Mechanisms contributing to low domoic acid uptake by oysters feeding on Pseudo-nitzschia cells. I. Filtration and pseudofeces production
Bibliographic record
Abstract
Bivalve molluscs feeding on toxigenic Pseudo-nitzschia spp.are the main vector of domoic acid (DA) to humans.Although different oyster species rarely exceed the internationally adopted regulatory level for shellfish harvesting closures (20 µg g -1 ), these are often applied to all bivalve species in an affected area.This study examines the influence of diet composition and Pseudo-nitzschia multiseries cell size, density and toxicity on oyster feeding rates to determine potential pre-ingestive mechanisms that may lead to low DA accumulation in the oysters Crassostrea virginica.Clearance rate (CR) and pseudofeces production of juvenile oysters were quantified under varying laboratory conditions representative of natural Pseudo-nitzschia blooms.Oysters filtered increasing amounts of P. multiseries cells as cell density increased, but ingestion was limited by pseudofeces production at concentrations >10 400 cells ml -1 (ca.6 mg dry weight l -1 ).Oysters significantly reduced their CR when fed both toxic and non-toxic P. multiseries clones in unialgal suspensions compared to Isochrysis galbana, and this rapid grazing inhibition was not related to growth stage, cell size, or exposure time.When offered mixed suspensions containing equivalent cellular volumes of the 2 species, however, relatively high CR was restored.Therefore, we suggest that DA intake by oysters from mono-specific Pseudo-nitzschia blooms would be limited by a persistently reduced CR and rejection of cells in pseudofeces.When an alternative, good source of food is present in a mixed phytoplankton assemblage with P. multiseries, no CR inhibition is expected and DA intake will be regulated by pre-ingestive particle selection on the feeding organs, as demonstrated in Mafra et al. (2009, in this Theme Section)
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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".