Chloroquine prevention of murine MHC-disparate acute graft-versus-host disease correlates with inhibition of splenic response to CpG oligodeoxynucleotides and alterations in T-cell cytokine production
Bibliographic record
Abstract
The 4-aminoquinolines, chloroquine and hydroxychloroquine, are established, with a 52% response rate, as therapy for human steroid-refractory GVHD after BMT. Chloroquine affects numerous mechanisms that play a role in GVHD, including inhibition of major histocompatibility complex (MHC) class II antigen presentation, cytokine production, and antigen-presenting cell activation by bacterially derived CpG oligodeoxynucleotides (ODNs). Using an MHC-disparate murine model, we evaluated the effect of chloroquine treatment on the development of acute GVHD. We assessed the effect of chloroquine on the immunostimulatory responses induced by CpG ODNs after BMT. We also evaluated the impact of chloroquine on cytokine-producing populations known to affect GVHD, including CD4+ and CD8+ T-cell and CD3(+)/NK1.1(+) natural killer T-cell (NKT cell) populations. Twelve (86%) of 14 mice receiving phosphate-buffered saline solution (PBS) developed lethal GVHD; only 4 (29%) of 14 mice receiving chloroquine 20 mg/kg 3 times per week developed lethal GVHD (P < .01). Chloroquine significantly suppressed CpG ODN-induced splenic proliferation and interleukin 6 (IL-6) production associated with GVHD. Chloroquine suppressed CD8+ T-cell production of IL-2 and IL-4 associated with GVHD in this model and maintained an early expansion (day 7) of splenic NKT cells. These results indicate that the 4-aminoquinolines are effective in therapy for or prevention of acute GVHD secondary to MHC disparities. Chloroquine actions may include inhibition of CpG ODN augmentation of GVHD. Other mechanisms involved may include suppression of CD8+ T-cell production of IL-2 and IL-4 and an increase in NKT cells associated with GVHD inhibition by chloroquine.
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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 | 0.000 |
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".