Chlorpyrifos Degradation by Crude Enzyme Extracts Obtained from<i>Alcanivorax borkumensis</i>
Bibliographic record
Abstract
Chlorpyrifos (CPF) is one of the most widely used organophosphate insecticides worldwide. In mammals, CPF exposure can affect the peripheral and central nervous systems, which can eventually even lead to death. In the present study, crude enzyme extracts obtained from Alcanivorax borkumensis were used for the degradation of CPF. Various experimental parameters that may affect the enzyme catalysis, such as pH, temperature, substrate (CPF), and enzyme concentrations, were studied along with the kinetics of enzymatic degradation. The major contributor toward the degradation of CPF could possibly be alkane hydroxylases and lipases, which might have contributed to the simultaneous degradation of alkane hydroxylase transformation products. A maximum of 95% degradation in 6 h was observed at 50 ppm of CPF. Michaelis–Menten kinetics was applied to study the enzymatic degradation. From the Lineweaver-Burk plot, the V max was calculated to be 1.06 mg L -1 h -1 and the K m was calculated to be 20.52 mg. A pH of 2 and temperature of 40 °C were found to be optimal for the effective CPF degradation. Moreover, increased enzyme activities (concentrations) had minimal effect on CPF degradation. An ~800% increase in enzyme activity resulted in only an ~20% increase in degradation of CPF. The current study provides insight into organophosphate pesticides biodegradation; further studies are required for the environmental applications of these enzymes in CPF-contaminated soils and water resources.
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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 | 0.000 |
| 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".