Characterization of a hepatitis C virus genotype 1 divergent isolate from an HIV-1 coinfected individual in Germany assigned to a new subtype 1o
Bibliographic record
Abstract
HCV exhibits a high genetic diversity and is classified into 7 genotypes which are further divided into 86 confirmed subtypes. However, there are multiple isolates with unassigned subtypes. We aimed to amplify and characterize the full-length genome sequence of an HCV genotype 1 (HCV-1) divergent isolate (DE/17–0414) in Germany. The HCV infection was detected in an HIV-1-positive German female within an HCV/HIV-coinfection study using a commercially available antigen-antibody HCV ELISA kit and confirmed by an in-house quantitative real-time RT-PCR assay. Preliminary genotyping was done by sequencing and phylogenetic analysis on partial NS5B region. The full-length genome sequence was determined by consensus RT-PCR assays. Resistance-associated substitutions (RASs) were analyzed using the web-based tool Geno2pheno [HCV] . Partial NS5B region of the isolate DE/17–0414 showed more than 95% identity to 73–08460349-1 l and HCV_Fr_003 from France and QC316 from Canada. Full-length genome analysis of the DE/17–0414 strain showed 91.8% identity to QC316 but less than 79.6% to other HCV-1 strains. Phylogenetic analyses demonstrated that DE/17–0414, 73–08460349-1 l, HCV_Fr_003, and QC316 formed a separate subcluster within HCV-1. DE/17–0414 had a distinct 3 amino acids insertion at the N-terminal of hypervariable region 1 (HVR1) within viral envelope glycoprotein 2 (E2) and several potential antiviral RASs among the NS3 and NS5A genes. We identified and analyzed an HCV-1 divergent isolate derived from an HIV-1 coinfected individual in Germany, which will be assigned to a new HCV-subtype 1o. Our understanding of the origin and transmission dynamics of this new subtype 1o requires further assessments from patients worldwide.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".