Effect of chemical treatments on physical properties of kenaf bast fibres

In the present study, kenaf bast fibre surfaces have been modified using different chemicals with varying concentration. The effects of these chemical treatments on moisture content, water absorption, fibre diameter and bundle strength are investigated. The benefit of chemical treatments in the removal of impurities from the fibre surfaces has been established by scanning electron microscopy. It is found that the fibres treated with sodium hydroxide and acetic acid show major effect on fibre diameter. Compared to untreated kenaf fibre, strong alkali (NaOH) treatment show maximum water absorption (78.76%) and moisture content (8.15%). In fibre bundle tensile strength, sodium hydroxide and sodium carbonate treated fibres show more than 80% improvement in the tensile strength of fibre. Kenaf fibre treated with 10% Na2CO3 show highest tensile strength of 410 MPa

Bioinspired Magneto-optical Bacteria

“Two-in-one” magneto-optical bacteria have been produced using the probiotic Lactobacillus fermentum for the first time. We took advantage of two features of bacteria to synthesize this novel and bifunctional nanostructure: their metal-reducing properties, to produce gold nanoparticles, and their capacity to incorporate iron oxide nanoparticles at their external surface. The magneto-optical bacteria survive the process and behave as a magnet at room temperature.This work was funded by Biosearch S.A. (POSTBIO project-Agency for Innovation and Development of Andalucia IDEA) and by MINECO and FEDER (project CTQ2012-32236)

Adaptation of High-Throughput Screening in Drug Discovery—Toxicological Screening Tests

High-throughput screening (HTS) is one of the newest techniques used in drug design and may be applied in biological and chemical sciences. This method, due to utilization of robots, detectors and software that regulate the whole process, enables a series of analyses of chemical compounds to be conducted in a short time and the affinity of biological structures which is often related to toxicity to be defined. Since 2008 we have implemented the automation of this technique and as a consequence, the possibility to examine 100,000 compounds per day. The HTS method is more frequently utilized in conjunction with analytical techniques such as NMR or coupled methods e.g., LC-MS/MS. Series of studies enable the establishment of the rate of affinity for targets or the level of toxicity. Moreover, researches are conducted concerning conjugation of nanoparticles with drugs and the determination of the toxicity of such structures. For these purposes there are frequently used cell lines. Due to the miniaturization of all systems, it is possible to examine the compound’s toxicity having only 1–3 mg of this compound. Determination of cytotoxicity in this way leads to a significant decrease in the expenditure and to a reduction in the length of the study

High throughput automated microbial bioreactor system used for clone selection and rapid scale-down process optimization

High throughput automated fermentation systems have become a useful tool in early bioprocess development. In this study, we investigated a 24 x 15 mL single use microbioreactor system, ambr 15f, designed for microbial culture. We compared the fed-batch growth and production capabilities of this system for two Escherichia coli strains, BL21 (DE3) and MC4100, and two industrially relevant molecules, hGH and scFv. In addition, different carbon sources were tested using bolus, linear or exponential feeding strategies, showing the capacity of the ambr 15f system to handle automated feeding. We used power per unit volume (P/V) as a scale criterion to compare the ambr 15f with 1 L stirred bioreactors which were previously scaled-up to 20 L with a different biological system, thus showing a potential 1,300 fold scale comparability in terms of both growth and product yield. By exposing the cells grown in the ambr 15f system to a level of shear expected in an industrial centrifuge, we determined that the cells are as robust as those from a bench scale bioreactor. These results provide evidence that the ambr 15f system is an efficient high throughput microbial system that can be used for strain and molecule selection as well as rapid scale-u

High-throughput, parallelized and automated protein purification for therapeutic antibody development

Abstract Antibody therapeutic development often involves significant demands for purified protein samples, from initial assessments of numerous constructs from early stage screening campaigns through to lead identification and then for process development and pilot scale runs. Efforts to reduce timelines and cost per sample are common to both platform purification and for process development. In the earliest stages, high-throughput purification platforms that utilize liquid handlers or other small volume approaches can be suitable, as the quantity requirements for assays are minimal. However, as the number of candidate molecules diminishes, the scope of assays can quickly expand and include a variety of cell-based and in vivo experiments which can require tens or hundreds of milligrams of products of defined purity and with low endotoxin levels. Purification of these samples in a high-throughput, parallelized manner represents a significant challenge with relatively few available off-the-shelf solutions. Process development requirements are also amendable to high-throughput purification strategies combined with statistical approaches in order to optimize the design space and narrow initial process operation parameters suitable for a given purification unit operation. While less often utilized, non-chromatographic purification methods may also be amenable to automation and parallelization at the initial stages of purification development

Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector

Measurements of electrons from $\nu_e$ interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyond the standard model, supernova neutrino detection, and solar neutrino measurements. This article describes the selection and reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector. ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and operated at CERN as a charged particle test beam experiment. A sample of low-energy electrons produced by the decay of cosmic muons is selected with a purity of 95%. This sample is used to calibrate the low-energy electron energy scale with two techniques. An electron energy calibration based on a cosmic ray muon sample uses calibration constants derived from measured and simulated cosmic ray muon events. Another calibration technique makes use of the theoretically well-understood Michel electron energy spectrum to convert reconstructed charge to electron energy. In addition, the effects of detector response to low-energy electron energy scale and its resolution including readout electronics threshold effects are quantified. Finally, the relation between the theoretical and reconstructed low-energy electron energy spectrum is derived and the energy resolution is characterized. The low-energy electron selection presented here accounts for about 75% of the total electron deposited energy. After the addition of lost energy using a Monte Carlo simulation, the energy resolution improves from about 40% to 25% at 50~MeV. These results are used to validate the expected capabilities of the DUNE far detector to reconstruct low-energy electrons.Comment: 19 pages, 10 figure

Impact of cross-section uncertainties on supernova neutrino spectral parameter fitting in the Deep Underground Neutrino Experiment

A primary goal of the upcoming Deep Underground Neutrino Experiment (DUNE) is to measure the $\mathcal{O}(10)$ MeV neutrinos produced by a Galactic core-collapse supernova if one should occur during the lifetime of the experiment. The liquid-argon-based detectors planned for DUNE are expected to be uniquely sensitive to the $\nu_e$ component of the supernova flux, enabling a wide variety of physics and astrophysics measurements. A key requirement for a correct interpretation of these measurements is a good understanding of the energy-dependent total cross section $\sigma(E_\nu)$ for charged-current $\nu_e$ absorption on argon. In the context of a simulated extraction of supernova $\nu_e$ spectral parameters from a toy analysis, we investigate the impact of $\sigma(E_\nu)$ modeling uncertainties on DUNE's supernova neutrino physics sensitivity for the first time. We find that the currently large theoretical uncertainties on $\sigma(E_\nu)$ must be substantially reduced before the $\nu_e$ flux parameters can be extracted reliably: in the absence of external constraints, a measurement of the integrated neutrino luminosity with less than 10\% bias with DUNE requires $\sigma(E_\nu)$ to be known to about 5%. The neutrino spectral shape parameters can be known to better than 10% for a 20% uncertainty on the cross-section scale, although they will be sensitive to uncertainties on the shape of $\sigma(E_\nu)$. A direct measurement of low-energy $\nu_e$-argon scattering would be invaluable for improving the theoretical precision to the needed level.Comment: 25 pages, 21 figure

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 10^3 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

Effect of chemical treatments on physical properties of kenaf bast fibres

432-436In the present study, kenaf bast fibre surfaces have been modified using different chemicals with varying concentration. The effects of these chemical treatments on moisture content, water absorption, fibre diameter and bundle strength are investigated. The benefit of chemical treatments in the removal of impurities from the fibre surfaces has been established by scanning electron microscopy. It is found that the fibres treated with sodium hydroxide and acetic acid show major effect on fibre diameter. Compared to untreated kenaf fibre, strong alkali (NaOH) treatment show maximum water absorption (78.76%) and moisture content (8.15%). In fibre bundle tensile strength, sodium hydroxide and sodium carbonate treated fibres show more than 80% improvement in the tensile strength of fibre. Kenaf fibre treated with 10% Na2CO3 show highest tensile strength of 410 MPa