Abstract:Interleukin-24 (IL-24), a member of the IL-20 subfamily within the IL-10 family, is the first tumor growth suppressor identified and isolated from melanoma, exhibiting a high degree of evolutionary conservation. Its functions are dual in different tissues and microenvironments, exerting bidirectional pro-inflammatory or anti-inflammatory effects, and play crucial roles in various diseases such as inflammatory disorders and cancers. Recent studies have revealed that IL-24 can also regulate the function of smooth muscle cells, protect endothelial cells, modulate angiogenesis, and participate in the pathogenesis and progression of cardiovascular diseases including atherosclerosis and vascular calcification, making it a promising novel target for the prevention and treatment of cardiovascular diseases.

Abstract:Aim To investigate the effects of TFPIct32, a 32-amino acid peptide segment of tissue factor pathway inhibitor C-terminal (TFPIct), on the progression of atherosclerosis (As) lesions in ApoE－/－ mice and its preliminary mechanisms. Methods ApoE－/－ mice were fed with a high-fat diet for 10 weeks to establish an As animal model.Mice successfully modeled were randomly divided into four groups of 10 (n＝10) each:model group, saline group (tail vein injection of saline on top of the model), TFPI group (negative control peptide group, 2.5 nmol/g TFPI per week, tail vein injection), TFPIct32 group (2.5 nmol/g TFPIct32 per week, tail vein injection). All groups received continuous treatment for 4 weeks. After treatment completion, tail bleed time was measured in mice from each group; Serum samples were collected to measure serum levels of total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDLC), and high density lipoprotein cholesterol (HDLC). Mouse aortas were isolated and stained with oil red O. Sections of aortic sinus tissue were stained with hematoxylin and eosin (HE), Masson's trichrome, and oil red O. A cell proliferation and migration model was established using platelet-derived growth factor-BB (PDGF-BB) treatment on vascular smooth muscle cells (VSMC), divided into control group, PDGF-BB group, PDGF-BB+TFPI group, PDGF-BB+TFPIct32 group, PDGF-BB+protein kinase B (Akt) agonist SC79 group and PDGF-BB+TFPIct32+SC79 group. Cell proliferation was assessed using the CCK-8 assay, while cell migration was evaluated via the scratch assay and Transwell method. Protein expression levels of proliferating cell nuclear antigen (PCNA), phosphoinositide 3-kinase (PI3K), phosphorylated Akt (p-AKT), and total Akt (t-Akt) were detected by Western blot analysis. Results Animal experimental results showed that, compared with the saline group and the TFPI group, the TFPIct32 group significantly reduced serum LDLC levels in ApoE－/－ mice (P＜0.05), while simultaneously decreased plaque area in the aortic wall and aortic sinus (both P＜0.01). TFPIct32 significantly inhibited PDGF-BB-induced proliferation and migration of VSMC (both P＜0.05), while the Akt-specific agonist SC79 partially restored the TFPIct32-inhibited VSMC proliferation and migration (P＜0.05). These findings suggested that the PI3K/Akt pathway played a crucial role in the regulation of TFPIct32-mediated inhibition of VSMC proliferation, migration, and subsequent atherosclerosis progression. Conclusion TFPIct32 significantly slows the progression of atherosclerotic lesions in ApoE－/－ mice fed a high-fat diet, a mechanism likely involving the inhibition of VSMC proliferation and migration.

Abstract:Aim To analyze the expression of miR-29c-5p in peripheral blood leukocytes of patients with coronary heart disease (CHD), and to explore its mechanism in regulating oxidative damage and apoptosis of endothelial cells induced by high-lipid conditions. Methods The expression levels of miR-29c-5p were detected in peripheral blood leukocytes of patients with CHD. Endothelial cell injury in EA.hy926 cells was induced by exposure to high concentrations of the lipid. miR-29c-5p was overexpressed and silenced respectively in the high-fat-induced model, and the expression of apoptosis-related proteins, the level of reactive oxygen species (ROS), and the degree of lipid peroxidation were detected. Bioinformatics methods were used to predict the potential target genes of miR-29c-5p, and the dual luciferase reporter assay was performed to verify its regulatory relationship with the target genes. Results Compared with the control group, the expression level of miR-29c-5p was decreased in the CHD group and had diagnostic significance for CHD with an AUC value of 0.712 (95%CI:0.632～0.792, P＜0.01). In the high-fat-induced model, cell viability was decreased and cell apoptosis was increased (P＜0.01), together with an elevated miR-29c-5p expression level (P＜0.01).Silencing miR-29c-5p expression alleviated cell damage, increased cell viability (P＜0.01), reduced hight-fat-induced apoptosis, lowered ROS and lipid peroxidation levels (all P＜0.05); while overexpressing miR-29c-5p decreased cell viability (P＜0.01), increased high-fat-induced cell apoptosis and raised ROS and lipid peroxidation levels (all P＜0.05). Moreover, bioinformatics analysis prediction and dual luciferase reporter assay confirmed that miR-29c-5p bound to the 3′UTR region of the histonedeacetylase 2 (HDAC2) gene, thereby downregulating the mRNA and protein expression levels of HDAC2 (all P＜0.05). Conclusion The expression of miR-29c-5p is decreased in peripheral blood leukocytes of patients with CHD, which may serve as a diagnostic biomarker for this disease. Inhibition of miR-29c-5p expression in endothelial cells may alleviate oxidative injury and apoptosis induced by high-fat exposure via upregulating HDAC2.

Abstract:Aim To investigate whether citronellal antagonizes oxidative stress-induced injury in human umbilical vein endothelial cells by enhancing the autophagy-lysosome pathway, promoting the degradation of ring finger protein 4 (RNF4) and thereby stabilizing the protein levels of guanosine triphosphate cyclohydrolase 1 (GTPCH1). Methods Human umbilical vein endothelial cells were treated with H₂O₂ to establish oxidative damage models, and then treated with 0.48 mmol/L citronellal. Cell viability was determined by MTT assay; the protein expressions of p62, microtubule-associated protein light chain 3B (LC3B), lysosome-associated membrane protein 1 (LAMP1), GTPCH1 and RNF4 were detected by Western blot. The cells were treated with the autophagy inhibitor chloroquine (CQ) and the proteasome inhibitor MG132. Co-immunoprecipitation (CoIP) was used to verify the GTPCH1 SUMOylation and its interaction with RNF4 in response to H₂O₂. Results Compared with the control group, H₂O₂ treatment significantly decreased endothelial cell viability (P＜0.05) and GTPCH1 protein level (P＜0.01) and up-regulated RNF4 protein expression (P＜0.01). CoIP assay confirmed that H₂O₂ induced GTPCH1 to undergo SUMOylation and bind to RNF4. Compared with the H₂O₂ group, citronellal treatment significantly reversed the above changes and improved the autophagic flux:p62 was significantly decreased (P＜0.001); the LC3B-Ⅱ/LC3B-Ⅰ ratio was restored (P＜0.001); and the expression of LAMP1 was up-regulated (P＜0.05). Inhibitor experiments showed that MG132 blocked GTPCH1 degradation (P＜0.01) and CQ inhibited RNF4 degradation (P＜0.05) compared with the H₂O₂ group. Conclusion H₂O₂ triggers endothelial cell injury via RNF4-mediated GTPCH1 SUMOylation-ubiquitination degradation; citronellal promotes the degradation of RNF4 by enhancing the function of the autophagy-lysosome pathway, thereby stabilizing GTPCH1 and antagonizing H₂O₂-induced endothelial cell injury.

Abstract:Aim To analyze the dynamic changes of the atherogenic index of plasma (AIP) during the course of severe acute pancreatitis (SAP) and its predictive efficacy for patient prognosis. Methods We collected and analyzed clinical data from 150 patients with SAP at 363 Hospital from June 2020 to June 2024, and patients were grouped based on their prognosis outcomes during the 28-day follow-up period after admission, with 112 patients assigned to the survival group and 38 patients to the mortality group. Repeated-measures analysis of variance (ANOVA) was used to compare changes in triglyceride (TG), high density lipoprotein cholesterol (HDLC), AIP and inflammatory markers between the two groups at baseline (T0), day 5 post-treatment (T5), and day 10 post-treatment (T10). Multiple linear regression analysis was performed to examine the relationship between AIP and inflammatory markers at different time points; Logistic regression models were used to analyze the independent association between AIP and SAP patient mortality risk at different time points; Receiver operating characteristic (ROC) curve analysis was used to evaluate the relationship between AIP, TG, HDLC, inflammatory markers and SAP patient mortality risk at different time points;Restricted cubic spline (RCS) analysis was used to analyze the relationship between AIP and SAP patient mortality risk; Multidimensional stratified analysis was used to analyze the association between AIP levels and SAP patient mortality risk; Kaplan-Meier survival curve analysis was used to analyze SAP patients' survival rates; Subgroup analysis was performed to examine the association between AIP and SAP mortality risk at T5 and T10 in patients with different etiologies. DeLong's test was further used to analyze the predictive efficacy of AIP for SAP after excluding lipidogenic patients. Results The age, multiple organ failure, white blood cell count (WBC), acute physiological and chronic health score Ⅱ (APACHEⅡ), and sequential organ failure assessment (SOFA) scores of patients in the death group were significantly higher than those in the survival group.Conversely, albumin (ALB), total cholesterol (TC), and low density lipoprotein cholesterol (LDLC) levels were significantly lower in the death group than those in the survival group (P＜0.05). In the survival group, TG, AIP, C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6) levels decreased sequentially at time points T0, T5, and T10, whereas in the death group, AIP, CRP, PCT, and IL-6 exhibited an initial increase followed by a decline. HDLC levels increased in the survival group but decreased first and then increased in the death group, with statistically significant differences (P＜0.05). Repeated measures ANOVA on TG, HDLC, AIP, CRP, PCT, and IL-6 in both groups revealed statistically significant differences in time, between groups, and time×group interaction (P＜0.05). At T0, T5, and T10, AIP showed a positive linear correlation with CRP, PCT and IL-6 (P＜0.05). Logistic regression analysis indicated that AIP at stages T5 and T10 was independently associated with mortality risk in SAP patients (P＜0.05). ROC curve analysis revealed that AIP exhibited optimal predictive efficacy at T5 (AUC:0.2,5%CI:0.873～0.965) and T10 (AUC:0.1,5%CI:0.914～0.993), with the highest predictive efficacy at T10, accompanied by the highest sensitivity (99.5%) and accuracy (88.7%). RCS analysis indicated a nonlinear dose-response relationship between AIP and SAP mortality risk at T5 and T10 (P＜0.05). Multidimensional stratified analysis revealed associations between AIP and SAP mortality risk at T5 and T10 in subgroups with APACHEⅡ≥20, SOFA≥8, CRP≥200 mg/L, PCT≥10 mg/L, and IL-6≥300 ng/L, with higher mortality risk observed in SAP patients with organ failure. Survival curve analysis revealed statistically significant differences between the AIP＞0.20 group and the AIP≤0.20 group at T5 (χ²＝6.437, P＜0.001) and between the AIP＞0.10 group and the AIP≤0.10 group at T10 (χ²＝5.831, P＜0.001). Subgroup analysis revealed independent associations between AIP and mortality risk at T5 and T10 in different etiologies, with more pronounce correlations observed in the high AIP level group, and both demonstrated good discriminatory ability. After excluding lipid-derived patients, ROC curve analysis indicated that AIP still retained predictive efficacy in non-lipid-derived SAP patients, with higher predictive performance at T10 (AUC:0.8,5%CI:0.880～0.971). Conclusions AIP exhibits dynamic changes during the disease course in SAP patients, At T5 and T10, AIP shows independent correlation with mortality risk, and exhibits linear correlations with CRP, PCT, and IL-6. The predictive efficacy of AIP is highest at T10, and it maintains robust predictive performance even after excluding lipid-derived patients. Incorporating dynamic AIP monitoring into clinical evaluation systems helps identify high-risk patients at an early stage and improves the efficacy of prognosis assessment.

Abstract:Aim To investigate the prognostic value of dynamic monitoring of inflammatory-coagulation biomarker profiles in patients with atrial fibrillation (AF) complicated with coronary heart disease (CHD), and to establish a multi-biomarker risk predictive model and develop an optimized risk stratification system. Methods A total of 130 patients with AF and CHD admitted from June 2021 to June 2024 were prospectively enrolled. Multiple inflammatory and coagulation biomarkers were measured at baseline, 1,3, 6, and 12 months, and dynamic follow-up was performed. The primary endpoint was major adverse cardiovascular events (MACE) during the 12-month follow-up period. LASSO regression was used to select predictive variables and construct an inflammation-coagulation score index (ICSI). Cox regression analysis was used to evaluate its prognostic value. Results During 12-month follow-up, 38 patients (29.2%) experienced MACE. The baseline levels of inflammatory-coagulation biomarkers were positively correlated with the SYNTAX score, and the levels of hs-CRP and D-dimer in the high-risk group were significantly 3.2-fold and 2.8-fold those in the low-risk group, respectively (P＜0.001). The biomarkers in the event group persistently remained at high levels during the follow-up period, while those in the non-event group showed a downward trend. Patients with ＜30% hs-CRP reduction or ＜25% D-dimer reduction at 3 months had 3.23-fold and 3.67-fold increased risk of MACE, respectively. The multi-biomarker model (incorporating,high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), D-dimer, fibrinogen, N-terminal pro-B-type natriuretic peptide (NT-proBNP) achieved an area under the curve (AUC) of 0.802, superior to CHA₂DS₂-VASc score (AUC=0.658) and HAS-BLED score (AUC=0.612). The risk stratification system based on ICSI identified 23 intermediate-to-high-risk patients among those with CHA₂DS₂-VASc＜4, with a MACE incidence rate of 39.1%. Conclusion Dynamic monitoring of inflammatory-coagulation biomarker profiles accurately predicts prognosis of AF patients complicated with CHD.

Abstract:Aim To establish an artificial neural network (ANN) model based on the GEO database for lipid metabolism-related genes in patients with acute myocardial infarction and evaluate its effectiveness, while predicting targeted traditional Chinese medicines for hub genes. Methods Six acute myocardial infarction chip data were obtained from the GEO database, and GSE48060, GSE60993 and GSE66360 were merged as training datasets, GSE34198, GSE61144 and GSE12288 were used as validation datasets, respectively. LASSO, random forest and SVM-RFE machine learning algorithms were used to screen hub genes related to lipid metabolism in patients with acute myocardial infarction, subsequently, an ANN model was constructed based on the selected hub genes. The effectiveness of the model was validated in independent validation sets GSE34198, GSE61144 and GSE12288, the clinical application value of ANN model was evaluated through area under the curve (AUC) analysis. Subsequently, a nomogram was constructed to predict the probability of disease occurrence, and RT-qPCR was used to validate the expression levels of hub genes. Finally, targeted traditional Chinese medicines were predicted based on hub genes, and the prediction results were validated through molecular docking technology. Results A total of 17 differentially expressed genes related to lipid metabolism were screened, including 14 upregulated genes and 3 downregulated genes. Four hub genes (ACSL1, DGAT2, MBOAT2 and CH25H) were further screened using three machine learning algorithms:LASSO, Random Forest and SVM-RFE, and an ANN diagnostic model was constructed. The ROC curves for the diagnosis of the training and validation groups were plotted using this model. The AUC value for the training set was 0.936 (P＜0.001), while the AUC values for the validation sets GSE34198, GSE61144 and GSE12288 were 0.786 (P＜0.001), 0.821 (P＜0.01), and 0.900 (P＜0.001), respectively. A nomogram was constructed based on four lipid metabolism related hub genes, and the calibration curve showed that the prediction probability of the nomogram model was almost consistent with the ideal model. RT-qPCR experiments further validated the reliability of the above results. Based on the hub genes, 27 traditional Chinese medicines were screened, with the four natures and five flavors mostly belonging to warm, calm, cold, bitter, spicy and sweet, and mostly returning to the liver, spleen, lungs and heart meridians. Their functions were mainly to clear heat and detoxify, promote blood circulation and unblock meridians, and drain dampness and eliminate phlegm. The molecular docking results showed that the binding energies of Ruta graveolens, Coconut and Ambergris Fish Bone were －6.9 kcal/mol, －7.4 kcal/mol and －8.2 kcal/mol, respectively, indicating a good interaction between the small molecule compounds they contain and the target protein. Conclusions This study employed machine learning methods to identify four lipid metabolism-related hub genes (ACSL1, DGAT2, MBOAT2 and CH25H) in acute myocardial infarction patients, and constructed an ANN model with high diagnostic efficacy. Furthermore, targeted traditional Chinese medicine prediction was performed based on these hub genes, providing new bioinformatics evidence for the early identification and potential intervention strategies of acute myocardial infarction.

Abstract:Aim To explore the association between atherogenic index of plasma (AIP) and its anthropometric-derived indicators AIP-waist-to-height ratio (AIP-WHtR) and AIP-body roundness index (AIP-BRI) and the long-term risk of stroke in middle-aged and elderly populations. Methods The study population was derived from the China Health and Retirement Longitudinal Study. Incident stroke cases were identified through self-reported questionnaire data.Enzyme-catalyzed colorimetric method was used to measure the levels of triglyceride (TG) and high density lipoprotein cholesterol (HDLC) in the blood of participants, and AIP and its anthropometric-derived indicators AIP-WHtR and AIP-BRI were calculated. Cox proportional hazards regression was used to evaluate the association between cumulative and categorical AIP and its anthropometric-derived indicators AIP-WHtR, AIP-BRI and stroke occurrence. Restrictied cubic spline was used to explore the potential nonlinear relationships between cumulative AIP and its anthropometric-derived indicators AIP-WHtR, AIP-BRI and the risk of stroke. Results The average age of 8 454 participants was (60.65±9.29) years, and during a median follow-up period of 7 years, a total of 670 participants (7.93%) had a new onset of stroke. After fully adjusting for confounding factors, for per 1-standard-deviation increment in AIP, the risk of stroke increased by 21% (HR＝1.1,5%CI:1.09～1.33, P＜0.001). Similarly, higher levels of AIP-WHtR (HR＝1.0,5%CI:1.18～1.66, P＜0.001) and AIP-BRI (HR＝1.4,5%CI:1.02～1.06, P＜0.001) were positively correlated with increased risk of stroke. Restrictive cubic spline analysis showed a positive dose-response relationship between AIP and its anthropometric-derived indicators AIP-WHtR, AIP-BRI and the risk of stroke, with a significant nonlinear trend. In addition, subgroup analysis further confirmed that higher AIP levels were associated with an increased risk of stroke in males (HR＝1.5,5%CI:1.08～1.44, P＜0.001), whereas the association was not significant in females (HR＝1.5,5%CI:1.00～1.32, P＝0.050). Conclusion In the middle-aged and elderly population, higher levels of AIP and its anthropometric-derived indicators AIP-WHtR and AIP-BRI are positively correlated with increased risk of stroke, and these indicators may serve as effective risk of stroke assessment tools.

Abstract:Acute coronary syndrome (ACS), as a critical cardiovascular emergency, involves a complex pathogenesis closely associated with the interplay of multiple inflammatory factors. Currently, risk assessment for ACS primarily relies on traditional factors such as age, lipid profiles, cardiac biomarkers, and C-reactive protein, yet there remains a lack of dynamic evaluation of inflammatory status. In recent years, the neutrophil-to-lymphocyte ratio (NLR) has emerged as a novel inflammatory marker, demonstrating significant value in risk prediction and prognosis assessment in ACS. Dynamic monitoring of NLR changes can facilitate earlier identification of a patient's inflammatory response, thereby providing a scientific basis for developing individualized treatment strategies. This review summarizes recent research advances in the application of NLR for ACS risk prediction, aiming to offer new insights and references for clinical practice.

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