NLRP3 Localizes to the Tubular Epithelium in Human Kidney and Correlates With Outcome in IgA Nephropathy
Bibliographic record
Abstract
Nod-like receptor pyrin domain-containing-3 (NLRP3) has been implicated in the pathogenesis of experimental renal injury, yet its characterization in human kidney disease remains largely unexplored. NLRP3 expression was evaluated in human kidney biopsies, primary renal tubular cells (HPTC) and correlated to disease outcomes in patients with IgA nephropathy (IgAN). NLRP3 localized to renal tubules in normal human kidney tissue and to mitochondria within HPTC by immunohistochemistry and immunofluorescence microscopy. Compared to control kidneys, NLRP3 gene expression was increased in biopsies of patients with IgAN. While NLRP3 expression in IgAN was detected in glomeruli, it remained largely confined to the tubular epithelial compartment. In vitro NLRP3 mRNA and protein expression were transiently induced in HPTC by TGF-β1 but subsequently diminished over time as cells lost their epithelial phenotype in a process regulated by transcription and ubiquitin-mediated degradation. Consistent with the in vitro data, low NLRP3 mRNA expression in kidney biopsies was associated with a linear trend of higher risk of composite endpoint of doubling serum creatinine and end stage renal disease in patients with IgAN. Taken together, these data show that NLRP3 is primarily a kidney tubule-expressed protein that decreases in abundance in progressive IgAN.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".