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Record W4292871483 · doi:10.1242/jeb.244099

Fast-growing growth hormone transgenic coho salmon (<i>Oncorhynchus kisutch</i>) show a lower incidence of vaterite deposition and malformations in sagittal otoliths

2022· article· en· W4292871483 on OpenAlexaff
Irvin Chalan, Laia Solsona, Clara Coll-Lladó, Paul B. Webb, Dionne Sakhrani, Robert H. Devlin, Daniel García de la serrana

Bibliographic record

VenueJournal of Experimental Biology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Genetics and Reproduction
Canadian institutionsFisheries and Oceans Canada
FundersMinisterio de Ciencia y Tecnología
KeywordsVateriteWhitingOtolithBiologyCalciteDeposition (geology)OncorhynchusAragoniteAnimal scienceAquacultureTransgeneFish <Actinopterygii>CarpentariaFisheryBiochemistryGene

Abstract

fetched live from OpenAlex

In fish otoliths, CaCO3 normally precipitates as aragonite, and more rarely as vaterite or calcite. A higher incidence of vaterite deposition in otoliths from aquaculture-reared fish has been reported and it is thought that high growth rates under farming conditions might promote its deposition. To test this hypothesis, otoliths from growth hormone (GH) transgenic coho salmon and non-transgenic fish of matching size were compared. Once morphometric parameters were normalized by animal length, we found that transgenic fish otoliths were smaller (-24%, -19%, -20% and -30% for length, width, perimeter and area, respectively; P<0.001) and rounder (-12%, +13.5%, +15% and -15.5% in circularity, form factor, roundness and ellipticity; P<0.001) than otoliths from non-transgenic fish of matching size. Interestingly, transgenic fish had smaller eyes (-30% eye diameter) and showed a strong correlation between eye and otolith size. We also found that the percentage of otoliths showing vaterite deposition was significantly smaller in transgenic fish (21-28%) than in non-transgenic fish (69%; P<0.001). Likewise, the area affected by vaterite deposition within individual otoliths was reduced in transgenic fish (21-26%) compared with non-transgenic fish (42.5%; P<0.001). Our results suggest that high growth rates per se are not sufficient to cause vaterite deposition in all cases, and that GH overexpression might have a protective role against vaterite deposition, a hypothesis that needs 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.415

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.007
GPT teacher head0.249
Teacher spread0.242 · 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 teacher head, 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

Citations5
Published2022
Admission routes1
Has abstractyes

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