Stable Metal Isotopes Reveal Copper Accumulation and Loss Dynamics in the Freshwater Bivalve <i>Corbicula</i>
Bibliographic record
Abstract
Characterization of uptake and loss dynamics is critical to understanding risks associated with contaminant exposure in aquatic animals. Dynamics are especially important in addressing questions such as why coexisting species in nature accumulate different levels of a contaminant. Here we manipulated copper (Cu) stable isotopic ratios (as an alternative to radioisotopes) to describe for the first time Cu dynamics in a freshwater invertebrate, the bivalve Corbicula fluminea. In the laboratory, Corbicula uptake and loss rate constants were determined from an environmentally realistic waterborne exposure to 65Cu (5.7 microg L(-1)). That is, we spiked deionized water with Cu that was 99.4% 65Cu. Net tracer uptake was detectable after 1 day and strongly evident after 4 days. Thus, short-term exposures necessary to determine uptake dynamics are feasible with stable isotopes of Cu. In Corbicula, 65Cu depuration was biphasic. An unusually low rate constant of loss (0.0038 d(-1)) characterized the slow component of efflux, explaining why Corbicula strongly accumulates copper in nature. We incorporated our estimates of rate constants for dissolved 65Cu uptake and physiological efflux into a bioaccumulation model and showed that dietary exposure to Cu is likely an important bioaccumulation pathway for Corbicula.
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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) | 0.000 | 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".