Palmitoyl‐<scp>dl</scp>‐Carnitine is a Multitarget Inhibitor of <i>Pseudomonas aeruginosa</i> Biofilm Development
Bibliographic record
Abstract
Bacteria growing in biofilms are often in metabolic and physiological states that do not respond well to antibiotics, and thus, are major contributors to chronic diseases. Biofilm inhibitors, therefore, have the potential to be used alone or as adjuvants to conventional antibiotic therapies. Here, we screened a chemically diverse collection of protein kinase inhibitors for molecules that perturb biofilm development. Among the inhibitory molecules identified, palmitoyl-DL-carnitine (pDLC) impaired Pseudomonas aeruginosa and Escherichia coli biofilm formation in a dose-dependent manner. The pDLC affected multiple pathways implicated in P. aeruginosa biofilm development; it stimulated motility, inhibited activity of the Las quorum sensing system, and overrode the biofilm-promoting effects of subminimal inhibitory concentrations of aminoglycosides and high levels of the second messenger, cyclic-di-GMP. Palmitic acid, but not carnitine, inhibited biofilm formation but did not stimulate motility, suggesting that pDLC works through unique mechanisms. The ability to target multiple pathways involved in biofilm formation is desirable in an inhibitor, which makes pDLC an interesting lead for antibiofilm therapies.
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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 | 0.000 | 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) | 0.001 | 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".