Hematopoietic stem cell regeneration through paracrine regulation of the Wnt5a/Prox1 signaling axis
Bibliographic record
Abstract
The crosstalk between the BM microenvironment (niche) and hematopoietic stem cells (HSCs) is critical for HSC regeneration. Here, we show that in mice, deletion of the Fanconi anemia (FA) genes Fanca and Fancc dampened HSC regeneration through direct effects on HSCs and indirect effects on BM niche cells. FA HSCs showed persistent upregulation of the Wnt target Prox1 in response to total body irradiation (TBI). Accordingly, lineage-specific deletion of Prox1 improved long-term repopulation of the irradiated FA HSCs. Forced expression of Prox1 in WT HSCs mimicked the defective repopulation phenotype of FA HSCs. WT mice but not FA mice showed significant induction by TBI of BM stromal Wnt5a protein. Mechanistically, FA proteins regulated stromal Wnt5a expression, possibly through modulating the Wnt5a transcription activator Pax2. Wnt5a treatment of irradiated FA mice enhanced HSC regeneration. Conversely, Wnt5a neutralization inhibited HSC regeneration after TBI. Wnt5a secreted by LepR+CXCL12+ BM stromal cells inhibited β-catenin accumulation, thereby repressing Prox1 transcription in irradiated HSCs. The detrimental effect of deregulated Wnt5a/Prox1 signaling on HSC regeneration was also observed in patients with FA and aged mice. Irradiation induced upregulation of Prox1 in the HSCs of aged mice, and deletion of Prox1 in aged HSCs improved HSC regeneration. Treatment of aged mice with Wnt5a enhanced hematopoietic repopulation. Collectively, these findings identified the paracrine Wnt5a/Prox1 signaling axis as a regulator of HSC regeneration under conditions of injury and aging.
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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) | 0.001 | 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".