Peroxiredoxin 1 aggravates acute kidney injury by promoting inflammation through Mincle/Syk/NF-κB signaling
Bibliographic record
Abstract
Damage-associated molecular patterns (DAMPs) are a cause of acute kidney injury (AKI). Our knowledge of these DAMPs remains incomplete. Here, we report serum peroxiredoxin 1 (Prdx1) as a novel DAMP for AKI. Lipopolysaccharide (LPS) and kidney ischemia/reperfusion injury instigated AKI with concurrent increases in serum Prdx1 and reductions of Prdx1 expression in kidney tubular epithelial cells. Genetic knockout of Prdx1 or use of a Prdx1–neutralizing antibody protected mice from AKI and this protection was impaired by introduction of recombinant Prdx1 (rPrdx1). Mechanistically, lipopolysaccharide increased serum and kidney proinflammatory cytokines, macrophage infiltration, and the content of M1 macrophages. All these events were suppressed in Prdx1 -/- mice and renewed upon introduction of rPrdx1. In primary peritoneal macrophages, rPrdx1 induced M1 polarization, activated macrophage-inducible C-type lectin (Mincle) signaling, and enhanced proinflammatory cytokine production. Prdx1 interacted with Mincle to initiate acute kidney inflammation. Of note, rPrdx1 upregulated Mincle and the spleen tyrosine kinase Syk system in the primary peritoneal macrophages, while knockdown of Mincle abolished the increase in activated Syk. Additionally, rPrdx1 treatment enhanced the downstream events of Syk, including transcription factor NF-κB signaling pathways. Furthermore, serum Prdx1 was found to be increased in patients with AKI; the increase of which was associated with kidney function decline and inflammatory biomarkers in patient serum. Thus, kidney-derived serum Prdx1 contributes to AKI at least in part by activating Mincle signaling and downstream pathways.
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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 | 0.001 |
| 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".