<i>HLF</i> expression defines the human hematopoietic stem cell state
Bibliographic record
Abstract
Hematopoietic stem cells (HSCs) sustain blood cell homeostasis throughout life and can regenerate all blood lineages after transplantation. Despite this clear functional definition, highly enriched isolation of human HSCs can currently only be achieved through combinatorial assessment of multiple surface antigens. Although several transgenic HSC reporter mouse strains have been described, no analogous approach to prospectively isolate human HSCs has been reported. To identify genes with the most selective expression in human HSCs, we profiled population and single-cell transcriptomes of unexpanded and ex vivo cultured cord blood-derived hematopoietic stem and progenitor cells as well as peripheral blood, adult bone marrow, and fetal liver. On the basis of these analyses, we propose the master transcription factor HLF (hepatic leukemia factor) as one of the most specific HSC marker genes. To directly track its expression in human hematopoietic cells, we developed a genomic HLF reporter strategy, capable of selectively labeling the most immature blood cells on the basis of a single engineered parameter. Most importantly, HLF-expressing cells comprise all stem cell activity in culture and in vivo during serial transplantation. Taken together, these results experimentally establish HLF as a defining gene of the human HSC state and outline a new approach to continuously mark these cells with high fidelity.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".