Transcriptional selectors, masters, and combinatorial codes: regulatory principles of neural subtype specification
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The broad range of tissue and cellular diversity of animals is generated to a large extent by the hierarchical deployment of sequence-specific transcription factors and co-factors (collectively referred to as TF's herein) during development. Our understanding of these developmental processes has been facilitated by the recognition that the activities of many TF's can be meaningfully described by a few functional categories that usefully convey a sense for how the TF's function, and also provides a sense for the regulatory organization of the developmental processes in which they participate. Here, we draw on examples from studies in Caenorhabditis elegans, Drosophila melanogaster, and vertebrates to discuss how the terms spatial selector, temporal selector, tissue/cell type selector, terminal selector and combinatorial code may be usefully applied to categorize the activities of TF's at critical steps of nervous system construction. While we believe that these functional categories are useful for understanding the organizational principles by which TF's direct nervous system construction, we however caution against the assumption that a TF's function can be solely or fully defined by any single functional category. Indeed, most TF's play diverse roles within different functional categories, and their roles can blur the lines we draw between these categories. Regardless, it is our belief that the concepts discussed here are helpful in clarifying the regulatory complexities of nervous system development, and hope they prove useful when interpreting mutant phenotypes, designing future experiments, and programming specific neuronal cell types for use in therapies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 it