Metabolic dysfunction-associated steatotic liver disease (MASLD) has become the most prevalent chronic liver disease worldwide, affecting approximately 32%-38% of the adult population and posing a growing public health burden. MASLD represents a continuous disease spectrum ranging from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH), progressive hepatic fibrosis, cirrhosis, and ultimately hepatocellular carcinoma (HCC). The pathological core of MASLD lies in disruption of hepatic lipid metabolic homeostasis, characterized by an imbalance among de novo lipogenesis, fatty acid β-oxidation, and very-low-density lipoprotein (VLDL)-mediated lipid export. This metabolic disequilibrium subsequently drives inflammatory injury and fibrotic progression. Among the multiple regulatory pathways involved, thyroid hormone (TH) signaling has emerged as a central regulator of hepatic metabolic homeostasis. The liver is a major peripheral target organ of TH action, where TH predominantly exerts its metabolic effects through thyroid hormone receptor β (TRβ). Large-scale epidemiological studies and meta-analyses have demonstrated that hypothyroidism is significantly associated with increased MASLD prevalence, more severe histological injury, and advanced hepatic fibrosis, suggesting that dysregulation of TH signaling may participate throughout the entire MASLD disease spectrum. At the molecular level, TH regulates hepatic lipid metabolism by coordinating suppression of lipogenesis, enhancement of mitochondrial fatty acid oxidation, and promotion of VLDL assembly and secretion through integrated genomic actions of the T3-TRβ axis and non-genomic signaling pathways. Across different stages of MASLD, TH signaling exerts stage-dependent protective effects. In the steatosis stage, TH improves metabolic flexibility by modulating insulin sensitivity, glucose metabolism, and lipid droplet clearance, thereby alleviating early lipotoxic stress. During progression to MASH, TH attenuates inflammatory amplification by improving mitochondrial homeostasis, suppressing activation of the NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome, and modulating the gut-liver axis microenvironment. In advanced stages, TH signaling influences hepatic stellate cell activation and extracellular matrix deposition, partly through interaction with the transforming growth factor-β (TGF-β)/SMAD pathway, while alterations in intrahepatic TH availability, mediated by dynamic changes in iodothyronine deiodinase 1 (DIO1), contribute to fibrosis progression and hepatocellular dedifferentiation. In hepatocellular carcinoma, coordinated downregulation of TRβ and DIO1 establishes a tumor-associated hypothyroid state that promotes metabolic reprogramming and tumor progression. The clinical relevance of TH signaling in MASLD has been underscored by the recent approval of Resmetirom, a liver-targeted TRβ‑selective agonist, for the treatment of non-cirrhotic MASH with moderate-to-severe fibrosis (F2-F3). This approval represents a landmark transition from mechanistic understanding to metabolism-centered precision therapy in MASLD. Clinical trials have demonstrated that Resmetirom not only improves key histological endpoints, including MASH resolution and fibrosis regression, but also favorably modulates atherogenic lipid profiles, highlighting the therapeutic potential of selectively targeting hepatic TH pathways. This review systematically summarizes the multidimensional regulatory roles of TH across the MASLD disease spectrum and discusses emerging diagnostic and therapeutic implications of TH-based interventions, aiming to inform future mechanistic research and optimize clinical management strategies.

With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

AIM To study the chemical constituents from Inula japonica Thunb.and their anti-asthmatic activity.METHODS Separation and purification were performed using silica gel and Sephadex LH-20,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The effect of compounds on the release rate of β-Hex was evaluated by substrate coloration method.RESULTS Twenty-three compounds were isolated and identified as dehydrodontic acid(1),vitexin(2),alternariol(3),globuxanthone(4),1,3,6,7-tetrahydroxyxanthone(5),hydroxyhydrolapachol(6),isoscopoletin(7),elephanmollen(8),benzoylcholine(9),hoconobiflavone(10),clovandiol(11),hydroxydihydrobovolide(12),5,7-dihydroxycoumarin(13),scopoletin(14),orlichenol glucoside(15),urolignoside(16),9-angeloyloxythymol(17),6,3′,4′-trihydroxyaurone(18),flufuran(19),sweroside(20),guajadial(21),5,7,4′-trimethoxy-4-phenylcoumarin(22),dibutylphthalate(23).After intervention with compounds 9 and 16,the release rates of β-Hex were(56.64±2.37)％and(58.07±2.29)％,respectively.CONCLUSION Compounds 1-23 are isolated from Ⅰ.japonica for the first time.Compounds 9 and 16 have anti-asthmatic activity.

Although teniposide(VM26)is widely used in the treatment of lymphoma,its poor water sol-ubility,low bioavailability and systemic toxicities still limit its clinical application.Nano-delivery systems are effective in increasing the bioavailability and reducing the toxicity of VM26,but there is an urgent need to overcome the problem of its non-specific targeting.Therefore,in this paper,we designed and constructed a hyaluronic acid-modified teniposide-targeted nano-delivery system(VM26-TNDS),and characterised its drug encapsulation rate,particle size and zeta potential.We also investigated the effects of VM26-TNDS on B-cell lymphoma cells with different expression of CD44 receptor,in terms of cellular targeting,inhibitory effect of proliferation,and induction of apoptosis and necrosis.The results showed that the drug encapsulation efficiency of VM26-TNDS exceeded 85％,and its liquid formulation could be stably stored at 4 ℃ for more than 6 months without precipitation.Based on CD44 receptor expression,Granta-519(high expression),Raji(medium-low expression)and SU-DHL-4(almost no expression)were screened for cellular experiments.Compared with VM26-NDS,the targeted modification could effec-tively reduce the uptake of VM26-TNDS by RAW264.7 and increase the uptake of VM26-TNDS by CD44 receptor-expressing lymphoma cells.The inhibitory proliferative effect and apoptotic necrosis-inducing a-bility of VM26-TNDS were stronger than those of VM26-NDS for Granta-519 and Raji cells,whereas there was no significant difference in the inhibitory effect on proliferation and ability to induce apoptosis and necrosis between VM26-NDS and VM26-TNDS in SU-DHL-4 cells,reflecting the targeting advantage for VM26-TNDS,as expected.However,its toxic effect on B-cell lymphoma cells only reflected the targeting advantage at some concentrations(0.25 μmol/L and 0.5 μmol/L),which met the expectation.The a-bove results indicate that a teniposide-targeted nano-delivery system,VM26-TNDS,has been successfully prepared in this study.VM26-TNDS improves the delivery efficiency of VM26 by targeting human B-cell lymphoma cells expressing the CD44 receptor,thus killing human B-cell lymphoma cells more effectively and overcoming the problem of non-specific targeting in drug delivery to improve the therapeutic effect.Its biological therapeutic effects and mechanisms still need to be proved by more in vitro and in vivo ex-perimental evidence.

Paraplegia caused by spinal cord injury is a serious neurological complication, for which surgery is currently the main treatment method. Due to different surgical approaches, patients are usually expected to maintain a passive prone position for a long time or switch between the supine and prone positions. Affected by multiple factors such as neurogenic sensory disorders, pathological changes in muscle tone and operative duration, the risk of intraoperative acquired pressure injury (IAPI) is significantly increased. Current clinical prevention strategies for IAPI in these patients predominantly focus on localized pressure relief during positioning, lacking systematic, standardized comprehensive prevention protocols or evidence-based guidelines. To address it, Department of Nursing, Orthopedics Branch, China International Exchange and Promotive Association for Medical and Health Care, Spinal Trauma Professional Committee, Orthopedics Branch, Chinese Medical Doctor Association, Nursing Group of Spine and Spinal Cord Professional Committee of Chinese Association of Rehabilitation Medicine organized experts in relevant fields to formulate Guideline for the prevention of intraoperative acquired pressure injury in paraplegic patients with spinal cord injury ( version 2025), based on evidence-based medical evidence and latest research results and clinical practice at home and abroad. Eleven recommendations were put forward from the aspects of preoperative risk assessment, intraoperative prevention strategies, postoperative handover and monitoring, and supportive mechanisms for IAPI prevention, aiming to standardize the prevention measures and management strategies of IAPI in paraplegic patients with spinal cord injury and accelerate the recovery of patients and improve the therapeutic effect.

Although teniposide(VM26)is widely used in the treatment of lymphoma,its poor water sol-ubility,low bioavailability and systemic toxicities still limit its clinical application.Nano-delivery systems are effective in increasing the bioavailability and reducing the toxicity of VM26,but there is an urgent need to overcome the problem of its non-specific targeting.Therefore,in this paper,we designed and constructed a hyaluronic acid-modified teniposide-targeted nano-delivery system(VM26-TNDS),and characterised its drug encapsulation rate,particle size and zeta potential.We also investigated the effects of VM26-TNDS on B-cell lymphoma cells with different expression of CD44 receptor,in terms of cellular targeting,inhibitory effect of proliferation,and induction of apoptosis and necrosis.The results showed that the drug encapsulation efficiency of VM26-TNDS exceeded 85％,and its liquid formulation could be stably stored at 4 ℃ for more than 6 months without precipitation.Based on CD44 receptor expression,Granta-519(high expression),Raji(medium-low expression)and SU-DHL-4(almost no expression)were screened for cellular experiments.Compared with VM26-NDS,the targeted modification could effec-tively reduce the uptake of VM26-TNDS by RAW264.7 and increase the uptake of VM26-TNDS by CD44 receptor-expressing lymphoma cells.The inhibitory proliferative effect and apoptotic necrosis-inducing a-bility of VM26-TNDS were stronger than those of VM26-NDS for Granta-519 and Raji cells,whereas there was no significant difference in the inhibitory effect on proliferation and ability to induce apoptosis and necrosis between VM26-NDS and VM26-TNDS in SU-DHL-4 cells,reflecting the targeting advantage for VM26-TNDS,as expected.However,its toxic effect on B-cell lymphoma cells only reflected the targeting advantage at some concentrations(0.25 μmol/L and 0.5 μmol/L),which met the expectation.The a-bove results indicate that a teniposide-targeted nano-delivery system,VM26-TNDS,has been successfully prepared in this study.VM26-TNDS improves the delivery efficiency of VM26 by targeting human B-cell lymphoma cells expressing the CD44 receptor,thus killing human B-cell lymphoma cells more effectively and overcoming the problem of non-specific targeting in drug delivery to improve the therapeutic effect.Its biological therapeutic effects and mechanisms still need to be proved by more in vitro and in vivo ex-perimental evidence.

AIM To study the chemical constituents from Inula japonica Thunb.and their anti-asthmatic activity.METHODS Separation and purification were performed using silica gel and Sephadex LH-20,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The effect of compounds on the release rate of β-Hex was evaluated by substrate coloration method.RESULTS Twenty-three compounds were isolated and identified as dehydrodontic acid(1),vitexin(2),alternariol(3),globuxanthone(4),1,3,6,7-tetrahydroxyxanthone(5),hydroxyhydrolapachol(6),isoscopoletin(7),elephanmollen(8),benzoylcholine(9),hoconobiflavone(10),clovandiol(11),hydroxydihydrobovolide(12),5,7-dihydroxycoumarin(13),scopoletin(14),orlichenol glucoside(15),urolignoside(16),9-angeloyloxythymol(17),6,3′,4′-trihydroxyaurone(18),flufuran(19),sweroside(20),guajadial(21),5,7,4′-trimethoxy-4-phenylcoumarin(22),dibutylphthalate(23).After intervention with compounds 9 and 16,the release rates of β-Hex were(56.64±2.37)％and(58.07±2.29)％,respectively.CONCLUSION Compounds 1-23 are isolated from Ⅰ.japonica for the first time.Compounds 9 and 16 have anti-asthmatic activity.

Objective:To analyze the predictive role of WT1 expression levels pre-and early post-transplantation on relapse and overall survival(OS)in patients with acute myeloid leukemia(AML)undergoing allogeneic hematopoietic stem cell transplantation(allo-HSCT)during their first complete remission(CR1).Methods:A retrospective analysis was conducted on the clinical data of 107 adult AML patients who underwent allo-HSCT during their CR1 at our center between May 2012 and December 2021.The predictive role of bone marrow WT1 expression levels before transplantation and at 3 and 6 months post-transplantation on relapse and OS was explored in combination with relevant clinical factors.Results:The median follow-up time for the 107 patients was 70(range:11-117)months.Among the patients,15 cases died.Kaplan-Meier survial analysis showed that the 3-year overall survival(OS)rate was 85.0％.20 patients experienced relapse,with a median time to relapse of 8(range:0.5-44)months and a l-year cumulative relapse rate of 13.1％.The overall median value of WT1 before transplantation,3 months after transplantation,and 6 months after transplantation was 0.26％(range:0％-23.64％),with an upper quartile value of 0.74％.No statistically significant differences in WT1 expression levels were observed among the pre-transplantation,3-month post-transplantation,and 6-month post-transplantation time points(P=0.227).Univariate analysis showed that patients with WT1 levels＞0.74％at 3 months post-transplantation had a higher 1-year relapse rate(P=0.029)and lower 3-year OS rate(P＜0.001)compared to patients with WT1 levels ≤0.74％.Other significant factors affecting 1-year relapse included stem cell source(P=0.041)and chronic graft-versus-host disease(cGVHD)(P=0.013).For 3-year OS,additional influencing factors were genetic high risk(P=0.048)and stem cell source(P=0.016).Multivariate analysis revealed that WT1 level＞0.74％at 3 months post-transplantation had a trend to affect 1-year relapse rate(HR=3.309,95％CI:0.958-11.431,P=0.058),while the absence of cGVHD was an independent risk factor for 1-year relapse(HR=3.473,95％CI:0.749-16.100,P=0.037).Only WT1 level＞0.74％at 3 months post-transplantation was an independent risk factor for 3-year OS(HR=6.886,95％CI:2.402-19.738,P＜0.001).Conclusion:High WT1 expression level at 3 months post-transplantation in AML patients undergoing allo-HSCT during CR1 affects the 1-year relapse rate and 3-year OS,and is an independent risk factor affecting 3-year OS.These findings suggest that dynamic monitoring of WT1 expression levels has certain value in prognostic assessment of AML patients who received allo-HSCT during CR1.

Objective:To evaluate the effect of lifestyle interventions based on mobile health technolo-gy on gestational weight gain among overweight or obese pregnant women,to explore the influencing fac-tors of the intervention effect,and to provide scientific evidence for weight management during pregnan-cy.Methods:The randomized controlled trial(RCT)design was used.From April 2024 to August 2024,200 singleton overweight or obese pregnant women aged 18-40 years in early pregnancy were re-cruited and stratified block-randomized according to body mass index(BMI)categories,age,and parity.The control group received routine prenatal care,while the intervention group received lifestyle interven-tions based on mobile health technology,which included biweekly face-to-face or telephone sessions;weekly recording of dietary behavior goals with personalized feedback on WeChat public account;6 000 steps per day and 150 minutes of brisk walking per week;and weekly weight recording with personalized feedback.Based on the intention-to-treat principle,generalized linear mixed models were used to analyze the effects on weight gain and weight gain rate up to 24-28 gestational weeks,gestational diabetes melli-tus(GDM),and dietary and physical activity behaviors.Additionally,subgroup analysis and interaction analysis were conducted to explore whether intervention effects on weight gain varied by different maternal characteristics.Results:The mean age of the women in the intervention and control groups was(30.49±3.99)years and(29.83±3.95)years,respectively,with gestational weeks at enrollment being(11.35±1.61)weeks and(11.26±1.52)weeks.No statistically significant differences were observed in the baseline characteristics between the two groups(P＞0.05).In the study,10 and 12 participants were lost to the follow-up in the intervention and control groups,respectively,with 178 women comple-ting the midterm follow-up.At the midterm follow-up(24-28 weeks),the weight gain in the interven-tion and control groups was(5.00±3.72)kg and(6.57±4.28)kg,respectively.After adjusting for age,parity,gravidity,region,pre-pregnancy BMI categories,and socioeconomic status,the between-group difference was-1.63 kg(95％CI:-2.80 to-0.46;P=0.007).The adjusted between-group difference in weight gain rate was-0.07 kg/week(95％CI:-0.11 to-0.02;P=0.005).Com-pared with the control group,the intervention group had lower fasting blood glucose at the oral glucose tolerance test(OGTT)by 0.19 mmol/L(95％CI:0.04 to0.33;P=0.013).No significant difference was observed in GDM incidence between the two groups.Among different subgroups based on characteris-tics,such as age,region,socioeconomic status,and parity,there was no statistically significant dif-ference in the effect on weight gain.Conclusion:The lifestyle interventions based on mobile health tech-nology effectively controlled weight gain up to 24-28 gestational weeks among overweight or obese women and improved fasting blood glucose level.This has significant public health implications for impro-ving the health of overweight or obese pregnant women in China.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.