Identification of Human Papillomavirus Type 58 Lineages and the Distribution Worldwide
Bibliographic record
Abstract
BACKGROUND: Human papillomavirus type 58 (HPV-58) accounts for a much higher proportion of cervical cancers in East Asia than other types. A classification system of HPV-58, which is essential for molecular epidemiological study, is lacking. METHODS AND RESULTS: This study analyzed the sequences of 401 isolates collected from 15 countries and cities. The 268 unique concatenated E6-E7-E2-E5-L1-LCR sequences that comprised 57% of the whole HPV-58 genome showed 4 distinct clusters. L1 and LCR produced tree topologies that best resembled the concatenated sequences and thus are the most appropriate surrogate regions for lineage classification. Moreover, short fragments from L1 (nucleotides 6014-6539) and LCR (nucleotides 7257-7429 and 7540-52) were found to contain sequence signatures informative for lineage identification. Lineage A was the most prevalent lineage across all regions. Lineage C was more frequent in Africa than elsewhere, whereas lineage D was more prevalent in Africa than in Asia. Among lineage A variants, sublineage A2 dominated in Africa, the Americas, and Europe, but not in Asia. Sublineage A1, which represents the prototype that originated from a patient with cancer, was rare worldwide except in Asia. CONCLUSIONS: HPV-58 can be classified into 4 lineages that show some degree of ethnogeographic predilection in distribution. The evolutionary, epidemiological, and pathological characteristics of these lineages warrant further study.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".