Childhood simple obesity has become a significant public health issue in China. Modern medicine primarily relies on lifestyle interventions and often suffers from poor long-term compliance， while pharmacological options are limited and associated with potential adverse effects. Traditional Chinese Medicine （TCM） has a long history in the prevention and management of this condition， demonstrating eight distinct advantages， including systematic theoretical foundation， diversified therapeutic approaches， definite therapeutic efficacy， high safety profile， good patient compliance， comprehensive intervention strategies， emphasis on prevention， and stepwise treatment protocols. Additionally， TCM is characterized by six distinctive features： the use of natural medicinal substances， non-invasive external therapies， integration of medicinal dietetics， simple exercise regimens， precise syndrome differentiation， and diverse dosage forms. By combining internal and external treatments， TCM facilitates individualized regimen adjustment and holistic regulation， demonstrating remarkable effects in improving obesity-related metabolic indicators， regulating constitutional imbalance， and promoting healthy behaviors. However， challenges remain， such as inconsistent operational standards， insufficient high-quality clinical evidence， and a gap between basic research and clinical application. Future efforts should focus on accelerating the standardization of TCM diagnosis and treatment， conducting multicenter randomized controlled trials， and fostering interdisciplinary integration， so as to enhance the scientific validity and international recognition of TCM in the prevention and treatment of childhood obesity.

Digital and intelligent technologies serve as the core engine driving the inheritance of the essence and the innovation while upholding the fundamentals of traditional Chinese medicine（TCM）. Currently， the digital and intelligent transformation of TCM has undergone four developmental stages， exhibiting inherent characteristics such as long-term inevitability， objective standardization， and ecological evolution. By introducing quantitative metrics， digital and intelligent technologies have achieved breakthroughs in TCM knowledge inheritance and innovation， clinical diagnosis and treatment， and herbal medicine supply. The practical applicability of methodological innovations has been empirically validated， though significant disparities exist in technological adaptability and application depth across different fields. Overall， the digital and intelligent transformation of TCM remains in its nascent stage， grappling with multiple structural challenges：weak data foundations， inadequate technological adaptability， incomplete institutional frameworks， shortages of multidisciplinary talent， lagging policies and regulations， and urban-rural digital divide. In order to foster sustainable development and modernization of TCM， this paper establishes a six-dimensional collaborative governance framework of encompassing data， technology， organization， institutions， environment and ethics， which is rooted in data governance and digital governance theories. Future efforts should center on standardization， integration， and ecosystem development to build a data and technology foundation. Focus should be placed on deepening innovation and application of key TCM-specific technologies， while simultaneously strengthening interdisciplinary talent cultivation， improving institutional mechanisms and policy frameworks， and increasing support for rural areas. By adopting a people-centered and technology-empowered approach， we can overcome developmental constraints and unleash the powerful driving force of digital and intelligent technologies for the inheritance of TCM.

ObjectiveTo analyze the infection status of main respiratory pathogens in influenza-like illness (ILI) cases in Anji County, Huzhou City, Zhejiang Province, and to provide a reference for the prevention, diagnosis, and treatment of respiratory infections. MethodsThroat swab samples were collected from 520 ILI cases in an influenza sentinel surveillance hospital in Anji County of Zhejiang Province from December 2023 to November 2024. Multiplex real-time fluorescence quantitative polymerase chain reaction (mRT-PCR) was used to detect 18 pathogens and their subtypes, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A virus (Flu A), influenza A (H1N1) virus, influenza A (H3N2) virus, influenza B virus (Flu B), influenza B virus Victoria lineage (BV), influenza B virus Yamagata lineage (BY), coronavirus (CoV), human parainfluenza virus (HPIV), respiratory syncytial virus (RSV), human metapneumovirus (HMPV), adenovirus (ADV), human bocavirus (HBoV), enterovirus (EV), rhinovirus (RV), Mycoplasma pneumoniae (MP), Chlamydia pneumoniae (CP), and Streptococcus pneumoniae (SP). ResultsThe overall positivity rate of pathogens in 520 samples was 33.65%, among which the detection rates of Flu (9.14%), ADV (7.50%), SARS-CoV-2 (6.15%), and EV (3.65%) were relatively high. There were statistically significant differences in the overall positivity rate of pathogens by age and season (all P<0.05). The highest overall positivity rate was observed in the 5‒14 years old group (42.77%), and the overall positivity rate in winter (53.08%) was significantly higher than that in other seasons. ConclusionFrom 2023 to 2024, the main respiratory pathogens detected in ILI cases in Anji County were Flu, ADV, SARS-CoV-2, and EV. The epidemic characteristics showed age and seasonal specificity, so it is necessary to strengthen prevention and control for high-risk populations and epidemic seasons in a targeted manner.

Objective: To investigate the incidence, characteristics, and influencing factors of resolution discrepancies within the minipool (MP) testing model across Chinese blood station laboratories in 2024. Methods: A nationwide, multicenter, cross-sectional study was conducted, including 334 blood station laboratories that reported nucleic acid reactive data among enzyme immunoassay non-reactive samples. Of these, 296 laboratories adopted the pool resolution model, with a total of 12 536 273 samples tested. Systematic analysis was performed on resolution data, focusing on the MP-NAT reactivity rate, the pool resolution concordance rate, and the resolution discrepancy rate. Subgroup analyses were conducted based on reagent types, viral targets, and Ct values. Potential causes were further explored through laboratory surveys and re-examination of raw amplification curves. Results: In 2024, the national average MP-NAT reactivity rate was 0.15%. The overall pool resolution concordance rate was 57.86%, which showed a gradual decline as Ct values increased across all reagents. The national average resolution discrepancy rate was 0.081‱(102/12 536 273), with 17.91%(53/296) of laboratories reporting at least one discrepancy. Nine reagent types were associated with these events, exhibiting reagent-specific patterns. For Reagent A2, the predominant discrepancy was HBV reactive pools resolving as HIV (36.36%); for Reagent D1, HBV pools frequently resolved as HCV (38.89%); and for Reagent E, the most common pattern was HIV pools resolving as HBV (48.00%). These resolution discrepancies were strongly associated with high Ct values: the median pool Ct for HBV exceeded 38, while those for HCV and HIV both exceeded 40. Investigations across 16 laboratories revealed that most discrepant samples exhibited “tailing” amplification curves, with some cases linked to cross-contamination or reagent batch-specific issues. Conclusion: While the incidence of resolution discrepancies in the MP-NAT model remains low in China, variations exist across different reagents and laboratories. These discrepancies are closely associated with low viral load, reagent performance, and laboratory operational practices.

ObjectiveTo construct a nomogram prediction model for non-valvular persistent atrial fibrillation （PeAF） patients with left ventricular hypertrophy （LVH） ， followed by prognostic analysis through follow-up. MethodsThis study retrospectively enrolled 949 patients with newly diagnosed and hospitalized non-valvular PeAF. Among them， 403 patients presented with LVH. The cohort was randomly stratified into a training set （n=665） and a validation set （n=284）. Univariate and multivariate Logistic regression analyses were employed to identify independent risk factors for PeAF complicated by LVH. A nomogram prediction model was subsequently constructed and evaluated for discriminative ability， calibration， and clinical utility using receiver operating characteristic （ROC） curve analysis， calibration plots， and decision curve analysis （DCA）. ResultsSeven independent risk factors were ultimately identified and included in the prediction model： female sex， hypertension， diabetes， red blood cell distribution width-SD （RDW-SD）， body mass index （BMI）， left atrial diameter （LAD）， and left ventricular ejection fraction （LVEF）. The area under the ROC curve （AUC） in the training set was 0.862 （95% CI： 0.834-0.890）， and in the validation set， it was 0.870 （95% CI： 0.829-0.911）， demonstrating excellent predictive performance. ConclusionIndependent risk factors for LVH in PeAF patients include female， hypertension， diabetes， RDW-SD， BMI， LAD， and LVEF. The prediction model built based on this can help early identification of PeAF patients with high risk of LVH. At the same time， the incidence of major adverse cardiovascular events （MACE） is higher in PeAF patients with LVH. Patients with atrial fibrillation combined with LVH may benefit from catheter ablation.

OBJECTIVE To explore the antidepressant mechanism of Wenyang jieyu granules （WYJYG） via the NOD-like receptor thermal protein domain associated protein 3 （NLRP3）/apoptosis-associated speck-like protein containing a CARD （ASC）/Caspase-1 pathway. METHODS A rat model of depression was established by chronic unpredictable mild stress combined with single-housing for 42 consecutive days.The experiment set up blank group， model group， MCC950 （NLRP3 inflammasome inhibitor） group （10 mg/kg）， fluoxetine group （positive control，2.08 mg/kg），low-dose WYJYG（3.78 g/kg） and high-dose WYJYG group （7.56 g/kg），with 10 rats in each group. From the 22nd day of the experiment， rats in the fluoxetine group， low-dose and high-dose WYJYG groups were intragastrically administered with the corresponding drugs and intraperitoneally injected with an equal volume of normal saline. Rats in the MCC950 group were intraperitoneally injected with MCC950 at the corresponding concentration and intragastrically administered with an equal volume of distilled water. Rats in the blank group and model group were given an equal volume of distilled water by gavage and an equal volume of normal saline by intraperitoneal injection. All interventions were performed once a day for 21 consecutive days. Behavioral tests were conducted once a week. After the last administration， the contents of ASC， ionized calcium binding adaptor molecule 1 （Iba1）， interleukin-1β （IL-1β）， and IL-18 in hippocampal tissues were detected. The protein expressions of NLRP3， cluster of differentiation 68 （CD68）， Caspase-1， B-cell lymphoma-2 （Bcl-2）， and Bcl-2-associated X protein were determined， and neuronal apoptosis was observed. RESULTS After the last administration， compared with the model group， the open-field activity time was significantly prolonged （ P ＜0.05）， and the latency to feed in a novel environment was significantly shortened （ P ＜0.05） in rats of the high-dose WYJYG group. In hippocampal tissue， the contents of ASC， Iba1， IL-1β， and IL-18， as well as the protein expression levels of NLRP3， Caspase-1， and CD68， and the positive rate of neuronal apoptosis were all significantly decreased/downregulated （ P ＜0.05）. Bcl-2 protein expression was significantly upregulated （ P ＜0.05）， and the density of neuronal apoptosis-positive cells was significantly reduced （ P ＜0.05）. CONCLUSIONS WYJYG play on antidepressant role by inhibiting the NLRP3/ASC/Caspase-1 pathway， reducing microglia-mediated neuroinflammation， and inhibiting hippocampal neurons apoptosis.

Background/Aims: Dysregulated cholesterol metabolism is a hallmark of hepatocellular carcinoma (HCC) that drives tumor initiation and progression. However, clinical targeting of cholesterol metabolism has yielded limited benefits due to stringent feedback in tumor cells. Identifying a central mediator capable of restoring cholesterol homeostasis within the cell’s intrinsically fine-tuned regulatory framework is urgently needed. Methods: We integrated a proteomic dataset from patients with cholesterol-dysregulated HCC into a global cholesterol metabolic regulatory network to identify potential therapeutic targets for disrupted cholesterol homeostasis. The prognostic significance of the candidate targets was further validated in an independent cohort through immunohistochemistry. Functional and mechanistic studies were conducted in vitro using HCC cell lines and in vivo using mouse models. The pharmacological efficacy of the candidate agent was evaluated in both subcutaneous and orthotopic HCC mouse models. Results: ER lipid raft-associated 1 (ERLIN1), a pivotal regulator of cholesterol metabolism reprogramming, was identified as an independent favorable prognostic indicator in HCC. ERLIN1 constrains HCC progression both in vitro and in vivo by stabilizing the INSIG1–SCAP–SREBP2 axis and maintaining the metabolic balance of intracellular cholesterol. Under hypoxia, impaired factor-inhibiting hypoxia-1-dependent hydroxylation of ASB11 at asparagine residues 90 and 92 enhances ASB11-mediated ERLIN1 degradation. Pharmacological targeting of this axis using zoledronic acid (ZoA) attenuated HCC progression by weakening the ASB11–ERLIN1 interaction and restoring cholesterol homeostasis. Conclusions ERLIN1 represents a druggable metabolic vulnerability in cholesterol-dysregulated HCC. Targeting the ASB11–ERLIN1 axis with the clinically approved ZoA reestablishes cholesterol homeostasis and offers a promising therapeutic strategy to overcome the current limitations of cholesterol-targeted HCC therapies.

ObjectiveTo evaluate the application effect of morphology driven preparation technique in indirect restoration of posterior teeth. Methods84 patients with dental defects were selected and divided into the control group and the experimental group randomly， with 42 patients in each group （a total of 84 teeth）. Traditional preparation and morphology driven preparation techniques were used to complete dental preparation and adhesive glass ceramic restorations， respectively. The satisfaction， masticatory function， World Dental Federation （FDI） Scores for edge fracture and fixation，edge adaptability index，periodontal bleeding index （BI） and plaque index （PLI） of the two groups of patients were evaluated and various indicator data were recorded and statistically analyzed at 3 and 6 months after restoration completion. ResultsThere was no statistically significant difference in satisfaction between the two groups after 3 and 6 months of repair； Both groups of data showed a significant improvement in masticatory function. There was no statistical difference after 3 and 6 months of repair. However， a statistically significant difference in masticatory function was noted after 6 months of repair compared with before and after 3 months of repair. As the repair time increased， the masticatory effect improved significantly. There was no statistically significant difference in the edge fracture and fixation index between the two groups at 3 months after repair， but there was a statistically significant difference between the two groups at 6 months with the experimental group outperforming the control group（P<0.05）. The edge adaptability， BI， and PLI index were statistically significant between the two groups after 3 and 6 months of repair and the experimental group had a significant advantage （P<0.05）. ConclusionBoth types of tooth preparation techniques can improve patient masticatory function and reach high satisfaction after repair. However， morphology driven preparation technique has significant advantages in edge adaptability， edge fracture and fixation index scores and improve periodontal conditions. This technique is an effective method for improving dental preparation in adhesive indirect restoration of posterior teeth.

Objective To verify the predictive performance of the population pharmacokinetic(PPK)model of lacosamide in children reported abroad using real-world case data,the exposure-response relationship was analyzed,and the optimal dosing regimen was simulated.Methods The plasma concentration data and clinical data of 64 children with epilepsy aged 4-13.42 years after oral administration of lacosamide reached a steady state were collected,and the prediction accuracy of foreign models was investigated by goodness-of-fit diagram and intuitive prediction test.The relationship between the daily dose or trough concentration of lacosamide and the clinical efficacy was analyzed,and Monte Carlo simulation was used to evaluate and screen the optimal dosing regimen of lacosamide for different body weight stratification and combinations based on pharmacokinetic parameters.Results The external validation results show that the prediction accuracy of the PPK model for children abroad is good.The pharmacokinetic parameters of lacosamide monotherapy in children with epilepsy were as follows:absorption rate constant(ka)=(2.43±0.04)h-1,apparent volume of distribution(Vd/F)=(22.69±6.00)L,clearance rate(CL/F)=(1.25±0.27)L·h-1,half-life(t1/2)=(12.74±2.40)h.The distribution range of 5％-95％quantile of daily dose of clinically effective cases was 2.5-6.3 mg·kg-1·d-1,and the distribution range of 5％-95％of trough concentration was 1.9-6.7 mg·L-1.The simulation results showed that the optimized dosing regimen of lacosamide recommended in this study could increase the probability of drug concentration reaching the target and ensure the efficacy and tolerability of treatment.Conclusions The prediction performance of the PPK model of lacosamide in foreign children was verified,and the optimal dosing regimen was simulated based on this model,which can provide a reference for clinicians to individualize and rationalize the use of drugs.

Objective Based on multi-dimensional bioinformatics technology,the molecular pathological mechanism of acute hypotension is systematically analyzed.Methods Integrate the gene expression profile of the Gene Expression Omnibus database(GSE2401),use limma package(R software)to screen differential genes,and optimize targets through data dimensionality reduction(log2(FC)＞1,P＜0.05);Further combine Gene Ontology,Kyoto Encyclopedia of Genes and Genomes and gene set enrichment analysis pathway enrichment and STRING-Cytoscape(MCODE,CytoHubba plug-in)to build a protein-protein interaction(PPI)network to mine core genes;realize the full-chain analysis of"differential gene-functional pathway-PPI network".Results 676 differential genes(304 upregulated,372 downregulated),ribosome structural components(Rps8,Rps27,Rpl35,etc.)and multiple pathways such as forkhead box protein and cyclic adenosine monophosphate were found to coordinate the regulation of acute hypotension.Conclusion This study uses a low-cost and efficient bioinformatics analysis framework to reveal the association between ribosomal dysfunction,changes in insulin signal efficacy and blood pressure regulation,providing new ideas for targeted therapy.