Effect of thyroid hormone on oxidative stress in cells from patients with mtDNA defects
Bibliographic record
Abstract
Mitochondrial DNA (mtDNA) mutations contribute to the development of various disease states and are characterized by low ATP production in patient cells. In contrast, thyroid hormone (T 3 ) induces mitochondrial biogenesis and enhances the ability of cells to generate ATP. To evaluate the role of T 3 ‐mediated mitochondrial biogenesis in patients with mtDNA mutations, three primary fibroblast cell lines with mtDNA mutations were evaluated, including a patient with Leigh’s syndrome, one with a tRNA leu mutation and another with an ATP6 mutation. Compared to normal cells, patient fibroblasts displayed similar levels of mitochondrial mass, a 1.6‐fold elevation in reactive oxygen species (ROS) production, a 1.7‐fold elevation in cytoplasmic Ca 2+ levels and a 10% lower mitochondrial membrane potential. Patient cells also exhibited 25% reduction in cytochrome c oxidase (COX) activity and MnSOD levels compared to normal cells. Following T 3 treatment, in normal and patient cells, mitochondrial mass did not change, but ROS production was decreased by 30–40%, cytoplasmic Ca 2+ levels were reduced by 20% and COX activity was increased by 10–20%. There was no significant change in the expression of the mitochondrial biogenesis regulator PGC‐1, but a 20% increase in Tfam levels was evident in both T 3 ‐treated patient and normal cells. T 3 also restored the levels of MnSOD to normal values in patient cells and increased MnSOD by 25% in control cells. These results suggest that T 3 acts to reduce cellular oxidative stress, which may help attenuate ROS‐mediated macromolecular damage. Supported by CIHR.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".