Nothybus sumatranus
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ABSTRACT:
PROVIDER: PRJNA791091 | ENA |
REPOSITORIES: ENA
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Project description:Sumatranus lignans (SL) isolated from Cleistanthus sumatranus have demonstrated bioactivities, e.g., they were shown to exhibit immunosuppressive properties in previous research. Their structure suggests potential antioxidant activity that has not attracted any attention thus far. Consistently, a comprehensive analysis of the antioxidant activity of these compounds is highly desirable with the view of prospective medical applications. In this work, the mechanism and kinetics of the antiradical properties of SL against hydroperoxyl radicals were studied by using calculations based on density functional theory (DFT). In the lipid medium, it was discovered that SL reacted with HOO• through the formal hydrogen transfer mechanism with a rate constant of 101-105 M-1 s-1, whereas in aqueous media, the activity primarily occurred through the sequential proton loss electron transfer mechanism with rate constants of 102-108 M-1 s-1. In both lipidic and aqueous environments, the antiradical activity of compounds 6 and 7 exceeds that of resveratrol, ascorbic acid, and Trolox. These substances are therefore predicted to be good radical scavengers in physiological environments.
| S-EPMC10586290 | biostudies-literature
Project description:One way to treat diabetes mellitus type II is by using α-glucosidase inhibitor, that will slow down the postprandial glucose intake. Metabolomics analysis of Artabotrys sumatranus leaf extract was used in this research to predict the active compounds as α-glucosidase inhibitors from this extract. Both multivariate statistical analysis and machine learning approaches were used to improve the confidence of the predictions. After performance comparisons with other machine learning methods, random forest was chosen to make predictive model for the activity of the extract samples. Feature importance analysis (using random feature permutation and Shapley score calculation) was used to identify the predicted active compound as the important features that influenced the activity prediction of the extract samples. The combined analysis of multivariate statistical analysis and machine learning predicted 9 active compounds, where 6 of them were identified as mangiferin, neomangiferin, norisocorydine, apigenin-7-O-galactopyranoside, lirioferine, and 15,16-dihydrotanshinone I. The activities of norisocorydine, apigenin-7-O-galactopyranoside, and lirioferine as α-glucosidase inhibitors have not yet reported before. Molecular docking simulation, both to 3A4A (α-glucosidase enzyme from Saccharomyces cerevisiae, usually used in bioassay test) and 3TOP (a part of α-glucosidase enzyme in human gut) showed strong to very strong binding of the identified predicted active compounds to both receptors, with exception of neomangiferin which only showed strong binding to 3TOP receptor. Isolation based on bioassay guided fractionation further verified the metabolomics prediction by succeeding to isolate mangiferin from the extract, which showed strong α-glucosidase activity when subjected to bioassay test. The correlation analysis also showed a possibility of 3 groups in the predicted active compounds, which might be related to the biosynthesis pathway (need further research for verification). Another result from correlation analysis was that in general the α-glucosidase inhibition activity in the extract had strong correlation to antioxidant activity, which was also reflected in the predicted active compounds. Only one predicted compound had very low positive correlation to antioxidant activity.
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Project description:The wild raspberry species Rubus sumatranus Miq 1861 is a promising resource for breeding thermotolerant cultivars. Its complete chloroplast genome spans 155,935 base pairs (bp), featuring the classic quadripartite structure: an 18,729 bp small single-copy region, an 85,662 bp large single-copy region, and two 25,772 bp inverted repeats. A total of 130 genes were identified, including 86 protein-coding, 36 tRNA genes, and 8 rRNA genes. A maximum likelihood phylogenetic tree based on chloroplast genomes shows that R. sumatranus, within the subgenus Idaeobatus, is sister to the subgenus Batothamnus. This confirms the polyphyletic nature of the subgenus Idaeobatus. The chloroplast genome assembly of R. sumatranus enhances our understanding of its evolutionary history.
| S-EPMC11626868 | biostudies-literature
Project description:Elephants were once widely distributed across the Indonesian island of Sumatra but now exist in small, isolated populations. Using the best data available on elephant occurrence, we aimed to (a) predict potential habitat suitability for elephants (Elephas maximus sumatranus) across the island of Sumatra and (b) model landscape connectivity among the extant elephant populations. We used direct sightings and indirect observations of elephant signs, as well as six remotely sensed proxies of surface ruggedness, vegetation productivity and structure, and human land use and disturbance, to model habitat suitability in a Google Earth Engine (GEE) environment. We validated the habitat suitability prediction using 10-fold spatial block cross validation and by calculating the area under the precision-recall curve (AUC-PR), sensitivity, and specificity for each model iteration. We also used a geolocation dataset collected from global positioning system (GPS) collars fitted on elephants as an independent validation dataset. Models showed good predictive performance with a mean AUC-PR of 0.73, sensitivity of 0.76, and specificity of 0.68. Greater than 83% of the independent GPS collar geolocations were located in predicted suitable habitat. We found human modification, surface ruggedness, and normalized difference vegetation index to be the most important variables for predicting suitable elephant habitat. Thirty-two percent, or 135,646 km2, of Sumatra's land area was predicted to be suitable habitat, with 43 patches of suitable habitat located across Sumatra. Areas with high connectivity were concentrated in the Riau and North Sumatra provinces. Though our analysis highlights the need to improve the quality of data collected on Sumatran elephants, more suitable habitat remains on Sumatra than is used by known populations. Targeted habitat conservation, especially of the suitable habitat in and around the Lamno, Balai Raja, Tesso Tenggara, Tesso Utara, Bukit Tigapuluh, Seblat, Padang Sugihan, and Bukit Barisan Selatan ranges, may improve the long-term viability of this critically endangered species.
| S-EPMC10539044 | biostudies-literature