Bayesian context trees: Modelling and exact inference for discrete time series

We develop a new Bayesian modelling framework for the class of higher-order, variable-memory Markov chains, and introduce an associated collection of methodological tools for exact inference with discrete time series. We show that a version of the context tree weighting algorithm can compute the prior predictive likelihood exactly (averaged over both models and parameters), and two related algorithms are introduced, which identify the a posteriori most likely models and compute their exact posterior probabilities. All three algorithms are deterministic and have linear-time complexity. A family of variable-dimension Markov chain Monte Carlo samplers is also provided, facilitating further exploration of the posterior. The performance of the proposed methods in model selection, Markov order estimation and prediction is illustrated through simulation experiments and real-world applications with data from finance, genetics, neuroscience, and animal communication. The associated algorithms are implemented in the R package BCT

Revisiting Context-Tree Weighting for Bayesian Inference

We revisit the statistical foundation of the celebrated context tree weighting (CTW) algorithm, and we develop a Bayesian modelling framework for the class of higher-order, variable-memory Markov chains, along with an associated collection of methodological tools for exact inference for discrete time series. In addition to deterministic algorithms that learn the a posteriori most likely models and compute their posterior probabilities, we introduce a family of variable-dimension Markov chain Monte Carlo samplers, facilitating further exploration of the posterior. The performance of the proposed methods in model selection, Markov order estimation and prediction is illustrated through simulation experiments and real-world applications

Human Papilloma Virus infection in sexually active adolescent girls

Purpose: Adolescents are a vulnerable group with regard to sexually transmitted infections, including Human Papilloma Virus (HPV). This is thought to be both because of their more liberal sexual behavior and also the relative immaturity of their genital tract. The aim of the study was to examine trends in HPV infection among sexually active adolescents attending for a sexual health screen. Methods: Sexually active adolescents were offered cervical screening, HPV typing and conventional genital cultures as part of a sexual health prevention protocol. Participating adolescents also completed a sexual health questionnaire. Results: Between January 2008 and July 2011, 149 sexually active girls were examined for reproductive health issues (mean age 17.3 years). 62 (42%) tested positive for HPV DNA, 30 were infected by multiple types and 54 had at least one high risk type identified. The most commonly identified HPV DNA was for low risk type 42 (15 cases, 7.8%), followed by high risk types 51 (14 cases, 7.3%) and 59 (11 cases, 5.7%). E6-E7 mRNA expression was detected in 16 girls (11%), of which half were for HPV 16. Girls who tested positive for HPV DNA and mRNA had similar age at sexual debut with those that tested negative (15.1 years in all groups) but had on average more sexual partners (4.1 vs1.9 p = 0.007). Only 9 girls in this cohort had been vaccinated against HPV. Approximately half of the girls reported using inadequate or no contraception. Conclusions: HPV infection rate was high in our sample. Furthermore a high percentage was infected with high risk types and a proportion of girls demonstrated mRNA HPV expression. As age at first sexual intercourse drops, vaccination against HPV and sexual education should be instituted in early adolescence, in order to reduce long term reproductive sequelae of unsafe sexual practices. © 2012 Elsevier Inc. All rights reserved

Bayesian Context Trees: Modelling and exact inference for discrete time series

We develop a new Bayesian modelling framework for the class of higher-order, variable-memory Markov chains, and introduce an associated collection of methodological tools for exact inference with discrete time series. We show that a version of the context tree weighting algorithm can compute the prior predictive likelihood exactly (averaged over both models and parameters), and two related algorithms are introduced, which identify the a posteriori most likely models and compute their exact posterior probabilities. All three algorithms are deterministic and have linear-time complexity. A family of variable-dimension Markov chain Monte Carlo samplers is also provided, facilitating further exploration of the posterior. The performance of the proposed methods in model selection, Markov order estimation and prediction is illustrated through simulation experiments and real-world applications with data from finance, genetics, neuroscience, and animal communication. The associated algorithms are implemented in the R package BCT

Oropharyngeal and laryngeal but not oral cancers are strongly associated with high-risk human papillomavirus in 172 Greek patients

A strong and consistent association has been reported between human papillomavirus (HPV) infection and oropharyngeal cancer, whereas a similar link has not yet been clarified in oral and laryngeal cancer. The purpose of this study was to investigate the association between HPV infection and head and neck squamous cell carcinoma (HNSCC) in Greek patients. Cytological or tissue specimens from 172 cases patients with HNSCC and cytological specimens from 91 control subjects were analyzed for HPV DNA detection and genotyping using a microarray-based assay. Multivariate logistic regression was used to estimate odds ratios (ORs) for the association between the presence of HPV infection and HNSCC for each of the tumor site, after adjustment for potential confounders. The adjusted ORs for positivity to high-risk HPV infection for oropharyngeal and laryngeal cancer were 20.3 (95% CI: 1.7–250.1) and 22.8 (95% CI: 2.5–206.2), respectively. High-risk HPV infection was not significantly associated with oral cancer. HPV infection was independently associated with poorly differentiated tumors (OR = 2.8; 95% CI: 1.1–7.5). Our results suggest a strong association of high-risk HPV infection with oropharyngeal and laryngeal cancer. J. Med. Virol. 89:170–176, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc

HPV infection and breast cancer : results of a microarray approach

Objectives: Human papilloma virus (HPV) has been implicated in several types of epithelial cancer. The role of HPV in breast carcinogenesis has been a matter of debate fueled by conflicting reports in recent years. The aim of this study is to identify the prevalence of breast and cervical HPV infection in cancer patients by using a modern microarray approach. Materials and methods: In the present prospective study, 201 breast cancer patients were included. For each patient a detailed medical history was taken and during the operation, under sterile conditions, samples were collected, from the tumour, the healthy adjacent breast tissue and any positive sentinel lymph nodes. In addition, for each patient a cervical sample was also collected. All samples were analysed for DNA of 24 types of HPV using a microarray technique. Results: Despite the high sensitivity of the technique used, no HPV DNA was identified in any of the breast or lymph node samples. Our analysis showed that patients with HPV positive cervical samples (28 cases) were more likely to have tumors with positive progesterone receptors (p=0.041) and were also more likely to have two or three positive lymph nodes (p=0.002). Conclusion: In the present study, a combination of careful sample collection and a very sensitive microarray approach showed no correlation between HPV and breast cancer. However some characteristics of the breast tumors were different among patients with HPV DNA in their cervical samples

HPV infection and breast cancer. Results of a microarray approach

Objectives: Human papilloma virus (HPV) has been implicated in several types of epithelial cancer. The role of HPV in breast carcinogenesis has been a matter of debate fueled by conflicting reports in recent years. The aim of this study is to identify the prevalence of breast and cervical HPV infection in cancer patients by using a modern microarray approach. Materials and methods: In the present prospective study, 201 breast cancer patients were included. For each patient a detailed medical history was taken and during the operation, under sterile conditions, samples were collected, from the tumour, the healthy adjacent breast tissue and any positive sentinel lymph nodes. In addition, for each patient a cervical sample was also collected. All samples were analysed for DNA of 24 types of HPV using a microarray technique. Results: Despite the high sensitivity of the technique used, no HPV DNA was identified in any of the breast or lymph node samples. Our analysis showed that patients with HPV positive cervical samples (28 cases) were more likely to have tumors with positive progesterone receptors (p=0.041) and were also more likely to have two or three positive lymph nodes (p=0.002). Conclusion: In the present study, a combination of careful sample collection and a very sensitive microarray approach showed no correlation between HPV and breast cancer. However some characteristics of the breast tumors were different among patients with HPV DNA in their cervical samples. © 2018 Elsevier Lt

Human papillomavirus genotyping and E6/E7 mRNA expression in Greek women with intraepithelial neoplasia and squamous cell carcinoma of the vagina and vulva

A large proportion of vaginal and vulvar squamous cell carcinomas (SCCs) and intraepithelial neoplasias (VAIN and VIN) are associated with HPV infection, mainly type 16. The purpose of this study was to identify HPV genotypes, as well as E6/E7 mRNA expression of high-risk HPVs (16, 18, 31, 33, and 45) in 56 histology samples of VAIN, VIN, vaginal, and vulvar SCCs. HPV was identified in 56 of VAIN and 50 of vaginal SCCs, 71.4 of VIN and 50 of vulvar SCCs. E6/E7 mRNA expression was found in one-third of VAIN and in all vaginal SCCs, 42.9 of VIN and 83.3 of vulvar SCCs. Our data indicated that HPV 16 was the commonest genotype identified in VAIN and VIN and the only genotype found in SCCs of the vagina and vulva. These findings may suggest, in accordance with other studies, that mRNA assay might be useful in triaging lesions with increased risk of progression to cancer. Copyright © 2012 Elpida Tsimplaki et al

Alteration of integrin expression in oral squamous cell carcinomas

OBJECTIVE: This study examines the intensity of expression of β1, α2, α3, α5, α6 integrin subunits in oral squamous cell carcinoma (SCC) as opposed to normal oral epithelium, and the intensity of expression and distribution pattern of the above subunits in relation to tumour differentiation grade. MATERIALS AND METHODS: Cryostat sections of 25 cases of oral SCC and 15 cases of normal oral epithelium were studied by immunohistochemistry (APAAP method). RESULTS: The intensity of expression of β1, α2 (Pearson χ2 P < 0.001) and α6 (Test for Trend P < 0.05) integrin subunits was reduced significantly in SCC compared to normal oral epithelium. All integrin subunits were mainly expressed in the peripheral cell layer of tumour islands. No correlation was found between the intensity of integrin expression and the degree of differentiation in SCC. The same applied to the distribution pattern of the integrin subunits. By means of cross examination of all integrins, the loss of intensity of α2β1 integrin expression was found to have the strongest correlation with oral SCC (Ordered Logistic Regression). CONCLUSIONS: Reduced intensity of expression of all subunits was found in oral SCC compared to normal epithelium. Further investigation is needed to determine whether α2β1 integrin expression can be used as a prognostic evaluator for the behaviour of the disease

Corrigendum to “HPV infection and breast cancer. Results of a microarray approach” [The Breast 40, (August 2018) 165–169](S0960977618301024)(10.1016/j.breast.2018.05.010)

The authors regret that Dr Theodoraki Kassiani was omit by error. The authors would like to apologise for any inconvenience caused. © 2018 Elsevier Lt