Virome Sequencing in Patients With Myocarditis
Bibliographic record
Abstract
BACKGROUND: Polymerase chain reaction analyses of cardiac tissues have detected viral sequences in up to 67% of cases of myocarditis. However, viruses have not been implicated in giant cell myocarditis (GCM). Furthermore, efforts to detect viruses implicated in myocarditis have been unsuccessful in more accessible samples such as peripheral blood. METHODS: We used Virome Capture Sequencing for Vertbrate Viruses (VirCapSeq-VERT), a method that simultaneously screens for all known vertebrate viruses, to investigate viruses in 33 patients with myocarditis. We investigated peripheral blood mononuclear cells (n=24), plasma (n=27), endomyocardial biopsies (n=2), and cardiac tissue samples from explanted hearts (n=13). RESULTS: Nine patients (27%) had GCM and 4 patients (13%) had fulminant myocarditis. We found the following viruses in the blood of patients with myocarditis: Epstein Barr virus (n=11, 41%), human pegivirus (n=1, 4%), human endogenous retrovirus K (n=27, 100%), and anellovirus (n=15, 56%). All tissue samples from fulminant myocarditis (n=2) and GCM (n=13) contained human endogenous retrovirus K. CONCLUSIONS: No nucleic acids from viruses previously implicated in myocarditis or other human illnesses were detected in relevant amounts in cardiac tissue samples from GCM or in blood samples from other types of myocarditis. These findings do not exclude a role for viral infection in GCM but do suggest that if viruses are implicated, the mechanism is likely to be indirect rather than due to cytotoxic infection of myocardium.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".