ObjectiveThis study aimed to establish a monocrotaline （MCT）-induced pulmonary arterial hypertension （PAH） rat model to systematically evaluate the protective effect of Xiao Qinglongtang （XQLT） on right cardiac function in model rats and further elucidate the underlying regulatory mechanism. MethodsSixty male SD rats were randomly assigned to the normal group， model group， XQLT low-， medium-， and high-dose groups （XQLT-L/M/H）， and the beraprost sodium tablet group （BST）. Except for the normal group， rats in all other groups were given a single subcutaneous injection of MCT （60 mg·kg^-1） to induce PAH. Three weeks after injection， rats in the XQLT-L/M/H groups were administered XQLT intragastrically at 3.07， 6.14， 12.28 g·kg^-1·d^-1， respectively. Rats in the BST group received beraprost sodium at 12.6 μg·kg^-1·d^-1， and rats in the model group received an equal volume of saline. All treatments lasted for 3 weeks. Right ventricular systolic pressure （RVSP） was measured by right ventricular catheterization. Cardiac function was assessed by echocardiography. The right ventricle was weighed to calculate the right ventricular hypertrophy index （RVHI）. Hematoxylin-eosin （HE） staining， Masson staining， and transmission electron microscopy were used to observe myocardial morphology. Serum metabolomic changes were analyzed using ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS）. Data-independent acquisition （DIA） proteomics was used to detect differentially expressed （DE） proteins in the right ventricle， and Western blot was used to measure the expression of uncoupling protein 3 （UCP3）， phosphatidylinositol 3-kinase catalytic subunit p110α （PIK3CA）， L1 cell adhesion molecule （L1CAM）， and quinone oxidoreductase （CRYZ）. UPLC-MS/MS was used to analyze the chemical components of XQLT. ResultsCompared with the normal group， the model group showed significantly increased RVSP and RVHI （P<0.05）， along with pathological changes in myocardial morphology. Compared with the model group， all XQLT-treated groups exhibited reductions in RVSP and RVHI as well as significant improvements in cardiac function and myocardial morphology. Among the XQLT groups， XQLT-M showed the most pronounced effects （P<0.05）， comparable to the BST group. Serum metabolomics revealed 105 differential metabolites in the XQLT groups versus the model group ［variable importance in projection （VIP） >1， P<0.05］， including 58 upregulated and 47 downregulated metabolites. KEGG enrichment analysis indicated that XQLT intervention downregulated phenylalanine metabolism （P<0.01） and upregulated unsaturated fatty acid biosynthesis （P<0.05）. Proteomics analysis showed that 982 DE proteins were identified in the MCT groups versus the normal group， including 455 upregulated and 527 downregulated proteins （|fold change （FC）| >1.3， P<0.05）. Compared with the model group， 237 DE proteins were identified in the XQLT groups， including 124 upregulated and 113 downregulated proteins （|FC| >1.3， P<0.05）， with 57 overlapping DE proteins. KEGG enrichment suggested that XQLT mainly modulated pathways related to mineral absorption， ribosomal biogenesis， peroxisomes， glycolysis/gluconeogenesis， spliceosomes， and thyroid hormone signaling. Western blot analysis showed that， compared with the model group， XQLT increased the expression of UCP3， PIK3CA， and L1CAM， while decreasing the expression of CRYZ （P<0.05）. ConclusionXQLT exerts a protective effect on right heart function in MCT-induced PAH rats， and its mechanism is associated with maintaining myocardial homeostasis and alleviating right ventricular remodeling.

[摘 要] 目的：探究纺锤体蛋白1（SPIN1）促进胃腺癌细胞迁移与侵袭的分子机制。方法: 通过TCGA数据库数据分析胃腺癌组织中SPIN1 mRNA表达与上皮间质转化（EMT）评分、血管生成评分间的相关性。收集2018年8月至2021年11月期间山东第一医科大学附属省立医院手术切除的52例胃腺癌患者的癌组织制成组织芯片，每例均包含胃腺癌组织、对应癌旁组织及淋巴结转移灶，通过免疫组织化学法检测胃腺癌组织中SPIN1与STAT3的蛋白表达水平及相关性。通过Transwell实验研究干扰SPIN1对胃腺癌细胞侵袭与迁移的影响。使用GEPIA2网站分析SPIN1基因与Janus-激酶/信号转导和转录激活因子（JAK/STAT）通路相关因子在胃腺癌中的表达相关性。通过qPCR法、WB法检测干扰SPIN1后JAK/STAT通路相关mRNA和蛋白的表达变化。结果: TCGA数据库数据分析结果显示，SPIN1表达与EMT评分和血管生成评分呈正相关（均P < 0.05）。SPIN1与STAT3在胃腺癌组织和淋巴结转移灶中表达升高（均P < 0.05），在癌旁胃黏膜组织中阴性表达。SPIN1与STAT3的表达显著正相关（P < 0.05）。干扰SPIN1后胃腺癌细胞的迁移、侵袭能力明显降低（P < 0.05或P < 0.01）。GEPIA2网站分析结果显示，SPIN1基因与JAK1、JAK2、STAT1、STAT2及STAT3表达均呈显著正相关（均P < 0.05）。干扰SPIN1后JAK2、STAT3的mRNA水平下降，而JAK1、STAT1、STAT2的mRNA水平变化不明显。WB法实验结果表明，干扰SPIN1后JAK2、STAT3、p-JAK2及p-STAT3的蛋白表达均显著降低（均P < 0.01），过表达SPIN1后JAK2、STAT3、p-JAK2及p-STAT3的蛋白表达均显著升高（均P < 0.01）。结论: SPIN1可通过参与JAK2/STAT3信号通路促进胃腺癌细胞迁移与侵袭。

The onset and progression of chronic heart failure （CHF） are closely associated with myocardial energy metabolism disorders， and this pathological process significantly affects patient prognosis. Traditional Chinese medicine （TCM）， grounded in time-based medical theories such as the correspondence between humans and nature and the theory of circadian flow of meridians （Ziwu Liuzhu）， exhibits intrinsic consistency with modern circadian rhythm theory， providing a unique theoretical framework for understanding and intervening in CHF from a temporal perspective. This article systematically explores the impact of circadian rhythms on energy metabolism and the potential mechanisms by which TCM active ingredients intervene in CHF through a review of relevant literature. It is found that various TCM active ingredients， including flavonoids （such as nobiletin）， alkaloids （such as berberine）， and polyphenols （such as resveratrol）， can improve mitochondrial function， promote fatty acid oxidation， enhance glucose uptake and utilization efficiency， maintain metabolic balance， and alleviate oxidative stress and inflammatory responses in myocardial cells by regulating the expression and rhythms of core circadian clock genes such as CLOCK， BMAL1， PER， and CRY. These actions thereby correct energy metabolism disorders and improve cardiac function. Further exploration of the interaction mechanisms between these components and the circadian rhythms holds promise for providing novel theoretical foundations and potential intervention strategies for the prevention and treatment of CHF.

Intravitreal anti-vascular endothelial growth factor(anti-VEGF)therapy has been widely used, but the variability in its therapeutic efficacy limits individualized treatment. In recent years, the application of artificial intelligence(AI)has opened up new avenues for personalized treatment response prediction, and its core branches include machine learning(ML)and deep learning(DL). This review systematically retrieved and analyzed 41 relevant studies published up to April 2025. Comprehensive analysis reveals that AI predictive models are evolving from forecasting single endpoints(such as visual acuity or central retinal thickness)to integrating multi-dimensional endpoints(encompassing anatomical, functional, and treatment demand parameters)and generating predictive imaging outputs. In terms of technical approaches, DL models(28 studies, accounting for 68.3%)dominate this field due to their robust image interpretation capabilities, while ML models(10 studies, 24.4%)retain significant value in the analysis of structured clinical data. Cross-disease comparisons indicate that research efforts are most concentrated on age-related macular degeneration(ARMD)and diabetic macular edema(DME), with shared conceptual frameworks for model construction, yet distinct anatomical and functional indicators are prioritized for each disease. Currently, the field confronts several key challenges, including insufficient prospective clinical validation, limited model interpretability(the “black box problem”), and a scarcity of high-quality multi-center datasets. Moving forward, it is imperative to advance real-world validation and develop explainable AI techniques to expedite the clinical translation of these predictive models.

Gastric variceal rupture and bleeding and hepatic encephalopathy are common and life-threatening complications in decompensated cirrhosis. As a minimally invasive interventional technique， balloon-occluded retrograde transvenous obliteration （BRTO） has made significant progress in the clinical management of gastric varices and hepatic encephalopathy in recent years. This article systematically reviews the technical principles， indications （e.g.， isolated gastric varices and refractory hepatic encephalopathy）， clinical efficacy （an acute hemostasis rate of 85% — 95%， a 1-year rebleeding rate of <15%， and an improvement rate of 60% — 80% for hepatic encephalopathy）， and safety （including complications such as renal impairment and elevated portal vein pressure） of BRTO. Meanwhile， this article discusses the advantages and disadvantages of BRTO and conventional treatment modalities （e.g.， transjugular intrahepatic portosystemic shunt and endoscopic treatment） and reviews the latest technological improvements in recent years， such as coil-assisted retrograde transvenous obliteration and plug-assisted retrograde transvenous obliteration. Future research should focus on the precision of patient selection （e.g.， stratification based on hemodynamic parameters）， the optimization of embolic materials （e.g.， application of new biodegradable embolic agents）， and the development of individualized treatment regimens， so as to improve efficacy and reduce the risk of complications.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

ObjectiveCleft palate (CP) is a common congenital deformity often associated with velopharyngeal insufficiency (VPI), which disrupts the physiological coupling between respiration and speech. Conventional clinical assessments, such as nasometry and spirometry, provide limited static data and fail to visualize the dynamic spatiotemporal distribution of lung ventilation during phonation. This study introduces spatiotemporal electrical impedance tomography (ST-EIT) to evaluate speech-respiratory functional features in CP patients compared to normal controls (NC). The aim is to characterize multi-domain respiratory patterns and to validate an interpretable machine learning framework for providing objective, quantitative evidence for clinical assessment. MethodsSeventy-five participants were enrolled in this study, comprising 37 patients with surgically repaired CP and 38 healthy volunteers matched for age, gender, and body mass index (BMI). All subjects performed standardized sustained phonation tasks while undergoing synchronous monitoring with a 16-electrode EIT system and a pneumotachograph. A comprehensive feature engineering pipeline was developed to extract physiological parameters across 3 complementary domains. (1) Temporal domain: including inspiratory/expiratory phase duration (tPhase), time constants (Tau), and inspiratory-to-expiratory time ratios (TI/TE); (2) airflow domain: comprising mean flow, peak flow, and instantaneous flow at 25%, 50%, and 75% of tidal volume; and (3) spatial domain: quantifying global and regional tidal impedance variation (TIV), global inhomogeneity (GI), and center of ventilation (CoV). Extreme Gradient Boosting (XGBoost) classifiers were trained using 5 distinct data sources (Spirometry, Nasometry, Inspiratory-EIT, Expiratory-EIT, and fused ST-EIT). Model performance was rigorously evaluated via stratified 5-fold cross-validation, and Shapley additive explanations (SHAP) were employed to quantify global and local feature contributions. ResultsThe CP group exhibited a distinct respiratory phenotype compared to controls. In the temporal domain, CP patients showed significantly shorter inspiratory (1.60 s vs.1.85 s, P<0.001) and expiratory phase durations (2.45 s vs. 3.95 s, P<0.001), indicating a rapid, shallow breathing rhythm. In the airflow domain, while inspiratory flows were comparable, the CP group demonstrated significantly elevated mean and peak flows during the expiratory phase (P<0.001), reflecting compensatory respiratory effort. Spatially, CP patients presented significant ventilation redistribution, characterized by higher regional TIV in the right-anterior (ROI1) and left-posterior (ROI4) quadrants, but lower TIV in the left-anterior (ROI2) quadrant. In terms of diagnostic accuracy, the multi-modal ST-EIT model achieved the highest performance (AUC: 0.915±0.012, Accuracy: 0.843±0.019, F1-score: 0.872±0.017), substantially outperforming models based on spirometry (AUC: 0.721) or nasometry (AUC: 0.625) alone. Interpretability analysis revealed that spatial domain features were the most critical, contributing 53.4% to the model’s decision-making, followed by temporal (25.0%) and airflow (21.6%) features. ConclusionST-EIT successfully captures the temporal, airflow, and spatial deviations in CP speech respiration that are undetectable by conventional methods—specifically, rapid phase transitions, hyperdynamic expiratory airflow, and regional ventilation heterogeneity. This study validates ST-EIT as a robust, non-invasive, and radiation-free tool for characterizing speech-respiratory dysfunction, offering high clinical value for bedside screening, rehabilitation planning, and longitudinal monitoring of patients with cleft palate.

Malignant tumors represent a major threat to global health. Conventional anti-tumor pharmacotherapy often encounters challenges such as drug resistance, highlighting an urgent need for the development of novel therapeutic strategies. Fatty acid synthase (FASN), the key enzyme catalyzing de novo fatty acid synthesis, is subject to precise regulation at multiple levels, including transcriptional control, various post-translational modifications such as ubiquitination and phosphorylation, as well as modulation by diverse signaling pathways. Recent studies have revealed that FASN is aberrantly overexpressed in various malignant tumors and is closely associated with tumor progression and poor patient prognosis. FASN is a homodimer composed of seven functional domains that catalyzes the NADPH-dependent condensation of acetyl-CoA and malonyl-CoA to generate saturated fatty acids, primarily palmitic acid. Its stability is regulated by multiple ubiquitin ligases and deubiquitinating enzymes. Additionally, FASN is subject to upstream regulation via neural precursor cell-expressed developmentally downregulated 8 (Nedd8) modification and the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway, thereby establishing a metabolic-signaling positive feedback loop. As a core executor of metabolic reprogramming, FASN promotes tumorigenesis through dual mechanisms. First, its fatty acid synthesis product, palmitate, participates in membrane phospholipid synthesis, lipid raft formation, and protein palmitoylation, thereby activating several key oncogenic signaling pathways, including PI3K/AKT/mTOR, wingless-type MMTV integration site family member (Wnt)/β‑catenin, and signal transducer and activator of transcription 3 (STAT3)/matrix metalloproteinase (MMP), leading to tumor development and progression. Second, FASN plays a pivotal role in modulating the anti-tumor functions of immune cells and remodeling the tumor immune microenvironment. Specifically, FASN enhances immune checkpoint inhibition by inducing programmed death-ligand 1 (PD-L1) palmitoylation, suppresses the activation of cytotoxic T lymphocytes and natural killer cells, and promotes the polarization of M2-type macrophages, consequently facilitating tumor immune evasion and malignant progression. Precisely due to its significant overexpression in tumor cells, its critical functional role, and its differential expression compared to normal cells, FASN has emerged as a highly promising target for anti-tumor drug development. Highly selective small-molecule inhibitors, notably represented by TVB-2640, have advanced to clinical trial stages and demonstrated favorable anti-tumor activity. Furthermore, the combination of FASN inhibitors with other chemotherapeutic agents or targeted drugs can overcome the limitations of monotherapy through synergistic effects or by resensitizing tumor cells to conventional drugs, achieving a “1+1>2” therapeutic outcome. With the advancement of modern traditional Chinese medicine (TCM), numerous active ingredients derived from TCM have been confirmed to exert anti-tumor effects by modulating FASN-related pathways. This integrated approach leverages the precision of Western medicine while simultaneously harnessing the holistic regulatory benefits of TCM to alleviate the side effects of radiotherapy and chemotherapy. Despite the promising prospects of FASN-targeted therapies, challenges remain, including tumor cell metabolic plasticity, tumor context-dependent responses, and heterogeneity. This review systematically summarizes the molecular structure, physiological functions, and mechanisms of FASN in tumorigenesis, as well as recent advances in targeted therapies. Future directions—including the precise identification of responsive patient populations using spatial transcriptomics, the development of novel combination regimens, and the active exploration of integrative strategies combining traditional Chinese and Western medicine—will facilitate the clinical translation of FASN-targeted therapies and open new avenues for improving the quality of life and prognosis of cancer patients.

Background As climate change intensifies and extreme temperature events become more frequent, non-optimal temperature has emerged as a significant contributor to the global disease burden, representing a pressing public health challenge. Objective To analyze the disease burden, temporal trends, and health inequalities attributable to non-optimal, high, and low temperatures in China from 1990 to 2021, and to compare these findings with global levels to provide a scientific basis for targeted prevention strategies. Methods Using data from the Global Burden of Disease 2021 (GBD 2021), we extracted mortality rates and disability-adjusted life year (DALY) rates, and other indicators attributable to non-optimal, high, and low temperatures by sex, age, region, and cause. Joinpoint regression was applied to examine temporal trends. Decomposition analysis identified driving factors of change, while the slope index of inequality (SII) and concentration index (CI) quantified disparities across socio-demographic index (SDI) levels. Results From 1990 to 2021, the age-standardized mortality rates (ASMR) and age-standardized DALY rates (ASDR) attributable to non-optimal temperature in China exhibited a downward trend, decreasing from 66.48 (95%UI: 58.09, 76.56) to 32.70 (95%UI: 27.26, 39.26) per 100000 population, and from 1219.59 (95%UI: 1056.28, 1418.37) to 493.22 (95%UI: 403.88, 609.32) per 100000 population, respectively. Burdens attributable to non-optimal temperature and low temperature were higher than the global average, whereas the high temperature burden was lower. Males consistently experienced higher ASMR and ASDR attributable to non-optimal temperature than females. Cardiovascular diseases, chronic respiratory diseases, and respiratory infections and tuberculosis were the top three causes of non-optimal temperature-attributable burdens. Decomposition analysis revealed that population aging and growth were the primary drivers of increased burden, while epidemiological changes primarily drove the decline. Health inequalities were most predominant between extreme SDI regions but narrowed over time. Conclusion Despite the overall decline in burden attributable to non-optimal temperature in China, significant challenges remain, including high risks from cold exposure, gender disparities, and the compounding effects of an aging population with cardiovascular or respiratory diseases. Policy makers should prioritize climate change adaptation, focusing on elderly health and regional equity while strengthening the public health workforce.

Background As climate change intensifies and extreme temperature events become more frequent, non-optimal temperature has emerged as a significant contributor to the global disease burden, representing a pressing public health challenge. Objective To analyze the disease burden, temporal trends, and health inequalities attributable to non-optimal, high, and low temperatures in China from 1990 to 2021, and to compare these findings with global levels to provide a scientific basis for targeted prevention strategies. Methods Using data from the Global Burden of Disease 2021 (GBD 2021), we extracted mortality rates and disability-adjusted life year (DALY) rates, and other indicators attributable to non-optimal, high, and low temperatures by sex, age, region, and cause. Joinpoint regression was applied to examine temporal trends. Decomposition analysis identified driving factors of change, while the slope index of inequality (SII) and concentration index (CI) quantified disparities across socio-demographic index (SDI) levels. Results From 1990 to 2021, the age-standardized mortality rates (ASMR) and age-standardized DALY rates (ASDR) attributable to non-optimal temperature in China exhibited a downward trend, decreasing from 66.48 (95%UI: 58.09, 76.56) to 32.70 (95%UI: 27.26, 39.26) per 100000 population, and from 1219.59 (95%UI: 1056.28, 1418.37) to 493.22 (95%UI: 403.88, 609.32) per 100000 population, respectively. Burdens attributable to non-optimal temperature and low temperature were higher than the global average, whereas the high temperature burden was lower. Males consistently experienced higher ASMR and ASDR attributable to non-optimal temperature than females. Cardiovascular diseases, chronic respiratory diseases, and respiratory infections and tuberculosis were the top three causes of non-optimal temperature-attributable burdens. Decomposition analysis revealed that population aging and growth were the primary drivers of increased burden, while epidemiological changes primarily drove the decline. Health inequalities were most predominant between extreme SDI regions but narrowed over time. Conclusion Despite the overall decline in burden attributable to non-optimal temperature in China, significant challenges remain, including high risks from cold exposure, gender disparities, and the compounding effects of an aging population with cardiovascular or respiratory diseases. Policy makers should prioritize climate change adaptation, focusing on elderly health and regional equity while strengthening the public health workforce.