Bacterial Membranes as Predictors of Antimicrobial Potency
Bibliographic record
Abstract
A wide range of chemical structures having antimicrobial activity have been studied in an effort to treat the increasing emergence of bacteria that are resistant to traditional antibiotics. These agents have varying degrees of toxicity against different bacterial species. We demonstrate, using members of a novel class of antimicrobial agents, the oligomers of acyllysine, that one cause for the difference in species selectivity is the ability to induce the clustering of anionic lipids, resulting in their segregation into domains. This phenomenon occurs only in bacterial membranes composed of both anionic and zwitterionic lipids and not with bacteria whose membrane lipids are largely anionic. As a consequence it can be predicted which bacterial species will be most affected by antimicrobial agents that function principally by this mechanism. This finding allows for the design of new antibiotics with selective toxicity against different groups of bacteria.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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".