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Record W7056196663

Differential domoic acid uptake by eastern oysters (Crassostrea virginica) and blue mussels (Mytilus edulis) exposed to toxic pseudo-nitzschia multiseries clones

2007· other· en· W7056196663 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2007
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsIsochrysis galbanaShellfishCrassostreaDomoic acidBivalviaOstreidaeEcosystemMesocosmParalytic shellfish poisoning
DOInot available

Abstract

fetched live from OpenAlex

Bivalve molluscs can pose a public health hazard by accumulating high levels of domoic acid (DA) when suspension-feeding on toxic Pseudo-nitzschia spp. DA has also caused mortalities of marine fauna and economic losses due to shellfish closures worldwide. Although there are no field reports to date of DA contamination above the regulatory limit (20 µg.g-1) in oysters, harvest closures are often imposed on all bivalve species, as occurred during an anomalous early spring bloom of P. seriata in the southern Gulf of St. Lawrence in 2002. The present study a) compares DA uptake rates in Eastern oysters (Crassostrea virginica) and blue mussels (Mytilus edulis) under common laboratory conditions, and b) investigates feeding responses in oysters that may explain their relatively low capacity for DA accumulation. Our findings will be used to evaluate the potential for species-specific management of DA-contaminated shellfish. In two long-term trials (~2 wks), juvenile oysters and mussels were offered either P. multiseries clone CLN-20 (24 µm cell length) or clone CLN-50 (81 µm) at a constant density (8,500 and 1,800 cells.ml-1, respectively), in stationary growth phase, at 12ºC. These clones were almost exclusively singlecelled. Pooled individuals were sampled in triplicate over time to determine DA content in tissues by HPLC. Short-term feeding experiments were also conducted to determine clearance rate (CR) and pseudofeces production of oysters fed toxic P. multiseries clones of various sizes. They were offered as unialgal diets or mixed with an equivalent cell volume of either the flagellate Isochrysis galbana (clone T-Iso) or another P. multiseries clone of contrasting cell size. The CR of mussels fed unialgal CLN-50 was also quantified. Particulate DA levels (pDA) ranged from 0.6 to 7.4 pg.cell-1 among clones and trials, but only clones of similar toxicity were combined within mixed diets. When fed the smaller CLN-20 clone (at 5.9 ng pDA.ml-1 of suspension), mussels accumulated weight-specific DA levels ~2.5x higher than oysters (mean peak toxicity = 43.5 and 17.2 µg.g-1, respectively). When fed the more toxic but larger CLN-50 clone (at 8.7 ng pDA.ml-1), maximum toxicity remained low in oysters (11 µg.g-1), whereas it increased to 243 µg.g-1 in mussels (~22x higher than in oysters). Mussels also had a higher CR than oysters (33.1 and 13.7 ml.min-1.g DW-1, respectively). In short-term feeding experiments using mixed diets, oysters showed high ingestion selectivity. They preferentially rejected two larger P. multiseries clones (80-100 µm) in pseudofeces when combined with the smaller clone CLN-20 (24-29 µm). They also selectively rejected P. multiseries cells when offered in a mixed suspension with I. galbana (4.5 µm), regardless of cell size, such that even the small CLN-20 clone was preferentially rejected in pseudofeces. Therefore, low toxicity in oysters fed toxic P. multiseries at bloom concentrations is at least partly explained by a combination of low clearance rate and pre-ingestive rejection of P. multiseries cells at the gills and/or labial palps. The mechanisms for particle selection, which involve differences in size and physical-chemical characteristics of the cells, are the subject of further investigation.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.253
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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