Lentivector-mediated clonal tracking reveals intrinsic heterogeneity in the human hematopoietic stem cell compartment and culture-induced stem cell impairment
Bibliographic record
Abstract
Knowledge of the composition and interrelationship of the various hematopoietic stem cells (HSCs) that comprise the human HSC pool and the consequence of culture on each class is required for effective therapies based on stem cells. Clonal tracking of retrovirally transduced HSCs in nonobese diabetic/severe combined immunodeficient (NOD/SCID) mice revealed heterogeneity in the repopulation capacity of SCID-repopulating cells (SRCs). However, it is impossible to establish whether HSC heterogeneity is intrinsic or whether the culture conditions required for retroviral transduction induce qualitative and quantitative alterations to SRCs. Here, we report establishment of a clonal tracking method that uses lentivectors to transduce HSCs with minimal manipulation during overnight culture without cytokine stimulation. By serial bone marrow (BM) sampling of mice receiving transplants, short-term SRCs (ST-SRCs) and long-term SRCs (LT-SRCs) were identified on the basis of repopulation dynamics demonstrating that their existence is not an experimental artifact but reflects the state of the HSC pool. However, 4 days of culture in conditions previously used for SRC retroviral transduction significantly reduced SRC number as assessed by clonal analysis. These studies provide a foundation to understand the molecular and cellular determinants of human HSC development and to develop therapies targeted to specific HSC classes.
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 | 0.000 |
| 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".