Comparative Analysis of Rhamnolipids from Novel Environmental Isolates of <i>Pseudomonas aeruginosa</i>
Bibliographic record
Abstract
Abstract A comparative analysis of rhamnolipids from environmental isolates of Pseudomonas aeruginosa was undertaken to evaluate strain‐specific rhamnolipid fingerprints obtained under different growth conditions. Environmental isolates of P. aeruginosa produced rhamnolipids on different types of substrates, including cheap and renewable sources like sunflower oil from deep fryers and sunflower oil mill effluent. Rhamnolipids were monitored by high‐performance liquid chromatography–electrospray ionization interface mass spectrometry, which allowed fast and reliable identification and quantification of the congeners present. The highest concentration of total rhamnolipids of 3.33 g/l was obtained by the strain P. aeruginosa 67, recovered from petroleum contaminated soil, and strains D1 (1.73 g/l) and D2 (1.70 g/l), recovered from natural microbial consortia originated from mazut‐contaminated soil, grown on sunflower oil as a carbon source. Di‐ to mono‐rhamnolipids ratios were in the range of 0.90–5.39 for different media composition and from 1.12 to 4.17 for different producing strains. Rhamnolipid profiles of purified mixtures of all tested strains are similar with chain length from C8–C12, pronounced abundance of Rha–C10–C10 and Rha–Rha–C10–C10 congeners, and a low content of 3‐(3‐hydroxyalkanoyloxy)‐alkanoic acids. Concentrations of major congeners of RLs were found to slightly vary, depending on strain and growth conditions, while variations in minor congeners were more pronounced. Statistically significant increase of critical micelle concentration values was observed with lowering the ratio of total mono‐ to di‐rhamnolipids ratio indicating that mono‐rhamnolipids start to form micelles at lower concentration than di‐rhamnolipids.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".