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Record W1939480328 · doi:10.5430/jst.v5n2p112

HPV prophylactic vaccines: Second-generation or first-generation vaccines

2015· article· en· W1939480328 on OpenAlexvenueno aff
Kimia Kardani, Golnaz Mardani, Azam Bolhassani

Bibliographic record

VenueJournal of Solid Tumors · 2015
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsnot available
FundersIran National Science FoundationNational Science Foundation
KeywordsGardasilHPV vaccinesCapsidMedicineVirologyVirus-like particleGenital wartsVaccinationFirst generationHuman papillomavirusAntibodyCervical cancerImmunologyVirusHPV infectionCancerBiologyRecombinant DNAInternal medicinePopulationGene

Abstract

fetched live from OpenAlex

High-risk genotypes of human papillomavirus (HPV) are associated with genital cancers especially cervical cancer. United State Food and Drug Administration (USFDA) has recently licensed two first-generation prophylactic vaccines ( i.e. , Gardasil and Cervarix), for control of HPV 16 and 18 infections. Both vaccines are able to generate neutralizing antibodies against major capsid protein L1 assembled as virus-like particles (VLPs). To enhance protection against other HPV genotypes, second-generation vaccines are underway. A HPV L1-based nonavalent vaccine showed is potent and safe in prevention of precancerous lesions associated with HPV types 16/18/31/33/45/52/58, as well as anogenital warts associated with HPV types 6/11. This vaccine is in the advanced stage of phase III clinical trials. Other second-generation vaccines were based on L1-pentameric subunits and also the minor capsid protein L2 that have shown to be effective in preclinical studies. The L2 protein co-assembles with the L1 protein for VLP formation increasing virion aggregation. This mini-review describes two vaccination strategies including first-generation and second-generation vaccines against HPV infections.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0040.000

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 head0.103
GPT teacher head0.362
Teacher spread0.259 · 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.

Study designNot applicable
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

Citations1
Published2015
Admission routes1
Has abstractyes

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