A Soluble Granulocyte Colony Stimulating Factor Decoy Receptor as a Novel Tool to Increase Hematopoietic Cell Homing and Reconstitution in Mice
Bibliographic record
Abstract
The relative ineffectiveness of hematopoietic stem cells in reaching the bone marrow upon transplantation combined with the limited number of these cells available is a major reason for graft failure and delayed hematopoietic recovery. Hence, the development of strategies that could enhance homing is of high interest. Here, we provide evidence that homing is severely impaired postexposure to ionizing radiation (IR) in mice, an effect we found was time dependent and could be partially rescued using mesenchymal stromal cell (MSC) therapy. In an attempt to further increase homing, we took advantage of our observation that the granulocyte colony stimulating factor (G-CSF), a cytokine known to induce cell mobilization, is increased in the marrow of mice shortly after their exposure to IR. As such, we developed a truncated, yet functional, soluble G-CSF receptor (solG-CSFR), which we hypothesized could act as a decoy and foster homing. Using MSCs or conditioned media as delivery vehicles, we show that an engineered solG-CSFR has the potential to increase homing and hematopoietic reconstitution in mice. Altogether, our results provide novel findings at the interplay of IR and stromal cell therapy and present the regulation of endogenous G-CSF as an innovative proof-of-concept strategy to manipulate hematopoietic cell homing.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".