81 research outputs found
Determination of soluble wheat protein fractions using the Bradford assay
Background and objectives
Determination of different grain protein fractions in wheat cultivars is an important task in analyzing bread baking quality. In many laboratories, the Bradford assay is used to determine protein concentrations in solutions. In any protein assay (including Bradford), the ideal protein to use as a standard is the purified protein being assayed. In the absence of such an absolute reference, protein another protein must be selected as a relative standard such as bovine serum albumin (BSA) which is widely used. The aim of this work was to find conversion factors for BSA to determine correct albumin–globulin, gliadin, and glutenin concentrations, because these purified wheat grain protein fractions are mostly not available to be used for calibration purposes.
Findings
In case of BSA calibration, gluten concentration was underestimated (50%–54%) compared to calibration with the respective purified wheat proteins (65%–70%) in extracts of wheat grain samples. This result is explained with the different amino acid composition of BSA and wheat protein fractions leading to a more intense signal with BSA in the Bradford assay. Calibration of the Bradford assay using BSA as well as purified wheat protein fractions allowed to calculate the conversion factors of 2.11 for BSA/albumin–globulin, 4.25 for BSA/gliadin, and 3.42 for BSA/glutenin. Application of these conversion factors proved to accurately adjust protein concentrations of wheat fractions originating from ten cultivars, determined with BSA calibration of the Bradford assay.
Conclusions
BSA calibration of the Bradford assay in combination with the conversion factors can be used to determine protein concentration of wheat grain fractions.
Significance and novelty
Findings of this study make a contribution toward the correction of a common method, to provide a basis for better comparability of research results from different laboratories
Robust normalization protocols for multiplexed fluorescence bioimage analysis
study of mapping and interaction of co-localized proteins at a sub-cellular level is important for understanding complex biological phenomena. One of the recent techniques to map co-localized proteins is to use the standard immuno-fluorescence microscopy in a cyclic manner (Nat Biotechnol 24:1270–8, 2006; Proc Natl Acad Sci 110:11982–7, 2013). Unfortunately, these techniques suffer from variability in intensity and positioning of signals from protein markers within a run and across different runs. Therefore, it is necessary to standardize protocols for preprocessing of the multiplexed bioimaging (MBI) data from multiple runs to a comparable scale before any further analysis can be performed on the data. In this paper, we compare various normalization protocols and propose on the basis of the obtained results, a robust normalization technique that produces consistent results on the MBI data collected from different runs using the Toponome Imaging System (TIS). Normalization results produced by the proposed method on a sample TIS data set for colorectal cancer patients were ranked favorably by two pathologists and two biologists. We show that the proposed method produces higher between class Kullback-Leibler (KL) divergence and lower within class KL divergence on a distribution of cell phenotypes from colorectal cancer and histologically normal samples
Exploring CEvNS with NUCLEUS at the Chooz Nuclear Power Plant
Coherent elastic neutrino-nucleus scattering (CENS) offers a unique way
to study neutrino properties and to search for new physics beyond the Standard
Model. Nuclear reactors are promising sources to explore this process at low
energies since they deliver large fluxes of (anti-)neutrinos with typical
energies of a few MeV. In this paper, a new-generation experiment to study
CENS is described. The NUCLEUS experiment will use cryogenic detectors
which feature an unprecedentedly low energy threshold and a time response fast
enough to be operated in above-ground conditions. Both sensitivity to
low-energy nuclear recoils and a high event rate tolerance are stringent
requirements to measure CENS of reactor antineutrinos. A new experimental
site, denoted the Very-Near-Site (VNS) at the Chooz nuclear power plant in
France is described. The VNS is located between the two 4.25 GW
reactor cores and matches the requirements of NUCLEUS. First results of on-site
measurements of neutron and muon backgrounds, the expected dominant background
contributions, are given. In this paper a preliminary experimental setup with
dedicated active and passive background reduction techniques is presented.
Furthermore, the feasibility to operate the NUCLEUS detectors in coincidence
with an active muon-veto at shallow overburden is studied. The paper concludes
with a sensitivity study pointing out the promising physics potential of
NUCLEUS at the Chooz nuclear power plant
MAIA—A machine learning assisted image annotation method for environmental monitoring and exploration
Digital imaging has become one of the most important techniques in environmental monitoring and exploration. In the case of the marine environment, mobile platforms such as autonomous underwater vehicles (AUVs) are now equipped with high-resolution cameras to capture huge collections of images from the seabed. However, the timely evaluation of all these images presents a bottleneck problem as tens of thousands or more images can be collected during a single dive. This makes computational support for marine image analysis essential. Computer-aided analysis of environmental images (and marine images in particular) with machine learning algorithms is promising, but challenging and different to other imaging domains because training data and class labels cannot be collected as efficiently and comprehensively as in other areas. In this paper, we present Machine learning Assisted Image Annotation (MAIA), a new image annotation method for environmental monitoring and exploration that overcomes the obstacle of missing training data. The method uses a combination of autoencoder networks and Mask Region-based Convolutional Neural Network (Mask R-CNN), which allows human observers to annotate large image collections much faster than before. We evaluated the method with three marine image datasets featuring different types of background, imaging equipment and object classes. Using MAIA, we were able to annotate objects of interest with an average recall of 84.1% more than twice as fast as compared to “traditional” annotation methods, which are purely based on software-supported direct visual inspection and manual annotation. The speed gain increases proportionally with the size of a dataset. The MAIA approach represents a substantial improvement on the path to greater efficiency in the annotation of large benthic image collections
Results on MeV-scale dark matter from a gram-scale cryogenic calorimeter operated above ground
Models for light dark matter particles with masses below 1 GeV/c are a
natural and well-motivated alternative to so-far unobserved weakly interacting
massive particles. Gram-scale cryogenic calorimeters provide the required
detector performance to detect these particles and extend the direct dark
matter search program of CRESST. A prototype 0.5 g sapphire detector developed
for the -cleus experiment has achieved an energy threshold of
eV, which is one order of magnitude lower than previous
results and independent of the type of particle interaction. The result
presented here is obtained in a setup above ground without significant
shielding against ambient and cosmogenic radiation. Although operated in a
high-background environment, the detector probes a new range of light-mass dark
matter particles previously not accessible by direct searches. We report the
first limit on the spin-independent dark matter particle-nucleon cross section
for masses between 140 MeV/c and 500 MeV/c.Comment: 6 pages, 6 figures, v3: ancillary files added, v4: high energy
spectrum (0.6-12keV) added to ancillary file
First results from the CRESST-III low-mass dark matter program
The CRESST experiment is a direct dark matter search which aims to measure
interactions of potential dark matter particles in an earth-bound detector.
With the current stage, CRESST-III, we focus on a low energy threshold for
increased sensitivity towards light dark matter particles. In this manuscript
we describe the analysis of one detector operated in the first run of
CRESST-III (05/2016-02/2018) achieving a nuclear recoil threshold of 30.1eV.
This result was obtained with a 23.6g CaWO crystal operated as a cryogenic
scintillating calorimeter in the CRESST setup at the Laboratori Nazionali del
Gran Sasso (LNGS). Both the primary phonon/heat signal and the simultaneously
emitted scintillation light, which is absorbed in a separate
silicon-on-sapphire light absorber, are measured with highly sensitive
transition edge sensors operated at ~15mK. The unique combination of these
sensors with the light element oxygen present in our target yields sensitivity
to dark matter particle masses as low as 160MeV/c.Comment: 9 pages, 9 figure
Effects of aging on the stress-induced martensitic transformation and cyclic superelastic properties in Co-Ni-Ga shape memory alloy single crystals under compression
Co-Ni-Ga shape memory alloys attracted scientific attention as promising candidate materials for damping applications at elevated temperatures, owing to excellent superelastic properties featuring a fully reversible stress-strain response up to temperatures as high as 500 °C. In the present work, the effect of aging treatments conducted in a wide range of aging temperatures and times, i.e. at 300–400 °C for 0.25–8.5 h, was investigated. It is shown that critical features of the martensitic transformation are strongly affected by the heat treatments. In particular, the formation of densely dispersed γ’-nanoparticles has a strong influence on the martensite variant selection and the morphology of martensite during stress-induced martensitic transformation. Relatively large, elongated particles promote irreversibility. In contrast, small spheroidal particles are associated with excellent functional stability during cyclic compression loading of 〈001〉-oriented single crystals. In addition to mechanical experiments, a detailed microstructural analysis was performed using in situ optical microscopy and neutron diffraction. Fundamental differences in microstructural evolution between various material states are documented and the relations between thermal treatment, microstructure and functional properties are explored and rationalized
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