From gene expression profiles to biological validation in enteroviral heart disease.
Bibliographic record
Abstract
In humans, coxsackievirus B3 is the primary etiological agent of viral myocarditis, an inflammatory disease process involving the heart muscle. Specific therapy is currently unavailable. Viral myocarditis is a complex, multiphasic infectious-inflammatory-reparative process. To address the temporal dimensionality of myocarditis, array- and nonarray-based molecular techniques, and histological and functional assays were used to help define enteroviral pathogenesis and its relation to heart failure. The application of high throughput genomic strategies and bioinformatics tools - coupled with established molecular techniques - have allowed us to perform a large-scale analysis of gene expression to better understand the host response to viral infection. Differential messenger RNA display, spotted complementary DNA arrays and Affymetrix Gene Chips (Affymetrix, United States) were used to study murine hearts during acute viremic, inflammatory and reparative stages. The observed global decreases in expression of metabolic and mitochondrial genes were focused on. The authors have previously characterized the role of mitochondria-triggered apoptosis, and pro- and anti-apoptotic Bcl-2 family proteins in enteroviral infections. The impact of altered mitochondrial transcripts on such host cell death and on metabolic injury to the heart is currently under study. In the authors' experience, the experimental progression from high throughput, unbiased analysis to biological validation has been only partially systematic. Insights are offered into the logic behind the selection of genes of potential interest for further investigation in the myocarditis model. A series of criteria for validatory decision-making, which the authors have developed based on their experiences, is described. Such criteria reflect known or putative gene function and expression patterns, as well as pragmatic considerations in the determination of steps toward investigation. This approach may help other investigators who need to dissect large genomic data sets to find targets for biological confirmation. Together, the authors' genomic studies have generated new, testable hypotheses regarding the interaction between host and enterovirus.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".