Glomerular type 1 angiotensin receptors augment kidney injury and inflammation in murine autoimmune nephritis
Bibliographic record
Abstract
Studies in humans and animal models indicate a key contribution of angiotensin II to the pathogenesis of glomerular diseases. To examine the role of type 1 angiotensin (AT1) receptors in glomerular inflammation associated with autoimmune disease, we generated MRL-Faslpr/lpr (lpr) mice lacking the major murine type 1 angiotensin receptor (AT1A); lpr mice develop a generalized autoimmune disease with glomerulonephritis that resembles SLE. Surprisingly, AT1A deficiency was not protective against disease but instead substantially accelerated mortality, proteinuria, and kidney pathology. Increased disease severity was not a direct effect of immune cells, since transplantation of AT1A-deficient bone marrow did not affect survival. Moreover, autoimmune injury in extrarenal tissues, including skin, heart, and joints, was unaffected by AT1A deficiency. In murine systems, there is a second type 1 angiotensin receptor isoform, AT1B, and its expression is especially prominent in the renal glomerulus within podocytes. Further, expression of renin was enhanced in kidneys of AT1A-deficient lpr mice, and they showed evidence of exaggerated AT1B receptor activation, including substantially increased podocyte injury and expression of inflammatory mediators. Administration of losartan, which blocks all type 1 angiotensin receptors, reduced markers of kidney disease, including proteinuria, glomerular pathology, and cytokine mRNA expression. Since AT1A-deficient lpr mice had low blood pressure, these findings suggest that activation of type 1 angiotensin receptors in the glomerulus is sufficient to accelerate renal injury and inflammation in the absence of hypertension.
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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) | 0.001 | 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".