Exploring the Antiviral, Antioxidant Potentials, and UPLC-MS/MS Characterization of Stenotrophomonas maltophilia GMM Methanolic Extract
Bibliographic record
Abstract
As a secondary metabolite with antioxidant and antiviral properties, microbial methanolic extract has drawn a lot of attention from researchers lately for its potential therapeutic applications. Therefore, in this study, a bacterium was isolated from the air in our lab at NRC Egypt, and this isolate is characterized by the production of faint orange methanolic extract and by using 16sRNA as Stenotrophomonas maltophilia GMM. The culture of our isolate was grown by solid surface fermentation on nutrient agar supplemented with 5% glycerol in order to produce crude methanolic extract. The antioxidant and antiviral activities of the extract was also assessed after it was extracted from the cells using methanol. A precise physicochemical characterization was carried out for the methanolic extract (MEGMM) using UPLC/ESI-qTOF-HRMS/MS technique. It is resulted in the identification of 28 major bioactive metabolites with a high structural diversity. Their structures confirmed as 12 organic bases, 6 aminoacid derivatives, 5carboxylic and long chain fatty acids, 3 phenolic derivatives, one sugar, and a long chain alkyl p-benzoquinone depending on matching of the major parameters, i.e. Rt-values, monoisotopic masses of the molecular and specific fragment ions and their relative abundances with conventional databases and literature. The results showed that the MEGMM has antioxidant activity ranged from 21.3 - 92.8 % using DPPH assay at different concentrations 1.25- 6.25 mg/ml and different time 30 - 120 min, with an IC50 of 2.5 mg/ml at 90 min. The MEGMM exhibited significant antiviral activity, with a 74.92% inhibition of HAV and a weaker activity of 41.89% against HSV-1 at 500 µg/ml. In terms of effective concentration (EC50), MEGMM showed potent activity against HAV (EC50 = 106.52 μg/mL), compared to amantadine as a reference drug (EC50 = 5.67 μg/mL). The results proved that the MEGMM has safety toward normal cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".