Exploring the antioxidant and enzyme inhibitory potential of the Streptomycesgobitricini strain: a promising biotechnological resource
Bibliographic record
Abstract
Streptomyces strains are renowned for their ability to produce a wide array of secondary metabolites, which play crucial roles in ecological interactions and have significant pharmaceutical applications. The optimization of culture conditions is a key factor in maximizing the production of these bioactive compounds. This study investigated the growth patterns and bioactivity of a newly isolated Streptomyces gobitricini cultured on different media: R5, R5E, R2YE, and YEME. Data showed that R5 and R2YE media supported higher biomass accumulation, achieving peak dry weights of 225 mg/L and 175 mg/L, respectively, after 96 h-incubation, compared to R5E (52 mg/L) and YEME (48 mg/L). Growth phases, especially the exponential phases, were longer and more pronounced in nutrient-rich media like R5 and R2YE. Furthermore, the inherent antioxidant activities, enzyme inhibitory properties against α-amylase, α-glucosidase, lipase, and trypsin, as well as secreted phospholipase A2, cyclooxygenases and lipooxygenase, showed significant variations influenced by the growth media, with R5 exhibiting the highest overall bioactivity. Specifically, R2YE extracts demonstrated potent inhibitory effects on α-glucosidase and phospholipases, while YEME showed promising lipase inhibition. These findings emphasized the critical role of media composition in promoting secondary metabolite production in S. gobitricini, ultimately enhancing its potential medicinal applications for several human diseases such as obesity and inflammation. Consequently, optimizing bacterial culture conditions could significantly improve yield and efficiency of bioactive compounds.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".