Novel Brn3a <i>cis</i>‐acting sequences mediate transcription of human trkA in neurons
Bibliographic record
Abstract
TrkA, the receptor tropomyosin-related kinase for nerve growth factor, is critical not only for the correct spatial and temporal development of sensory neurons during embryogenesis but also for the survival of sensory neurons, the differentiation and apoptosis of neuronal tumors and suppression of latent herpes simplex virus genomes. While the regulation of the expression of trkA is a complex process, the transcription factor Brn3a is known to play an important role as an enhancer of trkA transcription during development in the mouse. Despite considerable information on the regulation of trkA during embryogenesis, the mechanisms by which the expression of trkA is regulated in differentiated neurons, or the factors that influence its expression in tumor cells, have not been identified. We initiated studies to determine whether Brn3a/trkA promoter interactions may be important in a model of differentiated neurons and in medulloblastoma cells. We constructed a plasmid that contains 1043 base pairs of genomic sequences that extend to 30 nucleotides upstream of trkA coding region. In contrast to previous data, a short 190 bp region that lies proximal to the trkA initiation codon was sufficient for Brn3a responsiveness in Vero cells. This region was also sufficient for Brn3a trans-activation in nerve growth factor-differentiated PC12 cells. At least two portions of the 190 bp fragment bind to Brn3a with an affinity high enough to be detected in electromobility shift assays. In addition, Brn3a increased levels of endogenous trkA transcripts in PC12 cells and initiated trkA expression in medulloblastoma cells, which normally do not express trkA.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".