Geographical location influences the composition of the gut microbiota in wild house mice (Mus musculus domesticus) at a fine spatial scale.

The composition of the mammalian gut microbiota can be influenced by a multitude of environmental variables such as diet and infections. Studies investigating the effect of these variables on gut microbiota composition often sample across multiple separate populations and habitat types. In this study we explore how variation in the gut microbiota of the house mouse (Mus musculus domesticus) on the Isle of May, a small island off the east coast of Scotland, is associated with environmental and biological factors. Our study focuses on the effects of environmental variables, specifically trapping location and surrounding vegetation, as well as the host variables sex, age, body weight and endoparasite infection, on the gut microbiota composition across a fine spatial scale in a freely interbreeding population. We found that differences in gut microbiota composition were significantly associated with the trapping location of the host, even across this small spatial scale. Sex of the host showed a weak association with microbiota composition. Whilst sex and location could be identified as playing an important role in the compositional variation of the gut microbiota, 75% of the variation remains unexplained. Whereas other rodent studies have found associations between gut microbiota composition and age of the host or parasite infections, the present study could not clearly establish these associations. We conclude that fine spatial scales are important when considering gut microbiota composition and investigating differences among individuals

FU-net: Multi-class Image Segmentation Using Feedback Weighted U-net

In this paper, we present a generic deep convolutional neural network (DCNN) for multi-class image segmentation. It is based on a well-established supervised end-to-end DCNN model, known as U-net. U-net is firstly modified by adding widely used batch normalization and residual block (named as BRU-net) to improve the efficiency of model training. Based on BRU-net, we further introduce a dynamically weighted cross-entropy loss function. The weighting scheme is calculated based on the pixel-wise prediction accuracy during the training process. Assigning higher weights to pixels with lower segmentation accuracies enables the network to learn more from poorly predicted image regions. Our method is named as feedback weighted U-net (FU-net). We have evaluated our method based on T1- weighted brain MRI for the segmentation of midbrain and substantia nigra, where the number of pixels in each class is extremely unbalanced to each other. Based on the dice coefficient measurement, our proposed FU-net has outperformed BRU-net and U-net with statistical significance, especially when only a small number of training examples are available. The code is publicly available in GitHub (GitHub link: https://github.com/MinaJf/FU-net).Comment: Accepted for publication at International Conference on Image and Graphics (ICIG 2019

Echinoderms have bilateral tendencies

Echinoderms take many forms of symmetry. Pentameral symmetry is the major form and the other forms are derived from it. However, the ancestors of echinoderms, which originated from Cambrian period, were believed to be bilaterians. Echinoderm larvae are bilateral during their early development. During embryonic development of starfish and sea urchins, the position and the developmental sequence of each arm are fixed, implying an auxological anterior/posterior axis. Starfish also possess the Hox gene cluster, which controls symmetrical development. Overall, echinoderms are thought to have a bilateral developmental mechanism and process. In this article, we focused on adult starfish behaviors to corroborate its bilateral tendency. We weighed their central disk and each arm to measure the position of the center of gravity. We then studied their turning-over behavior, crawling behavior and fleeing behavior statistically to obtain the center of frequency of each behavior. By joining the center of gravity and each center of frequency, we obtained three behavioral symmetric planes. These behavioral bilateral tendencies might be related to the A/P axis during the embryonic development of the starfish. It is very likely that the adult starfish is, to some extent, bilaterian because it displays some bilateral propensity and has a definite behavioral symmetric plane. The remainder of bilateral symmetry may have benefited echinoderms during their evolution from the Cambrian period to the present

Pathophysiological regulation of lung function by the free fatty acid receptor FFA4.

Increased prevalence of inflammatory airway diseases including asthma and chronic obstructive pulmonary disease (COPD) together with inadequate disease control by current frontline treatments means that there is a need to define therapeutic targets for these conditions. Here, we investigate a member of the G protein-coupled receptor family, FFA4, that responds to free circulating fatty acids including dietary omega-3 fatty acids found in fish oils. We show that FFA4, although usually associated with metabolic responses linked with food intake, is expressed in the lung where it is coupled to Gq/11 signaling. Activation of FFA4 by drug-like agonists produced relaxation of murine airway smooth muscle mediated at least in part by the release of the prostaglandin E2 (PGE2) that subsequently acts on EP2 prostanoid receptors. In normal mice, activation of FFA4 resulted in a decrease in lung resistance. In acute and chronic ozone models of pollution-mediated inflammation and house dust mite and cigarette smoke-induced inflammatory disease, FFA4 agonists acted to reduce airway resistance, a response that was absent in mice lacking expression of FFA4. The expression profile of FFA4 in human lung was similar to that observed in mice, and the response to FFA4/FFA1 agonists similarly mediated human airway smooth muscle relaxation ex vivo. Our study provides evidence that pharmacological targeting of lung FFA4, and possibly combined activation of FFA4 and FFA1, has in vivo efficacy and might have therapeutic value in the treatment of bronchoconstriction associated with inflammatory airway diseases such as asthma and COPD

MRI for patients with cardiac implantable electronic devices: simplifying complexity with a 'one-stop' service model

BACKGROUND: Patients with cardiac pacemakers and defibrillators are disadvantaged because of poor access to MRI scans, leading to late and misdiagnosis particularly for cancer and neurological disease. New technology allied to tested protocols now allows safe MRI scanning of such patients; however, logistical barriers persist. AIM: To deliver a streamlined sustainable service that provides timely MRI scans to patients with cardiac implantable electronic devices (CIEDs). METHODS: Patients requested a 'one-stop' service for MRI, whereby devices could be reprogrammed and scans acquired at a single location and visit. To provide this 'one-stop' service, we trained a team including administrators, physicians, cardiac physiologists and radiographers. A standard protocol was used to prevent unnecessary request refusals and delays to scheduling. Service volume, waiting time and safety were analysed 6 months before and 2 years after service redesign. Waiting times for internal and external inpatient referrals plus time to treatment for patients on a cancer pathway were analysed. RESULTS: 215 MRI scans were performed over 2 years. After service redesign, MRI provision increased six-fold to 20 times the national average with reduced waiting time from 60 to 15 days and no adverse events. Departmental throughput was maintained. 85 (40%) referrals were external. 41 (19%) inpatients were scanned, reducing bed-stay by 3 days for internal referrals. 24 (11%) scans were for suspected cancer, 83% allowed treatment within the national standard of 62 days. There was no preintervention service for either inpatients or suspected cancer investigation. CONCLUSION: Implementation of a 'one-stop' service model to provide MRI for patients with CIEDs is safe, streamlined, scalable and has reduced delays making economic and clinical sense. Protocols and checklists are available at mrimypacemaker.com

Object Detection Through Exploration With A Foveated Visual Field

We present a foveated object detector (FOD) as a biologically-inspired alternative to the sliding window (SW) approach which is the dominant method of search in computer vision object detection. Similar to the human visual system, the FOD has higher resolution at the fovea and lower resolution at the visual periphery. Consequently, more computational resources are allocated at the fovea and relatively fewer at the periphery. The FOD processes the entire scene, uses retino-specific object detection classifiers to guide eye movements, aligns its fovea with regions of interest in the input image and integrates observations across multiple fixations. Our approach combines modern object detectors from computer vision with a recent model of peripheral pooling regions found at the V1 layer of the human visual system. We assessed various eye movement strategies on the PASCAL VOC 2007 dataset and show that the FOD performs on par with the SW detector while bringing significant computational cost savings.Comment: An extended version of this manuscript was published in PLOS Computational Biology (October 2017) at https://doi.org/10.1371/journal.pcbi.100574

Absence of gastrointestinal infections in a cohort of patients with Zollinger-Ellison syndrome and other acid hypersecretors receiving long-term acid suppression with lansoprazole

<p>Abstract</p> <p>Background</p> <p>The relationship between proton pump inhibitor therapy and other acid suppressing medications and the risk of gastrointestinal infections remains controversial.</p> <p>Methods</p> <p>Patients enrolled in a long-term trial of lansoprazole for Zollinger-Ellison syndrome and other acid hypersecretory states had interval histories taken every six months regarding hospitalizations or other intercurrent medical conditions. All medications taken were also reviewed at each visit. In addition, available patients were specifically queried during the study period 2006–2007 regarding the development of any gastrointestinal infections, hospitalizations, and prescriptions for antibiotics.</p> <p>Results</p> <p>Ninety patients were enrolled in our long-term study and 81 were available for review. The median basal gastric pH for the cohort after stabilization on therapy was 2.9 and ranged from 1.1 – 8.4 with a median pentagastrin stimulated gastric pH of 1.60 (range 1.0 – 8.2). No patient developed a clinically significant gastrointestinal infection during the study. The median patient years of follow-up were 6.25 years.</p> <p>Conclusion</p> <p>In a cohort of patients with gastric acid hypersecretion in whom acid secretion status was monitored on lansoprazole, all were free of significant gastrointestinal infections on long-term follow-up.</p> <p>Trial registration</p> <p>NCT00204373</p

A cognitive forcing tool to mitigate cognitive bias:A randomised control trial

Abstract Background Cognitive bias is an important source of diagnostic error yet is a challenging area to understand and teach. Our aim was to determine whether a cognitive forcing tool can reduce the rates of error in clinical decision making. A secondary objective was to understand the process by which this effect might occur. Methods We hypothesised that using a cognitive forcing tool would reduce diagnostic error rates. To test this hypothesis, a novel online case-based approach was used to conduct a single blinded randomized clinical trial conducted from January 2017 to September 2018. In addition, a qualitative series of “think aloud” interviews were conducted with 20 doctors from a UK teaching hospital in 2018. The primary outcome was the diagnostic error rate when solving bias inducing clinical vignettes. A volunteer sample of medical professionals from across the UK, Republic of Ireland and North America. They ranged in seniority from medical student to Attending Physician. Results Seventy six participants were included in the study. The data showed doctors of all grades routinely made errors related to cognitive bias. There was no difference in error rates between groups (mean 2.8 cases correct in intervention vs 3.1 in control group, 95% CI -0.94 – 0.45 P = 0.49). The qualitative protocol revealed that the cognitive forcing strategy was well received and a produced a subjectively positive impact on doctors’ accuracy and thoughtfulness in clinical cases. Conclusions The quantitative data failed to show an improvement in accuracy despite a positive qualitative experience. There is insufficient evidence to recommend this tool in clinical practice, however the qualitative data suggests such an approach has some merit and face validity to users

Branch&Rank for Efficient Object Detection

Ranking hypothesis sets is a powerful concept for efficient object detection. In this work, we propose a branch&rank scheme that detects objects with often less than 100 ranking operations. This efficiency enables the use of strong and also costly classifiers like non-linear SVMs with RBF-χ2 kernels. We thereby relieve an inherent limitation of branch&bound methods as bounds are often not tight enough to be effective in practice. Our approach features three key components: a ranking function that operates on sets of hypotheses and a grouping of these into different tasks. Detection efficiency results from adaptively sub-dividing the object search space into decreasingly smaller sets. This is inherited from branch&bound, while the ranking function supersedes a tight bound which is often unavailable (except for rather limited function classes). The grouping makes the system effective: it separates image classification from object recognition, yet combines them in a single formulation, phrased as a structured SVM problem. A novel aspect of branch&rank is that a better ranking function is expected to decrease the number of classifier calls during detection. We use the VOC’07 dataset to demonstrate the algorithmic properties of branch&rank.ISSN:0920-5691ISSN:1573-140