Use of<i> Mycobacterium austroafricanum</i> IFP 2012 in a MTBE-Degrading Bioreactor
Bibliographic record
Abstract
Mycobacterium austroafricanum IFP 2012 is able to slowly grow on methyl tert-butyl ether (MTBE), a fuel oxygenate widely used as a gasoline additive. The potential of M. austroafricanum IFP 2012 for aerobic MTBE degradation was investigated in the presence of a secondary carbon source, isopropanol. The strain was then tested for MTBE biodegradation at the laboratory-scale in a fixed-bed reactor using perlite as the matrix, and isopropanol was injected once a week to maintain M. austroafricanum IFP 2012 biomass inside the perlite bed. The biofilter was operated for 85 days at an influent flow rate of 20 ml/h by varying the MTBE concentration from 10 to 20 mg/l. The hydraulic retention time was fixed at 5 days. The removal of MTBE depended on the inlet MTBE concentration and a MTBE removal efficiency higher than 99% was obtained for MTBE concentrations up to 15 mg/l. A set of 16S rRNA gene primers specific for M. austroafricanum species was used to analyze the DNA extracted from the biofilter effluent in order to detect the presence of M. austroafricanum IFP 2012 and to estimate the effect of periodic injections of isopropanol on the release of the strain from the perlite bed. The results demonstrated that the injection of isopropanol served to maintain an active MTBE degrading biomass in the biofilter and that this system could be used to effectively treat MTBE contaminated groundwater.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".