Influence of packing density and stress on the dynamic response of granular materials

Laboratory geophysics tests including bender elements and acoustic emission measure the speed of propagation of stress or sound waves in granular materials to derive elastic stiffness parameters. This contribution builds on earlier studies to assess whether the received signal characteristics can provide additional information about either the material’s behaviour or the nature of the material itself. Specifically it considers the maximum frequency that the material can transmit; it also assesses whether there is a simple link between the spectrum of the received signal and the natural frequencies of the sample. Discrete element method (DEM) simulations of planar compression wave propagation were performed to generate the data for the study. Restricting consideration to uniform (monodisperse) spheres, the material fabric was varied by considering face-centred cubic lattice packings as well as random configurations with different packing densities. Supplemental analyses, in addition to the DEM simulations, were used to develop a more comprehensive understanding of the system dynamics. The assembly stiffness and mass matrices were extracted from the DEM model and these data were used in an eigenmode analysis that provided significant insight into the observed overall dynamic response. The close agreement of the wave velocities estimated using eigenmode analysis with the DEM results confirms that DEM wave propagation simulations can reliably be used to extract material stiffness data. The data show that increasing either stress or density allows higher frequencies to propagate through the media, but the low-pass wavelength is a function of packing density rather than stress level. Prior research which had hypothesised that there is a simple link between the spectrum of the received signal and the natural sample frequencies was not substantiated

VLDL Hydrolysis by Hepatic Lipase Regulates PPARδ Transcriptional Responses

PPARs (α,γ,δ) are a family of ligand-activated transcription factors that regulate energy balance, including lipid metabolism. Despite these critical functions, the integration between specific pathways of lipid metabolism and distinct PPAR responses remains obscure. Previous work has revealed that lipolytic pathways can activate PPARs. Whether hepatic lipase (HL), an enzyme that regulates VLDL and HDL catabolism, participates in PPAR responses is unknown.Using PPAR ligand binding domain transactivation assays, we found that HL interacted with triglyceride-rich VLDL (>HDL≫LDL, IDL) to activate PPARδ preferentially over PPARα or PPARγ, an effect dependent on HL catalytic activity. In cell free ligand displacement assays, VLDL hydrolysis by HL activated PPARδ in a VLDL-concentration dependent manner. Extended further, VLDL stimulation of HL-expressing HUVECs and FAO hepatoma cells increased mRNA expression of canonical PPARδ target genes, including adipocyte differentiation related protein (ADRP), angiopoietin like protein 4 and pyruvate dehydrogenase kinase-4. HL/VLDL regulated ADRP through a PPRE in the promoter region of this gene. In vivo, adenoviral-mediated hepatic HL expression in C57BL/6 mice increased hepatic ADRP mRNA levels by 30%. In ob/ob mice, a model with higher triglycerides than C57BL/6 mice, HL overexpression increased ADRP expression by 70%, demonstrating the importance of triglyceride substrate for HL-mediated PPARδ activation. Global metabolite profiling identified HL/VLDL released fatty acids including oleic acid and palmitoleic acid that were capable of recapitulating PPARδ activation and ADRP gene regulation in vitro.These data define a novel pathway involving HL hydrolysis of VLDL that activates PPARδ through generation of specific monounsaturated fatty acids. These data also demonstrate how integrating cell biology with metabolomic approaches provides insight into specific lipid mediators and pathways of lipid metabolism that regulate transcription

Multiple splice defects in ABCA1 cause low HDL-C in a family with Hypoalphalipoproteinemia and premature coronary disease

<p>Abstract</p> <p>Background</p> <p>Mutations at splice junctions causing exon skipping are uncommon compared to exonic mutations, and two intronic mutations causing an aberrant phenotype have rarely been reported. Despite the high number of functional <it>ABCA1 </it>mutations reported to date, splice variants have been reported infrequently. We screened DNA from a 41 year-old male with low HDL-C (12 mg/dL [0.31 mmol/L]) and a family history of premature coronary heart disease (CHD) using polymerase chain reaction single-strand conformation polymorphism (SSCP) analysis.</p> <p>Methods</p> <p>Family members with low levels of HDL-C (n = 6) were screened by SSCP for mutations in <it>ABCA1</it>. Samples with altered SSCP patterns were sequenced directly using either an ABI 3700 or ABI3730Xl DNA Analyzer. To screen for splicing defects, cDNA was isolated from the proband's RNA and was sequenced as above. A series of minigenes were constructed to determine the contribution of normal and defective alleles.</p> <p>Results</p> <p>Two novel splice variants in <it>ABCA1 </it>were identified. The first mutation was a single base pair change (T->C) in IVS 7, 6 bps downstream from the exon7/intron7 junction. Amplification of cDNA and allelic subcloning identified skipping of Exon 7 that results in the elimination of 59 amino acids from the first extracellular loop of the ABCA1 protein. The second mutation was a single base pair change (G->C) at IVS 31 -1, at the intron/exon junction of exon 32. This mutation causes skipping of exon 32, resulting in 8 novel amino acids followed by a stop codon and a predicted protein size of 1496 AA, compared to normal (2261 AA). Bioinformatic studies predicted an impact on splicing as confirmed by <it>in vitro </it>assays of constitutive splicing.</p> <p>Conclusion</p> <p>In addition to carnitine-acylcarnitine translocase (CACT) deficiency and Hermansky-Pudlak syndrome type 3, this represents only the third reported case in which 2 different splice mutations has resulted in an aberrant clinical phenotype.</p

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Alterations in regional vascular geometry produced by theoretical stent implantation influence distributions of wall shear stress: analysis of a curved coronary artery using 3D computational fluid dynamics modeling

BACKGROUND: The success of stent implantation in the restoration of blood flow through areas of vascular narrowing is limited by restenosis. Several recent studies have suggested that the local geometric environment created by a deployed stent may influence regional blood flow characteristics and alter distributions of wall shear stress (WSS) after implantation, thereby rendering specific areas of the vessel wall more susceptible to neointimal hyperplasia and restenosis. Stents are most frequently implanted in curved vessels such as the coronary arteries, but most computational studies examining blood flow patterns through stented vessels conducted to date use linear, cylindrical geometric models. It appears highly probable that restenosis occurring after stent implantation in curved arteries also occurs as a consequence of changes in fluid dynamics that are established immediately after stent implantation. METHODS: In the current investigation, we tested the hypothesis that acute changes in stent-induced regional geometry influence distributions of WSS using 3D coronary artery CFD models implanted with stents that either conformed to or caused straightening of the primary curvature of the left anterior descending coronary artery. WSS obtained at several intervals during the cardiac cycle, time averaged WSS, and WSS gradients were calculated using conventional techniques. RESULTS: Implantation of a stent that causes straightening, rather than conforms to the natural curvature of the artery causes a reduction in the radius of curvature and subsequent increase in the Dean number within the stented region. This straightening leads to modest skewing of the velocity profile at the inlet and outlet of the stented region where alterations in indices of WSS are most pronounced. For example, time-averaged WSS in the proximal portion of the stent ranged from 8.91 to 11.7 dynes/cm(2 )along the pericardial luminal surface and 4.26 to 4.88 dynes/cm(2 )along the myocardial luminal surface of curved coronary arteries as compared to 8.31 dynes/cm(2 )observed throughout the stented region of a straight vessel implanted with an equivalent stent. CONCLUSION: The current results predicting large spatial and temporal variations in WSS at specific locations in curved arterial 3D CFD simulations are consistent with clinically observed sites of restenosis. If the findings of this idealized study translate to the clinical situation, the regional geometry established immediately after stent implantation may predispose portions of the stented vessel to a higher risk of neointimal hyperplasia and subsequent restenosis

QSAR studies on a number of pyrrolidin-2-one antiarrhythmic arylpiperazinyls

The activity of a number of 1-[3-(4-arylpiperazin-1-yl)propyl]pyrrolidin-2-one antiarrhythmic (AA) agents was described using the quantitative structure–activity relationship model by applying it to 33 compounds. The molecular descriptors of the AA activity were obtained by quantum chemical calculations combined with molecular modeling calculations. The resulting model explains up to 91% of the variance and it was successfully validated by four tests (LOO, LMO, external test, and Y-scrambling test). Statistical analysis shows that the AA activity of the studied compounds depends mainly on the PCR and JGI4 descriptors

Knowledge-Driven Analysis Identifies a Gene–Gene Interaction Affecting High-Density Lipoprotein Cholesterol Levels in Multi-Ethnic Populations

Total cholesterol, low-density lipoprotein cholesterol, triglyceride, and high-density lipoprotein cholesterol (HDL-C) levels are among the most important risk factors for coronary artery disease. We tested for gene–gene interactions affecting the level of these four lipids based on prior knowledge of established genome-wide association study (GWAS) hits, protein–protein interactions, and pathway information. Using genotype data from 9,713 European Americans from the Atherosclerosis Risk in Communities (ARIC) study, we identified an interaction between HMGCR and a locus near LIPC in their effect on HDL-C levels (Bonferroni corrected Pc = 0.002). Using an adaptive locus-based validation procedure, we successfully validated this gene–gene interaction in the European American cohorts from the Framingham Heart Study (Pc = 0.002) and the Multi-Ethnic Study of Atherosclerosis (MESA; Pc = 0.006). The interaction between these two loci is also significant in the African American sample from ARIC (Pc = 0.004) and in the Hispanic American sample from MESA (Pc = 0.04). Both HMGCR and LIPC are involved in the metabolism of lipids, and genome-wide association studies have previously identified LIPC as associated with levels of HDL-C. However, the effect on HDL-C of the novel gene–gene interaction reported here is twice as pronounced as that predicted by the sum of the marginal effects of the two loci. In conclusion, based on a knowledge-driven analysis of epistasis, together with a new locus-based validation method, we successfully identified and validated an interaction affecting a complex trait in multi-ethnic populations