Bidirectional Phosphorylation Changes in Opsins Associated With Early Myopia and Hyperopia Signal Regulation by Phosphoproteomics
Bibliographic record
Abstract
Purpose: The study aimed to investigate the role of post-translational modifications (PTMs), specifically phosphorylation, in the pathogenesis of lens-induced myopia (LIM) and lens-induced hyperopia (LIH). Methods: This study used an untargeted phosphoproteomics approach to identify more than 12,000 phosphorylation sites in chick retinas. The changes in phosphorylation levels were quantified using the tandem mass tag (TMT) technique. Furthermore, targeted mass spectrometry was employed to characterize and validate the phosphorylation changes in visual opsins. Results: The analysis identified differential phosphorylation at specific sites: S334 in rhodopsin, S328 in violet-sensitive opsin, and S342 in blue-sensitive opsin. Notably, these serine residues were dephosphorylated during the onset of myopia, but they remained phosphorylated under hyperopic conditions. This finding indicates that phosphorylation patterns in opsins are significantly modulated by changes in optical conditions, potentially influencing retinal signaling pathways. Conclusions: The findings highlight the bidirectional modulation of phosphorylation in opsins as a potential mechanism linking optical factors from induced myopia and hyperopia to the molecular signaling processes that regulate ocular growth and adaptation.
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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 | 0.000 |
| 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".