Towards an integrated neonatal brain and cardiac examination capability at 7 T: electromagnetic field simulations and early phantom experiments using an 8-channel dipole array

Objective

Neonatal brain and cardiac imaging would benefit from the increased signal-to-noise ratio levels at 7 T compared to lower field. Optimal performance might be achieved using purpose designed RF coil arrays. In this study, we introduce an 8-channel dipole array and investigate, using simulations, its RF performances for neonatal applications at 7 T.

Methods

The 8-channel dipole array was designed and evaluated for neonatal brain/cardiac configurations in terms of SAR efficiency (ratio between transmit-field and maximum specific-absorption-rate level) using adjusted dielectric properties for neonate. A birdcage coil operating in circularly polarized mode was simulated for comparison. Validation of the simulation model was performed on phantom for the coil array.

Results

The 8-channel dipole array demonstrated up to 46% higher SAR efficiency levels compared to the birdcage coil in neonatal configurations, as the specific-absorption-rate levels were alleviated. An averaged normalized root-mean-square-error of 6.7% was found between measured and simulated transmit field maps on phantom.

Conclusion

The 8-channel dipole array design integrated for neonatal brain and cardiac MR was successfully demonstrated, in simulation with coverage of the baby and increased SAR efficiency levels compared to the birdcage. We conclude that the 8Tx-dipole array promises safe operating procedures for MR imaging of neonatal brain and heart at 7 T.

     

Zinc oxide-decorated multiwalled carbon nanotubes: a selective electrochemical sensor for the detection of Pb(II) ion in aqueous media

Journal of Materials Science: Materials in Electronics - Multiwalled carbon nanotubes, due to high conductivity, stability, and large specific surface area, have a potential ability to promote...     

Reduced Claudin-12 Expression Predicts Poor Prognosis in Cervical Cancer

Background: Within the claudin (CLDN) family, CLDN12 mRNA expression is altered in various types of cancer, but its clinicopathological relevance has yet to be established due to the absence of specific antibodies (Abs) with broad applications. Methods: We generated a monoclonal Ab (mAb) against human/mouse CLDN12 and verified its specificity. By performing immunohistochemical staining and semiquantification, we evaluated the relationship between CLDN12 expression and clinicopathological parameters in tissues from 138 cases of cervical cancer. Results: Western blot and immunohistochemical analyses revealed that the established mAb selectively recognized the CLDN12 protein. Twenty six of the 138 cases (18.8%) showed low CLDN12 expression, and the disease-specific survival (DSS) and recurrence-free survival rates were significantly decreased compared with those in the high CLDN12 expression group. We also demonstrated, via univariable and multivariable analyses, that the low CLDN12 expression represents a significant prognostic factor for the DSS of cervical cancer patients (HR 3.412, p = 0.002 and HR 2.615, p = 0.029, respectively). Conclusions: It can be concluded that a reduced CLDN12 expression predicts a poor outcome for cervical cancer. The novel anti-CLDN12 mAb could be a valuable tool to evaluate the biological relevance of the CLDN12 expression in diverse cancer types and other diseases.     

A hybrid knowledge and ensemble classification approach for prediction of venous thromboembolism

Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE.     

Can social media usage of scientific literature predict journal indices of AJG,SNIP and JCR? An altmetric study of economics

Scientometrics - Altmetrics are often praised as an alternative or complement to classic bibliometric metrics, especially in the social sciences discipline. However, empirical investigations of...     

Review on zirconate-cerate-based electrolytes for proton-conducting solid oxide fuel cell

The performance of low-to-intermediate temperature (400–800?°C) solid oxide fuel cells (SOFCs) depends on the properties of electrolyte used. SOFC performance can be enhanced by replacing electrolyte materials from conventional oxide ion (O^2-) conductors with proton (H⁺) conductors because H⁺ conductors have higher ionic conductivity and theoretical electrical efficiency than O^2- conductors within the target temperature range. Electrolytes based on cerate and/or zirconate have been proposed as potential H⁺ conductors. Cerate-based electrolytes have the highest H⁺ conductivity, but they are chemically and thermally unstable during redox cycles, whereas zirconate-based electrolytes exhibit the opposite properties. Thus, tailoring the properties of cerate and/or zirconate electrolytes by doping with rare-earth metals has become a main concern for many researchers to further improve the ionic conductivity and stability of electrolytes. This article provides an overview on the properties of four types of cerate and/or zirconate electrolytes including cerate-based, zirconate-based, single-doped cerate–zirconate and hybrid-doped cerate–zirconate. The properties of the proton electrolytes such as ionic conductivity, chemical stability and sinterability are also systematically discussed. This review further provides a summary of the performance of SOFCs operated with cerate and/or zirconate proton conductors and the actual potential of these materials as alternative electrolytes for proton-conducting SOFC application.     

Experimental investigation of Co and Fe-Doped CuO nanostructured electrode material for remarkable electrochemical performance

The current research work presents a facile and cost–effective co-precipitation method to prepare doped (Co & Fe) CuO and undoped CuO nanostructures without usage of any type of surfactant or capping agents. The structural analysis reveals monoclinic crystal structure of synthesized pure CuO and doped-CuO nanostructures. The effect of different morphologies on the performance of supercapacitors has been found in CV (cyclic voltammetry) and GCD (galvanic charge discharge) investigations. The specific capacitances have been obtained 156 (±5) Fg^?1, 168(±5) Fg^?1 and 186 (±5) Fg^?1 for CuO, Co-doped CuO and Fe-doped CuO electrodes, respectively at scan rate of 5 mVs^?1, while it is found to be 114 (±5) Fg^?1, 136 (±5) Fg^?1 and 170 (±5) Fg^?1 for CuO, Co–CuO and Fe–CuO, respectively at 0.5 Ag^-1 as calculated from the GCD. The super capacitive performance of the Fe–CuO nanorods is mainly attributed to the synergism that evolves between CuO and Fe metal ion. The Fe-doped CuO with its nanorods like morphology provides superior specific capacitance value and excellent cyclic stability among all studied nanostructured electrodes. Consequently, it motivates to the use of Fe-doped CuO nanostructures as electrode material in the next generation energy storage devices.     

A fog-based security framework for intelligent traffic light control system

Multimedia Tools and Applications - The world is facing many problems including that of traffic congestion. To highlight the issue of traffic congestion worldwide specially in urban areas and to...