Genetic diversity of hepatitis B virus genotypes B6, D and F among circumpolar indigenous individuals
Bibliographic record
Abstract
Hepatitis B virus (HBV) infection is highly prevalent in circumpolar indigenous peoples. However, the clinical outcome is extremely variable, such that while hepatocellular carcinoma (HCC) is uncommon in Canadian Inuit, the incidence of HCC is slightly higher in Greenlanders than in Danes, and it is especially high in Alaskan Native people infected with HBV genotypes F (HBV/F) and C (HBV/C). These differences may be associated with the genomic variability of the predominant HBV genotype in each group. The purpose of this study was to determine the rate, nature and regional susceptibility of HBV genomic mutations among circumpolar indigenous individuals. Paired serum samples, separated by 5-6 years, were analysed from Canadian and Greenlandic Inuit infected with HBV genotype B6 (HBV/B6) and HBV/D, respectively, and from Alaskan Native people infected with HBV/F, each having subsequently developed HCC. Phylogenetic and mutational analyses were performed on full-genome sequences, and the dynamic evolution within the quasispecies population of each patient group was determined by clonal analysis of the non-overlapping core coding region. Mutations associated with severe outcomes predominated in HBV/F, mostly within the precore/core and PreS1 region. HBV/B6 genomes exhibited higher diversity compared to HBV/D and HBV/F, particularly within the core coding region. Thus, differing mutational profiles and genetic variability were observed among different HBV genotypes predominating in circumpolar indigenous patients. The unusual observation of persistently high genetic variability with HBV/B6 despite clinical inactivity could be due to the evolution of a host-pathogen balance, but other possible factors also need to be explored.
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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 | 0.000 | 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".