Myocardial infarction is a cardiovascular disease (CVD) with high morbidity and mortality, which can trigger a cascade of cardiac pathophysiological changes, including fibrosis, inflammation, ischemia-reperfusion injury (IRI), and ventricular remodeling, ultimately leading to heart failure (HF). While conventional pharmacological treatments and clinical reperfusion therapy may enhance short-term prognoses and emergency survival rates, both approaches have limitations and adverse effects. Natural products (NPs) are extensively utilized as therapeutics globally, with some demonstrating potentially favorable therapeutic effects in preclinical and clinical pharmacological studies, positioning them as potential alternatives to modern drugs. This review comprehensively elucidates the pathophysiological mechanisms during myocardial infarction and summarizes the mechanisms by which NPs exert cardiac beneficial effects. These include classical mechanisms such as inhibition of inflammation and oxidative stress, alleviation of cardiomyocyte death, attenuation of cardiac fibrosis, improvement of angiogenesis, and emerging mechanisms such as cardiac metabolic regulation and histone modification. Furthermore, the review emphasizes the modulation by NPs of novel targets or signaling pathways in classical mechanisms, including other forms of regulated cell death (RCD), endothelial-mesenchymal transition, non-coding ribonucleic acids (ncRNAs) cascade, and endothelial progenitor cell (EPC) function. Additionally, NPs influencing a particular mechanism are categorized based on their chemical structure, and their relevance is discussed. Finally, the current limitations and prospects of NPs therapy are considered, highlighting their potential for use in myocardial infarction management and identifying issues that require urgent attention.
Humans ; Myocardial Infarction/genetics* ; Biological Products/therapeutic use* ; Animals ; Oxidative Stress/drug effects* ; Signal Transduction/drug effects*

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.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.

Objective: To explore the prognostic factors of extracellular NK/T cell lymphoma (ENKTL) treated with pegaspargase/L-asparaginase. Methods: The clinical data of 656 ENKTL patients diagnosed at 11 medical centers in the Huaihai Lymphoma Working Group from March 2014 to April 2021 were retrospectively analyzed. The patients were randomly divided into two groups: a training set (460 cases) and a validation set (196 cases) at 7∶3, and the prognostic factors of the patients were analyzed. A prognostic scoring system was established, and the predictive performance of different models was compared. Results: Patients' median age was 46 (34, 57) years, with 456 males (69.5% ) and 561 nasal involvement (85.5% ). 203 patients (30.9% ) received a chemotherapy regimen based on L-asparaginase combined with anthracyclines, and the 5-year overall survival rate of patients treated with P-GEMOX regimen (pegaspargase+gemcitabine+oxaliplatin) was better than those treated with SMILE regimen (methotrexate+dexamethasone+cyclophosphamide+L-asparaginase+etoposide) (85.9% vs 63.8% ; P=0.004). The results of multivariate analysis showed that gender, CA stage, the Eastern Cooperative Oncology Group performance status (ECOG PS) score, HGB, and EB virus DNA were independent influencing factors for the prognosis of ENKTL patients (P<0.05). In this study, the predictive performance of the prognostic factors is superior to the international prognostic index, Korean prognostic index, and prognostic index of natural killer lymphoma. Conclusion: Gender, CA stage, ECOG PS score, HGB, and EB virus DNA are prognostic factors for ENKTL patients treated with pegaspargase/L-asparaginase.
Male ; Humans ; Middle Aged ; Asparaginase/therapeutic use* ; Prognosis ; Retrospective Studies ; Lymphoma, Extranodal NK-T-Cell/drug therapy* ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Etoposide ; Cyclophosphamide ; Methotrexate/therapeutic use* ; DNA/therapeutic use* ; Treatment Outcome

Objective: To investigate hypertriglyceridemia and hepatomegaly caused by Schisandrae Sphenantherae Fructus (FSS) and Schisandra chinensis Fructus (FSC) oils in mice. Methods: Mice were orally administered a single dose of Schisandrae Fructus oils. Serum and hepatic triglyceride (TG), triglyceride transfer protein (TTP), apolipoprotein B48 (Apo B48), very-low-density lipoprotein (VLDL), hepatocyte growth factor (HGF), alanine aminotransfease (ALT) and liver index were measured at 6-120 h post-dosing. Results: FSS and FSC oil caused time and dose-dependent increases in serum and hepatic TG levels, with maximum increases in the liver (by 297% and 340%) at 12 h post-dosing and serum (244% and 439%) at 24-h post-dosing, respectively. Schisandrae Fructus oil treatments also elevated the levels of serum TTP by 51% and 63%, Apo B48 by 152% and 425%, and VLDL by 67% and 38% in mice, respectively. FSS and FSC oil treatments also increased liver mass by 53% and 55% and HGF by 106% and 174%, but lowered serum ALT activity by 38% and 22%, respectively. Fenofibrate pre/ co-treatment attenuated the FSS and FSC oil-induced elevation in serum TG levels by 41% and 49% at 48 h post-dosing, respectively, but increased hepatic TG contents (by 38% and 33%, respectively) at 12 h post-dosing. Conclusions: Our findings provide evidence to support the establishment of a novel mouse model of hypertriglyceridemia by oral administration of FSS oil (mainly increasing endogenous TG) and FSC oil (mainly elevating exogenous TG).