Endothelin A receptor antagonist attenuated renal iron accumulation in iron overload heme oxygenase-1 knockout mice
Bibliographic record
Abstract
Progressive iron accumulation and renal impairment are prominent in both patients and mouse models of sickle cell disease (SCD). Endothelin A receptor (ETA) antagonism prevents this iron accumulation phenotype and reduces renal iron deposition in the proximal tubules of SCD mice. To better understand the mechanisms of iron metabolism in the kidney and the role of the ETA receptor in iron chelation and transport, we studied renal iron handling in a nonsickle cell iron overload model, heme oxygenase-1 ( Hmox-1−/−) knockout mice. We found that Hmox-1−/− mice had elevated plasma endothelin-1 (ET-1), cortical ET-1 mRNA expression, and renal iron content compared with Hmox-1+/+ controls. The ETA receptor antagonist, ambrisentan, attenuated renal iron deposition, without any changes to anemia status in Hmox-1−/− mice. This was accompanied by reduced urinary iron excretion. Finally, ambrisentan had an important iron recycling effect by increasing the expression of the cellular iron exporter, ferroportin-1 (FPN-1), and circulating total iron levels in Hmox-1−/− mice. These findings suggest that the ET-1/ETA signaling pathway contributes to renal iron trafficking in a murine model of iron overload.
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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) | 0.003 | 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".