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Record W1991662727 · doi:10.1002/hep.22384

Hepatitis C virus in peripheral blood mononuclear cells of individuals with isolated anti‐hepatitis C virus antibody reactivity†

2008· letter· en· W1991662727 on OpenAlexaffabout
Tram N. Q. Pham, Tomasz I. Michalak

Bibliographic record

VenueHepatology · 2008
Typeletter
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPeripheral blood mononuclear cellHepatitis C virusVirologyRNABiologyAntibodyVirusReverse transcription polymerase chain reactionMolecular biologyReverse transcriptaseNested polymerase chain reactionRNA extractionTranscription (linguistics)ImmunologyPolymerase chain reactionMessenger RNAGeneIn vitroGenetics

Abstract

fetched live from OpenAlex

We were intrigued by the recent work by Bernardin and colleagues,1 who concluded that peripheral blood mononuclear cells (PBMCs) are unlikely to be a long-lived reservoir of hepatitis C virus (HCV) in individuals reactive for anti-HCV antibodies and negative for HCV RNA by transcription-mediated amplification assay (TMA) (sensitivity of 30 HCV RNA copies/mL; GenProbe Inc., San Diego, CA). Because this finding is in contrast with those previously reported by our and other groups,2-6 we want to briefly outline the most important methodological differences which might have led to this opposing conclusion. In the study by Bernardin et al.,1 HCV RNA was evaluated in cryopreserved, unstimulated PBMCs by so-called cell-associated TMA and reverse transcription–nested polymerase chain reaction (RT-nPCR) with sensitivities arguably between 2-50 and 15-150 virus copies/5 × 106 PBMCs, respectively. In our investigations, RT-nPCR followed by nucleic acid hybridization (NAH) analysis of amplicons (that is, Southern blotting), in order to validate specificity and enhance sensitivity of the signal detection by ≈10-fold over RT-nPCR, was applied.2, 7 This RT-nPCR/NAH method consistently detects <10 HCV RNA copies/mL or <5 copies/106 PBMCs, knowing that 1 × 106 PMBCs gives on average 1 μg RNA. Nonetheless, a more fundamental discrepancy concerns the amount of RNA used for analysis. In the work cited, RNA extracted with the RNeasy minikit (Qiagen, Valencia, CA) from an equivalent of, at most, 1.6 × 105 PBMCs (assuming, albeit unlikely, complete cell recovery after thawing and washing) was used for RT-nPCR. In contrast, we analyzed RNA from 1 × 106 to 2 × 106 of PBMCs that were unmanipulated after cryopreservation and extracted with Trizol (Invitrogen Life Technologies, Burlington, Canada), paying meticulous attention to the maximum recovery of high-quality RNA.2, 7 Furthermore, our experience indicates that RNA recovery after extraction with Trizol surpasses that with the RNeasy minikit by two-fold to three-fold. Therefore, the amount of template used for RT-nPCR by Bernardin and colleagues1 was 10-20 times lower than that in our studies, which also applied an overall more sensitive assay. Our investigations of several cohorts of individuals who were reactive to anti-HCV antibodies long after resolution of hepatitis C revealed HCV RNA positive strands in unstimulated PBMCs in ≈30% of cases at levels between 10 and 104 copies/107 cells.7 However, a brief culture of PBMCs with mitogens and cytokines that activated immune cells facilitated HCV RNA detection in as much as 75% of initially HCV-negative cases.7 Further, in up to 20% of cases, the HCV genome can be found in stimulated PBMCs but not in parallel serum. The simultaneous detection of an HCV RNA replicative strand, HCV protein, and unique HCV variants served to authenticate active virus replication in PBMCs, irrespective of serum HCV RNA status, as our recent study reassured.6 The above approach to HCV RNA identification was not employed by Bernardin and colleagues.1 Thus, as they alluded, it remains a distinct possibility that ex vivo stimulation of PBMCs might have augmented HCV detection in their study. Nevertheless, we recently demonstrated that replication of HCV can be confined to particular immune cell subsets, while total PBMCs appear nonreactive,6 suggesting that PBMC negativity does not necessarily exclude low-level HCV infection in this compartment. In summary, substantial differences in the methodology by which PBMCs and RNA were prepared, in the amount of template analyzed, and in the overall assay sensitivity are the most probable reasons behind the contradictory findings described by Bernardin et al.1 and others.2-6 As such, standardization of methods for HCV RNA detection in circulating immune cells based on the most sensitive approaches uncovered should be considered in future studies on this subject. Tram N.Q. Pham Ph.D.*, Tomasz I. Michalak M.D., Ph.D.*, * Molecular Virology and Hepatology Research Group, Faculty of Medicine, Health Science Center, Memorial University, St. John's, Canada.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.020
GPT teacher head0.288
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations9
Published2008
Admission routes2
Has abstractyes

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