Obesity represents a critical global health challenge characterized by a complex pathogenesis involving dysregulated adipogenesis and lipid metabolism. In recent years, long non-coding RNAs (lncRNAs) have been established as crucial regulators in the initiation and progression of obesity. These RNA molecules, typically exceeding 200 nucleotides in length, have emerged as key modulators of various biological processes through multiple molecular mechanisms. This review innovatively defines lncRNAs as “molecular switches” in energy metabolism—they regulate adipogenesis and lipid metabolism through key signaling pathways, and exert bidirectional control over obesity via ceRNA mechanisms or recruitment of chromatin-modifying complexes in tissues such as adipose and liver. Additionally, circulating lncRNAs, owing to their tissue specificity and stability, hold promise as non-invasive liquid biopsy biomarkers for obesity and related metabolic disorders. Furthermore, we systematically summarize lncRNA-based intervention strategies, including targeting pathogenic lncRNAs using antisense oligonucleotides (ASOs) or CRISPR/Cas gene editing systems, utilizing viral vectors (such as adeno-associated virus, AAV) to deliver or mimic beneficial lncRNAs in target tissues, and employing exercise as a non-pharmacological intervention that ameliorates obesity and its related complications at multiple levels, offering novel insights for personalized therapeutic approaches. We also critically assess the current challenges in clinical translation, particularly addressing issues related to delivery efficiency, target specificity, and long-term safety concerns. Future research should focus on the following directions: integrating multi-omics with functional screening to elucidate the regulatory networks of lncRNAs in obesity and its complications; leveraging artificial intelligence to construct predictive models of lncRNA-target gene interactions; developing efficient and safein vivo delivery systems, and optimizing drug design to enhance specificity and safety; establishing highly sensitive detection methods and stable circulating lncRNA biomarkers to enable precise patient stratification and real-time monitoring of therapeutic responses; investigating the synergistic effects of lncRNAs with existing treatments (e.g., GLP-1 receptor agonists, lifestyle interventions) to develop combination therapies and establish a multidimensional, personalized precision medicine framework for obesity. This review aims to provide novel perspectives for understanding the molecular mechanisms underlying obesity and to establish a solid theoretical foundation for developing lncRNA-targeted precision medicine strategies against obesity and its associated metabolic complications.

Obesity represents a critical global health challenge characterized by a complex pathogenesis involving dysregulated adipogenesis and lipid metabolism. In recent years, long non-coding RNAs (lncRNAs) have been established as crucial regulators in the initiation and progression of obesity. These RNA molecules, typically exceeding 200 nucleotides in length, have emerged as key modulators of various biological processes through multiple molecular mechanisms. This review innovatively defines lncRNAs as “molecular switches” in energy metabolism—they regulate adipogenesis and lipid metabolism through key signaling pathways, and exert bidirectional control over obesity via ceRNA mechanisms or recruitment of chromatin-modifying complexes in tissues such as adipose and liver. Additionally, circulating lncRNAs, owing to their tissue specificity and stability, hold promise as non-invasive liquid biopsy biomarkers for obesity and related metabolic disorders. Furthermore, we systematically summarize lncRNA-based intervention strategies, including targeting pathogenic lncRNAs using antisense oligonucleotides (ASOs) or CRISPR/Cas gene editing systems, utilizing viral vectors (such as adeno-associated virus, AAV) to deliver or mimic beneficial lncRNAs in target tissues, and employing exercise as a non-pharmacological intervention that ameliorates obesity and its related complications at multiple levels, offering novel insights for personalized therapeutic approaches. We also critically assess the current challenges in clinical translation, particularly addressing issues related to delivery efficiency, target specificity, and long-term safety concerns. Future research should focus on the following directions: integrating multi-omics with functional screening to elucidate the regulatory networks of lncRNAs in obesity and its complications; leveraging artificial intelligence to construct predictive models of lncRNA-target gene interactions; developing efficient and safein vivo delivery systems, and optimizing drug design to enhance specificity and safety; establishing highly sensitive detection methods and stable circulating lncRNA biomarkers to enable precise patient stratification and real-time monitoring of therapeutic responses; investigating the synergistic effects of lncRNAs with existing treatments (e.g., GLP-1 receptor agonists, lifestyle interventions) to develop combination therapies and establish a multidimensional, personalized precision medicine framework for obesity. This review aims to provide novel perspectives for understanding the molecular mechanisms underlying obesity and to establish a solid theoretical foundation for developing lncRNA-targeted precision medicine strategies against obesity and its associated metabolic complications.

ObjectiveTo evaluate the predictive value of epicardial adipose tissue （EAT） parameters for microvascular obstruction （MVO） formation in patients with ST segment elevation myocardial infarction （STEMI） using cardiac magnetic resonance quantification. MethodsA total of 139 STEMI patients were included in this study， and various parameters such as EAT thickness， volume， and mass index were measured utilizing cardiac magnetic resonance. All included patients were divided into MVO group and non-MVO group according to whether MVO occurred. Differences in EAT related parameters between two groups were compared and correlation analysis was applied to evaluate the correlation between quantitative indicators of EAT and indicators such as infarct size and ejection fraction. Logistic regression analysis was used to identify the relevant risk factors for MVO formation. Receiver Operating Characteristic （ROC） curve analysis was performed to assess the predictive value of the epicardial adipose tissue （EAT） quality index and other indicators for the occurrence of MVO. ResultsCompared with non MVO group， patients in MVO group presented with higher peak troponin T levels， increase of neutrophil lymphocyte ratio （NLR） and C-reactive protein （CRP）， larger infarct size and compromised left ventricular ejection fraction （LVEF） （P<0.05）. Total EAT volume， EAT mass index， left atrioventricular EAT volume， left atrioventricular EAT mass index and thickness of EAT in the left atrioventricular groove were significantly higher in patients with MVO. Multivariate Logistic regression analysis demonstrated that NLR， peak troponin T levels and left atrioventricular EAT mass index were independent predictors of MVO. The ROC curve suggested that the left atrioventricular EAT mass index had the highest predictive power for MVO formation in STEMI patients. ConclusionThe parameters of EAT quantified by cardiac magnetic resonance serve as imaging biomarkers for predicting MVO formation in STEMI patients. These metrics enable risk stratification post-myocardial infarction and facilitate early identification of high-risk individuals， thereby supporting personalized therapeutic decision-making.

Despite significant advances in the field of critical care medicine over the past three decades, veno-arterial extracorporeal membrane oxygenation (V-A ECMO) remains the primary temporary mechanical circulatory support modality for patients with acute severe circulatory failure. With the accumulation of clinical experience and the increasing maturity of operational techniques in V-A ECMO, its technical management—particularly hemodynamic management—has become a key factor influencing patient outcomes. To further improve patient survival, the Chinese Critical Care Ultrasound Study Group, in collaboration with the Hemodynamic Therapy of Critical Care Collaborative Group and the Critical Care Medicine Branch of the China International Exchange and Promotive Association for Medical and Health Care, organized experts in critical care medicine to develop the Consensus on Hemodynamic Management in Adult Veno-Arterial Extracorporeal Membrane Oxygenation (2026 Edition). Based on years of clinical experience and the latest evidence-based medical evidence, this consensus formulates 15 systematic recommendations covering the entire process of V-A ECMO, including initiation, management during support, and weaning, aiming to promote standardized application of hemodynamic management in V-A ECMO.

ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.

ObjectiveTo explore the expression levels of long non-coding RNA （lncRNA） H19 and microRNA-22-3p （miR-22-3p） in the serum of patients with acute myocardial infarction （AMI） and their diagnostic value for AMI. MethodsA total of 176 AMI patients were selected as the experimental group and were divided into ST-segment elevation myocardial infarction （STEMI） group （n=95） and non-ST-segment elevation myocardial infarction （NSTEMI） group （n=81） based on their medical history and electrocardiogram. Meanwhile， 156 patients with negative angiography during the same period were selected as the control group （CON group）. The relative expression levels of lncRNA H19 and miR-22-3p in the serum of the two groups were detected by real-time fluorescence quantitative polymerase chain reaction. The diagnostic value of miR-22-3p and lncRNA H19 in AMI was evaluated by receiver operating characteristic curve （ROC） analysis. The levels of serum cardiac troponin I （cTnI）， creatine kinase （CK）， creatine kinase MB isoenzyme （CK-MB）， and high-sensitivity C-reactive protein （CRP） were detected in all study subjects. Spearman correlation analyses were used to evaluate the correlations between lncRNA H19 and miR-22-3p and cTnI， CK， CK-MB and CRP. ResultsCompared with the control group， the expression level of lncRNA H19 was upregulated and the expression level of miR-22-3p was downregulated in the AMI group （all P<0.01）； compared with the NSTEMI group， the expression level of lncRNA H19 was upregulated and the expression level of miR-22-3p was downregulated in the STEMI group （P<0.01）. The areas under the ROC curves （AUC） for the diagnosis of AMI by miR-22-3p， lncRNA H19 and their combination were 0.555， 0.977， and 0.983， respectively. lncRNA H19 was positively correlated with cTnI， CK， CK-MB and CRP （P<0.05）， and negatively correlated with left ventricular ejection fraction （LVEF） （P<0.001）； miR-22-3p was negatively correlated with cTnI， CK and CRP， and positively correlated with LVEF （P<0.05）. ConclusionThe expression level of lncRNA H19 is elevated and the expression level of miR-22-3p decreased in AMI patients， and their levels may have potential value as an auxiliary biomarker for AMI diagnosis and cardiac function assessment.

Patients with lung cancer experience a heavy symptom burden during the perioperative period, which seriously affects their recovery and quality of life. Traditional symptom management models rely mainly on scheduled ward rounds during hospitalization and outpatient follow-up after discharge. However, they have limitations such as delayed symptom recognition, lack of post-discharge monitoring, and non-quantitative symptom assessment, which often lead to delayed interventions and low patient satisfaction. In recent years, the symptom management model based on electronic patient-reported outcomes (ePRO) has been increasingly valued in clinical practice. Existing high-level evidence from both domestic and international studies indicates that, through proactive monitoring, real-time alerts, and remote interventions, this model enables dynamic and continuous symptom management and helps improve patient recovery and healthcare experience. As a supplement to routine medical care, the ePRO-based symptom management model aims to enhance the quality of care rather than replace existing medical processes. To promote the standardized application of this model in perioperative lung cancer care, this consensus integrates domestic and international evidence. After multiple rounds of voting by more than 50 experts, it formulates 12 consensus statements covering the three core components, symptom monitoring, alerting, and intervention, to provide scientific and practical recommendations for clinical practice.

Objective: To establish a machine learning-based precision blood donor recruitment model at the county level and assess its generalizability and applicability. Methods: A retrospective study was conducted using blood donation and SMS recruitment data from the Taicang Branch of the Suzhou Blood Center between 2019 and 2024. Multiple machine learning algorithms were employed, including extreme gradient boosting, support vector machine, k-nearest neighbor, logistic regression, decision tree, random forest, and multilayer perceptron. These were combined with techniques such as synthetic minority oversampling, undersampling, and cost-sensitive learning (using MFE and MSFE loss functions). Model parameters were optimized through grid search to identify the best-performing model. Results: In a prospective comparative study against conventional methods, the machine learning models increased the recruitment success rate among high-willingness donors by an average of 129.15%, and the recruitment efficiency per SMS improved by 125.02% compared with the traditional method. Under full-scale SMS sending, the recruitment rate per SMS increased by 42.61%, and SMS sending efficiency improved by 31.77%, significantly enhancing recruitment performance. Conclusion: This study represents the first application of a machine learning-based precision donor recruitment model at the county-level in China. The precise recruitment framework not only improves recruitment efficiency and reduces recruitment costs but also demonstrates strong scalability and generalizability. It provides a scientific and feasible intelligent pathway to ensure the safety and sustainability of the blood supply.

Objective To explore the impact of ondansetron's use within 24 h before delirium assess-ment in ICU patients on the risk of delirium occurrence.Methods All data were derived from the Critical Care Medical Information Database(MIMIC)-Ⅲ,MIMIC-Ⅳ and the eICU Collaborative Research Database.The research subjects were the patients who were admitted to ICU for treatment for the first time and had re-cords of delirium assessment.The research variable was whether ondansetron was used within 24 h before de-lirium assessment.The main observation indicator was whether delirium occurred after the patient entering to ICU,and whether the patient died during hospitalization or was discharged and returned home was taken as the secondary observation indicator.The propensity score matching eliminated confounding factors,and the stepwise logistic regression and nearest neighbor matching were used to analyze the influencing factors.Results A total of 78 364 patients had the delirium assessment records,among them 22 158 patients had the positive assessment results.A total of 294 patients who used ondansetron within 24 h before delirium assess-ment were taken as the ondansetron group,and 78 070 patients who did not use ondansetron were taken as the control group.Propensity score matching corrected most of the covariates between the two groups.The results of multivariate logistic regression analysis showed that the use of ondansetron was a protective factor for the delirium occurrence(OR=0.72,95％CI:0.53-0.96),and the results of nearest neighbor matching analysis also supported this association(OR=0.48,95％CI:0.31-0.76).However,the use of ondansetron had no effect on the outcome of in-hospital death or discharge home for critically ill patients(P＞0.05).Conclusion Ondansetron may be an effective drug for the prevention or treatment of delirium in critically ill patients.

Poly(lactic-co-glycolide)(PLGA)is a key excipient in long-acting sustained-release preparations,and its degradation properties directly affect the drug release behavior.In this study,PLGA microspheres were prepared by microfluidic techniques,and the morphology changes of the microspheres were observed by scanning electron microscopy(SEM).In alkaline environment,due to the accelerated hydrolysis of ester bonds,the surface of the microspheres was rapidly dissolved and eroded,and the degradation rate was significantly higher than that in acidic environment.High temperature accelerated the degradation of PLGA microspheres.Under neutral and alkaline conditions,the microspheres showed aggregation and adhesion.Under acidic conditions,the microspheres gradually decomposed into irregular fragments.The high ionic strength further promoted the surface corrosion of the microspheres,especially under extreme pH conditions.Simultaneously,PLGA microspheres encapsulating coumarin were prepared to simulate the microsphere formulation.The release rate of coumarin after degradation of the microspheres under different conditions was observed by measuring the absorbance with ultraviolet-visible spectrophotometry.The results were consistent with those of the blank microspheres.This study revealed that the degradation of PLGA microspheres was significantly pH-dependent,temperature sensitive and ion strength responsive.These findings not only helped to understand and optimize the long-term stability and controlled release performance of drug-carrying microspheres,but also provided a theoretical basis for further improvement of PLGA-based drug carrier design.