Self-reported interoceptive deficits in eating disorders: A meta-analysis of studies using the eating disorder inventory

This document is the Accepted Manuscript version of the following article: Paul M. Jenkinson, Lauren Taylor, Keith R. Laws, ‘Self-reported interoceptive deficits in eating disorders: A meta-analysis of studies using the eating disorder inventory’, Journal of Psychosomatic Research, Vol. 110: 38-45, July 2018, under embargo until 19 April 2019. The Version of Record is available online at DOI: https://doi.org/10.1016/j.jpsychores.2018.04.005Objective: An impairment of the ability to sense the physiological condition of the body – interoception – has long been proposed as central to the onset and maintenance of eating disorders. More recent attention to this topic has generally indicated the presence of interoceptive deficits in individuals with an eating disorder diagnosis; however, possible links with specific diagnosis, BMI, age, illness duration, depression, and alexithymia remain unclear from individual studies. This meta-analysis aimed to provide a necessary quantitative overview of self-reported interoceptive deficits in eating disorder populations, and the relationship between these deficits and the previously mentioned factors. Methods: Using a random effects model, our meta-analysis assessed the magnitude of differences in interoceptive abilities as measured using the Eating Disorder Inventory in 41 samples comparing people with eating disorders (n=4308) and healthy controls (n=3459). Follow-up and moderator analysis was conducted, using group comparisons and meta-regressions. Results: We report a large pooled effect size of 1.62 for eating disorders with some variation between diagnostic groups. Further moderator analysis showed that BMI, age and alexithymia were significant predictors of overall effect size. Conclusion: This meta-analysis is the first to confirm that large interoceptive deficits occur in a variety of eating disorders and crucially, in those who have recovered. These deficits may be useful in identifying and distinguishing eating disorders. Future research needs to consider both objective and subjective measures of interoception across different types of eating disorders and may fruitfully examine interoception as a possible endophenotype and target for treatment.Peer reviewe

Algorithms for left atrial wall segmentation and thickness – Evaluation on an open-source CT and MRI image database

© 2018 The Authors Structural changes to the wall of the left atrium are known to occur with conditions that predispose to Atrial fibrillation. Imaging studies have demonstrated that these changes may be detected non-invasively. An important indicator of this structural change is the wall\u27s thickness. Present studies have commonly measured the wall thickness at few discrete locations. Dense measurements with computer algorithms may be possible on cardiac scans of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). The task is challenging as the atrial wall is a thin tissue and the imaging resolution is a limiting factor. It is unclear how accurate algorithms may get and how they compare in this new emerging area. We approached this problem of comparability with the Segmentation of Left Atrial Wall for Thickness (SLAWT) challenge organised in conjunction with MICCAI 2016 conference. This manuscript presents the algorithms that had participated and evaluation strategies for comparing them on the challenge image database that is now open-source. The image database consisted of cardiac CT (n=10) and MRI (n=10) of healthy and diseased subjects. A total of 6 algorithms were evaluated with different metrics, with 3 algorithms in each modality. Segmentation of the wall with algorithms was found to be feasible in both modalities. There was generally a lack of accuracy in the algorithms and inter-rater differences showed that algorithms could do better. Benchmarks were determined and algorithms were ranked to allow future algorithms to be ranked alongside the state-of-the-art techniques presented in this work. A mean atlas was also constructed from both modalities to illustrate the variation in thickness within this small cohort

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Assisting a Nonprofit in Creating a Sustainable Business in Cuenca, Ecuador

In Cuenca, Ecuador, the pandemic has caused difficulty for mothers to obtain the income required to support their family. The Hearts of Gold Foundation seeks to reduce job insecurity and financial instability by creating a cleaning business that employs disadvantaged mothers. To assist the foundation in their goal, we interviewed potential clients, employees, and people with legal experience, as well as researched the current market. Our investigations determined several stakeholder preferences: social responsibility, product options, and employee professionalism. We created a budgeting sheet and resource comparison tools to aid the facilitation of the business’s development. Upon examining the feasibility of the business, we determined it may need to start with fewer employees

Low AND Depth and Efficient Inverses: a Guide on S-boxes for Low-latency Masking

In this work, we perform an extensive investigation and construct a portfolio of S-boxes suitable for secure lightweight implementations, which aligns well with the ongoing NIST Lightweight Cryptography competition. In particular, we target good functional properties on the one hand and efficient implementations in terms of AND depth and AND gate complexity on the other. Moreover, we also consider the implementation of the inverse S-box and the possibility for it to share resources with the forward S-box. We take our exploration beyond the conventional small (and even) S-box sizes. Our investigation is twofold: (1) we note that implementations of existing S-boxes are not optimized for the criteria which define masking complexity (AND depth and AND gate complexity) and improve a tool published at FSE 2016 by Stoffelen in order to fill this gap. (2) We search for new S-box designs which take these implementation properties into account from the start. We perform a systematic search based on the properties of not only the S-box but also its inverse as well as an exploration of larger S-box sizes using length-doubling structures. The result of our investigation is not only a wide selection of very good S-boxes, but we also provide complete descriptions of their circuits, enabling their integration into future work

Low AND Depth and Efficient Inverses: a Guide on S-boxes for Low-latency Masking

In this work, we perform an extensive investigation and construct a portfolio of S-boxes suitable for secure lightweight implementations, which aligns well with the ongoing NIST Lightweight Cryptography competition. In particular, we target good functional properties on the one hand and efficient implementations in terms of AND depth and AND gate complexity on the other. Moreover, we also consider the implementation of the inverse S-box and the possibility for it to share resources with the forward S-box. We take our exploration bey ond the conventional small (and even) S-box sizes. Our investigation is twofold: (1) we note that implementations of existing S-boxes are not optimized for the criteria which define masking complexity(AND depth and AND gate complexity) and improve a tool published at FSE 2016by Stoffelen in order to fill this gap. (2) We search for new S-box designs which take these implementation properties into account from the start. We perform a systematic search based on the properties of not only the S-box but also its inverse as well as an exploration of larger S-box sizes using length-doubling structures. The result of our investigation is not only a wide selection of very good S-boxes, but weal so provide complete descriptions of their circuits, enabling their integration into future work

The University of Arizona Cooperative Extension Nutrition Network’s Contribution to the Arizona Economy in 2014

6 pp.The Arizona Nutrition Network (AzNN) is a public/private partnership engaged in a statewide effort to encourage healthy eating, increase physical activity, and achieve appropriate caloric balance for healthy body weights. The AzNN programmatic activities target people in low-income households that receive or are eligible to receive Supplemental Nutrition Assistance Program (SNAP) benefits. An integral partner in this statewide effort is the University of Arizona Cooperative Extension Nutrition Network (UANN), one of several local implementing agencies (LIAs) that conduct Supplemental Nutrition Assistance – Education (SNAP-Ed) programming throughout the state. The UANN receives funding from the AzNN to deliver nutrition and physical activity education programs to Arizona communities and implement policy, systems, and environmental approaches for obesity prevention