Immunohistochemical Analysis of DNA Repair- and Drug-Efflux-Associated Molecules in Tumor and Peritumor Areas of Glioblastoma

Glioblastoma (GBM), the most commonly occurring primary tumor arising within the central nervous system, is characterized by high invasiveness and poor prognosis. In spite of the improvement in surgical techniques, along with the administration of chemo- and radiation therapy and the incessant investigation in search of prospective therapeutic targets, the local recurrence that frequently occurs within the peritumoral brain tissue makes GBM the most malignant and terminal type of astrocytoma. In the current study, we investigated both GBM and peritumoral tissues obtained from 55 hospitalized patients and the expression of three molecules involved in the onset of resistance/unresponsiveness to chemotherapy: O6-methylguanine methyltransferase (MGMT), breast cancer resistance protein (BCRP1), and A2B5. We propose that the expression of these molecules in the peritumoral tissue might be crucial to promoting the development of early tumorigenic events in the tissue surrounding GBM as well as responsible for the recurrence originating in this apparently normal area and, accordingly, for the resistance to treatment with the standard chemotherapeutic regimen. Notably, the inverse correlation found between MGMT expression in peritumoral tissue and patients’ survival suggests a prognostic role for this protein.     

Kinetics and Heat Exchanger Design for Catalytic Ortho‐Para Hydrogen Conversion during Liquefaction

A major challenge for hydrogen liquefaction is the required catalytic ortho‐para hydrogen conversion. Efficient liquefaction plants use catalyst‐filled plate‐fin heat exchangers for the conversion. Kinetics of the allotropic reaction are determined using raw literature data on common first‐order and a Langmuir‐Hinshelwood kinetics, including temperature and molar concentration dependencies. Evaluation and comparison of the obtained kinetics results in the first‐order approach as the most stable model. A one‐dimensional continuum reactor model of the counterflow‐cooled, catalyst‐filled plate‐fin heat exchanger is developed and tested combining correlations for heat, mass, and momentum transfer as well as a state‐of‐the‐art equation‐of‐state.     

A Coupled 3-D PNP/ECP Model for Ion Transport in Biological Ion Channels

The Poisson-Nernst-Planck (PNP) or Drift-Diffusion theory can be used to compute macroscopic current in ion channels in an efficient manner. The major drawback of the standard PNP theory is that it is based on a continuum model for the charge flow, therefore it models ions as a gas of point particles. Water is also not simulated explicitly, but introduced as a background medium with a given permittivity. The PNP model can be modified to include effects of finite ion size and water occupation by including a correction term, the Excess Chemical Potential (ECP), in the standard model. Gillespie et al. [1] developed a model for ECP correction, based on Density Functional theory, which is introduced in an existing 3-D PNP solver for ion transport in biological ion channels realized using the numerical computational platform PROPHET. Since incorporation of the ECP correction directly into the PNP matrix formulation is not an easy task, for demonstration purposes we developed a relatively simple decoupled relaxed iteration algorithm. Preliminary tests were conducted on idealized channel geometries, showing how the adopted ECP correction model alters significantly the ion densities inside the channel from those predicted by the conventional PNP theory alone.     

用二维全带组合Monte Carlo方法模拟纤锌矿相GaN静电感应晶体管(SIT)特性

报告了用二维全带组合Monte Carlo方法模拟纤锌矿相GaN静电感应晶体管(SITs)交直流特性的结果.SIT的栅极长度为0.13μm,源极和漏极之间距离为0.5μm.模拟得到了SIT的输出特性,跨导和特征频率特性.模拟得到的跨导最大值为140ms/mm(Vgs=-1.5V),器件特征频率最大值为123GHz(I_ds=3.15A/cm).模拟结果表明纤锌矿相GaN SIT具有大功率和高频工作的潜力.     

Incorporation of Mg-Al hydrotalcite into a biodegradable Poly(ε-caprolactone) by high energy ball milling

The technique of high energy ball milling (HEBM) was used to prepare nanocomposites of poly(ε-caprolactone) (PCL) and an organically modified Mg-Al layered double hydroxide. The amount of inorganic material was varied from 0 to 6 wt%, and the samples were melted and quenched in ice-water after milling. The molecular weight of PCL decreased and its distribution increased as a consequence of milling. The structural analysis of the milled samples, conducted by X-ray diffraction and infrared absorption techniques, showed that the 12 hydroxydodecanoates organic modifier was still attached to the inorganic lamellae even if a partial delamination of the layered compounds occurred. The mechanical parameters (modulus, stress at yield point, strain at break point and stress at break values) derived from the stress-strain curves, improved in the composite samples containing up to 2.8 wt% of inorganic filler, with respect to the pure polymer, in spite of the molecular weight decrease. The thermodynamic diffusion coefficient of water vapor in composite samples was lower than in pure PCL, indicating an improvement of the barrier effect.     

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.     

A New Indicator for Unsteady Flow Analysis in Pressurized Irrigation Systems

Pressurized irrigation systems operating on-demand offer large flexibility to farmers for managing their irrigation practices. Within these systems, the fast moving water and the sudden closing of hydrants generates unsteady flow and may create a significant pressure variation in the pipes causing noise, vibration and, sometimes, also pipes’ collapse. The present study describes a simulation tool that was developed for the analysis of unsteady flow effects. A large number of configurations of hydrants simultaneously open has been used to reflect farmers’ behaviour. A new indicator, called Relative Pressure Variation (RPV), was proposed to evaluate the pressure variation occurring into the system in respect to the steady-state pressure. This is very relevant and can be used to identify pipes with potential risk of failure. In addition, an analysis with different gate-valves’ closing time was carried out. It demonstrated that closing time shorter than Tc?=?3 s may create dangerous pressures for the pipes.