Loss of Dll4 expression in thymic epithelial cell monolayer culture is mediated by reduction in both burst size and burst frequency of its gene transcription
Bibliographic record
Abstract
Abstract Commitment of thymic seeding progenitor (TSP) cells to the T-lineage depends on Notch signaling, which requires engagement of the Notch1 receptor on TSPs by the Notch ligand Dll4 on thymic epithelial cells (TECs). We previously showed that when TECs are cultured as monolayers (2-D), Dll4 expression is rapidly lost, as is their ability to support T-cell development in vitro. In the present study, we aim to examine the regulation of Dll4 expression in TECs at the levels of gene transcription and mRNA degradation in TECs from E15 embryos using a combination of multiple techniques. The half-life of Dll4 mRNA in TECs was found, by utilizing quantitative PCR (qPCR) combined with Uridine RNA analog pulse-labeling, only approximately 30 min, which makes its level very sensitive to changes in the rates of gene transcription. Nonetheless, reduction in gene transcription, rather than in mRNA stability, was determined to be the primary molecular mechanism underlying the loss of Dll4 expression in 2-D TECs. FoxN1, the transcription factor that drives thymic epithelial cell development, was found to bind to multiple sites at the Dll4 gene promoter and an enhancer region within its third intron by luciferase reporter assay. Consistent with the luciferase reporter assay result, enforced expression of FoxN1 in 2-D TECs restored Dll4 expression significantly. Further detailed analysis with PrimeFlow RNA assay revealed that FoxN1 regulates only the burst size, but not the burst frequency, of Dll4 gene transcription. We are currently working on identifying the transcription regulator(s) that could bind to the enhancer region to regulate the burst frequency of Dll4 gene transcription.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".