BTEX biodegradation and its nitrogen removal potential by a newly isolated <i>Pseudomonas</i> <i>thivervalensis</i> MAH1
Bibliographic record
Abstract
Benzene, toluene, ethylbenzene, and xylene (BTEX) are of great environmental concern because of their widespread occurrence in groundwater and soil, posing an increasing threat to human health. The aerobic denitrifying BTEX-degrading bacterium Pseudomonas thivervalensis MAH1 was isolated from BTEX-contaminated sediment under nitrate-reducing conditions. The degradation rates of benzene, toluene, ethylbenzene, and xylene by strain MAH1 were 4.71, 6.59, 5.64, and 2.59 mg·L⁻¹day⁻¹, respectively. The effects of sodium citrate, nitrate, and NaH2PO4 on improving BTEX biodegradation were investigated, and their optimum concentrations were 0.5 g·L⁻¹, 100 mg·L⁻¹, and 0.8 mmol·L⁻¹, respectively. Moreover, MAH1, which has nirS and nosZ genes, removed ammonium, nitrate, and nitrite at 2.49 mg NH(4)(+)-N·L⁻¹·h⁻¹, 1.50 mg NO(3)(-)-N·L⁻¹·h⁻¹, and 0.83 mg NO(2)(-)-N·L⁻¹·h⁻¹, respectively. MAH1 could help in mitigating the pollution caused by nitrogen amendments for biostimulation. This study highlighted the feasibility of using MAH1 for the bioremediation of BTEX-contaminated sites.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".