Interleukin-18 Enhances Atherosclerosis in Apolipoprotein E <sup>−/−</sup> Mice Through Release of Interferon-γ
Why this work is in the frame
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Bibliographic record
Abstract
We have previously shown that interferon-gamma (IFN-gamma) is a potent enhancer of atherogenesis. Interleukin-18 (IL-18) promotes inflammatory responses through release of IFN-gamma, although it can also exert direct actions on other inflammatory mediators. In this present study, we determined the effects of IL-18 on atherogenesis and the role of IFN-gamma in this response. Male apolipoprotein E(-/-) mice (apoE(-/-); aged 16 weeks, n=10/group) were fed a normal diet and injected intraperitoneally for 30 days with either recombinant IL-18 (30 ng/g/day) or saline. Atherosclerotic lesion size was quantified in 2 vascular beds: the ascending aorta and the aortic arch. IL-18 administration did not affect serum cholesterol concentrations or lipoprotein-cholesterol distribution; however, exogenous IL-18 administration increased lesion size 2-fold in both the ascending aorta (50 642 +/- 12 515 versus 112 399 +/- 13 227 microm(2) P=0.004; saline versus IL-18 groups, respectively) and the aortic arch (3.1 +/- 0.3% versus 6.2 +/- 0.9% area, P=0.006). Exogenous IL-18 promoted a 4-fold increase in the number of lesion-associated T lymphocytes (11 +/- 3 versus 50 +/- 5 cells; P<0.0001) and cells expressing major histocompatability complex class II (9 +/- 3 versus 40 +/- 6 cells; P=0.0002). To determine the role of IFN-gamma production in this response, exogenous IL-18 was administered to apoE(-/-) mice that were IFN-gamma deficient. These studies demonstrated that lack of endogenous IFN-gamma ablated the effects of IL-18 on atherosclerosis. Therefore, these data strongly implicates IL-18 in the atherogenic process and suggests that IL-18 increases lesion development through enhancement of an inflammatory response involving an IFN-gamma-dependent mechanism. The full text of this article is available at http://www.circresaha.org.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it