BackgroundHigh risk human papillomavirus (HR-HPV) infection in males is a health issue with implications for HPV-related lesions in their partners. The identification of risk factors for male infection may improve our understanding of HR-HPV transmission and prevention. The aim of this study was to evaluate the relationships between lifestyle, genital warts and HR-HPV infection. The study was focused on men with an increased risk of HR-HPV infection: male sexual partners of women diagnosed with high-grade squamous intraepithelial cervical lesions.MethodsMen were enrolled and prospectively recruited within the first six months after diagnosis of cervical lesions in their female partners (n = 175, 2013–2016). Epidemiological and sexual behaviour data were obtained. The presence of genital warts was established by visual inspection. Detection and genotyping of HR-HPV infection in genital samples were performed with a Linear Array HPV Genotyping Test. All HR-HPV positive men were offered a follow-up exam at 12 months. SPSS version 19 was used for statistical analysis.Results and discussionThe prevalence of HR-HPV infection in men was 45.1% (79/175). Genital warts were observed in 10.3% (18/175) of the subjects. Detection of genital warts (OR 3.5, p = 0.015), smoking habits (OR 2.3, p = 0.006) and sexual debut before 16 years old (OR 2, p = 0.035) were associated with an increased risk for HR-HPV infection (univariate analysis). This association was also observed for genital warts and smoking status in a multivariate analysis. The same genotype was found after one year in 71.4% (20/28) of subjects.ConclusionsThe presence of genital warts and smoking habits seem to be associated with a higher risk of HR-HPV infection in males. Earlier sexual debut may increase this risk. Extensive knowledge of the natural history of HR-HPV infection in males is an absolute requirement for the design and implementation of prevention strategies for the general population as well as for specific populations such as couples after treatment for high-grade cervical lesions.

Minute pulmonary meningothelial-like nodules (MPMNs) are usually unique lesions in the lung parenchyma. Diffuse pulmonary meningotheliomatosis, which is presented as multiple MPMNs, has been less frequently described. MPMNs are mainly asymptomatic and are diagnosed after lung surgery or during autopsy. We report on a patient with multiple and bilateral pulmonary nodules, some of which were cavitated, diagnosed with diffuse pulmonary meningotheliomatosis by transbronchial lung biopsy. Diffuse pulmonary meningotheliomatosis should be included in the differential diagnosis of bilateral lung nodules.

No abstract

Globally, over 80% of fisheries are at maximum sustainable levels or overexploited. However, small-scale fisheries (SSFs) in developing countries play a relevant role in coastal communities’ development with important impacts on the economy. The SSFs are normally multi-specific and due to the lack of data, studying them by simulation poses an important challenge especially forecasting models. These models are necessary to support management decisions or develop sustainable fisheries; therefore, models based on Deep Learning were proposed to forecast SSFs catch, using data from official catch landing reports (OCLRs), satellite images, and oceanographic data. The finfish fishery in Bahía Magdalena-Almejas (México) was used for the present study. According to an analysis of OCLRs, the target species of major importance in the fishery were identified and selected for the model. The proposed deep learning models used two artificial neural networks structures: non-linear autoregressive neural network and long-short term memory network, which were designed to assess and forecast monthly catch levels of Paralabrax nebulifer and Caulolatilus princeps. Models with a performance efficiency of R > 0.8, MSE < 300 were found, which indicate that the models are applicable in SSF with poor data and multi-specific fishery contexts, at low cost.