<i>Desulfitobacterium hafniense</i> Is Present in a High Proportion within the Biofilms of a High-Performance Pentachlorophenol-Degrading, Methanogenic Fixed-Film Reactor
Bibliographic record
Abstract
We developed a pentachlorophenol (PCP)-degrading, methanogenic fixed-film reactor by using broken granular sludge from an upflow anaerobic sludge blanket reactor. This methanogenic consortium was acclimated with increasing concentrations of PCP. After 225 days of acclimation, the reactor was performing at a high level, with a PCP removal rate of 1,173 muM day(-1), a PCP removal efficiency of up to 99%, a degradation efficiency of approximately 60%, and 3-chlorophenol as the main chlorophenol residual intermediate. Analyses by PCR-denaturing gradient gel electrophoresis (DGGE) showed that Bacteria and Archaea in the reactor stabilized in the biofilms after 56 days of operation. Important modifications in the profiles of Bacteria between the original granular sludge and the reactor occurred, as less than one-third of the sludge DGGE bands were still present in the reactor. Fluorescence in situ hybridization experiments with probes for Archaea or Bacteria revealed that the biofilms were composed mostly of Bacteria, which accounted for 70% of the cells. With PCR species-specific primers, the presence of the halorespiring bacterium Desulfitobacterium hafniense in the biofilm was detected very early during the reactor acclimation period. D. hafniense cells were scattered in the biofilm and accounted for 19% of the community. These results suggest that the presence of PCP-dehalogenating D. hafniense in the biofilm was crucial for the performance of the reactor.
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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".