ObjectiveTo investigate the value of predictive models established based on machine learning methods in predicting the risk of metabolic associated fatty liver disease （MAFLD）， and to analyze its key risk factors. MethodsA retrospective analysis was performed for the 50 variables of 2 168 healthy individuals who underwent physical examination in Department of Health Assessment， Xiyuan Hospital， China Academy of Chinese Medical Sciences， from January 2021 to December 2024， including body composition， past history， and laboratory tests， and according to whether they were diagnosed with MAFLD or not， they were divided into MAFLD group with 265 individuals and non-MAFLD group with 1 903 individuals. The Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. Randomly split the research data into a training set and a validation set in a 70% to 30% ratio. Predictive factors were screened from the training set data using univariate analysis， LASSO regression， and multivariate Logistic regression analysis. Predictive models were then constructed using seven machine learning methods： Logistic regression， decision tree， random forest （RF）， eXtreme gradient boosting， light gradient boosting machine， support vector machine， and artificial neural network. Model performance was evaluated by plotting receiver operating characteristic curve for the validation set and calculating the area under the curve （AUC）， sensitivity， specificity， and Youden index for each model. Furthermore， the SHapley Additive exPlanation （SHAP） method was used to analyze the contribution of variables in the optimal model. ResultsThe prevalence rate of MAFLD among the 2 168 subjects was 12.22% （265/2 168）. Smoking， diastolic blood pressure， phase angle， visceral fat area， muscle fat ratio， waist-to-hip ratio， aspartate aminotransferase， non-HDL-C/HDL-C ratio， triglyceride-glucose index， and gallstones were independent risk factors for MAFLD （all P<0.05）. The seven predictive models of support vector machine， eXtreme gradient boosting， decision tree， light gradient boosting machine， artificial neural network， RF， and Logistic regression had an AUC of 0.738， 0.754， 0.757， 0.786， 0.795， 0.796， and 0.815， respectively， in the validation set， among which the RF model had the best discriminatory ability （AUC=0.796， 95% confidence interval： 0.754 — 0.839）， with a sensitivity of 81.01%， a specificity of 63.16%， and a Youden index of 44.17%. The SHAP analysis showed that visceral fat area， waist-to-hip ratio， and diastolic blood pressure were the top three predictive factors in terms of importance. ConclusionThe RF model， constructed based on body composition and clinical indicators， has a good performance in predicting the risk of MAFLD， and its interpretability can help to identify high-risk individuals in the early stage in clinical practice.

ObjectiveColorectal cancer (CRC) is a highly heterogeneous malignancy, and traditional Chinese medicine (TCM) syndrome differentiation is widely used in its clinical management. However, the biological basis underlying different TCM syndromes remains insufficiently understood. This study aimed to investigate the proteomic differences between qi-blood deficiency syndrome (QBDS) and damp-heat syndrome (DHS) in CRC patients and to establish a “syndrome-differential protein-herbal component” network for exploring potential molecular mechanisms and therapeutic targets associated with syndrome-specific treatment strategies. MethodsTumor tissue samples were collected from 10 patients with pathologically confirmed CRC, including 5 patients diagnosed with QBDS and 5 with DHS according to standardized TCM syndrome differentiation criteria. Tandem mass tag (TMT)-based quantitative proteomics was employed to identify differentially expressed proteins (DEPs) between the two syndrome groups. Functional enrichment analyses, including Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, were performed to characterize the biological functions and signaling pathways associated with the identified DEPs. Least absolute shrinkage and selection operator (LASSO) regression analysis was further applied to screen key syndrome-related proteins and construct a core protein prediction model. Subsequently, molecular docking was conducted to evaluate the binding affinities between representative herbal compounds, astragaloside IV and berberine, and the identified core proteins. Finally, cell counting kit-8 (CCK-8) assays were performed in HCT 116 and HT-29 colorectal cancer cell lines to validate the anti-proliferative activities of these compounds in vitro. ResultsA total of 44 DEPs were identified between QBDS and DHS tissues, including 21 upregulated and 23 downregulated proteins in the QBDS group relative to the DHS group. Functional enrichment analyses revealed that these proteins were primarily associated with antiviral immune responses, regulation of inflammatory signaling, NF‑κB signaling pathways, cholesterol metabolism, and other biological processes relevant to tumor progression and host immune regulation. LASSO regression analysis identified eight core proteins with potential syndrome-specific significance. Among them, ST7, GPCPD1, and PODXL were closely associated with QBDS, whereas FAT1, GRB7, KRT7, MAFF, and MMP8 were associated with DHS. Molecular docking demonstrated favorable interactions between astragaloside IV and QBDS-related proteins, with binding energies lower than -5 kcal/mol, indicating stable binding activity. Berberine exhibited even lower binding energies and stronger binding specificity toward DHS-related core proteins. In vitro experiments further confirmed that both compounds inhibited CRC cell proliferation, while berberine displayed significantly greater anti-proliferative efficacy. The lowest 48 h IC₅₀ value of berberine reached 15.21 mg/L in CRC cells, indicating a stronger growth-inhibitory effect than astragaloside IV. ConclusionCRC patients with QBDS and DHS exhibit distinct proteomic characteristics, suggesting that different TCM syndromes possess unique molecular signatures. The identified core proteins may serve as potential biomarkers for syndrome differentiation, while astragaloside IV and berberine may exert therapeutic effects through targeting syndrome-specific molecular networks. These findings provide preliminary proteomic evidence supporting syndrome-guided precision integrative medicine in CRC and offer new insights into the biological basis of TCM syndrome differentiation and individualized therapeutic strategies.

Obesity is a chronic low-grade inflammation and a risk factor for diseases such as diabetes， hypertension， dyslipidemia， and malignant tumors， demonstrating an increasingly grim development situation. The nuclear factor-kappa B （NF-κB） signaling pathway is a key signaling pathway involved in the immune response and inflammatory response. In obese individuals， the expression of NF-κB is overactivated， which leads to abnormal inflammatory responses in the body. Therefore， it is expected to alleviate inflammation and treat obesity by regulating the NF-κB signaling pathway， which has been proven effective by a large number of studies. The available studies on the NF-κB signaling pathway mostly focus on tumors， and there is no systematic review of the mechanism of this pathway in mediating obesity and the traditional Chinese medicine （TCM） treatment. We reviewed the research progress in the pathological and physiological processes of obesity mediated by NF-κB signaling pathway and TCM treatment， aiming to give insights into the clinical treatment of obesity with TCM and provide reference targets and research directions for exploring the biological foundations and the development of new TCM preparations.

[Objective] To explore the predictive value of HALP score for prognosis in patients with multiple myeloma (MM). [Methods] A retrospective analysis was conducted on laboratory indicators and related clinical data of newly diagnosed multiple myeloma (NDMM) patients, treated at the Affiliated Hospital of North Sichuan Medical College from January 2016 to October 2023, prior to their first treatment. The HALP score was calculated, and the optimal cutoff value for HALP was determined using X-tile software. Survival analysis was performed using Kaplan-Meier curves for high HALP and low HALP groups. Univariate and multivariate analyses were conducted using the Cox regression model, and a forest plot was generated using Graphpad Prism to illustrate factors that may impact patient prognosis. The predictive ability of HALP score combined with β2-microglobulin and ECOG score for prognosis in MM patients was evaluated using receiver operating characteristic curve (ROC) analysis. [Results] A total of 203 MM patients were included, with the optimal cutoff value for HALP score being 29.15 (P<0.05). Among them, 101 patients were in the low HALP score group, and 102 patients were in the high HALP score group. The results of univariate and multivariate analysis using the Cox regression model showed that a HALP score <29.15 was an independent risk factor for progression-free survival (PFS) and overall survival (OS) (P<0.05). ROC curve analysis indicated that the combination of HALP score with β2-microglobulin and ECOG score had a higher predictive value for prognosis in MM patients compared to using HALP score alone. [Conclusion] The HALP score is closely related to the prognosis of patients with NDMM. A low HALP score indicates a poorer prognosis, while the combination of HALP score with β2-microglobulin and ECOG score provides a higher predictive value when assessed together.

Medication reconciliation plays a key role in improving patient medication safety,reducing inappropriate polypharmacy,and promoting the high-quality development of pharmaceutical services.Compared to advanced international guidelines,China's medication reconciliation service standards have deficiencies in areas such as definition and process design,and multidisciplinary team building.There is a need to establish a comprehensive medication reconciliation effect evaluation index system,develop pharmacist-led multidisciplinary teams,promote the advancement of artificial intelligence and big data technologies,and strengthen outpatient and community medication reconciliation coverage,thereby contributing to the high-quality development of pharmaceutical services in China.

Objective:To explore the impact of residents′ health literacy on healthcare choices.Methods:This mixed cross-sectional study utilized data from the 2009, 2011, and 2015 waves of the China Health and Nutrition Survey (CHNS), including adults aged≥18 years. Guided by Andersen′s Behavioral Model of Health Services Use and the Knowledge-Attitude-Practice (KAP) framework, variables were collected across three dimensions-predisposing, enabling, and need factors-including gender, marital status, age, education level, employment status, urban/rural residence, health management awareness, income, health insurance coverage, self-rated health, and chronic disease status. A multinomial Logistic regression model was applied to assess the association between health literacy and healthcare choice. Bootstrap analysis was conducted to test the mediating effect of health management awareness.Results:After excluding cases with missing or invalid data, 4 736 valid observations were included. The proportions of choosing township-, county-, and city-level hospitals were 60.60%, 15.08%, and 24.32%, respectively. After adjusting for confounders, health literacy showed a significant effect on healthcare choice ( P<0.05): individuals with higher health literacy were more likely to choose county-level hospitals ( RR=1.035, P<0.05) and city-level hospitals ( RR=1.044, P<0.01). Health management awareness mediated the relationship between health literacy and healthcare choice ( P<0.05). Conclusions:Health literacy significantly influences healthcare choices; individuals with higher health literacy are more inclined to utilize higher-level medical institutions. Furthermore, health literacy affects healthcare choices partly through the mediating role of health management awareness.

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.

Background and aims:Liver fibrosis is a prevalent pathological stage of various chronic liver diseases and has the potential to progress to liver cirrhosis and hepatocellular carcinoma.However,experimental models for in vivo research are limited.Unexpectedly,increased liver inflammation and fibrosis were previously observed in mice treated with aluminum adjuvant(commercial Imject Alum,a mixture of Al(OH)3 and Mg(OH)2).Our study aimed to reveal the pathogenesis and pathological features of Imject Alum-induced liver injury and evaluate its potential as an experimental model of fibrotic liver disease.Methods and materials:C57BL/6J mice were randomly divided into the following four groups:(ⅰ)control group,which received phosphate-buffered saline injections on days 1,12,26,40,and 54;(ⅱ)Imject Alum(Al(OH)3 160 mg/kg)D26 group,which was administered with Imject Alum(Al(OH)3 160 mg/kg)on days 1,12,and 26;(ⅲ)Imject Alum(Al(OH)3 80 mg/kg)D54;and(ⅳ)Imject Alum(Al(OH)3 160 mg/kg)D54 groups,which were treated with 80 mg/kg and 160 mg/kg of Imject Alum(Al(OH)3),respectively,on days 1,12,26,40,and 54.All reagents were delivered by intraperitoneal injection.Serum biochemical pa-rameters,liver pathology,and expression of genes related to inflammation and fibrogenesis were eval-uated.Transcriptome sequencing was performed.The genetic characteristics of the Imject Alum-induced liver lesions in the existing fibrosis model and patients with cirrhosis were determined.Results:Administration of Imject Alum(Al(OH)3 160 mg/kg)at certain points for 54 days led to extensive hepatic inflammation and fibrosis,accompanied by disturbed bile acid metabolism in mice.Moreover,Imject Alum aggravated liver inflammation and injury by activating the pyroptosis-related inflamma-some pathway.Transcriptome analysis revealed that Imject Alum-induced liver lesions had differentially expressed genes that were significantly enriched in pathways related to inflammation,fibrogenesis,and multiple metabolic processes.Moreover,Imject Alum-induced liver lesions exhibited gene signatures similar to those of existing fibrosis models and patients with cirrhosis.Conclusions:Aluminum adjuvant(Imject Alum;Al(OH)3 160 mg/kg)administration at certain points for 54 days resulted in notable liver injury,inflammation,and fibrosis.This model had similar gene expression characteristics with existing fibrosis models and liver samples from patients with cirrhosis.Overall,aluminum adjuvant(Imject Alum)-induced mouse model may be a novel approach for estab-lishing a liver fibrosis animal model.

Objective Aedes albopictus is the primary vector of the dengue virus.Screening and the analysis of immune-related genes in DENV2-infected Ae.albopictus provides a scientific basis for further research on blocking the extrinsic incubation period of the dengue virus.Methods Through the approach of literature mining,thirty-three potential immune-related genes were screened from species such as Aedes aegypti and Anopheles gambiae,which have a close genetic relationship with Ae.albopictus.The protein—protein interaction(PPI)analysis is employed to explore the interaction relationship of the proteins encoded by genes.The alterations in mRNA expression levels of the relevant genes in DENV2-infected Ae.albopictus midgut were detected using the qRT-PCR method.Results The PPI results indicates that TLR and Spz of Ae.albopictus;Rel1,Rel2,DefC,Spz,PIWI,Ago2,DOME and HOP of Ae.aegypti;and Rel1,Rel2,CACT,STAT and DOME of An.gambiae exhibit PPI relationships.After Ae.albopictus was infected with DENV2,10 genes showed significant difference in expression.Ago3(7.39,P<0.05),DOMEa(1.63,P<0.01),DOMEb(21.29,P<0.001),and TLRb(1.61,P<0.05)were significantly up-regulated.Rel1(0.62,P<0.001),CACTl(0.65,P<0.001),Rel2a(0.65,P<0.01),Rel2b(0.24,P<0.001),GATAa(0.64,P<0.01)and DefC(0.28,P<0.05)were significantly down-regulated.Conclusions The concordance of Ae.albopictus with Ae.aegypti was higher than that with An.gambiae.DOMEb,Ago3,Rel2b and DefC,can serve as the preferred target genes for subsequent studies on DENV2 immune blockade.

The morphological characteristics of hepatocellular carcinoma(HCC)tumor margins are pivotal in influencing patient's prognosis and the selection of therapeutic strategies.This paper re-viewed the classification methods of HCC tumor margins,ranging from traditional macroscopic classifi-cations to refined classification systems based on multi-omics analysis,and analyzed the role of these classification methods in guiding the formulation of personalized treatment plans.Additionally,this paper emphasized the crucial role of three-dimensional imaging techniques in assessing tumor margin morphology and outlined future research directions,including validating the effectiveness of multi-omics classification systems and developing new imaging and molecular biomarkers to achieve more precise treatment plans and prolong patient survival.