Left Ventricular Trabeculations Decrease the Wall Shear Stress and Increase the Intra-Ventricular Pressure Drop in CFD Simulations

The aim of the present study is to characterize the hemodynamics of left ventricular (LV) geometries to examine the impact of trabeculae and papillary muscles (PMs) on blood flow using high performance computing (HPC). Five pairs of detailed and smoothed LV endocardium models were reconstructed from high-resolution magnetic resonance images (MRI) of ex-vivo human hearts. The detailed model of one LV pair is characterized only by the PMs and few big trabeculae, to represent state of art level of endocardial detail. The other four detailed models obtained include instead endocardial structures measuring ≥1 mm2 in cross-sectional area. The geometrical characterizations were done using computational fluid dynamics (CFD) simulations with rigid walls and both constant and transient flow inputs on the detailed and smoothed models for comparison. These simulations do not represent a clinical or physiological scenario, but a characterization of the interaction of endocardial structures with blood flow. Steady flow simulations were employed to quantify the pressure drop between the inlet and the outlet of the LVs and the wall shear stress (WSS). Coherent structures were analyzed using the Q-criterion for both constant and transient flow inputs. Our results show that trabeculae and PMs increase the intra-ventricular pressure drop, reduce the WSS and disrupt the dominant single vortex, usually present in the smoothed-endocardium models, generating secondary small vortices. Given that obtaining high resolution anatomical detail is challenging in-vivo, we propose that the effect of trabeculations can be incorporated into smoothed ventricular geometries by adding a porous layer along the LV endocardial wall. Results show that a porous layer of a thickness of 1.2·10−2 m with a porosity of 20 kg/m2 on the smoothed-endocardium ventricle models approximates the pressure drops, vorticities and WSS observed in the detailed models.This paper has been partially funded by CompBioMed project, under H2020-EU.1.4.1.3 European Union’s Horizon 2020 research and innovation programme, grant agreement n◦ 675451. FS is supported by a grant from Severo Ochoa (n◦ SEV-2015-0493-16-4), Spain. CB is supported by a grant from the Fundació LaMarató de TV3 (n◦ 20154031), Spain. TI and PI are supported by the Institute of Engineering in Medicine, USA, and the Lillehei Heart Institute, USA.Peer ReviewedPostprint (published version

Evaluating the roles of detailed endocardial structures on right ventricular haemodynamics by means of CFD simulations

Computational modelling plays an important role in right ventricular (RV) haemodynamic analysis. However, current approaches use smoothed ventricular anatomies. The aim of this study is to characterise RV haemodynamics including detailed endocardial structures like trabeculae, moderator band, and papillary muscles. Four paired detailed and smoothed RV endocardium models (2 male and 2 female) were reconstructed from ex vivo human hearts high‐resolution magnetic resonance images. Detailed models include structures with ≥1 mm2 cross‐sectional area. Haemodynamic characterisation was done by computational fluid dynamics simulations with steady and transient inflows, using high‐performance computing. The differences between the flows in smoothed and detailed models were assessed using Q‐criterion for vorticity quantification, the pressure drop between inlet and outlet, and the wall shear stress. Results demonstrated that detailed endocardial structures increase the degree of intra‐ventricular pressure drop, decrease the wall shear stress, and disrupt the dominant vortex creating secondary small vortices. Increasingly turbulent blood flow was observed in the detailed RVs. Female RVs were less trabeculated and presented lower pressure drops than the males. In conclusion, neglecting endocardial structures in RV haemodynamic models may lead to inaccurate conclusions about the pressures, stresses, and blood flow behaviour in the cavity.The DICOMdatasetswere provided by the Visible Heart R Laboratory, obtained byMRI scanning of perfusion fixed hearts that were graciously donated by the organ donors and their families through LifeSource. Part of the simulation hours were provided by the CompBioMed project in the Archer supercomputer, EPCC, UK.Peer ReviewedPostprint (author's final draft

Performance of Landscape Plants from Northern Japan in the North Central United States

In 1984 and 1985, 21 landscape plant introductions from northern Japan were distributed for testing in the NC-7 Regional Ornamental Plant Trials. Seventeen of these introductions were evaluated for 10 years at six to ten sites representing a cross-section of growing conditions in the north central United States. For these 17 introductions, first-year survival averaged 60%; however, by year 10, fewer than 20% of the original 425 plants were alive. Based on these evaluations, the populations could be divided into four groups. One population of Rosa rugosa was adapted to most trial sites; two populations (Alnus hirsuta and Lonicera chrysantha) were adapted to some sites; three populations were of poorly adapted dieback shrubs, and the remaining II populations included a diverse set of trees and shrubs unadapted to any, or nearly any, trial site. Temperature and moisture data from Japan and from trial sites were used to examine relationships between plant adaptation and climate. Statistically significant, multiple-regression models were calculated to describe the functional relationships between temperature and moisture conditions and plant adaptation at the various trial sites. Our models predict that plants from northern Japan are best adapted to sites in the northeastern United States where moisture surpluses exceed those typically found in the north central United States. These models also suggest criteria to evaluate sites throughout northeastern Asia for future exploration

Challenges in quantifying changes in the global water cycle

Human influences have likely already impacted the large-scale water cycle but natural variability and observational uncertainty are substantial. It is essential to maintain and improve observational capabilities to better characterize changes. Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Performance and Operation of the CMS Electromagnetic Calorimeter

The operation and general performance of the CMS electromagnetic calorimeter using cosmic-ray muons are described. These muons were recorded after the closure of the CMS detector in late 2008. The calorimeter is made of lead tungstate crystals and the overall status of the 75848 channels corresponding to the barrel and endcap detectors is reported. The stability of crucial operational parameters, such as high voltage, temperature and electronic noise, is summarised and the performance of the light monitoring system is presented

Genome-wide meta-analysis identifies five new susceptibility loci for cutaneous malignant melanoma.

Thirteen common susceptibility loci have been reproducibly associated with cutaneous malignant melanoma (CMM). We report the results of an international 2-stage meta-analysis of CMM genome-wide association studies (GWAS). This meta-analysis combines 11 GWAS (5 previously unpublished) and a further three stage 2 data sets, totaling 15,990 CMM cases and 26,409 controls. Five loci not previously associated with CMM risk reached genome-wide significance (P < 5 × 10(-8)), as did 2 previously reported but unreplicated loci and all 13 established loci. Newly associated SNPs fall within putative melanocyte regulatory elements, and bioinformatic and expression quantitative trait locus (eQTL) data highlight candidate genes in the associated regions, including one involved in telomere biology.[Please see the Supplementary Note for acknowledgments.]This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/ng.337

Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods - recursive partitioning and regression - to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; Pcombined = 2.01 × 10-19 and 2.35 × 10-13, respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes. ©2007 Nature Publishing Group