Antibacterial and Anticancer Activities of Bioactive Compounds Produced by Bacillus thermoamylovorans
Bibliographic record
Abstract
The antibacterial and anticancer potential of Bacillus thermoamylovorans isolates was evaluated, and demonstrated activity against the tested uropathogenic strains such as Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Klebsiella pneumoniae.The maximum production of bioactive compounds was achieved when B. thermoamylovorans was cultured in tryptic soy broth supplemented with 40% glucose, adjusted to pH 7, and incubated at 50℃ for 96 hours.Further evaluation of minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) for selected bioactive compounds (cis-vaccenic acid, linoleic acid, oleic acid, dibutyl phthalate, diethyl phthalate, and ascorbic acid) demonstrated that cis-vaccenic acid exhibited the strongest activity, with values of MIC from 32 to128 µg/mL, and values of MBC from 64-256 µg/mL, particularly effective against S. aureus and K. pneumoniae.Diethyl phthalate showed moderate bactericidal potential (MBC 256-1024 µg/mL), while other compounds required higher concentrations (512-2048 µg/mL).P. aeruginosa showed strong resistance to most compounds, except for cis-vaccenic acid (MIC 64 µg/mL, MBC 128 µg/mL) and oleic acid (MIC 256 µg/mL).Cytotoxicity assays (MTT) against MCF-7 and HeLa cancer cell lines revealed potent effects of purified cis-vaccenic acid (IC₅₀ = 20 µg/mL for MCF-7, 12.9 µg/mL for HeLa), compared to diethyl phthalate (IC₅₀ = 445 µg/mL for MCF-7, 369 µg/mL for HeLa).These findings highlight the promising antibacterial and cytotoxicity potential of bioactive metabolites derived from B. thermoamylovorans.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".