Patients with a history of cardiovascular disease (CVD) who contract coronavirus disease 2019 (COVID-19) tend to have a worse prognosis and more severe cardiovascular side effects.COVID-19 vaccines, which are intended to prevent COVID-19, may also potentially reduce the severity and complications (including cardiovascular sequelae) of COVID-19, especially in patients with a history of CVD. However, there have also been reports of cardiovascular side effects from COVID-19 vaccines of various brands and types. The purpose of this study is to review the benefits and harms of COVID-19 vaccines in relation to CVD. In this thorough review of the most current evidence on the benefits and harms of COVID-19 vaccines, we present information about the characteristics of cardiovascular complications. Most of the evidence focuses on myocarditis or pericarditis, which are most strongly associated with mRNA vaccines and predominantly occur in young males within days of receiving the second dose. Meanwhile, post-vaccination myocardial infarction is more common in older males, and the first dose of adenoviral vector vaccines appears to play a greater role in this complication. This information may guide us in formulating alternative options and implementing targeted surveillance. Gaining more knowledge about the potential benefits and harms of COVID-19 vaccines will improve our ability to make informed decisions and judgments about the balance of these factors.

OBJECTIVETo study the effect of Dangua Recipe (DGR) on glycolipid metabolism, vascular cell adhesion molecule-1 (VCAM-1) and its mRNA expression level of transgenic Apo E(-/-) mouse with spontaneous atherosclerosis, thus revealing its partial mechanism for curing diabetes mellitus (DM) with angiopathy.

METHODSDiabetic model was prepared by peritoneally injecting streptozotocin (STZ) to Apo E(-/-) mouse. Totally 32 modeled mice were stratified by body weight, and then divided into 4 groups referring to blood glucose levels from low to high by random digit table, i.e., the model group (MOD, fed with sterile water, at the daily dose of 15 mL/kg), the DGR group (fed with DGR at the daily dose of 15 mL/kg), the combination group (COM, fed with DGR at the daily dose of 15 mL/kg and pioglitazone at the daily dose of 4.3 mg/kg), and the pioglitazone group (PIO, at the daily dose of 4.3 mg/kg), 8 in each group. Another 8 normal glucose C57 mouse of the same age and strain were recruited as the control group. All interventions lasted for 12 weeks by gastrogavage. The fasting blood glucose (FBG), body weight, food intake, water intake, skin temperature, the length of tail, and the degree of fatty liver were monitored. The hemoglobin A1c (HbA1c), total cholesterol (TC), and LDL-C were determined. Endothelin-1 (ET-1) was determined by radioimmunoassay. Nitrogen monoxidum (NO) was determined by nitrate reductase. The kidney tissue VCAM-1 level was analyzed with ELISA. The expression of VCAM-1 mRNA in the kidney tissue was detected with real time quantitative PCR.

RESULTSCompared with the control group, the body weight and food intake decreased, water intake increased in all the other model groups (P < 0.05). Besides, the curve of blood glucose was higher in all the other model groups than in the control group (P < 0.01). Compared with the model group, the body weight increased; levels of HbAlc, TC, LDL-C, ET-1, and VCAM-1 were significantly lower; and skin temperature was higher in the DGR group (P < 0.05, P < 0.01). Compared with the PIO group, body weight, the increment of body weight, FBG, TC, and LDL-C were lower (P < 0.05, P < 0.01); food intake and water intake increased more and the tail length was longer in the DRG group (P < 0.01). There was no statistical difference in the level of NO among groups. The degree of fatty liver in the model group was significantly severer than that in the control group (P < 0.05). It was obviously alleviated in the DGR group (P < 0.05) when compared with the model group and the PIO group (P < 0.05, P < 0.01). But it was severer in the PIO group than in the model group (P < 0.01). The degree of fatty liver in the combination group ranged between that of the DGR group and the PIO group (P < 0.05). The level of VCAM-1 mRNA expression was significantly lower in the DGR group than in the model group, the PIO group, and the combination group (P < 0.05).

CONCLUSIONSDGR had effect in lowering blood glucose and blood lipids, and fighting against fatty liver of transgenic Apo E(-/-) mouse with spontaneous atherosclerosis. DGR played an effective role in preventing and treating DM with angiopathy by comprehensively regulating glycolipid metabolism and promoting the vascular function.

Animals ; Apolipoproteins E ; genetics ; Blood Glucose ; metabolism ; Diabetes Mellitus, Experimental ; blood ; drug therapy ; Diabetic Angiopathies ; drug therapy ; Drugs, Chinese Herbal ; pharmacology ; Lipids ; blood ; Male ; Mice ; Mice, Knockout ; RNA, Messenger ; genetics ; Random Allocation ; Thiazolidinediones ; pharmacology ; Vascular Cell Adhesion Molecule-1 ; genetics ; metabolism

Purpose: Numerous studies have produced conflicting findings regarding the efficacy of statins in prostate cancer treatment. Our objective was to examine the correlation between statin usage and clinical outcomes in Taiwanese men with de novo metastatic prostate cancer. Materials and Methods: We identified patients diagnosed with de novo metastatic prostate cancer from the Chang Gung Research Database spanning the years 2007 to 2020. To minimize confounding bias, we employed the inverse probability of treatment weighting (IPTW) method. Clinical outcomes were assessed using IPTW-adjusted Kaplan-Meier curves. Multivariate Cox proportional hazard regression analysis was utilized to evaluate the association between mortality and clinical factors. Results: The study cohort comprised 1,716 statin users and 276 non-users. Patients who used statins exhibited a longer median overall survival (85.4 months compared to 58.2 months; p=0.001) and cancer-specific survival (112.6 months compared to 75.7 months; p<0.001) compared to non-users. The median time to the development of castration-resistant status was similar between statin users and non-users (p=0.069). Multivariable Cox proportional hazards regression analysis, after IPTW adjustment, demonstrated that statin use was associated with improved overall survival. Conclusions Our study indicates that the use of statins following a de novo metastatic prostate cancer diagnosis enhances survival outcomes. However, statins did not appear to delay the onset of castration-resistant status. Further large-scale and long-term studies are warranted to investigate the biological effects of statins in men with prostate cancer.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.