Modelling of the low-impulse blast behaviour of fibre–metal laminates based on different aluminium alloys

A parametric study has been undertaken in order to investigate the influence of the properties of the aluminium alloy on the blast response of fibre–metal laminates (FMLs). The finite element (FE) models have been developed and validated using experimental data from tests on FMLs based on a 2024-O aluminium alloy and a woven glass–fibre/polypropylene composite (GFPP). A vectorized user material subroutine (VUMAT) was employed to define Hashin’s 3D rate-dependant damage constitutive model of the GFPP. Using the validated models, a parametric study has been carried out to investigate the blast resistance of FML panels based on the four aluminium alloys, namely 2024-O, 2024-T3, 6061-T6 and 7075-T6. It has been shown that there is an approximation linear relationship between the dimensionless back face displacement and the dimensionless impulse for all aluminium alloys investigated here. It has also shown that the residual displacement of back surface of the FML panels and the internal debonding are dependent on the yield strength of the aluminium alloy

G-spots cause incorrect expression measurement in Affymetrix microarrays

Abstract Background High Density Oligonucleotide arrays (HDONAs), such as the Affymetrix HG-U133A GeneChip, use sets of probes chosen to match specified genes, with the expectation that if a particular gene is highly expressed then all the probes in that gene's probe set will provide a consistent message signifying the gene's presence. However, probes that contain a G-spot (a sequence of four or more guanines) behave abnormally and it has been suggested that these probes are responding to some biochemical effect such as the formation of G-quadruplexes. Results We have tested this expectation by examining the correlation coefficients between pairs of probes using the data on thousands of arrays that are available in the NCBI Gene Expression Omnibus (GEO) repository. We confirm the finding that G-spot probes are poorly correlated with others in their probesets and reveal that, by contrast, they are highly correlated with one another. We demonstrate that the correlation is most marked when the G-spot is at the 5' end of the probe. Conclusion Since these G-spot probes generally show little correlation with the other members of their probesets they are not fit for purpose and their values should be excluded when calculating gene expression values. This has serious implications, since more than 40% of the probesets in the HG-U133A GeneChip contain at least one such probe. Future array designs should avoid these untrustworthy probes. </jats:sec

Automated DNA Motif Discovery

Ensembl's human non-coding and protein coding genes are used to automatically find DNA pattern motifs. The Backus-Naur form (BNF) grammar for regular expressions (RE) is used by genetic programming to ensure the generated strings are legal. The evolved motif suggests the presence of Thymine followed by one or more Adenines etc. early in transcripts indicate a non-protein coding gene. Keywords: pseudogene, short and microRNAs, non-coding transcripts, systems biology, machine learning, Bioinformatics, motif, regular expression, strongly typed genetic programming, context-free grammar.Comment: 12 pages, 2 figure

Affymetrix probes containing runs of contiguous guanines are not gene-specific

High Density Oligonucleotide arrays (HDONAs), such as the Affymetrix HG-U133A GeneChip, use sets of probes chosen to match specified genes, with the expectation that if a particular gene is highly expressed then all the probes in the designated probe set will provide a consistent message signifying the gene&#x27;s presence. However, we demonstrate by data mining thousands of CEL files from NCBI&#x27;s GEO database that 4G-probes (defined as probes containing sequences of four or more consecutive guanine (G) bases) do not react in the intended way. Rather, possibly due to the formation of G-quadruplexes, most 4G-probes are correlated, irrespective of the expression of the thousands of genes for which they were separately intended. It follows that 4G-probes should be ignored when calculating gene expression levels. Furthermore, future microarray designs should make no use of 4G-probes

Estrogen Receptor Signaling in Cancer

Estrogen receptor signaling play

The unsteady flow of a weakly compressible fluid in a thin porous layer. I: Two-dimensional theory

We consider the problem of determining the pressure and velocity fields for a weakly compressible fluid flowing in a two-dimensional reservoir in an inhomogeneous, anisotropic porous medium, with vertical side walls and variable upper and lower boundaries, in the presence of vertical wells injecting or extracting fluid. Numerical solution of this problem may be expensive, particularly in the case that the depth scale of the layer h is small compared to the horizontal length scale l. This is a situation which occurs frequently in the application to oil reservoir recovery. Under the assumption that epsilon=h/l<<1, we show that the pressure field varies only in the horizontal direction away from the wells (the outer region). We construct two-term asymptotic expansions in epsilon in both the inner (near the wells) and outer regions and use the asymptotic matching principle to derive analytical expressions for all significant process quantities. This approach, via the method of matched asymptotic expansions, takes advantage of the small aspect ratio of the reservoir, epsilon, at precisely the stage where full numerical computations become stiff, and also reveals the detailed structure of the dynamics of the flow, both in the neighborhood of wells and away from wells

Emerging role of nuclear factor erythroid 2-related factor 2 in the mechanism of action and resistance to anticancer therapies

Nuclear factor E2-related factor 2 (NRF2), a transcription factor, is a master regulator of an array of genes related to oxidative and electrophilic stress that promote and maintain redox homeostasis. NRF2 function is well studied in in vitro, animal and general physiology models. However, emerging data has uncovered novel functionality of this transcription factor in human diseases such as cancer, autism, anxiety disorders and diabetes. A key finding in these emerging roles has been its constitutive upregulation in multiple cancers promoting pro-survival phenotypes. The survivability pathways in these studies were mostly explained by classical NRF2 activation involving KEAP-1 relief and transcriptional induction of reactive oxygen species (ROS) neutralizing and cytoprotective drug-metabolizing enzymes (phase I, II, III and 0). Further, NRF2 status and activation is associated with lowered cancer therapeutic efficacy and the eventual emergence of therapeutic resistance. Interestingly, we and others have provided further evidence of direct NRF2 regulation of anticancer drug targets like receptor tyrosine kinases and DNA damage and repair proteins and kinases with implications for therapy outcome. This novel finding demonstrates a renewed role of NRF2 as a key modulatory factor informing anticancer therapeutic outcomes, which extends beyond its described classical role as a ROS regulator. This review will provide a knowledge base for these emerging roles of NRF2 in anticancer therapies involving feedback and feed forward models and will consolidate and present such findings in a systematic manner. This places NRF2 as a key determinant of action, effectiveness and resistance to anticancer therapy