Imaging of the optic disc and retinal nerve fiber layer: the effects of age, optic disc area, refractive error, and gender.

We cross-sectionally examined the relationship between age, optic disc area, refraction, and gender and optic disc topography and retinal nerve fiber layer (RNFL) measurements, using optical imaging techniques. One eye from each of 155 Caucasian subjects (age range 23.0-80.8 y) without ocular pathology was included. Measurements were obtained by using the Heidelberg Retina Tomography (HRT), the GDx Nerve Fiber Analyzer, and the Optical Coherence Tomograph (OCT). The effects of age were small (R2 < 17%) and were limited to specific HRT, GDx, and OCT parameters. Disc area was significantly associated with most HRT parameters and isolated GDx and OCT parameters. Refraction and gender were not significantly associated with any optic disc or RNFL parameters. Although effects of age on the optic disc and RNFL are small, they should be considered in monitoring ocular disease. Optic disc area should be considered when cross-sectionally evaluating disc topography and, to a lesser extent, RNFL thickness.     

Bacterial polymers as materials for the development of micro/nanoparticles

Bacterial polysaccharides and polyhydroxyalkanoates present physical and chemical characteristics that impart them diverse functional properties, including the ability to produce structures from nano- to macroscale (e.g., spheres, capsules, beads). Such structures may be specially designed to fulfill the requirements of specific applications in different areas, either alone or conjugated with other polymers by means of ionic interactions, hydrogen bonding, or chemical reactions. The interest on using such biomaterials has been increasing due to their unique functional properties, nontoxicity, biodegradability, and biocompatibility. The fields of application of bacterial polymers-based structures include drug delivery, biomedicine, food products, environment, and agriculture, among others.     

Targeting the DNA Damage Response to Increase Anthracycline-Based Chemotherapy Cytotoxicity in T-Cell Lymphoma

Mature T-cell lymphomas (MTCLs) represent a heterogeneous group of aggressive non-Hodgkin lymphomas comprising different entities. Anthracycline-based regimens are considered the standard of care in the front-line treatment. However, responses to these approaches have been neither adequate nor durable, and new treatment strategies are urgently needed to improve survival. Genomic instability is a common feature of cancer cells and can be caused by aberrations in the DNA damage response (DDR) and DNA repair mechanisms. Consistently, molecules involved in DDR are being targeted to successfully sensitize cancer cells to chemotherapy. Recent studies showed that some hematological malignancies display constitutive DNA damage and intrinsic DDR activation, but these features have not been investigated yet in MTCLs. In this study, we employed a panel of malignant T cell lines, and we report for the first time the characterization of intrinsic DNA damage and basal DDR activation in preclinical models in T-cell lymphoma. Moreover, we report the efficacy of targeting the apical kinase ATM using the inhibitor AZD0156, in combination with standard chemotherapy to promote apoptotic cell death. These findings suggest that DDR is an attractive pathway to be pharmacologically targeted when developing novel therapies and improving MTCL patients’ outcomes.     

Fatty Acids,CD36, Thrombospondin-1, and CD47 in Glioblastoma: Together and/or Separately?

Glioblastoma (GBM) is one of the most aggressive tumors of the central nervous system, characterized by a wide range of inter- and intratumor heterogeneity. Accumulation of fatty acids (FA) metabolites was associated with a low survival rate in high-grade glioma patients. The diversity of brain lipids, especially polyunsaturated fatty acids (PUFAs), is greater than in all other organs and several classes of proteins, such as FA transport proteins (FATPs), and FA translocases are considered principal candidates for PUFAs transport through BBB and delivery of PUFAs to brain cells. Among these, the CD36 FA translocase promotes long-chain FA uptake as well as oxidated lipoproteins. Moreover, CD36 binds and recognizes thrombospondin-1 (TSP-1), an extracellular matrix protein that was shown to play a multifaceted role in cancer as part of the tumor microenvironment. Effects on tumor cells are mediated by TSP-1 through the interaction with CD36 as well as CD47, a member of the immunoglobulin superfamily. TSP-1/CD47 interactions have an important role in the modulation of glioma cell invasion and angiogenesis in GBM. Separately, FA, the two membrane receptors CD36, CD47, and their joint ligand TSP-1 all play a part in GBM pathogenesis. The last research has put in light their interconnection/interrelationship in order to exert a cumulative effect in the modulation of the GBM molecular network.     

Self-Adaptive Fault Tolerance in Multi-/Many-Core Systems

This paper presents a novel approach to the design of multi-/many-core systems with an adaptive level of reliability. The approach defines a layer at the operating system level that achieves fault detection/tolerance/diagnosis properties by means of thread replication and re-execution mechanisms. The layer applies the most convenient hardening mechanism to achieve the desired trade-off between reliability and performance by adapting at run-time to the changes of the working scenario. The proposed strategy has been applied in a set of experimental sessions considering a real-world parallel application, to evaluate its benefits on the final system with respect to various strategies selected at design time.     

On the optimal design of water distribution networks: a practical MINLP approach

We propose a practical solution method for real-world instances of a water-network optimization problem with fixed topology using a nonconvex continuous NLP (NonLinear Programming) relaxation and a MINLP (Mixed Integer NonLinear Programming) search. Our approach employs a relatively simple and accurate model that pays some attention to the requirements of the solvers that we employ. Our view is that in doing so, with the goal of calculating only good feasible solutions, complicated algorithmics can be confined to the MINLP solver. We report successful computational experience using available open-source MINLP software on problems from the literature and on difficult real-world instances. An important contribution of this paper is that the solutions obtained, besides being low cost, are immediately usable in practice because they are characterized by an allocation of diameters to pipes that leads to a correct hydraulic operation of the network. This is not the case for most of the other methods presented in the literature.     

Multi-Criteria Decision Making support system for pancreatic islet transplantation

Pancreatic islet transplantation consists of replacing insulin-producing cells to restore normal glycemia in diabetic patients. This is a minimal invasive procedure that has been proved successful. Unfortunately unpredictability of islet transplant outcome remains a frustrating and costly issue limiting the clinical implementation of this procedure. Multiple variables are involved in the procedure and assessment is subjective to individual operators. The aim of this study was to generate a system expressing the probability of transplant success in relation to four classes of identified variables (donor, organ, isolation and recipient). We have proposed the utilization of Multi-Criteria Decision Making methods (MCDM) as a powerful tool for evaluating pancreatic islet transplant-related information with the goal to achieve optimal decision. Technique Ordered Preference by Similarity to the Ideal Solution (TOPSIS), one of the most widely used MCDM methods in decision support systems, was here utilized with modification to fit better in a medical system. In our modified method, we have utilized fuzzy logic in order to consider uncertain and vague data.     

Effects of structural features of cotton cellulose on enzymatic hydrolysis

Textile cotton wastes were treated with γ rays and 18% NaOH and 70% ZnCl₂ solutions and were subjected to enzymatic hydrolysis. The untreated and treated samples were characterized both before and after hydrolysis by means of parameters concerning molecular structure (degree of polymerization), supermolecular structure (x-ray diffraction), accessibility, and reactivity (moisture regain, enzyme adsorption, and solubility in FeTNa). These parameters were correlated to kinetic parameters of the hydrolysis reaction. The V_max and K_m values were evaluated from Lineweaver–Burk plots at different temperatures. The V_max/K_m ratio, analogous to the specificity constant, proved to be less sensitive to experimental errors and more suitable for a comparison of the kinetic behavior of the samples. The modifications of both supermolecular structure and morphology of cellulose were of primary importance to attain high yields and rates of hydrolysis. Furthermore, the structural and morphologic parameters chosen to characterize the samples can be correlated to the kinetic parameters of enzymatic hydrolysis, in particular to K_m values.     

The Experience in Designing and Evaluating the High Performance Cluster Netuno

This paper presents the Netuno supercomputer, a large-scale cluster installed at Federal University of Rio de Janeiro in Brazil. A detailed performance evaluation of Netuno is presented, depicting its computational and I/O performance, as well as the results for two real-world applications. Since building a high- performance cluster for running a wide range of applications is a non-trivial task, some lessons learned from assembling and operating this cluster, such as the excellent performance of the OpenMPI library, and the relevance of employing an efficient parallel file system over the traditional NFS system, can be useful knowledge to support the design of new systems. Currently, Netuno is being heavily used to run large scale simulations in the areas of ocean modeling, meteorology, engineering, physics, and geophysics.