The T414G mitochondrial DNA mutation: a biomarker of ageing in human eye
Bibliographic record
Abstract
The mitochondrial mutation T414G (mtDNAT414G) has been shown to accumulate in aged and sun-exposed skin. The human eye is also exposed to solar harmful rays. More precisely, the anterior structures of the eye (cornea, iris) filter UV rays and the posterior portion of the eye (retina) is exposed to visible light. These rays can catalyse mutations in mitochondrial DNA such as the mtDNAT414G, but the latter has never been investigated in the human ocular structures. In this study, we have developed a technique to precisely assess the occurrence of mtDNAT414G. Using this technique, we have quantified mtDNAT414G in different human ocular structures. We found an age-dependent accumulation of mtDNAT414G in the corneal stroma, the cellular layer conferring transparency and rigidity to the human cornea, and in the iris. Since cornea and iris are two anterior ocular structures exposed to solar UV rays, this suggests that the mtDNAT414G mutation is resulting from cumulative solar exposure and this could make the mtDNAT414G a good marker of solar exposure. We have previously shown that the mtDNACD4977 and mtDNA3895 deletions accumulate over time in photo-exposed ocular structures. With the addition of mtDNAT414G mutation, it becomes feasible to combine the levels of these different mtDNA mutations to obtain an accurate assessment of the solar exposure that an individual has accumulated during his/her lifetime.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".