Computer-Aided Search for 5-Arylideneimidazolone Anticancer Agents Able To Overcome ABCB1-Based Multidrug Resistance

ABCB1 modulation is an interesting strategy in the search for new anticancer agents that can overcome multidrug resistance (MDR). Hence, 17 new 5-arylideneimidazolones containing an amine moiety, as potential ABCB1 inhibitors, were designed, synthesized, and investigated. The series was tested in both parental (PAR) and multidrug-resistant (MDR) ABCB1-overexpressing T-lymphoma cancer cells using cytotoxicity assays. The ABCB1-modulating activity was examined in rhodamine 123 accumulation tests, followed by Pgp-Glo™ Assay to determine the influence of the most active compounds on ATPase activity. Lipophilic properties were assessed both, in silico and experimentally (RP-TLC). Pharmacophore-based molecular modelling toward ABCB1 modulation was performed. The studies allowed the identification of anticancer agents (p-fluorobenzylidene derivatives) more potent than doxorubicin, with highly selective action on MDR T-lymphoma cells (selectivity index >40). Most of the investigated compounds showed ABCB1-modulating action; in particular, two 5-benzyloxybenzylidene derivatives displayed activity nearly as strong as that of tariquidar.     

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.     

Molecular Mechanisms of Fetal Tendon Regeneration Versus Adult Fibrous Repair

Tendinopathies are painful, disabling conditions that afflict 25% of the adult human population. Filling an unmet need for realistic large-animal models, we here present an ovine model of tendon injury for the comparative study of adult scarring repair and fetal regeneration. Complete regeneration of the fetal tendon within 28 days is demonstrated, while adult tendon defects remained macroscopically and histologically evident five months post-injury. In addition to a comprehensive histological assessment, proteome analyses of secretomes were performed. Confirming histological data, a specific and pronounced inflammation accompanied by activation of neutrophils in adult tendon defects was observed, corroborated by the significant up-regulation of pro-inflammatory factors, neutrophil attracting chemokines, the release of potentially tissue-damaging antimicrobial and extracellular matrix-degrading enzymes, and a response to oxidative stress. In contrast, secreted proteins of injured fetal tendons included proteins initiating the resolution of inflammation or promoting functional extracellular matrix production. These results demonstrate the power and relevance of our novel ovine fetal tendon regeneration model, which thus promises to accelerate research in the field. First insights from the model already support our molecular understanding of successful fetal tendon healing processes and may guide improved therapeutic strategies.     

The Co-Culture of Staphylococcal Biofilm and Fibroblast Cell Line: The Correlation of Biological Phenomena with Metabolic NMR1 Footprint

Staphylococcus aureus is one of the most prevalent pathogens associated with several types of biofilm-based infections, including infections of chronic wounds. Mature staphylococcal biofilm is extremely hard to eradicate from a wound and displays a high tendency to induce recurring infections. Therefore, in the present study, we aimed to investigate in vitro the interaction between S. aureus biofilm and fibroblast cells searching for metabolites that could be considered as potential biomarkers of critical colonization and infection. Utilizing advanced microscopy and microbiological methods to examine biofilm formation and the staphylococcal infection process, we were able to distinguish 4 phases of biofilm development. The analysis of staphylococcal biofilm influence on the viability of fibroblasts allowed us to pinpoint the moment of critical colonization—12 h post contamination. Based on the obtained model we performed a metabolomics analysis by ¹H NMR spectroscopy to provide new insights into the pathophysiology of infection. We identified a set of metabolites related to the switch to anaerobic metabolism that was characteristic for staphylococcal biofilm co-cultured with fibroblast cells. The data presented in this study may be thus considered a noteworthy but preliminary step in the direction of developing a new, NMR-based tool for rapid diagnosing of infection in a chronic wound.     

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...     

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.     

Polynomial-Time Algorithms for Energy Games with Special Weight Structures

Energy games belong to a class of turn-based two-player infinite-duration games played on a weighted directed graph. It is one of the rare and intriguing combinatorial problems that lie in NP∩co-NP, but are not known to be in P. The existence of polynomial-time algorithms has been a major open problem for decades and apart from pseudopolynomial algorithms there is no algorithm that solves any non-trivial subclass in polynomial time. In this paper, we give several results based on the weight structures of the graph. First, we identify a notion of penalty and present a polynomial-time algorithm when the penalty is large. Our algorithm is the first polynomial-time algorithm on a large class of weighted graphs. It includes several worst-case instances on which previous algorithms, such as value iteration and random facet algorithms, require at least sub-exponential time. Our main technique is developing the first non-trivial approximation algorithm and showing how to convert it to an exact algorithm. Moreover, we show that in a practical case in verification where weights are clustered around a constant number of values, the energy game problem can be solved in polynomial time. We also show that the problem is still as hard as in general when the clique-width is bounded or the graph is strongly ergodic, suggesting that restricting the graph structure does not necessarily help.     

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.