Renal immune surveillance and dipeptidase-1 contribute to contrast-induced acute kidney injury
Bibliographic record
Abstract
Radiographic contrast agents cause acute kidney injury (AKI), yet the underlying pathogenesis is poorly understood. Nod-like receptor pyrin containing 3-deficient (Nlrp3-deficient) mice displayed reduced epithelial cell injury and inflammation in the kidney in a model of contrast-induced AKI (CI-AKI). Unexpectedly, contrast agents directly induced tubular epithelial cell death in vitro that was not dependent on Nlrp3. Rather, contrast agents activated the canonical Nlrp3 inflammasome in macrophages. Intravital microscopy revealed diatrizoate (DTA) uptake within minutes in perivascular CX3CR1+ resident phagocytes in the kidney. Following rapid filtration into the tubular luminal space, DTA was reabsorbed and concentrated in tubular epithelial cells via the brush border enzyme dipeptidase-1 in volume-depleted but not euvolemic mice. LysM-GFP+ macrophages recruited to the kidney interstitial space ingested contrast material transported from the urine via direct interactions with tubules. CI-AKI was dependent on resident renal phagocytes, IL-1, leukocyte recruitment, and dipeptidase-1. Levels of the inflammasome-related urinary biomarkers IL-18 and caspase-1 were increased immediately following contrast administration in patients undergoing coronary angiography, consistent with the acute renal effects observed in mice. Taken together, these data show that CI-AKI is a multistep process that involves immune surveillance by resident and infiltrating renal phagocytes, Nlrp3-dependent inflammation, and the tubular reabsorption of contrast via dipeptidase-1.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".