A COMPARISON OF GENE EXPRESSION IN MURINE CARDIAC ALLOGRAFTS AND ISOGRAFTS BY MEANS DNA MICROARRAY ANALYSIS1
Bibliographic record
Abstract
BACKGROUND: Acute rejection of allografts remains a significant problem in clinical transplantation, and the fundamental mechanism underlying this rejection are as yet only poorly elucidated. Recently, DNA microarrays have come into use for the study of gene expression profiles, and we have taken advantage of this new technology to investigate acute rejection. We compared mRNA profiles in murine cardiac allografts with isografts using DNA microarrays with probe sets corresponding to more than 11,000 mice genes. METHODS: We screened for gene expression changes in murine cardiac allografts between fully incompatible mice strains (BALB/c H2d to C3H/He H2k) using a DNA microarray. The heart was heterotopically transplanted. Allografts (BALB/c to C3H/He) were removed on days 1, 3, and 5. As a control, isografts (C3H/He to C3H/He) harvested on days 1, 3, and 5 and native hearts of both strain mice (C3H/He and BALB/c) were obtained. RESULTS: On day 5, interferon-gamma (IFN-gamma) and many IFN-gamma-inducible genes were profoundly induced in the allograft relative to isograft. Monokine induced by IFN-gamma was most profoundly induced followed by inducibly expressed GTPase and Lmp-2. IFN-gamma was also profoundly induced. The induction was detectable from day 3. In contrast, genes regulated by other cytokines exhibited only modest changes. CONCLUSION: IFN-gamma-inducible genes are specifically up-regulated in murine cardiac allografts, suggesting that signaling mediated by IFN-gamma may play an important role in the late phase of acute rejection in vivo.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".