β-catenin/TCF/Lef controls a differentiation-associated transcriptional program in renal epithelial progenitors
Bibliographic record
Abstract
In the embryonic kidney, progenitors in the metanephric mesenchyme differentiate into specialized renal epithelia in a defined sequence characterized by the formation of cellular aggregates, conversion into polarized epithelia and segmentation along a proximal-distal axis. This sequence is reiterated throughout renal development to generate nephrons. Here, we identify global transcriptional programs associated with epithelial differentiation utilizing an organ culture model of rat metanephric mesenchymal differentiation, which recapitulates the hallmarks of epithelialization in vivo in a synchronized rather than reiterative fashion. We observe activation of multiple putative targets of beta-catenin/TCF/Lef-dependent transcription coinciding with epithelial differentiation. We show in cultured explants that isolated activation of beta-catenin signaling in epithelial progenitors induces, in a TCF/Lef-dependent manner, a subset of the transcripts associated with epithelialization, including Pax8, cyclin D1 (Ccnd1) and Emx2. This is associated with anti-apoptotic and proliferative effects in epithelial progenitors, whereas cells with impaired TCF/Lef-dependent transcription are progressively depleted from the epithelial lineage. In vivo, TCF/Lef-responsive genes comprise a conserved transcriptional program in differentiating renal epithelial progenitors and beta-catenin-containing transcriptional complexes directly bind to their promoter regions. Thus, beta-catenin/TCF/Lef-mediated transcriptional events control a subset of the differentiation-associated transcriptional program and thereby participate in maintenance, expansion and stage progression of the epithelial lineage.
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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 | 0.000 |
| 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 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".