Use of IVIg to identify potential miRNA targets for allograft rejection and GvHD therapy
Bibliographic record
Abstract
Allograft rejection (AR) and graft-versus-host disease (GvHD) are serious complications following transplantation. Micro-RNAs (miRNAs) have recently been identified as key players in the regulation of these disorders. Because intravenous immunoglobulin (IVIg) has shown therapeutic potential for the prophylaxis and post-transplant reduction of AR and GvHD, we hypothesized that the effect of IVIg could result from the modulation of specific miRNA expression. To identify such miRNA, we performed mixed lymphocyte reactions (MLRs) as an in vitro model of AR and GvHD, with or without IVIg. We herein show that IVIg strongly inhibits the MLRs. This inhibition is associated with a modulation in the expression of miRNAs implicated in the regulation of pro-inflammatory cytokine (IL-2, IL-6, IFN-γ) and costimulatory molecule (CD80) expression. We propose that these identified miRNAs could represent potential therapeutic targets for the prevention and therapy of AR and 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".