Preliminary Evidence on the Diagnostic and Molecular Role of Circulating Soluble EGFR in Non-Small Cell Lung Cancer

Assessment of biological diagnostic factors providing clinically-relevant information to guide physician decision-making are still needed for diseases with poor outcomes, such as non-small cell lung cancer (NSCLC). Epidermal growth factor receptor (EGFR) is a promising molecule in the clinical management of NSCLC. While the EGFR transmembrane form has been extensively investigated in large clinical trials, the soluble, circulating EGFR isoform (sEGFR), which may have a potential clinical use, has rarely been considered. This study investigates the use of sEGFR as a potential diagnostic biomarker for NSCLC and also characterizes the biological function of sEGFR to clarify the molecular mechanisms involved in the course of action of this protein. Plasma sEGFR levels from a heterogeneous cohort of 37 non-advanced NSCLC patients and 54 healthy subjects were analyzed by using an enzyme-linked immunosorbent assay. The biological function of sEGFR was analyzed in vitro using NSCLC cell lines, investigating effects on cell proliferation and migration. We found that plasma sEGFR was significantly decreased in the NSCLC patient group as compared to the control group (median value: 48.6 vs. 55.6 ng/mL respectively; p = 0.0002). Moreover, we demonstrated that sEGFR inhibits growth and migration of NSCLC cells in vitro through molecular mechanisms that included perturbation of EGF/EGFR cell signaling and holoreceptor internalization. These data show that sEGFR is a potential circulating biomarker with a physiological protective role, providing a first approach to the functional role of the soluble isoform of EGFR. However, the impact of these data on daily clinical practice needs to be further investigated in larger prospective studies.     

Modelling of effects of ultrastructural morphology on the hygroelastic properties of wood fibres

Wood fibres constitute the structural framework of e.g. wood, paper, board and composites, where stiffness and dimensional stability are of importance. An analytical modelling approach has been used for prediction of hygroelastic response, and assessment of the stresses in thick-walled cylinder models of wood fibres. A wood fibre was idealised as a multilayered hollow cylinder made of orthotropic material with helical orientation. The hygroelastic response of the layered assembly due to axisymmetric loading and moisture content changes was obtained by solving the corresponding boundary value problem of elasticity. A simple solution scheme based on the state space approach and the transfer matrix method was employed. This was combined with an analytical ultrastructural homogenisation method, used to link hygroelastic properties of constituent wood polymers to properties of each layer. Predicted hygroelastic response captured experimentally measured behaviour. Fibres that were constrained not to twist showed a stiffer response than fibres allowed twisting under uniaxial loading. It was also shown that the ultrastructure, i.e. the microfibril angle, will control the hygroexpansion in the same way as it controls the compliance of the cell wall. Qualitative failure trends comparable with experimental observations could be established with stress analysis and a simple plane-stress failure criterion.     

Stochastic molecular descriptors for polymers. 4. Study of complex mixtures with topological indices of mass spectra spiral and star networks: The blood proteome case

The Quantitative Structure-Property Relationships (QSPRs) based on Graph or Network Theory are important for predicting the properties of polymeric systems. In the three previous papers of this series (Polymer 45 (2004) 3845-3853; Polymer 46 (2005) 2791-2798; and Polymer 46 (2005) 6461-6473) we focused on the uses of molecular graph parameters called topological indices (TIs) to link the structure of polymers with their biological properties. However, there has been little effort to extend these TIs to the study of complex mixtures of artificial polymers or biopolymers such as nucleic acids and proteins. In this sense, Blood Proteome (BP) is one of the most important and complex mixtures containing protein polymers. For instance, outcomes obtained by Mass Spectrometry (MS) analysis of BP are very useful for the early detection of diseases and drug-induced toxicities. Here, we use two Spiral and Star Network representations of the MS outcomes and defined a new type of TIs. The new TIs introduced here are the spectral moments (π_k) of the stochastic matrix associated to the Spiral graph and describe non-linear relationships between the different regions of the MS characteristic of BP. We used the MARCH-INSIDE approach to calculate the π_k(SN) of different BP samples and S2SNet to determine several Star graph TIs. In the second step, we develop the corresponding Quantitative Proteome-Property Relationship (QPPR) models using the Linear Discriminant Analysis (LDA). QPPRs are the analogues of QSPRs in the case of complex biopolymer mixtures. Specifically, the new QPPRs derived here may be used to detect drug-induced cardiac toxicities from BP samples. Different Machine Learning classification algorithms were used to fit the QPPRs based on π_k(SN), showing J48 decision tree classifier to have the best performance. These results suggest that the present approach captures important features of the complex biopolymers mixtures and opens new opportunities to the application of the idea supporting classic QSPRs in polymer sciences.     

A survey on approaches to gridification

The Grid shows itself as a globally distributed computing environment, in which hardware and software resources are virtualized to transparently provide applications with vast capabilities. Just like the electrical power grid, the Grid aims at offering a powerful yet easy‐to‐use computing infrastructure to which applications can be easily ‘plugged’ and efficiently executed. Unfortunately, it is still very difficult to Grid‐enable applications, since current tools force users to take into account many details when adapting applications to run on the Grid. In this paper, we survey some of the recent efforts in providing tools for easy gridification of applications and propose several taxonomies to identify approaches followed in the materialization of such tools. We conclude this paper by describing common features among the proposed approaches, and by pointing out open issues and future directions in the research and development of gridification methods. Copyright © 2007 John Wiley & Sons, Ltd.     

Adenovirus-Mediated Inducible Expression of a PD-L1 Blocking Antibody in Combination with Macrophage Depletion Improves Survival in a Mouse Model of Peritoneal Carcinomatosis

Immune checkpoint inhibitors (ICIs) have demonstrated remarkable efficacy in a growing number of malignancies. However, overcoming primary or secondary resistances is difficult due to pharmacokinetics issues and side effects associated with high systemic exposure. Local or regional expression of monoclonal antibodies (mAbs) using gene therapy vectors can alleviate this problem. In this work, we describe a high-capacity adenoviral vector (HCA-EFZP-aPDL1) equipped with a mifepristone-inducible system for the controlled expression of an anti-programmed death ligand 1 (PD-L1) blocking antibody. The vector was tested in an immune-competent mouse model of colorectal cancer based on implantation of MC38 cells. A single local administration of HCA-EFZP-aPDL1 in subcutaneous lesions led to a significant reduction in tumor growth with minimal release of the antibody in the circulation. When the vector was tested in a more stringent setting (rapidly progressing peritoneal carcinomatosis), the antitumor effect was marginal even in combination with other immune-stimulatory agents such as polyinosinic-polycytidylic acid (pI:C), blocking mAbs for T cell immunoglobulin, mucin-domain containing-3 (TIM-3) or agonistic mAbs for 4-1BB (CD137). In contrast, macrophage depletion by clodronate liposomes enhanced the efficacy of HCA-EFZP-aPDL1. These results highlight the importance of addressing macrophage-associated immunoregulatory mechanisms to overcome resistance to ICIs in the context of colorectal cancer.     

Well-Known and Novel Serum Biomarkers for Risk Stratification of Patients with Non-ischemic Dilated Cardiomyopathy

Non-ischemic dilated cardiomyopathy encompasses a wide spectrum of myocardial disorders, characterized by left ventricular dilatation with systolic impairment and increased risk of sudden cardiac death. In spite of all the therapeutic progress that has been made in recent years, dilated cardiomyopathy continues to be an important cause of cardiac transplant, being associated with an enormous cost burden for health care systems worldwide. Predicting the prognosis of patients with dilated cardiomyopathy is essential to individualize treatment. Late gadolinium enhancement-cardiac magnetic resonance imaging, microvolt T-wave alternans, and genetic testing have emerged as powerful tools in predicting sudden cardiac death occurrence and maximizing patient’s selection. Despite all these new diagnostic modalities, additional tests to complement or replace current tools are required for better risk stratification. Therefore, biomarkers are an easy and important tool that can help to detect patients at risk of adverse cardiovascular events. Additionally, identifying potential biomarkers involved in dilated cardiomyopathy can provide us important information regarding the diagnostic, prognostic, risk stratification, and response to treatment for these patients. Many potential biomarkers have been studied in patients with dilated cardiomyopathy, but only a few have been adopted in current practice. Therefore, the aim of our review is to provide the clinicians with an update on the well-known and novel biomarkers that can be useful for risk stratification of patients with non-ischemic dilated cardiomyopathy.     

A universal design resource for rich Internet applications based on design patterns

Rich Internet applications have removed most of the constraints of Web 1.0 while giving users more responsiveness and advanced browsing and interaction experiences. These new horizons, however, raise many challenges for people with disabilities or using limited hardware and software technologies, whose risk to be excluded from the benefits deriving from advanced web applications. To address this problem, WCAG 2.0 guidelines have been released as the newest World Wide Web Consortium recommendation for accessible web content, and WAI-ARIA is a candidate recommendation which provides reference specifications for accessible rich Internet applications. However, both specifications contain a huge amount of information that often discourages most web designers from dealing with accessibility issues. Moreover, guidelines are suitable and usually adopted to judge a design solution a posteriori, but they do not suggest how to face a design problem constructively. This paper proposes a design pattern language for accessibility. The language can be regarded as a universal design resource for helping web designers create accessible rich Internet applications compliant with the most recent standards. Knowledge representation through design patterns reflects the problem-solving approach usually followed by software and web designers, while pattern organization in a structured language aims to guide web designers throughout the design process. The language has been implemented as an accessible rich Internet application itself, thus allowing designers with disabilities to participate in web design. In order to evaluate the design pattern language, a three-step process was carried out including: (1) a heuristic analysis with a group of human–computer interaction experts, (2) a survey study with a group of web designers, and (3) a validation on the field with two designers who have been requested to apply the language in real design cases.