3D electron microscopy reveals novel ultrastructural changes in the diabetic retinal neurovascular unit
Bibliographic record
Abstract
AIMS/HYPOTHESIS: This study used serial block-face scanning electron microscopy (SBF-SEM), a nanoscale imaging technique in x-y-z planes, to investigate 3D ultrastructural changes in the retinal neurovascular unit (NVU) associated with diabetes. We hypothesised that this approach would reveal previously uncharacterised pathological alterations that contribute to the development of diabetic retinal disease (DRD). METHODS: Retinas from male diabetic and non-diabetic mice, as well as from human male donors with and without diabetes, were prepared for SBF-SEM imaging. Retinal tissue was microdissected, fixed and embedded for serial sectioning and 3D reconstruction. Ultrastructural analysis of the NVU was performed in capillary regions exclusively within the superficial vascular plexus of both mouse and human retinas. Image stacks were processed using Microscopy Image Browser for contrast normalisation and segmentation, with 3D visualisation performed in Amira software. Quantitative analyses were conducted on pericyte-endothelial cell peg-and-socket formations, cell-basement membrane (BM) interactions, endothelial tubule formation and vascular BM thickness. RESULTS: SBF-SEM revealed novel 3D ultrastructural changes in the retinal NVU of diabetic mice and humans, including: (1) partial detachment and reduced frequency of pericyte-endothelium peg-and-socket formations (p<0.05-0.001); (2) localised detachment of endothelial cells and pericytes from the vascular BM (p<0.05-0.01), along with macroglial cell retraction from the outer vascular BM; and (3) increased formation of endothelial tubules (p<0.01-0.001). These changes were observed in the absence of any obvious vascular BM thickening, as no significant differences in mean or maximum BM thickness were found between diabetic and non-diabetic retinal capillaries analysed in this study. CONCLUSIONS/INTERPRETATION: This study provides new insights into the early ultrastructural changes in the retinal NVU in DRD, offering a basis for a better understanding of the pathological processes that contribute to the development of this disease. DATA AVAILABILITY: Links to all raw image stacks analysed in this article are available at https://doi.org/10.5281/zenodo.15210333 . The MATLAB vascular BM thickness measurement script is available at the GitHub link https://github.com/Curtis-WWIEM/BM_thickness .
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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".