Goat uromodulin promoter directs kidney-specific expression of GFP gene in transgenic mice
Bibliographic record
Abstract
BACKGROUND: Uromodulin is the most abundant protein found in the urine of mammals. In an effort to utilize the uromodulin promoter in order to target recombinant proteins in the urine of transgenic animals we have cloned a goat uromodulin gene promoter fragment (GUM promoter) and used it to drive expression of GFP in the kidney of transgenic mice. RESULTS: The GUM-GFP cassette was constructed and transgenic mice were generated in order to study the promoter's tissue specificity, the GFP kidney specific expression and its subcellular distribution. Tissues collected from three GUM-GFP transgenic mouse lines, and analyzed for the presence of GFP by Western blotting and fluorescence confirmed that the GUM promoter drove expression of GFP specifically in the kidney. More specifically, by using immuno-histochemistry analysis of kidney sections, we demonstrated that GFP expression was co-localized, with endogenous uromodulin protein, in the epithelial cells of the thick ascending limbs (TAL) of Henle's loop and the early distal convoluted tubule in the kidney. CONCLUSION: The goat uromodulin promoter is capable of driving recombinant protein expression in the kidney of transgenic mice. The goat promoter fragment cloned may be a useful tool in targeting proteins or oncogenes in the kidney of mammals.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".