Immune-Modifying Microparticles for Treatment of Acute Graft-Versus-Host-Disease
Bibliographic record
Abstract
Abstract Background Acute Graft versus host disease (aGVHD) is one of the most common complication of allogeneic hematopoietic stem cell transplant. We have previously shown that infused immune-modifying particles (IMPs) can reduce clinical symptoms and improve survival in inflammatory conditions. IMPs are taken up by inflammatory monocytes (θIM) via the macrophage receptor with collagenous structure (MARCO) and then undergo splenic sequestration. Given these findings, IMPs may be an effective method of reducing inflammation in aGVHD. Methods We tested the efficacy of IMP in an established aGVHD murine model. We also explored the changes in immune cell subsets and serum cytokines. To assess impact of IMP on graft-versus-tumor (GVT), we infused host mice with A20 lymphoma cells. Results We demonstrated that treatment with IMPs effectively rescues mice in a lethal aGVHD model. Treatment with IMPs also significantly improved clinical and target organ histopathological scores. IMP treatment resulted in increased splenic and intestinal CD4+CD25+Foxp3+ Tregs. IMP treated mice had lower numbers of colonic CD11b+Ly6chi θIM and a lower peak of serum inflammatory cytokines. Maintenance of GVT effect was demonstrated by comparable survival rates in host mice with co-infusion of A20 lymphoma cells. Conclusion Systemic IMP was effective at rescuing mice in this lethal aGVHD model. This demonstrates that targeting θIMs with IMPs could be an effective strategy to treat aGVHD. Further investigation of the mechanisms by which IMPs ameliorate aGVHD is warranted, as is investigation of the use of IMPs to treat aGVHD in the clinical setting. Supported by Nanoparticle Tolerance Research Fund
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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".