Developing tTA Transgenic Rats for Inducible and Reversible Gene Expression
Bibliographic record
Abstract
To develop transgenic lines for conditional expression of desired genes in rats, we generated several lines of the transgenic rats carrying the tetracycline-controlled transactivator (tTA) gene. Using a vigorous, ubiquitous promoter to drive the tTA transgene, we obtained widespread expression of tTA in various tissues. Expression of tTA was sufficient to strongly activate its reporter gene, but was below the toxicity threshold. We examined the dynamics of Doxycycline (Dox)-regulated gene expression in transgenic rats. In the two transmittable lines, tTA-mediated activation of the reporter gene was fully subject to regulation by Dox. Dox dose-dependently suppressed tTA-activated gene expression. The washout time for the effects of Dox was dose-dependent. We tested a complex regime of Dox administration to determine the optimal effectiveness and washout duration. Dox was administered at a high dose (500 microg/ml in drinking water) for two days to reach the effective concentration, and then was given at a low dose (20 microg/ml) to maintain effectiveness. This regimen of Dox administration can achieve a quick switch between ON and OFF statuses of tTA-activated gene expression. In addition, administration of Dox to pregnant rats fully suppressed postnatal tTA-activated gene expression in their offspring. Sufficient levels of Dox are present in mother's milk to produce maximal efficacy in nursing neonates. Administration of Dox to pregnant or nursing rats can provide a continual suppression of tTA-dependent gene expression during embryonic and postnatal development. The tTA transgenic rat allows for inducible and reversible gene expression in the rat; this important tool will be valuable in the development of genetic rat models of human diseases.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".