The antioxidant activities of flavonoids in Jerusalem artichoke (Helianthus tuberosus L.) leaves and their quantitative analysis

Jerusalem artichoke diversity in Türkiye: comparative analysis of clone and organ-based biochemical composition

In this study, biochemical analyses were performed for the first time on 22 different Jerusalem artichokes clones collected from different regions of Türkiye and samples from three different organs of each clone, considering the interaction effects. As a result of the study, the interaction effect of clones and sampled organs was found significant for total flavonoids, ascorbic acid, total chlorophyll, pH, H2O2 removal capacity, total dry matter, water soluble dry matter and antioxidant capacity via FRAP. According to the correlation analysis, the highest coefficient among the parameters in the tuber was between titratable acidity and total phenolic matter (0,576). Principal component analysis was used to assess the degree to which the parameters explained the variation in the gene pool. Factors directly and indirectly affecting the amount of water-soluble dry matter in the tuber were examined by path analysis.

Traditional Knowledge to Contemporary Medication in the Treatment of Infectious Disease Dengue: A Review

Dengue has become a worldwide affliction despite incessant efforts to search for a cure for this long-lived disease. Optimistic consequences for dengue vaccine are implausible as the efficiency is tied to previous dengue virus (DENV) exposure and a very high cost is required for large-scale production of vaccine. Medicinal plants are idyllic substitutes to fight DENV infection since they constitute important components of traditional medicine and show antiviral properties, although the mechanism behind the action of bioactive compounds to obstruct viral replication is less explored and yet to be discovered. This review includes the existing traditional knowledge on how DENV infects and multiplies in the host cells, conscripting different medicinal plants that obtained bioactive compounds with anti-dengue properties, and the probable mechanism on how bioactive compounds modulate the host immune system during DENV infection. Moreover, different plant species having such bioactive compounds reported for anti-DENV efficiency should be validated scientifically via different in vitro and in vivo studies.

Support vector regression-based QSAR models for prediction of antioxidant activity of phenolic compounds

The Support vector regression (SVR) was used to investigate quantitative structure-activity relationships (QSAR) of 75 phenolic compounds with Trolox-equivalent antioxidant capacity (TEAC). Geometric structures were optimized at the EF level of the MOPAC software program. Using Pearson correlation coefficient analysis, four molecular descriptors [n(OH), Cosmo Area (CA), Core-Core Repulsion (CCR) and Final Heat of Formation (FHF)] were selected as independent variables. The QSAR model was developed from the training set consisting of 57 compounds and then used the leave-one-out cross-validation (LOOCV) correlation coefficient to evaluate the prediction ability of the QSAR model. Used Artificial neural network (ANN) and multiple linear regression (MLR) for comparing. The RMSE (root mean square error) values of LOOCV in SVR, ANN and MLR models were 0.44, 0.46 and 0.54. The RMSE values of prediction of external 18 compounds were 0.41, 0.39 and 0.54 for SVR, ANN and MLR models, respectively. The obtained result indicated that the SVR models exhibited excellent predicting performance and competent for predicting the TEAC of phenolic compounds.