ObjectiveTo evaluate the therapeutic effect of Huazhuo SanJie Chubi presciption （HSCD） on chronic gouty arthritis （CGA） rats with low-grade inflammation and to explore the underlying mechanism with a focus on macrophage polarization. MethodsThe 41 male 6-week-old SD rats were randomly allocated， using the random number table， to a normal group （n=8） and a model group （n =33）. CGA with low-grade inflammation was induced in the model group by daily gavage of potassium oxonate （250 mg·kg^-1·d^-1） and hypoxanthine （300 mg·kg^-1·d^-1）， combined with intra-articular injection of a monosodium urate （MSU） crystal suspension （50 μL， 25 g·L^-¹） into the left ankle twice weekly. After 4 weeks of modeling， 3 rats were randomly selected from each group for model validation. The remaining successfully modeled rats were randomly divided into a model group， an HSCD group （10.35 g·kg^-1·d^-1， gavage once daily）， an M1 polarization agonist group （L-methionine sulfoximine， 300 mg·kg^-1， subcutaneous injection every other day）， an M1 polarization agonist + HSCD group， an M2 polarization inhibitor group （PD0325901， 10 mg·kg^-1·d^-1， gavage once daily）， and M2 polarization inhibitor + HSCD group. The corresponding drug or drug combination was administered according to group assignment， whereas rats in the normal and model groups received 0.5% carboxymethyl cellulose sodium （CMC-Na） vehicle （10.35 g·kg^-1·d^-1， gavage once daily）. All interventions were continued for four weeks. During the intervention period， except for the normal group， potassium oxonate （250 mg·kg⁻¹） and hypoxanthine （300 mg·kg^-1） were co-administered by gavage every other day to maintain the model. At the end of treatment， serum uric acid （SUA）， ankle joint diameter and joint swelling index were measured. The levels of high-sensitivity C-reactive protein （hs-CRP）， interleukin-1β （IL-1β）， interleukin-6 （IL-6）， tumor necrosis factor-α （TNF-α）， chemokine C-C motif ligand 2 （CCL2）， S100 calcium-binding protein A8/A9 （S100A8/A9）， interleukin-10 （IL-10） and arginase-1 （Arg-1） in serum and joint fluid were determined by enzyme-linked immunosorbent assay （ELISA）. High-frequency ultrasound was used to assess MSU deposition in the ankle joint. Hematoxylin-eosin （HE） staining was performed to evaluate synovial histopathological changes. Quantitative Real-time PCR and immunofluorescence were used to detect the mRNA and protein expression of the M1 macrophage polarization markers inducible nitric oxide synthase （iNOS） and the M2 macrophage polarization marker scavenger receptor cysteine-rich type 1 protein M130 （CD163） in synovial tissue. ResultsCompared with the normal group， the model group showed significantly elevated SUA level and joint swelling index， and increased levels of pro-inflammatory cytokines， CCL2， and S100A8/A9 in both serum and joint fluid （P<0.05）， accompanied by MSU deposition and synovial inflammation in the ankle joint. The mRNA and protein expression levels of macrophage polarization M1/M2 markers iNOS and CD163 in synovial tissues were also significantly up-regulated （P<0.05）. Compared with model group， rats in HSCD group had significantly lower SUA levels， attenuated joint swelling， reduced serum levels of pro-inflammatory cytokines， and decreased levels of CCL2 and S100A8/A9 in both serum and joint fluid， accompanied with alleviated MSU deposition and synovial inflammation （P<0.05）. HSCD markedly downregulated the mRNA and protein expression of M1 marker iNOS （P<0.05）， whereas it had no significant effect on the expression of M2 marker CD163. Compared with the M1 polarization agonist group， the M1 polarization agonist + HSCD group showed significantly reduced joint swelling， lower serum levels of pro-inflammatory cytokines， and decreased levels of CCL2 and S100A8/A9 in joint fluid （P<0.05）. In addition， synovial inflammatory cell infiltration and angiogenesis were attenuated， and iNOS mRNA and protein expression levels were significantly reduced （P<0.05）. Compared with the M2 polarization inhibitor group， the M2 polarization inhibitor + HSCD group exhibited reduced joint swelling， decreased levels of CCL2 and S100A8/A9 in joint fluid and ameliorated synovial inflammation （P<0.05）， whereas the levels of anti-inflammatory mediators （IL-10， Arg-1） and CD163 mRNA and protein expression were not significantly increased. ConclusionHSCD alleviates low-grade inflammation in CGA rats， at least in part， by inhibiting macrophage polarization toward the M1 phenotype.

ObjectiveTo construct and validate a risk assessment model for post-transplant diabetes mellitus （PTDM） using multiple machine learning algorithms， and to realize the early identification of PTDM. MethodsA retrospective analysis was performed for the clinical data of the patients who underwent allogeneic liver transplantation in The First Hospital of Shanxi Medical University from April 1， 2020 to December 31， 2024， and they were randomly divided into a training set and a validation set at a ratio of 7∶3. The LASSO regression analysis combined with 5-fold cross-validation was used for feature selection. Seven machine learning models were developed in the training set， i.e.， logistic regression （LR）， decision tree （DT）， Naive Bayes （NB）， random forest （RF）， K-nearest neighbor （KNN）， extreme gradient boosting （XGBoost）， and adaptive boosting （AdaBoost）. In the validation set， various methods were used to assess the predictive performance of each model， such as accuracy， precision， recall rate， specificity， F1 score， area under the receiver operating characteristic curve （AUROC）， and area under the precision-recall curve （AUPRC）. The Brier score and decision curve analysis were used to assess the calibration and clinical practicability of the models， and the SHAP method was used to analyze feature importance. The independent-samples t test or the Wilcoxon rank-sum test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. ResultsA total of 135 liver transplant recipients were enrolled， among whom 26 developed PTDM， and there were 94 patients in the training set and 41 in the validation set. Feature extraction and screening identified 7 key features of sex， overweight or obesity， anhepatic phase， time of operation， length of hospital stay， early postoperative hypomagnesemia， and impaired fasting glucose （IFG）. In the validation set， the XGBoost model showed the best predictive performance， with an AUROC of 0.907 （95% confidence interval ［CI］： 0.807 — 0.989）， an AUPRC of 0.649 （95%CI： 0.339 — 0.955）， an accuracy of 0.878， a precision of 0.667， a recall rate of 0.750， an F1-score of 0.706， a specificity of 0.909， and a Brier score of 0.104. The decision curve analysis showed that when the threshold probability was below 0.667， application of the XGBoost model in clinical decision-making provided relatively high net benefit. The SHAP analysis showed that the length of hospital stay ranked first in terms of feature importance， followed by time of operation， overweight or obesity， sex， IFG， anhepatic phase， and early postoperative hypomagnesemia. ConclusionThe risk assessment model for PTDM in liver transplant recipients based on XGBoost algorithm has excellent performance and can effectively identify high-risk individuals； however， multicenter large-sample data are needed for further validation.

Objective To investigate the relationship between ST-segment elevation myocardial infarction(STEMI)treatment time nodes and coronary microcirculation dysfunction(CMD)after primary percutaneous coronary intervention(PCI)and its prognosis,providing evidence for early identification of high-risk patients,further optimization of treatment system,shortening treatment time and improving prognosis.Methods This study selected 150 STEMI patients who received primary PCI at the 920th Hospital of the Joint Logistic Support Force of the People's Liberation Army of China from March 2023 to September 2023 as the CMD group after PCI(89 cases),with a microcirculation resistance index(caIMR)of≥40 U based on coronary angiography.caIMR＜40 U was classified as the non-CMD group(61 cases).The clinical data,various examination indicators and imaging data of the two groups of patients were collected,and the occurrence of major adverse cardiovascular events(MACE)within half a year after direct PCI of the patients was followed up.The correlation between the two variables was analyzed using Spearman.Multivariate Logistic regression was used to analyze the relationship between each treatment time point and the occurrence of CMD after direct PCI.Using receiver operating characteristic(ROC)curve analysis to predict the occurrence of CMD after direct PCI.The survival curves between the two groups were plotted using the Kaplan-Meier method.Results The levels of symptom onset-to-balloon(S-to-B),symptom onset-to-first medical contact(S-to-FMC),first medical contact-to-balloon(FMC-to-B),symptom onset-to-door(S-to-D)and first medical contact-to-door(FMC-to-D)in the CMD group were significantly higher than those in the non-CMD group(all P＜0.05).Correlation analysis showed that S-to-D,S-to-FMC,the time from FMC-to-B,and the time from FMC-to-D were all positively correlated with the time from S-to-B(r=0.996,P＜0.001;r=0.937,P＜0.001;r=0.431,P＜0.001;r=0.441,P＜0.001).Multivariate Logistic regression analysis indicated that the duration of S-to-D(OR 2.165,95％CI 1.655-2.830,P＜0.001)was a significant influencing factor for CMD.Moreover,S-to-D has a relatively high predictive value for the occurrence of CMD after direct PCI.The area under the ROC curve is 0.898(95％CI 0.850-0.946,P＜0.001),the optimal cut-off value is 231 min,the sensitivity is 82.0％,and the specificity is 88.5％.Kaplan-Meier curve analysis showed that the cumulative survival rate of MACE outcomes in the CMD group was significantly lower than that in the non-CMD group(Log-rank P=0.009).Conclusions Shortening the S-to-D time can reduce the occurrence of CMD after PCI,thereby reducing the incidence of MACE and improving prognosis.

Objective To estimate the prevalence of calcified nodule(CN)among patients with coronary artery disease(CAD)and identify the possible risk factors associated with an increased CN risk.Methods Databases include PubMed,Web of Science and Embase was conducted to identify studies reporting the prevalence and/or risk factors of CN.For this databases,the search was from inception to January 1,2024.Data analyses was performed using R statistical Software 4.2.2.Results A total of 46 studies involving 17 926 patients were included.Among them,13 studies with 4 187 patients reported both the prevalence and associated risk factors.The overall prevalence of CN was found to be 5.72％(95％CI 4.47％-7.31％),while in studies reporting both the prevalence and risk factors,the CN prevalence was slightly higher at 8.72％(95％CI 6.43％-11.71％).Hypertension(OR 1.75,95％CI 1.29-2.37),diabetes(OR 1.84,95％CI 1.46-2.33),chronic kidney disease(OR 2.50,95％CI 1.67-3.74),and hemodialysis(OR 7.77,95％CI 4.77-12.67)were associated with an elevated CN risk(all P＜0.001).Conversely,obesity(OR 0.39,95％CI 0.18-0.83)and history of smoking(OR 0.61,95％CI 0.47-0.80)were linked to a decreased CN risk(both P＜0.05).Conclusions The overall prevalence of CN is relatively low among patients with CAD.However,the prevalence of CN is influenced by a variety of clinical factors.Further research is warranted to elucidate the underlying mechanisms.

Aim To explore the potential mechanism of metformin on ATP-binding cassette transport A1(ABCA1)expression.Methods J774A.1 macrophages were treated with metformin and cycloheximide,and ABCA1 expression was determined by Western blot.His-tagged ABCA1 and HA-tagged Ub plasmids were co-transferred into HEK293 cells and stimulated with metformin.Co-immunoprecipitation(Co-IP)was used to test the binding ability of ABCA1 and ubiquitin.Candidate E3 ubiquitin-protein ligases(CE3)of ABCA1 were identified through Co-IP-based pro-teomics.The MIB1 plasmid was constructed and transferred into HEK293 cells,and Western blot was used to determine the effect of metformin and MIB1 on ABCA1 expression.Results Metformin increased the expression of ABCA1 in J774A.1 cells(P<0.01),and inhibited ABCA1 degradation(P<0.05).Metformin disrupted the binding of ABCA1 to ubiquitin(P<0.05).The proteins regulated by metformin in ABCA1 expression were primarily enriched in pathways re-lated to cell development,inflammation and immune defense.Metformin may upregulate ABCA1 protein expression via MIB1(P<0.05).Conclusion Metformin inhibits the degradation of ABCA1 by blocking the ubiquitin-proteasome system(UPS),and MIB1 might act as a candidate E3 ubiquitin-protein ligase(CE3)for ABCA1.

This consensus was developed by the Orthodontic Society of the Chinese Stomatological Association to provide a systematic, scientific, and practical guideline for informed consent in orthodontic care. Orthodontic treatment is typically lengthy, highly individualized, and involves multiple factors such as growth and development, occlusal function, and facial esthetics. Rapid technological advances and diverse risk profiles make the traditional reliance on orthodontist experience or institutional templates insufficient to ensure patients′ full understanding and autonomous decision-making. To address this, the expert panel conducted extensive reviews of domestic and international guidelines, analyzed representative dispute cases, and performed multicenter patient-clinician surveys. Using a multi-round Delphi method, the group established a standardized informed consent framework covering the initial consultation, treatment, and retention phases. The consensus emphasizes that informed consent is not only a fundamental legal and ethical requirement but also a key step in building trust, improving patient compliance, and enhancing treatment satisfaction. Orthodontists should clearly and comprehensively explain treatment plans, potential risks, uncertainties, and associated costs, while respecting the autonomy of patients or guardians, and maintain continuous communication and dynamic evaluation throughout the treatment process. The release of this consensus provides unified and authoritative guidance for clinical orthodontics, helping to standardize informed consent, enhance its transparency, safeguard patient rights, reduce medical risks, and promote high-quality, sustainable development of orthodontic practice.

To investigate the molecular mechanisms underlying the mechanosensitive ion channel PI-EZO2 in osteoarthritis(OA),we developed a lentiviral vector for endogenous PIEZO2 overexpression and established a stable PIEZO2-high-expressing immortalized human primary chondrocyte line.By map-ping the open reading frame of the PIEZO2 locus and designing sequence-specific sgRNA,we employed the CRISPR/Cas9 synergistic activation mediator(SAM)system to precisely integrate transcriptional ac-tivation elements into the PIEZO2 promoter region.Lentiviral-mediated targeted genomic integration en-sured endogenous PIEZO2 overexpression,confirmed by mCherry fluorescence tracing coupled with flow cytometric sorting,which revealed membrane-specific localization of PIEZO2 protein(localization effi-ciency:78.49％).Quantitative PCR demonstrated a 17-fold upregulation of PIEZO2 mRNA,while Western blotting validated enhanced membrane-localized protein expression.Strikingly,PIEZO2-overex-pressing chondrocytes exhibited hallmark OA metabolic phenotypes compared to wild-type controls:typeⅡ collagen mRNA expression decreased to 50％of baseline levels,whereas matrix metalloproteinase 13(MMP13)mRNA surged by 20-fold.These alterations recapitulated the pathological matrix metabolic phenotype observed in biomechanical OA models induced by cyclic mechanical stress(10％strain,0.5 Hz,8 h/day for 2 consecutive days).Collectively,we successfully generated a human chondrocyte model with stable PIEZO2 overexpression,which faithfully mirrors mechanotransduction-driven OA progression.This engineered cellular system provides a robust platform for dissecting PIEZO2-mediated mechanosig-naling networks and advancing targeted therapeutic discovery.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

The key role of the path planning technology for guide robots of the blind was introduced.The current research status of path planning algorithms based on traditional algorithms and intelligent algorithms was reviewed,involving in their advantages,disadvantages and application scopes and scenarios.The application of fusion algorithms in the path planning of guide robots for the blind was discussed,the challenges of the path planning algorithms of guide robots for the blind were analyzed,and its future development directions were pointed out.[Chinese Medical Equipment Journal,2025,46(2):92-101]