Cytochrome c oxidase-intermediate fibres: Importance in understanding the pathogenesis and treatment of mitochondrial myopathy
Bibliographic record
Abstract
An important diagnostic muscle biopsy finding in patients with mitochondrial DNA disease is the presence of respiratory-chain deficient fibres. These fibres are detected as cytochrome c oxidase-deficient following a sequential cytochrome c oxidase-succinate dehydrogenase reaction, often in a mosaic pattern within a population of cytochrome c oxidase-normal fibres. Detailed analysis of muscle biopsies from patients with various mitochondrial DNA defects shows that a spectrum of deficiency exists, as there are a large number of fibres which do not correspond to being either completely cytochrome c oxidase-normal (brown staining) or cytochrome c oxidase-deficient (blue staining). We have used a combination of histochemical and immunocytochemical techniques to show that a population of cytochrome c oxidase-intermediate reacting fibres are a gradation between normal and deficient fibres. We show that cytochrome c oxidase-intermediate fibres also have different genetic characteristics in terms of amount of mutated and wild-type mtDNA, and as such, may represent an important transition between respiratory normal and deficient fibres. Assessing changes in intermediate fibres will be crucial to evaluating the responses to treatment and in particular to exercise training regimes in patients with mitochondrial DNA disease.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".