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Record W2555487521 · doi:10.1242/jeb.128496

Temperature-induced cardiac remodeling in fish

2016· review· en· W2555487521 on OpenAlexafffund
A. Keen, Jordan M. Klaiman, Holly A. Shiels, Todd E. Gillis

Bibliographic record

VenueJournal of Experimental Biology · 2016
Typereview
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of Guelph
FundersBiotechnology and Biological Sciences Research CouncilDirectorate for Biological SciencesNatural Sciences and Engineering Research Council of CanadaHeart and Stroke Foundation of Canada
KeywordsVentricleInternal medicineAcclimatizationContext (archaeology)CardiologyVentricular remodelingHeart failureBiologyMedicineEcology

Abstract

fetched live from OpenAlex

Thermal acclimation causes the heart of multiple fish species to undergo significant remodeling. This includes changes in electrical activity, energy utilization and structural properties at the gross and molecular level of organization. The purpose of this Review is to summarize the current state of knowledge of temperature-induced structural remodeling in the fish ventricle across multiple levels of biological organization, and to examine how such changes result in the modification of the functional properties of the heart. The structural remodeling response is thought to be responsible for changes in cardiac stiffness, the Ca2+ sensitivity of force generation and the rate of force generation by the heart. Such changes to both active and passive properties help to compensate for the loss of cardiac function caused by a decrease in physiological temperature. Hence, temperature-induced cardiac remodeling is common in fish that remain active following seasonal decreases in temperature. This Review is organized around the ventricular phases of the cardiac cycle – specifically diastolic filling, isovolumic pressure generation and ejection – so that the consequences of remodeling can be fully described. We will also compare the thermal acclimation-associated modifications of the fish ventricle with those seen in the mammalian ventricle in response to cardiac pathologies and exercise. Finally, we will consider how the plasticity of the fish heart may be relevant to survival in a climate change context, where seasonal temperature changes could become more extreme and variable.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.051
GPT teacher head0.336
Teacher spread0.286 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations100
Published2016
Admission routes2
Has abstractyes

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