Antagonistic expression of hepatitis C virus and alpha interferon in lymphoid cells during persistent occult infection
Bibliographic record
Abstract
Detection of residual HCV in individuals with SVR after treatment of CHC can be significantly heightened by analyzing ex vivo mitogen-activated T and B lymphocytes and applying sensitive nucleic acid amplification assays. However, it remained unknown if synergistic activation of lymphocytes and monocytes would further augment HCV detection, if viral replication becomes universally upregulated in treated cells, and if examining sequential sera and lymphoid cells would improve detection of occult infection. Using paired sera and lymphoid cells collected 1 year apart from 17 individuals with normal liver enzymes for up to 72 months after SVR, it was found that simultaneous activation of lymphocytes and monocytes enhanced identification of silent HCV infection and revealed that in some cases monocytes were the principal immune cell type where HCV persisted. Testing of serial samples further increased detection of occult infection. Ultimately, by combining the above two approaches, all individuals with SVR were found to be silent carriers of HCV. Clonal sequencing revealed HCV variations in sera and lymphoid cells and evolution of viral genomes confirming ongoing virus replication. Surprisingly, similar to those with CHC, naive lymphoid cells from some individuals carried approximately 10(3) HCV copies/microg total RNA. HCV loads in naive lymphoid cells predetermined the outcome of ex vivo stimulation with respect to upregulation or inhibition of HCV replication. HCV RNA levels in occult infection were inversely proportional to the expression of IFNalpha and IFN-inducible MxA, but not to IFNgamma or tumour necrosis factor alpha in naive and mitogen-treated lymphoid cells.
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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 | 0.000 | 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 | 0.000 |
| 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".