The activating receptor <scp>NKG2D</scp> of natural killer cells promotes resistance against enterovirus‐mediated inflammatory cardiomyopathy
Bibliographic record
Abstract
In enterovirus-induced cardiomyopathy, information regarding the detailed impact of natural killer (NK) cells on the outcome of the disease is limited. We therefore hypothesized that NK cells and certain NK cell receptors determine the different outcome of coxsackievirus B3 (CVB3) myocarditis. Here, we demonstrate in murine models that resistance to chronic CVB3 myocarditis in immunocompetent C57BL/6 mice is characterized by significantly more mature CD11b(high) NK cells, the presence of NKG2D on NK cells, and enhanced NKG2D-dependent cytotoxicity compared to CVB3-susceptible A.BY/SnJ mice. The highly protective role of NKG2D in myocarditis was further proven by in vivo neutralization of NKG2D as well as in NKG2D-deficient mice but was shown to be independent of CD8(+) T-cell-dependent immunity. Moreover, the adoptive transfer of immunocompetent C57BL/6 NK cells pre- (day -1) as well as post-infectionem (day +2) displayed the potential to prevent permissive A.BY/SnJ mice from a progressive outcome of CVB3 myocarditis reflected by significantly improved cardiopathology and heart function. Altogether, our results provide firm evidence for a protective role of NKG2D-activated NK cells in CVB3 myocarditis leading to an effective virus clearance, thus offering novel therapeutic options in the treatment of virus-induced myocarditis.
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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 | 0.000 | 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".