Molecular determinants of WNT9b responsiveness in nephron progenitor cells
Bibliographic record
Abstract
Primed nephron progenitor cells (NPCs) appear in metanephric mesenchyme by E11.5 and differentiate in response to the inductive WNT9b signal from the ureteric bud. However, the NPC WNT-receptor complex is unknown. We obtained M15 cells from E10.5 mesonephric mesenchyme and systematically analyzed components required for canonical WNT9b-responsiveness. When M15 cells were transfected with a β-catenin luciferase reporter plasmid, exposure to recombinant WNT9b resulted in minimal luciferase activity. We then analyzed mRNA-expression of WNT-pathway components and identified Fzd1-6 and Lrp6 transcripts but not Rspo1. When M15 cells were treated with recombinant RSPO1 the response to transfected WNT9b was augmented 4.8-fold. Co-transfection of M15 cells with Fzd5 (but no other Fzd family member) further increased the WNT9b signal to 16.8-fold and siRNA knockdown of Fzd5 reduced the signal by 52%. Knockdown of Lrp6 resulted in 60% WNT9b signal reduction. We confirmed Fzd5, Lrp6 and Rspo1 mRNA expression in CITED1(+) NPCs from E15.5 embryonic mouse kidney. Thus, while many WNT signaling-pathway components are present by E10.5, optimum responsiveness of E11.5 cap mesenchyme requires that NPCs acquire RSPO1, FZD5 and LRP6.
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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) | 0.002 | 0.001 |
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".