Assessing the relationship between the cerebral metabolic rate of oxygen and the oxidation state of cytochrome-c-oxidase
Bibliographic record
Abstract
Significance: Hyperspectral near-infrared spectroscopy (hsNIRS) combined with diffuse correlation spectroscopy (DCS) provides a noninvasive approach for monitoring cerebral blood flow (CBF), the cerebral metabolic rate of oxygen (CMRO2) and the oxidation state of cytochrome-c-oxidase (oxCCO). CMRO2 is calculated by combining tissue oxygen saturation (StO2) with CBF, whereas oxCCO can be measured directly by hsNIRS. Although both reflect oxygen metabolism, a direct comparison has yet to be studied.Aim: We aim to investigate the relationship between CMRO2 and oxCCO during periods of restricted oxygen delivery and lower metabolic demand.Approach: A hybrid hsNIRS/DCS system was used to measure hemodynamic and metabolic responses in piglets exposed to cerebral ischemia and anesthetic-induced reductions in brain activity.Results: Although a linear relationship was observed between CMRO2 and oxCCO during ischemia, both exhibited a nonlinear relationship with respect to CBF. In contrast, linear correlation was sufficient to characterize the relationships between CMRO2 and CBF and between the two metabolic markers during reduced metabolic demand.Conclusions: The observed relationship between CMRO2 and oxCCO during periods of restricted oxygen delivery and lower metabolic demand indicates that the two metabolic markers are strongly correlated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".