PCB BIODEGRADATION IN AGED CONTAMINATED SOIL: INTERACTIONS BETWEEN EXOGENOUS<i>PHANEROCHAETE CHRYSOSPORIUM</i>AND INDIGENOUS MICROORGANISMS
Bibliographic record
Abstract
This work investigated whether the interaction between the white-rot fungus Phanerochaete chrysosporium and indigenous microorganisms could enhance polychlorinated biphenyl (PCB) removal from historically contaminated soil in aerobic microcosms. The PCB mixture was composed mainly of 14% tri-, 20% tetra-, 9% penta-, 17% hexa-, 26% hepta-, 11% octa-, and 3% nona-chlorobiphenyl (CB) congeners, determined by GC/MS. The fungus, which was grown on sugarcane bagasse and added via this solid substrate, successfully colonized the contaminated soil. The added fungi and the indigenous soil community biodegraded most PCB congeners, with removing efficiencies ranging from 13% to 100% for the 45-day incubation period. The interaction between the fungus and the microorganisms present in the added bagasse inhibited both heterotrophic activity (measured by CO2 evolution) and PCB degradation, suggesting a possible antagonism. In contrast, analysis of variance (ANOVA) inferred a synergistic effect between fungus and soil microorganisms, which resulted in a heterotrophic activity above 2.5 mg-CO2/g-initial dry matter/day. The statistical analyses also showed that the presence of fungus alone was particularly beneficial for the removal of penta- and hepta-CB.
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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 | 0.000 |
| 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".