Loss of Angiotensin-Converting Enzyme 2 Exacerbates Diabetic Retinopathy by Promoting Bone Marrow Dysfunction
Bibliographic record
Abstract
Abstract Angiotensin-converting enzyme 2 (ACE2) is the primary enzyme of the vasoprotective axis of the renin angiotensin system (RAS). We tested the hypothesis that loss of ACE2 would exacerbate diabetic retinopathy by promoting bone marrow dysfunction. ACE2–/y were crossed with Akita mice, a model of type 1 diabetes. When comparing the bone marrow of the ACE2–/y-Akita mice to that of Akita mice, we observed a reduction of both short-term and long-term repopulating hematopoietic stem cells, a shift of hematopoiesis toward myelopoiesis, and an impairment of lineage–c-kit+ hematopoietic stem/progenitor cell (HS/PC) migration and proliferation. Migratory and proliferative dysfunction of these cells was corrected by exposure to angiotensin-1-7 (Ang-1-7), the protective peptide generated by ACE2. Over the duration of diabetes examined, ACE2 deficiency led to progressive reduction in electrical responses assessed by electroretinography and to increases in neural infarcts observed by fundus photography. Compared with Akita mice, ACE2–/y-Akita at 9-months of diabetes showed an increased number of acellular capillaries indicative of more severe diabetic retinopathy. In diabetic and control human subjects, CD34+ cells, a key bone marrow HS/PC population, were assessed for changes in mRNA levels for MAS, the receptor for Ang-1-7. Levels were highest in CD34+ cells from diabetics without retinopathy. Higher serum Ang-1-7 levels predicted protection from development of retinopathy in diabetics. Treatment with Ang-1-7 or alamandine restored the impaired migration function of CD34+ cells from subjects with retinopathy. These data support that activation of the protective RAS within HS/PCs may represents a therapeutic strategy for prevention of diabetic retinopathy.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".