The scale of population structure in Arabidopsis thaliana

The population structure of an organism reflects its evolutionary history and influences its evolutionary trajectory. It constrains the combination of genetic diversity and reveals patterns of past gene flow. Understanding it is a prerequisite for detecting genomic regions under selection, predicting the effect of population disturbances, or modeling gene flow. This paper examines the detailed global population structure of Arabidopsis thaliana. Using a set of 5,707 plants collected from around the globe and genotyped at 149 SNPs, we show that while A. thaliana as a species self-fertilizes 97% of the time, there is considerable variation among local groups. This level of outcrossing greatly limits observed heterozygosity but is sufficient to generate considerable local haplotypic diversity. We also find that in its native Eurasian range A. thaliana exhibits continuous isolation by distance at every geographic scale without natural breaks corresponding to classical notions of populations. By contrast, in North America, where it exists as an exotic species, A. thaliana exhibits little or no population structure at a continental scale but local isolation by distance that extends hundreds of km. This suggests a pattern for the development of isolation by distance that can establish itself shortly after an organism fills a new habitat range. It also raises questions about the general applicability of many standard population genetics models. Any model based on discrete clusters of interchangeable individuals will be an uneasy fit to organisms like A. thaliana which exhibit continuous isolation by distance on many scales

Development of an Instrument to Assess Influences on Family Physician Opioid Therapy Prescribing

Rationale: Prescription drug abuse and misuse (PDA/M) is a significant problem in Central Appalachia and continues to grow. Since 2000, Tennessee has seen a 250% increase in prescription overdose deaths. Nationally, most prescription painkillers are prescribed by primary care doctors and dentists, rather than specialists. Objective: To develop and test a survey instrument aimed at understanding family physician knowledge, attitudes, and beliefs about opioid therapy prescribing. Design: Survey development. Setting: Survey questions were developed based on results of five focus groups held in primary care clinics in Northeast Tennessee and Southwest Virginia. Surveys were validated and tested by faculty and residents in three family medicine residency clinics in Northeast Tennessee. Participants: Survey questions were face validated for clarity and relevance by family physician attendings and third year residents (N=29). All faculty attendings and residents (N≈85) at the same family medicine residency clinics will be invited to complete the survey for psychometric testing. Main and Secondary Outcome Measures: Survey questions have been face validated for clarity and relevance. Data from the psychometric testing phase will be analyzed for internal consistency and inter-item correlations. Exploratory factor analysis will be used to identify underlying constructs. Results: Based on the results of the focus groups and physician expertise, a 51-item instrument was developed. Following face validation, wording was clarified on 25 questions, 3 questions were removed, and 5 questions were added, resulting in a 53-item instrument. Psychometric testing has not been completed at this time, but will be completed at the time of presentation. Conclusions: Researchers intend to use the findings to improve policies and practice guidelines for primary care clinics in the Appalachian region. Results will be used to design CME activities to decrease PDA/M and to help foster more effective and responsible prescribing of pain medication

Metabolic Phenotypes and Chronic Kidney Disease: A Cross-Sectional Assessment of Patients from a Large Federally Qualified Health Center

The purpose of this study is to determine if renal function varies by metabolic phenotype. A total of 9599 patients from a large Federally Qualified Health Center (FQHC) were included in the analysis. Metabolic health was classified as the absence of metabolic abnormalities defined by the National Cholesterol Education Program Adult Treatment Panel III criteria, excluding waist circumference. Obesity was defined as body mass index >30 kg/m2 and renal health as an estimated glomerular filtration rate (eGFR) >60 mL/min/1.73 m2. Linear and logistic regressions were used to analyze the data. The metabolically healthy overweight (MHO) phenotype had the highest eGFR (104.86 ± 28.76 mL/min/1.72 m2) and lowest unadjusted odds of chronic kidney disease (CKD) (OR = 0.46, 95%CI = 0.168, 1.267, p = 0.133), while the metabolically unhealthy normal weight (MUN) phenotype demonstrated the lowest eGFR (91.34 ± 33.28 mL/min/1.72 m2) and the highest unadjusted odds of CKD (OR = 3.63, p < 0.0001). After controlling for age, sex, and smoking status, the metabolically unhealthy obese (MUO) (OR = 1.80, 95%CI = 1.08, 3.00, p = 0.024) was the only phenotype with significantly higher odds of CKD as compared to the reference. We demonstrate that the metabolically unhealthy phenotypes have the highest odds of CKD compared to metabolically healthy individuals

Microglial Gi-dependent dynamics regulate brain network hyperexcitability.

Microglial surveillance is a key feature of brain physiology and disease. Here, we found that Gi-dependent microglial dynamics prevent neuronal network hyperexcitability. By generating MgPTX mice to genetically inhibit Gi in microglia, we show that sustained reduction of microglia brain surveillance and directed process motility induced spontaneous seizures and increased hypersynchrony after physiologically evoked neuronal activity in awake adult mice. Thus, Gi-dependent microglia dynamics may prevent hyperexcitability in neurological diseases

Microglial Gi-dependent dynamics regulate brain network hyperexcitability.

Microglial surveillance is a key feature of brain physiology and disease. Here, we found that Gi-dependent microglial dynamics prevent neuronal network hyperexcitability. By generating MgPTX mice to genetically inhibit Gi in microglia, we show that sustained reduction of microglia brain surveillance and directed process motility induced spontaneous seizures and increased hypersynchrony after physiologically evoked neuronal activity in awake adult mice. Thus, Gi-dependent microglia dynamics may prevent hyperexcitability in neurological diseases