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Record W2512485303 · doi:10.3923/pjbs.2016.306.311

Oncogenic Human Papillomavirus Infection and GenotypeCharacterization among Women in Orodara, Western BurkinaFaso

2016· article· en· W2512485303 on OpenAlexaff
Ina Marie Angèle Traore, Théodora Mahoukèdè Zohoncon, O. Ndo, Florencia Wendkuuni Djigma, D. Obiri-Yebo, T.R. Compaore, Sindimalgdé Patricia Guigma, Albert Théophane Yonli, Germain Traore, Paul Ouédraogo, Charlemagne Ouédraogo, Yves Traoré, Jacques Simporè

Bibliographic record

VenuePakistan Journal of Biological Sciences · 2016
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsSt. Thomas University
Fundersnot available
KeywordsHuman papillomavirusGenotypeCervical cancerMedicineHPV infectionGynecologyPopulationCarriageVirologyOncologyCancerInternal medicineBiologyEnvironmental healthGeneticsPathologyGene

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVE: Cervical cancer usually occurs several years after persistent infection with oncogenic or high-risk human papillomavirus. The objective of this study was to determine carriage of 14 genotypes of high-risk human papillomavirus among women at Orodara and then characterize the genotypes found in these women. MATERIALS AND METHODS: From June to July 2015, 120 women from the general population were recruited in the health district of Orodara. They voluntarily agreed to participate in the study. Endocervical samples were taken from these women prior to screening for precancerous lesions by visual inspection with acetic acid and lugol's iodine. Identification of high-risk human papillomavirus genotype was done using real-time PCR. RESULTS: High-risk human papillomavirus prevalence was 38.3% and the most common genotypes were HPV 52 (25.4%), HPV 33 (20.6%) and HPV 59 (11.1%). The HPV 66 was also identified with a prevalence of 9.5%. CONCLUSION: The HPV 16 and HPV 18 which are frequently associated with cancer worldwide were not found among the most frequent oncogenic HPV in women in Orodara.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.109
Threshold uncertainty score0.881

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.061
GPT teacher head0.381
Teacher spread0.320 · 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 teacher head, 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".

Quick stats

Citations18
Published2016
Admission routes1
Has abstractyes

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