Increased susceptibility to azithromycin of <i>Pseudomonas aeruginosa</i> biofilms using RPMI 1640 testing media
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Azithromycin (AZM) is efficient for treatment of chronic Pseudomonas aeruginosa biofilm lung infections, despite of resistance in conventional susceptibility testing. It has been shown that planktonic P. aeruginosa are more susceptible to AZM when tested in RPMI 1640 medium. The aim of the study was to test the susceptibility to AZM of P. aeruginosa biofilms in LB vs RPMI 1640 media. We investigated the effect of AZM on planktonic and biofilms of (WT) P. aeruginosa (PAO1), the hypermutable (Δ mutS ) and the antibiotic‐resistant phenotype(Δ nfxB ) mutants. The effect of AZM on young and mature biofilms was investigated in the modified Calgary Biofilm Device by estimation of the minimal biofilm inhibitory concentration (MBIC). The AZM MBIC 90 in LB/RPMI1640 on young biofilms treated for 24 h was 16/4 μg/mL for PAO1, 32/8 μg/mL for Δ mutS, and 256/16 μg/mL for Δ nfxB, while in mature biofilms was 256/2 μg/mL for PAO1 and Δ mutS and 16/1 μg/mL for Δ nfxB. The effect of AZM was improved when the treatment was prolonged to 72 h, supporting the intracellular accumulation of AZM. An increased susceptibility of P. aeruginosa biofilms to AZM was observed in RPMI 1640 than in LB medium. Our results might improve susceptibility testing and dosing of AZM for treatment of biofilm infections.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.000 | 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 it