Baseline Assessment: Alaska's Capacity and Infrastructure for Prescription Opioid Misuse Prevention

Funded by the Substance Abuse and Mental Health Services Administration, Center for Mental Health Services (Grant #SP020783) through the State of Alaska, Division of Behavioral Healt

PHYSIOLOGICAL COMPLIANCE DURING TEAM PERFORMANCE

Physiological compliance (PC) refers to the correlation between physiological measures of team members over time. The first goal of the current analyses was to generate several means to measure PC from heart rate variability (HRV) data. A second goal was to examine the relationship between PC and team performance during a building clearing task performed by 4-man teams. Teams were tasked with entering and clearing both real and simulated rooms populated with combatants (individuals with a weapon) and non-combatants (individuals without a weapon). Teams had to eliminate (shoot with a laser tag or simulated weapon) combatants and identify non-combatants (verbally or with a joystick). In Analysis I, linear correlation and directional agreement were shown to be the most sensitive PC measures when combined with HRV data. For Analysis II, 10 teams (20 subjects total, all male) were split into low and high performance groups based on their average team velocity and percentage of non-combatants acknowledged. Multivariate tests revealed a statistically significant difference between high a low performers, indicating that high, or better, performing teams tend to have higher PC. In Analysis III, one team was chosen to examine the relationship of performance and PC over time. Correlation testing on HRV data revealed a significant positive relationship between correlation RSA and performance (r=.853) and between correlation loge RSA and performance (r=.859). These results suggest that PC may have merit for predicting team performance in a dynamic task. However, further research is needed

Baseline Assessment: Alaska's Capacity and Infrastructure for Prescription Opioid Misuse Prevention

The State of Alaska Department of Health and Social Services (DHSS), Division of Behavioral Health (DBH) was awarded the Partnerships for Success (PFS) grant by the Substance Abuse and Mental Health Services Administration (SAHMSA) in 2015. DBH contracted with the Center for Behavioral Health Research and Services (CBHRS) at the University of Alaska Anchorage (UAA) to conduct a comprehensive project evaluation. As part of the evaluation, CBHRS performed a baseline assessment of the state’s capacity and infrastructure related to prescription opioid misuse prevention. Researchers conducted interviews with key stakeholders representing state government, healthcare agencies, law enforcement, substance abuse research, and service agencies. Interviews were semistructured, with questions addressing five domains of interest: (1) state climate and prevention efforts; (2) partnerships and coordinated efforts; (3) policies, practices, and laws; (4) data and data monitoring; and (5) knowledge and readiness. Thirteen interviews were conducted and analyzed using a qualitative template analysis technique combined with a SWOT analysis (i.e. strengths, weaknesses, opportunities, and threats). Emergent themes are displayed in Table 1 below. Table 1. Emergent themes from SWOT analysis Strengths Weaknesses Opportunities Threats (1) New and revised policies and guidelines (2) Activities and partnerships between state agencies and communities (3) Knowledge and awareness of state leadership (1) State policy limitations (2) Insufficient detox, treatment, and recovery support resources (3) Lack of full coordination within state agencies and with communities (1) Education enrichment (2) Policy improvements (3) Expansion of treatment, recovery, and mental health support (1) State fiscal crisis (2) Prescribing practices (3) Complexity and stigma of addiction (4) Legislative support Despite limitations in sample representativeness and interview timing, participants agreed that agencies, communities, and organizations across Alaska have demonstrated great concern about the opioid epidemic and that this concern has translated into considerable efforts to address and prevent opioid misuse. Participants also noted a variety of opportunities as targets for future work, many of which would address some of the current weaknesses that exist. Results yielded clear recommendations for increasing awareness and providing education to a variety of groups, further improving relevant policies to promote prevention, and expanding services for prevention and treatment.State of Alaska, Division of Behavioral Health Grant #SP020783Executive Summary / Introduction / Methodology / Results / Discussion / Reference

Implementing SBIRT in Primary Care: A Study of Three Mat-Su Borough Health Care Practices

Despite decades of research evidence that SBIRT is effective for addressing unhealthy patterns of drinking and reducing binge drinking, its adoption within healthcare practices continues to be slow. Providers have identified numerous reasons for not routinely screening and intervening on alcohol, including limited time, training, and resources for patients requiring treatment; lack of confidence in their ability to help patients reduce their drinking; inadequate reimbursement for SBIRT services, and worry about stigmatizing patients

Evaluation of alternatives for two-dimensional linear cascade facilities

This paper presents two low-cost alternatives for turbine blade surface heat transfer and fluid dynamics measurements. These models embody careful compromises between typical academic and full-scale turbomachinery experiments and represent a comprehensive strategy to develop experiments that can directly test shortcomings in current turbomachinery simulation tools. A full contextual history of the wide range of approaches to simulate turbine flow conditions is presented, along with a discussion of their deficiencies. Both models are simplifications of a linear cascade: the current standard for simulating two-dimensional turbine blade geometries. A single passage model is presented as a curved duct consisting of two half-blade geometries, carefully designed inlet and exit walls and inlet suction. This facility was determined to be best suited for heat transfer measurements where minimal surface conduction losses are necessary to allow accurate numerical model replication. A double passage model is defined as a single blade with two precisely designed outer walls, which is most appropriate for flow measurements. The design procedures necessary to achieve a desired flow condition are discussed

Hemorrhagic stroke outcomes of KApSR patients with co-morbid diabetes and Alzheimer’s disease

Background: Vascular risk factors, such as diabetes mellitus (DM), are associated with poorer outcomes following many neurodegenerative diseases, including hemorrhagic stroke and Alzheimer’s disease (AD). Combined AD and DM co-morbidities are associated with an increased risk of hemorrhagic stroke and increased Medicare costs. Therefore, we hypothesized that patients with DM in combination with AD, termed DM/AD, would have increased hemorrhagic stroke severity. Methods: Kentucky Appalachian Stroke Registry (KApSR) is a database of demographic and clinical data from patients that live in Appalachia, a distinct region with increased health disparities and stroke severity. Inpatients with a primary indication of hemorrhagic stroke were selected from KApSR for retrospective analysis and were separated into four groups: DM only, AD only, neither, or both. Results: Hemorrhagic stroke patients (2,071 total) presented with either intracerebral hemorrhage (ICH), n=1,448, or subarachnoid hemorrhage (SAH), n=623. When examining all four groups, subjects with AD were significantly older (AD+, 80.9±6.6 yrs) (DM+/AD+, 77.4±10.0 yrs) than non AD subjects (DM-/AD-, 61.3±16.5 yrs) and (DM+, 66.0±12.5 yrs). A higher percentage of females were among the AD+ group and a higher percentage of males among the DM+/AD+ group. Interestingly, after adjusting for multiple comparison, DM+/AD+ subjects were ten times as likely to suffer a moderate to severe stroke based on a National Institute of Health Stroke (NIHSS) upon admission [odds ratio (95% CI)] compared to DM-/AD- [0.1 (0.02–0.55)], DM+ [0.11 (0.02–0.59)], and AD+ [0.09(0.01–0.63)]. The odds of DM+/AD+ subjects having an unfavorable discharge destination (death, hospice, long-term care) was significant (P Conclusions: In our retrospective analysis utilizing KApSR, regardless of adjusting for age, sex, and comorbidities, DM+/AD+ patients were significantly more likely to have had a moderate or severe stroke leading to an unfavorable outcome following hemorrhagic stroke

The automatic detection of chronic pain-related expression: requirements, challenges and a multimodal dataset

Pain-related emotions are a major barrier to effective self rehabilitation in chronic pain. Automated coaching systems capable of detecting these emotions are a potential solution. This paper lays the foundation for the development of such systems by making three contributions. First, through literature reviews, an overview of how chronic pain is expressed and the motivation for detecting it in physical rehabilitation is provided. Second, a fully labelled multimodal dataset containing high resolution multiple-view face videos, head mounted and room audio signals, full body 3-D motion capture and electromyographic signals from back muscles is supplied. Natural unconstrained pain related facial expressions and body movement behaviours were elicited from people with chronic pain carrying out physical exercises. Both instructed and non- instructed exercises where considered to reflect different rehabilitation scenarios. Two sets of labels were assigned: level of pain from facial expressions annotated by eight raters and the occurrence of six pain-related body behaviours segmented by four experts. Third, through exploratory experiments grounded in the data, the factors and challenges in the automated recognition of such expressions and behaviour are described, the paper concludes by discussing potential avenues in the context of these findings also highlighting differences for the two exercise scenarios addressed

Korarchaeota Diversity, Biogeography, and Abundance in Yellowstone and Great Basin Hot Springs and Ecological Niche Modeling Based on Machine Learning

Over 100 hot spring sediment samples were collected from 28 sites in 12 areas/regions, while recording as many coincident geochemical properties as feasible (>60 analytes). PCR was used to screen samples for Korarchaeota 16S rRNA genes. Over 500 Korarchaeota 16S rRNA genes were screened by RFLP analysis and 90 were sequenced, resulting in identification of novel Korarchaeota phylotypes and exclusive geographical variants. Korarchaeota diversity was low, as in other terrestrial geothermal systems, suggesting a marine origin for Korarchaeota with subsequent niche-invasion into terrestrial systems. Korarchaeota endemism is consistent with endemism of other terrestrial thermophiles and supports the existence of dispersal barriers. Korarchaeota were found predominantly in >55°C springs at pH 4.7–8.5 at concentrations up to 6.6×106 16S rRNA gene copies g−1 wet sediment. In Yellowstone National Park (YNP), Korarchaeota were most abundant in springs with a pH range of 5.7 to 7.0. High sulfate concentrations suggest these fluids are influenced by contributions from hydrothermal vapors that may be neutralized to some extent by mixing with water from deep geothermal sources or meteoric water. In the Great Basin (GB), Korarchaeota were most abundant at spring sources of pH<7.2 with high particulate C content and high alkalinity, which are likely to be buffered by the carbonic acid system. It is therefore likely that at least two different geological mechanisms in YNP and GB springs create the neutral to mildly acidic pH that is optimal for Korarchaeota. A classification support vector machine (C-SVM) trained on single analytes, two analyte combinations, or vectors from non-metric multidimensional scaling models was able to predict springs as Korarchaeota-optimal or sub-optimal habitats with accuracies up to 95%. To our knowledge, this is the most extensive analysis of the geochemical habitat of any high-level microbial taxon and the first application of a C-SVM to microbial ecology

IL-12Rβ2 is critical for survival of primary Francisella tularensis LVS infection

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