Spatial Profiling of Nuclear Receptor Transcription Patterns over the Course of<i>Drosophila</i>Development
Bibliographic record
Abstract
Previous work has shown that many of the 18 family members of Drosophila nuclear receptor transcription factors function in a temporal hierarchy to coordinate developmental progression and growth with the rate limiting process of metabolism. To gain further insight into these interactions and processes, we have undertaken a whole-family analysis of nuclear receptor mRNA spatial expression patterns over the entire process of embryogenesis, as well as the 3rd instar wandering larva stage, by using high-resolution fluorescence in situ hybridization. Overall, the patterns of expression are remarkably consistent with previously mapped spatial activity profiles documented during the same time points, with similar hot spots and temporal profiles in endocrine and metabolically important tissues. Among the more remarkable of the findings is that the majority of mRNA expression patterns observed show striking subcellular distributions, indicating potentially critical roles in the control of protein synthesis and subsequent subcellular distributions. These patterns will serve as a useful reference for future studies on the tissue-specific roles and interactions of nuclear receptor proteins, partners, cofactors and ligands.
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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) | 0.000 | 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 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".