Reproducibility of coronary artery diameter assessments in magnetic resonance coronary angiography: phantom study

This report describes the development of a deformable model for the automatic delineation of coronary artery cross-sectional areas with magnetic resonance imaging. The method is validated with coronary artery phantoms of varying diameters and images with different levels of signal-to-noise ratios. The reproducibility of the technique was examined with simulated geometrical shifts and motions during data acquisition. The experimental results indicate a very high reproducibility and low inter-observers variability of the technique, suggesting its suitability for non-invasive assessment of serial changes of vessel dilatation following pharmacological intervention

Detection of Provasopressin in Invasive and Non-invasive (DCIS) Human Breast Cancer Using a Monoclonal Antibody Directed Against the C-terminus (MAG1)

The provasopressin protein (proAVP) is expressed by invasive breast cancer and non-invasive breast cancer, or ductal carcinoma in situ (DCIS). Here we demonstrate the ability of the monoclonal antibody MAG1 directed against the C-terminal end of proAVP to identify proAVP in all cases examined of human invasive cancer and DCIS (35 and 26, respectively). Tissues were chosen to represent a relevant variation in tumor type, grade, patient age, and menopausal status. By comparison, there was 65% positive staining for estrogen receptor, 61% for progesterone receptor, 67% for nuclear p53, and 39% for c-Erb-B2 with the invasive breast cancer sections. Reaction with the normal tissue types examined (67) was restricted to the vasopressinergic magnocellular neurons of the hypothalamus, where provasopressin is normally produced, and the posterior pituitary, where these neurons terminate. The breast epithelial tissue sections on the tissue microarray did not react with MAG1. Previously, we demonstrated that polyclonal antibodies to proAVP detected that protein in all breast cancer samples examined, but there was no reaction with breast tissue containing fibrocystic disease. The results presented here not only expand upon those earlier results, but they also demonstrate the specificity and effectiveness of what may be considered a more clinically-relevant agent. Thus, proAVP appears to be an attractive target for the detection of invasive breast cancer and DCIS, and these results suggest that MAG1 may be a beneficial tool for use in the development of such strategies

Constrained Statistical Modelling of Knee Flexion from Multi-Pose Magnetic Resonance Imaging

© 1982-2012 IEEE.Reconstruction of the anterior cruciate ligament (ACL) through arthroscopy is one of the most common procedures in orthopaedics. It requires accurate alignment and drilling of the tibial and femoral tunnels through which the ligament graft is attached. Although commercial computer-Assisted navigation systems exist to guide the placement of these tunnels, most of them are limited to a fixed pose without due consideration of dynamic factors involved in different knee flexion angles. This paper presents a new model for intraoperative guidance of arthroscopic ACL reconstruction with reduced error particularly in the ligament attachment area. The method uses 3D preoperative data at different flexion angles to build a subject-specific statistical model of knee pose. To circumvent the problem of limited training samples and ensure physically meaningful pose instantiation, homogeneous transformations between different poses and local-deformation finite element modelling are used to enlarge the training set. Subsequently, an anatomical geodesic flexion analysis is performed to extract the subject-specific flexion characteristics. The advantages of the method were also tested by detailed comparison to standard Principal Component Analysis (PCA), nonlinear PCA without training set enlargement, and other state-of-The-Art articulated joint modelling methods. The method yielded sub-millimetre accuracy, demonstrating its potential clinical value

Constituting monetary conservatives via the 'savings habit': New Labour and the British housing market bubble

The ongoing world credit crunch might well kill off the most recent bubble dynamics in the British housing market by driving prices systematically downwards from their 2007 peak. Nonetheless, the experience of that bubble still warrants analytical attention. The Labour Government might not have been responsible for consciously creating it, but it has certainly grasped the opportunities the bubble has provided in an attempt to enforce a process of agential change at the heart of the British economy. The key issue in this respect is the way in which the Government has challenged the legitimacy of passive welfare receipts in favour of establishing a welfare system based on incorporating the individual into an active asset-holding society. The housing market has taken on new political significance as a means for individuals first to acquire assets and then to accumulate wealth on the back of asset ownership. The ensuing integration of the housing market into an increasingly reconfigured welfare system has permeated into the politics of everyday life. It has been consistent with individuals remaking their political subjectivities in line with preferences for the type of conservative monetary policies that typically keep house price bubbles inflated

Deep De-Aliasing for Fast Compressive Sensing MRI

Fast Magnetic Resonance Imaging (MRI) is highly in demand for many clinical applications in order to reduce the scanning cost and improve the patient experience. This can also potentially increase the image quality by reducing the motion artefacts and contrast washout. However, once an image field of view and the desired resolution are chosen, the minimum scanning time is normally determined by the requirement of acquiring sufficient raw data to meet the Nyquist-Shannon sampling criteria. Compressive Sensing (CS) theory has been perfectly matched to the MRI scanning sequence design with much less required raw data for the image reconstruction. Inspired by recent advances in deep learning for solving various inverse problems, we propose a conditional Generative Adversarial Networks-based deep learning framework for de-aliasing and reconstructing MRI images from highly undersampled data with great promise to accelerate the data acquisition process. By coupling an innovative content loss with the adversarial loss our de-aliasing results are more realistic. Furthermore, we propose a refinement learning procedure for training the generator network, which can stabilise the training with fast convergence and less parameter tuning. We demonstrate that the proposed framework outperforms state-of-the-art CS-MRI methods, in terms of reconstruction error and perceptual image quality. In addition, our method can reconstruct each image in 0.22ms--0.37ms, which is promising for real-time applications

Assessing Within-Field Variation in Alfalfa Leaf Area Index Using UAV Visible Vegetation Indices

This study examines the use of leaf area index (LAI) to inform variable-rate irrigation (VRI) for irrigated alfalfa (Medicago sativa). LAI is useful for predicting zone-specific evapotranspiration (ETc). One approach toward estimating LAI is to utilize the relationship between LAI and visible vegetation indices (VVIs) using unmanned aerial vehicle (UAV) imagery. This research has three objectives: (1) to measure and describe the within-field variation in LAI and canopy height for an irrigated alfalfa field, (2) to evaluate the relationships between the alfalfa LAI and various VVIs with and without field average canopy height, and (3) to use UAV images and field average canopy height to describe the within-field variation in LAI and the potential application to VRI. The study was conducted in 2021–2022 in Rexburg, Idaho. Over the course of the study, the measured LAI varied from 0.23 m2 m−2 to 11.28 m2 m−2 and canopy height varied from 6 cm to 65 cm. There was strong spatial clustering in the measured LAI but the spatial patterns were dynamic between dates. Among eleven VVIs evaluated, the four that combined green and red wavelengths but excluded blue wavelengths showed the most promise. For all VVIs, adding average canopy height to multiple linear regression improved LAI prediction. The regression model using the modified green–red vegetation index (MGRVI) and canopy height (R2 = 0.93) was applied to describe the spatial variation in the LAI among VRI zones. There were significant (p \u3c 0.05) but not practical differences

Changes in timber haul emissions in the context of shifting forest management and infrastructure

<p>Abstract</p> <p>Background</p> <p>Although significant amounts of carbon may be stored in harvested wood products, the extraction of that carbon from the forest generally entails combustion of fossil fuels. The transport of timber from the forest to primary milling facilities may in particular create emissions that reduce the net sequestration value of product carbon storage. However, attempts to quantify the effects of transport on the net effects of forest management typically use relatively sparse survey data to determine transportation emission factors. We developed an approach for systematically determining transport emissions using: 1) -remotely sensed maps to estimate the spatial distribution of harvests, and 2) - industry data to determine landscape-level harvest volumes as well as the location and processing totals of individual mills. These data support spatial network analysis that can produce estimates of fossil carbon released in timber transport.</p> <p>Results</p> <p>Transport-related emissions, evaluated as a fraction of transported wood carbon at 4 points in time on a landscape in western Montana (USA), rose from 0.5% in 1988 to 1.7% in 2004 as local mills closed and spatial patterns of harvest shifted due to decreased logging on federal lands.</p> <p>Conclusion</p> <p>The apparent sensitivity of transport emissions to harvest and infrastructure patterns suggests that timber haul is a dynamic component of forest carbon management that bears further study both across regions and over time. The monitoring approach used here, which draws only from widely available monitoring data, could readily be adapted to provide current and historical estimates of transport emissions in a consistent way across large areas.</p

Vaccination with DNA plasmids expressing Gn coupled to C3d or alphavirus replicons expressing Gn protects mice against rift valley fever virus

Background: Rift Valley fever (RVF) is an arthropod-borne viral zoonosis. Rift Valley fever virus (RVFV) is an important biological threat with the potential to spread to new susceptible areas. In addition, it is a potential biowarfare agent. Methodology/Principal Findings: We developed two potential vaccines, DNA plasmids and alphavirus replicons, expressing the Gn glycoprotein of RVFV alone or fused to three copies of complement protein, C3d. Each vaccine was administered to mice in an all DNA, all replicon, or a DNA prime/replicon boost strategy and both the humoral and cellular responses were assessed. DNA plasmids expressing Gn-C3d and alphavirus replicons expressing Gn elicited high titer neutralizing antibodies that were similar to titers elicited by the live-attenuated MP12 virus. Mice vaccinated with an inactivated form of MP12 did elicit high titer antibodies, but these antibodies were unable to neutralize RVFV infection. However, only vaccine strategies incorporating alphavirus replicons elicited cellular responses to Gn. Both vaccines strategies completely prevented weight loss and morbidity and protected against lethal RVFV challenge. Passive transfer of antisera from vaccinated mice into naïve mice showed that both DNA plasmids expressing Gn-C3d and alphavirus replicons expressing Gn elicited antibodies that protected mice as well as sera from mice immunized with MP12. Conclusion/Significance: These results show that both DNA plasmids expressing Gn-C3d and alphavirus replicons expressing Gn administered alone or in a DNA prime/replicon boost strategy are effective RVFV vaccines. These vaccine strategies provide safer alternatives to using live-attenuated RVFV vaccines for human use. © 2010 Bhardwaj et al

Biallelic variants in ADARB1, encoding a dsRNA-specific adenosine deaminase, cause a severe developmental and epileptic encephalopathy

Background Adenosine-to-inosine RNA editing is a co-transcriptional/post-transcriptional modification of double-stranded RNA, catalysed by one of two active adenosine deaminases acting on RNA (ADARs), ADAR1 and ADAR2. ADARB1 encodes the enzyme ADAR2 that is highly expressed in the brain and essential to modulate the function of glutamate and serotonin receptors. Impaired ADAR2 editing causes early onset progressive epilepsy and premature death in mice. In humans, ADAR2 dysfunction has been very recently linked to a neurodevelopmental disorder with microcephaly and epilepsy in four unrelated subjects. Methods We studied three children from two consanguineous families with severe developmental and epileptic encephalopathy (DEE) through detailed physical and instrumental examinations. Exome sequencing (ES) was used to identify ADARB1 mutations as the underlying genetic cause and in vitro assays with transiently transfected cells were performed to ascertain the impact on ADAR2 enzymatic activity and splicing. Results All patients showed global developmental delay, intractable early infantile-onset seizures, microcephaly, severe-to-profound intellectual disability, axial hypotonia and progressive appendicular spasticity. ES revealed the novel missense c.1889G&gt;A, p.(Arg630Gln) and deletion c.1245_1247+1 del, p.(Leu415PhefsTer14) variants in ADARB1 (NM_015833.4). The p.(Leu415PhefsTer14) variant leads to incorrect splicing resulting in frameshift with a premature stop codon and loss of enzyme function. In vitro RNA editing assays showed that the p.(Arg630Gln) variant resulted in a severe impairment of ADAR2 enzymatic activity. Conclusion In conclusion, these data support the pathogenic role of biallelic ADARB1 variants as the cause of a distinctive form of DEE, reinforcing the importance of RNA editing in brain function and development