The Golgi body, a core organelle in eukaryotic cells, plays a critical role in protein modification, sorting, vesicular transport, and serves as a key site for lipid synthesis and glycosylation. Glucose and lipid metabolism are central processes for cellular energy maintenance and biosynthesis, and are closely linked to Golgi function. Recent studies have revealed the extensive involvement of the Golgi body in regulating glucose and lipid metabolism, where maintaining its structural and functional homeostasis is crucial for normal physiological activity. Under various stress conditions such as acidosis, hypoxia, and nutrient deficiency, the Golgi body undergoes structural and functional disruption, leading to Golgi stress. This in turn activates specific signaling pathways, such as those mediated by the cAMP-responsive element binding protein 3 (CREB3) and proteoglycans, to alleviate Golgi stress and enhance Golgi function. Golgi stress contributes to glucose and lipid metabolic disorders by affecting the activity of insulin receptors, glucose transporters, and lipid metabolism-related enzymes. For example, Golgi stress triggers the cleavage and release of the active fragment of CREB3, which enters the nucleus and upregulates the transcription of ADP-ribosylation factor 4 (ARF4) and key gluconeogenic enzymes, including phosphoenolpyruvate carboxykinase (PEPCK) and glucose-6-phosphatase (G6Pase). ARF4 promotes vesicle retrograde transport between the Golgi and endoplasmic reticulum, maintains secretory capacity, and enhances hepatic glucose output. This pathway is particularly active under high-fat or lipotoxic stress, leading to fasting hyperglycemia. When damaged Golgi components accumulate beyond a tolerable threshold, the cell initiates an autophagic response, selectively encapsulating the damaged Golgi into autophagosomes, which then fuse with lysosomes to form autolysosomes, leading to Golgiphagy. This process results in the degradation and clearance of damaged Golgi, thereby regulating Golgi quantity, quality, and function. Golgiphagy also plays a significant role in regulating glucose and lipid metabolism. For instance, under high-glucose conditions, autophagic flux may be suppressed, impairing the timely clearance and renewal of damaged Golgi, compromising its normal function, and further exacerbating glucose metabolism disorders. Additionally, Golgiphagy may participate in lipid degradation and influence lipid synthesis and transport. Research indicates that Golgi stress and Golgiphagy play important roles in glucose and lipid metabolism-related diseases. For example, the leucine zipper protein (LZIP) under Golgi stress conditions can promote hepatic steatosis. In mouse primary cells and human tissues, LZIP induces the expression of apolipoprotein A-IV (APOA4), which increases peripheral free fatty acid uptake, resulting in lipid accumulation in the liver and contributing to the development of fatty liver disease. This review systematically outlines the structure and function of the Golgi apparatus, the molecular regulatory mechanisms of Golgi stress and Golgiphagy, and their synergistic roles. It further elaborates on how Golgi stress and Golgiphagy participate in the regulation of glucose and lipid metabolism, discusses their clinical significance in related diseases such as diabetes, fatty liver disease, and obesity, and highlights potential novel therapeutic strategies from the perspective of Golgi-targeted medicine. Finally, this article addresses the challenges and future directions in Golgi-targeted interventions, aiming to advance the clinical translation of such strategies and foster breakthroughs in the treatment of glucose and lipid metabolism-related disorders.

The Golgi body, a core organelle in eukaryotic cells, plays a critical role in protein modification, sorting, vesicular transport, and serves as a key site for lipid synthesis and glycosylation. Glucose and lipid metabolism are central processes for cellular energy maintenance and biosynthesis, and are closely linked to Golgi function. Recent studies have revealed the extensive involvement of the Golgi body in regulating glucose and lipid metabolism, where maintaining its structural and functional homeostasis is crucial for normal physiological activity. Under various stress conditions such as acidosis, hypoxia, and nutrient deficiency, the Golgi body undergoes structural and functional disruption, leading to Golgi stress. This in turn activates specific signaling pathways, such as those mediated by the cAMP-responsive element binding protein 3 (CREB3) and proteoglycans, to alleviate Golgi stress and enhance Golgi function. Golgi stress contributes to glucose and lipid metabolic disorders by affecting the activity of insulin receptors, glucose transporters, and lipid metabolism-related enzymes. For example, Golgi stress triggers the cleavage and release of the active fragment of CREB3, which enters the nucleus and upregulates the transcription of ADP-ribosylation factor 4 (ARF4) and key gluconeogenic enzymes, including phosphoenolpyruvate carboxykinase (PEPCK) and glucose-6-phosphatase (G6Pase). ARF4 promotes vesicle retrograde transport between the Golgi and endoplasmic reticulum, maintains secretory capacity, and enhances hepatic glucose output. This pathway is particularly active under high-fat or lipotoxic stress, leading to fasting hyperglycemia. When damaged Golgi components accumulate beyond a tolerable threshold, the cell initiates an autophagic response, selectively encapsulating the damaged Golgi into autophagosomes, which then fuse with lysosomes to form autolysosomes, leading to Golgiphagy. This process results in the degradation and clearance of damaged Golgi, thereby regulating Golgi quantity, quality, and function. Golgiphagy also plays a significant role in regulating glucose and lipid metabolism. For instance, under high-glucose conditions, autophagic flux may be suppressed, impairing the timely clearance and renewal of damaged Golgi, compromising its normal function, and further exacerbating glucose metabolism disorders. Additionally, Golgiphagy may participate in lipid degradation and influence lipid synthesis and transport. Research indicates that Golgi stress and Golgiphagy play important roles in glucose and lipid metabolism-related diseases. For example, the leucine zipper protein (LZIP) under Golgi stress conditions can promote hepatic steatosis. In mouse primary cells and human tissues, LZIP induces the expression of apolipoprotein A-IV (APOA4), which increases peripheral free fatty acid uptake, resulting in lipid accumulation in the liver and contributing to the development of fatty liver disease. This review systematically outlines the structure and function of the Golgi apparatus, the molecular regulatory mechanisms of Golgi stress and Golgiphagy, and their synergistic roles. It further elaborates on how Golgi stress and Golgiphagy participate in the regulation of glucose and lipid metabolism, discusses their clinical significance in related diseases such as diabetes, fatty liver disease, and obesity, and highlights potential novel therapeutic strategies from the perspective of Golgi-targeted medicine. Finally, this article addresses the challenges and future directions in Golgi-targeted interventions, aiming to advance the clinical translation of such strategies and foster breakthroughs in the treatment of glucose and lipid metabolism-related disorders.

ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

Objective: To explore the relationship between life skills, psychological resilience and subjective well-being among primary and secondary school students, so as to provide evidence for targeted adolescent mental health education. Methods: From September to November, 2025, a total of 5 831 primary and secondary school students from five cities (Beijing, Guangzhou, Shenzhen, Chongqing, Urumqi) were selected by convenience sampling. The Adolescent Subjective Well being Scale, School based Adolescents Life Skills Scale, and Adolescent Psychological Resilience Scale were used for investigation. Data were analyzed using t-tests, one way ANOVA, and linear regression. Results: The total mean score of students subjective well being was (5.46± 0.91) ; the total mean score of life skills was (3.69±0.64); the total mean score of psychological resilience was (3.66±0.69). Statistically significant differences in subjective well being scores were found among students grouped by gender, grade, school stage, residential city, living with parents or living with siblings ( t/F =4.14, 53.92, 14.53, 49.99, 13.49, 2.18, all P <0.01). Stratified regression analyses were performed by gender (adjusting for school stage, residential city and living arrangement) and by school stage (adjusting for gender, residential city and living arrangement), the regression results indicated that life skills of boys, girls, primary school students and junior high school students( β =0.54, 0.53, 0.50, 0.57) and their psychological resilience ( β = 0.56 , 0.60, 0.56, 0.60) were positively associated with subjective well being (all P <0.01). Conclusions Life skills and psychological resilience may be important protective factors for subjective well being among primary and secondary school students. School based mental health education should emphasize life skills training and resilience building to promote students subjective well being.

Objective: To explore the association between parental subjective well-being and subjective well-being among primary and secondary school students, so as to provide evidence for promoting adolescent mental health from a family perspective. Methods: From September to November 2025, a convenience sampling method was used to recruit 4 612 students in grades 4-8 from 12 primary and secondary schools in five cities—Beijing, Guangzhou, Shenzhen, Chongqing, and Urumqi—along with their parents. Students completed the Adolescent Well being Survey Questionnaire, while parents completed the Parental Well being Survey Questionnaire. Data were analyzed using t-test, one way analysis of variance, multiple linear regression, Logistic regression, and stratified subgroup analyses. Results: The maximum score of the subjective well-being scale for primary and secondary school students was 301, with a total score of (224.07±46.63), representing 74.4% of the full score; the maximum score of the parental subjective well-being scale was 120, with a total score of (92.35±15.10), representing 77.0%. Multiple linear regression analysis showed that parental subjective well-being was positively associated with students overall subjective well-being, positive affect, and satisfaction in each domain (friendship, family, school, environment, freedom, and academics), and negatively associated with negative affect ( β =0.45, 0.08, 0.06, 0.07, 0.05, 0.04, 0.05, 0.04, -0.05, all P <0.01). Logistic regression and stratified analysis showed that parental subjective well-being was positively associated with students high subjective well-being ( OR =1.03), and the association existed in subgroups of different gender, grade and family structure ( OR =1.02-1.04) (all P <0.05). Conclusions Parental subjective well-being is positively associated with students subjective well-being. Future interventions should incorporate an integrated strategy featuring family-school collaboration to promote adolescent well-being.

The precision diagnosis and treatment of chest wall tumors heavily rely on imaging assessment, which is limited by the subjectivity of conventional methods and their insensitivity to microscopic features. Artificial intelligence (AI) technologies, particularly radiomics and deep learning, offer new opportunities to overcome these bottlenecks. It is important to note, however, that direct AI research focused specifically on chest wall tumors remains scarce. Most current insights are derived from methodological borrowing and conceptual extrapolation of studies on other solid tumors, such as lung, breast, and esophageal cancers. This review systematically outlines the potential application framework of AI in the management of chest wall tumors, encompassing benign-malignant differentiation, non-invasive pathological subtyping, early treatment response prediction, and prognosis stratification based on multi-modal imaging. It discusses the core model-building strategies and validation processes centered on data fusion, and critically analyzes the unique challenges in this field, including data scarcity, model interpretability, and clinical translation. Moving forward, key directions for translating the potential of AI into clinical reality include fostering the development of dedicated chest wall tumor datasets, conducting prospective validation studies, and exploring "imaging-genomics" integration as well as dynamic decision-support systems.

RNA modifications constitute a crucial class of post-transcriptional chemical alterations that profoundly influence RNA stability and translational efficiency, thereby shaping cellular protein expression profiles. These diverse chemical marks are ubiquitously involved in key biological processes, including cell proliferation, differentiation, apoptosis, and metastatic potential, and they exert precise regulatory control over these functions. A major advance in the field is the recognition that RNA modifications do not act in isolation. Instead, they participate in complex, dynamic interactions—through synergistic enhancement, antagonism, competitive binding, and functional crosstalk—forming what is now termed the “RNA modification interactome” or “RNA modification interaction network.” The formation and functional operation of this interactome rely on a multilayered regulatory framework orchestrated by RNA-modifying enzymes—commonly referred to as “writers,” “erasers,” and “readers.” These enzymes exhibit hierarchical organization within signaling cascades, often functioning in upstream-downstream sequences and converging at critical regulatory nodes. Their integration is further mediated through shared regulatory elements or the assembly into multi-enzyme complexes. This intricate enzymatic network directly governs and shapes the interdependent relationships among various RNA modifications. This review systematically elucidates the molecular mechanisms underlying both direct and indirect interactions between RNA modifications. Building upon this foundation, we introduce novel quantitative assessment frameworks and predictive disease models designed to leverage these interaction patterns. Importantly, studies across multiple disease contexts have identified core downstream signaling axes driven by specific constellations of interacting RNA modifications. These findings not only deepen our understanding of how RNA modification crosstalk contributes to disease initiation and progression, but also highlight its translational potential. This potential is exemplified by the discovery of diagnostic biomarkers based on interaction signatures and the development of therapeutic strategies targeting pathogenic modification networks. Together, these insights provide a conceptual framework for understanding the dynamic and multidimensional regulatory roles of RNA modifications in cellular systems. In conclusion, the emerging concept of RNA modification crosstalk reveals the extraordinary complexity of post-transcriptional regulation and opens new research avenues. It offers critical insights into the central question of how RNA-modifying enzymes achieve substrate specificity—determining which nucleotides within specific RNA transcripts are selectively modified during defined developmental or pathological stages. Decoding these specificity determinants, shaped in large part by the modification interactome, is essential for fully understanding the biological and pathological significance of the epitranscriptome.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.