METHODS: Scopus, PubMed, and Wiley Online Libraries were searched up to the date November 24, 2019. Two reviewers were requested to independently extract study characteristics and to assess the bias and applicability risks with reference to the study inclusion criteria. Meta-analyses were performed to specify the relationship between dietary intake and the risk of ovarian cancer identifying 97 cohort studies.
RESULTS: No significant association was found between dietary intake and risk of ovarian cancer. The results of subgroup analyses indicated that green leafy vegetables (RR = 0.91, 95%, 0.85-0.98), allium vegetables (RR = 0.79, 95% CI 0.64-0.96), fiber (RR = 0.89, 95% CI 0.81-0.98), flavonoids (RR = 0.83, 95% CI 0.78-0.89) and green tea (RR = 0.61, 95% CI 0.49-0.76) intake could significantly reduce ovarian cancer risk. Total fat (RR = 1.10, 95% CI 1.02-1.18), saturated fat (RR = 1.11, 95% CI 1.01-1.22), saturated fatty acid (RR = 1.19, 95% CI 1.04-1.36), cholesterol (RR = 1.13, 95% CI 1.04-1.22) and retinol (RR = 1.14, 95% CI 1.00-1.30) intake could significantly increase ovarian cancer risk. In addition, acrylamide, nitrate, water disinfectants and polychlorinated biphenyls were significantly associated with an increased risk of ovarian cancer.
CONCLUSION: These results could support recommendations to green leafy vegetables, allium vegetables, fiber, flavonoids and green tea intake for ovarian cancer prevention.
METHODS: In this study, anti-diabetic effect of ML extract is investigated in vivo to evaluate the biochemical changes, potential serum biomarkers and alterations in metabolic pathways pertaining to the treatment of HFD/STZ induced diabetic rats with ML extract using 1H NMR based metabolomics approach. Type 2 diabetic rats were treated with different doses (200 and 400 mg/kg BW) of Melicope lunu-ankenda leaf extract for 8 weeks, and serum samples were examined for clinical biochemistry. The metabolomics study of serum was also carried out using 1H NMR spectroscopy in combination with multivariate data analysis to explore differentiating serum metabolites and altered metabolic pathways.
RESULTS: The ML leaf extract (400 mg/kg BW) treatment significantly increased insulin level and insulin sensitivity of obese diabetic rats, with concomitant decrease in glucose level and insulin resistance. Significant reduction in total triglyceride, cholesterol and low density lipoprotein was also observed after treatment. Interestingly, there was a significant increase in high density lipoprotein of the treated rats. A decrease in renal injury markers and activities of liver enzymes was also observed. Moreover, metabolomics studies clearly demonstrated that, ML extract significantly ameliorated the disturbance in glucose metabolism, tricarboxylic acid cycle, lipid metabolism, and amino acid metabolism.
CONCLUSION: ML leaf extract exhibits potent antidiabetic properties, hence could be a useful and affordable alternative option for the management of T2DM.