Developmental riboflavin deficiency results in structural and functional changes in the neural retina and RPE
Bibliographic record
Abstract
The retina, a metabolically active tissue, relies on adequate flavin levels for optimal function. Our previous research demonstrated that ablation of RTBDN, a retina-specific riboflavin binding protein, plays a pivotal role in maintaining flavin levels, leading to progressive retinal degeneration. This raises the fundamental question of how riboflavin deficiency impacts retinal structure and function. We have previously evaluated an adult diet-induced model of riboflavin deficiency and showed that lack of flavins resulted in severe functional and structural deficits in the neural retina and retinal pigment epithelium with increased oxidative stress and metabolic dysregulation. Ariboflavinosis resulting from mutations in riboflavin transporters manifests early in life and is treatable with riboflavin supplementation. To mimic ariboflavinosis, we established an early-onset dietary model. At postnatal day 30, we observed a pronounced retinal phenotype characterized by early decline in cone function and subsequent loss of cone photoreceptors, while rods remained unaffected. Notably, RTBDN exhibited a biphasic response to early ariboflavinosis: initially upregulated, suggesting a protective role in maintaining retinal flavin levels, but decreased as deficiency persisted with subsequent photoreceptor functional decline. Riboflavin supplementation partially ameliorated these phenotypes by restoring retinal flavin and RTBDN levels, resulting in improvements in retinal structure and function. However, some cellular changes in the RPE remained irreversible and cone count was not restored. These findings underscore the critical roles of riboflavin and RTBDN in maintaining retinal and RPE health and highlight the importance of early detection and intervention for optimal therapeutic outcomes.
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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) | 0.001 | 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 | 0.001 | 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".