Overexpression of the Runx3 Transcription Factor Increases the Proportion of Mature Thymocytes of the CD8 Single-Positive Lineage
Bibliographic record
Abstract
The Runx family of transcription factors is thought to regulate the differentiation of thymocytes. Runx3 protein is detected mainly in the CD4(-)8(+) subset of T lymphocytes. In the thymus of Runx3-deficient mice, CD4 expression is de-repressed and CD4(-)8(+) thymocytes do not develop. This clearly implicates Runx3 in CD4 silencing, but does not necessarily prove its role in the differentiation of CD4(-)8(+) thymocytes per se. In the present study, we created transgenic mice that overexpress Runx3 and analyzed the development of thymocytes in these animals. In the Runx3-transgenic thymus, the number of CD4(-)8(+) cells was greatly increased, whereas the numbers of CD4(+)8(+) and CD4(+)8(-) cells were reduced. The CD4(-)8(+) transgenic thymocytes contained mature cells with a TCR(high)HSA(low) phenotype. These cells were released from the thymus and contributed to the elevated level of CD4(-)8(+) cells relative to CD4(+)8(-) cells in the spleen. Runx3 overexpression also increased the number of mature CD4(-)8(+) thymocytes in mice with class II-restricted, transgenic TCR and in mice with a class I-deficient background, both of which are favorable for CD4(+)8(-) lineage selection. Thus, Runx3 can drive thymocytes to select the CD4(-)8(+) lineage. This activity is likely to be due to more than a simple silencing of CD4 gene expression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".