Contribution of exopeptidases to formation of nonprotein nitrogen during ensiling of alfalfa

The experiment was conducted to investigate the exopeptidase classes in alfalfa (Medicago sativa L.) leaves, and to determine their contribution to the formation of nonprotein nitrogen (NPN) components during ensiling. Six classes of inhibitors that included bestatin (aminopeptidase inhibitor), potato carboxypeptidase inhibitor (PCI, carboxypeptidase inhibitor), 1,10-phenanthroline (dipeptidase inhibitor), diprotin A (dipeptidyl-peptidase inhibitor), butabindide (tripeptidyl-peptidase inhibitor), and dipeptide Phe-Arg (peptidyl-dipeptidase inhibitor) were used. To determine the contribution of each exopeptidase to the formation of NPN products, aqueous extracts of fresh alfalfa were fermented to imitate the proteolytic process of ensiled alfalfa and to ensure that each class of exopeptidase inhibitor would have immediate contact with the proteases in the alfalfa extract. Five classes of exopeptidases; namely, aminopeptidase, carboxypeptidase, dipeptidase, dipeptidyl-peptidase, and tripeptidyl-peptidase, were shown to be present in alfalfa leaves, each playing a different role in alfalfa protein degradation. Aminopeptidase, carboxypeptidase, and dipeptidase were the main exopeptidases contributing to the formation of NH3-N. Among the 5 exopeptidases, tripeptidyl-peptidase appeared to be the principal exopeptidase in hydrolyzing forage protein into peptides, whereas carboxypeptidase and dipeptidase appeared to be more important in contributing to the formation of amino acid-N. Dipeptidyl-peptidase and tripeptidyl-peptidase did not play a role in the formation of NH3-N or amino acid-N. Dipeptidase, carboxypeptidase, and tripeptidyl-peptidase were the principal exopeptidases for hydrolyzing forage protein into NPN during ensilage, and treatment with a mixture of the 5 inhibitors reduced the total NPN concentration in the fermented alfalfa extract to about 45% of that in the control after 21 d of fermentation

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Chemical vapor deposition of graphene: A route to device integration

In this thesis, I have shown that the quality of synthetic graphene can be as high as mechanically exfoliated graphene if we can get rid of the wrinkles. Any defects, impurities and grain boundaries will induce scattering, preventing ballistic transport. The experiment described in chapter 4 was the first to demonstrate ballistic transport in synthetic graphene, and it will pave the way for the mass production of high quality monolayer graphene. In 2008, monolayer graphene was difficult to make and it was ranked as the most expensive material in the world. A piece of mechanically exfoliated monolayer graphene with size smaller than the diameter of a human hair will cost more than $1,000 from Graphene Research Ltd in Manchester. Currently (2014), Monolayer graphene single crystals with size up to millimeters in diameter have already been routinely produced worldwide, and the price per cm2 sample has dropped to less than$200. In chapter 5 of this thesis, a parameterless equation was provided to calculate the number of graphene layers by measuring the transmittance of graphene films. The search for novel transparent electrode materials with good stability, high transparency and excellent conductivity is driven by the required trade-off between transparency and conductivity: Metals are very conductive but not transparent; plastics are quite transparent but not conductive. Graphene is a transparent and conductive material. However, the conductivity of monolayer graphene might not be sufficient for fabricating a highly conductive electrode. The dilemma is that the transmittance of a graphene film decreases as the number of layers increases. It therefore is of great importance to have a fast and reliable method to determine the number of layers in the fabrication and measurement of multilayer graphene. Having a simple relation to determine how many graphene layers can meet the transmittance requirement and provide good conductivity at the same time is a valuable tool. I have also successfully demonstrated the integration of graphene into silicon chips, and the pressure sensor devices can potentially be produced in wafer scale. A sensitivity of ?8.5?mV/bar was obtained, and the standard deviation was less than 15?mbar at 700?mbar full scale. This chip scale integration of graphene devices is a key process to link the current semiconductor technology and the future applications of high quality graphene films. The further development of wafer scale automation transfer process is one of the directions to realize the valorisation of graphene. In chapter 7 of this thesis, I have shown the potential application of graphene for optoelectronics devices. The speed of optoelectronics will outperform the current transistors especially in transmitting high-volume information on chip scale. Although lots of technical issues are still waiting to be solved and the delivery of high quality and large quantity of graphene based products is still a key issue, tremendous progresses has been made in graphene research. In the scope of 10-20 years, I believe that the price of large-scale monolayer graphene will drop below $1/cm2 comparable to the price of gate-oxide, which will enable graphene to enter potential markets, such as optoelectronics computing, flexible sensors and wearable devices, etc. There will be bright future for graphene technology.Precision and Microsystems Engineering (PME)Mechanical, Maritime and Materials Engineerin

Graphene Synthesis

Precision and Microsystems EngineeringMechanical, Maritime and Materials Engineerin

3-D Ego-Motion Estimation Using Multi-Channel FMCW Radar

The problem of estimating the 3D ego-motion velocity using multi-channel FMCW radar sensors has been studied. For the first time, the problem of ego-motion estimation is treated using radar raw signals. A robust algorithm using multi-channel FMCW radar sensors to instantly determine the complete 3D motion state of the ego-vehicle (i.e., translational speed and rotational speed) is proposed. The angle information of targets is extracted, and then their phase information from different times instances is used to determine vehicle ego-motion through an optimization process. Any pre-processing steps, such as clustering or clutter suppression, are not required. The performance of the algorithm is compared with the state-of-the-art algorithms based on real-world data, and superior performance has been demonstrated. The algorithm proposed can be easily integrated into radar signal processing pipelines for other tasks relevant to autonomous driving.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Microwave Sensing, Signals & System

A Chemical Reactor Network Approach for Modeling Pollutant Formation in Large Industrial Furnaces in Julia

The chemical reactor network (CRN) approach is a practical tool for precisely predicting the species concentration in combustion processes with low computational cost. This work examines the capability of the emerging Julia programming language and its ecosystem in solving large CRNs. The packages DifferentialEquations.jl and ModelingToolkit.jl are employed to defining and solving stiff ordinary differential equations, for which the implicit time-integration methods Rodas5 and TRBDF2 with the GMRES linear solver are used. The graph structure of reactor networks is constructed by LightGraphs.jl and SimpleWeightedGraphs.jl. The differential equation solver and the graph data structure are connected via NetworkDynamics.jl. It is concluded that Julia is a competent tool for CRNs containing up to 1000 nodes each with 4 species. Julia is capable of simulating pollutant formation in large reactor networks with reasonable time and memory space.CSE3000 Research ProjectComputer Science and Engineerin

Radar-only Instantaneous Ego-motion Estimation Using Neural Networks

The problem of 2D instantaneous ego-motion estimation for vehicles equipped with automotive radars is studied. To leverage multi-dimensional radar point clouds and exploit point features automatically, without human engineering, a novel approach is proposed that transforms ego-motion estimation into a weighted least squares (wLSQ) problem using neural networks. Comparison with existing methods is done using a challenging real-world radar dataset. The comparison results show that the proposed method can achieve better performance in terms of estimation accuracy, long-term stability, and runtime performance compared to a representative approach selected from the recent literature.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Microwave Sensing, Signals & System