The Freshwater Invertebrate <i>Mysis relicta</i> Can Eliminate Chiral Organochlorine Compounds Enantioselectively
Bibliographic record
Abstract
Accumulation and elimination of chiral polychlorinated biphenyls (PCBs) and organochlorine (OC) pesticides by the opossum shrimp, Mysis relicta, was investigated to determine if zooplankton can stereoselectively process chiral OC contaminants. Concentrations and enantiomer fractions were measured within mysids over a 10-day exposure followed by a 45-day depuration period. Rapid accumulation occurred within mysids exposed to sediment contaminated with racemic chiral OC compounds at microg/g levels. Enantiomer enrichment was observed within mysids for the second-eluting enantiomer and the (-)-enantiomer of PCB 95 and trans-chlordane, respectively, after 7 days of exposure to spiked sediment, and for the second-eluting enantiomers of PCBs 91 and 183 and (-)-PCB 149 over longer time periods. Enantiomer fractions decreased with time during the depuration phase of the experiment for these compounds, showing that their elimination from mysids was stereoselective. Oxychlordane was detected in nonracemic proportions after exposure, indicating that mysids can metabolize trans-chlordane enantioselectively. Minimum elimination rates calculated were higher than biotransformation rates calculated for fish in previous studies, which have been shown to metabolize OC contaminants. This study is the first to show stereoselective processing of chiral OC contaminants by aquatic invertebrates.
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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) | 0.000 | 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 | 0.000 | 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".