Molecular Modifications of the Pseudomonas Quinolone Signal in the Intermicrobial Competition with Aspergillus
Bibliographic record
Abstract
The Pseudomonas quinolone signal (PQS) is an important quorum-sensing molecule for Pseudomonas aeruginosa that regulates virulence factors, chelates iron, and is an important factor in interactions with eukaryotes, including fungi and mammalian hosts. It was previously shown to inhibit or boost Aspergillus, depending on the milieu iron concentration. We studied several molecular modifications of the PQS molecule, and their effects on Aspergillus biofilm metabolism and growth in vitro, and the effects of iron supplementation. We found that most molecules inhibited Aspergillus at concentrations similar to that of PQS, but with relatively flat dose-responses, and all were less potent than PQS. The inhibition was reversible by iron, suggesting interference with fungal iron metabolism. Stimulation of Aspergillus was not noted. We conclude that the critical Aspergillus-inhibiting moeities of the PQS molecule were partially, but not completely, interfered with by molecular modifications at several sites on the PQS molecule. The mechanism, as with PQS, appears to relate to fungal iron metabolism.
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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) | 0.002 | 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".