A chamber for biomechanical,electrochemical and electrophysiological measurements in functional segments of peripheral nerves

The aim of the work was to develop the chamber to be used in biomechanical, electrochemical and electrophysiological measurements in functional segments of peripheral nerves, when electrical stimulating pulses are selectively applied to preselected locations along the nerve and neural responses are measured.     

Controllable Broadband Absorption in the Mixed Phase of Metamagnets

Materials with broad absorption bands are highly desirable for electromagnetic filtering and processing applications, especially if the absorption can be externally controlled. Here, a new class of broadband‐absorption materials is introduced. Namely, layered metamagnets exhibit an electromagnetic excitation continuum in the magnetic‐field‐induced mixed ferro‐ and anti­ferromagnetic phase. Employing a series of complementary experimental techniques involving neutron scattering, muon spin relaxation, specific heat, ac and dc magnetization measurements, and electron magnetic resonance, a detailed magnetic phase diagram of Cu₃Bi(SeO₃)₂O₂Br is determined and it is found that the excitations in the mixed phase extend over at least ten decades of frequency. The results, which reveal a new dynamical aspect of the mixed phase in metamagnets, open up a novel approach to controllable microwave filtering.     

Autonomous evolutionary algorithm in medical data analysis

An autonomous evolutionary algorithm for constructing decision trees is presented. The algorithm requires no or minimal human interaction and shows some interesting properties when used on different medical datasets. The algorithm uses a non-standard implicit fitness evaluation in the selection phase of a co-evolving environment. Together with self-adaptation of evolution parameters and with some other improvements it can monitor and adjust its own behavior. The algorithm's capability to self-adapt to a given problem is used as a measure to predict if some dataset is just difficult or impossible to analyze. The autonomous algorithm on average produces very general solutions or gives no solution if the dataset is prone to the overfitting problem.     

A comparative study on the electrical and mechanical behaviour of multi‐walled carbon nanotube composites prepared by diluting a masterbatch with various types of polypropylenes

Polypropylene (PP) nanocomposites with multi‐walled carbon nanotubes (CNT) were produced by a small‐scale masterbatch melt dilution technique using five PP differing in melt flow index (MFI) and degree of maleination. PP used in a masterbatch has MFI = 12 (PP₁₂), the others used PP which have MFI = 2 or MFI = 8. The state of CNT dispersion as assessed by melt rheological and morphological investigations indicated a better dispersion when using unmodified PP with MFI = 8 (PP₈) and the masterbatch's PP₁₂. Electrical conductivity results showed nanotube percolation at contents between 1.1 and 2.0 vol %, whereas lower values were obtained for the matrices with the best dispersion, i.e., PP₈ and PP₁₂. The dependencies of the relative Young's modulus on the CNT content showed that the maleinization improved the interfacial interactions between the components, especially in the case of maleated PP with MFI = 8 (PP‐MA₈), but the better dispersion was prevented by the incompatibility between polar groups of PP‐MA and the nonpolar origin masterbatch PP₁₂. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009     

Mechanochemical synthesis of ternary chalcogenide chalcostibite CuSbS2 and its characterization

Journal of Materials Science: Materials in Electronics - In this work, the very rapid one-step mechanochemical synthesis of nanocrystalline ternary chalcogenide chalcostibite CuSbS2 prepared from...     

The Tumor Proteolytic Landscape: A Challenging Frontier in Cancer Diagnosis and Therapy

In recent decades, dysregulation of proteases and atypical proteolysis have become increasingly recognized as important hallmarks of cancer, driving community-wide efforts to explore the proteolytic landscape of oncologic disease. With more than 100 proteases currently associated with different aspects of cancer development and progression, there is a clear impetus to harness their potential in the context of oncology. Advances in the protease field have yielded technologies enabling sensitive protease detection in various settings, paving the way towards diagnostic profiling of disease-related protease activity patterns. Methods including activity-based probes and substrates, antibodies, and various nanosystems that generate reporter signals, i.e., for PET or MRI, after interaction with the target protease have shown potential for clinical translation. Nevertheless, these technologies are costly, not easily multiplexed, and require advanced imaging technologies. While the current clinical applications of protease-responsive technologies in oncologic settings are still limited, emerging technologies and protease sensors are poised to enable comprehensive exploration of the tumor proteolytic landscape as a diagnostic and therapeutic frontier. This review aims to give an overview of the most relevant classes of proteases as indicators for tumor diagnosis, current approaches to detect and monitor their activity in vivo, and associated therapeutic applications.     

A model-based approach to the evaluation of flame-protective garments

High-quality protective garments are essential in many occupational assignments, e.g., in the petrochemical industry and for firefighting. The problem addressed in this paper is how to objectively asses the performance of protective garments designed to resist fire. We present a system based on a flame mannequin equipped with an array of temperature sensors that provide information about the temperature on the mannequin’s surface during exposure to fire. Particular attention is devoted to reconstructing the heat flux reaching the mannequin’s surface on the basis of the available temperature records (the inverse heat-conduction problem). The estimated heat flux is used in a skin-simulation model to predict the level of injury that would occur in human exposed to the same heat. The paper includes a novel computational procedure based on a detailed model of the temperature sensor and a numerical solution of the accompanying heat equation. The effectiveness of the solution is demonstrated with experimental data.     

Iterative inflow-implicit outflow-explicit finite volume scheme for level-set equations on polyhedron meshes

In this paper, we propose a cell-centered finite volume method for advective and normal flows on polyhedron meshes which is second-order accurate in space and time for smooth solutions. In order to overcome a time restriction caused by CFL condition, an implicit time discretization of inflow fluxes and an explicit time discretization of outflow fluxes are used in an iterative procedure. For an efficient computation, an 1-ring face neighborhood structure is introduced. Since it is limited to access unknown variables in an 1-ring face neighborhood structure, an iterative procedure is proposed to resolve the limitation of assembled linear system. Two types of gradient approximations, an inflow-based gradient and an average-based gradient, are studied and compared from the point of numerical accuracy. Numerical schemes are tested for an advective and a normal flow of level-set functions illustrating a behavior of the proposed method for an implicit tracking of a smooth and a piecewise smooth interface.     

Degradomics in Biomarker Discovery

The upregulation of protease expression and proteolytic activity is implicated in numerous pathological conditions such as neurodegeneration, cancer, cardiovascular and autoimmune diseases, and bone degeneration. During disease progression, various proteases form characteristic patterns of cleaved proteins and peptides, which can affect disease severity and course of progression. It has been shown that qualitative and quantitative monitoring of cleaved protease substrates can provide relevant prognostic, diagnostic, and therapeutic information. As proteolytic fragments and peptides generated in the affected tissue are commonly translocated to blood, urine, and other proximal fluids, their possible application as biomarkers is the subject of ongoing research. The field of degradomics has been established to enable the global identification of proteolytic events on the organism level, utilizing proteomic approaches and sample preparation techniques that facilitate the detection of proteolytic processing of protease substrates in complex biological samples. In this review, some of the latest developments in degradomic methodologies used for the identification and validation of biologically relevant proteolytic events and their application in the search for clinically relevant biomarker candidates are presented. The current state of degradomics in clinics is discussed and the future perspectives of the field are outlined.     

Crystallization of 2D Hybrid Organic–Inorganic Perovskites Templated by Conductive Substrates

2D hybrid organic–inorganic perovskites are valued in optoelectronic applications for their tunable bandgap and excellent moisture and irradiation stability. These properties stem from both the chemical composition and crystallinity of the layer formed. Defects in the lattice, impurities, and crystal grain boundaries generally introduce trap states and surface energy pinning, limiting the ultimate performance of the perovskite; hence, an in-depth understanding of the crystallization process is indispensable. Here, a kinetic and thermodynamic study of 2D perovskite layer crystallization on transparent conductive substrates are provided—fluorine-doped tin oxide and graphene. Due to markedly different surface structure and chemistry, the two substrates interact differently with the perovskite layer. A time-resolved grazing-incidence wide-angle X-ray scattering (GIWAXS) is used to monitor the crystallization on the two substrates. Molecular dynamics simulations are employed to explain the experimental data and to rationalize the perovskite layer formation. The findings assist substrate selection based on the required film morphology, revealing the structural dynamics during the crystallization process, thus helping to tackle the technological challenges of structure formation of 2D perovskites for optoelectronic devices.