Anaerobic Microbial Dechlorination of 6:2 Chlorinated Polyfluorooctane Ether Sulfonate and the Underlying Mechanisms
Bibliographic record
Abstract
The microbial transformation potential of 6:2 chlorinated polyfluorooctane ether sulfonate (6:2 Cl-PFESA) was explored in anaerobic microbial systems. Microbial communities from anaerobic wastewater sludge, an anaerobic digester, and anaerobic dechlorinating cultures enriched from aquifer materials reductively dechlorinated 6:2 Cl-PFESA to 6:2 hydrogen-substituted polyfluorooctane ether sulfonate (6:2 H-PFESA), which was identified as the sole metabolite by non-target analysis. Rapid and complete reductive dechlorination of 6:2 Cl-PFESA was achieved by the anaerobic dechlorinating cultures. The microbial community of the anaerobic dechlorinating cultures was impacted by 6:2 Cl-PFESA exposure. Organohalide-respiring bacteria originally present in the anaerobic dechlorinating cultures, including Geobacter, Dehalobacter, and Dehalococcoides, decreased in relative abundance over time. As the relative abundance of organohalide-respiring bacteria decreased, the rates of 6:2 Cl-PFESA dechlorination decreased, suggesting that the most likely mechanism for reductive dechlorination of 6:2 Cl-PFESA was co-metabolism rather than organohalide respiration. Reductive defluorination of 6:2 Cl-PFESA was not observed. Furthermore, 6:2 H-PFESA exhibited 5.5 times lower sorption affinity to the suspended biosolids than 6:2 Cl-PFESA, with the prospect of increased mobility in the environment. These results show the susceptibility of 6:2 Cl-PFESA to microbially mediated reductive dechlorination and the likely persistence of the product, 6:2 H-PFESA, in anaerobic environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".