Computer-assisted polyp matching between optical colonoscopy and CT colonography: a phantom study

Potentially precancerous polyps detected with CT colonography (CTC) need to be removed subsequently, using an optical colonoscope (OC). Due to large colonic deformations induced by the colonoscope, even very experienced colonoscopists find it difficult to pinpoint the exact location of the colonoscope tip in relation to polyps reported on CTC. This can cause unduly prolonged OC examinations that are stressful for the patient, colonoscopist and supporting staff. We developed a method, based on monocular 3D reconstruction from OC images, that automatically matches polyps observed in OC with polyps reported on prior CTC. A matching cost is computed, using rigid point-based registration between surface point clouds extracted from both modalities. A 3D printed and painted phantom of a 25 cm long transverse colon segment was used to validate the method on two medium sized polyps. Results indicate that the matching cost is smaller at the correct corresponding polyp between OC and CTC: the value is 3.9 times higher at the incorrect polyp, comparing the correct match between polyps to the incorrect match. Furthermore, we evaluate the matching of the reconstructed polyp from OC with other colonic endoluminal surface structures such as haustral folds and show that there is a minimum at the correct polyp from CTC. Automated matching between polyps observed at OC and prior CTC would facilitate the biopsy or removal of true-positive pathology or exclusion of false-positive CTC findings, and would reduce colonoscopy false-negative (missed) polyps. Ultimately, such a method might reduce healthcare costs, patient inconvenience and discomfort.Comment: This paper was presented at the SPIE Medical Imaging 2014 conferenc

Tuneable 2D self-assembly of plasmonic nanoparticles at liquid|liquid interfaces

Understanding the structure and assembly of nanoparticles at liquid|liquid interfaces is paramount to their integration into devices for sensing, catalysis, electronics and optics. However, many difficulties arise when attempting to resolve the structure of such interfacial assemblies. In this article we use a combination of X-ray diffraction and optical reflectance to determine the structural arrangement and plasmon coupling between 12.8 nm diameter gold nanoparticles assembled at a water|1,2-dichloroethane interface. The liquid|liquid interface provides a molecularly flat and defect-correcting platform for nanoparticles to self-assemble. The amount of nanoparticles assembling at the interface can be controlled via the concentration of electrolyte within either the aqueous or organic phase. At higher electrolyte concentration more nanoparticles can settle at the liquid|liquid interface resulting in a decrease in nanoparticle spacing as observed from X-ray diffraction experiments. The plasmonic coupling between the nanoparticles as they come closer together is observed by a red-shift in the optical reflectance spectra. The optical reflectance and the X-ray diffraction data are combined to introduce a new 'plasmon ruler'. This allows extraction of structural information from simple optical spectroscopy techniques, with important implications for understanding the structure of self-assembled nanoparticle films at liquid interfaces.</p

High Energy Physics Forum for Computational Excellence: Working Group Reports (I. Applications Software II. Software Libraries and Tools III. Systems)

Computing plays an essential role in all aspects of high energy physics. As computational technology evolves rapidly in new directions, and data throughput and volume continue to follow a steep trend-line, it is important for the HEP community to develop an effective response to a series of expected challenges. In order to help shape the desired response, the HEP Forum for Computational Excellence (HEP-FCE) initiated a roadmap planning activity with two key overlapping drivers -- 1) software effectiveness, and 2) infrastructure and expertise advancement. The HEP-FCE formed three working groups, 1) Applications Software, 2) Software Libraries and Tools, and 3) Systems (including systems software), to provide an overview of the current status of HEP computing and to present findings and opportunities for the desired HEP computational roadmap. The final versions of the reports are combined in this document, and are presented along with introductory material.Comment: 72 page

METRIC-EF: magnetic resonance enterography to predict disabling disease in newly diagnosed Crohn's disease-protocol for a multicentre, non-randomised, single-arm, prospective study

INTRODUCTION: Crohn's disease (CD) is characterised by discontinuous, relapsing enteric inflammation. Instituting advanced therapies at an early stage to suppress inflammation aims to prevent future complications such as stricturing or penetrating disease, and subsequent surgical resection. Therapeutics are effective but associated with certain side-effects and relatively expensive. There is therefore an urgent need for robust methods to predict which newly diagnosed patients will develop disabling disease, to identify patients who are most likely to benefit from early, advanced therapies. We aim to determine if magnetic resonance enterography (MRE) features at diagnosis improve prediction of disabling CD within 5 years of diagnosis. METHODS AND ANALYSIS: We describe the protocol for a multicentre, non-randomised, single-arm, prospective study of adult patients with newly diagnosed CD. We will use patients already recruited to the METRIC study and extend their clinical follow-up, as well as a separate group of newly diagnosed patients who were not part of the METRIC trial (MRE within 3 months of diagnosis), to ensure an adequate sample size. Follow-up will extend for at least 4 years. The primary outcome is to evaluate the comparative predictive ability of prognostic models incorporating MRE severity scores (Magnetic resonance Enterography Global Score (MEGS), simplified MAgnetic Resonance Index of Activity (sMaRIA) and Lémann Index) versus models using standard characteristics alone to predict disabling CD (modified Beaugerie definition) within 5 years of new diagnosis. ETHICS AND DISSEMINATION: This study protocol achieved National Health Service Research Ethics Committee (NHS REC), London-Hampstead Research Ethics Committee approval (IRAS 217422). Our findings will be disseminated via conference presentations and peer-reviewed publications. TRIAL REGISTRATION NUMBER: ISRCTN76899103

Tuneable 2D self-assembly of plasmonic nanoparticles at liquid|liquid interfaces

Understanding the structure and assembly of nanoparticles at liquid|liquid interfaces is paramount to their integration into devices for sensing, catalysis, electronics and optics. However, many difficulties arise when attempting to resolve the structure of such interfacial assemblies. In this article we use a combination of X-ray diffraction and optical reflectance to determine the structural arrangement and plasmon coupling between 12.8 nm diameter gold nanoparticles assembled at a water|1,2-dichloroethane interface. The liquid|liquid interface provides a molecularly flat and defect-correcting platform for nanoparticles to self-assemble. The amount of nanoparticles assembling at the interface can be controlled via the concentration of electrolyte within either the aqueous or organic phase. At higher electrolyte concentration more nanoparticles can settle at the liquid|liquid interface resulting in a decrease in nanoparticle spacing as observed from X-ray diffraction experiments. The plasmonic coupling between the nanoparticles as they come closer together is observed by a red-shift in the optical reflectance spectra. The optical reflectance and the X-ray diffraction data are combined to introduce a new 'plasmon ruler'. This allows extraction of structural information from simple optical spectroscopy techniques, with important implications for understanding the structure of self-assembled nanoparticle films at liquid interfaces.</p

Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism

Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases

A genome-wide association study identifies risk alleles in plasminogen and P4HA2 associated with giant cell arteritis

Giant cell arteritis (GCA) is the most common form of vasculitis in individuals older than 50 years in Western countries. To shed light onto the genetic background influencing susceptibility for GCA, we performed a genome-wide association screening in a well-powered study cohort. After imputation, 1,844,133 genetic variants were analysed in 2,134 cases and 9,125 unaffected controls from ten independent populations of European ancestry. Our data confirmed HLA class II as the strongest associated region (independent signals: rs9268905, P = 1.94E-54, per-allele OR = 1.79; and rs9275592, P = 1.14E-40, OR = 2.08). Additionally, PLG and P4HA2 were identified as GCA risk genes at the genome-wide level of significance (rs4252134, P = 1.23E-10, OR = 1.28; and rs128738, P = 4.60E-09, OR = 1.32, respectively). Interestingly, we observed that the association peaks overlapped with different regulatory elements related to cell types and tissues involved in the pathophysiology of GCA. PLG and P4HA2 are involved in vascular remodelling and angiogenesis, suggesting a high relevance of these processes for the pathogenic mechanisms underlying this type of vasculitis

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

A Continuous Measure of Gross Primary Production for the Conterminous U.S. Derived from MODIS and AmeriFlux Data

The quantification of carbon fluxes between the terrestrial biosphere and the atmosphere is of scientific importance and also relevant to climate-policy making. Eddy covariance flux towers provide continuous measurements of ecosystem-level exchange of carbon dioxide spanning diurnal, synoptic, seasonal, and interannual time scales. However, these measurements only represent the fluxes at the scale of the tower footprint. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to upscale gross primary productivity (GPP) data from eddy covariance flux towers to the continental scale. We first combined GPP and MODIS data for 42 AmeriFlux towers encompassing a wide range of ecosystem and climate types to develop a predictive GPP model using a regression tree approach. The predictive model was trained using observed GPP over the period 2000-2004, and was validated using observed GPP over the period 2005-2006 and leave-one-out cross-validation. Our model predicted GPP fairly well at the site level. We then used the model to estimate GPP for each 1 km x 1 km cell across the U.S. for each 8-day interval over the period from February 2000 to December 2006 using MODIS data. Our GPP estimates provide a spatially and temporally continuous measure of gross primary production for the U.S. that is a highly constrained by eddy covariance flux data. Our study demonstrated that our empirical approach is effective for upscaling eddy flux GPP data to the continental scale and producing continuous GPP estimates across multiple biomes. With these estimates, we then examined the patterns, magnitude, and interannual variability of GPP. We estimated a gross carbon uptake between 6.91 and 7.33 Pg C yr{sup -1} for the conterminous U.S. Drought, fires, and hurricanes reduced annual GPP at regional scales and could have a significant impact on the U.S. net ecosystem carbon exchange. The sources of the interannual variability of U.S. GPP were dominated by these extreme climate events and disturbances