Targeting the RNA-Binding Protein QKI in Myeloid Cells Ameliorates Macrophage-Induced Renal Interstitial Fibrosis
Bibliographic record
Abstract
In the pathophysiologic setting of acute and chronic kidney injury, the excessive activation and recruitment of blood-borne monocytes prompts their differentiation into inflammatory macrophages, a process that leads to progressive glomerulosclerosis and interstitial fibrosis. Importantly, this differentiation of monocytes into macrophages requires the meticulous coordination of gene expression at both the transcriptional and post-transcriptional level. The transcriptomes of these cells are ultimately determined by RNA-binding proteins such as QUAKING (QKI), that define their pre-mRNA splicing and mRNA transcript patterns. Using two mouse models, namely (1) quaking viable mice (qkv) and (2) the conditional deletion in the myeloid cell lineage using the lysozyme 2-Cre (QKIFL/FL;LysM-Cre mice), we demonstrate that the abrogation of QKI expression in the myeloid cell lineage reduces macrophage infiltration following kidney injury induced by unilateral urethral obstruction (UUO). The qkv and QKIFL/FL;LysM-Cre mice both showed significant diminished interstitial collagen deposition and fibrosis in the UUO-damaged kidney, as compared to wild-type littermates. We show that macrophages isolated from QKIFL/FL;LysM-Cre mice are associated with defects in pre-mRNA splicing. Our findings demonstrate that reduced expression of the alternative splice regulator QKI in the cells of myeloid lineage attenuates renal interstitial fibrosis, suggesting that inhibition of this splice regulator may be of therapeutic value for certain kidney diseases.
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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 | 0.000 | 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 | 0.000 |
| 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".