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Record W1532261077 · doi:10.1111/nyas.12780

Sensing and surviving hypoxia in vertebrates

2015· review· en· W1532261077 on OpenAlexafffund
Michael G. Jonz, Leslie T. Buck, Steve F. Perry, Thorsten Schwerte, Giacomo Zaccone

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2015
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsUniversity of TorontoUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHypoxia (environmental)ChemoreceptorBiologyZebrafishNeuroscienceGlutamatergicNeuroepithelial cellCell biologyAnatomyGlutamate receptorGeneOxygenNeural stem cellGeneticsStem cellChemistryReceptor

Abstract

fetched live from OpenAlex

Surviving hypoxia is one of the most critical challenges faced by vertebrates. Most species have adapted to changing levels of oxygen in their environment with specialized organs that sense hypoxia, while only few have been uniquely adapted to survive prolonged periods of anoxia. The goal of this review is to present the most recent research on oxygen sensing, adaptation to hypoxia, and mechanisms of anoxia tolerance in nonmammalian vertebrates. We discuss the respiratory structures in fish, including the skin, gills, and air-breathing organs, and recent evidence for chemosensory neuroepithelial cells (NECs) in these tissues that initiate reflex responses to hypoxia. The use of the zebrafish as a genetic and developmental model has allowed observation of the ontogenesis of respiratory and chemosensory systems, demonstration of a putative intracellular O2 sensor in chemoreceptors that may initiate transduction of the hypoxia signal, and investigation into the effects of extreme hypoxia on cardiorespiratory development. Other organisms, such as goldfish and freshwater turtles, display a high degree of anoxia tolerance, and these models are revealing important adaptations at the cellular level, such as the regulation of glutamatergic and GABAergic neurotransmission in defense of homeostasis in central neurons.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.320
GPT teacher head0.413
Teacher spread0.093 · 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 designOther design
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

Citations91
Published2015
Admission routes2
Has abstractyes

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