Methods: Mice (n = 48) were fed high-fat diet (HFD) for 25 weeks to induce obesity, after which half were maintained on HFD and half switched to low-fat diet (LFD)while they were given normal water (H2O) or 0.1% (w/v) SCE in water at week 0-4 which was increased to 1% (w/v) at week 5-9. Effects of treatment with SCE were compared between HFDH2O, HFDSCE, LFDH2O and LFDSCE groups. Respiratory exchange ratios (RER) were measured at weeks 0, 5 and 10. Food, water intake and body weight were measured weekly. Plasma lipid profile and organ weights were determined at week 10.
Results: SCE had significantly reduced RER at week 9 (P = 0.011). Food intake, body weight, and abdominal adipose tissue weight were not altered by SCE at weeks 5 and 10. However, significant increase in plasma and liver cholesterol (P < 0.050) was observed.
Conclusion: Our findings suggest that SCE induced lipolysis and body fat oxidation and increased energy expenditure. Further studies in other animal models should be done to confirm the consistency of these results.
OBJECTIVES & METHODOLOGY: This systematic narrative review examines articles published from 1990 to 2017, generated from Ovid, MEDLINE, CINAHL, and PubMed. The search was also supplemented by an examination of reference lists for related articles via Scopus. We included 105 articles.
FINDINGS: We found that the type of unmet needs in stroke survivors and the contributing factors were substantially different from their caregivers. The unmet needs in stroke survivors ranged from health-related needs to re-integration into the community; while the unmet needs in stroke caregivers ranged from information needs to support in caring for the stroke survivors and caring for themselves. Additionally, the unmet needs in both groups were associated with different factors.
CONCLUSION: More research is required to understand the unmet needs of stroke survivors and stroke caregivers to improve the overall post-stroke care services.
RESULTS: Comparison of the PLS and RF showed that RF exhibited poorer generalization and hence poorer predictive performance. Both the regression coefficient of PLS and the variable importance of RF revealed that quercetin and kaempferol derivatives, caffeic acid and vitexin-2-O-rhamnoside were significant towards the tested bioactivities. Furthermore, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) results showed that sonication and absolute ethanol are the preferable extraction method and ethanol ratio, respectively, to produce N. oleracea extracts with high phenolic levels and therefore high DPPH scavenging and α-glucosidase inhibitory activities.
CONCLUSION: Both PLS and RF are useful regression models in metabolomics studies. This work provides insight into the performance of different multivariate data analysis tools and the effects of different extraction conditions on the extraction of desired phenolics from plants. © 2017 Society of Chemical Industry.