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Record W4407086092 · doi:10.3390/app15031542

Assessing the Relationship Between Cerebral Metabolic Rate of Oxygen and Redox Cytochrome C Oxidase During Cardiac Arrest and Cardiopulmonary Resuscitation

2025· article· en· W4407086092 on OpenAlexaff
Nima Soltani, Rohit Mohindra, Steve Lin, Vladislav Toronov

Bibliographic record

VenueApplied Sciences · 2025
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsSchwartz/Reisman Emergency Medicine InstituteNorth York General HospitalToronto Metropolitan UniversitySt. Michael's Hospital
Fundersnot available
KeywordsMedicineCytochrome c oxidaseCardiopulmonary resuscitationResuscitationCardiologyIntensive care medicineInternal medicineAnesthesiaChemistryMitochondrionBiochemistry

Abstract

fetched live from OpenAlex

Evaluating brain oxygen metabolism during cardiac arrest and cardiopulmonary resuscitation (CPR) is essential for improving neurological outcomes and guiding clinical interventions in high-stress medical emergencies. This study focused on two key indicators of brain oxygen metabolism: the cerebral metabolic rate of oxygen (CMRO2) and the oxidation state of redox cytochrome c oxidase (rCCO). Using advanced techniques such as hyperspectral near-infrared spectroscopy (hNIRS) and laser Doppler flowmetry (LDF), we conducted a comprehensive analysis of their relationship in pigs during and after cardiac arrest and CPR. Both the entire duration of these experiments and specific time intervals were investigated, providing a detailed view of how these metrics interact. The data reveal a non-linear relationship between rCCO and CMRO2. Our findings contribute to a deeper understanding of how the brain manages oxygen during critical episodes, potentially guiding future interventions in neurological care and improving outcomes in emergency medical settings.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.312
Teacher spread0.273 · 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 designObservational
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

Citations1
Published2025
Admission routes1
Has abstractyes

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