Graft-versus-host disease causes failure of donor hematopoiesis and lymphopoiesis in interferon-γ receptor-deficient hosts
Bibliographic record
Abstract
The immunopathologic condition known as graft-versus-host disease (GVHD) results from a type I T-cell process. However, a prototypical type I cytokine, interferon-gamma (IFN-gamma), can protect against several manifestations of GVHD in recipients of major histocompatibility complex (MHC)-mismatched hematopoietic cells. We transplanted hematopoietic cells from C3H.SW donors in wild-type (wt) and IFN-gamma-receptor-deficient (IFN-gammaRKO) MHC-matched C57BL/6 recipients. In IFN-gammaRKO recipients, host cells were unresponsive to IFN-gamma, whereas wt donor cells were exposed to exceptionally high levels of IFN-gamma. From an IFN-gamma perspective, we could therefore evaluate the impact of a loss-of-function on host cells and gain-of-function on donor cells. We found that lack of IFN-gammaR prevented up-regulation of MHC proteins on host cells but did not mitigate damage to most target organs. Two salient phenotypes in IFN-gammaRKO recipients involved donor cells: lymphoid hypoplasia and hematopoietic failure. Lymphopenia was due to FasL-induced apoptosis and decreased cell proliferation. Bone marrow aplasia resulted from a decreased proliferation of hematopoietic stem/progenitor cells that was associated with down-regulation of 2 genes negatively regulated by IFN-gamma: Ccnd1 and Myc. We conclude that IFN-gamma produced by alloreactive T cells may entail a severe graft-versus-graft reaction and could be responsible for cytopenias that are frequently observed in subjects with GVHD.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".