Automatic 3D bi-ventricular segmentation of cardiac images by a shape-refined multi-task deep learning approach

Deep learning approaches have achieved state-of-the-art performance in cardiac magnetic resonance (CMR) image segmentation. However, most approaches have focused on learning image intensity features for segmentation, whereas the incorporation of anatomical shape priors has received less attention. In this paper, we combine a multi-task deep learning approach with atlas propagation to develop a shape-constrained bi-ventricular segmentation pipeline for short-axis CMR volumetric images. The pipeline first employs a fully convolutional network (FCN) that learns segmentation and landmark localisation tasks simultaneously. The architecture of the proposed FCN uses a 2.5D representation, thus combining the computational advantage of 2D FCNs networks and the capability of addressing 3D spatial consistency without compromising segmentation accuracy. Moreover, the refinement step is designed to explicitly enforce a shape constraint and improve segmentation quality. This step is effective for overcoming image artefacts (e.g. due to different breath-hold positions and large slice thickness), which preclude the creation of anatomically meaningful 3D cardiac shapes. The proposed pipeline is fully automated, due to network's ability to infer landmarks, which are then used downstream in the pipeline to initialise atlas propagation. We validate the pipeline on 1831 healthy subjects and 649 subjects with pulmonary hypertension. Extensive numerical experiments on the two datasets demonstrate that our proposed method is robust and capable of producing accurate, high-resolution and anatomically smooth bi-ventricular 3D models, despite the artefacts in input CMR volumes

Differential Gene Expression in High- and Low-Active Inbred Mice

Numerous candidate genes have been suggested in the recent literature with proposed roles in regulation of voluntary physical activity, with little evidence of these genes' functional roles. This study compared the haplotype structure and expression profile in skeletal muscle and brain of inherently high- (C57L/J) and low- (C3H/HeJ) active mice. Expression of nine candidate genes [Actn2, Actn3, Casq1, Drd2, Lepr, Mc4r, Mstn, Papss2, and Glut4 (a.k.a. Slc2a4)] was evaluated via RT-qPCR. SNPs were observed in regions of Actn2, Casq1, Drd2, Lepr, and Papss2; however, no SNPs were located in coding sequences or associated with any known regulatory sequences. In mice exposed to a running wheel, Casq1 (P = 0.0003) and Mstn (P = 0.002) transcript levels in the soleus were higher in the low-active mice. However, when these genes were evaluated in naïve animals, differential expression was not observed, demonstrating a training effect. Among naïve mice, no genes in either tissue exhibited differential expression between strains. Considering that no obvious SNP mechanisms were determined or differential expression was observed, our results indicate that genomic structural variation or gene expression data alone is not adequate to establish any of these genes' candidacy or causality in relation to regulation of physical activity

Deep learning cardiac motion analysis for human survival prediction

Motion analysis is used in computer vision to understand the behaviour of moving objects in sequences of images. Optimising the interpretation of dynamic biological systems requires accurate and precise motion tracking as well as efficient representations of high-dimensional motion trajectories so that these can be used for prediction tasks. Here we use image sequences of the heart, acquired using cardiac magnetic resonance imaging, to create time-resolved three-dimensional segmentations using a fully convolutional network trained on anatomical shape priors. This dense motion model formed the input to a supervised denoising autoencoder (4Dsurvival), which is a hybrid network consisting of an autoencoder that learns a task-specific latent code representation trained on observed outcome data, yielding a latent representation optimised for survival prediction. To handle right-censored survival outcomes, our network used a Cox partial likelihood loss function. In a study of 302 patients the predictive accuracy (quantified by Harrell's C-index) was significantly higher (p < .0001) for our model C=0.73 (95$\%$ CI: 0.68 - 0.78) than the human benchmark of C=0.59 (95$\%$ CI: 0.53 - 0.65). This work demonstrates how a complex computer vision task using high-dimensional medical image data can efficiently predict human survival

The MH1 domain of Smad3 interacts with Pax6 and represses autoregulation of the Pax6 P1 promoter

Pax6 transcription is under the control of two main promoters (P0 and P1), and these are autoregulated by Pax6. Additionally, Pax6 expression is under the control of the TGFβ superfamily, although the precise mechanisms of such regulation are not understood. The effect of TGFβ on Pax6 expression was studied in the FHL124 lens epithelial cell line and was found to cause up to a 50% reduction in Pax6 mRNA levels within 24 h. Analysis of luciferase reporters showed that Pax6 autoregulation of the P1 promoter, and its induction of a synthetic promoter encoding six paired domain-binding sites, were significantly repressed by both an activated TGFβ receptor and TGFβ ligand stimulation. Subsequently, a novel Pax6 binding site in P1 was shown to be necessary for autoregulation, indicating a direct influence of Pax6 protein on P1. In transfected cells, and endogenously in FHL124 cells, Pax6 co-immunoprecipitated with Smad3 following TGFβ receptor activation, while in GST pull-down experiments, the MH1 domain of Smad3 was observed binding the RED sub-domain of the Pax6 paired domain. Finally, in DNA adsorption assays, activated Smad3 inhibited Pax6 from binding the consensus paired domain recognition sequence. We hypothesize that the Pax6 autoregulatory loop is targeted for repression by the TGFβ/Smad pathway, and conclude that this involves diminished paired domain DNA-binding function resulting from a ligand-dependant interaction between Pax6 and Smad3

Differential Gene Expression in High- and Low-Active Inbred Mice

Numerous candidate genes have been suggested in the recent literature with proposed roles in regulation of voluntary physical activity, with little evidence of these genes’ functional roles. This study compared the haplotype structure and expression profile in skeletal muscle and brain of inherently high- (C57L/J) and low- (C3H/HeJ) active mice. Expression of nine candidate genes [Actn2, Actn3, Casq1, Drd2, Lepr, Mc4r, Mstn, Papss2, and Glut4 (a.k.a. Slc2a4)] was evaluated via RT-qPCR. SNPs were observed in regions of Actn2, Casq1, Drd2, Lepr, and Papss2; however, no SNPs were located in coding sequences or associated with any known regulatory sequences. In mice exposed to a running wheel, Casq1 (P=0.0003) and Mstn (P=0.002) transcript levels in the soleus were higher in the low-active mice. However, when these genes were evaluated in naïve animals, differential expression was not observed, demonstrating a training effect. Among naïve mice, no genes in either tissue exhibited differential expression between strains. Considering that no obvious SNP mechanisms were determined or differential expression was observed, our results indicate that genomic structural variation or gene expression data alone is not adequate to establish any of these genes’ candidacy or causality in relation to regulation of physical activity

Correction for Kipkorir et al., "De Novo Cobalamin Biosynthesis, Transport, and Assimilation and Cobalamin-Mediated Regulation of Methionine Biosynthesis in Mycobacterium smegmatis"

Volume 203, no. 7, e00620-20, 2021, https://doi.org/10.1128/JB.00620-20. Page 1: This article was published on 8 March 2021 with Stephanie S. Dawes missing from the byline. The byline was updated in the version posted on 21 January 2022. The following corrections were also made in that version. Page 1, footnote box: The following footnote was added. “§Present address: Stephanie S. Dawes, Laboratory of Structural Biology, School of Biological Sciences and Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland, New Zealand.” Page 14, Acknowledgments, line 3: “and Stephanie Dawes for providing the DmetE cobK::hyg mutant” was deleted. Page 14, Acknowledgments, lines 1 and 2 from bottom: “(to V.M. and D.F.W.)” was changed to “(to S.S.D., V.M., and D.F.W.).

Pulmonary artery stiffness is independently associated with right ventricular mass and function: a cardiac MR imaging study

Purpose: To determine the relationship between pulmonary artery (PA) stiffness and both right ventricular (RV) mass and function with cardiac magnetic resonance (MR) imaging.Materials and Methods: The study was approved by the local research ethics committee, and all participants gave written informed consent. Cardiac MR imaging was performed at 1.5 T in 156 healthy volunteers (63% women; age range, 19-61 years; mean age, 36.1 years). High-temporal-resolution phase-contrast imaging was performed in the main and right PAs. Pulmonary pulse wave velocity (PWV) was determined by the interval between arterial systolic upslopes. RV function was assessed with feature tracking to derive peak systolic strain and strain rate, as well as peak early-diastolic strain rate. RV volumes, ejection fraction (RVEF), and mass were measured from the cine images. The association of pulmonary PWV with RV function and mass was quantified with univariate linear regression. Interstudy repeatability was assessed with intraclass correlation.Results: The repeatability coefficient for pulmonary PWV was 0.96. Increases in pulmonary PWV and RVEF were associated with increases in age (r = 0.32, P < .001 and r = 0.18, P = .025, respectively). After adjusting for age (P = .090), body surface area (P = .073), and sex (P = .005), pulmonary PWV demonstrated an independent positive association with RVEF (r = 0.34, P = .026). Significant associations were also seen with RV mass (r = 0.41, P = .004), RV radial strain (r = 0.38, P =. 022), and strain rate (r = 0.35, P = .002), and independent negative associations were seen with radial (r = 0.27, P = .003), longitudinal (r = 0.40, P = .007), and circumferential (r = 0.31, P = .005) peak early-diastolic strain rate with the same covariates.Conclusion: Pulmonary PWV is reliably assessed with cardiac MR imaging. In subjects with no known cardiovascular disease, increasing PA stiffness is associated with increasing age and is also moderately associated with both RV mass and function after controlling for age, body surface area, and sex. (C) RSNA, 201

SEND: a system for electronic notification and documentation of vital sign observations

Background: Recognising the limitations of a paper-based approach to documenting vital sign observations and responding to national clinical guidelines, we have explored the use of an electronic solution that could improve the quality and safety of patient care. We have developed a system for recording vital sign observations at the bedside, automatically calculating an Early Warning Score, and saving data such that it is accessible to all relevant clinicians within a hospital trust. We have studied current clinical practice of using paper observation charts, and attempted to streamline the process. We describe our user-focussed design process, and present the key design decisions prior to describing the system in greater detail. Results: The system has been deployed in three pilot clinical areas over a period of 9 months. During this time, vital sign observations were recorded electronically using our system. Analysis of the number of observations recorded (21,316 observations) and the number of active users (111 users) confirmed that the system is being used for routine clinical observations. Feedback from clinical end-users was collected to assess user acceptance of the system. This resulted in a System Usability Scale score of 77.8, indicating high user acceptability. Conclusions: Our system has been successfully piloted, and is in the process of full implementation throughout adult inpatient clinical areas in the Oxford University Hospitals. Whilst our results demonstrate qualitative acceptance of the system, its quantitative effect on clinical care is yet to be evaluated

Burying the 'refuse revolution': the rise of controlled tipping in Britain 1920-1960

The definitive, peer-reviewed and edited version of this article is published in Environment and Planning A, 42, 5, 1033-1048, 2010, 10.1068/a42120.This paper investigates the emergence of ‘controlled tipping’ as the dominant method of municipal waste disposal in Britain between 1920 and 1960. The triumph of controlled tipping, despite the availability of alternative disposal technologies, needs to be understood in the context of the contested meanings of ‘waste’ and ‘wasteland’, which helped to determine attitudes and approaches to disposal. Following the conclusion of the First World War there was an urgent requirement for a cheap means of disposing of increasing amounts of urban municipal waste. The obvious choice was tipping. Before the war, however, refuse tipping had been rejected as insanitary by the emerging waste disposal profession. Public cleansing professionals therefore had to recuperate tipping as a medically and environmentally benign mode of disposal that was reconcilable with the needs of sanitary science and landscape preservation. Controlled tipping, with its combined claims to scientific progress and the revalorization of refuse, enabled dumping to be successfully re-produced as the dominant mode of municipal refuse disposal in Britain. However, tipping faced further challenges after 1945 from changing popular understandings of the value of ‘derelict’ landscapes and from the politics of amenity. The ‘refuse revolution’ was a work in progress

Development and psychometric testing of an instrument to evaluate cognitive skills of evidence based practice in student health professionals

<p>Abstract</p> <p>Background</p> <p>Health educators need rigorously developed instruments to evaluate cognitive skills relating to evidence based practice (EBP). Previous EBP evaluation instruments have focused on the acquisition and appraisal of the evidence and are largely based in the medical profession. The aim of this study was to develop and validate an EBP evaluation instrument to assess EBP cognitive skills for entry-level health professional disciplines.</p> <p>Methods</p> <p>The Fresno test of competence in evidence based medicine was considered in the development of the 'Knowledge of Research Evidence Competencies' instrument (K-REC). The K-REC was reviewed for content validity. Two cohorts of entry-level students were recruited for the pilot study, those who had been exposed to EBP training (physiotherapy students, n = 24), and who had not been exposed to EBP training (human movement students, n = 76). The K-REC was administered to one cohort of students (n = 24) on two testing occasions to evaluate test-retest reliability. Two raters independently scored the first test occasion (n = 24) to evaluate the inter-rater reliability of the marking guidelines. Construct validity was assessed by comparison of the two groups, 'exposed' and 'non-exposed', and the percentage of students achieving a 'pass' score in each of these groups. Item difficulty was established.</p> <p>Results</p> <p>Among the 100 participants (24 EBP 'exposed', and 76 EBP 'non-exposed' students), there was a statistically significant (<it>p </it>< 0.0001) difference in the total K-REC scores. The test-retest and inter-rater reliability of the individual items and total scores ranged from moderate to excellent (measured by Cohen's Kappa and ICC, range: 0.62 to perfect agreement).</p> <p>Conclusions</p> <p>The K-REC instrument is a valid and reliable evaluation instrument of cognitive skills of EBP in entry-level student health professionals. The instrument is quick to disseminate and easy to score, making it a suitable instrument for health educators to employ to evaluate students' knowledge of EBP or in the evaluation of entry-level EBP training.</p