Stromally Expressed β-Catenin Modulates Wnt9b Signaling in the Ureteric Epithelium
Bibliographic record
Abstract
The mammalian kidney undergoes cell interactions between the epithelium and mesenchyme to form the essential filtration unit of the kidney, termed the nephron. A third cell type, the kidney stroma, is a population of fibroblasts located in the kidney capsule, cortex and medulla and is ideally located to affect kidney formation. We found β-catenin, a transcriptional co-activator, is strongly expressed in distinctive intracellular patterns in the capsular, cortical, and medullary renal stroma. We investigated β-catenin function in the renal stroma using a conditional knockout strategy that genetically deleted β-catenin specifically in the renal stroma cell lineage (β-cats-/-). β-cats-/- mutant mice demonstrate marked kidney abnormalities, and surprisingly we show β-catenin in the renal stroma is essential for regulating the condensing mesenchyme cell population. We show that the population of induced mesenchyme cells is significantly reduced in β-cats-/- mutants and exhibited decreased cell proliferation and a specific loss of Cited 1, while maintaining the expression of other essential nephron progenitor proteins. Wnt9b, the key signal for the induction of nephron progenitors, was markedly reduced in adjacent ureteric epithelial cells in β-cats-/-. Analysis of Wnt9b-dependent genes in the neighboring nephron progenitors was significantly reduced while Wnt9b-independent genes remained unchanged. In contrast mice overexpressing β-catenin exclusively in the renal stroma demonstrated massive increases in the condensing mesenchyme population and Wnt9b was markedly elevated. We propose that β-catenin in the renal stroma modulates a genetic program in ureteric epithelium that is required for the induction of nephron progenitors.
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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".