5 research outputs found
Viral Outbreaks of SARS-CoV1, SARS-CoV2, MERS-CoV, Influenza H1N1, and Ebola in 21st Century; A Comparative Review of the Pathogenesis and Clinical Characteristics
 Throughout the past twenty years, humankind had its fair share of challenges with viral epidemics. In late December 2019, a zoonotic member of the coronaviruses was responsible for the COVID-19 outbreak of viral pneumonia in Wuhan, China. As a worldwide crisis, meanwhile, conclusive prevention or therapy has yet to be discovered, the death toll of COVID-19 has exceeded 278000 by May 11th, 2020. Alike other members of Coronavirus family such as MERS and SARS-CoV-1, SARS-CoV-2 provokes influenza-like syndrome which might further progress to the severe state of acute respiratory disease in some patients. Comparably, in 2009 the H1N1 influenza outbreak affected countless people by manifestations of respiratory system involvement. Additionally, Ebolavirus, as a member of the Filoviridae family, had also made a global catastrophe by causing hemorrhagic diseases in the past twenty years. The unknown intrinsic nature of SARS-CoV-2, as a great missing piece of this pandemic puzzle, has had physicians to empirically test the possibly efficacious agents of the former viral epidemics on the COVID-19 cases. Here, the current knowledge in SARS-CoV-2 clinical features, transmissibility, and pathogenicity are all summed up as against the other emerging viruses in the last two decades, and the data crucially required for a better management of the illness has been spotlighted
The effects of pomegranate consumption on liver function enzymes in adults: A systematic review and meta-analysis
Background: We performed a systematic review and meta-analysis of all published clinical trial studies to provide a more accurate estimation of pomegranate effects on liver enzymes in different clinical conditions. Methods: A systematic literature search was carried out using electronic databases, including PubMed, Web of Science, and Scopus, up to March 2023 to identify eligible randomized clinical trials (RCTs) evaluating the effect of pomegranate consumption on liver function enzymes. Heterogeneity tests of the selected trials were performed using the I2 statistic. Random effects models were assessed based on the heterogeneity tests, and pooled data were determined as the weighted mean difference with a 95% confidence interval. Results: Out of 3811 records, 9 eligible RCTs were included in the current study. However, there are limitations in the included studies, which can be mentioned in the dose, duration, and type of interventions that are different among the studies, as well as the small number of included studies. All this causes heterogeneity among studies and this heterogeneity limits the consistency of the results. Our meta-analysis showed that pomegranate intake had a significant effect on lowering aspartate aminotransferase (AST) levels in long-term intervention (> 8 weeks), obese (BMIâ„30) individuals, or patients with metabolic disorders. Furthermore, results showed a significant decrease in alanine aminotransferase (ALT) levels in the long-term intervention (> 8 weeks) or in patients with metabolic disorders following the pomegranate intake. Combined results from the randomâeffects model indicated a significant reduction in gamma-glutamyl transferase (GGT) levels (WMD: â5.43 IU/L 95% CI: â7.78 to â3.08; p < 0.001;) following the pomegranate intake. The results of Eggerâs test mentioned a significant publication bias for the trials examining the effect of pomegranate intake on AST (p = 0.007) and ALT (p = 0.036). Conclusion: Our results suggest that long-term pomegranate intake may be effective in ameliorating liver enzymes in adults with obesity and metabolic disorders who are more likely to have elevated baseline liver enzymes due to some degree of liver injury or tissue damage. However, some studies failed to conduct independent biochemical characterization of the product used, including the presence and quantity of polyphenols, antioxidants, and proanthocyanidins
The effects of pomegranate consumption on lipid profile in adults: A systematic review and meta-analysis
Background: Inconsistent evidence exists regarding the impact of pomegranate on lipid profile. Hence, this meta-analysis aimed to identify this effect. Methods: Database search was performed until June 2023 to identify eligible trials. Estimated 95 % confidence (CI) and the weighted mean difference (WMD) was used for triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) through the random-effects model. Results: Analyzing overall effect sizes for TG and TC demonstrated a significant reduction in TG levels (WMD-12.65 mg/dL; 95%CI: â20.13 to â5.17; p = 0.001), whereas indicated no significant alteration in TC levels (WMD: â3.82 mg/dL; 95%CI: â7.66 to 0.02; p = 0.052). Pomegranate intake had a significant diminishing effect on LDL-C levels (WMD: â3.07 mg/dl; 95%CI: â5.70 to â0.44; p = 0.022), and a significant increasing influence on HDL-C levels (WMD: 2.53 mg/dl; 95%CI: 1.08 to 3.62; p < 0.001). Conclusion: Pomegranate consumption has a beneficial effect in improving TG, LDL-C, and HDL-C levels. Prospero registration code: CRD42023403365
Additional file 1 of Effects of supplementation with milk protein on glycemic parameters: a GRADE-assessed systematic review and doseâresponse meta-analysis
Additional file 1: Supplemental Table 1. Risk of bias assessment for included RCTs in the meta-analysis. Supplemental Table 2. GRADE assessment. Supplemental Fig. 1. Flow diagram of study selection. Supplemental Fig. 2. Funnel plots for the effect of supplementation with milk protein on (A) fasting blood glucose (FBG) (B) fasting insulin (C) hemoglobin A1c(HbA1c), and (D) homeostasis model assessment of insulin resistance (HOMA-IR). Supplemental Fig. 3. Non-linear dose-response association between dose (gr/day) of supplementation with milk protein and absolute mean differences in (A) fasting blood glucose (FBG) (B) fasting insulin (C) hemoglobin A1c(HbA1c), and (D) homeostasis model assessment of insulin resistance (HOMA-IR). The 95% CI (confidence interval) is demonstrated in the shaded parts. Supplemental Fig. 4. Non-linear association between duration of the supplementation with milk protein (weeks) and absolute mean differences in (A) fasting blood glucose (FBG) (B) fasting insulin (C) hemoglobin A1c(HbA1c), and (D) homeostasis model assessment of insulin resistance (HOMA-IR). The 95% CI (confidence interval) is depicted in the shaded parts. Supplemental Fig. 5. Linear dose-response association between dose (gr/day) of supplementation with milk protein and absolute mean differences in (A) fasting blood glucose (FBG) (B) fasting insulin (C) hemoglobin A1c(HbA1c), and (D) homeostasis model assessment of insulin resistance (HOMA-IR). Supplemental Fig. 6. Linear association between duration of the supplementation with milk protein (weeks) and absolute mean differences in (A) fasting blood glucose (FBG) (B) fasting insulin (C) hemoglobin A1c (HbA1c), and (D) homeostasis model assessment of insulin resistance (HOMA-IR)
Additional file 1 of The effects of conjugated linoleic acid supplementation on glycemic control, adipokines, cytokines, malondialdehyde and liver function enzymes in patients at risk of cardiovascular disease: a GRADE-assessed systematic review and doseâresponse meta-analysis
Additional file 1