β‐Catenin in the kidney stroma modulates pathways and genes to regulate kidney development
Bibliographic record
Abstract
BACKGROUND: Kidney development is regulated by cellular interactions between the ureteric epithelium, mesenchyme, and stroma. Previous studies demonstrate essential roles for stromal β-catenin in kidney development. However, how stromal β-catenin regulates kidney development is not known. We hypothesize that stromal β-catenin modulates pathways and genes that facilitate communications with neighboring cell populations to regulate kidney development. RESULTS: We isolated purified stromal cells with wild type, deficient, and overexpressed β-catenin by fluorescence-activated cell sorting and conducted RNA Sequencing. A Gene Ontology network analysis demonstrated that stromal β-catenin modulates key kidney developmental processes, including branching morphogenesis, nephrogenesis and vascular formation. Specific stromal β-catenin candidate target genes that may mediate these effects included secreted, cell-surface and transcriptional factors that regulate branching morphogenesis and nephrogenesis (Wnts, Bmp, Fgfr, Tcf/Lef) and secreted vascular guidance cues (Angpt1, VEGF, Sema3a). We validated established β-catenin targets including Lef1 and novel candidate β-catenin targets including Sema3e which have unknown roles in kidney development. CONCLUSIONS: These studies advance our understanding of gene and biological pathway dysregulation in the context of stromal β-catenin misexpression during kidney development. Our findings suggest that during normal kidney development, stromal β-catenin may regulate secreted and cell-surface proteins to communicate with adjacent cell populations.
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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) | 0.001 | 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".