Abnormal oxidative metabolism in the cuprizone mouse model of demyelination: An in vivo NIRS-MRI study
Bibliographic record
Abstract
Disruptions in oxidative metabolism may occur in multiple sclerosis and other demyelinating neurological diseases. The impact of demyelination on metabolic rate is also not understood. It is possible that mitochondrial damage may be associated with many such neurological disorders. To study oxidative metabolism with one model of demyelination, we implemented a novel multimodal imaging technique combining Near-Infrared Spectroscopy (NIRS) and MRI to cuprizone mouse model. The cuprizone model is used to study demyelination and may be associated with inhibition of mitochondrial function. Cuprizone mice showed reduced oxygen extraction fraction (-39.1%, p ≤ 0.001), increased tissue oxygenation (6.4%, p ≤ 0.001), and reduced cerebral metabolic rate of oxygen in cortical gray matter (-62.1%, p ≤ 0.001). These changes resolved after the cessation of cuprizone exposure and partial remyelination. A decrease in hemoglobin concentration (-34.4%, p ≤ 0.001), but no change in cerebral blood flow were also observed during demyelination. The oxidized state of the mitochondrial enzyme, Cytochrome C Oxidase (CCO) increased (46.3%, p ≤ 0.001) while the reduced state decreased (-34.4%, p ≤ 0.05) significantly in cuprizone mice. The total amount of CCO did not change significantly during cuprizone exposure. Total CCO did decline after recovery both in control (-23.1%, p ≤ 0.01) and cuprizone (-28.8%, p ≤ 0.001) groups which may relate to age. A reduction in the magnetization transfer ratio, indicating demyelination, was found in the cuprizone group in the cerebral cortex (-3.2%, p ≤ 0.01) and corpus callosum (-5.5%, p ≤ 0.001). In summary, we were able to detect evidence of altered CCO metabolism during cuprizone exposure, consistent with a mitochondrial defect. We observed increased oxygenation and reduced metabolic rate associated with reduced myelination in the gray and white matter. The novel multimodal imaging technique applied here shows promise for noninvasively assessing parameters associated with oxidative metabolism in both mouse models of neurological disease and for translation to study oxidative metabolism in the human brain.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".