A Live Zebrafish-Based Screening System for Human Nuclear Receptor Ligand and Cofactor Discovery
Bibliographic record
Abstract
Nuclear receptors (NRs) belong to a superfamily of transcription factors that regulate numerous homeostatic, metabolic and reproductive processes. Taken together with their modulation by small lipophilic molecules, they also represent an important and successful class of drug targets. Although many NRs have been targeted successfully, the majority have not, and one third are still orphans. Here we report the development of an in vivo GFP-based reporter system suitable for monitoring NR activities in all cells and tissues using live zebrafish (Danio rerio). The human NR fusion proteins used also contain a new affinity tag cassette allowing the purification of receptors with bound molecules from responsive tissues. We show that these constructs 1) respond as expected to endogenous zebrafish hormones and cofactors, 2) facilitate efficient receptor and cofactor purification, 3) respond robustly to NR hormones and drugs and 4) yield readily quantifiable signals. Transgenic lines representing the majority of human NRs have been established and are available for the investigation of tissue- and isoform-specific ligands and cofactors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".