Enhanced ERK-1/2 activation in mice susceptible to coxsackievirus-induced myocarditis
Bibliographic record
Abstract
Group B coxsackieviral (CVB) infection commonly causes viral myocarditis. Mice are protected from CVB3 myocarditis by gene-targeted knockout of p56(Lck)(Lck), the Src family kinase (Src) essential for T cell activation. Extracellular signal-regulated kinase 1 and 2 (ERK-1/2) can influence cell function downstream of Lck. Using T cell lines and neonatal cardiac myocytes we investigated the role of ERK-1/2 in CVB3 infection. In Jurkat T cells ERK-1/2 is rapidly activated by CVB3; but, this response is absent in Lck-negative JCaM T cells. Inhibition of ERK-1/2 with UO126 reduced CVB3 titers in Jurkat cells, but not in JCaM cells. In cardiac myocytes CVB3 activation of ERK-1/2 is blocked by the Src inhibitor PP2. In addition, viral production in myocytes is decreased by Src or ERK-1/2 inhibition. In vitro, in both immune and myocardial cells, ERK-1/2 is activated by CVB3 downstream of Lck and other Src's and is necessary for efficient CVB3 replication. In vivo, following CVB3 infection, ERK-1/2 activation is evident in the myocardium. ERK-1/2 activation is intense in the hearts of myocarditis-susceptible A/J mice. In contrast, significantly less ERK-1/2 activation is found in the hearts of myocarditis-resistant C57BL/6 mice. Therefore, the ERK-1/2 response to CVB3 infection may contribute to differential host susceptibility to viral 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 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".