Calcium oxalate crystals induce renal inflammation by NLRP3-mediated IL-1β secretion
Bibliographic record
Abstract
Nephrocalcinosis, acute calcium oxalate (CaOx) nephropathy, and renal stone disease can lead to inflammation and subsequent renal failure, but the underlying pathological mechanisms remain elusive. Other crystallopathies, such as gout, atherosclerosis, and asbestosis, trigger inflammation and tissue remodeling by inducing IL-1β secretion, leading us to hypothesize that CaOx crystals may induce inflammation in a similar manner. In mice, intrarenal CaOx deposition induced tubular damage, cytokine expression, neutrophil recruitment, and renal failure. We found that CaOx crystals activated murine renal DCs to secrete IL-1β through a pathway that included NLRP3, ASC, and caspase-1. Despite a similar amount of crystal deposits, intrarenal inflammation, tubular damage, and renal dysfunction were abrogated in mice deficient in MyD88; NLRP3, ASC, and caspase-1; IL-1R; or IL-18. Nephropathy was attenuated by DC depletion, ATP depletion, or therapeutic IL-1 antagonism. These data demonstrated that CaOx crystals trigger IL-1β-dependent innate immunity via the NLRP3/ASC/caspase-1 axis in intrarenal mononuclear phagocytes and directly damage tubular cells, leading to the release of the NLRP3 agonist ATP. Furthermore, these results suggest that IL-1β blockade may prevent renal damage in nephrocalcinosis.
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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) | 0.001 | 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".