Genetic Determinants of Coxsackievirus B3 Pathogenesis
Bibliographic record
Abstract
The development of high throughput genomic and bioinformatic analysis tools, coupled with established molecular techniques, has allowed new insights into the pathogenesis of infectious diseases. In humans, coxasackievirus B3 (CVB3) is the primary etiological agent of viral myocarditis, an inflammatory disease process involving the heart muscle. Early host cellular survival and apoptotic mechanisms during viral infections, as well as immune events, affect myocarditis progression and outcome. Therefore, our laboratory has been keenly interested in infectomics, defined here as the transcriptional events of both virus and host. We first elucidated up- or downregulated transcriptional activities in CVB3-infected hearts by mRNA differential display. Further characterization of these regulated genes including Nip21, IP10, and IGTPase, and study of their role in CVB3-infection are underway. In further dissection of the stages of myocarditis-peak viremia, inflammatory infiltration and tissue repair-we used cDNA microarrays to probe differential gene expression in the myocardium following virus infection. Following virus infection, there are global decreases in metabolic and mitochondrial genes, increases in signaling genes and distinctive patterns in other functional groups. To establish early gene expression profiles in infected cells by themselves, we also used oligonucleotide arrays in an in vitro model of CVB3 infection. Notably, we have found increased expression of transcription factors c-fos and c-jun down-stream of extracellular signal-related kinase, a pathway which is crucial for virus replication and pathogenesis. Our investigations based on gene profiling following CVB3 infection have thus far been fruitful in providing new experimental leads. High throughput genetic analysis has allowed us to simultaneously try on greater than 12,000 potential genetic "glass slippers." Our in vitro experimental plan has enabled us to chart prominent patterns of gene expression, analyzed by novel bioinformatic approaches, and to separate varied and potentially significant gene expression events.
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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) | 0.002 | 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".