Bone marrow localization and functional properties of human hematopoietic stem cells
Bibliographic record
Abstract
PURPOSE OF REVIEW: Historically, studies of the hematopoietic stem cell (HSC) microenvironment in bone marrow have focused on the identification of individual supportive cell lineages likely to be responsible for maintaining HSCs in a self-renewing and regenerative state. More recently, awareness has developed regarding the broad and dynamic heterogeneity of nonhematopoietic cells that reside within the bone marrow space. We review recent insights that provide an emerging and complex context for understanding the spatially dependent regulation of HSC functional properties in the bone marrow and the collective inputs of multiple cell types. RECENT FINDINGS: Within the last 18 months, high-resolution imaging, xenograft modeling, and genetic mouse models have afforded innovative methods of detecting and interrogating HSCs with precision at the cellular level. Spatially distinct sites within the bone marrow house functionally divergent HSCs and progenitors, and these different habitats are becoming carefully characterized from a cellular and molecular perspective. This is critical toward understanding how bone marrow microenvironments adapt to accommodate cellular demands for hematopoiesis and how these mechanisms are disrupted in pathological conditions. SUMMARY: The bone marrow is not a continuum but an integrated unit with complex trophic interactions. Emphasis on human data will become necessary as these concepts mature and develop translationally toward changing clinical practices in HSC transplantation and even in the treatment of leukemias.
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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 | 0.001 |
| 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".