Neuroinflammation and Hypothalamo-Pituitary Dysfunction: Focus of Traumatic Brain Injury

The incidence of traumatic brain injury (TBI) has increased over the last years with an important impact on public health. Many preclinical and clinical studies identified multiple and heterogeneous TBI-related pathophysiological mechanisms that are responsible for functional, cognitive, and behavioral alterations. Recent evidence has suggested that post-TBI neuroinflammation is responsible for several long-term clinical consequences, including hypopituitarism. This review aims to summarize current evidence on TBI-induced neuroinflammation and its potential role in determining hypothalamic-pituitary dysfunctions.     

Design guidelines of CMOS class-AB output stages: a tutorial

This article presents useful guidelines for designing CMOS class-AB output stages. Three Quality Factors, which allow analysis and comparison of different output stages, are used to design two CMOS class-AB stages. We show that using the proposed Quality Factors and the related strategy leads to an efficient design in terms trade-off among area, current consumption, bandwidth and distortion. Indeed, for one of the two stages adopted as example, the design through the Quality Factors results in superior distortion performance with respect to the design suggested in the original article. Design examples and simulations are provided to validate the design strategy.     

Temperature Effect on Concrete Creep Modeled by Microprestress-Solidification Theory

The previously developed microprestress-solidification theory for concrete creep and shrinkage is generalized for the effect of temperature (not exceeding 100°C). The solidification model separates the viscoelasticity of the solid constituent, the cement gel, from the chemical aging of material caused by solidification of cement and characterized by the growth of volume fraction of hydration products. This permits considering the viscoelastic constituent as non-aging. The temperature dependence of the rates of creep and of volume growth is characterized by two transformed time variables based on the activation energies of hydration and creep. The concept of microprestress achieves a grand unification of theory in which the long-term aging and all transient hygrothermal effects simply become different consequences of one and the same physical phenomenon. The microprestress, which is independent of the applied load, is initially produced by incompatible volume changes in the microstructure during hydration, and later builds up when changes of moisture content and temperature create a thermodynamic imbalance between the chemical potentials of vapor and adsorbed water in the nanopores of cement gel. As recently shown, this simultaneously captures two basic effects: First, the creep decreases with increasing age at loading after the growth of the volume fraction of hydrated cement has ceased; and, second, the drying creep, i.e., the transient creep increases due to drying (Pickett effect) which overpowers the effect of steady-state moisture content (i.e., less moisture—less creep). Now it is demonstrated that the microprestress buildup and relaxation also captures a third effect: The transitional thermal creep, i.e., the transient creep increase due to temperature change. For computations, an efficient (exponential-type) integration algorithm is developed. Finite element simulations, in which the apparent creep due to microcracking is taken into account separately, are used to identify the constitutive parameters and a satisfactory agreement with typical test data is achieved.     

A software development system based on a macroprocessor

In this paper a system for software development is described. This system consists of a general-purpose macroprocessor and a set of service programs. The macroprocessor has been planned to work in a conversational environment and to this purpose a set of utilities has been inserted to aid the editing and the debugging of the macrodefinitions. Indeed the system allows the user to select, by means of commands, the flow of the operations to be executed and to choose when and how any program has to be expanded. The macroprocessor is easy to use and it is suitable to generate codes for both high-level languages and assembler languages.     

Artificial neural network for the second virial coefficient of organic and inorganic compounds: An ANN for B of organic and inorganic compounds

An artificial neural network (ANN) to estimate the second virial coefficient, valid for organic and inorganic compounds, is presented. First, we statistically analyzed 6,531 experimental points, belonging to 234 fluids, collected from literature. The data were investigated with a factor analysis approach to identify the most significant parameters that influence the second virial coefficient. The factor analysis, combined with physical considerations, allowed to find four (T_r, T_c, P_c, ω) or five (μ_r) parameters as input variables for the ANN, according to the specific chemical family. The architecture of the proposed multi-layers perceptron (MLP) neural network consists of one input layer with five input variables (T_r, T_c, P_c, ω, μ_r), one output layer with one neuron (B) and two-hidden-layers with 19 neurons each. We trained, validated and tested several configurations of the neural network to obtain this network topology that minimizes the deviations between experimental and calculated points. Results show that the ANN is able to calculate the second virial coefficient with greater accuracy (RMSE?=?29.38?cm³/mol) than that of correlations available in literature. To identify the outliers and applicability domain of the proposed MLP neural network, an outlier diagnosis based on the Leverage approach was performed. This analysis shows that the model is statistically valid.     

Development of Potent Inhibitors of the Mycobacterium tuberculosis Virulence Factor Zmp1 and Evaluation of Their Effect on Mycobacterial Survival inside Macrophages

The enzyme Zmp1 is a zinc‐containing peptidase that plays a critical role in the pathogenicity of Mycobacterium tuberculosis. Herein we describe the identification of a small set of Zmp1 inhibitors based on a novel 8‐hydroxyquinoline‐2‐hydroxamate scaffold. Among the synthesized compounds, N‐(benzyloxy)‐8‐hydroxyquinoline‐2‐carboxamide ( 1 c ) was found to be the most potent Zmp1 inhibitor known to date, and its binding mode was analyzed both by kinetics studies and molecular modeling, identifying critical interactions of 1 c with the zinc ion and residues in the active site. The effect of 1 c on intracellular Mycobacterium survival was assayed in J774 murine macrophages infected with M. tuberculosis H37Rv or M. bovis BCG and human monocyte‐derived macrophages infected with M. tuberculosis H37Rv. Cytotoxicity and genotoxicity were also assessed. Overall, inhibitor 1 c displays interesting in vitro antitubercular properties worthy of further investigation.     

A remote scanning Raman spectrometer for in situ measurements of works of art

In conservation science, one of the main concerns is to extract information from an artistic surface without damaging it. Raman spectroscopy has emerged in recent years as a reliable tool for the non-destructive analysis of a wide range of inorganic and organic materials in works of art and archaeological objects. Nevertheless, the technique is still mainly limited to the analysis of micro-samples taken from artistic surfaces. The development of an instrument able to perform non-contact analysis of an area of a few square centimeters aims to further increase the employment of this technique. This paper describes the development of a prototype Raman scanning spectrometer based on a diode laser, a 2D scanning mirror stage and a custom optical system, which can map a surface of 6 cm in diameter at a working distance of 20 cm. The device exhibits collecting optics with a depth of field close to 6 cm, which makes the Raman system suitable for the analysis of non-flat surfaces and three-dimensional objects. In addition, the overall dimensions and weight of the instrument have been limited in order to make the device transportable and, in principle, usable for in situ measurements. Details on the design of the device, with particular emphasis on the collecting optical system, and on results of the characterization tests carried out to assess its performances are reported. Finally, an example of an application involving the identification of pigments from a model painting is presented.     

Exploiting OpenMP and OpenACC to accelerate a geometric approach to molecular docking in heterogeneous HPC nodes

The Journal of Supercomputing - In drug discovery, molecular docking is the task in charge of estimating the position of a molecule when interacting with the docking site. This task is usually used...     

Verifying data secure flow in AUTOSAR models

This paper presents an approach for enhancing the design phase of AUTOSAR models when security annotations are required. The approach is based on information flow analysis and abstract interpretation. The analysis evaluates the correctness of the model by assessing if the flow of data is secure with respect to causal data dependencies within the model. To find these dependencies an exhaustive search through the model would be required. Abstract interpretation is used as a trade-off between the precision and complexity of the analysis. The approach also provides annotated models without oversizing the set of annotations.     

An effective extension of the applicability of alignment-free biological sequence comparison algorithms with Hadoop

Alignment-free methods are one of the mainstays of biological sequence comparison, i.e., the assessment of how similar two biological sequences are to each other, a fundamental and routine task in computational biology and bioinformatics. They have gained popularity since, even on standard desktop machines, they are faster than methods based on alignments. However, with the advent of Next-Generation Sequencing Technologies, datasets whose size, i.e., number of sequences and their total length, is a challenge to the execution of alignment-free methods on those standard machines are quite common. Here, we propose the first paradigm for the computation of k-mer-based alignment-free methods for Apache Hadoop that extends the problem sizes that can be processed with respect to a standard sequential machine while also granting a good time performance. Technically, as opposed to a standard Hadoop implementation, its effectiveness is achieved thanks to the incremental management of a persistent hash table during the map phase, a task not contemplated by the basic Hadoop functions and that can be useful also in other contexts.