Polymorphisms in EGFR Gene Predict Clinical Outcome in Unresectable Non-Small Cell Lung Cancer Treated with Radiotherapy and Platinum-Based Chemoradiotherapy

For non-small cell lung cancer (NSCLC), radiotherapy (RT) and platinum-based chemotherapy (CHT) are among the main treatment options. On the other hand, radioresistance and cytotoxic drug resistance are common causes of failure. The epidermal growth factor receptor (EGFR) plays an important role in radioresponse and therapy resistance. We hypothesized that single nucleotide polymorphisms (SNPs) in the EGFR gene might affect individual sensitivity to these treatments, and thus, therapy outcome and prognosis. The association between functional EGFR SNPs and overall (OS), locoregional recurrence-free (LFRS), and metastasis-free (MFS) survival was examined in 436 patients with unresectable NSCLC receiving RT and platinum-based CHTRT. In a multivariate analysis, the rs712830 CC homozygotes showed reduced OS in the whole group (p = 0.039) and in the curative treatment subset (p = 0.047). The rs712829 TT genotype was strongly associated with decreased LRFS (p = 0.006), and the T-C haplotype was a risk factor for locoregional recurrence in our patients (p = 0.003). The rs2227983 GG alone and in combination with rs712829 T was an indicator of unfavorable LRFS (p = 0.028 and 0.002, respectively). Moreover, significant independent effects of these SNPs on OS, LRFS, and MFS were observed. Our results demonstrate that inherited EGFR gene variants may predict clinical outcomes in NSCLC treated with DNA damage-inducing therapy.     

Effect of Ca2+ and Mg2+ ions on the sintering and spectroscopic properties of cr-doped yttrium aluminum garnet ceramics

In this work, we investigated the effects of Ca²⁺ and Mg²⁺ ions and annealing temperature on the spectroscopic parameters of chromium-doped yttrium aluminum garnet ceramics (Cr:YAG). Samples were obtained with either a separate or a simultaneous addition of calcium and magnesium oxides. To achieve this, aqueous suspensions were prepared using Y₂O₃, Al₂O₃, Cr₂O₃, MgO, and CaO high-purity powders as raw materials. The obtained suspensions were freeze-granulated, pressed into pellets, debinded, and subjected to reactive sintering in vacuum at 1715°C for 6 h. Each material was annealed in air with temperatures between 1300 and 1700°C. Samples were also compared to Cr:YAG ceramics with the addition of silica as a sintering aid. All the materials obtained were then exposed to 445 nm excitation, and emission spectra in the visible and infrared wavelengths were recorded. The results showed that the emission spectra of Cr:YAG ceramics varied according to the annealing conditions: as-sintered samples exhibited strong emissions of around 680 nm and, after air annealing, of around 1400 nm. This phenomenon is attributed to the Cr³⁺→Cr⁴⁺ transition. Samples doped solely with MgO exhibited the highest emission intensity in the infrared region. Thus, Mg²⁺ ions provided the best conversion efficiency of chromium ions.     

Microstructure and Mechanical Properties of the Ductile Al–Ti–Mo–Nb–V Refractory High Entropy Alloys

Metallurgical and Materials Transactions A - A number of non-equimolar refractory high entropy alloys (RF HEAs) from the Al–Ti–Mo–Nb–V system are synthesized, with the...     

Stability of nonlinear 2D systems described by the continuous-time Roesser model

This paper considers systems with two-dimensional dynamics (2D systems) described by the continuous-time nonlinear state-space Roesser model. The sufficient conditions of exponential stability in terms of vector Lyapunov functions are established. These conditions are then applied to analysis of the absolute stability of a certain class of systems comprising a linear continuous-time plant in the form of the Roesser model with a nonlinear characteristic in the feedback loop, which satisfies quadratic constraints. The absolute stability conditions are reduced to computable expressions in the form of linear matrix inequalities. The obtained results are extended to the class of continuous-time systems governed by the Roesser model with Markovian switching. The problems of absolute stability and stabilization via state- and output-feedback are solved for linear systems of the above class. The solution procedures for these problems are in the form of algorithms based on linear matrix inequalities.     

Comments on “Necessary and sufficient stability condition of fractional-order interval linear systems” [Automatica 44 (2008), 2985–2988]

This paper shows that the main thesis of the article “Necessary and sufficient stability condition of fractional-order interval linear systems” by Ahn and Chen (Automatica, vol. 44, pp. 2985–2988) is only a sufficient (and not a necessary) condition for the robust stability of fractional-order linear systems.     

Production of nanoparticles of copper compounds by anodic dissolution of copper in organic solvents

The anodic behaviour of copper was investigated in ethanol solution containing LiClO₄, LiCl electrolyte and water. The type of electrolyte and the water content influences the mechanism of the anodic process and the formation of anodic products. In LiClO₄ electrolyte the dissolution of copper is related to the oxidation of Cu(I) to Cu(II). In solutions of LiCl the etching of copper begins with the creation of soluble complexes of Cu(I) with chloride ions and solvent molecules. At potentials above 0.4 V the formation of alkoxides was observed in both solutions, characterized by a yellow tint. On the other hand, above 0.8 V (i.e. above the equilibrium potential of alcohol oxidation) copper dissolution is accompanied by the formation of a blue colloidal suspension of Cu (II) copper salt. Anodic etching of copper in solutions containing 3% H₂O at potentials higher than 0.4 V leads to the formation of colloidal suspension of copper oxide nanoparticles.     

Detecting Fixed Patterns in Chordal Graphs in Polynomial Time

The Contractibility problem takes as input two graphs G and H, and the task is to decide whether H can be obtained from G by a sequence of edge contractions. The Induced Minor and Induced Topological Minor problems are similar, but the first allows both edge contractions and vertex deletions, whereas the latter allows only vertex deletions and vertex dissolutions. All three problems are NP-complete, even for certain fixed graphs H. We show that these problems can be solved in polynomial time for every fixed H when the input graph G is chordal. Our results can be considered tight, since these problems are known to be W[1]-hard on chordal graphs when parameterized by the size of H. To solve Contractibility and Induced Minor, we define and use a generalization of the classic Disjoint Paths problem, where we require the vertices of each of the k paths to be chosen from a specified set. We prove that this variant is NP-complete even when k=2, but that it is polynomial-time solvable on chordal graphs for every fixed k. Our algorithm for Induced Topological Minor is based on another generalization of Disjoint Paths called Induced Disjoint Paths, where the vertices from different paths may no longer be adjacent. We show that this problem, which is known to be NP-complete when k=2, can be solved in polynomial time on chordal graphs even when k is part of the input. Our results fit into the general framework of graph containment problems, where the aim is to decide whether a graph can be modified into another graph by a sequence of specified graph operations. Allowing combinations of the four well-known operations edge deletion, edge contraction, vertex deletion, and vertex dissolution results in the following ten containment relations: (induced) minor, (induced) topological minor, (induced) subgraph, (induced) spanning subgraph, dissolution, and contraction. Our results, combined with existing results, settle the complexity of each of the ten corresponding containment problems on chordal graphs.     

Seed Selection for Spread of Influence in Social Networks: Temporal vs. Static Approach

The problem of finding optimal set of users for influencing others in the social network has been widely studied. Because it is NP-hard, some heuristics were proposed to find sub-optimal solutions. Still, one of the commonly used assumption is the one that seeds are chosen on the static network, not the dynamic one. This static approach is in fact far from the real-world networks, where new nodes may appear and old ones dynamically disappear in course of time. The main purpose of this paper is to analyse how the results of one of the typical models for spread of influence - linear threshold - differ depending on the strategy of building the social network used later for choosing seeds. To show the impact of network creation strategy on the final number of influenced nodes - outcome of spread of influence, the results for three approaches were studied: one static and two temporal with different granularities, i.e. various number of time windows. Social networks for each time window encapsulated dynamic changes in the network structure. Calculation of various node structural measures like degree or betweenness respected these changes by means of forgetting mechanism - more recent data had greater influence on node measure values. These measures were, in turn, used for node ranking and their selection for seeding. All concepts were applied to experimental verification on five real datasets. The results revealed that temporal approach is always better than static and the higher granularity in the temporal social network while seeding, the more finally influenced nodes. Additionally, outdegree measure with exponential forgetting typically outperformed other time-dependent structural measures, if used for seed candidate ranking.     

Upgrading a Granular Computing Based Data Mining Framework to a Relational Case

One of the popular methods to develop an algorithm for mining data stored in a relational structure is to upgrade an existing attribute‐value algorithm to a relational case. Current approaches to this problem have some shortcomings such as (1) a dependence on the upgrading process of the algorithm to be extended, (2) complicated redefinitions of crucial notions (e.g., pattern generality, pattern refinement), and (3) a tolerant limitation of the search space for pattern discovery. In this paper, we propose and evaluate a general methodology for upgrading a data mining framework to a relational case. This methodology is defined in a granular computing environment. Thanks to our relational extension of a granular computing based data mining framework, the three above problems can be overcome.