The GDNF Target Vsnl1 Marks the Ureteric Tip
Bibliographic record
Abstract
Glial cell line-derived neurotrophic factor (GDNF) is indispensable for ureteric budding and branching. If applied exogenously, GDNF promotes ectopic ureteric buds from the Wolffian duct. Although several downstream effectors of GDNF are known, the identification of early response genes is incomplete. Here, microarray screening detected several GDNF-regulated genes in the Wolffian duct, including Visinin like 1 (Vsnl1), which encodes a neuronal calcium-sensor protein. We observed renal Vsnl1 expression exclusively in the ureteric epithelium, but not in Gdnf-null kidneys. In the tissue culture of Gdnf-deficient kidney primordium, exogenous GDNF and alternative bud inducers (FGF7 and follistatin) restored Vsnl1 expression. Hence, Vsnl1 characterizes the tip of the ureteric bud epithelium regardless of the inducer. In the tips, Vsnl1 showed a mosaic expression pattern that was mutually exclusive with β-catenin transcriptional activation. Vsnl1 was downregulated in both β-catenin-stabilized and β-catenin-deficient kidneys. Moreover, in a mouse collecting duct cell line, Vsnl1 compromised β-catenin stability, suggesting a counteracting relationship between Vsnl1 and β-catenin. In summary, Vsnl1 marks ureteric bud tips in embryonic kidneys, and its mosaic pattern demonstrates a heterogeneity of cell types that may be critical for normal ureteric branching.
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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".