DeepCare: A Deep Dynamic Memory Model for Predictive Medicine

Personalized predictive medicine necessitates the modeling of patient illness and care processes, which inherently have long-term temporal dependencies. Healthcare observations, recorded in electronic medical records, are episodic and irregular in time. We introduce DeepCare, an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes. At the data level, DeepCare represents care episodes as vectors in space, models patient health state trajectories through explicit memory of historical records. Built on Long Short-Term Memory (LSTM), DeepCare introduces time parameterizations to handle irregular timed events by moderating the forgetting and consolidation of memory cells. DeepCare also incorporates medical interventions that change the course of illness and shape future medical risk. Moving up to the health state level, historical and present health states are then aggregated through multiscale temporal pooling, before passing through a neural network that estimates future outcomes. We demonstrate the efficacy of DeepCare for disease progression modeling, intervention recommendation, and future risk prediction. On two important cohorts with heavy social and economic burden -- diabetes and mental health -- the results show improved modeling and risk prediction accuracy.Comment: Accepted at JBI under the new name: "Predicting healthcare trajectories from medical records: A deep learning approach

Sensory Electrical Stimulation Improves Foot Placement during Targeted Stepping Post-Stroke

Proper foot placement is vital for maintaining balance during walking, requiring the integration of multiple sensory signals with motor commands. Disruption of brain structures post-stroke likely alters the processing of sensory information by motor centers, interfering with precision control of foot placement and walking function for stroke survivors. In this study, we examined whether somatosensory stimulation, which improves functional movements of the paretic hand, could be used to improve foot placement of the paretic limb. Foot placement was evaluated before, during, and after application of somatosensory electrical stimulation to the paretic foot during a targeted stepping task. Starting from standing, twelve chronic stroke participants initiated movement with the non-paretic limb and stepped to one of five target locations projected onto the floor with distances normalized to the paretic stride length. Targeting error and lower extremity kinematics were used to assess changes in foot placement and limb control due to somatosensory stimulation. Significant reductions in placement error in the medial–lateral direction (p = 0.008) were observed during the stimulation and post-stimulation blocks. Seven participants, presenting with a hip circumduction walking pattern, had reductions (p = 0.008) in the magnitude and duration of hip abduction during swing with somatosensory stimulation. Reductions in circumduction correlated with both functional and clinical measures, with larger improvements observed in participants with greater impairment. The results of this study suggest that somatosensory stimulation of the paretic foot applied during movement can improve the precision control of foot placement

From venture idea to venture formation:The role of sensemaking, sensegiving and sense receiving

This article explores the sensemaking processes entrepreneurs use when transitioning between venture ideas and venture formation. Adopting a sensemaking/sensegiving approach and utilising an interpretivist methodology, we use sensemaking to analyse the entrepreneurial journey of four diverse entrepreneurs. In so doing, we make three contributions: first, we locate the early stages of the entrepreneurial context as a primary site where sensemaking occurs as entrepreneurs deal with the differences between expectations and reality. Second, we show how sensemaking occurs when entrepreneurs build a causal map of the problem they wish to address and how social exchanges are crucial as entrepreneurs then refine that idea with other sensegivers. Finally, we extend scholarly understanding through explaining the ways in which sensemaking, sensegiving and sense receiving contribute to the entrepreneurs' decision to act and create a new venture

Particle emission characteristics of a gas turbine with a double annular combustor

The total climate, air quality and health impact of aircraft black carbon (BC) emissions depends on quantity (mass and number concentration), as well as morphology (fractal dimension and surface area) of emitted BC aggregates. This study examines multiple BC emission metrics from a gas turbine with a double annular combustor, CFM56-5B4-2P. As a part of the SAMPLE III.2 campaign, concurrent measurements of particle mobility, particle mass, particle number concentration and mass concentration, as well as collection of transmission electron microscopy (TEM) samples, allowed for characterization of the BC emissions. Mass- and number-based emission indices were strongly influenced by thrust setting during pilot combustion and ranged from <1 to 208 mg/kg-fuel and 3×1012 to 3×1016 particles/kg-fuel, respectively. Mobility measurements indicated that mean diameters ranged from 7-44 nm with a strong dependence on thrust during pilot-only combustion. Using aggregation and sintering theory with empirical effective density relationships, a power law relationship between primary particle diameter and mobility diameter is presented. Mean primary particle diameter ranged from 6-19 nm, however, laser induced incandescence (LII) and mass-mobility calculated primary particle diameters demonstrated opposite trends with thrust setting. Similarly, mass-mobility-calculated aggregate mass specific surface area and LII-measured surface area were not in agreement, indicating both methods need further development and validation before use as quantitative indicators of primary particle diameter and mass-specific surface area.The authors express their gratitude to a number of people and organizations in helping to plan, conduct, finance and provide instruments for this measurement campaign. The 537 European Aviation Safety Agency (EASA) funded the SAMPLE III SC02 campaign (EASA.2010.FC.10, Specific Contract No: SC02). The Federal Office of Civil Aviation, Switzerland (FOCA) was critical in for providing additional financial support and arranging facilities which made this study possible. We also thank the SR Technics test bed staff, including Frithjof Siegerist, for operating the engines and enabling access to the test facility. We thank AVL, Cambustion, Grimm & TSI supplying both instruments and expertise.This is the author accepted manuscript. The final version is available from Taylor & Francis via http://dx.doi.org/10.1080/02786826.2015.107845

A taxonomy for community-based care programs focused on HIV/AIDS prevention, treatment, and care in resource-poor settings

Community-based care (CBC) can increase access to key services for people affected by HIV/AIDS through the mobilization of community interests and resources and their integration with formal health structures. Yet, the lack of a systematic framework for analysis of CBC focused on HIV/AIDS impedes our ability to understand and study CBC programs. We sought to develop taxonomy of CBC programs focused on HIV/AIDS in resource-limited settings in an effort to understand their key characteristics, uncover any gaps in programming, and highlight the potential roles they play. Our review aimed to systematically identify key CBC programs focused on HIV/AIDS in resource-limited settings. We used both bibliographic database searches (Medline, CINAHL, and EMBASE) for peer-reviewed literature and internet-based searches for gray literature. Our search terms were &#x2018;HIV&#x2019; or &#x2018;AIDS&#x2019; and &#x2018;community-based care&#x2019; or &#x2018;CBC&#x2019;. Two co-authors developed a descriptive taxonomy through an iterative, inductive process using the retrieved program information. We identified 21 CBC programs useful for developing taxonomy. Extensive variation was observed within each of the nine categories identified: region, vision, characteristics of target populations, program scope, program operations, funding models, human resources, sustainability, and monitoring and evaluation strategies. While additional research may still be needed to identify the conditions that lead to overall program success, our findings can help to inform our understanding of the various aspects of CBC programs and inform potential logic models for CBC programming in the context of HIV/AIDS in resource-limited settings. Importantly, the findings of the present study can be used to develop sustainable HIV/AIDS-service delivery programs in regions with health resource shortages

Protein Pattern Formation

Protein pattern formation is essential for the spatial organization of many intracellular processes like cell division, flagellum positioning, and chemotaxis. A prominent example of intracellular patterns are the oscillatory pole-to-pole oscillations of Min proteins in \textit{E. coli} whose biological function is to ensure precise cell division. Cell polarization, a prerequisite for processes such as stem cell differentiation and cell polarity in yeast, is also mediated by a diffusion-reaction process. More generally, these functional modules of cells serve as model systems for self-organization, one of the core principles of life. Under which conditions spatio-temporal patterns emerge, and how these patterns are regulated by biochemical and geometrical factors are major aspects of current research. Here we review recent theoretical and experimental advances in the field of intracellular pattern formation, focusing on general design principles and fundamental physical mechanisms.Comment: 17 pages, 14 figures, review articl

Inquiry pedagogy to promote emerging proportional reasoning in primary students

Proportional reasoning as the capacity to compare situations in relative (multiplicative) rather than absolute (additive) terms is an important outcome of primary school mathematics. Research suggests that students tend to see comparative situations in additive rather than multiplicative terms and this thinking can influence their capacity for proportional reasoning in later years. In this paper, excerpts from a classroom case study of a fourth-grade classroom (students aged 9) are presented as they address an inquiry problem that required proportional reasoning. As the inquiry unfolded, students' additive strategies were progressively seen to shift to proportional thinking to enable them to answer the question that guided their inquiry. In wrestling with the challenges they encountered, their emerging proportional reasoning was supported by the inquiry model used to provide a structure, a classroom culture of inquiry and argumentation, and the proportionality embedded in the problem context

Targeting medication non-adherence behavior in selected autoimmune diseases: a systematic approach to digital health program development

Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns

Athlete brand construction: A perspective based on fans’ perceptions

Abstract The purpose of this study was to develop a framework for understanding the antecedents and components of athlete brand. Based on a set of 21 interviews conducted in three different countries, a detailed framework is proposed including five antecedents and two components of athlete brand. The antecedents are media (social media, mass media, video games and major sport events), oral communications (word of mouth, and rumors and narratives), impression management, social agents (parents, family members, friends and community), and teams and sport (sport interest, team interest and team geographical location). In turn, the components of athlete brand are related with on-field attributes (behavior, team, achievements, style of play and skills) and off-field attributes (physical attraction, lifestyle, personal appeal, ethnicity and entertainment). Complementarily, these components of athlete brand are proposed to have an impact on fans' loyalty towards the athlete. Implications of these findings for building and managing athlete brand are discussed, and directions for future studies are provided

Hierarchical Regression for Multiple Comparisons in a Case-Control Study of Occupational Risks for Lung Cancer

BACKGROUND Occupational studies often involve multiple comparisons and therefore suffer from false positive findings. Semi-Bayes adjustment methods have sometimes been used to address this issue. Hierarchical regression is a more general approach, including Semi-Bayes adjustment as a special case, that aims at improving the validity of standard maximum-likelihood estimates in the presence of multiple comparisons by incorporating similarities between the exposures of interest in a second-stage model. METHODOLOGY/PRINCIPAL FINDINGS We re-analysed data from an occupational case-control study of lung cancer, applying hierarchical regression. In the second-stage model, we included the exposure to three known lung carcinogens (asbestos, chromium and silica) for each occupation, under the assumption that occupations entailing similar carcinogenic exposures are associated with similar risks of lung cancer. Hierarchical regression estimates had smaller confidence intervals than maximum-likelihood estimates. The shrinkage toward the null was stronger for extreme, less stable estimates (e.g., "specialised farmers": maximum-likelihood OR: 3.44, 95%CI 0.90-13.17; hierarchical regression OR: 1.53, 95%CI 0.63-3.68). Unlike Semi-Bayes adjustment toward the global mean, hierarchical regression did not shrink all the ORs towards the null (e.g., "Metal smelting, converting and refining furnacemen": maximum-likelihood OR: 1.07, Semi-Bayes OR: 1.06, hierarchical regression OR: 1.26). CONCLUSIONS/SIGNIFICANCE Hierarchical regression could be a valuable tool in occupational studies in which disease risk is estimated for a large amount of occupations when we have information available on the key carcinogenic exposures involved in each occupation. With the constant progress in exposure assessment methods in occupational settings and the availability of Job Exposure Matrices, it should become easier to apply this approach