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Record W4386037693 · doi:10.1139/facets-2022-0177

Using transcriptomics to examine the physiological status of wild-caught walleye (<i>Sander vitreus</i>)

2023· article· en· W4386037693 on OpenAlexafffundvenueabout
Jennifer D. Jeffrey, Matt J. Thorstensen, Eva C. Enders, Jason R. Treberg, Ken M. Jeffries

Bibliographic record

VenueFACETS · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversity of Manitoba
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsGenome Canada
KeywordsTranscriptomeBiologyEcologyHypoxia (environmental)ZoologyFisheryGeneGene expressionGenetics

Abstract

fetched live from OpenAlex

Lake Winnipeg, Manitoba, is Canada’s second largest commercial inland freshwater fishery, and concern over collapse of the walleye fishery is growing. Molecular techniques have been increasingly used to study responses of wild organisms to environmental and anthropogenic stressors. The present study used transcriptomics to examine the physiology of wild-caught walleye ( Sander vitreus (Mitchell, 1818)) across Lake Winnipeg using non-lethal techniques. Gill transcriptomes of walleye sampled from the north and south basins of Lake Winnipeg, and the channel connecting them, exhibited distinct profiles implicating regionally specific biological responses. North basin walleye exhibited transcriptomic responses indicative of exposure to environmental stressors. Transcriptomic patterns suggested a shift to increased reliance on anaerobic metabolism and up-regulation of hypoxia-sensitive genes in north basin fish, possibly representing exposure to low-oxygen conditions. Exposure to environmental stressors may also have driven increases in gene transcripts associated with proteasomal catabolism, DNA repair, molecular chaperones, and ion regulation. North basin fish also exhibited transcriptomic patterns indicative of gill remodeling via regulation of the mTOR pathway, cytoskeleton reorganization, and fatty acid synthesis. Our results highlight the complexity of examining wild fish across environmental gradients but also the potential use of molecular techniques in elucidating organismal sensitivity to local environmental factors.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score0.590

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)0.0010.000

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 head0.082
GPT teacher head0.286
Teacher spread0.203 · 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

Citations20
Published2023
Admission routes4
Has abstractyes

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