El Registro de Gemelos de Murcia. Un recurso para la investigación sobre conductas relacionadas con la salud

Genetically informative designs and, in particular, twin studies, are the most widely used methodology to analyse the relative contribution of genetic and environmental factors to inter-individual variability. These studies basically compare the degree of phenotypical similarity between monozygotic and dizygotic twin pairs. In addition to the traditional estimate of heritability, this kind of registry enables a wide variety of analyses which are unique due to the characteristics of the sample. The Murcia Twin Registry is population-based and focused on the analysis of health-related behaviour. The observed prevalence of health problems is comparable to that of other regional and national reference samples, which guarantees its representativeness. Overall, the characteristics of the Registry facilitate developing various types of research as well as genetically informative designs, and collaboration with different initiatives and consortia.     

Nuevos retos en gestión de vectores en salud pública: la mosca negra en Murcia (España)

Historically, no black fly (Diptera: Simuliidae) nuisance has been reported in the Murcia Region. Back in September 2016 the Ojós City Council has contacted the Regional Public Health General Directorate for help regarding a local insect nuisance, most probably based on mosquitoes. After sampling with a BG-sentinel 2 trap, collecting adult specimens with an entomological aspirator, and collect larvae and pupae on submerged giant cane stalks at the river, it turned out that Simulium sergenti was the insect species causing the nuisance. This species is not considered particularly anthropophilic; therefore, a low vector risk for human health was considered. However, the high fly density impaired the life quality of the people at the village. A management plan was recommended, treating the river with Bacillus thuringiensis var israelensis.     

Singular value based characterization and analysis of thermal patches for early breast abnormality detection

The purpose of this study is to develop a novel breast abnormality detection system by utilizing the potential of infrared breast thermography (IBT) in early breast abnormality detection. Since the temperature distributions are different in normal and abnormal thermograms and hot thermal patches are visible in abnormal thermograms, the abnormal thermograms possess more complex information than the normal thermograms. Here, the proposed method exploits the presence of hot thermal patches and vascular changes by using the power law transformation for pre-processing and singular value decomposition to characterize the thermal patches. The extracted singular values are found to be statistically significant (p?<?0.001) in breast abnormality detection. The discriminability of the singular values is evaluated by using seven different classifiers incorporating tenfold cross-validations, where the thermograms of the Department of Biotechnology-Tripura University-Jadavpur University (DBT-TU-JU) and Database of Mastology Research (DMR) databases are used. In DMR database, the highest classification accuracy of 98.00% with the area under the ROC curve (AUC) of 0.9862 is achieved with the support vector machine using polynomial kernel. The same for the DBT-TU-JU database is 92.50% with AUC of 0.9680 using the same classifier. The comparison of the proposed method with the other reported methods concludes that the proposed method outperforms the other existing methods as well as other traditional feature sets used in IBT based breast abnormality detection. Moreover, by using Rank1 and Rank2 singular values, a breast abnormality grading (BAG) index has also been developed for grading the thermograms based on their degree of abnormality.     

Estimating transmitted power density from mobile phone: an epidemiological pilot study with a software modified phone

The aims of this study were to evaluate the weekly and annual cumulative radiofrequency-electromagnetic field (RF-EMF) exposure attributed to mobile phone (MP) use, and assess whether a novel app (Quanta Monitor?) could be employed in a small human sample to characterise the RF-EMF exposures associated with the use of MPs. Ten participants provided their two months’ daily objective data on their MP exposures (i.e. transmitted and received power densities) attributed to different modes of MP usage such as cellular calls, cellular data and Wi-Fi. The results demonstrated that total transmitted power density (cellular phone calls, data and Wi-Fi surfing) could be many orders of magnitude higher than that from the total received power density. Of the total transmitted power density, cellular data use contributed the largest portion. Our study showed that Quanta Monitor? could be employed in prospective assessment of exposures to MPs in epidemiological studies.