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Find video protocols related to scientific articles indexed in Pubmed.
Human papillomavirus DNA prevalence and type distribution in anal carcinomas worldwide.
Int. J. Cancer
PUBLISHED: 04-25-2014
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Knowledge about human papillomaviruses (HPV) types involved in anal cancers in some world regions is scanty. Here, we describe the HPV DNA prevalence and type distribution in a series of invasive anal cancers and anal intraepithelial neoplasias (AIN) grades 2/3 from 24 countries. We analyzed 43 AIN 2/3 cases and 496 anal cancers diagnosed from 1986 to 2011. After histopathological evaluation of formalin-fixed paraffin-embedded samples, HPV DNA detection and genotyping was performed using SPF-10/DEIA/LiPA25 system (version 1). A subset of 116 cancers was further tested for p16(INK4a) expression, a cellular surrogate marker for HPV-associated transformation. Prevalence ratios were estimated using multivariate Poisson regression with robust variance in the anal cancer data set. HPV DNA was detected in 88.3% of anal cancers (95% confidence interval [CI]: 85.1-91.0%) and in 95.3% of AIN 2/3 (95% CI: 84.2-99.4%). Among cancers, the highest prevalence was observed in warty-basaloid subtype of squamous cell carcinomas, in younger patients and in North American geographical region. There were no statistically significant differences in prevalence by gender. HPV16 was the most frequent HPV type detected in both cancers (80.7%) and AIN 2/3 lesions (75.4%). HPV18 was the second most common type in invasive cancers (3.6%). p16(INK4a) overexpression was found in 95% of HPV DNA-positive anal cancers. In view of the results of HPV DNA and high proportion of p16(INK4a) overexpression, infection by HPV is most likely to be a necessary cause for anal cancers in both men and women. The large contribution of HPV16 reinforces the potential impact of HPV vaccines in the prevention of these lesions.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.