657. Epstein–Barr Virus Genetic Diversity in Blood vs. Saliva Samples From Patients with Infectious Mononucleosis
Bibliographic record
Abstract
The Epstein–Barr virus (EBV) is associated with several diseases, including infectious mononucleosis as well as malignant disorders. The relationship between strains of the virus and disease manifestation or illness severity is of interest. Such strains have been defined by genetic variations in the major viral genes. As a first step toward a better understanding of the relationship between strains and clinical outcomes, data are required on the patterns of genetic diversity of the virus in different populations. In this study, we examined the genetic diversity of the BZLF-1 gene, which is a major lytic gene of the virus. We sequenced the BZLF-1 gene of EBV following amplification from DNA that was extracted from blood and saliva from previously healthy Canadian children and young adults with infectious mononucleosis. Sequencing was done by Sanger methodology (dideoxy DNA sequencing) and the sequences were aligned with a reference strain of EBV using Geneious software. The variant burden and types of single nucleotide variants were compared in blood and saliva samples. Twenty-six samples were obtained from 24 patients less than 24 years of age (16 saliva and 10 blood samples). Two subjects provided paired blood and saliva samples at the same visit. Among 36 single nucleotide variations (SNVs), 22% were common to both blood and saliva samples. There was a nonstatistically significant trend for more SNVs among blood compared with saliva samples (median 6 and 1, ranges 0–8 and 0–9, respectively). Of the 3 exons of BZLF-1, exon 1 had the greatest frequency of SNVs compared with exons 2 and 3. Among the paired samples of blood and saliva, there were different genetic variants of the BZLF-1 gene in the blood compared with the saliva samples obtained from patients with infectious mononucleosis. Among patients with infectious mononucleosis, different genetic variants of EBV may be present in blood compared with saliva. Blood samples revealed viral strains with a tendency for more genetic diversity compared with saliva. The potential compartmentalization of strains is of relevance in sample selection for the evaluation of the potential clinical impact of the genetic diversity of EBV. In addition, the potential impact on disease pathogenesis is of interest. All authors: No reported disclosures.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".