INHIBITORY ACTIVITY OF ALLYL ALCOHOL DERIVED FROM ALLIIN IN GARLIC AGAINST FOOD BORNE PATHOGEN CANDIDA ALBICAN
Bibliographic record
Abstract
The objectives of the present study were to evaluate the antimicrobial activity of allyl alcohol produced by the thermal decomposition of garlic against food borne pathogen Albicans, and to find out the minimum inhibitory concentration of allyl alcohol in heated garlic. The initial concentration of the organism Candida was estimated by direct microscopic count (DMC) method. Minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) tests were performed to observe the antimicrobial activity of allyl alcohol-a product of garlic, against Albicans at different pH levels and heating times such as: pH 4 and heating time 90 min, pH 4 and heating time 30 minutes, pH 8 and heating time 90 minutes, and pH 8 and heating time 30 minutes respectively in the YMPG broth and PDA agar, by incubating at 350C for 24 hours. Similarly HPLC method was used to determine the amount of extracted product of garlic - allyl alcohol at different pH levels. It has been observed that allyl alcohol showed comparatively more anti yeast activity at pH 4, with heating time 90 minutes, which is 1.56% at dilution 1/64. Similarly generation of allyl alcohol from heated garlic extract by HPLC test was found maximum at pH 4, and time 90 minutes that is 8.05 % as compared to other three combined variables of pH, and time. The findings of present study clearly met with the hypothesis that allyl alcohol in heated garlic had anti yeast activity, it was able to inhibit the growth of pathogen such as Albicans, by extending heating time at low pH level.
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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 | 0.000 |
| 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 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".