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Abstract The design of high‐entropy single‐atom catalysts (HESAC) with 5.2 times higher entropy compared to single‐atom catalysts (SAC) is proposed, by using four different metals (FeCoNiRu‐HESAC) for oxygen reduction reaction (ORR). Fe active sites with intermetallic distances of 6.1 Å exhibit a low ORR overpotential of 0.44 V, which originates from weakening the adsorption of OH intermediates. Based on density functional theory (DFT) findings, the FeCoNiRu‐HESAC with a nitrogen‐doped sample were synthesized. The atomic structures are confirmed with X‐ray photoelectron spectroscopy (XPS), X‐ray absorption (XAS), and scanning transmission electron microscopy (STEM). The predicted high catalytic activity is experimentally verified, finding that FeCoNiRu‐HESAC has overpotentials of 0.41 and 0.37 V with Tafel slopes of 101 and 210 mVdec−1 at the current density of 1 mA cm−2 and the kinetic current densities of 8.2 and 5.3 mA cm−2, respectively, in acidic and alkaline electrolytes. These results are comparable with Pt/C. The FeCoNiRu‐HESAC is used for Zinc–air battery applications with an open circuit potential of 1.39 V and power density of 0.16 W cm−2. Therefore, a strategy guided by DFT is provided for the rational design of HESAC which can be replaced with high‐cost Pt catalysts toward ORR and beyond.

OBJECTIVES/GOALS: Academic research centers often struggle to recruit and retain a diverse and competent clinical and translational science (CTS) workforce. Specifically, the clinical research professional (CRP) career pathway is not well known to undergraduate students and other individuals outside of academic medicine despite various potential career routes. METHODS/STUDY POPULATION: To address these workforce challenges, the CRP Task Force at the University of Cincinnati (UC) aims to train a competent and diverse CRP workforce through targeted educational programming in the UC undergraduate population. Using a six-step curriculum development process that included: 1) performing a needs assessment, 2) determining content, 3) writing goals and objectives, 4) selecting the educational strategies, 5) implementing the curriculum, and 6) evaluating the curriculum, we designed an undergraduate certificate program in CTS. RESULTS/ANTICIPATED RESULTS: The needs assessment included both internal and external data gathering to inform curriculum development and program decisions. Content was determined using the CRP Competency Framework 2.0, and program learning outcomes were written with both the competency framework and local workforce needs in mind. Educational strategies were selected based upon optimization of available resources and local expertise with an emphasis on interactive didactics complemented by experiential learning. Implementation is underway and evaluation will follow once students begin enrolling. DISCUSSION/SIGNIFICANCE: We anticipate an increase in numbers of well-qualified, diverse applicants who pursue CRP careers locally and regionally. In addition, we expect that the certificate program will build competency earlier in CRP staff, improving job satisfaction and retention as a result of a stronger foundation from which to build their professional skills.

OBJECTIVES/GOALS: Residents of environmental justice (EJ) communities experience significantly higher rates of negative health outcomes associated with poor air quality. Low-cost air sensors may supplement regulatory monitoring to better measure air pollution at local scales, but widespread application of this technology remains limited due to many challenges. METHODS/STUDY POPULATION: To address these obstacles, we designed a training program to equip community and academic research partners with the skills and knowledge to successfully apply low-cost sensors in community-engaged environmental health research. The R esearch Innovations using Sensor Technology in Environmental Justice Communities (RISE Communities) program was established through an NIEHS R25 award in 2022 and has three specific aims: 1) Foster community-academic partnerships through research education, training, and team development activities, 2) Provide technical training in the application of low-cost sensors for indoor, outdoor, and personal air monitoring in EJ communities, and 3) Establish a community of practice to address air quality in communities nationwide. RESULTS/ANTICIPATED RESULTS: We hosted our first cohort in August 2023, training five community-academic research teams in team collaboration, community-engaged research, and technical skills for collecting and analyzing data from PurpleAir sensors. Each team received 12 sensors to take to their home EJ communities to begin their projects. Community of practice development continues through interactive webinars and development of a web-based repository of training videos and discussion board posts. Evaluation data show high participant learning and satisfaction, with mean confidence scores improving on 6/8 metrics. Evaluation data also suggest several areas for improvement such as more time spent in teams for planning and additional opportunities for interaction within the cohort and with program instructors for problem-solving. DISCUSSION/SIGNIFICANCE: Effective training for team-based community-engaged research requires careful planning for team development and study implementation. Longitudinal training and support for the technical aspects of utilizing air sensors is also critical to team success. The RISE Communities program is actively recruiting for future training cohorts.

Introduction: Academic research centers often struggle to recruit and retain a well-trained and diverse clinical and translational science (CTS) workforce. In particular, the clinical research professional (CRP) career pathway is not well known to undergraduate students and other individuals outside of academic medicine despite being a potential career route. To address these workforce challenges, the CRP Task Force at the University of Cincinnati (UC) aims to train a competent and diverse CRP workforce through targeted educational programming in the UC undergraduate population.Methods: Using a six-step curriculum development process that included: 1) performing a needs assessment, 2) determining content, 3) writing goals and objectives, 4) selecting the educational strategies, 5) implementing the curriculum, and 6) evaluating the curriculum, we designed an undergraduate certificate program in CTS.Results: The needs assessment included both internal and external data gathering to inform curriculum development and program decisions. Content was determined using the Core Competency Framework for the Clinical Research Professional Version 3.1., and program learning outcomes were written with both the competency framework and local workforce needs in mind. Educational strategies were selected based on optimization of available resources and local expertise with an emphasis on interactive didactics complemented by experiential learning. Implementation is underway and evaluation will follow once students begin enrolling.Discussion: By educating an undergraduate student population about CTS methods and career opportunities, we anticipate increased numbers of well-qualified, diverse applicants who pursue CRP careers locally and regionally.

Background: Cystic fibrosis (CF) is a genetic disease but is greatly impacted by non-genetic (social/environmental and stochastic) influences. Some people with CF experience rapid decline, a precipitous drop in lung function relative to patient- and/or center-level norms. Those who experience rapid decline in early adulthood, compared to adolescence, typically exhibit less severe clinical disease but greater loss of lung function. The extent to which timing and degree of rapid decline are informed by social and environmental determinants of health (geomarkers) is unknown. Methods: A longitudinal cohort study was performed (24,228 patients, aged 6–21 years) using the U.S. CF Foundation Patient Registry. Geomarkers at the ZIP Code Tabulation Area level measured air pollution/respiratory hazards, greenspace, crime, and socioeconomic deprivation. A composite score quantifying social-environmental adversity was created and used in covariate-adjusted functional principal component analysis, which was applied to cluster longitudinal lung function trajectories. Results: Social-environmental phenotyping yielded three primary phenotypes that corresponded to early, middle, and late timing of peak decline in lung function over age. Geographic differences were related to distinct cultural and socioeconomic regions. Extent of peak decline, estimated as forced expiratory volume in 1 s of % predicted/year, ranged from 2.8 to 4.1 % predicted/year depending on social-environmental adversity. Middle decliners with increased social-environmental adversity experienced rapid decline 14.2 months earlier than their counterparts with lower social-environmental adversity, while timing was similar within other phenotypes. Early and middle decliners experienced mortality peaks during early adolescence and adulthood, respectively. Conclusion: While early decliners had the most severe CF lung disease, middle and late decliners lost more lung function. Higher social-environmental adversity associated with increased risk of rapid decline and mortality during young adulthood among middle decliners. This sub-phenotype may benefit from enhanced lung-function monitoring and personalized secondary environmental health interventions to mitigate chemical and non-chemical stressors.

Abstract Objectives The Charlson comorbidity index (CCI), the most ubiquitous comorbid risk score, predicts one-year mortality among hospitalized patients and provides a single aggregate measure of patient comorbidity. The Quan adaptation of the CCI revised the CCI coding algorithm for applications to administrative claims data using the International Classification of Diseases (ICD). The purpose of the current study is to adapt and validate a coding algorithm for the CCI using the SNOMED CT standardized vocabulary, one of the most commonly used vocabularies for data collection in healthcare databases in the U.S. Methods The SNOMED CT coding algorithm for the CCI was adapted through the direct translation of the Quan coding algorithms followed by manual curation by clinical experts. The performance of the SNOMED CT and Quan coding algorithms were compared in the context of a retrospective cohort study of inpatient visits occurring during the calendar years of 2013 and 2018 contained in two U.S. administrative claims databases. Differences in the CCI or frequency of individual comorbid conditions were assessed using standardized mean differences (SMD). Performance in predicting one-year mortality among hospitalized patients was measured based on the c-statistic of logistic regression models. Results For each database and calendar year combination, no significant differences in the CCI or frequency of individual comorbid conditions were observed between vocabularies (SMD ≤ 0.10). Specifically, the difference in CCI measured using the SNOMED CT vs. Quan coding algorithms was highest in MDCD in 2013 (3.75 vs. 3.6; SMD = 0.03) and lowest in DOD in 2018 (3.93 vs. 3.86; SMD = 0.02). Similarly, as indicated by the c-statistic, there was no evidence of a difference in the performance between coding algorithms in predicting one-year mortality (SNOMED CT vs. Quan coding algorithms, range: 0.725–0.789 vs. 0.723–0.787, respectively). A total of 700 of 5,348 (13.1%) ICD code mappings were inconsistent between coding algorithms. The most common cause of discrepant codes was multiple ICD codes mapping to a SNOMED CT code (n = 560) of which 213 were deemed clinically relevant thereby leading to information gain. Conclusion The current study repurposed an important tool for conducting observational research to use the SNOMED CT standardized vocabulary.

Background: Characterization studies of COVID-19 patients with chronic obstructive pulmonary disease (COPD) are limited in size and scope. The aim of the study is to provide a large-scale characterization of COVID-19 patients with COPD. Methods: We included thirteen databases contributing data from January-June 2020 from North America (US), Europe and Asia. We defined two cohorts of patients with COVID-19 namely a ‘diagnosed’ and ‘hospitalized’ cohort. We followed patients from COVID-19 index date to 30 days or death. We performed descriptive analysis and reported the frequency of characteristics and outcomes among COPD patients with COVID-19. Results: The study included 934,778 patients in the diagnosed COVID-19 cohort and 177,201 in the hospitalized COVID-19 cohort. Observed COPD prevalence in the diagnosed cohort ranged from 3.8% (95%CI 3.5-4.1%) in French data to 22.7% (95%CI 22.4-23.0) in US data, and from 1.9% (95%CI 1.6-2.2) in South Korean to 44.0% (95%CI 43.1-45.0) in US data, in the hospitalized cohorts. COPD patients in the hospitalized cohort had greater comorbidity than those in the diagnosed cohort, including hypertension, heart disease, diabetes and obesity. Mortality was higher in COPD patients in the hospitalized cohort and ranged from 7.6% (95%CI 6.9-8.4) to 32.2% (95%CI 28.0-36.7) across databases. ARDS, acute renal failure, cardiac arrhythmia and sepsis were the most common outcomes among hospitalized COPD patients. Conclusion: COPD patients with COVID-19 have high levels of COVID-19-associated comorbidities and poor COVID-19 outcomes. Further research is required to identify patients with COPD at high risk of worse outcomes.

Two-dimensional (2D) hexagonal boron nitride (hBN), due to its extraordinary thermal, chemical, and optical properties, has arisen as an enticing material for the research community to explore for various applications, including the use of site defects in hBN as single photon emitters (SPEs). In this review, we systematically summarize recent advanced strategies towards the controllable synthesis of 2D hBN using chemical vapor deposition, towards a full control of the domain size, orientation, morphology, layer number, and stacking order, etc. Moreover, we review the underlying mechanisms for single photon emission (SPE) in hBN and methods to selectively generate and tune the SPEs. Defects (e.g., carbon substituted defects) are discussed for the potential use as emission sites. We finally give an outlook of future challenges and opportunities on desirable hBN synthesis and further investigation of SPEs in hBN, targeting to utilize hBN as single photon emitters in an industrial scale.

Background: Routinely collected healthcare data such as administrative claims and electronic health records (EHR) can complement clinical trials and spontaneous reports to detect previously unknown risks of vaccines, but uncertainty remains about the behavior of alternative epidemiologic designs to detect and declare a true risk early.Methods: Using three claims and one EHR database, we evaluate several variants of the case-control, comparative cohort, historical comparator, and self-controlled designs against historical vaccinations using real negative control outcomes (outcomes with no evidence to suggest that they could be caused by the vaccines) and simulated positive control outcomes.Results: Most methods show large type 1 error, often identifying false positive signals. The cohort method appears either positively or negatively biased, depending on the choice of comparator index date. Empirical calibration using effect-size estimates for negative control outcomes can bring type 1 error closer to nominal, often at the cost of increasing type 2 error. After calibration, the self-controlled case series (SCCS) design most rapidly detects small true effect sizes, while the historical comparator performs well for strong effects.Conclusion: When applying any method for vaccine safety surveillance we recommend considering the potential for systematic error, especially due to confounding, which for many designs appears to be substantial. Adjusting for age and sex alone is likely not sufficient to address differences between vaccinated and unvaccinated, and for the cohort method the choice of index date is important for the comparability of the groups. Analysis of negative control outcomes allows both quantification of the systematic error and, if desired, subsequent empirical calibration to restore type 1 error to its nominal value. In order to detect weaker signals, one may have to accept a higher type 1 error.

Post-marketing vaccine safety surveillance aims to detect adverse events following immunization in a population. Whether certain methods of surveillance are more precise and unbiased in generating safety signals is unclear. Here, we synthesized information from existing literature to provide an overview of the strengths, weaknesses, and clinical applications of epidemiologic and analytical methods used in vaccine monitoring, focusing on cohort, case-control and self-controlled designs. These designs are proposed to be evaluated in the EUMAEUS (Evaluating Use of Methods for Adverse Event Under Surveillance–for vaccines) study because of their widespread use and potential utility. Over the past decades, there have been an increasing number of epidemiological study designs used for vaccine safety surveillance. While traditional cohort and case-control study designs remain widely used, newer, novel designs such as the self-controlled case series and self-controlled risk intervals have been developed. Each study design comes with its strengths and limitations, and the most appropriate study design will depend on availability of resources, access to records, number and distribution of cases, and availability of population coverage data. Several assumptions have to be made while using the various study designs, and while the goal is to mitigate any biases, violations of these assumptions are often still present to varying degrees. In our review, we discussed some of the potential biases (i.e., selection bias, misclassification bias and confounding bias), and ways to mitigate them. While the types of epidemiological study designs are well established, a comprehensive comparison of the analytical aspects (including method evaluation and performance metrics) of these study designs are relatively less well studied. We summarized the literature, reporting on two simulation studies, which compared the detection time, empirical power, error rate and risk estimate bias across the above-mentioned study designs. While these simulation studies provided insights on the analytic performance of each of the study designs, its applicability to real-world data remains unclear. To bridge that gap, we provided the rationale of the EUMAEUS study, with a brief description of the study design; and how the use of real-world multi-database networks can provide insights into better methods evaluation and vaccine safety surveillance.

Testis-restricted melanoma antigen (MAGE) proteins function as substrate adapters for E3 ubiquitin ligases. Biochemical and structural analyses of MAGE-A11 provide insight into the substrate binding mode of MAGE proteins and enable discovery of potent, cytotoxic inhibitors of MAGE-A11:substrate interaction.

Detailed knowledge of the characteristics of COVID-19 patients helps with public health planning. Here, the authors use routinely-collected data from seven databases in three countries to describe the characteristics of >30,000 patients admitted with COVID-19 and compare them with those admitted for influenza in previous years.

Abstract Randomized controlled trials (RCTs) are regarded as the most reputable source of evidence. In some studies, factors beyond the intervention itself may contribute to the measured effect, an occurrence known as heterogeneity of treatment effect (HTE). If the RCT population differs from the real-world population on factors that induce HTE, the trials effect will not replicate. The RCTs eligibility criteria should identify the sub-population in which its evidence will replicate. However, the extent to which the eligibility criteria identify the appropriate population is unknown, which raises concerns for generalizability. We compared reported data from RCTs with real-world data from the electronic health records of a large, academic medical center that was curated according to RCT eligibility criteria. Our results show fundamental differences between the RCT population and our observational cohorts, which suggests that eligibility criteria may be insufficient for identifying the applicable real-world population in which RCT evidence will replicate.

An increasing amount of evidence suggests ultrafine particles (UFPs) are linked to adverse health effects, especially in those with chronic conditions such as asthma, due to their small size and physicochemical characteristics. Toxicological and experimental studies have demonstrated these properties, and the mechanisms by which they deposit and translocate in the body result in increased toxicity in comparison to other air pollutants. However, current epidemiological literature is limited due to exposure misclassification and thus identifying health outcomes associated with UFPs. The objective of this study was to investigate the association between weekly personal UFP exposure with lung function and respiratory symptoms in 117 asthmatic and non-asthmatic adolescents between 13 and 17 years of age in the Cincinnati area. Between 2017 and 2019, participants collected weekly UFP concentrations by sampling for 3 h a day in their home, school, and during transit. In addition, pulmonary function was evaluated at the end of the sampling week, and respiratory symptoms were logged on a mobile phone application. Multivariable linear regression and zero-inflated Poisson (ZIP) models were used to estimate the association between personal UFP and respiratory outcomes. The average median weekly UFP exposure of all participants was 4340 particles/cm3 (p/cc). Results of fully adjusted regression models revealed a negative association between UFPs and percent predicted forced expiratory volume/forced vital capacity ratio (%FEV1/FVC) (β:-0.03, 95% CI [-0.07, 0.02]). Prediction models estimated an association between UFPs and respiratory symptoms, which was greater in asthmatics compared to non-asthmatics. Our results indicate an interaction between asthma status and the likelihood of experiencing respiratory symptoms when exposed to UFPs, indicating an exacerbation of this chronic condition. More research is needed to determine the magnitude of the role UFPs play on respiratory health.

Abstract Background Single birth cohort studies have been the basis for many discoveries about early life risk factors for childhood asthma but are limited in scope by sample size and characteristics of the local environment and population. The Children’s Respiratory and Environmental Workgroup (CREW) was established to integrate multiple established asthma birth cohorts and to investigate asthma phenotypes and associated causal pathways (endotypes), focusing on how they are influenced by interactions between genetics, lifestyle, and environmental exposures during the prenatal period and early childhood. Methods and results CREW is funded by the NIH Environmental influences on Child Health Outcomes (ECHO) program, and consists of 12 individual cohorts and three additional scientific centers. The CREW study population is diverse in terms of race, ethnicity, geographical distribution, and year of recruitment. We hypothesize that there are phenotypes in childhood asthma that differ based on clinical characteristics and underlying molecular mechanisms. Furthermore, we propose that asthma endotypes and their defining biomarkers can be identified based on personal and early life environmental risk factors. CREW has three phases: 1) to pool and harmonize existing data from each cohort, 2) to collect new data using standardized procedures, and 3) to enroll new families during the prenatal period to supplement and enrich extant data and enable unified systems approaches for identifying asthma phenotypes and endotypes. Conclusions The overall goal of CREW program is to develop a better understanding of how early life environmental exposures and host factors interact to promote the development of specific asthma endotypes.

Summary: To date, phase separation studies have largely been limited to in vitro assays using non-native conditions and aggregation-prone recombinant proteins that are often difficult to purify. This protocol describes the determination of relative protein concentration thresholds for phase separation through fluorescent imaging of GFP-tagged proteins in cells. The commercial availability of various plasmids and antibodies, as well as advances in gene editing, allow this procedure to be modified for the study of various phase-separating proteins in their relevant contexts.For complete details on the use and execution of this protocol, please refer to Lee et al. (2020).

This study develops a comprehensive method to assess seasonal influences on a longitudinal marker and compare estimates between cohorts. The method extends existing approaches by (i) combining a sine-cosine model of seasonality with a specialized covariance function for modeling longitudinal correlation; (ii) performing mediation analysis on a seasonality model. An example dataset and R code are provided. The bundle of methods is referred to as seasonality, mediation and comparison (SMAC). The case study described utilizes lung function as the marker observed on a cystic fibrosis cohort but SMAC can be used to evaluate other markers and in other disease contexts. Key aspects of customization are as follows. • This study introduces a novel seasonality model to fit trajectories of lung function decline and demonstrates how to compare this model to a conventional model in this context. • Steps required for mediation analyses in the seasonality model are shown. • The necessary calculations to compare seasonality models between cohorts, based on estimation coefficients, are derived in the study.

Prader-Willi syndrome (PWS) is a developmental disorder caused by loss of maternally imprinted genes on 15q11-q13, including melanoma antigen gene family member L2 (MAGEL2). The clinical phenotypes of PWS suggest impaired hypothalamic neuroendocrine function; however, the exact cellular defects are unknown. Here, we report deficits in secretory granule (SG) abundance and bioactive neuropeptide production upon loss of MAGEL2 in humans and mice. Unbiased proteomic analysis of Magel2pΔ/m+ mice revealed a reduction in components of SG in the hypothalamus that was confirmed in 2 PWS patient–derived neuronal cell models. Mechanistically, we show that proper endosomal trafficking by the MAGEL2-regulated WASH complex is required to prevent aberrant lysosomal degradation of SG proteins and reduction of mature SG abundance. Importantly, loss of MAGEL2 in mice, NGN2-induced neurons, and human patients led to reduced neuropeptide production. Thus, MAGEL2 plays an important role in hypothalamic neuroendocrine function, and cellular defects in this pathway may contribute to PWS disease etiology. Moreover, these findings suggest unanticipated approaches for therapeutic intervention.

Early life exposure to air pollution poses a significant risk to brain development from direct exposure to toxicants or via indirect mechanisms involving the circulatory, pulmonary or gastrointestinal systems. In children, exposure to traffic related air pollution has been associated with adverse effects on cognitive, behavioral and psychomotor development. We aimed to determine whether childhood exposure to traffic related air pollution is associated with regional differences in brain volume and cortical thickness among children enrolled in a longitudinal cohort study of traffic related air pollution and child health. We used magnetic resonance imaging to obtain anatomical brain images from a nested subset of 12 year old participants characterized with either high or low levels of traffic related air pollution exposure during their first year of life. We employed voxel-based morphometry to examine group differences in regional brain volume, and with separate analyses, changes in cortical thickness. Smaller regional gray matter volumes were determined in the left pre- and post-central gyri, the cerebellum, and inferior parietal lobe of participants in the high traffic related air pollution exposure group relative to participants with low exposure. Reduced cortical thickness was observed in participants with high exposure relative to those with low exposure, primarily in sensorimotor regions of the brain including the pre- and post-central gyri and the paracentral lobule, but also within the frontal and limbic regions. These results suggest that significant childhood exposure to traffic related air pollution is associated with structural alterations in brain.

Abstract Introduction In the EASEL study of patients with type 2 diabetes and high cardiovascular risk, initiation of sodium glucose co‐transporter 2 inhibitors (SGLT2i) was associated with lower risk of cardiovascular events and mortality and higher risk of below‐knee lower extremity (BKLE) amputation versus non‐SGLT2i therapies. This analysis further examined risk of cardiovascular events, cardiovascular and noncardiovascular death and BKLE amputation with the SGLT2i canagliflozin versus non‐SGLT2i. Methods New user cohorts were constructed from Department of Defense Military Health System patients initiating canagliflozin or non‐SGLT2i (4/1/2013‐12/31/2016). Propensity score matching (1:1) controlled for imbalances in baseline covariates. Incidence rates, hazard ratios and 95% confidence intervals for time to first composite outcome of all‐cause mortality (ACM) and hospitalization for heart failure (HHF), composite major adverse cardiovascular events (MACE) and individual components were evaluated using conditional Cox models. The National Death Index was used to differentiate cardiovascular from noncardiovascular death. The exploratory safety end‐point was BKLE amputation. Results After propensity matching, 15 394 patients with well‐balanced baseline covariates were followed for a median of 2.03 years (intent‐to‐treat). Canagliflozin showed significant benefit for ACM and HHF (P

Abstract Background This article presents a detailed idiographic analysis of Dialectical Behaviour Therapy (DBT) clinicians’ experiences of team consultation meetings. DBT is an evidence-based psychological intervention with a demonstrated efficacy in the treatment of borderline personality disorder (BPD). Team consultation meetings encompass one of the primary components involved in this treatment model; where DBT clinicians regularly meet to discuss client work and enhance further learning. The present study’s aim was to assess what are DBT clinicians’ experiences of the consultation meeting component and whether it is useful or not. Method Semi-structured interviews were completed with 11 DBT clinicians (nine females, two males) from three different consultation teams. The research project utilised an interpretative phenomenological analysis (IPA) framework. Audio-recorded interview data was analysed using this framework. Results Four superordinate themes emerged from the interview data, which included ten subordinate themes. The superordinate themes focused on: (1) the acquisition of DBT technical knowledge and other MDT related expertise (2) participants’ emotional experiences of DBT and consultation meetings, and how this can evolve over time (3) the underlying processes that occur in the consultation team including the development of a team bond and the impact of membership changes and (4) the largely consistent and reliable nature of consultation meetings and how they help maintain clinician motivation. Conclusions Team consultation meetings were found to be supportive; playing an important role in maintaining clinician motivation through the availability of team support, opportunities to reflect and learn, and assistance in regulating emotions. Challenges arose in relation to team membership changes and acclimatisation to the type of feedback utilised in team consultation. The study’s implications for practise are considered.

Abstract Background Mammographic breast density is a well-established strong risk factor for breast cancer. The environmental contributors to geographic variation in breast density in urban and rural areas are poorly understood. We examined the association between breast density and exposure to ambient air pollutants (particulate matter

C-terminal α-amidation of peptides is an important event in the course of pro-hormone and neuropeptide processing; it is a modification that contributes to the biological activity and stability of about 25 peptides in neural and endocrine systems. This laboratory has shown that bovine growth hormone (bGH) also has a catalytic function, i.e. peptidylglycine monooxygenase activity, which is the first step in the alpha-amidation of glycine-extended peptides. We report here that the peptidylglycine monooxygenase activity of monomeric bovine pituitary GH, in the presence of ascorbate, is stimulated by combination with oligomeric forms of bGH one of which is a hetero-oligomer with metallothionein. Three species of recombinant monomeric GH (bovine, human and chicken) also catalyze this monooxygenase reaction. Tetrahydrobiopterin also functions as a reductant - with a significantly greater turnover than achieved with ascorbate. These findings clarify the role of GH in peptidylglycine monooxygenation and provide an explanation for earlier observations that peptide amidation is not totally obliterated in the absence of ascorbate, in cultured pituitary cells or in vivo. The evolution of bifunctional GH is also discussed, as are some of the significances of the peptidylglycine monooxygenase activity of human GH in relation to peptides such as oxytocin, glucagon-like peptide-1 and peptide PYY.

Background: Acquired dysfunctional immunity in cirrhosis predisposes patients to frequent bacterial infections, especially spontaneous bacterial peritonitis (SBP), leading to systemic inflammation that is associated with poor outcome. But systemic inflammation can also be found in the absence of a confirmed infection. Detection of bacterial DNA has been investigated as a marker of SBP and as a predictor of prognosis. Data is, however, contradictory. Here we investigated whether levels of IL-6 and IL-8 putatively produced by myeloid cells in ascites are associated with systemic inflammation and whether inflammation depends on the presence of specific bacterial DNA.Methods and Materials: We enrolled 33 patients with decompensated liver cirrhosis from whom we collected paired samples of blood and ascites. IL-6 and IL-8 were measured in serum samples of all patients using ELISA. In a subset of 10 representative patients, bacterial DNA was extracted from ascites and whole blood, followed by 16S rRNA gene amplicon sequencing.Results: There were significantly higher levels of IL-6 in ascites fluid compared to blood samples in all patients. Interestingly, IL-6 levels in blood correlated tightly with disease severity and surrogates of systemic inflammation, while IL-6 levels in ascites did not. Moreover, patients with higher blood CRP levels showed greater SBP prevalence compared to patients with lower levels, despite similar positive culture results. Bacterial richness was also significantly higher in ascites compared to the corresponding patient blood. We identified differences in microbial composition and diversity between ascites and blood, but no tight relationship with surrogates of systemic inflammation could be observed.Discussion: In decompensated cirrhosis, markers of systemic inflammation and microbiota composition seem to be dysregulated in ascites and blood. While a relationship between systemic inflammation and microbiota composition seems to exist in blood, this is not the case for ascites in our hands. These data may suggest compartmentalization of the immune response and interaction of the latter with the microbiota especially in the blood compartment.

ObjectivesA distributed research network (DRN) has the advantages of improved statistical power, and it can reveal more significant relationships by increasing sample size. However, differences in data structure constitute a major barrier to integrating data among DRN partners. We describe our experience converting Electronic Health Records (EHR) to the Observational Health Data Sciences and Informatics (OHDSI) Common Data Model (CDM).MethodsWe transformed the EHR of a hospital into Observational Medical Outcomes Partnership (OMOP) CDM ver. 4.0 used in OHDSI. All EHR codes were mapped and converted into the standard vocabulary of the CDM. All data required by the CDM were extracted, transformed, and loaded (ETL) into the CDM structure. To validate and improve the quality of the transformed dataset, the open-source data characterization program ACHILLES was run on the converted data.ResultsPatient, drug, condition, procedure, and visit data from 2.07 million patients who visited the subject hospital from July 1994 to November 2014 were transformed into the CDM. The transformed dataset was named the AUSOM. ACHILLES revealed 36 errors and 13 warnings in the AUSOM. We reviewed and corrected 28 errors. The summarized results of the AUSOM processed with ACHILLES are available at http://ami.ajou.ac.kr:8080/.ConclusionsWe successfully converted our EHRs to a CDM and were able to participate as a data partner in an international DRN. Converting local records in this manner will provide various opportunities for researchers and data holders.

This study evaluated the impact of a theory-driven cognitive attention training program, "Keeping Score!," in improving students' sustained attention capacity. Training was based on sustained updating. Students engaged this process by mentally keeping score during an interactive game of table tennis without external aids. Students (9-11 years) were assigned to a 6-week training program (n = 18) or an active control (n = 18). Assessments of sustained attention/working memory and parent ratings of executive function were completed at pretraining, post-training, and 6-week follow-up. We found no evidence to support the efficacy of training (i.e., there was no statistically significant time × group interaction effects for any outcome). Overall, these findings add to the mixed body of literature supporting the efficacy of cognitive attention training for improving children's attentional capacity. One possibility for why the training program was unsuccessful is perhaps that cognitive attention training may not be sufficient for enhancing sustained attention.

BackgroundThe number of patients with diabetes is increasing particularly in Asia-Pacific region. Many of them are treated with antidiabetics. As the basis of the studies on the benefit and harm of antidiabetic drugs in the region, the information on patterns of market penetration of new classes of antidiabetic medications is important in providing context for subsequent research and analyzing and interpreting results.MethodsWe compared penetration patterns of dipeptidyl peptidase-4 (DPP-4) inhibitors in Taiwan, Hong Kong, Japan, and the United States. We used the Taiwan National Health Insurance Research Database, a random sample of the Hong Kong Clinical Data Analysis and Reporting System, the Japan Medical Data Center database, and a 5% random sample of the US Medicare database converted to the Observational Medical Outcomes Partnership's Common Data Model to identify new users of oral antidiabetic medications. We standardized prevalence and incidence rates of medication use by age and sex to those in the 2010 Taiwanese population. We compared age, sex, comorbid conditions, and concurrent medications between new users of DPP-4 inhibitors and biguanides.ResultsUse of DPP-4 inhibitors 1 year after market entry was highest in Japan and lowest in Hong Kong. New users had more heart failure, hyperlipidemia, and renal failure than biguanide users in Taiwan, Hong Kong, and the United States while the proportions were similar in Japan. In a country with low penetration of DPP-4 inhibitors (eg, Hong Kong), users had diabetes with multiple comorbid conditions compared with biguanidine users. In a country with high penetration (eg, Japan), the proportion of users with comorbid conditions was similar to that of biguanide users.ConclusionsWe observed a marked difference of the penetration patterns of newly marketed antidiabetics in different countries in Asia. Those results will provide the basic information useful in the future studies.

Administrative claims and electronic health records are valuable resources for evaluating pharmaceutical effects during pregnancy. However, direct measures of gestational age are generally not available. Establishing a reliable approach to infer the duration and outcome of a pregnancy could improve pharmacovigilance activities. We developed and applied an algorithm to define pregnancy episodes in four observational databases: three US-based claims databases: Truven MarketScan® Commercial Claims and Encounters (CCAE), Truven MarketScan® Multi-state Medicaid (MDCD), and the Optum ClinFormatics® (Optum) database and one non-US database, the United Kingdom (UK) based Clinical Practice Research Datalink (CPRD). Pregnancy outcomes were classified as live births, stillbirths, abortions and ectopic pregnancies. Start dates were estimated using a derived hierarchy of available pregnancy markers, including records such as last menstrual period and nuchal ultrasound dates. Validation included clinical adjudication of 700 electronic Optum and CPRD pregnancy episode profiles to assess the operating characteristics of the algorithm, and a comparison of the algorithm's Optum pregnancy start estimates to starts based on dates of assisted conception procedures. Distributions of pregnancy outcome types were similar across all four data sources and pregnancy episode lengths found were as expected for all outcomes, excepting term lengths in episodes that used amenorrhea and urine pregnancy tests for start estimation. Validation survey results found highest agreement between reviewer chosen and algorithm operating characteristics for questions assessing pregnancy status and accuracy of outcome category with 99-100% agreement for Optum and CPRD. Outcome date agreement within seven days in either direction ranged from 95-100%, while start date agreement within seven days in either direction ranged from 90-97%. In Optum validation sensitivity analysis, a total of 73% of algorithm estimated starts for live births were in agreement with fertility procedure estimated starts within two weeks in either direction; ectopic pregnancy 77%, stillbirth 47%, and abortion 36%. An algorithm to infer live birth and ectopic pregnancy episodes and outcomes can be applied to multiple observational databases with acceptable accuracy for further epidemiologic research. Less accuracy was found for start date estimations in stillbirth and abortion outcomes in our sensitivity analysis, which may be expected given the nature of the outcomes.

We report on the development of an electrochemical probe for the trace analysis of 2,4,6-trinitrotoluene (TNT) in soil samples. The probe is a combination of graphite electrodes, filter paper, with ethylene glycol and choline chloride as the solvent/electrolyte. Square wave chromatovoltammograms show the probes have a sensitivity for TNT of 0.75 nA/ng and a limit of detection of 100 ng. In addition, by taking advantage of the inherent paper chromatography step, TNT can be separated in both time and cathodic peak potential from 4-amino-dinitrotolene co-spotted on the probe or in soil samples with the presence of methyl parathion as a possible interferent.

Exhaled nitric oxide (eNO) is increasingly used as a non-invasive measure of airway inflammation. Despite this, little information exists regarding the potential effects of indoor microbial components on eNO. We determined the influence of microbial contaminants in house dust and other indoor environmental characteristics on eNO levels in seven-year-olds with and without a physician-diagnosis of asthma. The study included 158 children recruited from a birth cohort study, and 32 were physician-diagnosed as asthmatic. The relationship between eNO levels and exposures to home dust streptomycetes, endotoxin, and molds was investigated. Streptomycetes and endotoxin were analyzed both as loads and concentrations in separate models. Dog, cat, and dust mite allergens also were evaluated. In the multivariate exposure models, high streptomycetes loads and concentrations were significantly associated with a decrease in eNO levels in asthmatic (p

Pre-emptive pharmacogenomic (PGx) testing of a panel of genes may be easier to implement and more cost-effective than reactive pharmacogenomic testing if a sufficient number of medications are covered by a single test and future medication exposure can be anticipated. We analysed the incidence of exposure of individual patients in the United States to multiple drugs for which pharmacogenomic guidelines are available (PGx drugs) within a selected four-year period (2009-2012) in order to identify and quantify the incidence of pharmacotherapy in a nation-wide patient population that could be impacted by pre-emptive PGx testing based on currently available clinical guidelines. In total, 73 024 095 patient records from private insurance, Medicare Supplemental and Medicaid were included. Patients enrolled in Medicare Supplemental age > = 65 or Medicaid age 40-64 had the highest incidence of PGx drug use, with approximately half of the patients receiving at least one PGx drug during the 4 year period and one fourth to one third of patients receiving two or more PGx drugs. These data suggest that exposure to multiple PGx drugs is common and that it may be beneficial to implement wide-scale pre-emptive genomic testing. Future work should therefore concentrate on investigating the cost-effectiveness of multiplexed pre-emptive testing strategies.

From 1997 to 2000, Mycobacterium tuberculosis was diagnosed in two Asian elephants (Elephas maximus), three Rocky Mountain goats (Oreamnos americanus), and one black rhinoceros (Diceros bicornis) in the Los Angeles Zoo. DNA fingerprint patterns suggested recent transmission. An investigation found no active cases of tuberculosis in humans; however, tuberculin skin-test conversions in humans were associated with training elephants and attending an elephant necropsy.

The expansion and impact of the Wari polity across the Andes has been heavily debated by scholars over the past two decades. We use radiocarbon dates, Bayesian statistics, and contextual data from several Andean regions to review the chronology for Wari expansion, political reorganization, and impact on local settlements. We recognize that Wari political and economic influence will vary in space and time and present a model that addresses how influential moments (expansion, reorganization, collapse) in Wari's trajectory may or may not have had broader impacts across the landscapes of its peer polities. Our model, while not completely comprehensive, draws on both Wari's presence in the north highlands and in the south, where scholars have argued for distinct trajectories and character of Wari influence. It also examines data from local communities in these same regions contemporary with identified Wari settlements, but perhaps without outward indicators of Wari hegemony, to evaluate broader patterns in Middle Horizon settlement through the latter half of the first millennium CE. [ABSTRACT FROM AUTHOR]