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Record W4401629915 · doi:10.1016/j.aquatox.2024.107047

Oil uptake via marine snow: Effects on blue mussels (Mytilus sp.)

2024· article· en· W4401629915 on OpenAlexafffund
Verena Kalter, Benjamin de Jourdan, Nasima Chorfa, Fei Wang, David C. Schneider, Uta Passow

Bibliographic record

VenueAquatic Toxicology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsUniversity of ManitobaHuntsman Marine Science CentreMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMytilusBlue musselSnowEnvironmental chemistryMarine snowBivalviaEnvironmental scienceMolluscaFisheryBiologyEcologyChemistryGeology

Abstract

fetched live from OpenAlex

Accidental oil spills into the ocean can lead to downward transport and settling of oil onto the seafloor as part of marine snow, as seen during the Deepwater Horizon incident in 2010 in the Gulf of Mexico. The arctic and subarctic regions may favor conditions leading to this benthic oil deposition, prompting questions about the potential impacts on benthic communities. This study investigated the effects of oil-contaminated marine snow uptake on the blue mussel (Mytilus sp.). We exposed mussels for four days to 1) oil-contaminated marine snow (MOS treatment), or to 2) chemically-enhanced water-accommodated fraction (CEWAF) of oil plus unaggregated food particles (CEWAF treatment). Both oil treatments received the same nominal concentration of oil and food. Two controls were included: 1) Clean seawater plus unaggregated food (agg-free control) and 2) clean seawater plus marine snow (marine snow control). After the exposure, mussels were allowed to recover for ten days under clean, running seawater. Samples were taken right before and after the exposure period, and after the recovery phase for the following endpoints: distribution (partitioning) of oil compounds between seawater and MOS, and between seawater and mussel tissue; DNA damage (assessed via the comet assay); clearance rate; and condition index [tissue dry weight (g) divided by shell length (mm)]. Some discernable patterns were found in the partitioning of oil compounds between seawater and MOS. However, these patterns did not translate to any significant differences in the partitioning of oil compounds into mussel tissue between the two oil treatments. DNA damage did not exceed background levels (10% tail DNA or less; to be expected in healthy, viable cells) at any sampling time point, but significantly higher DNA damage was observed in CEWAF-T compared to MOS-T mussels after the recovery phase. After the exposure, a significant difference emerged in the clearance rate between the CEWAF treatment and the agg-free control, but not between the MOS treatment and the marine snow control. All mussels except those from the CEWAF treatment exhibited an increased condition index after the exposure time. Together, these results suggest that aggregates could moderate the effects of oil exposure on blue mussels, possibly by providing better, more concentrated nutrition than unaggregated food particles.

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 score0.005
Threshold uncertainty score0.011

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 head0.009
GPT teacher head0.246
Teacher spread0.237 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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