Enhanced Renal Immunocytochemical Expression of ANG-(1-7) and ACE2 During Pregnancy
Bibliographic record
Abstract
Previously we demonstrated that kidney concentration and urinary excretion of angiotensin-(1-7) are increased during normal pregnancy in rats. Since this finding may reflect local kidney production of angiotensin-(1-7), we determined the immunocytochemical distribution of angiotensin-(1-7) and its newly described processing enzyme, ACE2, in kidneys of virgin and 19-day-pregnant Sprague-Dawley rats. Sprague-Dawley rats were killed at the 19th day of pregnancy, and tissues were prepared for immunocytochemical by using a polyclonal antibody to angiotensin- (1-7) or a monoclonal antibody to ACE2. Angiotensin-(1-7) immunostaining was predominantly localized to the renal tubules traversing both the inner cortex and outer medulla. ACE2 immunostaining was localized throughout the cortex and outer medulla and was visualized in the renal tubules of both virgin and pregnant rats. The quantification of angiotensin-(1-7) and ACE2 immunocytochemical staining showed that in pregnant animals, the intensity of the staining increased by 56% and 117%, respectively (P<0.05). This first demonstration of the immunocytochemical distribution of angiotensin-(1-7) and ACE2 in kidneys of pregnant rats shows that pregnancy increases angiotensin-(1-7) immunocytochemical expression in association with increased ACE2 intensity of staining. The findings suggest that ACE2 may contribute to the local production and overexpression of angiotensin-(1-7) in the kidney during pregnancy.
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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 | 0.000 |
| 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".