Using anti-biofilm peptides to treat antibiotic-resistant bacterial infections
Bibliographic record
Abstract
Host defense (antimicrobial) peptides (HDPs) are produced by virtually all organisms and have an important role in protection against microbial infections. Some naturally occurring peptides such as the human cathelicidin LL-37 and the bovine peptide indolicidin have been shown to inhibit bacterial biofilm development. Rearrangement and substantial modification of the amino acid sequence of these and other HDPs has led to the identification of small synthetic peptides with increased, broad-spectrum anti-biofilm activity that is independent of activity vs. planktonic cells. Some of these peptides have also been shown to act in synergy with antibiotics commonly used in the clinic to prevent biofilm formation and eradicate pre-existing biofilms. Recently, the mechanism of action of one of these peptides (i.e., 1018) was shown to involve binding to and causing degradation of the second messenger stress response nucleotide ppGpp, which plays an important role in biofilm formation and maintenance. Here, we review recent progress in the field of anti-biofilm peptides and propose future directions to further develop these therapeutic agents.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".