A Model to account for the effects of Friction during Explosive Pinch

Safety is of paramount importance in the handling, processing and storage of explosives. Mechanical insults resulting from low-speed impact, that crush and pinch an explosive, have been identified as a possible ignition source. However, modelling such an ignition mechanism numerically with hydrocodes proves to offer some considerable challenges. Here we develop a model for the pinching of an explosive cylinder between two flat plates which accounts for the effects of friction at the contact between the plates and the explosive. An ad hoc analytical method of the axial pinching of an explosive cylinder by two flat plates moving at constant speed is developed and discussed in [1]. In this formulation it is assumed that as the material is compressed it is in perfect plastic flow under adiabatic conditions. The explosive reaction is modelled using a simple Arrhenius Law. The heating of the explosive due to mechanical heating and self heating due to the reaction are calculated. In the analysis presented there is no treatment of friction at the contact region between the plate and explosive. As a result of this simplification the dissipation calculated is constant throughout the sample. This is contrast with experiments conducted at AWE in which non-uniform heating is observed [2]. Sherwood and Durban [3] investigated the squeezing of a non-reactive viscoplastic solid in the presence of friction. It is suggested that their paper may form a strong basis to explore frictional effects in the configuration posed in [1]. Here we adopt the approach taken in [3] to describe the mechanical behaviour of an explosive sample subject to axial compression, and then introduce a simple Arrhenius Law, as in [1], to model the reaction. The work presented allows us to investigate the effects of frictional heating during compression and arrive at an improved model of the so called Pinch Test

Shear localisation during deformation of reactive thermo-visco-elastic-plastic materials

A one-dimensional model for the initiation of shear bands in a reactive material is developed, with an Arrhenius source term to model the chemical reaction occurring in the band. An inhomogeneity in the heat flux is used as the stimulus for localised plastic deformation, and the problem is treated as a perturbation to the elastic solution. In the analysis, the thin zone of localisation is identified as a boundary layer. It is found that the behaviour of the perturbations to the temperature and stress in the band are governed by three dimensionless parameters which are known in terms of various material properties. The resulting equations are solved numerically and a criterion for the onset of shear banding is discussed

A mechanism for hot spot generation in a reactive two- dimensional sheared viscous layer

A two-dimensional model for the non-uniform melting of a thin sheared viscous layer is developed. An asymptotic solution is presented for both a non-reactive and a reactive material. It is shown that the melt front is linearly stable to small perturbations in the non-reactive case, but becomes linearly unstable upon introduction of an Arrhenius source term to model the chemical reaction. Results demonstrate that non-uniform melting acts as a mechanism to generate hot spots which are found to be sufficient to reduce the time to ignition when compared with the corresponding one-dimensional model of melting

Advances in mass spectrometry-based cancer research and analysis: from cancer proteomics to clinical diagnostics

Introduction: The last 20 years have seen significant improvements in the analytical capabilities of biological mass spectrometry. Studies using advanced mass spectrometry (MS) have resulted in new insights into cell biology and the aetiology of diseases as well as its use in clinical applications. Areas Covered: This review will discuss recent developments in MS-based technologies and their cancer-related applications with a focus on proteomics. It will also discuss the issues around translating the research findings to the clinic and provide an outline of where the field is moving. Expert Opinion: Proteomics has been problematic to adapt for the clinical setting. However, MS-based techniques continue to demonstrate potential in novel clinical uses beyond classical cancer proteomics

A cancer cell-line titration series for evaluating somatic classification.

BackgroundAccurate detection of somatic single nucleotide variants and small insertions and deletions from DNA sequencing experiments of tumour-normal pairs is a challenging task. Tumour samples are often contaminated with normal cells confounding the available evidence for the somatic variants. Furthermore, tumours are heterogeneous so sub-clonal variants are observed at reduced allele frequencies. We present here a cell-line titration series dataset that can be used to evaluate somatic variant calling pipelines with the goal of reliably calling true somatic mutations at low allele frequencies.ResultsCell-line DNA was mixed with matched normal DNA at 8 different ratios to generate samples with known tumour cellularities, and exome sequenced on Illumina HiSeq to depths of >300×. The data was processed with several different variant calling pipelines and verification experiments were performed to assay >1500 somatic variant candidates using Ion Torrent PGM as an orthogonal technology. By examining the variants called at varying cellularities and depths of coverage, we show that the best performing pipelines are able to maintain a high level of precision at any cellularity. In addition, we estimate the number of true somatic variants undetected as cellularity and coverage decrease.ConclusionsOur cell-line titration series dataset, along with the associated verification results, was effective for this evaluation and will serve as a valuable dataset for future somatic calling algorithm development. The data is available for further analysis at the European Genome-phenome Archive under accession number EGAS00001001016. Data access requires registration through the International Cancer Genome Consortium's Data Access Compliance Office (ICGC DACO)

Improved early detection of ovarian cancer using longitudinal multimarker models

© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Background: Ovarian cancer has a poor survival rate due to late diagnosis and improved methods are needed for its early detection. Our primary objective was to identify and incorporate additional biomarkers into longitudinal models to improve on the performance of CA125 as a first-line screening test for ovarian cancer. Methods: This case–control study nested within UKCTOCS used 490 serial serum samples from 49 women later diagnosed with ovarian cancer and 31 control women who were cancer-free. Proteomics-based biomarker discovery was carried out using pooled samples and selected candidates, including those from the literature, assayed in all serial samples. Multimarker longitudinal models were derived and tested against CA125 for early detection of ovarian cancer. Results: The best performing models, incorporating CA125, HE4, CHI3L1, PEBP4 and/or AGR2, provided 85.7% sensitivity at 95.4% specificity up to 1 year before diagnosis, significantly improving on CA125 alone. For Type II cases (mostly high-grade serous), models achieved 95.5% sensitivity at 95.4% specificity. Predictive values were elevated earlier than CA125, showing the potential of models to improve lead time. Conclusions: We have identified candidate biomarkers and tested longitudinal multimarker models that significantly improve on CA125 for early detection of ovarian cancer. These models now warrant independent validation.Peer reviewe

Transcriptional profiling of ErbB signalling in mammary luminal epithelial cells - interplay of ErbB and IGF1 signalling through IGFBP3 regulation

Background: Members of the ErbB family of growth factor receptors are intricately linked with epithelial cell biology, development and tumourigenesis; however, the mechanisms involved in their downstream signalling are poorly understood. Indeed, it is unclear how signal specificity is achieved and the relative contribution each receptor has to specific gene expression.Methods: Gene expression profiling of a human mammary luminal epithelial cell model of ErbB2-overexpression was carried out using cDNA microarrays with a common RNA reference approach to examine long-term overlapping and differential responses to EGF and heregulin beta1 treatment in the context of ErbB2 overexpression. Altered gene expression was validated using quantitative real time PCR and/or immunoblotting. One gene of interest was targeted for further characterisation, where the effects of siRNA-mediated silencing on IGF1-dependent signalling and cellular phenotype were examined and compared to the effects of loss of ErbB2 expression.Results: 775 genes were differentially expressed and clustered in terms of their growth factor responsiveness. As well as identifying uncharacterized genes as novel targets of ErbB2-dependent signalling, ErbB2 overexpression augmented the induction of multiple genes involved in proliferation (e. g. MYC, MAP2K1, MAP2K3), autocrine growth factor signalling (VEGF, PDGF) and adhesion/cytoskeletal regulation (ZYX, THBS1, VCL, CNN3, ITGA2, ITGA3, NEDD9, TAGLN), linking them to the hyper-poliferative and altered adhesive phenotype of the ErbB2-overexpressing cells. We also report ErbB2-dependent down-regulation of multiple interferon-stimulated genes that may permit ErbB2-overexpressing cells to resist the anti-proliferative action of interferons. Finally, IGFBP3 was unique in its pattern of regulation and we further investigated a possible role for IGFBP3 down-regulation in ErbB2-dependent transformation through suppressed IGF1 signalling. We show that IGF1-dependent signalling and proliferation were enhanced in ErbB2-overexpressing cells, whilst loss of ErbB2 expression by siRNA silencing reduced IGF1 signalling. Furthermore, IGFBP3 knockdown resulted in basal ERK and Akt activation in luminal epithelial cells and increased invasiveness and anchorage-independent colony formation in SKBR3 cells.Conclusions: These data show IGFBP3 as a negative regulator of transformation and that its down-regulation enhances IGF1-dependent signalling. They also show that ErbB2 can up-regulate IGF1-dependent signalling, possibly via the regulated expression of IGFBP3

Start to Farm: New Farmer Learning Network’s Dairy Series

Start to Farm: New Farmer Learning Networks were for beginning and early-career farmers looking for an edge in managing and growing their farm business. The ISUEO Dairy Team provided an opportunity to address ways to improve business practices and production techniques, tour successful farm operations, and form a community to share new ideas and profitable farming methods. The goal of the networks was to provide an open atmosphere for discussion, sharing of ideas and learning about resources for producers who are in their first 10-12 years of dairy farming. It is important to help producers make sound dairy farm management decisions that are backed by current and relevant information. Based on pre-post evaluations of all in class sessions and a follow up evaluation 1 month post workshops and dairy tours, participants attending the Start to Farm Dairy Series are making better decisions in different areas of their operation or prospective operations. They can evaluate the effect making changes has on their operation, which will increase profitability and sustainability of new and early career dairy farmers to continue in the business