BACKGROUND:Although previous studies have reported associations between lipids and the risk of osteoporotic pathological fractures,the specific causal relationships between lipid level and osteoporotic pathological fractures remain unclear.OBJECTIVE:To elucidate the causal relationship between lipids and osteoporotic pathological fractures using a two-sample bidirectional Mendelian randomization analysis.METHODS:The data for 178 lipid metabolites were obtained from the IEU-GWAS database(developed by the MRC Integrative Epidemiology Unit at the University of Bristol,UK,which provides extensive summary data from genome-wide association studies),while osteoporotic pathological fracture data(from 173 619 European participants)were acquired from the FinnGen database(constructed by the Finnish national gene research program,focusing on investigating relationships between genomics and health/disease in the Finnish population).Osteoporotic pathological fracture data were used as the outcome variable,with lipids serving as exposures,for the bidirectional Mendelian randomization study to evaluate the causal effects of different lipids on osteoporotic pathological fractures.The UK Biobank database was employed as a validation set by switching the outcome variable to verify the findings horizontally.RESULTS AND CONCLUSION:(1)The inverse variance weighted analysis indicated that each unit increase in sterol ester(27∶1/20∶2)levels was associated with a 25.55％increase in the risk of osteoporotic pathological fractures(odds ratio=1.256,95％confidence interval:1.001-1.575,P=0.049),suggesting a significant positive correlation between elevated sterol ester levels and increased fracture risk.Reverse Mendelian randomization analysis revealed a significant negative association between osteoporotic pathological fractures and three types of phosphatidylcholine.Horizontal validation yielded consistent results,confirming sterol ester as a risk factor for osteoporotic pathological fractures.(2)The results indicate that sterol ester is a risk factor for osteoporotic pathological fractures,while phosphatidylcholine serves as a protective factor.These findings strengthen the evidence supporting the effect of lipids on the risk of osteoporotic pathological fractures.Although the GWAS data used in this study were derived from European populations,given the broad commonality of human genetics,the results provide valuable reference significance for improving osteoporosis in Chinese populations through lipid regulation.

ObjectiveTo investigate the epigenetic mechanism of Diwu Yanggan Capsule in improving liver regeneration microenvironment in a rat model of liver cancer by regulating DNA methylation， and to provide a basis for scientific clinical medication. MethodsA total of 48 specific pathogen-free Sprague-Dawley rats were divided into normal group， model group， and Diwu Yanggan Capsule group using a random number table， with 16 rats in each group. The Solt-Farber two-step method was used to establish a rat model of liver cancer. The rats in the Diwu Yanggan Capsule group were given Diwu Yanggan Capsule at a dose of 750 mg/kg/d by gavage， and those in the normal group and the model group were given an equal volume of normal saline by gavage. Liver tissue samples were collected from each group of rats after 16 weeks of continuous intervention； DNA methylation chips were used to analyze the change in DNA methylation in liver tissue， and gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were used for data analysis. In addition， the MeDIP-PCR technique was used to detect the changes in candidate differentially methylated genes such as YWHAB， ADCK2， ERLIN2， SEMA3B， and TPH2 in the liver tissue of rats， and Western blot and RT-qPCR were used to verify the expression of key methylated genes. The independent-samples t test was used for comparison of continuous data between two groups， and a one-way analysis of variance was used for comparison between multiple groups， while the least significant difference t-test was used for further comparison between two groups. ResultsThe DNA methylation chip analysis showed that compared with the normal group， the model group had significant methylation changes in the promoter region of 2 422 genes in liver tissue of rats. The GO functional enrichment analysis and the KEGG pathway enrichment analysis showed that these differentially methylated genes were significantly enriched in metabolic pathways such as steroid hormone biosynthesis and drug metabolism-cytochrome P450. Compared with the model group， the Diwu Yanggan Capsule group had significant reversal of promoter methylation in 1 650 genes， and the KEGG enrichment analysis showed that these genes were mainly involved in the pathways closely associated with cell proliferation， apoptosis， and microenvironment regulation， such as the calcium ion signaling pathway， the cAMP signaling pathway， and the extracellular factor signaling pathway. Compared with the model group， the Diwu Yanggan Capsule group had a significant increase in the promoter methylation level of the ADCK2 gene （P<0.05） and significant reductions in the promoter methylation levels of the ERLIN2 and TPH2 genes （all P<0.05）. Compared with the model group， the Diwu Yanggan Capsule group had significant reductions in the mRNA expression levels and the protein expression levels of the ADCK2 （all P<0.05）. ConclusionAbnormal DNA methylation in liver tissue participates in the development and progression of liver cancer. The effect of Diwu Yanggan Capsule on DNA methylation level is an important epigenetic mechanism for its effect in the prevention and treatment of liver cancer.

BACKGROUND:Although previous studies have reported associations between lipids and the risk of osteoporotic pathological fractures,the specific causal relationships between lipid level and osteoporotic pathological fractures remain unclear.OBJECTIVE:To elucidate the causal relationship between lipids and osteoporotic pathological fractures using a two-sample bidirectional Mendelian randomization analysis.METHODS:The data for 178 lipid metabolites were obtained from the IEU-GWAS database(developed by the MRC Integrative Epidemiology Unit at the University of Bristol,UK,which provides extensive summary data from genome-wide association studies),while osteoporotic pathological fracture data(from 173 619 European participants)were acquired from the FinnGen database(constructed by the Finnish national gene research program,focusing on investigating relationships between genomics and health/disease in the Finnish population).Osteoporotic pathological fracture data were used as the outcome variable,with lipids serving as exposures,for the bidirectional Mendelian randomization study to evaluate the causal effects of different lipids on osteoporotic pathological fractures.The UK Biobank database was employed as a validation set by switching the outcome variable to verify the findings horizontally.RESULTS AND CONCLUSION:(1)The inverse variance weighted analysis indicated that each unit increase in sterol ester(27∶1/20∶2)levels was associated with a 25.55％increase in the risk of osteoporotic pathological fractures(odds ratio=1.256,95％confidence interval:1.001-1.575,P=0.049),suggesting a significant positive correlation between elevated sterol ester levels and increased fracture risk.Reverse Mendelian randomization analysis revealed a significant negative association between osteoporotic pathological fractures and three types of phosphatidylcholine.Horizontal validation yielded consistent results,confirming sterol ester as a risk factor for osteoporotic pathological fractures.(2)The results indicate that sterol ester is a risk factor for osteoporotic pathological fractures,while phosphatidylcholine serves as a protective factor.These findings strengthen the evidence supporting the effect of lipids on the risk of osteoporotic pathological fractures.Although the GWAS data used in this study were derived from European populations,given the broad commonality of human genetics,the results provide valuable reference significance for improving osteoporosis in Chinese populations through lipid regulation.

This study establishes an integrated research paradigm based on traditional Chinese medicine （TCM） theory， guided by pathological characteristics， centered on formula compatibility principles， and supported by multidisciplinary technologies， to systematically analyze the mechanisms of hepatotoxicity induced by toxic Chinese herbal medicinals and strategies for reducing toxicity through compatibility. The findings revealed that the pathomechanism aligns closely with the "liver aversion to acute irritation" theory from Inner Canon of Yellow Emperor （《黄帝内经》）. The core pathology involves an imbalance between liver's form and function， which is characterized by malnourishment of liver form due to yin-blood depletion and dysfunction in ascending-dispersing and free-flowing activities， and closely linked to modern pathological mechanisms such as microcirculatory disturbances， oxidative stress， inflammatory response， metabolic disorder and gut-liver axis dysregulation. Based on this， a multi-layered compatibility strategy for toxicity reduction is put forward， which involves using sweet medicinals to alleviate urgency， balancing the liver form and its function， and pre-regulating other organs. This provides a theoretical basis for the safe application of toxic Chinese herbal medicinals.

ObjectiveTo clarify whether METTL14 mediates the core role of acupuncture at Neiguan (PC6) in promoting myelination and improving behavior in young autistic rats through gene intervention technology. MethodsThe ASD model was established by intraperitoneal injection of valproic acid (VPA) in pregnant rats. Male offspring were intracerebroventricularly injected with adenovirus-packaged METTL14 shRNA (sh-METTL14) or its control (sh-NC) on postnatal day 1, with a model group set as well. Subsequently, the juvenile rats were divided into model group, acupuncture group, acupuncture+sh-NC group, and acupuncture+sh-METTL14 group. The acupuncture group received acupuncture at Neiguan (PC6) from postnatal day 7, once daily for 21 consecutive days. Neurobehavioral changes were evaluated by behavioral tests; METTL14 knockdown efficiency and the expression of METTL14, METTL3, and PTEN were detected by quantitative real-time PCR (qRT-PCR) and Western blot (WB); PTEN m⁶A levels were measured by RNA immunoprecipitation-qPCR (RIP-qPCR); myelin ultrastructure, expression of myelin basic protein (MBP) and neurofascin 155 (NF155), and dendritic spine density were observed using transmission electron microscopy (TEM), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, qRT-PCR, and primary neuron culture. ResultsBehaviorally, knockdown of METTL14 significantly counteracted the beneficial effects of acupuncture in improving self-grooming, open field exploration, three-chamber social interaction, and Morris water maze learning and memory (P<0.05, P<0.01). Compared with the acupuncture+sh-NC group, the acupuncture+sh-METTL14 group showed significantly decreased mRNA and protein expression of hippocampal METTL14 (P<0.01), and the upregulating effects of acupuncture on METTL3 and PTEN expression were reversed (P<0.01). Meanwhile, knockdown of METTL14 significantly inhibited the acupuncture-induced increase in PTEN m⁶A levels (P<0.01). Morphologically, knockdown of METTL14 attenuated the improvement of myelin structure by acupuncture, reversed the downregulation of MBP and upregulation of NF155 induced by acupuncture, and blocked the increase in dendritic spine density (P<0.05, P<0.01). ConclusionMETTL14 is a key molecule mediating the therapeutic effect of acupuncture at Neiguan. Acupuncture at Neiguan upregulates METTL14, thereby enhancing m⁶A methylation modification of PTEN mRNA to stabilize its expression, ultimately promoting myelin development and improving behavioral symptoms in ASD juvenile rats. This preliminarily reveals the modern biological connotation of “opening Xuanfu and dredging myelin”.

ObjectiveTo clarify whether METTL14 mediates the core role of acupuncture at Neiguan (PC6) in promoting myelination and improving behavior in young autistic rats through gene intervention technology. MethodsThe ASD model was established by intraperitoneal injection of valproic acid (VPA) in pregnant rats. Male offspring were intracerebroventricularly injected with adenovirus-packaged METTL14 shRNA (sh-METTL14) or its control (sh-NC) on postnatal day 1, with a model group set as well. Subsequently, the juvenile rats were divided into model group, acupuncture group, acupuncture+sh-NC group, and acupuncture+sh-METTL14 group. The acupuncture group received acupuncture at Neiguan (PC6) from postnatal day 7, once daily for 21 consecutive days. Neurobehavioral changes were evaluated by behavioral tests; METTL14 knockdown efficiency and the expression of METTL14, METTL3, and PTEN were detected by quantitative real-time PCR (qRT-PCR) and Western blot (WB); PTEN m⁶A levels were measured by RNA immunoprecipitation-qPCR (RIP-qPCR); myelin ultrastructure, expression of myelin basic protein (MBP) and neurofascin 155 (NF155), and dendritic spine density were observed using transmission electron microscopy (TEM), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, qRT-PCR, and primary neuron culture. ResultsBehaviorally, knockdown of METTL14 significantly counteracted the beneficial effects of acupuncture in improving self-grooming, open field exploration, three-chamber social interaction, and Morris water maze learning and memory (P<0.05, P<0.01). Compared with the acupuncture+sh-NC group, the acupuncture+sh-METTL14 group showed significantly decreased mRNA and protein expression of hippocampal METTL14 (P<0.01), and the upregulating effects of acupuncture on METTL3 and PTEN expression were reversed (P<0.01). Meanwhile, knockdown of METTL14 significantly inhibited the acupuncture-induced increase in PTEN m⁶A levels (P<0.01). Morphologically, knockdown of METTL14 attenuated the improvement of myelin structure by acupuncture, reversed the downregulation of MBP and upregulation of NF155 induced by acupuncture, and blocked the increase in dendritic spine density (P<0.05, P<0.01). ConclusionMETTL14 is a key molecule mediating the therapeutic effect of acupuncture at Neiguan. Acupuncture at Neiguan upregulates METTL14, thereby enhancing m⁶A methylation modification of PTEN mRNA to stabilize its expression, ultimately promoting myelin development and improving behavioral symptoms in ASD juvenile rats. This preliminarily reveals the modern biological connotation of “opening Xuanfu and dredging myelin”.

Objective To investigate the effects and underlying mechanisms of a spray prepared from exosomes derived from M2 macrophages induced by interleukin-4 （IL-4） and tantalum particles （Ta） on the healing of pressure ulcers. Methods Bone marrow-derived macrophages were polarized into M2 macrophages using IL-4 or Ta, and exosomes （Exo-IL-4/Exo-Ta） were extracted. The regulatory effects of Exo-IL-4/Exo-Ta on M1 macrophage phenotypes and fibroblast matrix secretion were evaluated in vitro. Proteomic analysis was conducted to explore the biological processes and regulatory networks associated with Exo-Ta. A rat pressure ulcer model was used to assess the effects of Exo-IL-4/Exo-Ta spray on wound healing rate, inflammatory cell infiltration, and collagen deposition. Results In vitro, Exo-IL-4/Exo-Ta induced the polarization of M1 macrophages to M2 macrophages, reduced the secretion of pro-inflammatory factors, and promoted the expression of anti-inflammatory substances. Additionally, Exo-IL-4/Exo-Ta enhanced the production of collagen and fibronectin in fibroblasts. Proteomic analysis revealed that Exo-Ta primarily participated in biological processes such as energy metabolism and macromolecule biosynthesis. In vivo, Exo-IL-4/Exo-Ta spray accelerated wound healing, reduced inflammatory infiltration, and improved tissue remodeling in the rat pressure ulcer model. Conclusion Exosome sprays derived from M2 macrophages could accelerate pressure ulcer healing by modulating inflammation and promoting tissue regeneration, which demonstrated excellent clinical application potential.

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.

Objective: To evaluate the effectiveness for the construction of the "mosquito-free village" in Jinzishan Village, Fuling District, Chongqing Municipality, so as to provide references for improving mosquito control practices in hilly and mountainous rural areas. Methods: The "mosquito-free village" initiative in Fuling District was launched in April 2023. Mosquito density monitoring was conducted annually from April to October. Larval mosquito density was monitored using the path method and scoop-catch method, and adult mosquito density was monitored using human-baited landing catch. One hundred and fifty-two villagers were randomly conducted before the "mosquito-free village" construction (April 2023) and one hundred and sixty-seven villagers were randomly conducted after the construction (November 2024). Knowledge awareness rate and correct behavioral practices regarding mosquito control among villagers were assessed. The satisfaction among villagers were evaluated in November 2024. The effectiveness of the initiative was evaluated based on mosquito density data, health education outcomes from 2023 to 2024, and satisfaction. Results: The average larval mosquitoes path index in Jinshanzi Village decreased from 1.50 spots/km in 2023 to 0.07 spots/km in 2024 (P<0.05). The average sampling spoon index of larval mosquitoes decreased from 3.43% in 2023 to 0 in 2024. The average landing rate index of adult mosquitoes decreased from 3.90 mosquitoes/(person·time) in 2023 to 0.38 mosquitoes/(person·time) in 2024 (P<0.05). The awareness rate of mosquito control knowledge and the formation rate of correct behaviors among villagers increased from 59.87% and 57.24% in 2023 to 92.22% and 90.42% in 2024, respectively (both P<0.05). In 2024, the satisfaction of villagers was 92.81%. Conclusion The mosquito density, health education effectiveness, and satisfaction of villagers in Jinzishan Village have all met the evaluation criteria for a "mosquito-free village", providing a replicable model for promotion in hilly and mountainous rural areas.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.