Changes in the cytokine regulation of stem cell self-renewal during ontogeny
Bibliographic record
Abstract
The last 10 years have seen the development of a quantitative assay that is specific for transplantable totipotent murine hematopoietic cells with durable in vivo blood-forming ability. Recently, this assay has been successfully adapted to allow the detection and enumeration of an analogous population of human hematopoietic stem cells using myelosuppressed immunodeficient (nonobese diabetic/severe-combined immunodeficiency) mice as recipients. Characterization of the cells detected by this assay indicates their close relationship in both mice and humans with cells detected in vitro as long-term culture-initiating cells (LTC-IC). Culture conditions have now been identified that support a significant net expansion of these cells from both species. More detailed analyses of the cytokine requirements for this response indicate that the viability, mitogenesis and maintenance of LTC-IC function by human CD34+ CD38- cells can be independently regulated by exogenous factors. Superimposed on this uncoupling of hematopoietic stem cell "self-renewal" and proliferation control is a change during ontogeny in the particular cytokines that regulate their responses. These findings unite stochastic and deterministic models of hematopoietic stem cell control through the concept of a molecular mechanism that actively blocks stem cell differentiation and must be maintained when these cells are stimulated to divide by exposure to certain types and concentrations of cytokines.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".