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We report about a clinical observation in a well-characterized group of patients with obsessive-compulsive disorder (OCD) during an experimental medicine study in which a single dose of amisulpride (a selective D₂/₃ antagonist) was administered. Almost half of the OCD patients, in particular those with less severe obsessive-compulsive symptoms, experienced acute akathisia in response to the amisulpride challenge. This unexpectedly high incidence of akathisia in the selective serotonin reuptake inhibitor (SSRI)-treated patients with OCD suggests that individual differences in dopamine-serotonin interactions underlie the clinical heterogeneity of OCD, and may thus explain the insufficiency of SSRI monotherapy in those patients not experiencing a satisfactory outcome in symptom reduction. We further speculate about the neuropathology possibly underlying this clinical observation and outline a testable hypothesis for future molecular imaging studies. [ABSTRACT FROM AUTHOR]

Albatrosses are increasingly drawing attention from the scientific community due to their remarkable flight capabilities. Recent studies suggest that grey-headed albatrosses (GHA) may be the fastest and most energy-efficient of the albatross species, yet no attempts have been made to replicate their wing design. A key factor in aircraft design is the airfoil, which remains uncharacterized for the GHA. Other critical aspects, such as wing twist and dihedral/anhedral, also remain unquantified for any albatross species. This study aimed to fill this gap in the current knowledge by extracting detailed morphological data from a GHA wing to recreate digitally. A well-preserved dried GHA wing was scanned in the presence of airflow in a wind tunnel, at conditions that represent a GHA in gliding flight. Wing cross-sections were extracted and smoothed to produce a series of airfoils along the wing span. The 3D properties such as wing dihedral/anhedral, sweep and twist were also extracted and used to build a CAD model of the wing. Variations in airfoil shape were observed along the wing span, with thicker, more cambered airfoils near the wing base. The model wing's camber was slightly higher, particularly in the arm section, but overall matched flight photographs. The body, tail, and bill were modelled based on available photographs and known dimensions from literature and merged with the wing to form the final bill-body-wing-tail model. This model is based on real GHA morphology under aerodynamic pressure, in gliding flight. Although geometric changes due to scanner interference remain a limitation of this method, the extracted geometric data still provide valuable insights into wing performance under varying conditions. The geometry can also be fully parameterized for complex simulations, aiding studies of GHA aerodynamics and engineering design, such as in aircraft or wind turbines at similar Reynolds numbers., (© 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Background/Objectives : Few studies have assessed barriers to providing care from the perspective of interprofessional healthcare providers. Despite Idaho's predominantly rural geography, limited research exists assessing barriers to providing care within the state. This study sought to assess barriers to providing optimal healthcare using a sample of 400 healthcare providers at 22 clinic sites across the state. Methods : A barriers to providing optimal care 9-factor, 41-item survey was modified from an existing survey. Healthcare providers rated barrier items using an 11-point Likert scale. The survey was distributed to a convenience sample of healthcare providers in 22 different clinic sites in rural Idaho. Results : Four hundred interprofessional healthcare providers in Idaho across 13 professional disciplines completed surveys. Items in the Service Access (mean = 7.14), Patient Complexity (mean = 6.59), and Resource Limitations (mean = 6.18) factors were reported as the most commonly perceived barriers to providing optimal care. Conclusions : Few studies have assessed rural interprofessional providers' perceived barriers to providing optimal, high-quality, care, specifically in the rural state of Idaho, where healthcare services are often not equitable compared to urban regions. The results suggest that commonly perceived barriers exist throughout the state, particularly Service Access , Patient Complexity , and Resource Limitations . Further research is needed to develop data-driven decisions to address these concerns.

As the population of older adults grows at an unprecedented rate, there is a large gap to provide culturally tailored end-of-life care. This study describes a payor-led, informatics-based approach to identify Medicare members who may benefit from a Compassionate Care SM Program (CCP), which was designed to provide specialized care management services and support to members who have end-stage and/or life-limiting illnesses by addressing the quintuple aim. Potential participants are identified through machine learning models whereby nurse care managers then provide tailored outreach via telephone. A retrospective, observational cohort analysis of propensity-weighted Medicare members was performed to compare decedents who did or did not participate in the CCP. This program enhanced the end-of-life care experience while providing equitable outcomes regardless of age, gender, and geography and decreased inpatient (-37%) admissions with concomitant reduced (-59%) medical spend when compared to decedents that did not utilize the end-of-life care management program., Competing Interests: All authors were employed by CVS Health® Corporation at the time of the study. AZ, KJTC, and HY own stock and/or equity in CVS Health. AZ is also employed by Hartford Hospital. The authors have no conflicts germane to this study., (©2023 AMIA - All rights reserved.)

Enhancing diversity and inclusion in clinical trial recruitment, especially for historically marginalized populations including Black, Indigenous, and People of Color individuals, is essential. This practice ensures that generalizable trial results are achieved to deliver safe, effective, and equitable health and healthcare. However, recruitment is limited by two inextricably linked barriers - the inability to recruit and retain enough trial participants, and the lack of diversity amongst trial populations whereby racial and ethnic groups are underrepresented when compared to national composition. To overcome these barriers, this study describes and evaluates a framework that combines 1) probabilistic and machine learning models to accurately impute missing race and ethnicity fields in real-world data including medical and pharmacy claims for the identification of eligible trial participants, 2) randomized controlled trial experimentation to deliver an optimal patient outreach strategy, and 3) stratified sampling techniques to effectively balance cohorts to continuously improve engagement and recruitment metrics., (©2023 AMIA - All rights reserved.)

Artificial intelligence-based algorithms are being widely implemented in health care, even as evidence is emerging of bias in their design, problems with implementation, and potential harm to patients. To achieve the promise of using of AI-based tools to improve health, healthcare organizations will need to be AI-capable, with internal and external systems functioning in tandem to ensure the safe, ethical, and effective use of AI-based tools. Ideas are starting to emerge about the organizational routines, competencies, resources, and infrastructures that will be required for safe and effective deployment of AI in health care, but there has been little empirical research. Infrastructures that provide legal and regulatory guidance for managers, clinician competencies for the safe and effective use of AI-based tools, and learner-centric resources such as clear AI documentation and local health ecosystem impact reviews can help drive continuous improvement., Competing Interests: The authors have no competing interests to report other than employment (JS and KJTC are/were employed by IBM® Corporation; KJTC employed by CVS Health® Corporation)., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: The use of artificial intelligence (AI)-based tools in the care of individual patients and patient populations is rapidly expanding., Objective: The aim of this paper is to systematically identify research on provider competencies needed for the use of AI in clinical settings., Methods: A scoping review was conducted to identify articles published between January 1, 2009, and May 1, 2020, from MEDLINE, CINAHL, and the Cochrane Library databases, using search queries for terms related to health care professionals (eg, medical, nursing, and pharmacy) and their professional development in all phases of clinical education, AI-based tools in all settings of clinical practice, and professional education domains of competencies and performance. Limits were provided for English language, studies on humans with abstracts, and settings in the United States., Results: The searches identified 3476 records, of which 4 met the inclusion criteria. These studies described the use of AI in clinical practice and measured at least one aspect of clinician competence. While many studies measured the performance of the AI-based tool, only 4 measured clinician performance in terms of the knowledge, skills, or attitudes needed to understand and effectively use the new tools being tested. These 4 articles primarily focused on the ability of AI to enhance patient care and clinical decision-making by improving information flow and display, specifically for physicians., Conclusions: While many research studies were identified that investigate the potential effectiveness of using AI technologies in health care, very few address specific competencies that are needed by clinicians to use them effectively. This highlights a critical gap., (©Kim V Garvey, Kelly Jean Thomas Craig, Regina Russell, Laurie L Novak, Don Moore, Bonnie M Miller. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 16.11.2022.)

Background: Disease prevention is a central aspect of primary care practice and is comprised of primary (eg, vaccinations), secondary (eg, screenings), tertiary (eg, chronic condition monitoring), and quaternary (eg, prevention of overmedicalization) levels. Despite rapid digital transformation of primary care practices, digital health interventions (DHIs) in preventive care have yet to be systematically evaluated., Objective: This review aimed to identify and describe the scope and use of current DHIs for preventive care in primary care settings., Methods: A scoping review to identify literature published from 2014 to 2020 was conducted across multiple databases using keywords and Medical Subject Headings terms covering primary care professionals, prevention and care management, and digital health. A subgroup analysis identified relevant studies conducted in US primary care settings, excluding DHIs that use the electronic health record (EHR) as a retrospective data capture tool. Technology descriptions, outcomes (eg, health care performance and implementation science), and study quality as per Oxford levels of evidence were abstracted., Results: The search yielded 5274 citations, of which 1060 full-text articles were identified. Following a subgroup analysis, 241 articles met the inclusion criteria. Studies primarily examined DHIs among health information technologies, including EHRs (166/241, 68.9%), clinical decision support (88/241, 36.5%), telehealth (88/241, 36.5%), and multiple technologies (154/241, 63.9%). DHIs were predominantly used for tertiary prevention (131/241, 54.4%). Of the core primary care functions, comprehensiveness was addressed most frequently (213/241, 88.4%). DHI users were providers (205/241, 85.1%), patients (111/241, 46.1%), or multiple types (89/241, 36.9%). Reported outcomes were primarily clinical (179/241, 70.1%), and statistically significant improvements were common (192/241, 79.7%). Results were summarized across the following 5 topics for the most novel/distinct DHIs: population-centered, patient-centered, care access expansion, panel-centered (dashboarding), and application-driven DHIs. The quality of the included studies was moderate to low., Conclusions: Preventive DHIs in primary care settings demonstrated meaningful improvements in both clinical and nonclinical outcomes, and across user types; however, adoption and implementation in the US were limited primarily to EHR platforms, and users were mainly clinicians receiving alerts regarding care management for their patients. Evaluations of negative results, effects on health disparities, and many other gaps remain to be explored., (©Van C Willis, Kelly Jean Thomas Craig, Yalda Jabbarpour, Elisabeth L Scheufele, Yull E Arriaga, Monica Ajinkya, Kyu B Rhee, Andrew Bazemore. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 21.01.2022.)

Objective: Identify how novel datasets and digital health technology, including both analytics-based and artificial intelligence (AI)-based tools, can be used to assess non-clinical, social determinants of health (SDoH) for population health improvement., Methods: A state-of-the-art literature review with systematic methods was performed on MEDLINE, Embase, and the Cochrane Library databases and the grey literature to identify recently published articles (2013-2018) for evidence-based qualitative synthesis. Following single review of titles and abstracts, two independent reviewers assessed eligibility of full-texts using predefined criteria and extracted data into predefined templates., Results: The search yielded 2,714 unique database records of which 65 met inclusion criteria. Most studies were conducted retrospectively in a United States community setting. Identity, behavioral, and economic factors were frequently identified social determinants, due to reliance on administrative data. Three main themes were identified: 1) improve access to data and technology with policy - advance the standardization and interoperability of data, and expand consumer access to digital health technologies; 2) leverage data aggregation - enrich SDoH insights using multiple data sources, and use analytics-based and AI-based methods to aggregate data; and 3) use analytics-based and AI-based methods to assess and address SDoH - retrieve SDoH in unstructured and structured data, and provide contextual care management sights and community-level interventions., Conclusions: If multiple datasets and advanced analytical technologies can be effectively integrated, and consumers have access to and literacy of technology, more SDoH insights can be identified and targeted to improve public health. This study identified examples of AI-based use cases in public health informatics, and this literature is very limited., Competing Interests: Competing Interests The authors are or were employed by IBM® Corporation and have no conflicts germane to this study., (This is an Open Access article. Authors own copyright of their articles appearing in the Journal of Public Health Informatics. Readers may copy articles without permission of the copyright owner(s), as long as the author and OJPHI are acknowledged in the copy and the copy is used for educational, not-for-profit purposes.)

Background: Contact tracing in association with quarantine and isolation is an important public health tool to control outbreaks of infectious diseases. This strategy has been widely implemented during the current COVID-19 pandemic. The effectiveness of this nonpharmaceutical intervention is largely dependent on social interactions within the population and its combination with other interventions. Given the high transmissibility of SARS-CoV-2, short serial intervals, and asymptomatic transmission patterns, the effectiveness of contact tracing for this novel viral agent is largely unknown., Objective: This study aims to identify and synthesize evidence regarding the effectiveness of contact tracing on infectious viral disease outcomes based on prior scientific literature., Methods: An evidence-based review was conducted to identify studies from the PubMed database, including preprint medRxiv server content, related to the effectiveness of contact tracing in viral outbreaks. The search dates were from database inception to July 24, 2020. Outcomes of interest included measures of incidence, transmission, hospitalization, and mortality., Results: Out of 159 unique records retrieved, 45 (28.3%) records were reviewed at the full-text level, and 24 (15.1%) records met all inclusion criteria. The studies included utilized mathematical modeling (n=14), observational (n=8), and systematic review (n=2) approaches. Only 2 studies considered digital contact tracing. Contact tracing was mostly evaluated in combination with other nonpharmaceutical interventions and/or pharmaceutical interventions. Although some degree of effectiveness in decreasing viral disease incidence, transmission, and resulting hospitalizations and mortality was observed, these results were highly dependent on epidemic severity (R0 value), number of contacts traced (including presymptomatic and asymptomatic cases), timeliness, duration, and compliance with combined interventions (eg, isolation, quarantine, and treatment). Contact tracing effectiveness was particularly limited by logistical challenges associated with increased outbreak size and speed of infection spread., Conclusions: Timely deployment of contact tracing strategically layered with other nonpharmaceutical interventions could be an effective public health tool for mitigating and suppressing infectious outbreaks by decreasing viral disease incidence, transmission, and resulting hospitalizations and mortality., (©Kelly Jean Thomas Craig, Rubina Rizvi, Van C Willis, William J Kassler, Gretchen Purcell Jackson. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 06.10.2021.)

Health risk behaviors are leading contributors to morbidity, premature mortality associated with chronic diseases, and escalating health costs. However, traditional interventions to change health behaviors often have modest effects, and limited applicability and scale. To better support health improvement goals across the care continuum, new approaches incorporating various smart technologies are being utilized to create more individualized digital behavior change interventions (DBCIs). The purpose of this study is to identify context-aware DBCIs that provide individualized interventions to improve health. A systematic review of published literature (2013-2020) was conducted from multiple databases and manual searches. All included DBCIs were context-aware, automated digital health technologies, whereby user input, activity, or location influenced the intervention. Included studies addressed explicit health behaviors and reported data of behavior change outcomes. Data extracted from studies included study design, type of intervention, including its functions and technologies used, behavior change techniques, and target health behavior and outcomes data. Thirty-three articles were included, comprising mobile health (mHealth) applications, Internet of Things wearables/sensors, and internet-based web applications. The most frequently adopted behavior change techniques were in the groupings of feedback and monitoring, shaping knowledge, associations, and goals and planning. Technologies used to apply these in a context-aware, automated fashion included analytic and artificial intelligence (e.g., machine learning and symbolic reasoning) methods requiring various degrees of access to data. Studies demonstrated improvements in physical activity, dietary behaviors, medication adherence, and sun protection practices. Context-aware DBCIs effectively supported behavior change to improve users' health behaviors., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society of Behavioral Medicine.)

Objective: To conduct a systematic review identifying workplace interventions that mitigate physician burnout related to the digital environment including health information technologies (eg, electronic health records) and decision support systems) with or without the application of advanced analytics for clinical care., Materials and Methods: Literature published from January 1, 2007 to June 3, 2020 was systematically reviewed from multiple databases and hand searches. Subgroup analysis identified relevant physician burnout studies with interventions examining digital tool burden, related workflow inefficiencies, and measures of burnout, stress, or job satisfaction in all practice settings., Results: The search strategy identified 4806 citations of which 81 met inclusion criteria. Thirty-eight studies reported interventions to decrease digital tool burden. Sixty-eight percent of these studies reported improvement in burnout and/or its proxy measures. Burnout was decreased by interventions that optimized technologies (primarily electronic health records), provided training, reduced documentation and task time, expanded the care team, and leveraged quality improvement processes in workflows., Discussion: The contribution of digital tools to physician burnout can be mitigated by careful examination of usability, introducing technologies to save or optimize time, and applying quality improvement to workflows., Conclusion: Physician burnout is not reduced by technology implementation but can be mitigated by technology and workflow optimization, training, team expansion, and careful consideration of factors affecting burnout, including specialty, practice setting, regulatory pressures, and how physicians spend their time., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Disparities in cardiovascular disease (CVD) and associated health and healthcare delivery outcomes have been partially attributed to differential risk factors, and to prevention and treatment inequities within racial and ethnic (including language) minority groups and low socioeconomic status (SES) populations in urban and rural settings. Digital health interventions (DHIs) show promise in promoting equitable access to high-quality care, optimal utilization, and improved outcomes; however, their potential role and impact has not been fully explored. The role of DHIs to mitigate drivers of the health disparities listed above in populations disproportionately affected by atherosclerotic-related CVD was systematically reviewed using published literature (January 2008-July 2020) from multiple databases. Study design, type and description of the technology, health disparities information, type of CVD, outcomes, and notable barriers and innovations associated with the technology utilized were abstracted. Study quality was assessed using the Oxford Levels of Evidence. Included studies described digital health technologies in a disparity population with CVD and reported outcomes. DHIs significantly improved health (eg, clinical, intermediate, and patient-reported) and healthcare delivery (eg, access, quality, and utilization of care) outcomes in populations disproportionately affected by CVD in 24 of 38 included studies identified from 2104 citations. Hypertension control was the most frequently improved clinical outcome. Telemedicine, mobile health, and clinical decision support systems were the most common types of DHIs identified. DHIs improved CVD-related health and healthcare delivery outcomes in racial/ethnic groups and low SES populations in both rural and urban geographies globally., (© 2020 Heart Rhythm Society. Published by Elsevier Inc.)

Background: Hospital performance quality assessments inform patients, providers, payers, and purchasers in making healthcare decisions. These assessments have been developed by government, private and non-profit organizations, and academic institutions. Given the number and variability in available assessments, a knowledge gap exists regarding what assessments are available and how each assessment measures quality to identify top performing hospitals. This study aims to: (a) comprehensively identify current hospital performance assessments, (b) compare quality measures from each methodology in the context of the Institute of Medicine's (IOM) six domains of STEEEP (safety, timeliness, effectiveness, efficiency, equitable, and patient-centeredness), and (c) formulate policy recommendations that improve value-based, patient-centered care to address identified gaps., Methods: A scoping review was conducted using a systematic search of MEDLINE and the grey literature along with handsearching to identify studies that provide assessments of US-based hospital performance whereby the study cohort examined a minimum of 250 hospitals in the last two years (2017-2019)., Results: From 3058 unique records screened, 19 hospital performance assessments met inclusion criteria. Methodologies were analyzed across each assessment and measures were mapped to STEEEP. While safety and effectiveness were commonly identified measures across assessments, efficiency, and patient-centeredness were less frequently represented. Equity measures were also limited to risk- and severity-adjustment methods to balance patient characteristics across populations, rather than stand-alone indicators to evaluate health disparities that may contribute to community-level inequities., Conclusions: To further improve health and healthcare value-based decision-making, there remains a need for methodological transparency across assessments and the standardization of consensus-based measures that reflect the IOM's quality framework. Additionally, a large opportunity exists to improve the assessment of health equity in the communities that hospitals serve.

To assess the impact of organization-directed workplace interventions on physician burnout, including stress or job satisfaction in all settings, we conducted a systematic review of the literature published from January 1, 2007, to October 3, 2018, from multiple databases. Manual searches of grey literature and bibliographies were also performed. Of the 633 identified citations, 50 met inclusion criteria. Four unique categories of organization-directed workplace interventions were identified. Teamwork involved initiatives to incorporate scribes or medical assistants into electronic health record (EHR) processes, expand team responsibilities, and improve communication among physicians. Time studies evaluated the impact of schedule adjustments, duty hour restrictions, and time-banking initiatives. Transitions referred to workflow changes such as process improvement initiatives or policy changes within the organization. Technology related to the implementation or improvement of EHRs. Of the 50 included studies, 35 (70.0%) reported interventions that successfully improved the 3 measures of physician burnout, job satisfaction, and/or stress. The largest benefits resulted from interventions that improved processes, promoted team-based care, and incorporated the use of scribes/medical assistants to complete EHR documentation and tasks. Implementation of EHR interventions to improve clinical workflows worsened burnout, but EHR improvements had positive effects. Time interventions had mixed effects on burnout. The results of our study suggest that organization-directed workplace interventions that improve processes, optimize EHRs, reduce clerical burden by the use of scribes, and implement team-based care can lessen physician burnout. Benefits of process changes can enhance physician resiliency, augment care provided by the team, and optimize the coordination and communication of patient care and health information., (© 2019 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc.)

Rationale: Patients with obsessive-compulsive disorder (OCD) have been found to show exaggerated error responses and prediction error learning signals in a variety of EEG and fMRI tasks, with data converging on the anterior cingulate cortex as a key locus of dysfunction. Considerable evidence has linked prediction error processing to dopaminergic function., Objective: In this study, we investigate potential dopaminergic dysfunction during reward processing in the context of OCD., Methods: We studied OCD patients (n = 18) and controls (n = 18) whilst they learned probabilistic associations between abstract stimuli and monetary rewards in the fMRI scanner involving administration (on separate visits) of a dopamine receptor agonist, pramipexole 0.5 mg; a dopamine receptor antagonist, amisulpride 400 mg; and placebo. We fitted a Q-learning computational model to fMRI prediction error responses; group differences were examined in anterior cingulate and nucleus accumbens regions of interest., Results: There were no significant group, drug, or interaction effects in the number of correct choices; computational modeling suggested a marginally significant difference in learning rates between groups (p = 0.089, partial ƞ 2  = 0.1). In the imaging results, there was a significant interaction of group by drug (p = 0.013, partial ƞ 2  = 0.13). OCD patients showed abnormally strong cingulate signaling of prediction errors during omission of an expected reward, with unexpected reduction by both pramipexole and amisulpride (p = 0.014, partial ƞ 2  = 0.26, 1-β error probability = 0.94). Exaggerated cingulate prediction error signaling to omitted reward in placebo was related to trait subjective difficulty in self-regulating behavior in OCD., Conclusions: Our data support cingulate dysfunction during reward processing in OCD, and bidirectional remediation by dopaminergic modulation, suggesting that exaggerated cingulate error signals in OCD may be of dopaminergic origin. The results help to illuminate the mechanisms through which dopamine receptor antagonists achieve therapeutic benefit in OCD. Further research is needed to disentangle the different functions of dopamine receptor agonists and antagonists during bidirectional modulation of cingulate activation.

Celiac disease (CD) is an immune-mediated gastrointestinal (GI) disorder driven by innate and adaptive immune responses to gluten. Presentation of CD has changed over time, with non-GI symptoms, such as anemia and osteoporosis, presenting more commonly. With improved screening and diagnostic methods, the reported prevalence of CD has increased globally, and there is considerable global variation in diagnostic and treatment practices. The objective of this study was to describe the current state of CD diagnosis and treatment patterns. A targeted review of literature from MEDLINE, Embase, the Cochrane Library, and screening of relevant conference abstracts was performed. The generally recommended diagnostic approach is GI endoscopy with small bowel biopsy; however, in selected patients, biopsy may be avoided and diagnosis based on positive serology and clinical symptoms. Diagnosis often is delayed; the average diagnostic delay after symptom onset is highly variable and can last up to 12 years. Barriers to accurate and timely diagnosis include atypical presentation, lack of physician awareness about current diagnostic criteria, misdiagnosis, and limited access to specialists. Currently, strict adherence to a gluten-free diet (GFD) is the only recommended treatment, which is not successful in all patients. Only one-third of patients are monitored regularly following diagnosis. Unmet needs for CD include improvements in the accuracy and timeliness of diagnosis, and the development of treatments for both refractory CD and GFD nonresponsive CD. Further research should investigate the impact of education about gluten-free eating and the availability of gluten-free foods support adherence and improve outcomes in patients with CD.

Celiac disease (CD) is an immune-mediated gastrointestinal disorder driven by innate and adaptive immune responses to gluten. Patients with CD are at an increased risk of several neurological manifestations, frequently peripheral neuropathy and gluten ataxia. A systematic literature review of the most commonly reported neurological manifestations (neuropathy and ataxia) associated with CD was performed. MEDLINE, Embase, the Cochrane Library, and conference proceedings were systematically searched from January 2007 through September 2018. Included studies evaluated patients with CD with at least one neurological manifestation of interest and reported prevalence, and/or incidence, and/or clinical outcomes. Sixteen studies were included describing the risk of gluten neuropathy and/or gluten ataxia in patients with CD. Gluten neuropathy was a neurological manifestation in CD (up to 39%) in 13 studies. Nine studies reported a lower risk and/or prevalence of gluten ataxia with a range of 0%⁻6%. Adherence to a gluten-free diet appeared to improve symptoms of both neuropathy and ataxia. The prevalence of gluten neuropathy and gluten ataxia in patients with CD varied in reported studies, but the increased risk supports the need for physicians to consider CD in patients with ataxia and neurological manifestations of unknown etiology., Competing Interests: E.M., A.C., S.P., and K.C. were employees of IBM Watson Health during the completion of this study. A.T., M.G., and D.L. were employees of Takeda Pharmaceuticals International Co during the completion of this study. D.S., B.L., and M.H. serve as consultants for Takeda Pharmaceuticals International Co. The authors declare no conflict of interest.

Background: The prevalence of celiac disease (CD) has rapidly increased over recent decades, but costs related to CD remain poorly quantified., Objective: This systematic review assessed the economic burden of CD in North America and Europe., Methods: MEDLINE, EMBASE, EconLit, and the Cochrane Library databases were systematically searched to identify English-language literature from 2007 to 2018 that assessed costs, cost effectiveness, and health resource utilization for CD., Results: Forty-nine studies met the inclusion criteria, of which 28 (57.1%) addressed costs of testing and diagnosis; 33 (67.3%) were from Europe. The cost per positive CD diagnosis of testing patients already undergoing esophagogastroduodenoscopy for other indications ranged from 1300 Canadian dollars ($Can) in Canada (2016 value) to €44,712 in the Netherlands (2013 value). Adding the CD test was cost effective when it combined diagnostic modalities (e.g., serology and biopsy). Direct annual excess costs to a US payer per diagnosed CD patient totaled $US6000 (2013 value) more than for a person without CD, chiefly due to outpatient care. Hospitalizations, emergency visits, and medication use were more common with CD. After initiating a gluten-free diet (GFD), patients visited primary care providers less often, used more medications, and missed fewer days from school and work., Conclusions: Most of the few available economic studies of CD assess testing and diagnosis costs, especially in Europe. Methods of testing generally are considered cost effective when they combine diagnostic modalities in symptomatic patients. Most costs to a payer of managing CD derive from outpatient care. Following GFD initiation, patients lose fewer days from work and school than pretreatment.

The development of drugs to improve cognition in patients with schizophrenia is a major unmet clinical need. A number of promising compounds failed in recent clinical trials, a pattern linked to poor translation between preclinical and clinical stages of drug development. Seeking proof of efficacy in early Phase 1 studies in surrogate patient populations (for example, high schizotypy individuals where subtle cognitive impairment is present) has been suggested as a strategy to reduce attrition in the later stages of drug development. However, there is little agreement regarding the pattern of distribution of schizotypal features in the general population, creating uncertainty regarding the optimal control group that should be included in prospective trials. We aimed to address this question by comparing the performance of groups derived from the general population with low, average and high schizotypy scores over a range of cognitive and oculomotor tasks. We found that tasks dependent on frontal inhibitory mechanisms (N-Back working memory and anti-saccade oculomotor tasks), as well as a smooth-pursuit oculomotor task were sensitive to differences in the schizotypy phenotype. In these tasks the cognitive performance of 'low schizotypes' was significantly different from 'high schizotypes' with 'average schizotypes' having an intermediate performance. These results indicate that for evaluating putative cognition enhancers for treating schizophrenia in early-drug development studies the maximum schizotypy effect would be achieved using a design that compares low and high schizotypes., Competing Interests: IK has been awarded a Manchester Strategic PhD Studentship, sponsored by the University of Manchester and P1vital Ltd. The PhD project of AS was partly funded by P1vital Ltd. UE is supported by the Deutsche Forschungsgemeinschaft (Et 31/2-1). JFWD has been supported by the Manchester Biomedical Research Centre. JFWD has carried out paid consultancy work and speaking engagements for Servier, Merck Sharpe and Dohme, Astrazeneca, Janssen, and Eli Lilly. The fees are paid to the University of Manchester to reimburse them for the time taken. JFWD, GRD and CTD own shares in P1vital Ltd. EB acknowledges the support of a Young Investigator Award from NARSAD. KJC worked for P1vital Ltd at the time that this research was conducted. He is currently an employee and shareholder in Covance Inc. DJ declares no relevant conflicts of interest.

Spatial navigation requires a well-established network of brain regions, including the hippocampus, caudate nucleus, and retrosplenial cortex. Amnestic Mild Cognitive Impairment (aMCI) is a condition with predominantly memory impairment, conferring a high predictive risk factor for dementia. aMCI is associated with hippocampal atrophy and subtle deficits in spatial navigation. We present the first use of a functional Magnetic Resonance Imaging (fMRI) navigation task in aMCI, using a virtual reality analog of the Radial Arm Maze. Compared with controls, aMCI patients showed reduced activity in the hippocampus bilaterally, retrosplenial cortex, and left dorsolateral prefrontal cortex. Reduced activation in key areas for successful navigation, as well as additional regions, was found alongside relatively normal task performance. Results also revealed increased activity in the right dorsolateral prefrontal cortex in aMCI patients, which may reflect compensation for reduced activations elsewhere. These data support suggestions that fMRI spatial navigation tasks may be useful for staging of progression in MCI.

Patients with amnestic mild cognitive impairment (aMCI) show preserved or mildly impaired working memory, despite their deficits in episodic memory. We aimed to identify performance and/or neural differences between aMCI patients and matched controls on a standard working memory fMRI task. Neuropsychological assessment demonstrated aMCI impairments in verbal and visual episodic long-term memory, with intact IQ and executive function. Participants completed a standard three-level N-back task where patients were unimpaired. Functional activations in the control group were found in expected areas, including the inferior parietal lobule and dorsolateral prefrontal cortex. Group differences were found in the insula and lingual gyrus and, in a region of interest analysis, in the hippocampus. In all cases, these were caused by an absence of task-related deactivations in the aMCI group. The results are consistent with reports of failure in task-related deacivations in aMCI and could be early indications of pathology.

Fibrosis in response to tissue damage or persistent inflammation is a pathological hallmark of many chronic degenerative diseases. By using a model of acute peritoneal inflammation, we have examined how repeated inflammatory activation promotes fibrotic tissue injury. In this context, fibrosis was strictly dependent on interleukin-6 (IL-6). Repeat inflammation induced IL-6-mediated T helper 1 (Th1) cell effector commitment and the emergence of STAT1 (signal transducer and activator of transcription-1) activity within the peritoneal membrane. Fibrosis was not observed in mice lacking interferon-γ (IFN-γ), STAT1, or RAG-1. Here, IFN-γ and STAT1 signaling disrupted the turnover of extracellular matrix by metalloproteases. Whereas IL-6-deficient mice resisted fibrosis, transfer of polarized Th1 cells or inhibition of MMP activity reversed this outcome. Thus, IL-6 causes compromised tissue repair by shifting acute inflammation into a more chronic profibrotic state through induction of Th1 cell responses as a consequence of recurrent inflammation., (Copyright © 2014 Elsevier Inc. All rights reserved.)

The non-competitive N-methyl-D-aspartate receptor antagonist ketamine leads to transient psychosis-like symptoms and impairments in oculomotor performance in healthy volunteers. This study examined whether the adverse effects of ketamine on oculomotor performance can be reversed by the atypical antipsychotic risperidone. In this randomized double-blind, placebo-controlled study, 72 healthy participants performed smooth pursuit eye movements (SPEM), prosaccades (PS) and antisaccades (AS) while being randomly assigned to one of four drug groups (intravenous 100 ng ml(-1) ketamine, 2 mg oral risperidone, 100  ng ml(-1) ketamine plus 2 mg oral risperidone, placebo). Drug administration did not lead to harmful adverse events. Ketamine increased saccadic frequency and decreased velocity gain of SPEM (all P < 0.01) but had no significant effects on PS or AS (all P > or = 0.07). An effect of risperidone was observed for amplitude gain and peak velocity of PS and AS, indicating hypometric gain and slower velocities compared with placebo (both P < or = 0.04). No ketamine by risperidone interactions were found (all P > or = 0.26). The results confirm that the administration of ketamine produces oculomotor performance deficits similar in part to those seen in schizophrenia. The atypical antipsychotic risperidone did not reverse ketamine-induced deteriorations. These findings do not support the cognitive enhancing potential of risperidone on oculomotor biomarkers in this model system of schizophrenia and point towards the importance of developing alternative performance-enhancing compounds to optimise pharmacological treatment of schizophrenia.

Retrieval of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) using the Collection 5 (C005) algorithm provides large-scale (10 × 10 km) estimates that can be used to predict surface layer concentrations of particulate matter with aerodynamic diameter smaller than 2.5 μm (PM 2.5 ). However, these large-scale estimates are not suitable for identifying intraurban variability of surface PM 2.5 concentrations during wildfire events when individual plumes impact populated areas. We demonstrate a method for providing high-resolution (2.5 km) kernel-smoothed estimates of AOD over California during the 2008 northern California fires. The method uses high-resolution surface reflectance ratios of the 0.66 and 2.12 μm channels, a locally derived aerosol optical model characteristic of fresh wildfire plumes, and a relaxed cloud filter. Results show that the AOD derived for the 2008 northern California fires outperformed the standard product in matching observed aerosol optical thickness at three coastal Aerosol Robotic Network sites and routinely explained more than 50% of the variance in hourly surface PM 2.5 concentrations observed during the wildfires.

A computational fluid dynamics (CFD) model that evaluates mechanical mixing in a full-scale anaerobic digester was developed to investigate the influence of sewage sludge rheology on the steady-state digester performance. Mechanical mixing is provided through an impeller located in a draft tube. Use is made of the Multiple Reference Frame model to incorporate the rotating impeller. The non-Newtonian sludge is modeled using the Hershel-Bulkley law because of the yield stress present in the fluid. Water is also used as modeling fluid to illustrate the significant non-Newtonian effects of sewage sludge on mixing patterns. The variation of the sewage sludge rheology as a result of the digestion process is considered to determine its influence on both the required impeller torque and digester mixing patterns. It was found that when modeling the fluid with the Hershel-Bulkley law, the high slope of the sewage stress-strain curve at high shear rates causes significant viscous torque on the impeller surface. Although the overall fluid shear stress property is reduced during digestion, this slope is increased with sludge age, causing an increase in impeller torque for digested sludge due to the high strain rates caused by the pumping impeller. Consideration should be given to using the Bingham law to deal with high strain rates. The overall mixing flow patterns of the digested sludge do however improve slightly., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Rationale: The increasing demand to develop more efficient compounds to treat cognitive impairments in schizophrenia has led to the development of experimental model systems. One such model system combines the study of surrogate populations expressing high levels of schizotypy with oculomotor biomarkers., Objectives: We aimed (1) to replicate oculomotor deficits in a psychometric schizotypy sample and (2) to investigate whether the expected deficits can be remedied by compounds shown to ameliorate impairments in schizophrenia., Methods: In this randomized double-blind, placebo-controlled study 233 healthy participants performed prosaccade (PS), antisaccade (AS) and smooth pursuit eye movement (SPEM) tasks after being randomly assigned to one of four drug groups (nicotine, risperidone, amisulpride, placebo). Participants were classified into medium- and high-schizotypy groups based on their scores on the Schizotypal Personality Questionnaire (SPQ, Raine (Schizophr Bull 17:555-564, 1991))., Results: AS error rate showed a main effect of Drug (p < 0.01), with nicotine improving performance, and a Drug by Schizotypy interaction (p = 0.04), indicating higher error rates in medium schizotypes (p = 0.01) but not high schizotypes under risperidone compared to placebo. High schizotypes had higher error rates than medium schizotypes under placebo (p = 0.03). There was a main effect of Drug for saccadic peak velocity and SPEM velocity gain (both p ≤ 0.01) indicating impaired performance with risperidone., Conclusions: We replicate the observation of AS impairments in high schizotypy under placebo and show that nicotine enhances performance irrespective of group status. Caution should be exerted in applying this model as no beneficial effects of antipsychotics were seen in high schizotypes.

A number of compounds aimed at improving cognition in schizophrenia have failed to demonstrate efficacy in Phase 2 clinical trials. Translational studies using biomarkers in surrogate populations, such as schizotypy, could be used to assess the efficacy of novel compounds. In this study, we aimed to validate the sensitivity and inter-site reliability of cognitive biomarkers (working memory (N-back), spatial working memory (SWM) and verbal fluency (VF) tasks) to detect the schizotypy phenotype and its reversal by psychotropic drugs. Healthy volunteers scoring high or average on a schizotypal personality measure (122 in each group) were randomized to receive a single dose of risperidone, amisulpride, nicotine or placebo in a double-blind, between-subject design. We found evidence for a poorer performance on N-back and VF tasks in the high schizotypy group, replicating previous research. This effect was counteracted by amisulpride on N-back: it improved working memory in high schizotypy group but impaired the controls. A similar pattern was seen in SWM and VF. We interpret this finding in the light of the dopamine enhancing action of amisulpride when given in low doses. In contrast, risperidone impaired both groups and nicotine had a beneficial effect for the low baseline performers only. These effects were consistent across sites. These data demonstrates the utility of biomarkers in detecting the effect of schizotypy and its reversal by drugs that enhance dopamine and cholinergic function. Studies using similar design could help the early assessment of potential of compounds designed to improve cognition in schizophrenia., (Copyright © 2011 Elsevier B.V. All rights reserved.)

There are reasons for thinking that obsessive-compulsive disorder (OCD) and drug dependence, although conventionally distinct diagnostic categories, might share important cognitive and neurobiological substrates. We tested this hypothesis directly by comparing brain functional connectivity measures between patients with OCD, stimulant dependent individuals (SDIs; many of whom were non-dependent users of other recreational drugs) and healthy volunteers. We measured functional connectivity between each possible pair of 506 brain regional functional MRI time series representing low frequency (0.03-0.06 Hz) spontaneous brain hemodynamics in healthy volunteers (N=18), patients with OCD (N=18) and SDIs (N=18). We used permutation tests to identify i) brain regions where strength of connectivity was significantly different in both patient groups compared to healthy volunteers; and ii) brain regions and connections which had significantly different functional connectivity between patient groups. We found that functional connectivity of right inferior and superior orbitofrontal cortex (OFC) was abnormally reduced in both disorders. Whether diagnosed as OCD or SDI, patients with higher scores on measures of compulsive symptom severity showed greater reductions of right orbitofrontal connectivity. Functional connections specifically between OFC and dorsal medial pre-motor and cingulate cortex were attenuated in both patient groups. However, patients with OCD demonstrated more severe and extensive reductions of functional connectivity compared to SDIs. OCD and stimulant dependence are not identical at the level of brain functional systems but they have some important abnormalities in common compared with healthy volunteers. Orbitofrontal connectivity may serve as a human brain systems biomarker for compulsivity across diagnostic categories., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Background: Compulsivity is a hallmark of drug addiction and in animal models is measured by consecutive incorrect responses to a previously rewarded stimulus during reversal learning. The aim of this study was to measure behavioral and neural markers of compulsivity in stimulant-dependent individuals and to test whether these markers could be modulated by treatment with drugs targeting the dopamine system., Methods: In a randomized, double-blind, placebo-controlled, crossover design, stimulant-dependent individuals (SDIs; n = 18) and healthy volunteers (n = 18) received single doses of dopamine D(2/3) receptor antagonist (amisulpride, 400 mg) and agonist (pramipexole, 0.5 mg) drugs. To examine compulsivity and its dopaminergic modulation more generally, patients with obsessive-compulsive disorder (OCD; n = 18) were also included in the study., Results: SDIs made significantly more perseverative responses to the previously correct stimulus immediately following reversal, compared with both healthy volunteers and patients with OCD. Across all participants, the number of perseverative errors was negatively correlated with functional activation in right fronto-striato-parietal networks-in particular, the right caudate nucleus. In SDIs, perseveration-related caudate activation was abnormally reduced in the placebo condition, but the dopamine D(2/3) agonist pramipexole normalized both perseverative responding and related activation of the right caudate., Conclusions: Perseveration during reversal learning was associated specifically with stimulant dependence rather than with compulsive behaviors more generally. The beneficial effects of a dopamine agonist drug challenge on both behavior and associated brain activation in SDIs may indicate new avenues for pharmacologic treatment in stimulant dependence., (Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

In the pharmaceutical industry deciding whether to progress a compound to the next stage of development or choosing between compounds in a development portfolio is laden with risk. This is particularly true of compounds developed to treat CNS disorders. The use of pre-clinical models in CNS drug development is well established but these models often lack predictive validity and many compounds fail when they reach the target patient group. Bridging the gap between pre-clinical CNS models and patient studies, P1vital's objective is to develop human volunteer models that will enable rapid, accurate and reliable decision making about which compounds to progress into patient trials. The research strategy of P1vital and its academic research network is to focus on science that progresses the development of clinical efficacy models. As part of this strategy P1vital established a CNS Experimental Medicine Consortium with members from both academic research and the pharmaceutical industry. This consortium is unique in that experimental medicine models initially developed through academic research are selected for further validation in a process that is managed by the Pharma members of the P1vital CNS Experimental Medicine Consortium steering (PEM) committee. The P1vital consortium is very much a work in progress. However, since its inception in 2007 the consortium has successfully delivered results from five clinical studies in four therapeutic areas namely, anxiety, cognitive disorders, schizophrenia and depression., (2011. Published by Elsevier Inc.)

Rationale: Patients with obsessive compulsive disorder (OCD) demonstrate impaired cognition in some selected domains. Although serotoninergic dysfunction has been implicated in OCD, recent evidence suggests that dopamine may play a role as well., Objective: The aim of the study was to evaluate learning and working memory in OCD and to determine the effects of dopaminergic manipulations on these capacities., Methods: Visuospatial associative memory and spatial and verbal working memory were examined in 18 nondepressed patients with OCD and 18 matched healthy controls. The study further investigated whether acute administration of dopamine D2/D3 receptor agonist and antagonist would differentially modulate cognition in OCD. Each participant underwent the cognitive battery three times in a randomized double-blind, placebo-controlled crossover design., Results: Significant impairments in patients compared with controls were noted on the Cambridge Neuropsychological Test Automated Battery (CANTAB) paired associates learning (PAL) and a measure of sustained attention (rapid visual information processing, RVIP) that persisted across all sessions, with deficient strategy in the CANTAB spatial working memory task in the first session alone. Although the dopamine D2/D3 agonist, pramipexole, led to poorer performance on the PAL and RVIP tasks, no differential effects were noted between the two groups. No significant effects were noted for the D2/D3 antagonist, amisulpride., Conclusions: The results are consistent with a specific associative memory deficit in OCD that remained robust despite possible practice effects and compensatory strategies and point to abnormal medial temporal lobe involvement in OCD in addition to the previously implicated frontostriatal loops, with no clear evidence of D2 receptor mediation.

Context: There are no effective pharmacotherapies for stimulant dependence but there are many plausible targets for development of novel therapeutics. We hypothesized that dopamine-related targets are relevant for treatment of stimulant dependence, and there will likely be individual differences in response to dopaminergic challenges., Objective: To measure behavioral and brain functional markers of drug-related attentional bias in stimulant-dependent individuals studied repeatedly after short-term dosing with dopamine D(2)/D(3) receptor antagonist and agonist challenges., Design: Randomized, double-blind, placebo-controlled, parallel-groups, crossover design using pharmacological functional magnetic resonance imaging., Setting: Clinical research unit (GlaxoSmithKline) and local community in Cambridge, England., Participants: Stimulant-dependent individuals (n = 18) and healthy volunteers (n = 18)., Interventions: Amisulpride (400 mg), pramipexole dihydrochloride (0.5 mg), or placebo were administered in counterbalanced order at each of 3 repeated testing sessions., Main Outcome Measures: Attentional bias for stimulant-related words was measured during functional magnetic resonance imaging by a drug-word Stroop paradigm; trait impulsivity and compulsivity of dependence were assessed at baseline by questionnaire., Results: Drug users demonstrated significant attentional bias for drug-related words, which was correlated with greater activation of the left prefrontal and right cerebellar cortex. Attentional bias was greater in people with highly compulsive patterns of stimulant abuse; the effects of dopaminergic challenges on attentional interference and related frontocerebellar activation were different between high- and low-compulsivity subgroups., Conclusions: Greater attentional bias for and greater prefrontal activation by stimulant-related words constitute a candidate neurocognitive marker for dependence. Individual differences in compulsivity of stimulant dependence had significant effects on attentional bias, its brain functional representation, and its short-term modulation by dopaminergic challenges.

Irritability is an important symptom in patients with neuropsychiatric disorders. It is a major source of distress to patients and their carers and can lead to social and family dysfunction. Despite this, there has been little systematic research on irritability in psychiatry. The development of an instrument that captures the various components of irritability is a prerequisite to more detailed research in this area. The aim of this study was to design a scale to measure irritable mood and to explore its nature and subtypes. Following a review of the literature and examination of current theories in affective neuroscience, a new self-rating questionnaire was developed covering a range of subjective experiences, judgements and behaviours deemed to encompass the components of irritability. The items were rated along intensity and frequency dimensions. The questionnaire was administered to patients with affective disorders (n=22), Huntington's disease (n=23), Alzheimer's disease (n=19) and a control group (n=46). The new questionnaire shows good reliability and validity. Preliminary differences in irritability were identified between the diagnostic groups.

Background: Diabetic nephropathy is characterised by extracellular matrix (ECM) expansion, a key modulator of which is TGF-b1. Glucose-stimulated transcriptional activation of the TGF-b1 gene is an important component of the pathogenesis of nephropathy, following which latent TGF-b1 protein is synthesised. Matrix metalloproteinase 9 (MMP9) remodels the ECM and has been implicated in TGF-b1 activation. The ECM glycosaminoglycan hyaluronan (HA) influences TGF-b1 generation and can modulate its signal transduction activity; renal HA is synthesised by HA synthases HAS2 and HAS3., Methods: We report the first screening of the genes encoding HAS2 and HAS3 for sequence variants predisposing to nephropathy in UK type 2 diabetes patients, together with the MMP9 and TGF-b1 genes. Also for the first time, we used validated DNA pools to carry out association analyses of single nucleotide polymorphisms on nephropathic and non-nephropathic cohorts from a total of 199 type 2 diabetes patients, to increase the throughput and decrease the cost of genotype analysis., Results: None of the 23 single nucleotide polymorphisms analysed in DNA pools were found to be associated with diabetic nephropathy. However, genotyping of alleles at the MMP9 promoter microsatellite locus D20S838 in individual genomic DNA samples supported previous evidence of association between this locus and diabetic nephropathy., Conclusions: The use of DNA pooling technology increased the throughput and decreased the cost of our association analysis of nephropathy in our type 2 diabetes sample, which demonstrated sufficient sensitivity to support previous positive findings of association with a microsatellite in the MMP9 promoter region.