Plant Copper Amine Oxidases: Key Players in Hormone Signaling Leading to Stress-Induced Phenotypic Plasticity

Polyamines are ubiquitous, low-molecular-weight aliphatic compounds, present in living organisms and essential for cell growth and differentiation. Copper amine oxidases (CuAOs) oxidize polyamines to aminoaldehydes releasing ammonium and hydrogen peroxide, which participates in the complex network of reactive oxygen species acting as signaling molecules involved in responses to biotic and abiotic stresses. CuAOs have been identified and characterized in different plant species, but the most extensive study on a CuAO gene family has been carried out in Arabidopsis thaliana. Growing attention has been devoted in the last years to the investigation of the CuAO expression pattern during development and in response to an array of stress and stress-related hormones, events in which recent studies have highlighted CuAOs to play a key role by modulation of a multilevel phenotypic plasticity expression. In this review, the attention will be focused on the involvement of different AtCuAOs in the IAA/JA/ABA signal transduction pathways which mediate stress-induced phenotypic plasticity events.     

A novel ceramic matrix composite based on YNbO4–TiO2 for microwave applications

This work presents the dielectric properties of YNbO₄ (YNO)–TiO₂ composites in the microwave range. X-ray diffraction analysis demonstrates that the addition of TiO₂ to YNO results in the formation of a Y(Nb_0.5Ti_0.5)₂O₆ phase. In the microwave range, the values of permittivity and dielectric loss did not present major changes with the increment of TiO₂. Moreover, the addition of TiO₂ results in an improvement in the thermal stability of YNO, with YNO63 demonstrating a resonant frequency of ?8.96 ppm.°C^?1. We utilised numerical simulations to evaluate the behaviour of these materials as dielectric resonator antennae and it is found that they exhibit a reflection coefficient below ?10 dB at the resonant frequency, with a realised gain of 4.94 – 5.76 dBi, a bandwidth of 665–1050 MHz and a radiation efficiency above 84%. Our results indicate that YNO–TiO₂ composites are interesting candidates for microwave operating devices.     

Dielectric performance of pyrochlore-type Bi2MgNb2-xTaxO9 ceramics: The effects of tantalum doping

The solid solutions based on the pyrochlore-type system Bi₂MgNb_2-xTa_xO₉ were formed in the compositional range х = 0–2.0 (Bi_1·6Mg_0·8Nb_1.6-tTa_tO_7.2, t = 0–1.6). The Rietveld method was used to refine the structure for Bi₂MgNb_2-xTa_xO₉ (x = 0, 1.0, 2.0). The increasing tantalum content led to the slight decrease in the cubic unit cell parameters from 10.56934 (4) Å for x = 0 and 10.54607 (3) Å for x = 2 (sp.gr. Fd-3m:2). At the same time, tantalum additions suppressed grain growth in the pyrochlore ceramics during sintering and made it possible to obtain materials with an average grain size of 1–2 μm (Bi_1·6Mg_0·8Ta_1·6O_7.2). The increase in the Ta⁵⁺ concentration led to the decrease in the dielectric permeability from 104 (Bi_1·6Mg_0·8Nb_1·6O_7.2) to 20 (Bi_1·6Mg_0·8Ta_1·6O_7.2) at room temperature, while the dielectric loss tangent remained lower than 0.002, which is due to the small grain size and the high porosity of the samples. An increase in temperature has practically no effect on the values of the dielectric permittivity in the entire frequency range. The samples have weak through conductivity. The activation energies of electrical conductivity varied in the range of 0.84–1.00 eV, and the less tantalum, the lower the activation energy. The electrical properties of the samples at 200 Hz to 1 MHz are described by the simplest parallel scheme.     

Tailored-Made Polydopamine Nanoparticles to Induce Ferroptosis in Breast Cancer Cells in Combination with Chemotherapy

Ferroptosis is gaining followers as mechanism of selective killing cancer cells in a non-apoptotic manner, and novel nanosystems capable of inducing this iron-dependent death are being increasingly developed. Among them, polydopamine nanoparticles (PDA NPs) are arousing interest, since they have great capability of chelating iron. In this work, PDA NPs were loaded with Fe³⁺ at different pH values to assess the importance that the pH may have in determining their therapeutic activity and selectivity. In addition, doxorubicin was also loaded to the nanoparticles to achieve a synergist effect. The in vitro assays that were performed with the BT474 and HS5 cell lines showed that, when Fe³⁺ was adsorbed in PDA NPs at pH values close to which Fe(OH)₃ begins to be formed, these nanoparticles had greater antitumor activity and selectivity despite having chelated a smaller amount of Fe³⁺. Otherwise, it was demonstrated that Fe³⁺ could be released in the late endo/lysosomes thanks to their acidic pH and their Ca²⁺ content, and that when Fe³⁺ was co-transported with doxorubicin, the therapeutic activity of PDA NPs was enhanced. Thus, reported PDA NPs loaded with both Fe³⁺ and doxorubicin may constitute a good approach to target breast tumors.     

Extremum Strategies of Approach of Controlled Objects in Dynamic Game Problems with Terminal Payoff Function

Cybernetics and Systems Analysis - The authors propose a method for solving the problem of approach of controlled objects in dynamic game problems with a terminal payoff function. The method is...     

Validation of scientific topic models using graph analysis and corpus metadata

Probabilistic topic modeling algorithms like Latent Dirichlet Allocation (LDA) have become powerful tools for the analysis of large collections of documents (such as papers, projects, or funding applications) in science, technology an innovation (STI) policy design and monitoring. However, selecting an appropriate and stable topic model for a specific application (by adjusting the hyperparameters of the algorithm) is not a trivial problem. Common validation metrics like coherence or perplexity, which are focused on the quality of topics, are not a good fit in applications where the quality of the document similarity relations inferred from the topic model is especially relevant. Relying on graph analysis techniques, the aim of our work is to state a new methodology for the selection of hyperparameters which is specifically oriented to optimize the similarity metrics emanating from the topic model. In order to do this, we propose two graph metrics: the first measures the variability of the similarity graphs that result from different runs of the algorithm for a fixed value of the hyperparameters, while the second metric measures the alignment between the graph derived from the LDA model and another obtained using metadata available for the corresponding corpus. Through experiments on various corpora related to STI, it is shown that the proposed metrics provide relevant indicators to select the number of topics and build persistent topic models that are consistent with the metadata. Their use, which can be extended to other topic models beyond LDA, could facilitate the systematic adoption of this kind of techniques in STI policy analysis and design.

     

Modeling the Destruction of an Anisotropic Composite Barrier in Interaction with Slender Strikers at an Angle

Journal of Engineering Physics and Thermophysics - A numerical investigation has been made into the interaction of slender (5–20 calibers) steel cylinder strikers with orthotropic compost...     

Influence of the Corrosion Process on Thermotechnical Characteristics of Heat Pipes of Low-Temperature Range

Journal of Engineering Physics and Thermophysics - Results of investigation into the influence of a corrosion process on thermotechnical characteristics of heat pipes of low-temperature range are...     

Wall Rock Alteration,Uranium Mineralization,and Potentiality of Uranium and Iron Dissolution from Mineralized Abu Rusheid Gneiss Rock,South Eastern Desert,Egypt

Radiochemistry - Ferrugination, sericitization, desulfitization, chloritization, and kaolinitization of hydrothermal origin are the main wall rock alterations occurring within the NNW shear zones...     

Justification for the Use of Cohen’s Kappa Statistic in Experimental Studies of NLP and Text Mining

Modern metrics for evaluating agreement coefficients between the experimental results and expert opinion are compared, and the possibility of using these metrics in experimental research in automatic text processing by machine learning methods is assessed. The choice of Cohen’s kappa coefficient as a measure of expert opinion agreement in the NLP and Text Mining problems is justified. An example of using Cohen’s kappa coefficient for evaluating the level of agreement between the opinion of an expert and the results of ML classification and the measure of agreement of expert opinions in the alignment of sentences of the Kazakh-Russian parallel corpus is given. Based on this analysis, it is proved that Cohen’s kappa coefficient is one of the best statistical methods for determining the level of agreement in experimental studies due to its ease of use, computing simplicity, and high accuracy of the results.