Unique effects of Stat3 on the early phase of hematopoietic stem cell regeneration
Bibliographic record
Abstract
Self-renewal of hematopoietic stem cells (HSCs) is key to their reconstituting ability, but the signaling pathways that regulate this process remain poorly understood. Here we show that transduction of adult mouse bone marrow cells with a constitutively activated form of Stat3 (Stat3-C) increased their regenerative activity in lethally irradiated recipients. Conversely, transduction of these cells with a dominant-negative form of Stat3 suppressed their regenerative activity. Serial transplantation and clonal tracking of the HSC progeny regenerated in vivo from STAT3-C-transduced HSCs demonstrated that the major effect of forced expression of STAT3-C was to enhance HSC self-renewal during the initial phase of hematopoietic recovery. This acquired potential for enhanced self-renewal divisions then became latent, but was reactivated when the cells were transferred to new irradiated recipients. Increased levels of activated STAT3 were also found to be associated with greater preservation of primitive hematopoietic cells in short-term cultures. These results indicate a novel biphasic regulation of HSC self-renewal in vivo in which activated STAT3 promotes HSC self-renewal under stimulated, but not homeostatic, conditions. STAT3 may thus be an important regulator of hematopoietic regeneration and a novel target for HSC engineering.
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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 | 0.000 |
| 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".