Analysis of benzene, toluene, ethylbenzene, xylene(s) biodegradation under anoxic conditions using response surface methodology
Bibliographic record
Abstract
The biodegradation potential and metabolism of bacteria depend on the terminal electron acceptors present at contaminated sites. Due to the quick consumption of oxygen, microorganisms tend to use substitute electron acceptors such as nitrate, sulfate, manganese, and iron for biodegradation. The present study aims to investigate the effect of electron acceptors (nitrate, sulfate, and ferric ions) on BTEX biodegradation using Bacillus infantis (B. infantis) and Microbacterium esteraromaticum (M. esteraromaticum) . The experiment was designed with response surface methodology using the Box-Behnken method. All four compounds of BTEX biodegraded with removal efficiencies ranging from 46% to 57% in Bacillus-treated samples, while 88–98% biodegradation in Microbacterium-treated cultures. The optimal growth of B. infantis was observed at 250 mg/L of nitrate and iron, while no effect of sulfate was observed. For M. esteraromaticum , 250 mg/L of nitrate and sulfate showed the maximum growth of more than 1 optical density (OD), however, no change in growth was noticed with iron treatment. The investigation showed a maximum BTEX biodegradation of 57% by B. infantis under sulfate reduction and overall, 98% by M. esteraromaticum in combined nitrate and sulfate reduction. The present work provides new insights into soil microbial community responses to electron acceptors under anoxic conditions, signifying that intrinsic microorganisms could be successfully stimulated for ISB with electron acceptors as a supplement. • B. infantis and M. esteraromaticum degraded BTEX in anoxic environment. • B. infantis degraded more BTEX during sulfate reduction. • M. esteraromaticum used both nitrate and sulfate for BTEX degradation. • No significant effect of iron-reducing conditions in the presence of other ions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".