Novel Retinal and Cone Photoreceptor Transcripts Revealed by Human Macular Expression Profiling
Bibliographic record
Abstract
PURPOSE: The macula is essential for visual acuity. It contains many more cone photoreceptors than does the peripheral retina. In this study, macular gene expression was compared with that in the rod-rich peripheral retina. METHODS: Two-millimeter foveomacular and four-millimeter macular punches from human donor eyes, in addition to sections of midperipheral retina, were used to study differential gene expression. Multiple microarray experiments were combined with quantitative PCR and bioinformatic analyses. In the present study, the expression of both known and previously unidentified retinal genes was determined. RESULTS: Several macula enriched transcripts were revealed. Nuclear pore complex interacting protein (NPIP) and eukaryotic translation initiation factor 2alpha kinase (GCN2) were expressed at levels approaching that of red/green cone opsin in the macula. The protein products of several genes highlighted using these expression analyses were also localized in the retina. Both NPIP and histone deacetylase 9 (HDAC9) proteins were detected in cone photoreceptor outer segments. CONCLUSIONS: Characterizing macula enriched transcripts is an important stepping-stone in understanding the molecular basis for visual acuity in the retina. The approach also provides excellent candidates for diseases that affect the macula and fovea such as age-related macular degeneration (AMD). Indeed, several of these transcripts, such as NPIP and GCN2, have genomic loci that are consistent with being candidate genes for AMD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".