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Record W4417531111 · doi:10.1093/conphys/coaf088

Identification of food deprivation in salmonids using gill biomarkers

2025· article· en· W4417531111 on OpenAlexaff

Bibliographic record

VenueConservation Physiology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of VictoriaSimon Fraser UniversityFisheries and Oceans CanadaUniversity of British Columbia
Fundersnot available
KeywordsJuvenileChinook windPredationFood intakePrivationShellfish

Abstract

fetched live from OpenAlex

) may experience prolonged periods of food deprivation upon marine entry and during their first marine winter. We assessed the physiological and transcriptional consequences of food deprivation to discover and develop mRNA-based biomarkers for food deprivation in the gill of juvenile Chinook salmon. Gill and liver tissue were collected from juvenile Chinook salmon held at 16 or 8°C that were fed or food deprived for up to 56 days and during a 21-day refeeding period. Chinook salmon at 16 and 8°C were able to withstand food deprivation for periods of 35 and 56 days, respectively, with declines in body morphometrics, hepatosomatic index, insulin-like growth factor-1 and energy density observed in food-deprived individuals, followed by rapid recovery during refeeding. RNA-sequencing at the end of the food deprivation period revealed candidate biomarkers for food deprivation representing structural and functional components of the gill as well as metabolic processes like lipid storage and energy metabolism in the liver. Using the strongest 12 gill biomarkers paired with high-throughput qPCR and a random forest classification model, transcriptional signatures of food deprivation were detected within 14 to 28 days following food deprivation and persisted for at least 6 days following refeeding. These gill biomarkers can be non-lethally applied to wild juvenile salmon to answer long standing questions regarding food deprivation and the drivers of mortality during their early marine migration and overwintering.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.339
Threshold uncertainty score0.221

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 head0.017
GPT teacher head0.251
Teacher spread0.234 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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