Adaptation to <i>ex vivo</i> culture drives human haematopoietic stem cell loss of repopulation capacity in a cell cycle independent manner
Bibliographic record
Abstract
Abstract Loss of long-term haematopoietic stem cell function (LT-HSC) hampers the success of ex vivo HSC gene therapy and expansion procedures, but the kinetics and the mechanisms by which this occurs remain incompletely characterized. Here through time-resolved scRNA-Seq, matched in vivo functional analysis and the use of a reversible in vitro system of early G 1 arrest, we define the sequence of transcriptional and functional events occurring during the first ex vivo division of human LT-HSCs. We demonstrate that contrary to current assumptions, loss of long-term repopulation capacity during culture is independent of cell cycle progression. Instead it is a rapid event that follows an early period of adaptation to culture, characterised by transient gene expression dynamics and constrained global variability in gene expression. Cell cycle progression however contributes to the establishment of differentiation programmes in culture. Our data have important implications for improving HSC gene therapy and expansion protocols.
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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) | 0.002 | 0.001 |
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".