Correlation Between Serum Albumin and D-Dimer Levels in 909 Patients with Non-Valvular Atrial Fibrillation: A Retrospective Study from a Single Center in China.

BACKGROUND D-dimer level can reflect the hypercoagulable state of atrial fibrillation (AF) and predict thromboembolic events. However, no effective indicator associated with D-dimer of AF patients has been found to prevent thromboembolic events in AF. This retrospective study from a single center aimed to investigate the correlation between serum albumin and D-dimer levels in 909 patients with non-valvular AF (NVAF) and 653 subjects in sinus rhythm. MATERIAL AND METHODS A total of 909 NVAF patients and 653 sex- and age-matched sinus rhythm participants were used to compare serum albumin and D-dimer levels. Serum albumin was determined by colorimetry, and D-dimer level was determined by latex-enhanced photoimmunoassay. We analyzed the correlation of serum albumin and D-dimer with NVAF by correlation analysis, logistic regression analysis, and receiver operating characteristic (ROC) curve. RESULTS Albumin (P<0.001) and D-dimer (P<0.001) were significantly associated with NVAF. Among NVAF patients, D-dimer level was negatively correlated with albumin levels (P<0.001), and albumin level was an independent risk factor of abnormal D-dimer level (>0.5 ug/mL), which was also an effective predictor of abnormal D-dimer level (the area under the ROC curve was 0.77, P<0.001), and the optimal cutoff value was 36.95 g/L. CONCLUSIONS Serum albumin and D-dimer levels were significantly associated with NVAF. In NVAF patients, D-dimer level was inversely correlated with albumin levels, and albumin level was an independent risk factor and effective predictor of abnormal D-dimer level. Close examination and supplementation of serum albumin can prevent thromboembolic events, but further clinical research and confirmation are needed.

Intravenous immunoglobulin-based adjuvant therapy for severe COVID-19: a single-center retrospective cohort study.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) is a major challenge facing the world. Certain guidelines issued by National Health Commission of the People's Repubilic of China recommend intravenous immunoglobulin (IVIG) for adjuvant treatment of COVID-19. However, there is a lack of clinical evidence to support the use of IVIG. METHODS: This single-center retrospective cohort study included all adult patients with laboratory-confirmed severe COVID-19 in the Respiratory and Critical Care Unit of Dabie Mountain Regional Medical Center, China. Patient information, including demographic data, laboratory indicators, the use of glucocorticoids and IVIG, hospital mortality, the application of mechanical ventilation, and the length of hospital stay was collected. The primary outcome was the composite end point, including death and the use of mechanical ventilation. The secondary outcome was the length of hospital stay. RESULTS: Of the 285 patients with confirmed COVID-19, 113 severely ill patients were included in this study. Compared to the non-IVIG group, more patients in the IVIG group reached the composite end point [12 (25.5%) vs 5 (7.6%), P = 0.008] and had longer hospital stay periods [23.0 (19.0-31.0) vs 16.0 (13.8-22.0), P < 0.001]. After adjusting for confounding factors, differences in primary outcomes between the two groups were not statistically significant (P = 0.167), however, patients in the IVIG group had longer hospital stay periods (P = 0.041). CONCLUSION: Adjuvant therapy with IVIG did not improve in-hospital mortality rates or the need for mechanical ventilation in severe COVID-19 patients. Our study does not support the use of immunoglobulin in patients with severe COVID-19 patients.

[Effect of Fuxin Mixture on The 01-AR-cAMP-PKA Pathway of Rats with Heart Failure].

Objective To observe the effect of Fuxin Mixture(FXM) on the ß,-AR(adrenergic receptor) -cAMP(cyclic adenosine monophosphate, cAMP) -PKA ( protein kinase A, PKA) pathway of rats with heart failure. Methods Male Wistar rats were randomly divided into blank control group, captopril group, FXM low dose group, FXM high dose group and model group.Models of CHF were established. After drug intervention for 6 weeks, the left ventricular mass index (LVMI) was analysed, the expression of ß1 - AR mRNA in myocardial tissue was measured,the level of cAMP in rat plasma,the OD value PKA content of spleen tissue homogenate were detected. Results Compared with the blank control group, the LVMI and the cAMP in plasma of model group were increased (P <0. 05), the expression of ß1,-AR mRNA, the OD value of spleen tissue homogenate and PKA were decreased (P <0. 01). Compared with the model group, the LVMI were decreased,and the expression of ß1-AR mRNA were increased in FXM high dose group and captopril group (P <0. 01 , P <0. 05) ; the level of cAMP in plasma of each drug group were decreased (P <0. 01) , the OD value of spleen tissue homogenate and PKA were increased (P <0. 01). Compared with the captopril group, the expression of ß1-AR mRNA, the OD value of spleen tissue homogenate and PKA were decreased, and the LVMI and the cAMP were increased in the FXM low dose group (P <0. 01 , P <0. 05). Compared with the FXM low dose group, the LVMI and the cAMP of FXM high dose group were decreased (P <0. 05), the expression of ß1-AR mRNA, the OD value of spleen tissue homogenate and PKA were increased (P <0. 01). Conclusion FXM could play the role of anti-heart fail- ure through regulating P1-AR-cAMP-PKA pathway.

Identification and validation of aging-related genes in heart failure based on multiple machine learning algorithms.

Background: In the face of continued growth in the elderly population, the need to understand and combat age-related cardiac decline becomes even more urgent, requiring us to uncover new pathological and cardioprotective pathways. Methods: We obtained the aging-related genes of heart failure through WGCNA and CellAge database. We elucidated the biological functions and signaling pathways involved in heart failure and aging through GO and KEGG enrichment analysis. We used three machine learning algorithms: LASSO, RF and SVM-RFE to further screen the aging-related genes of heart failure, and fitted and verified them through a variety of machine learning algorithms. We searched for drugs to treat age-related heart failure through the DSigDB database. Finally, We use CIBERSORT to complete immune infiltration analysis of aging samples. Results: We obtained 57 up-regulated and 195 down-regulated aging-related genes in heart failure through WGCNA and CellAge databases. GO and KEGG enrichment analysis showed that aging-related genes are mainly involved in mechanisms such as Cellular senescence and Cell cycle. We further screened aging-related genes through machine learning and obtained 14 key genes. We verified the results on the test set and 2 external validation sets using 15 machine learning algorithm models and 207 combinations, and the highest accuracy was 0.911. Through screening of the DSigDB database, we believe that rimonabant and lovastatin have the potential to delay aging and protect the heart. The results of immune infiltration analysis showed that there were significant differences between Macrophages M2 and T cells CD8 in aging myocardium. Conclusion: We identified aging signature genes and potential therapeutic drugs for heart failure through bioinformatics and multiple machine learning algorithms, providing new ideas for studying the mechanism and treatment of age-related cardiac decline.

Combining WGCNA and machine learning to identify mechanisms and biomarkers of ischemic heart failure development after acute myocardial infarction.

Background: Ischemic heart failure (IHF) is a serious complication after acute myocardial infarction (AMI). Understanding the mechanism of IHF after AMI will help us conduct early diagnosis and treatment. Methods: We obtained the AMI dataset GSE66360 and the IHF dataset GSE57338 from the GEO database, and screened overlapping genes common to both diseases through WGCNA analysis. Subsequently, we performed GO and KEGG enrichment analysis on overlapping genes to elucidate the common mechanism of AMI and IHF. Machine learning algorithms are also used to identify key biomarkers. Finally, we performed immune cell infiltration analysis on the dataset to further evaluate immune cell changes in AMI and IHF. Results: We obtained 74 overlapping genes of AMI and IHF through WGCNA analysis, and the enrichment analysis results mainly focused on immune and inflammation-related mechanisms. Through the three machine learning algorithms of LASSO, RF and SVM-RFE, we finally obtained the four Hub genes of IL1B, TIMP2, IFIT3, and P2RY2, and verified them in the IHF dataset GSE116250, and the diagnostic model AUC = 0.907. The results of immune infiltration analysis showed that 8 types of immune cells were significantly different in AMI samples, and 6 types of immune cells were significantly different in IHF samples. Conclusion: We explored the mechanism of IHF after AMI by WGCNA, enrichment analysis, and immune infiltration analysis. Four potential diagnostic candidate genes and therapeutic targets were identified by machine learning algorithms. This provides a new idea for the pathogenesis, diagnosis, and treatment of IHF after AMI.

Chinese medicinal formula Fu Xin decoction against chronic heart failure by inhibiting the NLRP3/caspase-1/GSDMD pyroptotic pathway.

BACKGROUND: Various heart diseases ultimately lead to chronic heart failure (CHF). In CHF, the inflammatory response is associated with pyroptosis, which is mediated by the NOD-like receptor protein 3 (NLRP3) inflammasome. Fu Xin decoction (FXD) is commonly used in clinical practice to treat CHF and improve inflammatory conditions. However, the specific pharmacological mechanisms of action for FXD in these processes have yet to be fully understood. PURPOSE: The objective of this study was to examine the protective mechanism of FXT against CHF, both in H9c2 cells and mice. METHOD: A CHF mouse model was established, and the effect of FXD was observed via gavage. Cardiac function was evaluated using echocardiography, while serum BNP and LDH levels were analyzed to assess the severity of CHF. Hematoxylin and eosin staining (H&E) and Masson staining were performed to evaluate myocardial pathological changes, and TdT-mediated dUTP Nick-End Labeling staining was used to detect DNA damage. Additionally, doxorubicin was utilized to induce myocardial cell injury in H9c2 cells, establishing a relevant model. CCK8 was used to observe cell viability and detect LDH levels in the cell supernatant. Subsequently, the expression of pyroptosis-related proteins was detected using immunohistochemistry, immunofluorescence, and western blotting. Finally, the pharmacological mechanism of FXD against CHF was further validated by treating H9c2 cells with an NLRP3 activator and inducing NLRP3 overexpression. RESULT: According to current research findings, echocardiography demonstrated a significant improvement of cardiac function by FXD, accompanied by reduced levels of BNP and LDH, indicating the amelioration of cardiac injury in CHF mice. FXD exhibited the ability to diminish serum CRP and MCP inflammatory markers in CHF mice. The results of HE and Masson staining analyses revealed a significant reduction in pathological damage of the heart tissue following FXD treatment. The CCK8 assay demonstrated the ability of FXD to enhance H9c2 cell viability, improve cell morphology, decrease LDH levels in the cell supernatant, and alleviate cell damage. Immunohistochemistry, Western blotting, and immunofluorescence staining substantiated the inhibitory effect of FXD on the NLRP3/caspase-1/GSDMD pyroptosis signaling pathway in both CHF and H9c2 cell injury models. Ultimately, the administration of the NLRP3 activator (Nigericin) and the overexpression of NLRP3 counteract the effects of FXD on cardiac protection and pyroptosis inhibition in vitro. CONCLUSION: FXD exhibits a cardioprotective effect, improving CHF and alleviating pyroptosis by inhibiting the NLRP3/caspase-1/GSDMD pathway.

Association of Serum Uric Acid with Non-Valvular Atrial Fibrillation: A Retrospective Study in China.

Purpose: The association between serum uric acid (SUA) and atrial fibrillation (AF) has been widely focused on and studied in recent years. However, the exact association between SUA and AF is unclear, and the effect of gender on the association between SUA levels and AF has been controversial. This study aimed to investigate the association between SUA levels and non-valvular AF (NVAF) and the potential effect of gender on it. Patients and Methods: A total of 866 NVAF patients (463 males, age 69.44 ± 8.07 years) and 646 sex-matched control patients in sinus rhythm, with no history of arrhythmia were included in this study. t-test, ANOVA, and chi-square test were used for baseline data analysis. The receiver operating characteristic curve, logistic regression and Pearson correlation analysis were used for correlation analysis. Results: Compared to controls, NVAF patients exhibited higher SUA (P<0.001). After adjusting for confounders of NVAF, SUA remained significantly associated with NVAF, regardless of gender (OR= 1.31, 95% CI 1.18-1.43, P<0.001). SUA demonstrated higher predictability and sensitivity in predicting the occurrence of female NVAF compared to male (area under the curve was 0.68 (95% CI 0.64-0.72, P<0.001), sensitivity 87.3%), with the optimal cut-off point identified as 5.72 mg/dL. Furthermore, SUA levels correlated with APOA1, Scr and NT-proBNP in NVAF patients. SUA levels varied significantly among NVAF subtypes. Conclusion: High SUA levels were independently associated with NVAF, regardless of gender. SUA exhibited higher predictability and sensitivity in predicting the occurrence of NVAF in females compared to males. High SUA levels may affect other NVAF-related factors and participate in the pathophysiological process of NVAF.

Exploring the mechanism of diabetic cardiomyopathy treated with Qigui Qiangxin mixture based on UPLC-Q/TOF-MS, network pharmacology and experimental validation.

Despite its effectiveness in treating diabetic cardiomyopathy (DCM), Qigui Qiangxin Mixture (QGQXM) remains unclear in terms of its active ingredients and specific mechanism of action. The purpose of this study was to explore the active ingredients and mechanism of action of QGQXM in the treatment of DCM through the comprehensive strategy of serum pharmacology, network pharmacology and combined with experimental validation. The active ingredients of QGQXM were analyzed using Ultra-performance liquid chromatography coupled with quadrupole time of flight mass spectrometry (UPLC-Q/TOF-MS). Network pharmacology was utilized to elucidate the mechanism of action of QGQXM for the treatment of DCM. Finally, in vivo validation was performed by intraperitoneal injection of STZ combined with high-fat feeding-induced DCM rat model. A total of 25 active compounds were identified in the drug-containing serum of rats, corresponding to 121 DCM-associated targets. GAPDH, TNF, AKT1, PPARG, EGFR, CASP3, and HIF1 were considered as the core therapeutic targets. Enrichment analysis showed that QGQXM mainly treats DCM by regulating PI3K-AKT, MAPK, mTOR, Insulin, Insulin resistance, and Apoptosis signaling pathways. Animal experiments showed that QGQXM improved cardiac function, attenuated the degree of cardiomyocyte injury and fibrosis, and inhibited apoptosis in DCM rats. Meanwhile, QGQXM also activated the PI3K/AKT signaling pathway, up-regulated Bcl-2, and down-regulated Caspase9, which may be an intrinsic mechanism for its anti-apoptotic effect. This study preliminarily elucidated the mechanism of QGQXM in the treatment of DCM and provided candidate compounds for the development of new drugs for DCM.

Effect of anger on endothelial-derived vasoactive factors in spontaneously hypertensive rats.

AIMS: We tested whether anger affects the balance between endothelium-derived vasodilators and vasoconstrictors in spontaneously hypertensive rats (SHRs). METHODS: Five endothelium-produced vasoactive factors (nitric oxide, prostacyclin, urotensin, endothelin and thromboxane B2) were measured in an established SHR behavioural model of anger, in "non-angry" SHR rats, and in control Wistar-Kyoto rats. RESULTS: All angry SHR rats showed the typical angry behaviour and angry SHR rats had significantly higher blood pressure and heart rate than control rats. Angry rats had significantly lower levels of two vasodilators, nitric oxide and prostacyclin, and significantly higher levels of two vasoconstrictors, endothelin and thromboxane B2 than either non-angry SHR or control rats. Levels of a third vasoconstrictor, urotensin, were significantly lower in angry SHR than in non-angry SHR or control rats. CONCLUSIONS: Our results suggest that anger causes an imbalance of endothelium-produced vasodilating and vasoconstricting substances. This may have implications for the development and/or progression of hypertension.

Identification and verification of feature biomarkers associated in heart failure by bioinformatics analysis.

Heart failure is the final destination of most cardiovascular diseases, and its complex molecular mechanisms remain largely uncertain. This study aimed to systematically investigate the underlying molecular mechanisms and diagnostic and therapeutic targets of heart failure using bioinformatics. We obtained 8 healthy samples and 8 heart failure samples from GSE8331 and GSE76701. After removing the batch effect, we performed a differential analysis on it and obtained 185 differentially expressed ID. The results of enrichment analysis showed that the molecular mechanisms of heart failure were mostly related to immune, inflammation, and metabolism-related pathways. Immune cell infiltration analysis showed that the degree of infiltration of Tgd cells and Neurons was significantly enriched in heart failure samples, whereas pDCs and NKTs were in healthy tissue samples. We obtained Hub genes including EGR1, EGR2, FOS and FOSB by PPI network analysis. We established a 4-gene diagnostic model with Hub gene, and validated it in GSE21610 and GSE57338, and evaluated the discriminative ability of Hub gene by ROC curve. The 4-gene diagnostic model has an AUC value of 0.775 in GSE21610 and 0.877 in GSE57338. In conclusion, we explored the underlying molecular mechanisms of heart failure and the immune cell infiltration environment of failing myocardium by performing bioinformatic analysis of the GEO dataset. In addition, we identified EGR1, EGR2, FOS and FOSB as potential diagnostic biomarkers and therapeutic targets for heart failure. More importantly, a diagnostic model of heart failure based on these 4 genes was developed, which leads to a new understanding of the pathogenesis of heart failure and may be an interesting target for future in-depth research.

Identification of immune-related genes for the diagnosis of ischemic heart failure based on bioinformatics.

The role of immune cells in the pathogenesis of ischemic heart failure (IHF) is well-established. However, identifying key genes in patients with IHF remains a challenge. We obtained two IHF datasets from the GEO database (GSE76701 and GSE21610), and identified four potential diagnostic candidate genes for IHF by using bioinformatics and machine learning algorithms, namely RNASE2, MFAP4, CHRDL1, and KCNN3. We constructed nomogram and validated the diagnostic value of these genes on additional GEO datasets (GSE57338). The results showed that these four genes had high diagnostic value (area under the curve value of 0.961). Furthermore, our immune infiltration analysis revealed the presence of three dysregulated immune cells in IHF, namely macrophages M2, monocytes, and T cells gamma delta. We also explored the potential molecular mechanisms of IHF. These findings provide new insights into the pathogenesis, diagnosis, and treatment of IHF.

Association between lean body mass and hypertension: A cross-sectional study of 50 159 NHANES participants.

Increasing attention has been paid to the association between lean body mass (LBM) and hypertension in recent years, but the previous findings have often been contradictory. Therefore, the authors investigated the association between LBM and hypertension through a cross-sectional study in the United States. To investigate the relationship between LBM and hypertension, the authors conducted weighted multivariable logistic regression models. The authors used the restricted cubic spline regression model to determine if there was a nonlinear correlation. In order to locate the inflection point, the authors built a two-part linear regression model using a recursive method. In the full adjustment model, LBM was positively associated with hypertension, with ORs (95% CI) of 1.19 (1.02, 1.38). In the further linear trend test, the ORs (95% CI) for Q2, Q3, and Q4 were 0.76 (0.60, 0.95), 0.62 (0.47, 0.80), and 0.66 (0.48, 0.91), respectively, compared to Q1, which suggested that the association between LBM and hypertension might be non-linear. The authors performed the restricted cubic spline curve to confirm this non-linear relationship and found the inflection point of 43.21 kg with an opposite relationship in which LBM and hypertension exhibited a negative correction of 0.66 (0.50, 0.86) before the inflection point and a positive correlation of 1.20 (1.03, 1.39) after the inflection point. Our study highlighted a non-linear association between LBM and hypertension in the general US population.

Cuproptosis, the novel therapeutic mechanism for heart failure: a narrative review.

Background and Objective: Heart failure (HF) is a global public health problem with high morbidity, readmission, and mortality rates. The central mediators of cardiomyocyte survival and death are mitochondria. Mitochondria are a key therapeutic target for HF and are closely involved in the pathophysiological process of HF. A recent study proposes that cuproptosis, a novel cell death mechanism, is closely related to mitochondrial respiration. Therefore, this study aims to explore the link between cuproptosis and HF, and to find novel therapeutic targets and treatments for HF. Methods: A literature search (up to April 2022) was conducted through PubMed database, and the search range was limited to publications in English. After further literature search and screening, we found that we are currently the first study to explore the association between HF and cuproptosis. Key Content and Findings: Research has found that mitochondria are a key therapeutic target in HF and are involved in the pathophysiological processes of energy metabolism, oxidative stress, calcium regulation, and cell death in HF. The micronutrient copper is involved in regulating mitochondrial biological processes, and high serum copper levels are significantly associated with HF. Copper overload affects mitochondrial function and exacerbates the development of HF. And cuproptosis induced by copper overload targeting lipoylated tricarboxylic acid cycle proteins, is closely related to mitochondrial respiration. Copper chelators not only treat HF but also partially rescue copper-mediated cell death. Copper binding to lipoylated components may be the reason for the hyperacetylation of mitochondrial proteins in HF. Ferredoxin 1 (FDX1) may be an upstream regulator of protein lipoylation and is closely related to cuproptosis. Conclusions: This study demonstrates the important roles of mitochondria and micronutrient copper in HF. Cuproptosis may be involved in the pathophysiological process of HF and is responsible for the hyperacetylation of mitochondrial proteins in HF. Cuproptosis has the potential to be a novel therapeutic mechanism for HF, and FDX1 may be a key target for cuproptosis-based treatment of HF. This study provides a new research direction for the treatment of HF and new ideas for the development of new drugs.

To Explore the Key Active Compounds and Therapeutic Mechanism of Guizhi Gancao Decoction in Coronary Heart Disease by Network Pharmacology and Molecular Docking.

Objective: Coronary heart disease (CHD) is the leading cause of death from cardiovascular disease and has become an important public health problem worldwide. Guizhi Gancao Decoction (GGD) has been shown to be used in the treatment of CHD with good efficacy, but its specific therapeutic mechanism and active ingredients have not been fully clarified. This study aims to identify the active compounds and key targets of GGD in the treatment of CHD, explore the therapeutic mechanism of GGD, and provide candidate compounds for anti-CHD drug development. Methods: The main compounds of GGD were determined by UPLC-MS/MS analysis and screened by SwissADME. The corresponding targets of GGD compounds were obtained from SwissTargetPrediction, and the targets of CHD were obtained from the HERB and GeneCards databases. The STRING 11.5 database was used to analyze the PPI (Protein-Protein Interactions) network of potential therapeutic targets of GGD compounds. Cytoscape 3.7.2 was used to construct target-related networks and find core targets. The GEO database was used to validate the differential expression of core targets. The PANTHER Classification System was used to functionally classify potential therapeutic targets for GGD. The GO biological process analysis and KEGG pathway analysis of targets were completed by DAVID 6.8 database. AutoDockTools 1.5.6 and PyMol 2.5.2 were used to perform molecular docking of core targets with the active GGD compounds. Results: 7 active GGD compounds were obtained based on UPLC-MS/MS and pharmacological parameter evaluation, which corresponded to 131 CHD-related targets. Among them, EGFR, MAPK3, RELA, CCND1, ESR1, PTGS2, NR3C1, CYP3A4, MMP9, and PTPN11 were considered core targets. According to the targets related to CHD, glycyrrhetinic acid, liquiritigenin, and schisandrin are considered key active ingredients. GO biological process and KEGG analysis indicated that the potential targets of GGD in the treatment of CHD involve a variety of biological processes and therapeutic mechanisms. Molecular docking results showed that both the core targets and the corresponding compounds had the good binding ability. Conclusions: This study contributes to a more comprehensive understanding of the therapeutic mechanism and active ingredients of GGD for CHD and provides candidate compounds for drug development of CHD.

Therapeutic Mechanism and Key Active Ingredients of Shenfu Injection in Sepsis: A Network Pharmacology and Molecular Docking Approach.

At present, although the early treatment of sepsis is advocated, the treatment effect of sepsis is unsatisfactory, and the mortality rate remains high. Shenfu injection (SFI) has been used to treat sepsis with good clinical efficacy. Based on network pharmacology, this study adopted a new research strategy to identify the potential therapeutic targets and key active ingredients of SFI for sepsis from the perspective of the pathophysiology of sepsis. This analysis identified 28 active ingredients of SFI based on UHPLC-QQQ MS, including 18 ginsenosides and 10 aconite alkaloids. 59 targets were associated with the glycocalyx and sepsis pathways. Based on the number of targets related to the pathophysiological process of sepsis, we identified songorine, ginsenoside Rf, ginsenoside Re, and karacoline as the key active ingredients of SFI for the treatment of sepsis. According to the cluster analysis of MCODE and the validation on the GEO dataset, LGALS3, BCHE, AKT1, and IL2 were identified as the core targets. This study further explored the therapeutic mechanism and the key active ingredients of SFI in sepsis and provided candidate compounds for drug development.

Guanmaitong Granule Attenuates Atherosclerosis by Inhibiting Inflammatory Immune Response in ApoE-/- Mice Fed High-Fat Diet.

Background: Atherosclerosis (AS) is the leading cause of cardiovascular diseases, such as myocardial infarction and stroke. Guanmaitong granule (GMTG) is a TCM (Traditional Chinese medicine) prescribed to treat AS. However, its mechanism remains unclear. Methods: We obtained reliable ingredients and targets of GMTG using the HERB database. AS-related targets were obtained from HERB and GeneCards databases. The target database was constructed by intersecting the ingredients of GMTG with the AS-related targets. STRING and Cytoscape were used to create protein-protein interaction (PPI) network and screen core targets. GO enrichment analysis and KEGG pathway analyses were performed using R. Finally, the ApoE-/- mice AS model was induced by a high-fat diet (HFD) for in vivo validation of core pathways and targets. Results: A total of 124 ingredients and 418 potential targets of GMTG for treating AS were obtained. Numerous ingredients and targets were related to Panax notoginseng, Salvia miltiorrhiza, and Astragalus. Most core targets and pathways were involved in the inflammatory immune response. GMTG could decrease serum triglycerides, total cholesterol, low-density lipoprotein-cholesterol, and oxidized low-density lipoprotein level and increase the serum high-density lipoprotein-cholesterol level. Furthermore, GMTG reduced the plaque burden and promoted plaque remodeling by reducing plaque area, lipid deposition, foam cell content, and collagen fiber content in the plaque in the aortic root of ApoE-/- mice. GMTG inhibited systemic and plaque inflammatory immune response and increased plaque stability by inhibiting the excessive release of the TLR4/MyD88/NF-κB pathway-induced inflammatory cytokines, tumor necrosis factor, interleukin-6, and interleukin-1 beta. Conclusion: Radix notoginseng, Radix salviae liguliobae, and Radix astragali are the main ingredients of GMTG for treating AS. Further, GMTG could regulate the level of serum lipids and inhibit inflammatory immune response, which resulted in anti-AS effects such as plaque stabilization, reduction of plaque burden, and plaque remodeling. GMTG is a promising multi-target treatment for AS.

Risk factors for in-stent restenosis after coronary stent implantation in patients with coronary artery disease: A retrospective observational study.

To explore the risk factors for in-stent restenosis (ISR) after stent implantation in patients with coronary heart disease (CHD) using logistic regression analysis. From February 2020 to February 2022, 350 patients with CHD after percutaneous coronary intervention (PCI) were divided into a stent stenosis group and a stent nonstenosis group based on coronary angiography results performed 2 years after PCI. Univariate and multivariate logistic regressions were used to analyze the factors related to ISR after coronary stent implantation in patients with CHD. This study was approved by the Ethics Committee of Shandong University of Traditional Chinese Medicine. Patient signed informed consent. Of the 350 patients with CHD, 138 (39.43%) had stent restenosis while 212 did not. Univariate analysis showed that a family history of CHD, history of type 2 diabetes, hypertension, smoking, and drinking, discontinuation of aspirin, use of conventional dose statins, calcified lesions, ≥ 3 implanted stents, stent length ≥ 30 mm, stent diameter < 3 mm, and tandem stent increased the risk of restenosis. The incidence of restenosis was higher in the stent group than that in the nonstent group (P < .05). There were no significant differences in the blood lipid level, left ventricular ejection fraction, clopidogrel/ticagrelor or beta-blocker withdrawal, location of culprit vessels, and thrombotic lesions between the 2 groups (P > .05). Multivariate logistic regression analysis showed that family history of CHD, history of type 2 diabetes, hypertension, smoking, and drinking, aspirin withdrawal, use of conventional doses of statins, calcified lesions, ≥ 3 implanted stents, stent length ≥ 30 mm, stent diameter < 3 mm, and tandem stenting were risk factors for ISR within 2 years after PCI. A family history of CHD, history of type 2 diabetes, hypertension, smoking, and drinking, discontinuation of aspirin, use of conventional dose statins, calcified lesions, ≥ 3 stent implantations, stent length ≥ 30 mm, stent diameter < 3 mm, and tandem stenting are risk factors for ISR within 2 years after PCI in patients with CHD.

Application of network pharmacology and molecular docking approach to explore active compounds and potential pharmacological mechanisms of Aconiti Lateralis Radix Praeparata and Lepidii Semen Descurainiae Semen for treatment of heart failure.

BACKGROUND: Heart failure (HF) is the end stage of the development of heart disease, whose prognosis is poor. The previous research of our team indicated that the formulae containing Aconiti Lateralis Radix Praeparata and Lepidii Semen Descurainiae Semen (ALRP-LSDS) could inhibit myocardial hypertrophy, inhibit cardiomyocyte apoptosis, delay myocardial remodeling (REM), and improve the prognosis of patients with HF effectively. In order to explore the mechanism of ALRP-LSDS for the treatment of HF, a combined approach of network pharmacology and molecular docking was conducted. METHODS: Public database TCMSP was used to screen the active compounds of ALRP-LSDS. The targets of screened active compounds were obtained from the TCMSP database and predicted using the online analysis tool PharmMapper. The targets of HF were obtained from 6 databases including GeneCards, OMIM, DrugBank, TTD, PharmGKB, and DisGeNET. Protein-protein interaction and enrichment analysis were performed, respectively, by STRING and Metascape online tools after merging the targets of active compounds and HF. Cytoscape software was used to conduct networks. Finally, molecular docking was performed by Vina to verify the correlation between key targets and active compounds. RESULTS: Final results indicated that the active compounds including ß-sitosterol, isorhamnetin, quercetin, kaempferol, and (R)-norcoclaurine, the targets including AKT1, CASP3, and MAPK1 might be the main active compounds and key targets of ALRP-LSDS for the treatment of HF separately. The binding ability of AKT1 to the main active compounds was better compared with the other 2 key targets, which means it might be more critical. The pathways including AGE-RAGE signaling pathway in diabetic complications, Pathways in cancer, and Fluid shear stress and atherosclerosis might play important roles in the treatment of HF with ALRP-LSDS. In general, ALRP-LSDS could inhibit cardiomyocyte apoptosis, delay REM, and improve cardiac function through multicompound, multitarget, and multipathway, which contributes to the treatment of HF. CONCLUSIONS: Based on the combined approach of network pharmacology and molecular docking, this study screened out the main active compounds, key targets, and main pathways of ALRP-LSDS for the treatment of HF, and revealed its potential mechanisms, providing a theoretical basis for further research.

Decoding the Mechanism of Shixiao Powder in Treating Coronary Heart Disease Based on Network Pharmacology and Molecular Docking.

Shixiao powder comes from the Formularies of the Bureau of People's Welfare Pharmacies in the Song Dynasty and consists of two herbs, Puhuang (PH) and Wulingzhi (WLZ). PH-WLZ is a commonly used drug pair for the treatment of coronary heart disease (CHD), and its clinical effect is remarkable. However, our understanding of the mechanism of treatment of CHD is still unclear. In this study, the method of network pharmacology was used to explore the mechanism of PH-WLZ in the treatment of CHD. A total of 56 active ingredients were identified from PH-WLZ, of which 93 targets of 41 active ingredients overlapped with those of CHD. By performing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, we obtained the main pathways associated with CHD and those associated with the mechanism of PH-WLZ in the treatment of CHD. By constructing the protein-protein interaction (PPI) network of common targets, 10 hub genes were identified. Based on the number of hub genes contained in the enrichment analysis, we obtained the key pathways of PH-WLZ in the treatment of CHD. The key KEGG pathway in the treatment of CHD by PH-WLZ is mainly enriched in atherosclerosis, inflammation, immunity, oxidative stress, and infection-related pathways. Moreover, the results of molecular docking showed that the active ingredients of PH-WLZ had a good affinity with the hub genes. The results indicate that the mechanism of PH-WLZ in the treatment of CHD may be related to regulation of lipid metabolism, regulation of immune and inflammatory responses, regulation of downstream genes of fluid shear stress, antiaging and oxidative stress, and virus inhibition.

Bioinformatics analysis identifies ferroptosis­related genes in the regulatory mechanism of myocardial infarction.

Since ferroptosis is considered to be a notable cause of cardiomyocyte death, inhibiting ferroptosis has become a novel strategy in reducing cardiac cell death and improving cardiopathic conditions. Therefore, the aim of the present study was to search for ferroptosis-related hub genes and determine their diagnostic value in myocardial infarction (MI) to aid in the diagnosis and treatment of the disease. A total of 10,286 DEGs were identified, including 6,822 upregulated and 3.464 downregulated genes in patients with MI compared with healthy controls. After overlapping with ferroptosis-related genes, 128 ferroptosis-related DEGs were obtained. WGCNA successfully identified a further eight functional modules, from which the blue module had the strongest correlation with MI. Blue module genes and ferroptosis-related differentially expressed genes were overlapped to obtain 20 ferroptosis-related genes associated with MI. Go and KEGG analysis showed that these genes were mainly enriched in cellular response to chemical stress, trans complex, transferring, phosphorus-containing groups, protein serine/threonine kinase activity, FoxO signaling pathway. Hub genes were obtained from 20 ferroptosis-related genes through the PPI network. The expression of hub genes was found to be down-regulated in the MI group. Finally, the miRNAs-hub genes and TFs-hub genes networks were constructed. The GSE141512 dataset and the use of RT-qPCR assays on patient blood samples were used to confirm these results. The results showed that ATM, PIK3CA, MAPK8, KRAS and SIRT1 may play key roles in the development of MI, and could therefore be novel markers or targets for the diagnosis or treatment of MI.