Broad Spectrum Anti-Quorum Sensing Activity of Tannin-Rich Crude Extracts of Indian Medicinal Plants
Bibliographic record
Abstract
Quorum sensing (QS) mechanisms have been demonstrated to have significance in expression of pathogenicity in infectious bacteria. In Gram negative bacteria the autoinducer molecules that mediate QS are acyl homoserine lactones (AHL) and in Gram positive bacteria they are peptides called autoinducing peptides (AIP). A screening of tannin-rich medicinal plants was attempted to identify extracts that could interrupt the QS mechanisms in both Gram positive and Gram negative bacteria over a wide range of concentrations and therefore potentially be potent agents that could act as broad spectrum QS inhibitors. Six out of the twelve Indian medicinal plant extracts that were analyzed exhibited anti-QS activity in Chromobacterium violaceum 12472 and in S. aureus strain with agr:blaZ fusion over a broad range of subinhibitory concentrations, indicating that the extracts contain high concentration of molecules that can interfere with the QS mechanisms mediated by AHL as well as AIP.
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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 | 0.001 | 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) | 0.001 | 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".