Ambient light alleviates retinal neurodegeneration in mice by powering mitochondria via the engineered optoenergetic rhodopsin
Bibliographic record
Abstract
The mitochondrial proton motive force (pmf) is a critical driver of cellular energy production and influences various cellular processes. Dysregulation of pmf is implicated in a range of diseases, including neurodegenerative diseases, mitochondrial diseases, cancer and aging-related pathologies. Currently, an efficient strategy to rescue ATP production and mitigate reactive oxygen species (ROS) generation under conditions of energy deprivation is lacking. Here, we engineered a light-sensitive, mitochondria-targeting proton-pumping rhodopsin (PPR), mt-EcGAPR, capable of generating an efficient pmf for ATP synthesis while simultaneously mitigating reactive oxygen species (ROS) generation during stress and decreasing DNA double-strand breaks (DSBs). Owing to its transparency to visible light, eye is the ideal candidate for the noninvasive application of mt-EcGAPR in the treatment of mitochondria-related retinal degenerative diseases. Using a silicone oil-induced ocular hypertension glaucoma mouse model, we demonstrate that ambient light activation of mt-EcGAPR significantly increased ATP production, suppressed ROS accumulation, and protected retinal ganglion cells (RGCs) from degeneration. Mechanistically, mt-EcGAPR inhibited endoplasmic reticulum (ER) stress-ATF6-gasdermin D (GSDMD)-mediated pyroptosis, thereby preserving retinal structure and function. This intervention ultimately led to improved visual acuity in glaucomatous eyes of mice. Collectively, our findings establish mt-EcGAPR as a promising therapeutic strategy for glaucoma and potentially other neurodegenerative diseases associated with mitochondrial dysfunction and impaired bioenergetics.
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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) | 0.001 | 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".