Characterization of Retinal Microvascular Complications and the Effects of Endoplasmic Reticulum Stress in Mouse Models of Diabetic Atherosclerosis
Bibliographic record
Abstract
Purpose: Recent evidence suggests that there is a correlation between the micro- and macrovascular complications of diabetes mellitus. The aim of this study is to investigate the molecular mechanisms by which diabetes promotes the development of microvascular disease (diabetic retinopathy [DR]) through characterization of the effects of hyperglycemia in the retina of mouse models of diabetic atherosclerosis. Methods: Hyperglycemia was induced in apolipoprotein E-deficient (ApoE-/-) mice, a model of accelerated atherosclerosis, either through streptozotocin (STZ) injection or introduction of the Ins2Akita mutation (ApoE-/-Ins2+/Akita). Another subset of ApoE-/- mice was supplemented with glucosamine (GlcN). To attenuate atherosclerosis, subsets of mice from each experimental group were treated with the chemical chaperone, 4-phenylbutyric acid (4PBA). Eyes from 15-week-old mice were either trypsin digested and stained with periodic acid-Schiff (PAS) or frozen for cryostat sectioning and immunostained for endoplasmic reticulum (ER) stress markers, including C/EBP homologous protein (CHOP) and 78-kDa glucose-regulated protein (GRP78). PAS-stained retinal flatmounts were analyzed for microvessel density, acellular capillaries, and pericyte ghosts. Results: Features of DR, including pericyte ghosts and reduced microvessel density, were observed in hyperglycemic and GlcN-supplemented mice. Treatment with 4PBA reduced ER stress in the retinal periphery and attenuated DR in the experimental groups. Conclusions: Mouse models of diabetic atherosclerosis show characteristic pathologies of DR that correlate with atherosclerosis. The increased magnitude of these changes and responses to 4PBA in the peripheral retina suggest that future studies should be aimed at assessing regional differences in mechanisms of ER stress-related pathways in these mouse models.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".