“I just want to be skinny.”: A content analysis of tweets expressing eating disorder symptoms

There is increasing concern about online communities that promote eating disorder (ED) behaviors through messages and/or images that encourage a “thin ideal” (i.e., promotion of thinness as attractive) and harmful weight loss/weight control practices. The purpose of this paper is to assess the content of body image and ED-related content on Twitter and provide a deeper understanding of EDs that may be used for future studies and online-based interventions. Tweets containing ED or body image-related keywords were collected from January 1-January 31, 2015 (N = 28,642). A random sample (n = 3000) was assessed for expressions of behaviors that align with subscales of the Eating Disorder Examination (EDE) 16.0. Demographic characteristics were inferred using a social media analytics company. The comprehensive research that we conducted indicated that 2,584 of the 3,000 tweets were ED-related; 65% expressed a preoccupation with body shape, 13% displayed issues related to food/eating/calories, and 4% expressed placing a high level of importance on body weight. Most tweets were sent by girls (90%) who were ≤19 years old (77%). Our findings stress a need to better understand if and how ED-related content on social media can be used for targeting prevention and intervention messages towards those who are in-need and could potentially benefit from these efforts.</div

Detection of functional PTEN lipid phosphatase protein and enzyme activity in squamous cell carcinomas of the head andeck, despite loss of heterozygosity at this locus

The human tumour suppressor gene PTEN located at 10q23 is mutated in a variety of tumour types particularly metastatic cases and in the germline of some individuals with Cowdens cancer predisposition syndrome. We have assessed the status of PTEN and associated pathways in cell lines derived from 19 squamous cell carcinomas of the head and neck. Loss of heterozygosity is evident at, or close to the PTEN gene in 5 cases, however there were no mutations in the remaining alleles. Furthermore by Western analysis PTEN protein levels are normal in all of these SCC-HN tumours and cell lines. To assess the possibility that PTEN may be inactivated by another mechanism, we characterized lipid phosphatase levels and from a specific PIP3 biochemical assay it is clear that PTEN is functionally active in all 19 human SCCs. Our data strongly suggest the possibility that a tumour suppressor gene associated with development of SCC-HN, other than PTEN, is located in this chromosomal region. This gene does not appear to be MXI-1, which has been implicated in some other human tumour types. PTEN is an important negative regulator of PI3Kinase, of which subunit alpha is frequently amplified in SCC-HN. To examine the possibility that PI3K is upregulated by amplification in this tumour set we assessed the phosphorylation status of Akt, a downstream target of PI3K. In all cases there is no detectable increase in Akt phosphorylation. Therefore there is no detectable defect in the PI3K pathway in SCC-HN suggesting that the reason for 3q26.3 over-representation may be due to genes other than PI3K110α. © 2001 Cancer Research Campaign http://www.bjcancer.co

A framework for applying natural language processing in digital health interventions

BACKGROUND: Digital health interventions (DHIs) are poised to reduce target symptoms in a scalable, affordable, and empirically supported way. DHIs that involve coaching or clinical support often collect text data from 2 sources: (1) open correspondence between users and the trained practitioners supporting them through a messaging system and (2) text data recorded during the intervention by users, such as diary entries. Natural language processing (NLP) offers methods for analyzing text, augmenting the understanding of intervention effects, and informing therapeutic decision making. OBJECTIVE: This study aimed to present a technical framework that supports the automated analysis of both types of text data often present in DHIs. This framework generates text features and helps to build statistical models to predict target variables, including user engagement, symptom change, and therapeutic outcomes. METHODS: We first discussed various NLP techniques and demonstrated how they are implemented in the presented framework. We then applied the framework in a case study of the Healthy Body Image Program, a Web-based intervention trial for eating disorders (EDs). A total of 372 participants who screened positive for an ED received a DHI aimed at reducing ED psychopathology (including binge eating and purging behaviors) and improving body image. These users generated 37,228 intervention text snippets and exchanged 4285 user-coach messages, which were analyzed using the proposed model. RESULTS: We applied the framework to predict binge eating behavior, resulting in an area under the curve between 0.57 (when applied to new users) and 0.72 (when applied to new symptom reports of known users). In addition, initial evidence indicated that specific text features predicted the therapeutic outcome of reducing ED symptoms. CONCLUSIONS: The case study demonstrates the usefulness of a structured approach to text data analytics. NLP techniques improve the prediction of symptom changes in DHIs. We present a technical framework that can be easily applied in other clinical trials and clinical presentations and encourage other groups to apply the framework in similar contexts

The Energetic Particle Detector (EPD) Investigation and the Energetic Ion Spectrometer (EIS) for the Magnetospheric Multiscale (MMS) Mission

Abstract The Energetic Particle Detector (EPD) Investigation is one of 5 fields-and-particles investigations on the Magnetospheric Multiscale (MMS) mission. MMS comprises 4 spacecraft flying in close formation in highly elliptical, near-Earth-equatorial orbits targeting understanding of the fundamental physics of the important physical process called magnetic reconnection using Earth’s magnetosphere as a plasma laboratory. EPD comprises two sensor types, the Energetic Ion Spectrometer (EIS) with one instrument on each of the 4 spacecraft, and the Fly’s Eye Energetic Particle Spectrometer (FEEPS) with 2 instruments on each of the 4 spacecraft. EIS measures energetic ion energy, angle and elemental compositional distributions from a required low energy limit of 20 keV for protons and 45 keV for oxygen ions, up to \u3e0.5 MeV (with capabilities to measure up to \u3e1 MeV). FEEPS measures instantaneous all sky images of energetic electrons from 25 keV to \u3e0.5 MeV, and also measures total ion energy distributions from 45 keV to \u3e0.5 MeV to be used in conjunction with EIS to measure all sky ion distributions. In this report we describe the EPD investigation and the details of the EIS sensor. Specifically we describe EPD-level science objectives, the science and measurement requirements, and the challenges that the EPD team had in meeting these requirements. Here we also describe the design and operation of the EIS instruments, their calibrated performances, and the EIS in-flight and ground operations. Blake et al. (The Flys Eye Energetic Particle Spectrometer (FEEPS) contribution to the Energetic Particle Detector (EPD) investigation of the Magnetospheric Magnetoscale (MMS) Mission, this issue) describe the design and operation of the FEEPS instruments, their calibrated performances, and the FEEPS in-flight and ground operations. The MMS spacecraft will launch in early 2015, and over its 2-year mission will provide comprehensive measurements of magnetic reconnection at Earth’s magnetopause during the 18 months that comprise orbital phase 1, and magnetic reconnection within Earth’s magnetotail during the about 6 months that comprise orbital phase 2

Investigating the Dynamics of Elk Population Size and Body Mass in a Seasonal Environment Using a Mechanistic Integral Projection Model

Environmentally mediated changes in body size often underlie population responses to environmental change, yet this is not a universal phenomenon. Understanding when phenotypic change underlies population responses to environmental change is important for obtaining insights and robust predictions of population dynamics in a changing world. We develop a dynamic integral projection model that mechanistically links environmental conditions to demographic rates and phenotypic traits (body size) via changes in resource availability and individual energetics. We apply the model to the northern Yellowstone elk population and explore population responses to changing patterns of seasonality, incorporating the interdependence of growth, demography, and density-dependent processes operating through population feedback on available resources. We found that small changes in body size distributions can have large impacts on population dynamics but need not cause population responses to environmental change. Environmental changes that altered demographic rates directly, via increasing or decreasing resource availability, led to large population impacts in the absence of substantial changes to body size distributions. In contrast, environmentally driven shifts in body size distributions could occur with little consequence for population dynamics when the effect of environmental change on resource availability was small and seasonally restricted and when strong density-dependent processes counteracted expected population responses. These findings highlight that a robust understanding of how associations between body size and demography influence population responses to environmental change will require knowledge of the shape of the relationship between phenotypic distributions and vital rates, the population status with regard to its carrying capacity, and importantly the nature of the environmentally driven change in body size and carrying capacity

Patterns of care and survival for patients aged under 40 years with bone sarcoma in Britain, 1980–1994

The purpose of the study was to calculate population-based survival rates for osteosarcoma (OS) and Ewing's sarcoma (ES) in Great Britain during 1980–1994, determine proportions of patients treated at specialist centres or entered in national and international clinical trials, and investigate effects of these factors on survival. Data on a population-based series of 1349 patients with OS and 849 with ES were compiled from regional and national cancer registries, UK Children's Cancer Study Group, regional bone tumour registries and clinical trials. Follow-up was through population registers. Survival was analysed by actuarial analysis with log-rank tests and by Cox's proportional hazards analysis. Five-year survival rates during 1980–1984, 1985–1989 and 1990–1994 were 42% (95% CI: 37, 46), 54% (95% CI: 50, 59) and 53% (95% CI: 48, 57), respectively, for OS and 31% (95% CI: 26, 37), 46% (95% CI: 40, 51) and 51% (95% CI: 45, 57) for ES. Proportions of patients treated at a supraregional bone tumour centre or a paediatric oncology centre in the three quinquennia were 36, 56 and 67% for OS and 41, 60 and 69% for ES. In 1983–1992, 48% of OS patients were entered in a national trial; for ES, 27% were entered in 1980–1986 and 54% in 1987–1994. Survival was similar for trial and nontrial patients with OS. For ES, trial patients had consistently higher 5-year survival than nontrial patients: 1980–1986, 42 vs 30%; 1987–1992, 59 vs 42%; 1993–1994, 54 vs 43%. During 1985–1994, patients with OS or ES whose main treatment centre was a nonteaching hospital had lower survival rates. In multivariate analyses of patients diagnosed during 1985–1994 that also included age, sex, primary site, surgical treatment centre, the results relating to main treatment centre for both OS and ES retained significance but the survival advantage of trial entry for ES became nonsignificant. For both OS and ES diagnosed since 1985, patients whose main treatment centre was a nonspecialist hospital had a lower survival rate

Asset liability modelling and pension schemes: the application of robust optimization to USS

This paper uses a novel numerical optimization technique - robust optimization - that is well suited to solving the asset-liability management (ALM) problem for pension schemes. It requires the estimation of fewer stochastic parameters, reduces estimation risk and adopts a prudent approach to asset allocation. This study is the first to apply it to a real-world pension scheme, and the first ALM model of a pension scheme to maximise the Sharpe ratio. We disaggregate pension liabilities into three components - active members, deferred members and pensioners, and transform the optimal asset allocation into the scheme’s projected contribution rate. The robust optimization model is extended to include liabilities and used to derive optimal investment policies for the Universities Superannuation Scheme (USS), benchmarked against the Sharpe and Tint, Bayes-Stein, and Black-Litterman models as well as the actual USS investment decisions. Over a 144 month out-of-sample period robust optimization is superior to the four benchmarks across 20 performance criteria, and has a remarkably stable asset allocation – essentially fix-mix. These conclusions are supported by six robustness checks

Changes in Adiposity and Cerebrospinal Fluid Biomarkers Following a Modified Mediterranean Ketogenic Diet in Older Adults at Risk for Alzheimer's Disease

Background: Ketogenic diets have been used to treat both obesity and neurological disorders, including epilepsy and more recently Alzheimer's disease (AD), likely due to favorable effects on both central and peripheral metabolism. Improvements in body composition have also been reported; however, it is unclear if diet-induced changes in adiposity are related to improvements in AD and related neuropathology. Purpose: We examined the effects of a Modified Mediterranean Ketogenic (MMK) diet vs. an American Heart Association (AHA) diet on body weight, body composition, and body fat distribution and their association with cerebrospinal fluid (CSF) biomarkers in older adults at risk for AD. Methods: Twenty adults (mean age: 64.3 ± 6.3 years, 35% Black, 75% female) were randomly assigned to a crossover trial starting with either the MMK or AHA diet for 6 weeks, followed by a 6-week washout and then the opposite diet for 6 weeks. At baseline and after each diet adiposity was assessed by dual-energy x-ray absorptiometry and CSF biomarkers were measured. Linear mixed effect models were used to examine the effect of diet on adiposity. Spearman correlations were examined to assess associations between adiposity and CSF biomarkers. Results: At baseline there was a high prevalence of overweight/obesity and central adiposity, and higher visceral fat and lower peripheral fat were associated with an adverse CSF biomarker profile. The MMK and AHA diets led to similar improvements in body composition and body fat distribution. Significant correlations were found between changes in adiposity and changes in CSF biomarkers (r's = 0.63-0.92, p's < 0.05), with notable differences by diet. Decreases in body fat on the MMK diet were related to changes in Aβ biomarkers, whereas decreases in body fat on the AHA diet were related to changes in tau biomarkers and cholinesterase activity. Interestingly, increases in CSF Aβ on the MMK diet occurred in those with less fat loss. Conclusion: An MMK diet leads to favorable changes in body composition, body fat distribution, and CSF biomarkers. Our data suggest that modest weight loss that maximizes visceral fat loss and preserves peripheral fat, may have the greatest impact on brain health. Clinical Trial Registration: [www.ClinicalTrials.gov], identifier [NCT02984540]