Caracterização da estrutura sub-superficial da ilha do Faial (Açores)

The aim of this communication is to present the velocity models of propagation of seismic waves P and S using geophysical methods, such as refraction surveys, MASW (Multichannel Analysis of Surface Waves), and Horizontal-to-Vertical spectral ratio ambient-noise in Faial Island (Azores). After determining the velocity models and ratios H/V, the results were compared for the same location, with previous works of ambient-noise and with lithology of the island. These results providing important physical parameters for a near surface characterization of the soil structure and to predict seismic ground motion in this region

Advances achieved by ionic-liquid-based materials as alternative supports and purification platforms for proteins and enzymes

Ionic liquids (ILs) have been applied in several fields in which enzymes and proteins play a noteworthy role, for instance in biorefinery, biotechnology, and pharmaceutical sciences, among others. Despite their use as solvents and co-solvents, their combination with materials for protein- and enzyme-based applications has raised significant attention in the past few years. Among them, significant advances were brought by supported ionic liquids (SILs), in which ILs are introduced to modify the surface and properties of materials, e.g., as ligands when covalently bond or when physiosorbed. SILs have been mainly investigated as alternative supports for enzymes in biocatalysis and as new supports in preparative liquid chromatography for the purification of high-value proteins and enzymes. In this manuscript, we provide an overview on the most relevant advances by using SILs as supports for enzymes and as purification platforms for a variety of proteins and enzymes. The interaction mechanisms occurring between proteins and SILs/ILs are highlighted, allowing the design of efficient processes involving SILs. The work developed is discussed in light of the respective development phase and innovation level of the applied technologies. Advantages and disadvantages are identified, as well as the missing links to pave their use in relevant applications.publishe

Reusability of L-asparaginase immobilized on silica-based supported ionic liquids

L-asparaginase (ASNase) is an aminohydrolase enzyme used as an anticancer drug, e.g. in the treatment of acute lymphoblastic leukemia, in acrylamide reduction and in biosensing. Nevertheless, its low stability and thermolability, and susceptibility to proteases, hinder its application in the health and food industries. Hence, the improvement of its properties through efficient immobilization methods is in high demand. Thus, this work aims the development of silica-based supported ionic liquids (SILs) for the ASNase immobilization to improve its stability and enable its reusability. While activated silica with no ILs only kept total initial ASNase activity during the first cycle of reaction, SILs allowed 5 cycles of reaction, keeping 82% of initial ASNase activity, reinforcing their potential as alternative enzymatic supports.publishe

Enhanced enzyme reuse through the bioconjugation of L-asparaginase and silica-based supported ionic liquid-like phase materials

L-asparaginase (ASNase) is an amidohydrolase that can be used as a biopharmaceutical, as an agent for acrylamide reduction, and as an active molecule for L-asparagine detection. However, its free form displays some limitations, such as the enzyme’s single use and low stability. Hence, immobilization is one of the most effective tools for enzyme recovery and reuse. Silica is a promising material due to its low-cost, biological compatibility, and tunable physicochemical characteristics if properly functionalized. Ionic liquids (ILs) are designer compounds that allow the tailoring of their physicochemical properties for a given task. If properly designed, bioconjugates combine the features of the selected ILs with those of the support used, enabling the simple recovery and reuse of the enzyme. In this work, silica-based supported ionic liquid-like phase (SSILLP) materials with quaternary ammoniums and chloride as the counterion were studied as novel supports for ASNase immobilization since it has been reported that ammonium ILs have beneficial effects on enzyme stability. SSILLP materials were characterized by elemental analysis and zeta potential. The immobilization process was studied and the pH effect, enzyme/support ratio, and contact time were optimized regarding the ASNase enzymatic activity. ASNase–SSILLP bioconjugates were characterized by ATR-FTIR. The bioconjugates displayed promising potential since [Si][N3444]Cl, [Si][N3666]Cl, and [Si][N3888]Cl recovered more than 92% of the initial ASNase activity under the optimized immobilization conditions (pH 8, 6 × 10−3 mg of ASNase per mg of SSILLP material, and 60 min). The ASNase–SSILLP bioconjugates showed more enhanced enzyme reuse than reported for other materials and immobilization methods, allowing five cycles of reaction while keeping more than 75% of the initial immobilized ASNase activity. According to molecular docking studies, the main interactions established between ASNase and SSILLP materials correspond to hydrophobic interactions. Overall, it is here demonstrated that SSILLP materials are efficient supports for ASNase, paving the way for their use in the pharmaceutical and food industries.publishe

Mycobacterial dihydrofolate reductase inhibitors identified using chemogenomic methods and in vitro validation.

The lack of success in target-based screening approaches to the discovery of antibacterial agents has led to reemergence of phenotypic screening as a successful approach of identifying bioactive, antibacterial compounds. A challenge though with this route is then to identify the molecular target(s) and mechanism of action of the hits. This target identification, or deorphanization step, is often essential in further optimization and validation studies. Direct experimental identification of the molecular target of a screening hit is often complex, precisely because the properties and specificity of the hit are not yet optimized against that target, and so many false positives are often obtained. An alternative is to use computational, predictive, approaches to hypothesize a mechanism of action, which can then be validated in a more directed and efficient manner. Specifically here we present experimental validation of an in silico prediction from a large-scale screen performed against Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis. The two potent anti-tubercular compounds studied in this case, belonging to the tetrahydro-1,3,5-triazin-2-amine (THT) family, were predicted and confirmed to be an inhibitor of dihydrofolate reductase (DHFR), a known essential Mtb gene, and already clinically validated as a drug target. Given the large number of similar screening data sets shared amongst the community, this in vitro validation of these target predictions gives weight to computational approaches to establish the mechanism of action (MoA) of novel screening hit

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/c charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1 ± 0.6 % and 84.1 ± 0.6 %, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 103 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype