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Record W1599174528 · doi:10.1002/9780470035009.ch7

The Role of TASK‐Like K <sup>+</sup> Channels in Oxygen Sensing in the Carotid Body

2006· article· en· W1599174528 on OpenAlexaff
Keith J. Buckler, Beatrice A. Williams, Rodrigo Varas Orozco, Christopher N. Wyatt

Bibliographic record

VenueNovartis Foundation symposium · 2006
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsWestern University
Fundersnot available
KeywordsCarotid bodyDepolarizationMitochondrionHypoxia (environmental)Membrane potentialHypoxemiaMetabolismCell biologyCell typeBiophysicsOxygenChemistryBiologyCellElectrophysiologyInternal medicineBiochemistryNeuroscienceMedicine

Abstract

fetched live from OpenAlex

The carotid body plays an important role in initiating protective responses to hypoxemia. The primary oxygen sensing cells are the glomus or type 1 cells. Hypoxia evokes the secretion of neurotransmitters from these cells which then excite afferent nerves. This response is mediated via membrane depolarization and voltage-gated Ca2+ entry. Studies from this laboratory have revealed that membrane depolarization in response to hypoxia is primarily the result of inhibition of background K+ channels which show strong similarities to the acid sensitive tandem-P-domain K+ channels TASK-1 and TASK-3. The background K+ channels of type-1 cells are also very sensitive to inhibition of mitochondrial energy metabolism and, in excised patches, appear to be directly activated by ATP. Thus these TASK-like background channels would appear to confer the ability to sense changes in oxygen levels, pH and metabolism upon the type 1 cell. The key issue of whether the effects of hypoxia are mediated through changes in metabolism remains unanswered but the effects of inhibition of mitochondrial energy metabolism and of hypoxia upon background K+ channels is mutually exclusive suggesting that there is a close link between metabolism and oxygen sensing in the type 1 cell.

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 score0.251
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.254
Teacher spread0.237 · 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

Citations12
Published2006
Admission routes1
Has abstractyes

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