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.

Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

ObjectiveProtein-protein interactions (PPIs) are fundamental to the execution of biological functions within living cells. However, traditional biochemical methods, such as co-immunoprecipitation (Co-IP), often fail to capture transient, weak, or membrane-associated interactions due to the stringent detergent requirements for cell lysis. Proximity labeling (PL) has emerged in recent years as a transformative technology for mapping the proteomes of specific subcellular compartments and identifying dynamic interactomes in situ. Golgi protein 73 (GP73, also known as GOLPH2), a resident type II Golgi transmembrane protein, is a well-recognized clinical biomarker for liver diseases, including hepatocellular carcinoma (HCC). Despite its clinical significance, the comprehensive physiological and pathological functions of GP73 remain partially understood. This study aims to establish an APEX2-mediated proximity labeling system specifically targeting GP73 to map its interactome in a living cellular environment, thereby providing new insights into its molecular roles and regulatory mechanisms. MethodsTo achieve spatial specificity, we first constructed a stable cell line expressing a fusion protein consisting of GP73 and the engineered soybean peroxidase APEX2. The localization of the GP73-APEX2 fusion protein was validated to ensure it correctly targeted the Golgi apparatus. The proximity labeling reaction was initiated by incubating the cells with biotin-phenol (BP) for 30 min, followed by a brief (1 min) treatment with1 mmol/L hydrogen peroxide (H₂O₂). This catalytic reaction converts BP into highly reactive, short-lived biotin-phenoxyl radicals that covalently attach to endogenous proteins within a small labeling radius of the GP73-APEX2 enzyme. Subsequently, the cells were quenched, and biotinylated proteins were enriched using high-affinity streptavidin-coated magnetic beads. The captured “neighbor” proteins were subjected to on-bead digestion and analyzed via liquid chromatography-tandem mass spectrometry (LC-MS/MS) for high-throughput identification. Rigorous bioinformatics analysis, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction network mapping, was performed to interpret the biological significance of the identified candidates. ResultsOur results demonstrate the successful establishment of a robust and sensitive APEX2-based proximity labeling system for GP73. We identified a total of 95 high-confidence interacting proteins that were significantly enriched in the GP73 proximity proteome compared to control groups. Bioinformatics analysis revealed that these interactors were predominantly associated with biological processes such as vesicular transport, protein localization, and, most notably, molecular functions related to “ribosome binding” and “translation regulation”. This suggested an unexpected role for the Golgi-resident GP73 in the cellular translation machinery. To validate these findings, we performed targeted biochemical assays which confirmed a direct interaction between GP73 and the subunits of the eukaryotic translation initiation factor 3 (eIF3) complex, specifically EIF3G and EIF3I. Furthermore, functional validation using the surface sensing of translation (SUnSET) assay—a non-radioactive method to monitor protein synthesis—revealed that the overexpression of GP73 significantly promoted global protein translation levels in the cell, whereas its depletion or inhibition resulted in reduced translation efficiency. ConclusionThis study successfully utilized APEX2-mediated proximity labeling to provide the first systematic map of GP73 interactome in living cells. Our findings uncover a novel, unconventional function of GP73 as a regulator of cellular protein translation, likely mediated through its interaction with the eIF3 complex. This discovery significantly broadens our understanding of the biological roles of GP73 beyond its traditional function in the Golgi apparatus and suggests that it may act as a bridge between Golgi-related trafficking and the protein synthesis machinery. Furthermore, the technical framework established in this study provides a valuable template for investigating other complex organelle-associated protein networks and resolving transient macromolecular interactions in various physiological and pathological contexts.

Background: Adrenocortical hormones, particularly 11-oxygenated androgens, are pivotal in female reproductive health and fertility. Standardized detection kits and population-specific reference intervals are lacking in China, hindering related clinical applications. Methods: A HPLC-tandem mass spectrometry (HPLC-MS/MS) pipeline was developed, rigorously validated, and applied to simultaneously quantify corticosterone, cortisone, cortisol, 18-OH cortisol, androstenedione (A4), 11β-hydroxyandrostenedione (11-OH A4), dehydroepiandrosterone, and dehydroepiandrosterone sulfate in serum samples from 455 reproductive-aged women (18–45 yrs) in Guangxi, China. Age-dependent concentration trends were analyzed, and reference intervals stratified by age (2.5th to 97.5th percentiles) were established. Correlations with body-composition metrics, ethnicity, and the menstrual cycle were investigated. Results: The HPLC-MS/MS method demonstrated high precision (intra- and inter-assay CVs < 15%), accuracy, and sensitivity. All eight hormones exhibited significant age-related declines (P < 0.001 for seven hormones; P = 0.001 for 11-OH A4). Notably, 11-OH A4 levels were significantly lower in the 35–45-yr (3.05 nmol/L) and 25–34-yr (3.09 nmol/L) age groups than in the 18–24-yr (3.57 nmol/L) age group, whereas no significant difference was observed between the 35–45-yr and 25–34-yr age groups. Weak negative correlations were observed between the body mass index and corticosterone and cortisone levels, whereas ethnicity and the menstrual cycle showed no significant associations with hormone levels. Conclusions We developed an HPLC-MS/MS-based method for simultaneously quantifying eight adrenocortical hormones, including 11-OH A4, and defined age-specific reference intervals for reproductive-aged Chinese women. These findings advance the clinical utility of adrenocortical hormones in diagnosing and managing reproductive disorders.

Objective This study aimed to investigate the genetic diversity, differentiation, and population structure of Aedes albopictus across different geographical regions in Shandong Province, and to explore the relationship between genetic diversity and geographical distribution. Methods Between July and August 2024, ten Ae. albopictus populations were sampled from seven cities in Shandong Province. Genomic DNA was extracted from individual mosquitoes, and the mitochondrial cytochrome c oxidase subunit I(COⅠ)gene was amplified using PCR and sequenced. The obtained sequences were verified using BLAST and analyzed with MAFFT, MEGA 11, DnaSP v6.12, Arlequin 3.5, PopART 1.7, STRUCTURE 2.3.4 and the R packages adegenet and vegan to assess genetic diversity and population structure. Results A total of 229 COⅠ sequences(662 bp) was obtained, revealing ten variable sites with no insertions or deletions. The overall base composition showed an AT bias of 67.7%. Haplotype analysis identified 11 haplotypes, with Hap2 being the dominant and most widely distributed haplotype across all populations. Neutrality tests showed significant population expansion only in the Rizhao population. Mantel testing result revealed that geographical distance does not significantly impede gene flow. Overall, genetic differentiation among populations was low, indicating frequent gene flow. When combined with additional samples from Shanghai, Fujian, Guangdong, Yunnan, Hainan and Guangxi, STRUCTURE, UPGMA and DAPC analyses revealed two primary genetic clusters of Ae. albopictus. Conclusions Ae. albopictus populations in Shandong Province exhibit frequent gene flow, low genetic differentiation, and relatively low overall genetic diversity. However, the Rizhao population showed signs of recent expansion, highlighting the need for enhanced surveillance and targeted control measures in this area.

Objective To investigate the significance of modified Seoul National University Renal Stone Complexity score (S-ReSC), renal stone complexity score (R.I.R.S.), and Clinical Research Office of the Endourological Society Nephrolithometric Nomogram (CROES) score in predicting the stone-clearance rate (SFR) after ureteroscopy combined with flexible negative pressure suction sheath in the treatment of kidney stones. Methods A total of 200 patients with kidney stones treated in our hospital during Dec.2022 and Apr.2024 were selected.According to abdominal CT evaluation 1 month after surgery, the patients were divided into the residual group (n=38) and the non-residual group (n=162).The relationship between the scores was assessed with Pearson correlation, the independent risk factors were identified with binary logistic regression, the predictive efficacy was evaluated with the receiver operating characteristic (ROC) curves, and the difference in the area under the ROC curves (AUCs) was compared with the Delong test. Results Compared with the non-residual group, the residual group had significantly higher modified S-ReSC and R.I.R.S., but significantly lower CROES score (P＜0.05). Modified S-ReSC was positively correlated with R.I.R.S. (P＜0.05), while CROES score was negatively correlated with S-ReSC and R.I.R.S.Staghorn stones, maximum stone diameter, elevated CT values, increased S-ReSC and R.I.R.S., and decreased CROES score were independent risk factors for postoperative stone residual (P＜0.05).ROC curves showed the optimal AUC of R.I.R.S.was 0.855, and the optimal AUC of combined prediction was 0.950.Conclusion The R.I.R.S.has the best efficacy in predicting postoperative stone residual, especially for complex stones.The combination of stone characteristics and the three scoring systems can improve the prediction efficiency, and provide reference for preoperative evaluation and individualized treatment.

BACKGROUND: Death burden of stroke is severe with over one-third rural residents in China, but there is still a lack of specific national and high-quality reports on the urban-rural differences in stroke burden, especially for subtypes. We aimed to update the understanding of urban-rural differences in stroke deaths. METHODS: This is a descriptive observational study. Data from the national mortality surveillance system, which covers 323.8 million with 605 disease surveillance points (DSPs) across all 31 provinces, municipalities, and autonomous regions in China. All deaths from stroke as the underlying cause from 2015 to 2020 according to DSPs. Crude mortality rate and age-standardized mortality rate (ASMR) were estimated through DSPs. Average annual percentage change was used to explain the change in mortality rate. RESULTS: From 2015 to 2020, the majority of deaths from all stroke subtypes occurred in rural areas. There were significant differences between the changes of urban and rural ASMRs. On the whole, the changes in urban areas were evidently better, and the ASMR differences were basically expanding. Stroke ASMR in urban China decreased by 15.5%. The rural ASMR of ischemic stroke increased by 12.9%. The rural and urban ASMRs of intracerebral hemorrhage decreased by 24.9% and 27.4%, and those of subarachnoid hemorrhage decreased by 29.5% and 40.4%, respectively. The highest ASMRs of all stroke subtypes and the increasing trend of ischemic stroke ASMR make rural males the focus of stroke management. CONCLUSIONS The death burden of stroke varies greatly between urban and rural China. Rural residents face unique challenges.
Humans ; China/epidemiology* ; Stroke/mortality* ; Rural Population/statistics & numerical data* ; Male ; Female ; Urban Population/statistics & numerical data* ; Middle Aged ; Aged ; Aged, 80 and over ; Adult

The increasing prevalence of aging has led to a rising incidence of comorbidity of sarcopenia and obesity, posing significant burdens on socioeconomic and public health. Current research has systematically explored the pathogenesis of each condition; however, the mechanisms underlying their comorbidity remain unclear. This study reviews the current literature on sarcopenia and obesity in the aging population, focusing on their shared biological mechanisms, which include loss of autophagy, abnormal macrophage function, mitochondrial dysfunction, and reduced sex hormone secretion. It also identifies metabolic mechanisms such as insulin resistance, vitamin D metabolism abnormalities, dysregulation of iron metabolism, decreased levels of nicotinamide adenine dinucleotide, and gut microbiota imbalances. Additionally, this study also explores the important role of genetic factors, such as alleles and microRNAs, in the co-occurrence of sarcopenia and obesity. A better understanding of these mechanisms is vital for developing clinical interventions and preventive strategies.
Humans ; Sarcopenia/physiopathology* ; Obesity/physiopathology* ; Aging/physiology* ; Autophagy/physiology* ; Insulin Resistance ; Comorbidity ; Vitamin D/metabolism* ; Gonadal Steroid Hormones/metabolism* ; Gastrointestinal Microbiome ; Mitochondria ; MicroRNAs

This study investigates the effect and underlying mechanism of Guizhi Tongluo Tablets(GZTL) in treating atherosclerosis(AS) in a mouse model. Apolipoprotein E-knockout(ApoE~(-/-)) mice were randomly assigned to the following groups: model, high-, medium-, and low-dose GZTL, and atorvastatin(ATV), and age-matched C57BL/6J mice were selected as the control group. ApoE~(-/-) mice in other groups except the control group were fed with a high-fat diet for the modeling of AS and administrated with corresponding drugs via gavage for 8 weeks. General conditions, signs of blood stasis, and body mass of mice were monitored. Aortic plaques and their stability were assessed by hematoxylin-eosin, Masson, and oil red O staining. Serum levels of total cholesterol(TC), triglycerides(TG), and low-density lipoprotein cholesterol(LDL-C) were measured by biochemical assays, and those of interleukin-1β(IL-1β), tumor necrosis factor-α(TNF-α), and interleukin-6(IL-6) were determined via enzyme-linked immunosorbent assay. Apoptosis was assessed by terminal deoxynucleotidyl transferase dUTP nick end labeling(TUNEL). Single-cell RNA sequencing(scRNA-seq) was employed to analyze the differential expression of CD72hi macrophages(CD72hi-Mφ) in the aortas of AS patients and mice. The immunofluorescence assay was employed to visualize CD72hi-Mφ expression in mouse aortic plaques, and real-time fluorescence quantitative PCR was utilized to determine the mRNA levels of IL-1β, TNF-α, and IL-6 in the aorta. The results demonstrated that compared with the control group, the model group exhibited significant increases in body mass, aortic plaque area proportion, necrotic core area proportion, and lipid deposition, a notable decrease in collagen fiber content, and an increase in apoptosis. Additionally, the model group showcased elevated serum levels of TC, TG, LDL-C, IL-1β, TNF-α, and IL-6, alongside marked upregulations in the mRNA levels of IL-1β, TNF-α, and IL-6 in the aorta. In comparison with the model group, the GZTL groups and the ATV group showed a reduction in body mass, and the medium-and high-dose GZTL groups and the ATV group demonstrated reductions in aortic plaque area proportion, necrotic core area proportion, and lipid deposition, an increase in collagen fiber content, and a decrease in apoptosis. Furthermore, the treatment goups showcased lowered serum levels of TC, TG, LDL-C, IL-1β, TNF-α, and IL-6. The data of scRNA-seq revealed significantly elevated CD72hi-Mφ signaling in carotid plaques of AS patients compared with that in the normal arterial tissue. Animal experiments confirmed that CD72hi-Mφ expression, along with several pro-inflammatory cytokines, was significantly upregulated in the aortas of AS mice, which were downregulated by GZTL treatment. In conclusion, GZTL may alleviate AS by inhibiting CD72hi-Mφ activity.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Atherosclerosis/immunology* ; Mice ; Mice, Inbred C57BL ; Macrophages/immunology* ; Male ; Humans ; Apolipoproteins E/genetics* ; Tablets ; Tumor Necrosis Factor-alpha/genetics* ; Apoptosis/drug effects* ; Interleukin-1beta/genetics* ; Interleukin-6/genetics* ; Disease Models, Animal ; Mice, Knockout