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Record W3047909880 · doi:10.1113/jp280301

Fail‐safe aspects of oxygen supply

2020· article· en· W3047909880 on OpenAlexaff
James Duffin

Bibliographic record

VenueThe Journal of Physiology · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsThornhill Medical (Canada)University of Toronto
Fundersnot available
KeywordsHypoxia (environmental)OxygenComputer scienceRemedial educationBlood supplyCarotid bodyHypercapniaOxygen deliveryBiochemical engineeringNeuroscienceMedicineSurgeryPhysiologyEngineeringChemistryBiologyPsychologyElectrophysiologyCardiorespiratory fitness

Abstract

fetched live from OpenAlex

KEY POINTS: A fall in oxygen supply releases a remedial response that is otherwise prevented when the oxygen supply is sufficient; for example, the remedial function of HIF-1α is released when oxygen levels fall. CONCEPT: the physiological responses initiated when oxygen supply is compromised operate in a fail-safe manner. This concept is applied to two cases: the control of cerebral blood flow, and the detection of hypoxia by the carotid body. The fail-safe oxygen supply concept was tested with simple computer simulations to demonstrate its function and verify the ability to reproduce measured data. The computer model reproduced published observations, suggesting that the fail-safe concept can be considered as a principle that provides novel insight into the physiology of oxygen supply in these cases. ABSTRACT: An engineered fail-safe system automatically prevents or mitigates the consequences of a system failure. This operational concept can be applied both to the delivery of oxygen to the brain during hypoxia and anaemia, and to the carotid body response to hypoxia and hypercapnia. I aimed to develop simple mathematical models of these fail-safe processes and examine their ability to replicate experimental observations. The intent is to demonstrate the validity of applying the fail-safe concept, not to reveal the details of the physiology involved. The model calculations are based on a single compartment of the relevant tissue in each case that is challenged with a decrease in oxygen supply. The model equation parameters were adjusted to reproduce experimental observations. The fail-safe model of cerebral blood flow control yielded results similar in form to published experimental observations of the cerebral blood flow responses to hypoxia and anaemia. The fail-safe model of carotid body glomus cell control of intracellular hydrogen ion concentration also yielded results similar in form to observations of carotid sinus nerve responses to hypoxia and hypercapnia. The ability of these simple models to simulate experimental observations demonstrates the applicability of the fail-safe concept to oxygen delivery. I suggest that a fail-safe view of oxygen delivery provides novel physiological insight.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.044
GPT teacher head0.277
Teacher spread0.233 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations8
Published2020
Admission routes1
Has abstractyes

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