Volumetric Reconstruction of a Human Retinal Pigment Epithelial Cell Reveals Specialized Membranes and Polarized Distribution of Organelles
Bibliographic record
Abstract
Purpose: Despite the centrality of the retinal pigment epithelium (RPE) in vision and retinopathy our picture of RPE morphology is incomplete. With a volumetric reconstruction of human RPE ultrastructure, we aim to characterize major membranous features including apical processes and their interactions with photoreceptor outer segments, basolateral infoldings, and the distribution of intracellular organelles. Methods: A parafoveal retinal sample was acquired from a 21-year-old male organ donor. With serial block-face scanning electron microscopy, a tissue volume from the inner-outer segment junction to basal RPE was captured. Surface membranes and complete internal ultrastructure of an individual RPE cell were achieved with a combination of manual and automated segmentation methods. Results: In one RPE cell, apical processes constitute 69% of the total cell surface area, through a dense network of over 3000 terminal branches. Single processes contact several photoreceptors. Basolateral infoldings facing the choriocapillaris resemble elongated filopodia and comprise 22% of the cell surface area. Membranous tubules and sacs of endoplasmic reticulum represent 20% of the cell body volume. A dense basal layer of mitochondria extends apically to partly overlap electron-dense pigment granules. Pores in the nuclear envelope form a distinct pattern of rows aligned with chromatin. Conclusions: Specialized membranes at the apical and basal side of the RPE cell body involved in intercellular uptake and transport represent over 90% of the total surface area. Together with the polarized distribution of organelles within the cell body, these findings are relevant for retinal clinical imaging, therapeutic approaches, and disease pathomechanisms.
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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 | 0.001 | 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".