Pulse exposure to microplastics depolarizes the goldfish gill: Interactive effects of DOC and differential degradation
Bibliographic record
Abstract
Microplastics (MPs) are constantly degrading while moving through aquatic systems as a result of mechanical abrasion, thermal fluctuations, UV light, and chemical exposure. As such, fish may experience pulse exposures to differentially degraded plastics. This study addresses how pulse exposures, over the course of minutes, to differentially degraded microplastics alters a key ionoregulatory property of the goldfish gill. We used transepithelial potential (TEP) across the gills, a diffusion potential resulting from the differential permeability of cations versus anions, as a sensitive indicator of potential ionoregulatory effects. Virgin (non-degraded) MPs along with mechanically, UV, and thermally degraded plastics immediately depolarized the gills (less negative TEP), whereas chemically degraded MPs resulted in no change to TEP. To further explore the physicochemical interaction between the surface of the gill and MPs, combinations of MPs and a single source of dissolved organic carbon (DOC) were tested and revealed that the presence of DOC negated the effects of MPs at the gill regardless of whether DOC or MPs were introduced first. This study suggests that while MPs have the ability to cause ionoregulatory effects at the gill, the effects of ambient water quality, specifically the presence of DOC, are of greater influence.
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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".