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Record W1998355768 · doi:10.1139/f03-039

Red blood cell Hsp 70 mRNA and protein as bio-indicators of temperature stress in the brook trout (<i>Salvelinus fontinalis</i>)

2003· article· en· W1998355768 on OpenAlexfundvenueaboutno aff
Susan G. Lund, Mervyn E.A Lund, Bruce L. Tufts

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSalvelinusTroutHeat shock proteinHsp70FontinalisHeat shockBiologyBiomarkerAndrologyChemistryFish <Actinopterygii>BiochemistryMedicineFisheryGene

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the heat shock protein (Hsp) 70 mRNA and protein response in several tissues of Miramichi brook trout (Salvelinus fontinalis) under both acute and extended heat stress conditions to determine the utility of the red blood cell (rbc) heat shock response as a biomarker of sublethal temperature stress. Red blood cells consistently produced one of the highest responses of all of the tissues examined. Recovery of Hsp 70 mRNA following acute temperature increase required between 24 h and 48 h. In contrast, Hsp 70 protein levels remained significantly elevated for more than 48 h after the heat stress was terminated. During a 6-day extended (23°C) heat stress, rbc Hsp 70 mRNA returned to control levels between 72 and 144 h, whereas Hsp 70 protein was still significantly elevated after 6 days. Thus, although Hsp 70 mRNA proved to be a more sensitive indicator of heat stress in all tissues examined, Hsp 70 protein levels were more sustained. This study confirms the utility of rbcs as a biomarker tissue of thermal stress in fish and indicates that water temperatures presently being reached in brook trout habitats in Canada are capable of inducing a significant heat shock response in this species.

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)0.001
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 score0.315
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.232
Teacher spread0.224 · 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

Citations64
Published2003
Admission routes3
Has abstractyes

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