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.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

ObjectiveTo explore the mechanism by which aerobic exercise improves hippocampal neuroinflammation and learning and memory ability in brain-aged mice via interferon regulatory factor 7 (IRF7). MethodsA total of 60 male specific pathogen-free (SPF) C57BL/6J mice were enrolled in the experiment, including 30 young mice (2 months old) and 30 naturally aging mice (12 months old). Young mice and old mice were respectively randomly assigned to four groups: young control group (group C, n=15), young exercise group (group CE, n=15), and aging control group (group A, n=15), aging exercise group (group AE, n=15). Mice in the exercise groups received an 8-week continuous treadmill aerobic exercise intervention, while control mice were kept under routine feeding without exercise intervention. After the intervention, Barnes maze and Y-maze behavioral tests were performed to comprehensively assess the learning and memory abilities of each group of mice. Transmission electron microscopy was used to observe the ultrastructural morphological changes of hippocampal synapses. Western blot assay was utilized to detect the protein expression and phosphorylation levels of Janus kinase 1 (JAK1), signal transducer and activator of transcription 1 (STAT1), as well as the expression of postsynaptic density protein 95 (PSD95). Immunofluorescence staining was applied to quantify the fluorescence intensity of ionized calcium-binding adapter molecule 1 (IBA1) in hippocampal tissues. The expression levels of inflammatory cytokines including interferon-α (IFN-α), interferon-β (IFN-β), tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) were measured by enzyme-linked immunosorbent assay (ELISA). Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect the mRNA expression level of IRF7, and DNA methylation assay was further conducted to analyze the methylation level of the IRF7 gene in mouse hippocampus. ResultsAt the molecular level, compared with group C, the protein expression levels of JAK1, STAT1, p‑JAK1, and p‑STAT1 in group A were significantly increased (P<0.05), whereas PSD95 expression was decreased (P<0.05). ELISA assays showed that the levels of IFN‑α, IFN‑β, TNF‑α, and IL‑1β were significantly elevated in group A (P<0.001). RT‑PCR analysis revealed that, compared with group C, the mRNA expression of IRF7 in group A was markedly upregulated (P<0.000 1), while the CpG methylation rate of the IRF7 promoter was significantly reduced (P<0.05). In contrast, all the above parameters in the AE group showed improvements relative to those in group A. Immunofluorescence staining indicated positive IBA1 expression in the brain tissues of group A mice. Exercise intervention reversed these abnormal changes. ConclusionIn aged mice, aerobic exercise induces hypermethylation of the IRF7 promoter region, suppresses IRF7 expression and activation of the downstream IFN‑I/JAK1/STAT1 signaling pathway, accompanied by alleviated neuroinflammation, improved learning and memory, and ameliorated brain aging-related phenotypes.

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

Eight compounds were isolated and purified from the ethyl acetate part of 70% acetone extract of Rehmannia glutinosa by various chromatographic techniques such as silica gel, MCI gel CHP-20, ODS, Toyopearl HW-40C, combined with TLC and semi-preparative HPLC. Their structures were elucidated by modern spectroscopy techniques (NMR, MS, UV, IR), and identified as neomartynoside A (1), osmanthuside B₆ (2), martynoside (3), isomartynoside (4), (E)-p-hydroxycinnamic acid (5), caffeic acid (6), ferulic acid (7), and methyl caffeate (8). Compound 1 is a new phenylethanol glycoside, which was identified as neomartynoside A. Compound 2 was isolated from Rehmannia glutinosa for the first time. In addition, compounds 2, 6 and 7 significantly increased relative glucose consumption, showing potential hypoglycemic activity.

Objective:To evaluate the impact of short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves on the risk of road traffic mortality and calculate the attributable mortality burden.Methods:This study collected road traffic mortality data from the Disease Surveillance System in Guangdong, Hunan, Zhejiang, Yunnan, and Jilin Provinces from 2013 to 2018. A time-stratified case-crossover design was used in this study, with the death date for each case serving as the case day. Control days were selected from the same year, month, and day of the week as the case day. A conditional logistic regression model was employed to estimate the cumulative associations of short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves on the risk of road traffic mortality (lag 0-1 day) and to calculate the attributable fractions (AF).Results:Compared to non-heatwave days, the excess risk ( ER) of road traffic mortality on daytime heatwave days, nighttime heatwave days, and compound heatwave days was 5.3% (95% CI: 0.5%-10.2%), 4.9% (95% CI: 0.5%-9.4%) and 7.5% (95% CI: 2.3%- 12.9%), with corresponding AF of 5.0% (95% CI: 0.5%-9.3%), 4.7% (95% CI: 0.5%-8.6%), and 6.9% (95% CI: 2.3%-11.4%), respectively. Stratified analysis showed that the risk of traffic mortalities caused by daytime heatwaves was higher in females ( ER=15.7%, 95% CI: 5.8%-26.5%) than in males ( ER=1.8%, 95% CI: -3.6%-7.4%). Elderly individuals over 64 years old ( ER=10.9%, 95% CI: 0.3%- 22.6%) had a higher risk of road traffic mortalities from compound heatwaves than those under 45 years old ( ER=2.6%, 95% CI: -5.4%-11.2%). The risk of road traffic injury mortality from motor vehicle accidents caused by compound heatwaves ( ER=16.6%, 95% CI:2.4%-32.7%) was higher than that from non-motor vehicle accidents ( ER=5.7%, 95% CI:0.1%-11.5%). Conclusions:Short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves was associated with an increased risk of road traffic mortality, with the strongest association observed for compound heatwaves. The mortality burden attributable to compound heatwaves was higher than that for daytime and nighttime heatwaves. Heatwaves were more significantly associated with road traffic mortality risk among females, elderly individuals over 64 years old, and motor vehicle accidents.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Fragility fractures represent the final clinical manifestation of osteoporosis and are influenced by a range of risk factors. This article discusses the findings from two large-scale studies utilizing biobank and genomic data to investigate the relationships among obesity, type 2 diabetes and fracture risk, and to explore their implications for health management. The studies suggest that general obesity(defined by body mass index, BMI), central obesity(defined by waist circumference), and peripheral obesity exert different effects on fracture risk in older adults. Specifically, individuals who are overweight based on BMI have a lower fracture risk compared to those with normal weight, whereas an increased waist circumference is associated with a higher fracture risk. Moreover, genetic research indicates that genetically determined type 2 diabetes is not causally associated with increased fracture risk. In contrast, observational studies have reported a higher fracture risk in patients with type 2 diabetes; however, this association becomes non-significant after adjusting for diabetes-related risk factors. These findings highlight that maintaining a moderately elevated BMI may benefit bone formation in the elderly by providing mechanical loading to stimulate bone formation. Additionally, effective management of type 2 diabetes complications is essential for reducing fracture risk, and a certain degree of obesity may confer a protective effect against fractures in individuals with type 2 diabetes.

Objective:To investigate the clinical characteristics and independent risk factors of severe disease in patients with anti-nuclear matrix protein (NXP) 2 antibody-positive juvenile dermatomyositis (JDM).Methods:A retrospective cohort study was conducted, including 219 anti-NXP2 antibody-positive JDM patients admitted to 23 children′s hospitals across China from July 2011 to July 2023. Patients were classified into severe and non-severe groups based on classification criteria for severe dermatomyositis. Demographic characteristics, clinical manifestations, and laboratory parameters were compared between the 2 groups using independent sample t-test, Mann-Whitney U test, or χ2 test. Univariate and multivariate Logistic regression analyses were performed to identify risk factors for severe disease. The receiver operating characteristic curve was employed to calculate optimal cut-off values. Results:Among the 219 patients, 108 were male and 111 were female, with an age at onset of 6.3 (3.5, 9.4) years. The severe group comprised 69 patients, and the non-severe group 150 patients. The severe group had significantly higher rates of fever, heliotrope rash, subcutaneous edema, periorbital edema, anti-Ro52 antibody positivity, as well as elevated levels of ferritin-to-albumin ratio (FAR), creatine kinase (CK), aspartate aminotransferase (AST), and lactate dehydrogenase (LDH) (all P<0.05). Multivariate analysis identified anti-Ro52 antibody positivity ( OR=13.26, 95% CI 1.37-128.29) and elevated FAR ( OR=1.90, 95% CI 1.09-2.31) as independent risk factors for severe anti-NXP2 antibody-positive JDM (both P<0.05). Receiver operating characteristic curve analysis revealed that a FAR cutoff value of 6.82 predicted severe disease with an area under the curve of 0.87 (95% CI 0.81-0.94, P<0.001), sensitivity of 0.85, and specificity of 0.70. All patients received glucocorticoid therapy, and the severe group received higher proportions of steroid pulse therapy, cyclophosphamide, mycophenolate mofetil, intravenous immunoglobulin, biologics, and adjuvant treatments compared to the non-severe group (all P<0.05). In terms of outcomes, 2 patients (2.9%) in the severe group died (due to neurological involvement and intestinal perforation, respectively), while the remaining patients achieved complete clinical response or remission. All patients in the non-severe group achieved remission. Conclusions:The primary clinical features of anti-NXP2 antibody-positive JDM included fever, heliotrope rash, subcutaneous edema, periorbital edema, anti-Ro52 antibody positivity, and elevated levels of CK, AST, LDH, and FAR. Furthermore, anti-Ro52 antibody positivity and a FAR>6.82 were identified as independent risk factors.

Objective To explore the value of a combined model based on high-kilovoltage CT radiomics and clinical factors for predicting monosodium urate(MSU)crystal deposition in gouty arthritis.Methods The clinical data of 136 patients with MSU crystal deposition adjacent to joints confirmed by dual-energy CT(DECT)and 79 patients with non-MSU calcifications adjacent to joints were retrospectively analyzed.The dataset was randomly divided into a training set(n=150)and a validation set(n=65)at a ratio of 7:3 for the construction of predictive models.Radiomic features were extracted from high-kilovolt(135 kV)images,and 20 radiomic features were selected using minimum redundancy-maximum relevance and least absolute shrinkage and selection operator(LASSO)regression.Logistic regression,light gradient boosting machine(LightGBM),and support vector machine models were built based on the selected features,and the best-performing model was identified.Multivariate logistic regression analysis was used to screen for risk factors associated with MSU crystal deposition adjacent to joints.A nomogram model was then constructed by integrating radiomic features and clinical variables.The diagnostic performance of the models was evaluated by means of the receiver operating characteristics(ROC)area under the curve(AUC).Results Multivariate logistic regression analysis revealed that CT value was an independent risk factor for MSU crystal deposition adjacent to joints(P<0.001).Among the three machine-learning models,the LightGBM model demonstrated the best predictive performance and good dataset robustness.Therefore,the nomogram was constructed using the LightGBM model.The AUCs of the nomogram model for predicting MSU crystal deposition in the training and validation sets were 0.932 and 0.856,respectively,both exceeding 0.85 and significantly higher than those of the clinical model(De-long test,P<0.05).No statistically significant difference was observed between nomogram model and radiomics model(De-long test,P>0.05).Conclusions High-kilovoltage CT radiomics analysis can predict MSU crystal deposition adjacent to joints.The nomogram model and the radiomics model both demonstrate high diagnostic performance,which can provide valuable references for clinical decision-making.