Analysis of HSC activity and compensatory Hox gene expression profile in Hoxb cluster mutant fetal liver cells
Bibliographic record
Abstract
Overexpression of Hoxb4 in bone marrow cells promotes expansion of hematopoietic stem cell (HSC) populations in vivo and in vitro, indicating that this homeoprotein can activate the genetic program that determines self-renewal. However, this function cannot be solely attributed to Hoxb4 because Hoxb4(-/-) mice are viable and have an apparently normal HSC number. Quantitative polymerase chain reaction analysis showed that Hoxb4(-/-) c-Kit+ fetal liver cells expressed moderately higher levels of several Hoxb cluster genes than control cells, raising the possibility that normal HSC activity in Hoxb4(-/-) mice is due to a compensatory up-regulation of other Hoxb genes. In this study, we investigated the competitive repopulation potential of HSCs lacking Hoxb4 alone, or in conjunction with 8 other Hoxb genes. Our results show that Hoxb4(-/-) and Hoxb1-b9 (-/-) fetal liver cells retain full competitive repopulation potential and the ability to regenerate all myeloid and lymphoid lineages. Quantitative Hox gene expression profiling in purified c-Kit+ Hoxb1-b9(-/-) fetal liver cells revealed an interaction between the Hoxa, b, and c clusters with variation in expression levels of Hoxa4,-a11, and -c4.Together, these studies show a complex network of genetic interactions between several Hox genes in primitive hematopoietic cells and demonstrate that HSCs lacking up to 30% of the active Hox genes remain fully competent.
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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 | 0.001 | 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) | 0.001 | 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".