Hydrophobicity development, alkane oxidation, and crude-oil emulsification in a <i>Rhodococcus</i> species
Bibliographic record
Abstract
The relationship between the phenomena alkane oxidation, extreme hydrophobicity of the cell surface, and crude-oil emulsification in Rhodococcus sp. strain 094 was investigated. Compounds that induce the emulsifying ability simultaneously induced the cytochrome P450-containing alkane oxidizing system and the transition from low to high cell-surface hydrophobicity. Exposed to inducers of crude-oil emulsification, the cells developed a strong hydrophobic character during exponential growth, which was rapidly lost when entering stationary phase. The loss in hydrophobicity coincided in time with the crude-oil emulsification, indicating that the components responsible for the formation of cell-surface hydrophobicity act as excellent emulsion stabilisers only after release from the cells. Rhodococcus sp. strain 094 possessed three distinct levels of cell-surface hydrophobicity. One level of low hydrophobicity was characteristic of cells in late stationary phase and was independent of growth substrate. A second and more hydrophobic level was observed for cells in exponential phase grown on water-soluble substrates, while a third level, characterised by extreme cell hydrophobicity, was observed for cells in exponential phase cultivated on hydrophobic substrates such as hexadecane. The production of the oil-emulsifying agents seems to require external sources of nitrogen and phosphate.
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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) | 0.000 | 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".