ObjectivesParkinson’s disease (PD) is a neurological condition with selective progressive degeneration of dopaminergic neurons. Routine therapies are symptomatic and palliative. Although, hesperidin (Hsd) is known for its neuroprotective effects, its exact cellular mechanism is still a mystery. Considering the important role of calcium (Ca2+) in cellular mechanisms of neurodegenerative diseases, the present study aimed to investigate the possible effects of Hsd on Ca2+ channels in cellular model of PD and the possible association between the selective vulnerability of neurons in cellular models of PD and expression of the physiological phenotype that changes Ca2+ homeostasis.MethodsSH-SY5Y cell line was used in this study; cell damage was induced by 150 µM 6-OHDA and the cells’ viability was examined using MTT assay. Intracellular calcium, reactive oxygen species (ROS) and mitochondrial membrane potential were determined by the fluorescence spectrophotometry method. The expressions of calcium channel receptors were determined by gel electrophoresis and immunoblotting.ResultsLoss of cell viability and mitochondrial membrane potential were confirmed in 6-OHDA treated cells. In addition, intracellular ROS and calcium levels, calcium channel receptors significantly increased in 6-OHDA-treated cells. Incubation of SH-SY5Y cells with hesperidin showed a protective effect, reduced the biochemical markers of cell damage/death, and balanced calcium hemostasis.ConclusionsBased on our findings, it seems that hesperidin could suppress the progression of the cellular model of PD via acting on intracellular calcium homeostasis. Further studies are needed to confirm the potential benefits of preventive and therapeutic effects of stabilizing cellular calcium homeostasis in neurodegenerative disease.

BackgroundAs the era of big data analytics unfolds, machine learning (ML) might be a promising tool for predicting clinical outcomes. This study aimed to evaluate the predictive ability of ML models for estimating mortality after coronary artery bypass grafting (CABG).Materials and methodsVarious baseline and follow-up features were obtained from the CABG data registry, established in 2005 at Tehran Heart Center. After selecting key variables using the random forest method, prediction models were developed using: Logistic Regression (LR), Support Vector Machine (SVM), Naïve Bayes (NB), K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGBoost), and Random Forest (RF) algorithms. Area Under the Curve (AUC) and other indices were used to assess the performance.ResultsA total of 16,850 patients with isolated CABG (mean age: 67.34 ± 9.67 years) were included. Among them, 16,620 had one-year follow-up, from which 468 died. Eleven features were chosen to train the models. Total ventilation hours and left ventricular ejection fraction were by far the most predictive factors of mortality. All the models had AUC > 0.7 (acceptable performance) for 1-year mortality. Nonetheless, LR (AUC = 0.811) and XGBoost (AUC = 0.792) outperformed NB (AUC = 0.783), RF (AUC = 0.783), SVM (AUC = 0.738), and KNN (AUC = 0.715). The trend was similar for two-to-five-year mortality, with LR demonstrating the highest predictive ability.ConclusionVarious ML models showed acceptable performance for estimating CABG mortality, with LR illustrating the highest prediction performance. These models can help clinicians make decisions according to the risk of mortality in patients undergoing CABG.

ImportanceBell palsy (BP) has been reported as an adverse event following the SARS-CoV-2 vaccination, but neither a causative relationship nor a higher prevalence than in the general population has been established.ObjectiveTo compare the incidence of BP in SARS-CoV-2 vaccine recipients vs unvaccinated individuals or placebo recipients.Data SourcesA systematic search of MEDLINE (via PubMed), Web of Science, Scopus, Cochrane Library, and Google Scholar from the inception of the COVID-19 report (December 2019) to August 15, 2022.Study SelectionArticles reporting BP incidence with SARS-CoV-2 vaccination were included.Data Extraction and SynthesisThis study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline and was conducted with the random- and fixed-effect models using the Mantel-Haenszel method. The quality of the studies was evaluated by the Newcastle-Ottawa Scale.Main Outcomes and MeasuresThe outcomes of interest were to compare BP incidence among (1) SARS-CoV-2 vaccine recipients, (2) nonrecipients in the placebo or unvaccinated cohorts, (3) different types of SARS-CoV-2 vaccines, and (4) SARS-CoV-2–infected vs SARS-CoV-2–vaccinated individuals.ResultsFifty studies were included, of which 17 entered the quantitative synthesis. Pooling 4 phase 3 randomized clinical trials showed significantly higher BP in recipients of SARS-CoV-2 vaccines (77 525 vaccine recipients vs 66 682 placebo recipients; odds ratio [OR], 3.00; 95% CI, 1.10-8.18; I2 = 0%). There was, however, no significant increase in BP after administration of the messenger RNA SARS-CoV-2 vaccine in pooling 8 observational studies (13 518 026 doses vs 13 510 701 unvaccinated; OR, 0.70; 95% CI, 0.42-1.16; I2 = 94%). No significant difference was found in BP among 22 978 880 first-dose recipients of the Pfizer/BioNTech vaccine compared with 22 978 880 first-dose recipients of the Oxford/AstraZeneca vaccine (OR, 0.97; 95% CI, 0.82-1.15; I2 = 0%). Bell palsy was significantly more common after SARS-CoV-2 infection (n = 2 822 072) than after SARS-CoV-2 vaccinations (n = 37 912 410) (relative risk, 3.23; 95% CI, 1.57-6.62; I2 = 95%).Conclusions and RelevanceThis systematic review and meta-analysis suggests a higher incidence of BP among SARS-CoV-2–vaccinated vs placebo groups. The occurrence of BP did not differ significantly between recipients of the Pfizer/BioNTech vs Oxford/AstraZeneca vaccines. SARS-CoV-2 infection posed a significantly greater risk for BP than SARS-CoV-2 vaccination.

Background Despite the recognized implications of high-density lipoprotein cholesterol (HDL-C) in cardiovascular diseases, the role of body mass index (BMI) in HDL-C association with cardiovascular outcomes remains unclear. This study investigated the possible modifying implications of BMI on the correlation between HDL-C and coronary artery bypass grafting (CABG) outcomes. Methods The present cohort included isolated CABG patients (median follow-up: 76.58 [75.79–77.38] months). The participants were classified into three groups: 18.5 ≤ BMI < 25 (normal), 25 ≤ BMI < 30 (overweight), and 30 ≤ BMI < 35 (obese) kg/m2. Cox proportional hazard models (CPHs) and restricted cubic splines (RCSs) were applied to evaluate the relationship between HDL-C and all-cause mortality as well as major adverse cardio-cerebrovascular events (MACCEs) in different BMI categories. Results This study enrolled a total of 15,639 patients. Considering the final Cox analysis among the normal and overweight groups, HDL-C ≥ 60 was a significant protective factor compared to 40 < HDL-C < 60 for all-cause mortality (adjusted hazard ratio (aHR): 0.47, P: 0.027; and aHR: 0.64, P: 0.007, respectively). However, the protective effect of HDL-C ≥ 60 was no longer observed among patients with 30 ≤ BMI < 35 (aHR: 1.16, P = 0.668). RCS trend analyses recapitulated these findings; among 30 ≤ BMI < 35, no uniform inverse linear association was observed; after approximately HDL-C≈55, its increase was no longer associated with reduced mortality risk. RCS analyses on MACCE revealed a plateau effect followed by a modest rise in overweight and obese patients from HDL-C = 40 onward (nonlinear association). Conclusions Very high HDL-C (≥ 60 mg/dL) was not related to better outcomes among obese CABG patients. Furthermore, HDL-C was related to the post-CABG outcomes in a nonlinear manner, and the magnitude of its effects also differed across BMI subgroups.