Mitogen-induced upregulation of hepatitis C virus expression in human lymphoid cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Considering growing evidence indicating that hepatitis C virus (HCV) replicates in lymphoid cells, establishment of a reliable and sensitive method for detection of HCV in these cells may provide means for monitoring the infection and the efficacy of sterilizing antiviral therapy. In this study, conditions for ex vivo augmentation and detection of the HCV genome in peripheral blood mononuclear cells (PBMCs) from patients with chronic hepatitis C (CHC) or after a sustained virological response (SVR) to antiviral treatment were assessed. Following stimulation with combinations of mitogens and/or cytokines, PBMCs and, in certain cases, affinity-purified T and B cells were examined for HCV positive- and negative-strand RNA by using RT-PCR followed by nucleic acid hybridization, while the presence of viral NS3 protein was determined by flow cytometry. HCV RNA augmentation was assessed by quantification of Southern and dot-blot hybridization signals. The results showed that treatment of peripheral lymphoid cells with mitogens stimulating T- and B-cell proliferation and with cytokines supporting their growth significantly increased HCV RNA detection in patients with both CHC and SVR. This enhancement was up to 100-fold for the HCV genome and fivefold for the NS3 protein compared with untreated cells. In conclusion, HCV RNA can be readily detected in circulating lymphoid cells in progressing hepatitis C and following SVR after ex vivo cell stimulation. As such, this method offers a new investigative tool to study HCV lymphotropism and to monitor virus presence during the course of HCV infection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 it