four MR studies based on the same European population but using different instrumental variable selection criteria, as well as another MR study in a different European cohort, consistently identified blood pressure as a risk factor for IA and its subtypes. Findings for blood lipids, blood glucose, obesity-related indicators, and inflammatory cytokines were inconsistent across MR studies. CONCLUSIONS Blood pressure appears to increase the risk of IA and its subtypes. Associations between other cardiometabolic factors and IA/subtypes require further in-depth investigation. Given the inherent limitations of MR studies, causal inferences should be made cautiously in combination with other lines of evidence.
Humans ; Mendelian Randomization Analysis ; Intracranial Aneurysm/etiology* ; Risk Factors ; Blood Pressure ; Blood Glucose ; Obesity/complications* ; Cardiometabolic Risk Factors ; Lipids/blood*

Recent studies have indicated that the expression of ubiquitin-specific protease 51 (USP51), a novel deubiquitinating enzyme (DUB) that mediates protein degradation as part of the ubiquitin‒proteasome system (UPS), is associated with tumor progression and therapeutic resistance in multiple malignancies. However, the underlying mechanisms and signaling networks involved in USP51-mediated regulation of malignant phenotypes remain largely unknown. The present study provides evidence of USP51's functions as the prominent DUB in chemoresistant triple-negative breast cancer (TNBC) cells. At the molecular level, ectopic expression of USP51 stabilized the 78 kDa Glucose-Regulated Protein (GRP78) protein through deubiquitination, thereby increasing its expression and localization on the cell surface. Furthermore, the upregulation of cell surface GRP78 increased the activity of ATP binding cassette subfamily B member 1 (ABCB1), the main efflux pump of doxorubicin (DOX), ultimately decreasing its accumulation in TNBC cells and promoting the development of drug resistance both in vitro and in vivo. Clinically, we found significant correlations among USP51, GRP78, and ABCB1 expression in TNBC patients with chemoresistance. Elevated USP51, GRP78, and ABCB1 levels were also strongly associated with a poor patient prognosis. Importantly, we revealed an alternative intervention for specific pharmacological targeting of USP51 for TNBC cell chemosensitization. In conclusion, these findings collectively indicate that the USP51/GRP78/ABCB1 network is a key contributor to the malignant progression and chemotherapeutic resistance of TNBC cells, underscoring the pivotal role of USP51 as a novel therapeutic target for cancer management.

COMPERA 2.0 risk stratification has been demonstrated to be useful in patients with precapillary pulmonary hypertension (PH). However, its suitability for patients at risk for post-capillary PH or PH associated with left heart disease (PH-LHD) is unclear. To investigate the use of COMPERA 2.0 in patients with severe aortic stenosis (SAS) undergoing transcatheter aortic valve replacement (TAVR), who are at risk for post-capillary PH, a total of 327 eligible SAS patients undergoing TAVR at our institution between September 2015 and November 2020 were included in the study. Patients were classified into four strata before and after TAVR using the COMPERA 2.0 risk score. The primary endpoint was all-cause mortality. Survival analysis was performed using Kaplan-Meier curves, log-rank test, and Cox proportional hazards regression model. The study cohort had a median (interquartile range) age of 76 (70‒80) years and a pulmonary arterial systolic pressure of 33 (27‒43) mmHg (1 mmHg=0.133 kPa) before TAVR. The overall mortality was 11.9% during 26 (15‒47) months of follow-up. Before TAVR, cumulative mortality was higher with an increase in the risk stratum level (log-rank, both P<0.001); each increase in the risk stratum level resulted in an increased risk of death (hazard ratio (HR) 2.53, 95% confidential interval (CI) 1.54‒4.18, P<0.001), which was independent of age, sex, estimated glomerular filtration rate (eGFR), hemoglobin, albumin, and valve type (HR 1.76, 95% CI 1.01‒3.07, P=0.047). Similar results were observed at 30 d after TAVR. COMPERA 2.0 can serve as a useful tool for risk stratification in patients with SAS undergoing TAVR, indicating its potential application in the management of PH-LHD. Further validation is needed in patients with confirmed post-capillary PH by right heart catheterization.
Humans ; Aortic Valve Stenosis/complications* ; Aged ; Hypertension, Pulmonary/mortality* ; Male ; Female ; Transcatheter Aortic Valve Replacement ; Aged, 80 and over ; Risk Assessment/methods* ; Proportional Hazards Models ; Kaplan-Meier Estimate ; Retrospective Studies

Clear aligner treatment is a novel technique in current orthodontic practice. Distinct from traditional fixed orthodontic appliances, clear aligners have different material features and biomechanical characteristics and treatment efficiencies, presenting new clinical challenges. Therefore, a comprehensive and systematic description of the key clinical aspects of clear aligner treatment is essential to enhance treatment efficacy and facilitate the advancement and wide adoption of this new technique. This expert consensus discusses case selection and grading of treatment difficulty, principle of clear aligner therapy, clinical procedures and potential complications, which are crucial to the clinical success of clear aligner treatment.
Humans ; Consensus ; Orthodontic Appliance Design ; Orthodontic Appliances, Removable ; Tooth Movement Techniques/methods* ; Malocclusion/therapy* ; Orthodontics, Corrective/instrumentation*

Purpose To explore deep transfer learning(DTL)based on multi-parameter MRI for joint prediction of uterine endometrial cancer microsatellite expression with clinical parameters.Materials and Methods Retrospective analysis was conducted on 262 patients with uterine endometrial cancer in the Affiliated Huaian NO.1 People's Hospital of Nanjing Medical University from January 2020 to December 2022,who were randomly divided into a training cohort(n=183)and a validation cohort(n=79)in a 7∶3 ratio.DTL features were extracted from T2WI and diffusion-weighted imaging(DWI)using a 50-layer residual neural network(ResNet50).Subsequently,T2-net,DWI-net,multi-sequence fusion and a combined model were constructed.A combined model was constructed via incorporating multiparametric fusion DTL features and clinically independent prognostic factors identified through both univariate and multivariate Logistic regression analysis.Model performance was assessed using the area under the curve,calibration curve and decision curve.Grad-CAM was used for model visualization analysis.Results Compared with single-sequence models,the multi-sequence fusion models exhibited superior performance,with area under the curve value of 0.898 for the validation cohort,accuracy of 0.823,sensitivity of 0.812,specificity of 0.825,respectively,and F1 score was 0.650.Univariate and multivariate Logistic regression analyses revealed that serum human epididymis protein 4 levels and the presence of uterine fibroids were clinically independent risk factors.Ultimately,the combined model demonstrated the best predictive performance in the validation cohort,with area under the curve value of 0.924,accuracy of 0.835,sensitivity of 0.875,specificity of 0.825,respectively,and F1 score was 0.683.Conclusion The multi-parameter fusion model based on DTL features can effectively and non-invasively predict the microsatellite status of endometrial cancer patients.