1.Clinical Efficacy of Tangning Tongluo Tablets for Nonproliferative Diabetic Retinopathy
Fuwen ZHANG ; Junguo DUAN ; Wen XIA ; Tiantian SUN ; Yuheng SHI ; Shicui MEI ; Xiangxia LUO ; Xing LI ; Yujie PAN ; Yong DENG ; Chuanlian RAN ; Hao CHEN ; Li PEI ; Shuyu YANG
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(3):132-139
ObjectiveTo observe the clinical efficacy and safety of Tangning Tongluo tablets in the treatment of nonproliferative diabetic retinopathy (DR). MethodsFourteen research centers participated in this study, which spanned a time interval from September 2021 to May 2023. A total of 240 patients with nonproliferative DR were included and randomly assigned into an observation group (120 cases) and a control group (120 cases). The observation group was treated with Tangning Tongluo tablets, and the control group with calcium dobesilate capsules. Both groups were treated for 24 consecutive weeks. The vision, DR progression rate, retinal microhemangioma, hemorrhage area, exudation area, glycosylated hemoglobin (HbA1c) level, and TCM syndrome score were assessed before and after treatment, and the safety was observed. ResultsThe vision changed in both groups after treatment (P<0.05), and the observation group showed higher best corrected visual acuity (BCVA) than the control group (P<0.05). The DR progression was slow with similar rates in the two groups. The fundus hemorrhage area and exudation area did not change significantly after treatment in both groups, while the observation group outperformed the control group in reducing the fundus hemorrhage area and exudation area. There was no significant difference in the number of microhemangiomas between the two groups before treatment. After treatment, the number of microhemangiomas decreased in both the observation group (Z=-1.437, P<0.05) and the control group (Z=-2.238, P<0.05), and it showed no significant difference between the two groups. As the treatment time prolonged, the number of microhemangiomas gradually decreased in both groups. There was no significant difference in the HbA1c level between the two groups before treatment. After treatment, the decline in the HbA1c level showed no significant difference between the two groups. The TCM syndrome score did not have a statistically significant difference between the two groups before treatment. After treatment, neither the TCM syndrome score nor the response rate had significant difference between the two groups. With the extension of the treatment time, both groups showed amelioration of TCM syndrome compared with the baseline. ConclusionTangning Tongluo tablets are safe and effective in the treatment of nonproliferative DR, being capable of improving vision and reducing hemorrhage and exudation in the fundus.
2.Effect and mechanism of compatibility of Astragali Radix-Puerariae Lobatae Radix on ferroptosis in T2DM insulin resistance rats
Shuang WEI ; Feng HAO ; Wenchun ZHANG ; Zhangyang ZHAO ; Ji LI ; Dongwei HAN ; Huan XING
China Pharmacy 2025;36(1):57-63
OBJECTIVE To explore the effect and potential mechanism of the compatibility of Astragali Radix-Puerariae Lobatae Radix on ferroptosis of liver cells in type 2 diabetes mellitus (T2DM) insulin resistance (IR) rats. METHODS Sixty male SD rats were randomly divided into control group (12 rats) and modeling group (48 rats). The modeling group was fed with a high- fat diet for 4 consecutive weeks and then given a one-time tail vein injection of 1% streptozotocin to establish T2DM IR model. The model rats were randomly divided into model group, the compatibility of Astragali Radix-Puerariae Lobatae Radix group [QG group, 4.05 g/(kg·d), intragastric administration], ferroptosis inhibitor ferrostatin-1 group [Fer-1 group, 5 mg/kg by intraperitoneal injection, once every other day], the compatibility of Astragali Radix-Puerariae Lobatae Radix+ferroptosis inducer erastin group [QG+erastin group, 4.05 g/(kg·d) by intragastric administration+erastin 10 mg/(kg·d), intraperitoneal injection]. After 4 weeks of intervention, serum fasting blood glucose (FBG) and fasting insulin (FINS) were measured in each group of rats, and homeostasis model assessment of insulin resistance (HOMA-IR) and the natural logarithm of insulin action index(IAI) were calculated; the serum levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), aspartate transaminase (AST) and alanine transaminase (ALT), Fe2+ and Fe content, glutathione (GSH), malondialdehyde (MDA) and superoxide dismutase (SOD) levels, NADP+/NADPH ratio and reactive oxygen species (ROS) were determined. The pathological morphology of its liver tissue was observed; the protein expressions of glutathione peroxidase 4 (GPX4), ferritin heavy chain 1 (FTH1), long-chain acyl-CoA synthetase 3 (ACSL3), ACSL4, ferritin mitochondrial (FTMT), and cystine/glutamate anti-porter (xCT) in the liver tissue of rats were detected. RESULTS Compared with control group, the liver cells in the model group of rats showed disordered arrangement, swelling, deepened nuclear staining, and more infiltration of inflammatory cells, as well as a large number of hepatocyte vacuoles and steatosis; FBG (after medication), the levels of TC, TG, LDL-C, AST, ALT, FINS, MDA and ROS, HOMA-IR, Fe2+ and Fe content, NADP+/NADPH ratio and protein expression of ACSL4 were significantly increased or up-regulated, while the levels of HDL-C, GSH and SOD, IAI, protein expressions of GPX4, FTH1, ACSL3, FTMT and xCT were significantly reduced or down-regulated (P<0.01). Compared with the model group, both QG group and Fer-1 group showed varying degrees of improvement in pathological damage of liver tissue and the levels of the above indicators, the differences in the changes of most indicators were statistically significant (P<0.01 or P<0.05). Compared with QG group, the improvement of the above indexes of QG+erastin group had been reversed significantly (P<0.01). CONCLUSIONS The compatibility decoction of Astragali Radix-Puerariae Lobatae Radix can reduce the level of FBG in T2DM IR rats, and alleviate IR degree, ion overload and pathological damage of liver tissue. The above effects are related to the inhibition of ferroptosis.
3.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
4.In situ Analytical Techniques for Membrane Protein Interactions
Zi-Yuan KANG ; Tong YU ; Chao LI ; Xue-Hua ZHANG ; Jun-Hui GUO ; Qi-Chang LI ; Jing-Xing GUO ; Hao XIE
Progress in Biochemistry and Biophysics 2025;52(5):1206-1218
Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.
5.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
6.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
7.Unregistered treatment situation among pulmonary tuberculosis patients in Quzhou City from 2017 to 2023
YAN Qingxiu ; WANG Wei ; HAO Xiaogang ; GAO Yu ; FANG Chunfu ; ZHANG Xing ; LIU Wenfeng
Journal of Preventive Medicine 2025;37(8):799-803
Objective:
To analyze the unregistered treatment situation and its influencing factors among pulmonary tuberculosis patients in Quzhou City, Zhejiang Province from 2017 to 2023, so as to provide a basis for promoting the management of tuberculosis patients and optimizing disease prevention and control strategies.
Methods:
Data of pulmonary tuberculosis patients including demographic information, etiological results, and mortality status were collected through the China Disease Prevention and Control Information System Infectious Disease Reporting and Surveillance System and the Tuberculosis Management Information System. Pulmonary tuberculosis patients not matched in the Tuberculosis Management Information System were defined as unregistered treatment patients, and the unregistered treatment rate was analyzed. Factors affecting unregistered treatment among pulmonary tuberculosis patients were analyzed using a multivariable logistic regression model.
Results:
A total of 10 779 pulmonary tuberculosis patients were reported in Quzhou City from 2017 to 2023, including 7 700 males (71.44%) and 3 079 females (28.56%). There were 5 484 cases aged <65 years, accounting for 50.88%. Among them, 630 cases were unregistered treatment, with an unregistered treatment rate of 5.84% (95%CI: 5.42%-6.38%). Multivariable logistic regression analysis showed pulmonary tuberculosis patients aged ≥65 years (OR=1.829, 95%CI: 1.512-2.212) had a higher risk of being unregistered treatment than those aged <65 years; patients with non-local household registration (OR=5.710, 95%CI: 4.724-6.901) had a higher risk than local patients; and patients engaged in housework/unemployed (OR=2.001, 95%CI: 1.421-2.818) or other occupations (OR=2.396, 95%CI: 1.789-3.137) had a higher risk than farmers. The mortality of unregistered treatment pulmonary tuberculosis patients was higher than the registered treatment patients (26.67% vs. 5.02%),with a significantly elevated mortality risk (OR=7.147, 95%CI: 5.738-8.902).
Conclusions
The unregistered treatment rate among pulmonary tuberculosis patients was well controlled in Quzhou City from 2017 to 2023, but the elderly, patients with non-local household registration, and those engaged in housework/unemployed had a higher risk of unregistered treatment. It is recommended to improve medical and social security policies, strengthen health education on tuberculosis prevention, enhance treatment adherence, and reduce mortality risk.
8.Associations of systemic immune-inflammation index and systemic inflammation response index with maternal gestational diabetes mellitus: Evidence from a prospective birth cohort study.
Shuanghua XIE ; Enjie ZHANG ; Shen GAO ; Shaofei SU ; Jianhui LIU ; Yue ZHANG ; Yingyi LUAN ; Kaikun HUANG ; Minhui HU ; Xueran WANG ; Hao XING ; Ruixia LIU ; Wentao YUE ; Chenghong YIN
Chinese Medical Journal 2025;138(6):729-737
BACKGROUND:
The role of inflammation in the development of gestational diabetes mellitus (GDM) has recently become a focus of research. The systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI), novel indices, reflect the body's chronic immune-inflammatory state. This study aimed to investigate the associations between the SII or SIRI and GDM.
METHODS:
A prospective birth cohort study was conducted at Beijing Obstetrics and Gynecology Hospital from February 2018 to December 2020, recruiting participants in their first trimester of pregnancy. Baseline SII and SIRI values were derived from routine clinical blood results, calculated as follows: SII = neutrophil (Neut) count × platelet (PLT) count/lymphocyte (Lymph) count, SIRI = Neut count × monocyte (Mono) count/Lymph count, with participants being grouped by quartiles of their SII or SIRI values. Participants were followed up for GDM with a 75-g, 2-h oral glucose tolerance test (OGTT) at 24-28 weeks of gestation using the glucose thresholds of the International Association of Diabetes and Pregnancy Study Groups (IADPSG). Logistic regression was used to analyze the odds ratios (ORs) (95% confidence intervals [CIs]) for the the associations between SII, SIRI, and the risk of GDM.
RESULTS:
Among the 28,124 women included in the study, the average age was 31.8 ± 3.8 years, and 15.76% (4432/28,124) developed GDM. Higher SII and SIRI quartiles were correlated with increased GDM rates, with rates ranging from 12.26% (862/7031) in the lowest quartile to 20.10% (1413/7031) in the highest quartile for the SII ( Ptrend <0.001) and 11.92-19.31% for the SIRI ( Ptrend <0.001). The ORs (95% CIs) of the second, third, and fourth SII quartiles were 1.09 (0.98-1.21), 1.21 (1.09-1.34), and 1.39 (1.26-1.54), respectively. The SIRI findings paralleled the SII outcomes. For the second through fourth quartiles, the ORs (95% CIs) were 1.24 (1.12-1.38), 1.41 (1.27-1.57), and 1.64 (1.48-1.82), respectively. These associations were maintained in subgroup and sensitivity analyses.
CONCLUSION
The SII and SIRI are potential independent risk factors contributing to the onset of GDM.
Humans
;
Female
;
Pregnancy
;
Diabetes, Gestational/immunology*
;
Prospective Studies
;
Adult
;
Inflammation/immunology*
;
Glucose Tolerance Test
;
Birth Cohort
9.Clinical course, causes of worsening, and outcomes of severe ischemic stroke: A prospective multicenter cohort study.
Simiao WU ; Yanan WANG ; Ruozhen YUAN ; Meng LIU ; Xing HUA ; Linrui HUANG ; Fuqiang GUO ; Dongdong YANG ; Zuoxiao LI ; Bihua WU ; Chun WANG ; Jingfeng DUAN ; Tianjin LING ; Hao ZHANG ; Shihong ZHANG ; Bo WU ; Cairong ZHU ; Craig S ANDERSON ; Ming LIU
Chinese Medical Journal 2025;138(13):1578-1586
BACKGROUND:
Severe stroke has high rates of mortality and morbidity. This study aimed to investigate the clinical course, causes of worsening, and outcomes of severe ischemic stroke.
METHODS:
This prospective, multicenter cohort study enrolled adult patients admitted ≤30 days after ischemic stroke from nine hospitals in China between September 2017 and December 2019. Severe stroke was defined as a score of ≥15 on the National Institutes of Health Stroke Scale (NIHSS). Clinical worsening was defined as an increase of 4 in the NIHSS score from baseline. Unfavorable functional outcome was defined as a modified Rankin scale score ≥3 at 3 months and 1 year after stroke onset, respectively. We performed Logistic regression to explore baseline features and reperfusion therapies associated with clinical worsening and functional outcomes.
RESULTS:
Among 4201 patients enrolled, 854 patients (20.33%) had severe stroke on admission. Of 3347 patients without severe stroke on admission, 142 (4.24%) patients developed severe stroke in hospital. Of 854 patients with severe stroke on admission, 33.95% (290/854) experienced clinical worsening (median time from stroke onset: 43 h, Q1-Q3: 20-88 h), with brain edema (54.83% [159/290]) as the leading cause; 24.59% (210/854) of these patients died by 30 days, and 81.47% (677/831) and 78.44% (633/807) had unfavorable functional outcomes at 3 months and 1 year respectively. Reperfusion reduced the risk of worsening (adjusted odds ratio [OR]: 0.24, 95% confidence interval [CI]: 0.12-0.49, P <0.01), 30-day death (adjusted OR: 0.22, 95% CI: 0.11-0.41, P <0.01), and unfavorable functional outcomes at 3 months (adjusted OR: 0.24, 95% CI: 0.08-0.68, P <0.01) and 1 year (adjusted OR: 0.17, 95% CI: 0.06-0.50, P <0.01).
CONCLUSIONS:
Approximately one-fifth of patients with ischemic stroke had severe neurological deficits on admission. Clinical worsening mainly occurred in the first 3 to 4 days after stroke onset, with brain edema as the leading cause of worsening. Reperfusion reduced the risk of clinical worsening and improved functional outcomes.
REGISTRATION
ClinicalTrials.gov , NCT03222024.
Humans
;
Male
;
Female
;
Prospective Studies
;
Ischemic Stroke/mortality*
;
Aged
;
Middle Aged
;
Aged, 80 and over
;
Stroke
;
Brain Ischemia
10.Xinyang Tablets ameliorate ventricular remodeling in heart failure via FTO/m6A signaling pathway.
Dong-Hua LIU ; Zi-Ru LI ; Si-Jing LI ; Xing-Ling HE ; Xiao-Jiao ZHANG ; Shi-Hao NI ; Wen-Jie LONG ; Hui-Li LIAO ; Zhong-Qi YANG ; Xiao-Ming DONG
China Journal of Chinese Materia Medica 2025;50(4):1075-1086
The study was conducted to investigate the mechanism of Xinyang Tablets( XYP) in modulating the fat mass and obesity-associated protein(FTO)/N6-methyladenosine(m6A) signaling pathway to ameliorate ventricular remodeling in heart failure(HF). A mouse model of HF was established by transverse aortic constriction(TAC). Mice were randomized into sham, model, XYP(low, medium, and high doses), and positive control( perindopril) groups(n= 10). From day 3 post-surgery, mice were administrated with corresponding drugs by gavage for 6 consecutive weeks. Following the treatment, echocardiography was employed to evaluate the cardiac function, and RT-qPCR was employed to determine the relative m RNA levels of key markers, including atrial natriuretic peptide( ANP), B-type natriuretic peptide( BNP), β-myosin heavy chain(β-MHC), collagen type I alpha chain(Col1α), collagen type Ⅲ alpha chain(Col3α), alpha smooth muscle actin(α-SMA), and FTO. The cardiac tissue was stained with Masson's trichrome and wheat germ agglutinin(WGA) to reveal the pathological changes. Immunohistochemistry was employed to detect the expression levels of Col1α, Col3α, α-SMA, and FTO in the myocardial tissue. The m6A modification level in the myocardial tissue was measured by the m6A assay kit. An H9c2 cell model of cardiomyocyte injury was induced by angiotensin Ⅱ(AngⅡ), and small interfering RNA(siRNA) was employed to knock down FTO expression. RT-qPCR was conducted to assess the relative m RNA levels of FTO and other genes associated with cardiac remodeling. The m6A modification level was measured by the m6A assay kit, and Western blot was employed to determine the phosphorylated phosphatidylinositol 3-kinase(p-PI3K)/phosphatidylinositol 3-kinase(PI3K) and phosphorylated serine/threonine kinase(p-Akt)/serine/threonine kinase(Akt) ratios in cardiomyocytes. The results of animal experiments showed that the XYP treatment significantly improved the cardiac function, reduced fibrosis, up-regulated the m RNA and protein levels of FTO, and lowered the m6A modification level compared with the model group. The results of cell experiments showed that the XYP-containing serum markedly up-regulated the m RNA level of FTO while decreasing the m6A modification level and the p-PI3K/PI3K and p-Akt/Akt ratios in cardiomyocytes. Furthermore, FTO knockdown reversed the protective effects of XYP-containing serum on Ang Ⅱ-induced cardiomyocyte hypertrophy. In conclusion, XYP may ameliorate ventricular remodeling by regulating the FTO/m6A axis, thereby inhibiting the activation of the PI3K/Akt signaling pathway.
Animals
;
Ventricular Remodeling/drug effects*
;
Heart Failure/physiopathology*
;
Signal Transduction/drug effects*
;
Mice
;
Male
;
Alpha-Ketoglutarate-Dependent Dioxygenase FTO/genetics*
;
Drugs, Chinese Herbal/administration & dosage*
;
Mice, Inbred C57BL
;
Humans
;
Adenosine/analogs & derivatives*
;
Myocytes, Cardiac/metabolism*
;
Disease Models, Animal


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