Transfusable neutrophil progenitors as cellular therapy for the prevention of invasive fungal infections
Bibliographic record
Abstract
The use of mature neutrophil (granulocyte) transfusions for the treatment of neutropenic patients with invasive fungal infections (IFIs) has been the focus of multiple clinical trials. Despite these efforts, the transfusion of mature neutrophils has resulted in limited clinical benefit, likely owing to problems of insufficient numbers and the very short lifespan of these donor cells. In this report, we employed a system of conditionally immortalized murine neutrophil progenitors that are capable of continuous expansion, allowing for the generation of unlimited numbers of homogenous granulocyte-macrophage progenitors (GMPs). These GMPs were assayed in vivo to demonstrate their effect on survival in 2 models of IFI: candidemia and pulmonary aspergillosis. Mature neutrophils derived from GMPs executed all cardinal functions of neutrophils. Transfused GMPs homed to the bone marrow and spleen, where they completed normal differentiation to mature neutrophils. These neutrophils were capable of homing and extravasation in response to inflammatory stimuli using a sterile peritoneal challenge model. Furthermore, conditionally immortalized GMP transfusions significantly improved survival in models of candidemia and pulmonary aspergillosis. These data confirm the therapeutic benefit of prophylactic GMP transfusions in the setting of neutropenia and encourage development of progenitor cellular therapies for the management of fungal disease in high-risk patients.
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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) | 0.000 | 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 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".