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In recent decades, animal welfare science has evolved to utilize a multidisciplinary approach to assess the welfare of animals in accredited zoos and aquariums. Science-based animal welfare assessments have become an essential component of management programs and widespread application is expected by animal care professionals. Management practices for bottlenose dolphins in accredited facilities incorporate several programs that potentially impact animal welfare including environmental enrichment and animal training. Additionally, habitat characteristics, such as the dimensions of the habitat, have been proposed to affect welfare. While accredited facilities are required to meet high standards of care, habitat characteristics and management practices are not standardized across locations. Knowledge and subsequent application of these practices and habitat characteristics can enhance our understanding of factors associated with positive welfare. As part of a larger study of dolphin welfare titled "Towards understanding the welfare of cetaceans in zoos and aquariums" (colloquially called the Cetacean Welfare Study), survey data were collected from 86 bottlenose dolphins in 40 habitats at 38 facilities in seven countries. The major aims of this paper are to provide general descriptive information regarding dolphin management in accredited zoos and aquariums and to provide supplemental context to the other research published from the Cetacean Welfare Study data set. This paper provides a review of current habitat characteristics and management practices at those 38 accredited zoos and aquariums. These data enabled the identification and quantification of how cetacean management practices differed between participating facilities accredited by the Alliance for Marine Mammal Parks and Aquariums and the Association of Zoos & Aquariums. Variables were selected based on their potential association with welfare including the physical habitat, environmental enrichment, and training programs. The variables were also used for subsequent research in this collection of related papers to investigate important connections between potential indicators of welfare and habitat characteristics, environmental enrichment, and training programs.

INTRODUCTION: Latinos are the fastest growing aging population in the U.S. However, there has been limited attention to conceptualizing successful aging among Latinos, especially those residing in rural communities. Latinos are the largest racial or ethnic group residing in rural underserved communities and rural Latinos experience significant structural barriers to access the conditions they need to age well. The goal of this study is to make unique contributions to the successful aging literature by describing what successful aging means for middle-aged Latinas residing in a rural community. METHODS: This qualitative paper used inductive thematic content analysis to examine definitions of successful aging among Latina women (n = 40) residing in an underserved agricultural community and entering mid-life (mean = 49 years old; age range 40-64). RESULTS: With regards to definitions of successful aging, four themes emerged: 1) Having good health; 2) maintaining an active lifestyle; 3) the wellbeing of ones children; and 4) being independent. DISCUSSION: Participants definitions of successful aging aligned to some extent with existing frameworks, specifically related to health and independence. However, middle-aged Latina participants unique definitions of successful aging also diverged from existing frameworks, especially around the wellbeing of their children and the importance of work as a way of maintaining an active lifestyle. More research is needed to understand the unique social context and circumstances of middle-aged Latinos residing in rural communities and how they influence their aging journeys. This can provide important information for the development of culturally sensitive services, interventions, and policies to help Latinos age well.

Nurse, Midwives and Allied Health Professionals (AHPs), along with other health and social care colleagues are the backbone of healthcare services. They have played a key role in responding to the increased demands on healthcare during the COVID-19 pandemic. This paper compares cross-sectional data on quality of working life, wellbeing, coping and burnout of nurses, midwives and AHPs in the United Kingdom (UK) at two time points during the COVID-19 pandemic. An anonymous online repeated cross-sectional survey was conducted at two timepoints, Phase 1 (7th May 2020-3rd July 2020); Phase 2 (17th November 2020-1st February 2021). The survey consisted of the Short Warwick-Edinburgh Mental Wellbeing Scale, the Work-Related Quality of Life Scale, and the Copenhagen Burnout Inventory (Phase 2 only) to measure wellbeing, quality of working life and burnout. The Brief COPE scale and Strategies for Coping with Work and Family Stressors scale assessed coping strategies. Descriptive statistics and multiple linear regressions examined the effects of coping strategies and demographic and work-related variables on wellbeing and quality of working life. A total of 1839 nurses, midwives and AHPs responded to the first or second survey, with a final sample of 1410 respondents -586 from Phase 1; 824 from Phase 2, (422 nurses, 192 midwives and 796 AHPs). Wellbeing and quality of working life scores were significantly lower in the Phase 2 sample compared to respondents in Phase 1 (p

Porcine reproductive and respiratory syndrome (PRRS) is an extremely contagious disease that causes great damage to the U.S. pork industry. PRRS is not subject to official control in the U.S., but most producers adopt control strategies, including vaccination. However, the PRRS virus mutates frequently, facilitating its ability to infect even vaccinated animals. In this paper we analyze how increased vaccination on sow farms reduces PRRS losses and when vaccination is profitable. We develop a SIR model to simulate the spread of an outbreak between and within swine farms located in a region of Minnesota. Then, we estimate economic losses due to PRRS and calculate the benefits of vaccination. We find that increased vaccination of sow farms increases the private profitability of vaccination, and also transmits positive externalities to farms that do not vaccinate. Although vaccination reduces industry losses, a low to moderate vaccine efficacy implies that large PRRS losses remain, even on vaccinated farms. Our approach provides useful insight into the dynamics of an endemic animal disease and the benefits of different vaccination regimens.

To date, the effect of both fixed and time-varying individual, social, psychological, environmental, and behavioral characteristics on temporal growth trends in physical activity (PA) among younger individuals remains an under-studied topic. In this paper, we address this gap in previous work by examining how temporal growth trends in PA respond to changing social, environmental, and behavioral characteristics using a large sample of college students (N = 692) who participated in the NetHealth project at the University of Notre Dame and from which fine-grained longitudinal data on physical activity and social interaction were collected unobtrusively via the use of wearables for 637 days (August 16, 2015 to May 13, 2017). These data are augmented by periodic survey data on fixed sociodemographic and psychological variables. We estimate latent growth-curve models for daily activity status, steps, active minutes, and activity calories. We find evidence of both a generalized friendship paradox and a peer effect for PA, with the average PA level of study participants' contacts being on average larger than their own, and with this average level exerting a statistically significant effect on individual PA levels. Notably, there was limited evidence of temporal growth in PA across the 637 days of observation with null temporal effects for three out of the four PA indicators, except for daily steps taken. Finally, we find that social, psychological, and behavioral factors (e.g., large network size, high extroversion levels, and more courses taken) are systematically associated with higher PA levels in this sample. Overall, our findings highlight the importance of social, environmental, and behavioral factors (such as peer networks and daily sociability) in modulating the dynamics of PA levels among college students.

Undocumented status is widely recognized as an important social determinant of health. While undocumented immigrants have lower levels of health care access, they do not have consistently poorer physical health than the US-born or other immigrant groups. Furthermore, heterogeneity by race/ethnicity has been largely ignored in this growing literature. This paper used the 2001, 2004, 2008 panels of the restricted Survey of Income and Program Participation (SIPP), one of the only representative surveys equipped to adequately identify Asian undocumented immigrants, to compare health patterns between Asians and Latinos by immigration status. We examined three general measures of health/health access: self-rated health, disability, and current health insurance. Latino undocumented immigrants displayed some advantages in self-rated health and disability but had lower insurance coverage compared to US-born Latinos. In contrast, Asian undocumented immigrants did not differ from US-born Asians in any of the three outcomes. While undocumented status has been proposed as a fundamental cause of disease, we found no evidence that Latino and Asian undocumented immigrants consistently fare worse in health access or physical health outcomes than immigrants in other status categories. Different racial groups also appeared to have unique patterns between immigration status and health outcomes from one another.

A crucial question in the governance of infectious disease outbreaks is how to ensure that people continue to adhere to mitigation measures for the longer duration. The present paper examines this question by means of a set of cross-sectional studies conducted in the United States during the COVID-19 pandemic, in May, June, and July of 2020. Using stratified samples that mimic the demographic characteristics of the U.S. population, it seeks to understand to what extent Americans continued to adhere to social distancing measures in the period after the first lockdown ended. Moreover, it seeks to uncover which variables sustained (or undermined) adherence across this period. For this purpose, we examined a broad range of factors, relating to people's (1) knowledge and understanding of the mitigation measures, (2) perceptions of their costs and benefits, (3) perceptions of legitimacy and procedural justice, (4) personal factors, (5) social environment, and (6) practical circumstances. Our findings reveal that adherence was chiefly shaped by three major factors: respondents adhered more when they (a) had greater practical capacity to adhere, (b) morally agreed more with the measures, and (c) perceived the virus as a more severe health threat. Adherence was shaped to a lesser extent by impulsivity, knowledge of social distancing measures, opportunities for violating, personal costs, and descriptive social norms. The results also reveal, however, that adherence declined across this period, which was partly explained by changes in people's moral alignment, threat perceptions, knowledge, and perceived social norms. These findings show that adherence originates from a broad range of factors that develop dynamically across time. Practically these insights help to improve pandemic governance, as well as contributing theoretically to the study of compliance and the way that rules come to shape behavior.

Currently, injection sites of probes, cannula, and optic fibers in stereotactic neurosurgery are typically located manually. This step involves location estimations based on human experiences and thus introduces errors. In order to reduce localization error and improve repeatability of experiments and treatments, we investigate an automated method to locate injection sites. This paper proposes a localization framework, which integrates a region-based convolutional network and a fully convolutional network, to locate specific anatomical points on skulls of rodents. Experiment results show that the proposed localization framework is capable of identifying and locatin bregma and lambda in rodent skull anatomy images with mean errors less than 300 μm. This method is robust to different lighting conditions and mouse orientations, and has the potential to simplify the procedure of locating injection sites.

Primary symptoms of adults with autism spectrum disorder (ASD), such as pervasive social deficits in social interaction and communication, cause adults with ASD to adopt a sedentary lifestyle. Meanwhile, gamified and behavioral theory-based interventions have been shown to improve physical activity in a fun and unobtrusive way. In this paper, we describe the iterative design inquiry process of PuzzleWalk, a gamified, physical activity-promoting mobile app designed for adults with ASD. We report the design rationales and lessons learned across four user-centered design phases with ASD experts and adults with ASD, including user requirement gathering, iterative participatory design, usability evaluation, and field deployment. The design insights generated from this work could inform future research focusing on designing sociotechnical systems, games, and interventions for people with ASD.

Background and aimsThe Veterans Health Administration (VA) cares for over 80,000 Veterans with cirrhosis annually. Given the importance of understanding patient reported outcomes in this complex population, we aimed to assess the associations between attitudes towards care, disease knowledge, and health related quality of life (HRQoL) in a national sample.MethodsIn this cross-sectional study, we mailed paper surveys to a random sample of Veterans with cirrhosis, oversampling those with decompensated disease. Surveys included the Veterans RAND 12-Item Health Survey (measuring HRQoL) and questions about demographics, characteristics of care, satisfaction with care ("attitudes towards care"), and symptoms of cirrhosis. Those who reported being "unsure" about whether they had decompensation events were defined as "unsure about cirrhosis symptoms" ("disease knowledge"). We used multivariable regression models to assess the factors associated with HRQoL.ResultsOf 1374 surveys, 551 (40%) completed surveys were included for analysis. Most Veterans (63%) were "satisfied" or "very satisfied" with VA liver care. Patients often self-reported being unsure about whether they had experienced hepatic decompensation events (34%). Overall average physical (PCS) and mental (MCS) component scores of HRQoL were 30±11 and 41±12. In multivariable regression models, hepatic decompensation (PCS:β = -3.8, MCS:β = -2.2), medical comorbidities (β = --2.0, β = -1.7), and being unsure about cirrhosis symptoms (β = -1.9, β = -3.3) were associated with worse HRQoL, while age (β = 0.1, β = 0.2) and satisfaction with care (β = 0.6; β = 1.6) were associated with significantly better HRQoL.ConclusionsHepatic decompensation, lower satisfaction with care, and being unsure about cirrhosis symptoms were associated with reduced QOL scores in this national cohort.

Background and aimsThe Veterans Health Administration (VA) cares for over 80,000 Veterans with cirrhosis annually. Given the importance of understanding patient reported outcomes in this complex population, we aimed to assess the associations between attitudes towards care, disease knowledge, and health related quality of life (HRQoL) in a national sample.MethodsIn this cross-sectional study, we mailed paper surveys to a random sample of Veterans with cirrhosis, oversampling those with decompensated disease. Surveys included the Veterans RAND 12-Item Health Survey (measuring HRQoL) and questions about demographics, characteristics of care, satisfaction with care ("attitudes towards care"), and symptoms of cirrhosis. Those who reported being "unsure" about whether they had decompensation events were defined as "unsure about cirrhosis symptoms" ("disease knowledge"). We used multivariable regression models to assess the factors associated with HRQoL.ResultsOf 1374 surveys, 551 (40%) completed surveys were included for analysis. Most Veterans (63%) were "satisfied" or "very satisfied" with VA liver care. Patients often self-reported being unsure about whether they had experienced hepatic decompensation events (34%). Overall average physical (PCS) and mental (MCS) component scores of HRQoL were 30±11 and 41±12. In multivariable regression models, hepatic decompensation (PCS:β = -3.8, MCS:β = -2.2), medical comorbidities (β = --2.0, β = -1.7), and being unsure about cirrhosis symptoms (β = -1.9, β = -3.3) were associated with worse HRQoL, while age (β = 0.1, β = 0.2) and satisfaction with care (β = 0.6; β = 1.6) were associated with significantly better HRQoL.ConclusionsHepatic decompensation, lower satisfaction with care, and being unsure about cirrhosis symptoms were associated with reduced QOL scores in this national cohort.

BackgroundApproximately one in every five adolescent girls in Kenya has either had a live birth or is pregnant with her first child. There is an urgent need to understand the language and symbols used to represent adolescent pregnancy, if the current trend in adolescent pregnancy is to be reversed. Agreement on the definition of a societal problem is an important precursor to a social issue's political prioritization and priority setting.MethodsWe apply the Public Arenas Model to appraise the environments, definitions, competition dynamics, principles of selection and current actors involved in problem-solving and prioritizing adolescent pregnancy as a policy issue. Using a focused ethnographic approach, we undertook semi-structured interviews with 14 members of adolescent sexual reproductive health networks at the national level and conducted thematic analysis of the interviews.FindingsWe found that existing definitions center around adolescent pregnancy as a "disease" that needs prevention and treatment, socially deviant behaviour that requires individual agency, and a national social concern that drains public resources and therefore needs to be regulated. These competing definitions contribute to the rarity of the topic achieving traction within the political agenda and contribute to conflicting solutions, such as lowering the legal age of consenting to sex, while limiting access to contraceptive information and services to minors.ConclusionThis paper provides a timely theoretical approach to draw attention to the different competing definitions and subsequent divergent interpretations of the problem of adolescent pregnancy in Kenya. Adolescent reproductive health stakeholders need to be familiar with the existing definitions and deliberately reframe this important social problem for better political prioritization and resource allocation. We recommend a definition of adolescent pregnancy that cuts across different arenas, and leverages already existing dominant and concurrent social and economic issues that are already on the agenda table.

BackgroundApproximately one in every five adolescent girls in Kenya has either had a live birth or is pregnant with her first child. There is an urgent need to understand the language and symbols used to represent adolescent pregnancy, if the current trend in adolescent pregnancy is to be reversed. Agreement on the definition of a societal problem is an important precursor to a social issue's political prioritization and priority setting.MethodsWe apply the Public Arenas Model to appraise the environments, definitions, competition dynamics, principles of selection and current actors involved in problem-solving and prioritizing adolescent pregnancy as a policy issue. Using a focused ethnographic approach, we undertook semi-structured interviews with 14 members of adolescent sexual reproductive health networks at the national level and conducted thematic analysis of the interviews.FindingsWe found that existing definitions center around adolescent pregnancy as a "disease" that needs prevention and treatment, socially deviant behaviour that requires individual agency, and a national social concern that drains public resources and therefore needs to be regulated. These competing definitions contribute to the rarity of the topic achieving traction within the political agenda and contribute to conflicting solutions, such as lowering the legal age of consenting to sex, while limiting access to contraceptive information and services to minors.ConclusionThis paper provides a timely theoretical approach to draw attention to the different competing definitions and subsequent divergent interpretations of the problem of adolescent pregnancy in Kenya. Adolescent reproductive health stakeholders need to be familiar with the existing definitions and deliberately reframe this important social problem for better political prioritization and resource allocation. We recommend a definition of adolescent pregnancy that cuts across different arenas, and leverages already existing dominant and concurrent social and economic issues that are already on the agenda table.

The increased mortality rate among the Acoli people of northern Uganda is anecdotally blamed on excessive consumption of cheap and widely available sachet-packaged alcohol in the region. In this paper, we quantify this perceived association by determining statistically the health risks associated with ingesting 20 heavy metals in 17 popular spirits products consumed in Acoli. Thirteen of these products were industrially packaged in sachets (locally known as 'sachet,' waragi, arege or moo lyec) and four were locally produced Lira-Lira spirits from Bolo, Awere and Teso Bar in the region and Nsambya in southern Uganda. A Scottish whisky purchased in San Diego (USA) was our reference. Risk assessment was performed according to standardized protocols developed by the United States Environmental Protection Agency (US EPA). Our results show that a strong correlation indeed exists between health risks and ingestion of spirits in Acoli. At >2.5 sachets/day for 240 day/year over a lifetime for example, the risk of developing cancer due to exposure to As, Pb and Cr alone is 1 in 102,041. This estimate excludes ethanol, a known carcinogen, and 17 heavy metals also studied due to lack of their cancer slope factors. The primary non-cancer related health risk factor in all samples tested is ethanol with unacceptably high health index of four. The Lira-Lira spirits, with 100-6000% copper above the US EPA limit for intake by oral ingestion in water, would be the 'cleanest' without copper and at par with the Scottish whisky. Collectively, we find that no amount of alcohol consumed in Acoli is safe. Preventive measures are therefore recommended to reduce mortality in Acoli in particular, and in Uganda in general. These measures should include public education, better public policies, creating productive economic activities other than brewing alcohol, and social activities that engage people away from drinking.

The placenta is a dynamic organ which undergoes extensive remodeling throughout pregnancy to support, protect and nourish the developing fetus. Despite the importance of the placenta, very little is known about its gene expression beyond very early pregnancy and post-partum. Therefore, we utilized RNA-sequencing to characterize the transcriptome from the fetal (chorioallantois) and maternal (endometrium) components of the placenta from mares throughout gestation (4, 6, 10, 11 m). Within the endometrium, 47% of genes changed throughout pregnancy, while in the chorioallantois, 29% of genes underwent significant changes in expression. Further bioinformatic analyses of both differentially expressed genes and highly expressed genes help reveal similarities and differences between tissues. Overall, the tissues were more similar than different, with ~ 95% of genes expressed in both tissues, and high similarities between the most highly expressed genes (9/20 conserved), as well as marked similarities between the PANTHER pathways identified. The most highly expressed genes fell under a few broad categories, including endocrine and immune-related transcripts, iron-binding proteins, extracellular matrix proteins, transport proteins and antioxidants. Serine protease inhibitors were particularly abundant, including SERPINA3, 6 and 14, as well as SPINK7 and 9. This paper also demonstrates the ability to effectively separate maternal and fetal components of the placenta, with only a minimal amount of chorioallantoic contamination in the endometrium (~8%). This aspect of equine placentation is a boon for better understanding gestational physiology and allows the horse to be used in areas where a separation of fetal and maternal tissues is essential. Overall, these data represent the first large-scale characterization of placental gene expression in any species and include time points from multiple mid- to late-gestational stages, helping further our understanding of gestational physiology.

The placenta is a dynamic organ which undergoes extensive remodeling throughout pregnancy to support, protect and nourish the developing fetus. Despite the importance of the placenta, very little is known about its gene expression beyond very early pregnancy and post-partum. Therefore, we utilized RNA-sequencing to characterize the transcriptome from the fetal (chorioallantois) and maternal (endometrium) components of the placenta from mares throughout gestation (4, 6, 10, 11 m). Within the endometrium, 47% of genes changed throughout pregnancy, while in the chorioallantois, 29% of genes underwent significant changes in expression. Further bioinformatic analyses of both differentially expressed genes and highly expressed genes help reveal similarities and differences between tissues. Overall, the tissues were more similar than different, with ~ 95% of genes expressed in both tissues, and high similarities between the most highly expressed genes (9/20 conserved), as well as marked similarities between the PANTHER pathways identified. The most highly expressed genes fell under a few broad categories, including endocrine and immune-related transcripts, iron-binding proteins, extracellular matrix proteins, transport proteins and antioxidants. Serine protease inhibitors were particularly abundant, including SERPINA3, 6 and 14, as well as SPINK7 and 9. This paper also demonstrates the ability to effectively separate maternal and fetal components of the placenta, with only a minimal amount of chorioallantoic contamination in the endometrium (~8%). This aspect of equine placentation is a boon for better understanding gestational physiology and allows the horse to be used in areas where a separation of fetal and maternal tissues is essential. Overall, these data represent the first large-scale characterization of placental gene expression in any species and include time points from multiple mid- to late-gestational stages, helping further our understanding of gestational physiology.

Time-dependent data collected in studies of Alzheimer's disease usually has missing and irregularly sampled data points. For this reason time series methods which assume regular sampling cannot be applied directly to the data without a pre-processing step. In this paper we use a random forest to learn the relationship between pairs of data points at different time separations. The input vector is a summary of the time series history and it includes both demographic and non-time varying variables such as genetic data. To test the method we use data from the TADPOLE grand challenge, an initiative which aims to predict the evolution of subjects at risk of Alzheimer's disease using demographic, physical and cognitive input data. The task is to predict diagnosis, ADAS-13 score and normalised ventricles volume. While the competition proceeds, forecasting methods may be compared using a leaderboard dataset selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and with standard metrics for measuring accuracy. For diagnosis, we find an mAUC of 0.82, and a classification accuracy of 0.73 compared with a benchmark SVM predictor which gives mAUC = 0.62 and BCA = 0.52. The results show that the method is effective and comparable with other methods.

ObjectiveTo test the impact of a nationwide Long-Lasting Insecticidal Nets [LLINs] distribution program in the Democratic Republic of Congo [DRC] on all-cause under-five child mortality exploiting subnational variation in malaria endemicity and the timing in the scale-up of the program across provinces.DesignGeospatial Impact Evaluation using a difference-in-differences approach.SettingDemocratic Republic of the Congo.Participants52,656 children sampled in the 2007 and 2013/2014 DRC Demographic and Health Surveys.InterventionsThe analysis provides plausibly causal estimates of both average treatment effects of the LLIN distribution campaign and geospatial heterogeneity in these effects based on malaria endemicity. It compares the under-five, all-cause mortality for children pre- and post-LLIN campaign relative to children in those areas that had not yet been exposed to the campaign using a difference-in-differences model and controlling for year- and province-fixed effects, and province-level trends in mortality.ResultsWe find that the campaign led to a 41% decline [3.7 percentage points, 95% CI 1.3 to 6.0] in under-5 mortality risk among children living in rural areas with malaria ecology above the sample median. Results were robust to controlling for household assets and the presence of other health aid programs. No effect was detected in children living in areas with malaria ecology below the median.ConclusionThe findings of this paper make important contributions to the evidence base for the effectiveness of large scale-national LLIN campaigns against malaria. We found that the program was effective in areas of the DRC with the highest underlying risk of malaria. Targeting bednets to areas with greatest underlying risk for malaria may help to increase the efficiency of increasingly limited malaria resources but should be balanced against other malaria control concerns.

ObjectiveTo test the impact of a nationwide Long-Lasting Insecticidal Nets [LLINs] distribution program in the Democratic Republic of Congo [DRC] on all-cause under-five child mortality exploiting subnational variation in malaria endemicity and the timing in the scale-up of the program across provinces.DesignGeospatial Impact Evaluation using a difference-in-differences approach.SettingDemocratic Republic of the Congo.Participants52,656 children sampled in the 2007 and 2013/2014 DRC Demographic and Health Surveys.InterventionsThe analysis provides plausibly causal estimates of both average treatment effects of the LLIN distribution campaign and geospatial heterogeneity in these effects based on malaria endemicity. It compares the under-five, all-cause mortality for children pre- and post-LLIN campaign relative to children in those areas that had not yet been exposed to the campaign using a difference-in-differences model and controlling for year- and province-fixed effects, and province-level trends in mortality.ResultsWe find that the campaign led to a 41% decline [3.7 percentage points, 95% CI 1.3 to 6.0] in under-5 mortality risk among children living in rural areas with malaria ecology above the sample median. Results were robust to controlling for household assets and the presence of other health aid programs. No effect was detected in children living in areas with malaria ecology below the median.ConclusionThe findings of this paper make important contributions to the evidence base for the effectiveness of large scale-national LLIN campaigns against malaria. We found that the program was effective in areas of the DRC with the highest underlying risk of malaria. Targeting bednets to areas with greatest underlying risk for malaria may help to increase the efficiency of increasingly limited malaria resources but should be balanced against other malaria control concerns.

Time-dependent data collected in studies of Alzheimer's disease usually has missing and irregularly sampled data points. For this reason time series methods which assume regular sampling cannot be applied directly to the data without a pre-processing step. In this paper we use a random forest to learn the relationship between pairs of data points at different time separations. The input vector is a summary of the time series history and it includes both demographic and non-time varying variables such as genetic data. To test the method we use data from the TADPOLE grand challenge, an initiative which aims to predict the evolution of subjects at risk of Alzheimer's disease using demographic, physical and cognitive input data. The task is to predict diagnosis, ADAS-13 score and normalised ventricles volume. While the competition proceeds, forecasting methods may be compared using a leaderboard dataset selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and with standard metrics for measuring accuracy. For diagnosis, we find an mAUC of 0.82, and a classification accuracy of 0.73 compared with a benchmark SVM predictor which gives mAUC = 0.62 and BCA = 0.52. The results show that the method is effective and comparable with other methods.

Adverse Childhood Experiences (ACEs) are associated with poor health outcomes, underlining the significance of early identification and intervention. Currently, there is no validated tool to screen for ACEs exposure in childhood. To fill this gap, we designed and implemented a pediatric ACEs questionnaire in an urban pediatric Primary Care Clinic. Questionnaire items were selected and modified based on literature review of existing childhood adversity tools. Children twelve years and under were screened via caregiver report, using the developed instrument. Cognitive interviews were conducted with caregivers, health providers, and clinic staff to assess item interpretation, clarity, and English/Spanish language equivalency. Using a rapid cycle assessment, information gained from the interviews were used to iteratively change the instrument. Additional questions assessed acceptability of screening within primary care and preferences around administration. Twenty-eight (28) caregivers were administered the questionnaire. Cognitive interviews conducted among caregivers and among 16 health providers and clinic staff resulted in the changes in wording and addition of examples in the items to increase face validity. In the final instrument, no new items were added; however, two items were merged and one item was split into three separate items. While there was a high level of acceptability of the overall questionnaire, some caregivers reported discomfort with the sexual abuse, separation from caregiver, and community violence items. Preference for methods of administration were split between tablet and paper formats. The final Pediatric ACE and other Determinants of Health Questionnaire is a 17-item instrument with high face validity and acceptability for use within primary care settings. Further evaluation on the reliability and construct validity of the instrument is being conducted prior to wide implementation in pediatric practice.

Adverse Childhood Experiences (ACEs) are associated with poor health outcomes, underlining the significance of early identification and intervention. Currently, there is no validated tool to screen for ACEs exposure in childhood. To fill this gap, we designed and implemented a pediatric ACEs questionnaire in an urban pediatric Primary Care Clinic. Questionnaire items were selected and modified based on literature review of existing childhood adversity tools. Children twelve years and under were screened via caregiver report, using the developed instrument. Cognitive interviews were conducted with caregivers, health providers, and clinic staff to assess item interpretation, clarity, and English/Spanish language equivalency. Using a rapid cycle assessment, information gained from the interviews were used to iteratively change the instrument. Additional questions assessed acceptability of screening within primary care and preferences around administration. Twenty-eight (28) caregivers were administered the questionnaire. Cognitive interviews conducted among caregivers and among 16 health providers and clinic staff resulted in the changes in wording and addition of examples in the items to increase face validity. In the final instrument, no new items were added; however, two items were merged and one item was split into three separate items. While there was a high level of acceptability of the overall questionnaire, some caregivers reported discomfort with the sexual abuse, separation from caregiver, and community violence items. Preference for methods of administration were split between tablet and paper formats. The final Pediatric ACE and other Determinants of Health Questionnaire is a 17-item instrument with high face validity and acceptability for use within primary care settings. Further evaluation on the reliability and construct validity of the instrument is being conducted prior to wide implementation in pediatric practice.

Effective symptom management is a critical component of cancer treatment. Computational tools that predict the course and severity of these symptoms have the potential to assist oncology clinicians to personalize the patient's treatment regimen more efficiently and provide more aggressive and timely interventions. Three common and inter-related symptoms in cancer patients are depression, anxiety, and sleep disturbance. In this paper, we elaborate on the efficiency of Support Vector Regression (SVR) and Non-linear Canonical Correlation Analysis by Neural Networks (n-CCA) to predict the severity of the aforementioned symptoms between two different time points during a cycle of chemotherapy (CTX). Our results demonstrate that these two methods produced equivalent results for all three symptoms. These types of predictive models can be used to identify high risk patients, educate patients about their symptom experience, and improve the timing of pre-emptive and personalized symptom management interventions.

ObjectiveThe overall aim of this paper is to examine effectiveness of an evidence-based intervention in community settings, and the factors associated with effectiveness. Limited research in the area of HIV prevention has focused on evaluating intervention program effectiveness in real-world settings.MethodsWe implemented an efficacious theory-based sexual risk reduction intervention for female sex workers (FSW) called Mujer Segura across 13 different clinics in 13 sites across Mexico. The overall design was a cluster randomized Type I design simultaneously testing intervention program effectiveness with an observational study of implementation factors. We aimed to examine the effectiveness of Mujer Segura at reducing HIV/STI incidence among FSW participants at each site, and to examine the client-, provider-, organization-, and structure-related factors associated with program effectiveness.ResultsWe found lower HIV/STI incidence density in the intervention relative to the control group in 5 sites we labeled as "program effective sites," but not in 8 sites we labeled as "program ineffective sites." Using generalized estimating equations controlling for site and computed mean difference effect sizes, we examined statistically and practically significant differences, respectively, between the two groups of sites along various client-, provider-, organization-, and structure-related characteristics. Results indicated that client-level HIV/AIDS related knowledge, and proficiency and engagement in the organizational social context were associated with program effectiveness.ConclusionsEnormous resources are required to systematically and adequately test the role of multilevel factors on program effectiveness. We successfully implemented Mujer Segura in 13 sites in Mexico. Results suggest that other measures may need to be included in future implementation studies than the ones included here. We were able to point to a few specific factors that should be targeted to increase effectiveness of similar evidence-based programs in low- and other middle-income countries like Mexico.Trial registrationClinicalTrials.gov NCT01465607.

ObjectiveThe overall aim of this paper is to examine effectiveness of an evidence-based intervention in community settings, and the factors associated with effectiveness. Limited research in the area of HIV prevention has focused on evaluating intervention program effectiveness in real-world settings.MethodsWe implemented an efficacious theory-based sexual risk reduction intervention for female sex workers (FSW) called Mujer Segura across 13 different clinics in 13 sites across Mexico. The overall design was a cluster randomized Type I design simultaneously testing intervention program effectiveness with an observational study of implementation factors. We aimed to examine the effectiveness of Mujer Segura at reducing HIV/STI incidence among FSW participants at each site, and to examine the client-, provider-, organization-, and structure-related factors associated with program effectiveness.ResultsWe found lower HIV/STI incidence density in the intervention relative to the control group in 5 sites we labeled as "program effective sites," but not in 8 sites we labeled as "program ineffective sites." Using generalized estimating equations controlling for site and computed mean difference effect sizes, we examined statistically and practically significant differences, respectively, between the two groups of sites along various client-, provider-, organization-, and structure-related characteristics. Results indicated that client-level HIV/AIDS related knowledge, and proficiency and engagement in the organizational social context were associated with program effectiveness.ConclusionsEnormous resources are required to systematically and adequately test the role of multilevel factors on program effectiveness. We successfully implemented Mujer Segura in 13 sites in Mexico. Results suggest that other measures may need to be included in future implementation studies than the ones included here. We were able to point to a few specific factors that should be targeted to increase effectiveness of similar evidence-based programs in low- and other middle-income countries like Mexico.Trial registrationClinicalTrials.gov NCT01465607.

Adverse Childhood Experiences (ACEs) are associated with poor health outcomes, underlining the significance of early identification and intervention. Currently, there is no validated tool to screen for ACEs exposure in childhood. To fill this gap, we designed and implemented a pediatric ACEs questionnaire in an urban pediatric Primary Care Clinic. Questionnaire items were selected and modified based on literature review of existing childhood adversity tools. Children twelve years and under were screened via caregiver report, using the developed instrument. Cognitive interviews were conducted with caregivers, health providers, and clinic staff to assess item interpretation, clarity, and English/Spanish language equivalency. Using a rapid cycle assessment, information gained from the interviews were used to iteratively change the instrument. Additional questions assessed acceptability of screening within primary care and preferences around administration. Twenty-eight (28) caregivers were administered the questionnaire. Cognitive interviews conducted among caregivers and among 16 health providers and clinic staff resulted in the changes in wording and addition of examples in the items to increase face validity. In the final instrument, no new items were added; however, two items were merged and one item was split into three separate items. While there was a high level of acceptability of the overall questionnaire, some caregivers reported discomfort with the sexual abuse, separation from caregiver, and community violence items. Preference for methods of administration were split between tablet and paper formats. The final Pediatric ACE and other Determinants of Health Questionnaire is a 17-item instrument with high face validity and acceptability for use within primary care settings. Further evaluation on the reliability and construct validity of the instrument is being conducted prior to wide implementation in pediatric practice.

Effective symptom management is a critical component of cancer treatment. Computational tools that predict the course and severity of these symptoms have the potential to assist oncology clinicians to personalize the patient's treatment regimen more efficiently and provide more aggressive and timely interventions. Three common and inter-related symptoms in cancer patients are depression, anxiety, and sleep disturbance. In this paper, we elaborate on the efficiency of Support Vector Regression (SVR) and Non-linear Canonical Correlation Analysis by Neural Networks (n-CCA) to predict the severity of the aforementioned symptoms between two different time points during a cycle of chemotherapy (CTX). Our results demonstrate that these two methods produced equivalent results for all three symptoms. These types of predictive models can be used to identify high risk patients, educate patients about their symptom experience, and improve the timing of pre-emptive and personalized symptom management interventions.

Marine Protected Areas (MPA) are important management tools shown to protect marine organisms, restore biomass, and increase fisheries yields. While MPAs have been successful in meeting these goals for many relatively sedentary species, highly mobile organisms may get few benefits from this type of spatial protection due to their frequent movement outside the protected area. The use of a large MPA can compensate for extensive movement, but testing this empirically is challenging, as it requires both large areas and sufficient time series to draw conclusions. To overcome this limitation, MPA models have been used to identify designs and predict potential outcomes, but these simulations are highly sensitive to the assumptions describing the organism's movements. Due to recent improvements in computational simulations, it is now possible to include very complex movement assumptions in MPA models (e.g. Individual Based Model). These have renewed interest in MPA simulations, which implicitly assume that increasing the detail in fish movement overcomes the sensitivity to the movement assumptions. Nevertheless, a systematic comparison of the designs and outcomes obtained under different movement assumptions has not been done. In this paper, we use an individual based model, interconnected to population and fishing fleet models, to explore the value of increasing the detail of the movement assumptions using four scenarios of increasing behavioral complexity: a) random, diffusive movement, b) aggregations, c) aggregations that respond to environmental forcing (e.g. sea surface temperature), and d) aggregations that respond to environmental forcing and are transported by currents. We then compare these models to determine how the assumptions affect MPA design, and therefore the effective protection of the stocks. Our results show that the optimal MPA size to maximize fisheries benefits increases as movement complexity increases from ~10% for the diffusive assumption to ~30% when full environment forcing was used. We also found that in cases of limited understanding of the movement dynamics of a species, simplified assumptions can be used to provide a guide for the minimum MPA size needed to effectively protect the stock. However, using oversimplified assumptions can produce suboptimal designs and lead to a density underestimation of ca. 30%; therefore, the main value of detailed movement dynamics is to provide more reliable MPA design and predicted outcomes. Large MPAs can be effective in recovering overfished stocks, protect pelagic fish and provide significant increases in fisheries yields. Our models provide a means to empirically test this spatial management tool, which theoretical evidence consistently suggests as an effective alternative to managing highly mobile pelagic stocks.

United States-based biorepositories are on the cusp of substantial change in regulatory oversight at the same time that they are increasingly including samples and data from large populations, e.g. all patients in healthcare system. It is appropriate to engage stakeholders from these populations in new governance arrangements. We sought to describe community recommendations for biorepository governance and oversight using deliberative community engagement (DCE), a qualitative research method designed to elicit lay perspectives on complex technical issues. We asked for stakeholders to provide input on governance of large biorepositories at the University of California (UC), a public university. We defined state residents as stakeholders and recruited residents from two large metropolitan areas, Los Angeles (LA) and San Francisco (SF). In LA, we recruited English and Spanish speakers; in SF the DCE was conducted in English only. We recruited individuals who had completed the 2009 California Health Interview Survey and were willing to be re-contacted for future studies. Using stratified random sampling (by age, education, race/ethnicity), we contacted 162 potential deliberants of whom 53 agreed to participate and 51 completed the 4-day DCE in June (LA) and September-October (SF), 2013. Each DCE included discussion among deliberants facilitated by a trained staff and simultaneously-translated in LA. Deliberants also received a briefing book describing biorepository operations and regulation. During the final day of the DCE, deliberants voted on governance and oversight recommendations using an audience response system. This paper describes 23 recommendations (of 57 total) that address issues including: educating the public, sharing samples broadly, monitoring researcher behavior, using informative consent procedures, and involving community members in a transparent process of biobank governance. This project demonstrates the feasibility of obtaining meaningful input on biorepository governance from diverse lay stakeholders. Such input should be considered as research institutions respond to changes in biorepository regulation.

United States-based biorepositories are on the cusp of substantial change in regulatory oversight at the same time that they are increasingly including samples and data from large populations, e.g. all patients in healthcare system. It is appropriate to engage stakeholders from these populations in new governance arrangements. We sought to describe community recommendations for biorepository governance and oversight using deliberative community engagement (DCE), a qualitative research method designed to elicit lay perspectives on complex technical issues. We asked for stakeholders to provide input on governance of large biorepositories at the University of California (UC), a public university. We defined state residents as stakeholders and recruited residents from two large metropolitan areas, Los Angeles (LA) and San Francisco (SF). In LA, we recruited English and Spanish speakers; in SF the DCE was conducted in English only. We recruited individuals who had completed the 2009 California Health Interview Survey and were willing to be re-contacted for future studies. Using stratified random sampling (by age, education, race/ethnicity), we contacted 162 potential deliberants of whom 53 agreed to participate and 51 completed the 4-day DCE in June (LA) and September-October (SF), 2013. Each DCE included discussion among deliberants facilitated by a trained staff and simultaneously-translated in LA. Deliberants also received a briefing book describing biorepository operations and regulation. During the final day of the DCE, deliberants voted on governance and oversight recommendations using an audience response system. This paper describes 23 recommendations (of 57 total) that address issues including: educating the public, sharing samples broadly, monitoring researcher behavior, using informative consent procedures, and involving community members in a transparent process of biobank governance. This project demonstrates the feasibility of obtaining meaningful input on biorepository governance from diverse lay stakeholders. Such input should be considered as research institutions respond to changes in biorepository regulation.

Marine Protected Areas (MPA) are important management tools shown to protect marine organisms, restore biomass, and increase fisheries yields. While MPAs have been successful in meeting these goals for many relatively sedentary species, highly mobile organisms may get few benefits from this type of spatial protection due to their frequent movement outside the protected area. The use of a large MPA can compensate for extensive movement, but testing this empirically is challenging, as it requires both large areas and sufficient time series to draw conclusions. To overcome this limitation, MPA models have been used to identify designs and predict potential outcomes, but these simulations are highly sensitive to the assumptions describing the organism's movements. Due to recent improvements in computational simulations, it is now possible to include very complex movement assumptions in MPA models (e.g. Individual Based Model). These have renewed interest in MPA simulations, which implicitly assume that increasing the detail in fish movement overcomes the sensitivity to the movement assumptions. Nevertheless, a systematic comparison of the designs and outcomes obtained under different movement assumptions has not been done. In this paper, we use an individual based model, interconnected to population and fishing fleet models, to explore the value of increasing the detail of the movement assumptions using four scenarios of increasing behavioral complexity: a) random, diffusive movement, b) aggregations, c) aggregations that respond to environmental forcing (e.g. sea surface temperature), and d) aggregations that respond to environmental forcing and are transported by currents. We then compare these models to determine how the assumptions affect MPA design, and therefore the effective protection of the stocks. Our results show that the optimal MPA size to maximize fisheries benefits increases as movement complexity increases from ~10% for the diffusive assumption to ~30% when full environment forcing was used. We also found that in cases of limited understanding of the movement dynamics of a species, simplified assumptions can be used to provide a guide for the minimum MPA size needed to effectively protect the stock. However, using oversimplified assumptions can produce suboptimal designs and lead to a density underestimation of ca. 30%; therefore, the main value of detailed movement dynamics is to provide more reliable MPA design and predicted outcomes. Large MPAs can be effective in recovering overfished stocks, protect pelagic fish and provide significant increases in fisheries yields. Our models provide a means to empirically test this spatial management tool, which theoretical evidence consistently suggests as an effective alternative to managing highly mobile pelagic stocks.

IntroductionFemale sex workers (FSWs) are the second most affected population by HIV in Iran. However, their HIV testing practices are poorly understood. The aim of this study was to investigate testing and its associated factors among HIV negative FSWs.Materials and methodsUsing facility based sampling, 1005 FSWs were recruited in 14 cities of Iran in 2010. Biological and survey data were collected through dried blood spot testing and standardized risk assessment questionnaire, respectively. In this paper, the prevalence of HIV testing and its correlates were explored among 714 HIV-negative FSWs using descriptive statistics and logistic regression models.ResultsOverall 65.4% had not tested in the past year. Only 27.5% had tested in the past year and received their results. FSWs who perceived themselves at risk of HIV (Adjusted Odds Ratio (AOR) = 8.35, 95% CI: 1.46, 47.6), had received free condom during past year (AOR = 3.90, 95% CI: 1.67, 9.14), started sex work at an older age (AOR18-24 = 2.83, 95% CI: 1.14, 7.0; AOR >24 = 2.76, 95% CI: 1.11, 6.84), and knew an HIV testing site (AOR = 5.67, 95% CI: 2.60, 12.4) had a significantly higher chance of having a recent HIV test result.ConclusionsLess than one third of FSWs in Iran knew their recent HIV status. Interventions to help FSWs evaluate their potential risk for HIV and integrate HIV testing services in condom distribution programs, could be viable strategies in increasing HIV testing uptake among FSWs. Health policy makers should also try to de-stigmatize HIV testing, identify the barriers to HIV testing, and make HIV testing sites more visible to FSWs.

BackgroundDengue virus (and Chikungunya and Zika viruses) is transmitted by Aedes aegypti and Aedes albopictus mosquitoes and causes considerable human morbidity and mortality. As there is currently no vaccine or chemoprophylaxis to protect people from dengue virus infection, vector control is the only viable option for disease prevention. The purpose of this paper is to illustrate the design and placement process for an attractive lethal ovitrap to reduce vector populations and to describe lessons learned in the development of the trap.MethodsThis study was conducted in 2010 in Iquitos, Peru and Lopburi Province, Thailand and used an iterative community-based participatory approach to adjust design specifications of the trap, based on community members' perceptions and feedback, entomological findings in the lab, and design and research team observations. Multiple focus group discussions (FGD) were held over a 6 month period, stratified by age, sex and motherhood status, to inform the design process. Trap testing transitioned from the lab to within households.ResultsThrough an iterative process of working with specifications from the research team, findings from the laboratory testing, and feedback from FGD, the design team narrowed trap design options from 22 to 6. Comments from the FGD centered on safety for children and pets interacting with traps, durability, maintenance issues, and aesthetics. Testing in the laboratory involved releasing groups of 50 gravid Ae. aegypti in walk-in rooms and assessing what percentage were caught in traps of different colors, with different trap cover sizes, and placed under lighter or darker locations. Two final trap models were mocked up and tested in homes for a week; one model was the top choice in both Iquitos and Lopburi.DiscussionThe community-based participatory process was essential for the development of novel traps that provided effective vector control, but also met the needs and concerns of community members.

The tendency to mimic the behaviour of others is affected by a variety of social factors, and it has been argued that such "mirroring" is often unconsciously deployed as a means of increasing affiliation during interpersonal interactions. However, the relationship between automatic motor imitation and status/power is currently unclear. This paper reports five experiments that investigated whether social status (Experiments 1, 2, and 3) or power (Experiments 4 and 5) had a moderating effect on automatic imitation (AI) in finger-movement tasks, using a series of different manipulations. Experiments 1 and 2 manipulated the social status of the observed person using an associative learning task. Experiment 3 manipulated social status via perceived competence at a simple computer game. Experiment 4 manipulated participants' power (relative to the actors) in a card-choosing task. Finally, Experiment 5 primed participants using a writing task, to induce the sense of being powerful or powerless. No significant interactions were found between congruency and social status/power in any of the studies. Additionally, Bayesian hypothesis testing indicated that the null hypothesis should be favoured over the experimental hypothesis in all five studies. These findings are discussed in terms of their implications for AI tasks, social effects on mimicry, and the hypothesis of mimicry as a strategic mechanism to promote affiliation.

Electrolysis, electrochemotherapy with reversible electroporation, nanosecond pulsed electric fields and irreversible electroporation are valuable non-thermal electricity based tissue ablation technologies. This paper reports results from the first large animal study of a new non-thermal tissue ablation technology that employs "Synergistic electrolysis and electroporation" (SEE). The goal of this pre-clinical study is to expand on earlier studies with small animals and use the pig liver to establish SEE treatment parameters of clinical utility. We examined two SEE methods. One of the methods employs multiple electrochemotherapy-type reversible electroporation magnitude pulses, designed in such a way that the charge delivered during the electroporation pulses generates the electrolytic products. The second SEE method combines the delivery of a small number of electrochemotherapy magnitude electroporation pulses with a low voltage electrolysis generating DC current in three different ways. We show that both methods can produce lesion with dimensions of clinical utility, without the need to inject drugs as in electrochemotherapy, faster than with conventional electrolysis and with lower electric fields than irreversible electroporation and nanosecond pulsed ablation.

Resting-state functional brain imaging studies of network connectivity have long assumed that functional connections are stationary on the timescale of a typical scan. Interest in moving beyond this simplifying assumption has emerged only recently. The great hope is that training the right lens on time-varying properties of whole-brain network connectivity will shed additional light on previously concealed brain activation patterns characteristic of serious neurological or psychiatric disorders. We present evidence that multiple explicitly dynamical properties of time-varying whole-brain network connectivity are strongly associated with schizophrenia, a complex mental illness whose symptomatic presentation can vary enormously across subjects. As with so much brain-imaging research, a central challenge for dynamic network connectivity lies in determining transformations of the data that both reduce its dimensionality and expose features that are strongly predictive of important population characteristics. Our paper introduces an elegant, simple method of reducing and organizing data around which a large constellation of mutually informative and intuitive dynamical analyses can be performed. This framework combines a discrete multidimensional data-driven representation of connectivity space with four core dynamism measures computed from large-scale properties of each subject's trajectory, ie., properties not identifiable with any specific moment in time and therefore reasonable to employ in settings lacking inter-subject time-alignment, such as resting-state functional imaging studies. Our analysis exposes pronounced differences between schizophrenia patients (Nsz = 151) and healthy controls (Nhc = 163). Time-varying whole-brain network connectivity patterns are found to be markedly less dynamically active in schizophrenia patients, an effect that is even more pronounced in patients with high levels of hallucinatory behavior. To the best of our knowledge this is the first demonstration that high-level dynamic properties of whole-brain connectivity, generic enough to be commensurable under many decompositions of time-varying connectivity data, exhibit robust and systematic differences between schizophrenia patients and healthy controls.

Electrolysis, electrochemotherapy with reversible electroporation, nanosecond pulsed electric fields and irreversible electroporation are valuable non-thermal electricity based tissue ablation technologies. This paper reports results from the first large animal study of a new non-thermal tissue ablation technology that employs "Synergistic electrolysis and electroporation" (SEE). The goal of this pre-clinical study is to expand on earlier studies with small animals and use the pig liver to establish SEE treatment parameters of clinical utility. We examined two SEE methods. One of the methods employs multiple electrochemotherapy-type reversible electroporation magnitude pulses, designed in such a way that the charge delivered during the electroporation pulses generates the electrolytic products. The second SEE method combines the delivery of a small number of electrochemotherapy magnitude electroporation pulses with a low voltage electrolysis generating DC current in three different ways. We show that both methods can produce lesion with dimensions of clinical utility, without the need to inject drugs as in electrochemotherapy, faster than with conventional electrolysis and with lower electric fields than irreversible electroporation and nanosecond pulsed ablation.

The tendency to mimic the behaviour of others is affected by a variety of social factors, and it has been argued that such "mirroring" is often unconsciously deployed as a means of increasing affiliation during interpersonal interactions. However, the relationship between automatic motor imitation and status/power is currently unclear. This paper reports five experiments that investigated whether social status (Experiments 1, 2, and 3) or power (Experiments 4 and 5) had a moderating effect on automatic imitation (AI) in finger-movement tasks, using a series of different manipulations. Experiments 1 and 2 manipulated the social status of the observed person using an associative learning task. Experiment 3 manipulated social status via perceived competence at a simple computer game. Experiment 4 manipulated participants' power (relative to the actors) in a card-choosing task. Finally, Experiment 5 primed participants using a writing task, to induce the sense of being powerful or powerless. No significant interactions were found between congruency and social status/power in any of the studies. Additionally, Bayesian hypothesis testing indicated that the null hypothesis should be favoured over the experimental hypothesis in all five studies. These findings are discussed in terms of their implications for AI tasks, social effects on mimicry, and the hypothesis of mimicry as a strategic mechanism to promote affiliation.

Resting-state functional brain imaging studies of network connectivity have long assumed that functional connections are stationary on the timescale of a typical scan. Interest in moving beyond this simplifying assumption has emerged only recently. The great hope is that training the right lens on time-varying properties of whole-brain network connectivity will shed additional light on previously concealed brain activation patterns characteristic of serious neurological or psychiatric disorders. We present evidence that multiple explicitly dynamical properties of time-varying whole-brain network connectivity are strongly associated with schizophrenia, a complex mental illness whose symptomatic presentation can vary enormously across subjects. As with so much brain-imaging research, a central challenge for dynamic network connectivity lies in determining transformations of the data that both reduce its dimensionality and expose features that are strongly predictive of important population characteristics. Our paper introduces an elegant, simple method of reducing and organizing data around which a large constellation of mutually informative and intuitive dynamical analyses can be performed. This framework combines a discrete multidimensional data-driven representation of connectivity space with four core dynamism measures computed from large-scale properties of each subject's trajectory, ie., properties not identifiable with any specific moment in time and therefore reasonable to employ in settings lacking inter-subject time-alignment, such as resting-state functional imaging studies. Our analysis exposes pronounced differences between schizophrenia patients (Nsz = 151) and healthy controls (Nhc = 163). Time-varying whole-brain network connectivity patterns are found to be markedly less dynamically active in schizophrenia patients, an effect that is even more pronounced in patients with high levels of hallucinatory behavior. To the best of our knowledge this is the first demonstration that high-level dynamic properties of whole-brain connectivity, generic enough to be commensurable under many decompositions of time-varying connectivity data, exhibit robust and systematic differences between schizophrenia patients and healthy controls.

The hormone cortisol is likely to be a key mediator of the stress response that influences multiple physiologic systems that are involved in common chronic disease, including the cardiovascular system, the immune system, and metabolism. In this paper, a candidate gene approach was used to investigate genetic contributions to variability in multiple correlated features of the daily cortisol profile in a sample of European Americans, African Americans, and Hispanic Americans from the Multi-Ethnic Study of Atherosclerosis (MESA). We proposed and applied a new gene-level multiple-phenotype analysis and carried out a meta-analysis to combine the ethnicity specific results. This new analysis, instead of a more routine single marker-single phenotype approach identified a significant association between one gene (ADRB2) and cortisol features (meta-analysis p-value=0.0025), which was not identified by three other commonly used existing analytic strategies: 1. Single marker association tests involving each single cortisol feature separately; 2. Single marker association tests jointly testing for multiple cortisol features; 3. Gene-level association tests separately carried out for each single cortisol feature. The analytic strategies presented consider different hypotheses regarding genotype-phenotype association and imply different costs of multiple testing. The proposed gene-level analysis integrating multiple cortisol features across multiple ethnic groups provides new insights into the gene-cortisol association.

Barriers to accessing legal abortion services in Tunisia are increasing, despite a liberal abortion law, and women are often denied wanted legal abortion services. In this paper, we seek to explore the reasons for abortion denial and whether these reasons had a legal or medical basis. We also identify barriers women faced in accessing abortion and make recommendations for improved access to quality abortion care. We recruited women immediately after they had been turned away from legal abortion services at two facilities in Tunis, Tunisia. Thirteen women consented to participate in qualitative interviews two months after they were turned away from the facility. Women were denied abortion care on the day they were recruited due to three main reasons: gestational age, health conditions, and logistical barriers. Nine women ultimately terminated their pregnancies at another facility, and four women carried to term. None of the women attempted illegal abortion services or self-induction. Further research is needed in order to assess abortion denial from the perspective of providers and medical staff.

BackgroundWhile a great number of papers have been published on the short-term effects of air pollution on mortality, few have tried to assess whether this association varies according to the neighbourhood socioeconomic level and long-term ambient air concentrations measured at the place of residence. We explored the effect modification of 1) socioeconomic status, 2) long-term NO2 ambient air concentrations, and 3) both combined, on the association between short-term exposure to NO2 and all-cause mortality in Paris (France).MethodsA time-stratified case-crossover analysis was performed to evaluate the effect of short-term NO2 variations on mortality, based on 79,107 deaths having occurred among subjects aged over 35 years, from 2004 to 2009, in the city of Paris. Simple and double interactions were statistically tested in order to analyse effect modification by neighbourhood characteristics on the association between mortality and short-term NO2 exposure. The data was estimated at the census block scale (n=866).ResultsThe mean of the NO2 concentrations during the five days prior to deaths were associated with an increased risk of all-cause mortality: overall Excess Risk (ER) was 0.94% (95%CI=[0.08;1.80]. A higher risk was revealed for subjects living in the most deprived census blocks in comparison with higher socioeconomic level areas (ER=3.14% (95%CI=[1.41-4.90], p

Barriers to accessing legal abortion services in Tunisia are increasing, despite a liberal abortion law, and women are often denied wanted legal abortion services. In this paper, we seek to explore the reasons for abortion denial and whether these reasons had a legal or medical basis. We also identify barriers women faced in accessing abortion and make recommendations for improved access to quality abortion care. We recruited women immediately after they had been turned away from legal abortion services at two facilities in Tunis, Tunisia. Thirteen women consented to participate in qualitative interviews two months after they were turned away from the facility. Women were denied abortion care on the day they were recruited due to three main reasons: gestational age, health conditions, and logistical barriers. Nine women ultimately terminated their pregnancies at another facility, and four women carried to term. None of the women attempted illegal abortion services or self-induction. Further research is needed in order to assess abortion denial from the perspective of providers and medical staff.

The hormone cortisol is likely to be a key mediator of the stress response that influences multiple physiologic systems that are involved in common chronic disease, including the cardiovascular system, the immune system, and metabolism. In this paper, a candidate gene approach was used to investigate genetic contributions to variability in multiple correlated features of the daily cortisol profile in a sample of European Americans, African Americans, and Hispanic Americans from the Multi-Ethnic Study of Atherosclerosis (MESA). We proposed and applied a new gene-level multiple-phenotype analysis and carried out a meta-analysis to combine the ethnicity specific results. This new analysis, instead of a more routine single marker-single phenotype approach identified a significant association between one gene (ADRB2) and cortisol features (meta-analysis p-value=0.0025), which was not identified by three other commonly used existing analytic strategies: 1. Single marker association tests involving each single cortisol feature separately; 2. Single marker association tests jointly testing for multiple cortisol features; 3. Gene-level association tests separately carried out for each single cortisol feature. The analytic strategies presented consider different hypotheses regarding genotype-phenotype association and imply different costs of multiple testing. The proposed gene-level analysis integrating multiple cortisol features across multiple ethnic groups provides new insights into the gene-cortisol association.

BackgroundWhile a great number of papers have been published on the short-term effects of air pollution on mortality, few have tried to assess whether this association varies according to the neighbourhood socioeconomic level and long-term ambient air concentrations measured at the place of residence. We explored the effect modification of 1) socioeconomic status, 2) long-term NO2 ambient air concentrations, and 3) both combined, on the association between short-term exposure to NO2 and all-cause mortality in Paris (France).MethodsA time-stratified case-crossover analysis was performed to evaluate the effect of short-term NO2 variations on mortality, based on 79,107 deaths having occurred among subjects aged over 35 years, from 2004 to 2009, in the city of Paris. Simple and double interactions were statistically tested in order to analyse effect modification by neighbourhood characteristics on the association between mortality and short-term NO2 exposure. The data was estimated at the census block scale (n=866).ResultsThe mean of the NO2 concentrations during the five days prior to deaths were associated with an increased risk of all-cause mortality: overall Excess Risk (ER) was 0.94% (95%CI=[0.08;1.80]. A higher risk was revealed for subjects living in the most deprived census blocks in comparison with higher socioeconomic level areas (ER=3.14% (95%CI=[1.41-4.90], p

In this paper we try to define insulin resistance (IR) precisely for a group of Chinese women. Our definition deliberately does not depend upon body mass index (BMI) or age, although in other studies, with particular random effects models quite different from models used here, BMI accounts for a large part of the variability in IR. We accomplish our goal through application of Gauss mixture vector quantization (GMVQ), a technique for clustering that was developed for application to lossy data compression. Defining data come from measurements that play major roles in medical practice. A precise statement of what the data are is in Section 1. Their family structures are described in detail. They concern levels of lipids and the results of an oral glucose tolerance test (OGTT). We apply GMVQ to residuals obtained from regressions of outcomes of an OGTT and lipids on functions of age and BMI that are inferred from the data. A bootstrap procedure developed for our family data supplemented by insights from other approaches leads us to believe that two clusters are appropriate for defining IR precisely. One cluster consists of women who are IR, and the other of women who seem not to be. Genes and other features are used to predict cluster membership. We argue that prediction with "main effects" is not satisfactory, but prediction that includes interactions may be.

Myocardial infarction leads to changes in the geometry (remodeling) of the left ventricle (LV) of the heart. The degree and type of remodeling provides important diagnostic information for the therapeutic management of ischemic heart disease. In this paper, we present a novel analysis framework for characterizing remodeling after myocardial infarction, using LV shape descriptors derived from atlas-based shape models. Cardiac magnetic resonance images from 300 patients with myocardial infarction and 1991 asymptomatic volunteers were obtained from the Cardiac Atlas Project. Finite element models were customized to the spatio-temporal shape and function of each case using guide-point modeling. Principal component analysis was applied to the shape models to derive modes of shape variation across all cases. A logistic regression analysis was performed to determine the modes of shape variation most associated with myocardial infarction. Goodness of fit results obtained from end-diastolic and end-systolic shapes were compared against the traditional clinical indices of remodeling: end-diastolic volume, end-systolic volume and LV mass. The combination of end-diastolic and end-systolic shape parameter analysis achieved the lowest deviance, Akaike information criterion and Bayesian information criterion, and the highest area under the receiver operating characteristic curve. Therefore, our framework quantitatively characterized remodeling features associated with myocardial infarction, better than current measures. These features enable quantification of the amount of remodeling, the progression of disease over time, and the effect of treatments designed to reverse remodeling effects.

Brain computer interfaces (BCIs) offer a broad class of neurologically impaired individuals an alternative means to interact with the environment. Many BCIs are "synchronous" systems, in which the system sets the timing of the interaction and tries to infer what control command the subject is issuing at each prompting. In contrast, in "asynchronous" BCIs subjects pace the interaction and the system must determine when the subject's control command occurs. In this paper we propose a new idea for BCI which draws upon the strengths of both approaches. The subjects are externally paced and the BCI is able to determine when control commands are issued by decoding the subject's intention for initiating control in dedicated time slots. A single task with randomly interleaved trials was designed to test whether it can be used as stimulus for inducing initiation and non-initiation states when the sensory and motor requirements for the two types of trials are very nearly identical. Further, the essential problem on the discrimination between initiation state and non-initiation state was studied. We tested the ability of EEG spectral power to distinguish between these two states. Among the four standard EEG frequency bands, beta band power recorded over parietal-occipital cortices provided the best performance, achieving an average accuracy of 86% for the correct classification of initiation and non-initiation states. Moreover, delta band power recorded over parietal and motor areas yielded a good performance and thus could also be used as an alternative feature to discriminate these two mental states. The results demonstrate the viability of our proposed idea for a BCI design based on conventional EEG features. Our proposal offers the potential to mitigate the signal detection challenges of fully asynchronous BCIs, while providing greater flexibility to the subject than traditional synchronous BCIs.

Using a prospective, longitudinal study design, this paper addresses the impact of genetic counseling and testing for deafness on deaf adults and the Deaf community. This study specifically evaluated the effect of genetic counseling and Connexin-26 and Connexin-30 genetic test results on participants' deaf identity and understanding of their genetic test results. Connexin-26 and Connexin-30 genetic testing was offered to participants in the context of linguistically and culturally appropriate genetic counseling. Questionnaire data collected from 209 deaf adults at four time points (baseline, immediately following pre-test genetic counseling, 1-month following genetic test result disclosure, and 6-months after result disclosure) were analyzed. Four deaf identity orientations (hearing, marginal, immersion, bicultural) were evaluated using subscales of the Deaf Identity Development Scale-Revised. We found evidence that participants understood their specific genetic test results following genetic counseling, but found no evidence of change in deaf identity based on genetic counseling or their genetic test results. This study demonstrated that culturally and linguistically appropriate genetic counseling can improve deaf clients' understanding of genetic test results, and the formation of deaf identity was not directly related to genetic counseling or Connexin-26 and Connexin-30 genetic test results.

This paper presents a method for selecting Regions of Interest (ROI) in brain Magnetic Resonance Imaging (MRI) for diagnostic purposes, using statistical learning and vector quantization techniques. The proposed method models the distribution of GM and WM tissues grouping the voxels belonging to each tissue in ROIs associated to a specific neurological disorder. Tissue distribution of normal and abnormal images is modelled by a Self-Organizing map (SOM), generating a set of representative prototypes, and the receptive field (RF) of each SOM prototype defines a ROI. Moreover, the proposed method computes the relative importance of each ROI by means of its discriminative power. The devised method has been assessed using 818 images from the Alzheimer's disease Neuroimaging Initiative (ADNI) which were previously segmented through Statistical Parametric Mapping (SPM). The proposed algorithm was used over these images to parcel ROIs associated to the Alzheimer's Disease (AD). Additionally, this method can be used to extract a reduced set of discriminative features for classification, since it compresses discriminative information contained in the brain. Voxels marked by ROIs which were computed using the proposed method, yield classification results up to 90% of accuracy for controls (CN) and Alzheimer's disease (AD) patients, and 84% of accuracy for Mild Cognitive Impairment (MCI) and AD patients.