The MCK mouse heart model of Friedreich's ataxia: Alterations in iron-regulated proteins and cardiac hypertrophy are limited by iron chelation
Bibliographic record
Abstract
There is no effective treatment for the cardiomyopathy of the most common autosomal recessive ataxia, Friedreich's ataxia (FA). The identification of potentially toxic mitochondrial (MIT) iron (Fe) deposits in FA suggests that Fe plays a role in its pathogenesis. This study used the muscle creatine kinase conditional frataxin (Fxn) knockout (mutant) mouse model that reproduces the classical traits associated with cardiomyopathy in FA. We examined the mechanisms responsible for the increased cardiac MIT Fe loading in mutants. Moreover, we explored the effect of Fe chelation on the pathogenesis of the cardiomyopathy. Our investigation showed that increased MIT Fe in the myocardium of mutants was due to marked transferrin Fe uptake, which was the result of enhanced transferrin receptor 1 expression. In contrast to the mitochondrion, cytosolic ferritin expression and the proportion of cytosolic Fe were decreased in mutant mice, indicating cytosolic Fe deprivation and markedly increased MIT Fe targeting. These studies demonstrated that loss of Fxn alters cardiac Fe metabolism due to pronounced changes in Fe trafficking away from the cytosol to the mitochondrion. Further work showed that combining the MIT-permeable ligand pyridoxal isonicotinoyl hydrazone with the hydrophilic chelator desferrioxamine prevented cardiac Fe loading and limited cardiac hypertrophy in mutants but did not lead to overt cardiac Fe depletion or toxicity. Fe chelation did not prevent decreased succinate dehydrogenase expression in the mutants or loss of cardiac function. In summary, we show that loss of Fxn markedly alters cellular Fe trafficking and that Fe chelation limits myocardial hypertrophy in the mutant.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".