ISOLATION AND CHARACTERIZATION OF BACTERIOCIN‐PRODUCING MICROORGANISMS FROM <i>AGOS‐OS</i>
Bibliographic record
Abstract
ABSTRACT Agos‐os, a fermented meat and sweetpotato mixture, was produced and analyzed for its microbial characteristics. pH decreased during fermentation. Mold and anaerobic bacterial counts increased while yeasts and aerobic bacterial counts decreased during the third and seventh day of fermentation. Six isolates with the widest zones of inhibition on the indicator lawn were selected for bacteriocin production. These isolates had exactly the same morphological, physiological and biochemical characteristics. The ribosomal RNA sequence was 99.5% identical with Enterococcus faecalis VRE 1492. The identification was confirmed through DNA homology test by the EMBL Genbank, Canada. This bacterium produced the L‐isomer lactic acid. The amount of bacteriocin produced by the bacterium was optimized by growing the bacterium at different growth media, initial pH and fermentation time. Maximum production of bacteriocin was achieved in MRS (De Man Rugosa and Sharpe) medium (with glucose) at pH 7.50. The crude bacteriocin inhibited the growth of gram‐positive bacteria such as Lactobacillus sake 15521 and Listeria innocua. The gram‐negative bacteria such as Escherichia coli DH 5‐alpha (with plasmid, PUC), Salmonella typhii and Staphylococcus aureus were weakly inhibited. Other microorganisms such as Lactobacillus curvatus D31685, Lactobacillus confusius M23036, Lactococcus lactis MG1363, Leuconostoc paramesenteroides S67831, Pediococcus pentosaceus M58834, Saccharomyces cerevisiae SS553 (wild type) and Escherichia coli JM109 (no plasmid) were not inhibited.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".