Apoptosis has been observed previously in hearts subjected to either continuous ischemia or ischemia followed by reperfusion. The purpose of this study was to compare the timing and extent of apoptosis in both continuously ischemic and reperfused myocardium. We show that rats subjected to continuous coronary artery occlusion display characteristic signs of apoptosis solely in the ischemic myocardium after only 2.25 hours of ischemia, as illustrated by positive in situ end labeling (ISEL) of apoptotic cardiomyocyte nuclei in tissue sections and/or the presence of DNA “ladders” in agarose gels. In contrast, reperfusion after a 45-minute occlusion accelerated the process, with apoptosis becoming evident solely in the reperfused myocardium after only 1 hour of reperfusion. ISEL and DNA ladder intensity increased with duration of ischemia or reperfusion. The volume of myocardium in which ISEL was observed was smaller in the reperfused hearts, and the ISEL-stained nuclei represented 23% and 33% of the total nuc...

Apoptosis in Ischemic and Reperfused Rat Myocardium

Paeoniflorin protects against intestinal ischemia/reperfusion by activating LKB1/AMPK and promoting autophagy.

Current state and future perspective of cardiovascular medicines derived from natural products.

Danshen, the dried root of Salvia miltiorrhiza Bge, is a common medicinal herb in Traditional Chinese Medicine, which has been used for the treatment of a number of diseases for thousands of years. More than 2000 years ago, the Chinese early pharmacy monograph "Shennong Materia Medica" recorded that Danshen could be used for the treatment of gastrointestinal diseases, cardiovascular diseases, certain gynecological diseases, etc. Since then, Danshen has been widely used clinically in many different prescriptions for many different diseases, especially for the treatment of cardiovascular diseases. Nowadays, many pharmacological studies about the water-soluble components from Danshen have been reported, especially salvianolic acids. It turned out that salvianolic acids showed strong anti-lipid peroxidation and anti-thrombic activities, and among them, SalAA and SalAB were the most potent. This review focused on the achievements in research of salvianolic acids regarding their bioactivities and pharmacological effects. These studies not only shed light on the water-soluble active components of Danshen and their mechanisms at the molecular level, but also provided theoretical information for the development of new medicines from Danshen for the treatment of cardiovascular and cerebrovascular diseases, inflammatory diseases, metabolic diseases, etc.

Chemical and pharmacological research on the polyphenol acids isolated from Danshen: A review of salvianolic acids.

Stroke is an acute cerebrovascular disease caused by ruptured or blocked blood vessels. For the prevention of ischemic stroke, the coagulation state of blood and cerebrovascular protection should be considered. Our previous study has shown that salvianolic acid A (SAA), which is a water-soluble component from the root of Salvia Miltiorrhiza Bge, prevents thrombosis with a mild inhibitory effect on platelet aggregation. In this study we investigated the preventive effects of SAA on cerebrovascular endothelial injury caused by ischemia in vivo and oxygen-glucose deprivation (OGD) in vitro, and explored the underlying mechanisms. An autologous thrombus stroke model was established in SD rats by electrocoagulation. SAA (10 mg/kg) was orally administered twice a day for 5 days before the operation. The rats were sacrificed at 24 h after the operation. We showed that pretreatment with SAA significantly improved the neurological deficits, intracerebral hemorrhage, BBB disruption, and vascular endothelial dysfunction as compared with model group. In human brain microvascular endothelial cells (HBMECs), pretreatment with SAA (10 μM) significantly inhibited OGD-induced cell viability reduction and degradation of tight junction proteins (ZO-1, occludin, claudin-5). Furthermore, we found that SAA inhibited the upregulation of Src signaling pathway in vivo and vitro and reversed the increased expression of matrix metalloproteinases (MMPs) after ischemic stroke. In conclusion, our results suggest that SAA protects cerebrovascular endothelial cells against ischemia and OGD injury via suppressing Src signaling pathway. These findings show that pretreatment with SAA is a potential therapeutic strategy for the prevention of ischemic stroke.

Salvianolic acid A prevented cerebrovascular endothelial injury caused by acute ischemic stroke through inhibiting the Src signaling pathway.

Prompt myocardial reperfusion during acute myocardial infarction by fibrinolytic therapy, percutaneous coronary intervention, or coronary artery bypass grafting limits the affected area and improves prognosis. However, reperfusion itself can cause cardiomyocyte damage and decrease treatment efficacy. No treatments that effectively prevent myocardial ischemia/reperfusion (I/R) injury are currently available, and are therefore the focus of ongoing research. Salvianolic acid A (SAA), the active ingredient of the traditional Chinese herbal remedy Salvia miltiorrhiza, has anti-thrombotic activity, anti-inflammatory, and anti-cancer activity; regulates blood lipids and provides hepatic and neural protection. Recent studies demonstrated that SAA inhibits cardiomyocyte apoptosis in response to I/R by the PI3K/Akt, GSK-3β, JNK, and ERK1/2 pathways, and by JNK-ERK1/2 crosstalk. The mechanisms for SAA attenuating cardiomyocytes apoptosis during I/R injury through the P38 MAPK, caspase, JAK/STAT, NF-κB and LOX-1 signaling pathways need further illustration. There may be potential crosstalks between PI3K/Akt and JNK, and Akt/GSK-3β and ERK1/2 in the process of SAA against I/R-incuced cardiomyocytes apoptosis. This review summarizes the recent evidence of the anti-apoptotic effects and mechanisms of SAA against myocardial I/R injury and discusses the basis of potential clinical applications of SAA.

Anti-apoptotic effects and mechanisms of salvianolic acid A on cardiomyocytes in ischemia-reperfusion injury

Objective The aim of this study was to evaluate the value of real-time myocardial contrast echocardiography (RT-MCE) for detecting coronary microcirculation (CM) function in coronary artery disease (CAD) patients. Methods Sixty-five consecutive patients were divided into CAD (n=52) and no-CAD (n=13) groups using coronary angiography (CAG). All patients underwent RT-MCE at rest and CAG within 1 week after RT-MCE. The ventricular segments in CAD patients were divided semi-quantitatively into ischemic and non-ischemic myocardial groups based on RT-MCE images. Myocardial blood volume (A), myocardial blood flow velocity (s), and mean myocardial blood flow (Axβ) were obtained. The Gensini scores were calculated for CAD patients. The receiver operating characteristic (ROC) curve areas of A, s, and Axs were calculated to assess CM function in CAD patients. Results A total of 798 and 204 segments were investigated in the CAD and non-CAD groups, respectively. In CAD patients, 332 ischemic and 466 non-ischemic segments were identified. The values of A, s, and Axs were significantly different among non-CAD, CAD, ischemic, and nonischemic groups. ROC curve areas of A, s, and Axs were 0.85, 0.79, and 0.83, respectively, and significant differences were observed in these values among three Gensini score groups of the CAD patients. Conclusion Varying degrees of CM function deterioration was observed in CAD patients both in ischemic and non-ischemic areas, with the deterioration being more sever in the former.

The value of real-time myocardial contrast echocardiography for detecting coronary microcirculation function in coronary artery disease patients.

Background Many diabetic patients develop and progress to diabetic foot ulcers, which seriously affect health and quality of life and cause great economic and psychological stress, especially in elderly diabetic patients who often have various underlying diseases, and the consequences of their progression to diabetic foot ulcers are more serious and seriously affect elderly patients in surgery. Therefore, it is particularly important to analyze the influencing factors related to the progression of elderly diabetic patients to diabetic foot, and the column line graph prediction model is drawn based on regression analysis to derive the influencing factors of the progression of elderly diabetic patients to diabetic foot, and the total score derived from the combination of various influencing factors can visually calculate the probability of the progression of elderly diabetic patients to diabetic foot. Objective The influencing factors of progression deterioration to diabetic foot in elderly diabetic patients based on LASSO regression analysis and logistics regression analysis, and the column line graph prediction model was established by statistically significant risk factors. Methods The clinical data of elderly diabetic patients aged 60 years or older in the orthopedic ward and endocrine ward of the Third Hospital of Shanxi Medical University from 2015-01-01 to 2021-12-31 were retrospectively analyzed and divided into a modeling population (211) and an internal validation population (88) according to the random assignment principle. Firstly, LASSO regression analysis was performed based on the modeling population to screen out the independent influencing factors for progression to diabetic foot in elderly diabetic patients; Logistics univariate and multifactor regressions were performed by the screened influencing factors, and then column line graph prediction models for progression to diabetic foot in elderly diabetic patients were made by these influencing factors, using ROC (subject working characteristic curve) and AUC (their area under the curve), C-index validation, and calibration curve to initially evaluate the model discrimination and calibration. Model validation was performed by the internal validation set, and the ROC curve, C-index and calibration curve were used to further evaluate the column line graph model performance. Finally, using DCA (decision curve analysis), we observed whether the model could be used better in clinical settings. Results and conclusions (1) LASSO (Least absolute shrinkage and selection operator) regression analysis yielded a more significant significance on risk factors for progression to diabetic foot in elderly diabetic patients, such as age, presence of peripheral neuropathy, history of smoking, duration of disease, serum lactate dehydrogenase, and high-density cholesterol; (2) Based on the influencing factors and existing theories, a column line graph prediction model for progression to diabetic foot in elderly diabetic patients was constructed. The working characteristic curves of subjects in the training group and their area under the curve (area under the curve = 0.840) were also analyzed simultaneously with the working characteristic curves of subjects in the external validation population and their area under the curve (area under the curve = 0.934), which finally showed that the model was effective in predicting column line graphs; (iii) the C-index in the modeled cohort was 0.840 (95%CI: 0.779-0.901) and the C-index in the validation cohort was 0.934 (95%CI: 0.887-0.981), indicating that the model had good predictive accuracy; the calibration curve fit was good; (iv) the results of the decision curve analysis showed that the model would have good results in clinical use; (v) it indicated that the established predictive model for predicting progression to diabetic foot in elderly diabetic patients had good test efficacy and helped clinically screen the possibility of progression to diabetic foot in elderly diabetic patients and give personalized interventions to different patients in time.

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Establishment and validation of a nomogram for progression to diabetic foot ulcers in elderly diabetic patients

Background Prevention and treatment of liver fibrosis at an early stage is of great prognostic importance, whereas changes in liver stiffness are often overlooked in patients before the onset of obvious clinical symptoms. Recognition of liver fibrosis at an early stage is therefore essential. Objective An XGBoost machine learning model was constructed to predict participants' liver stiffness measures (LSM) from general characteristic information, blood test metrics and insulin resistance-related indexes, and to compare the fit efficacy of different datasets for LSM. Methods All data were obtained from the National Health and Nutrition Examination Survey (NHANES) for the time interval January 2017 to March 2020. Participants' general characteristics, Liver Ultrasound Transient Elastography (LUTE) information, indicators of blood tests and insulin resistance-related indexes were collected, including homeostasis model assessment of insulin resistance (HOMA-IR) and metabolic score for insulin resistance (METS-IR). Three datasets were generated based on the above information, respectively named dataset A (without the insulin resistance-related indexes as predictor variables), dataset B (with METS-IR as a predictor variable) and dataset C (with HOMA-IR as a predictor variable). XGBoost regression was used in the three datasets to construct machine learning models to predict LSM in participants. A random split was used to divide all participants included in the study into training and validation cohorts in a 3:1 ratio, and models were developed in the training cohort and validated with the validation cohort. Results A total of 3,564 participants were included in this study, 2,376 in the training cohort and 1,188 in the validation cohort, and all information was not statistically significantly different between the two cohorts (p > 0.05). In the training cohort, datasets A and B both had better predictive efficacy than dataset C for participants' LSM, with dataset B having the best fitting efficacy [±1.96 standard error (SD), (-1.49,1.48) kPa], which was similarly validated in the validation cohort [±1.96 SD, (-1.56,1.56) kPa]. Conclusions XGBoost machine learning models built from general characteristic information and clinically accessible blood test indicators are practicable for predicting LSM in participants, and a dataset that included METS-IR as a predictor variable would improve the accuracy and stability of the models.

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Zilong Wang

Papers

Anti-apoptotic effects and mechanisms of salvianolic acid A on cardiomyocytes in ischemia-reperfusion injury

The value of real-time myocardial contrast echocardiography for detecting coronary microcirculation function in coronary artery disease patients.

Establishment and validation of a nomogram for progression to diabetic foot ulcers in elderly diabetic patients

Machine learning models including insulin resistance indexes for predicting liver stiffness in United States population: Data from NHANES