Effect of carbon starvation on p-nitrophenol degradation by a Moraxella strain in buffer and river water
Bibliographic record
Abstract
This study examines the effect of carbon starvation on the ability of a Moraxella sp. strain to degrade p-nitrophenol (PNP). Carbon starvation for 24 h decreased the induction time for p-nitrophenol degradation by the bacterium in a minimal salt medium from 6 to 1 h but it did not completely eliminate the induction time. Moraxella cells with 2-day carbon starvation had an induction time of 3 h and the induction time of the 3-day starved cells was 6 h. A 100% increase in density of the non-starved cells did not affect the induction time for p-nitrophenol degradation by the bacterium, indicating that the initial increase in cell density of the carbon-starved culture did not cause the faster onset of p-nitrophenol degradation. However, the initial uptake of p-nitrophenol of the 1-day carbon-starved Moraxella cells was 3-fold higher than the non-starved cells. A green fluorescent protein gene (gfp)-labelled Moraxella (M6 strain) was constructed to examine the survival of and p-nitrophenol degradation by the bacterium in non-sterile river water samples. Similar p-nitrophenol degradation behaviour was observed in the river water samples inoculated with the M6 cells. The time needed for complete degradation of p-nitrophenol by the non-starved M6 was 19-27 and 33 h in samples spiked with 80, 200 and 360 microM p-nitrophenol, respectively. However, the 1-day carbon-starved inocula required about 16 h to degrade the p-nitrophenol completely regardless of its concentration in the water samples. Survival of the carbon-starved and non-starved M6 was not significantly different from each other in the river water regardless of the p-nitrophenol concentration. In the absence of p-nitrophenol, the inoculum density decreased continuously. At 200 and 360 microM p-nitrophenol, the cell densities of M6 increased in the first two days of incubation and declined steadily afterward.
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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) | 0.001 | 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".