TIMP-3 recruits quiescent hematopoietic stem cells into active cell cycle and expands multipotent progenitor pool
Bibliographic record
Abstract
Regulating transition of hematopoietic stem cells (HSCs) between quiescent and cycling states is critical for maintaining homeostasis of blood cell production. The cycling states of HSCs are regulated by the extracellular factors such as cytokines and extracellular matrix; however, the molecular circuitry for such regulation remains elusive. Here we show that tissue inhibitor of metalloproteinase-3 (TIMP-3), an endogenous regulator of metalloproteinases, stimulates HSC proliferation by recruiting quiescent HSCs into the cell cycle. Myelosuppression induced TIMP-3 in the bone marrow before hematopoietic recovery. Interestingly, TIMP-3 enhanced proliferation of HSCs and promoted expansion of multipotent progenitors, which was achieved by stimulating cell-cycle entry of quiescent HSCs without compensating their long-term repopulating activity. Surprisingly, this effect did not require metalloproteinase inhibitory activity of TIMP-3 and was possibly mediated through a direct inhibition of angiopoietin-1 signaling, a critical mediator for HSC quiescence. Furthermore, bone marrow recovery from myelosuppression was accelerated by over-expression of TIMP-3, and in turn, impaired in TIMP-3-deficient animals. These results suggest that TIMP-3 may act as a molecular cue in response to myelosuppression for recruiting dormant HSCs into active cell cycle and may be clinically useful for facilitating hematopoietic recovery after chemotherapy or ex vivo expansion of HSCs.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".