A Genomics-Based Model for Prediction of Severe Bioprosthetic Mitral Valve Calcification

Severe bioprosthetic mitral valve calcification is a significant problem in cardiovascular surgery. Unfortunately, clinical markers did not demonstrate efficacy in prediction of severe bioprosthetic mitral valve calcification. Here, we examined whether a genomics-based approach is efficient in predicting the risk of severe bioprosthetic mitral valve calcification. A total of 124 consecutive Russian patients who underwent mitral valve replacement surgery were recruited. We investigated the associations of the inherited variation in innate immunity, lipid metabolism and calcium metabolism genes with severe bioprosthetic mitral valve calcification. Genotyping was conducted utilizing the TaqMan assay. Eight gene polymorphisms were significantly associated with severe bioprosthetic mitral valve calcification and were therefore included into stepwise logistic regression which identified male gender, the T/T genotype of the rs3775073 polymorphism within the TLR6 gene, the C/T genotype of the rs2229238 polymorphism within the IL6R gene, and the A/A genotype of the rs10455872 polymorphism within the LPA gene as independent predictors of severe bioprosthetic mitral valve calcification. The developed genomics-based model had fair predictive value with area under the receiver operating characteristic (ROC) curve of 0.73. In conclusion, our genomics-based approach is efficient for the prediction of severe bioprosthetic mitral valve calcification.     

Automatic word naming recognition for an on-line aphasia treatment system

One of the most common effects among aphasia patients is the difficulty to recall names or words. Typically, word retrieval problems can be treated through word naming therapeutic exercises. In fact, the frequency and the intensity of speech therapy are key factors in the recovery of lost communication functionalities. In this sense, speech and language technology can have a relevant contribution in the development of automatic therapy methods. In this work, we present an on-line system designed to behave as a virtual therapist incorporating automatic speech recognition technology that permits aphasia patients to perform word naming training exercises. We focus on the study of the automatic word naming detector module and on its utility for both global evaluation and treatment. For that purpose, a database consisting of word naming therapy sessions of aphasic Portuguese native speakers has been collected. In spite of the different patient characteristics and speech quality conditions of the collected data, encouraging results have been obtained thanks to a calibration method that makes use of the patients’ word naming ability to automatically adapt to the patients’ speech particularities.     

Thirty Years of the International Journal of Intelligent Systems: A Bibliometric Review

The International Journal of Intelligent Systems was created in 1986. Today, the journal is 30 years old. To celebrate this anniversary, this study develops a bibliometric review of all of the papers published in the journal between 1986 and 2015. The results are largely based on the Web of Science Core Collection, which classifies leading bibliographic material by using several indicators including total number of publications and citations, the h‐index, cites per paper, and citing articles. The work also uses the VOS viewer software for visualizing the main results through bibliographic coupling and co‐citation. The results show a general overview of leading trends that have influenced the journal in terms of highly cited papers, authors, journals, universities and countries.     

Environmental Control of Triplet Emission in Donor–Bridge–Acceptor Organometallics

Carbene‐metal‐amides (CMAs) are a promising family of donor–bridge–acceptor molecular charge‐transfer (CT) emitters for organic light‐emitting diodes. A universal approach is demonstrated to tune the energy of their CT emission. A blueshift of up to 210 meV is achievable in solid state via dilution in a polar host matrix. The origin of this shift has two components: constraint of thermally‐activated triplet diffusion, and electrostatic interactions between guest and polar host. This allows the emission of mid‐green CMA archetypes to be tuned to sky blue without chemical modifications. Monte‐Carlo simulations based on a Marcus‐type transfer integral successfully reproduce the concentration‐ and temperature‐dependent triplet diffusion process, revealing a substantial shift in the ensemble density of states in polar hosts. In gold‐bridged CMAs, this shift does not lead to a significant change in luminescence lifetime, thermal activation energy, reorganization energy, or intersystem crossing rate. These discoveries offer new insight into coupling between the singlet and triplet manifolds in CMA materials, revealing a dominant interaction between states of CT character. The same approach is employed using materials which have been chemically modified to alter the energy of their CT state directly, shifting the emission of sky‐blue chromophores into the practical blue range.     

Modulation of iron–nickel layers composition by an external magnetic field

In this article, characterization of FeNi layers deposited on a Cu plate for variable magnetic field arrangement is shown. Layers were prepared using a simple electrodeposition process, from an aqueous solution of Fe²⁺ and Ni²⁺ sulfate salts containing boric acid, an iron activator. By application of variation of current values, times, and external magnetic field orientations, the resultant film quality was examined and the efficiency of the embedded elements was investigated. The studies show differences in the coating morphology and relative composition of ferromagnetic metals (Ni, Fe) electrodeposited on a not ferromagnetic (paramagnetic) metal (Cu). The obtained layers were investigated by Scanning Electron Microscopy and Energy Dispersive X-ray Spectroscopy.