Catching Missional: Shaping a Participatory Environment in Missiological Education (A Case Study)

https://place.asburyseminary.edu/firstfruitspapers/1023/thumbnail.jp

Do highly divergent loci reside in genomic regions affecting reproductive isolation? A test using next-generation sequence data in Timema stick insects

Background: Genetic divergence during speciation with gene flow is heterogeneous across the genome, with some regions exhibiting stronger differentiation than others. Exceptionally differentiated regions are often assumed to experience reduced introgression, i.e., reduced flow of alleles from one population into another because such regions are affected by divergent selection or cause reproductive isolation. In contrast, the remainder of the genome can be homogenized by high introgression. Although many studies have documented variation across the genome in genetic differentiation, there are few tests of this hypothesis that explicitly quantify introgression. Here, we provide such a test using 38,304 SNPs in populations of Timema cristinae stick insects. We quantify whether loci that are highly divergent between geographically separated (‘allopatric’) populations exhibit unusual patterns of introgression in admixed populations. To the extent this is true, highly divergent loci between allopatric populations contribute to reproductive isolation in admixed populations. Results: As predicted, we find a substantial association between locus-specific divergence between allopatric populations and locus-specific introgression in admixed populations. However, many loci depart from this relationship, sometimes strongly so. We also report evidence for selection against foreign alleles due to local adaptation. Conclusions: Loci that are strongly differentiated between allopatric populations sometimes contribute to reproductive isolation in admixed populations. However, geographic variation in selection and local adaptation, in aspects of genetic architecture (such as organization of genes, recombination rate variation, number and effect size of variants contributing to adaptation, etc.), and in stochastic evolutionary processes such as drift can cause strong differentiation of loci that do not always contribute to reproductive isolation. The results have implications for the theory of ‘genomic islands of speciation’

Alignment of patient and primary care practice member perspectives of chronic illness care: a cross-sectional analysis

Polly H. Noel and Luci K. Leykum are with the South Texas Veterans Health Care System, 7400 Merton Minter Blvd, San Antonio, TX 78229, USA -- Polly H. Noel, Ray F. Palmer, Raquel L. Romero, Luci K. Leykum, Holly J. Lanham, and Krista W. Bowers are with the Department of Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229, USA -- Michael L. Parchman is with the MacColl Center for Healthcare Innovation, Group Health Research Institute, Group Health Cooperative, 1730 Minor Ave 1600, Seattle, WA 98101, USA -- Holly J. Leykum is with the The McCombs School of Business, The University of Texas at Austin, 2110 Speedway, Stop B6000, Austin, TX 78712, USA -- John E. Zeber is with the Central Texas Veterans Health Care System, 1901 S. 1st St, Temple, TX 76504, USA and Scott and White Healthcare Center for Applied Health Research, 2401 S. 31st St, Temple, TX 76508, USABackground: Little is known as to whether primary care teams’ perceptions of how well they have implemented the Chronic Care Model (CCM) corresponds with their patients’ own experience of chronic illness care. We examined the extent to which practice members’ perceptions of how well they organized to deliver care consistent with the CCM were associated with their patients’ perceptions of the chronic illness care they have received. Methods: Analysis of baseline measures from a cluster randomized controlled trial testing a practice facilitation intervention to implement the CCM in small, community-based primary care practices. All practice “members” (i.e., physician providers, non-physician providers, and staff) completed the Assessment of Chronic Illness Care (ACIC) survey and adult patients with 1 or more chronic illnesses completed the Patient Assessment of Chronic Illness Care (PACIC) questionnaire. Results: Two sets of hierarchical linear regression models accounting for nesting of practice members (N = 283) and patients (N = 1,769) within 39 practices assessed the association between practice member perspectives of CCM implementation (ACIC scores) and patients’ perspectives of CCM (PACIC). ACIC summary score was not significantly associated with PACIC summary score or most of PACIC subscale scores, but four of the ACIC subscales were consistently associated with PACIC summary score and the majority of PACIC subscale scores after controlling for patient characteristics. The magnitude of the coefficients, however, indicates that the level of association is weak. Conclusions: The ACIC and PACIC scales appear to provide complementary and relatively unique assessments of how well clinical services are aligned with the CCM. Our findings underscore the importance of assessing both patient and practice member perspectives when evaluating quality of chronic illness care.Information, Risk, and Operations Management (IROM)[email protected]

Patterns of primary care and mortality among patients with schizophrenia or diabetes: a cluster analysis approach to the retrospective study of healthcare utilization

Abstract Background Patients with schizophrenia have difficulty managing their medical healthcare needs, possibly resulting in delayed treatment and poor outcomes. We analyzed whether patients reduced primary care use over time, differentially by diagnosis with schizophrenia, diabetes, or both schizophrenia and diabetes. We also assessed whether such patterns of primary care use were a significant predictor of mortality over a 4-year period. Methods The Veterans Healthcare Administration (VA) is the largest integrated healthcare system in the United States. Administrative extracts of the VA's all-electronic medical records were studied. Patients over age 50 and diagnosed with schizophrenia in 2002 were age-matched 1:4 to diabetes patients. All patients were followed through 2005. Cluster analysis explored trajectories of primary care use. Proportional hazards regression modelled the impact of these primary care utilization trajectories on survival, controlling for demographic and clinical covariates. Results Patients comprised three diagnostic groups: diabetes only (n = 188,332), schizophrenia only (n = 40,109), and schizophrenia with diabetes (Scz-DM, n = 13,025). Cluster analysis revealed four distinct trajectories of primary care use: consistent over time, increasing over time, high and decreasing, low and decreasing. Patients with schizophrenia only were likely to have low-decreasing use (73% schizophrenia-only vs 54% Scz-DM vs 52% diabetes). Increasing use was least common among schizophrenia patients (4% vs 8% Scz-DM vs 7% diabetes) and was associated with improved survival. Low-decreasing primary care, compared to consistent use, was associated with shorter survival controlling for demographics and case-mix. The observational study was limited by reliance on administrative data. Conclusion Regular primary care and high levels of primary care were associated with better survival for patients with chronic illness, whether psychiatric or medical. For schizophrenia patients, with or without comorbid diabetes, primary care offers a survival benefit, suggesting that innovations in treatment retention targeting at-risk groups can offer significant promise of improving outcomes.http://deepblue.lib.umich.edu/bitstream/2027.42/78274/1/1472-6963-9-127.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78274/2/1472-6963-9-127.pdfPeer Reviewe

The Challenges of Multimorbidity from the Patient Perspective

BACKGROUND Although multiple co-occurring chronic illnesses within the same individual are increasingly common, few studies have examined the challenges of multimorbidity from the patient perspective. OBJECTIVE The aim of this study is to examine the self-management learning needs and willingness to see non-physician providers of patients with multimorbidity compared to patients with single chronic illnesses. DESIGN. This research is designed as a cross-sectional survey. PARTICIPANTS Based upon ICD-9 codes, patients from a single VHA healthcare system were stratified into multimorbidity clusters or groups with a single chronic illness from the corresponding cluster. Nonproportional sampling was used to randomly select 720 patients. MEASUREMENTS Demographic characteristics, functional status, number of contacts with healthcare providers, components of primary care, self-management learning needs, and willingness to see nonphysician providers. RESULTS Four hundred twenty-two patients returned surveys. A higher percentage of multimorbidity patients compared to single morbidity patients were "definitely" willing to learn all 22 self-management skills, of these only 2 were not significant. Compared to patients with single morbidity, a significantly higher percentage of patients with multimorbidity also reported that they were "definitely" willing to see 6 of 11 non-physician healthcare providers. CONCLUSIONS Self-management learning needs of multimorbidity patients are extensive, and their preferences are consistent with team-based primary care. Alternative methods of providing support and chronic illness care may be needed to meet the needs of these complex patients.US Department of Veterans Affairs (01-110, 02-197); Agency for Healthcare Research and Quality (K08 HS013008-02

Genome-wide RAD sequencing resolves the evolutionary history of serrate leaf Juniperus and reveals discordance with chloroplast phylogeny

Juniper (Juniperus) is an ecologically important conifer genus of the Northern Hemisphere, the members of which are often foundational tree species of arid regions. The serrate leaf margin clade is native to topologically variable regions in North America, where hybridization has likely played a prominent role in their diversification. Here we use a reduced-representation sequencing approach (ddRADseq) to generate a phylogenomic data set for 68 accessions representing all 22 species in the serrate leaf margin clade, as well as a number of close and distant relatives, to improve understanding of diversification in this group. Phylogenetic analyses using three methods (SVDquartets, maximum likelihood, and Bayesian) yielded highly congruent and well-resolved topologies. These phylogenies provided improved resolution relative to past analyses based on Sanger sequencing of nuclear and chloroplast DNA, and were largely consistent with taxonomic expectations based on geography and morphology. Calibration of a Bayesian phylogeny with fossil evidence produced divergence time estimates for the clade consistent with a late Oligocene origin in North America, followed by a period of elevated diversification between 12 and 5 Mya. Comparison of the ddRADseq phylogenies with a phylogeny based on Sanger-sequenced chloroplast DNA revealed five instances of pronounced discordance, illustrating the potential for chloroplast introgression, chloroplast transfer, or incomplete lineage sorting to influence organellar phylogeny. Our results improve understanding of the pattern and tempo of diversification in Juniperus, and highlight the utility of reduced-representation sequencing for resolving phylogenetic relationships in non-model organisms with reticulation and recent divergence

Experimental evidence for ecological selection on genome variation in the wild

Understanding natural selection's effect on genetic variation is a major goal in biology, but the genome-scale consequences of contemporary selection are not well known. In a release and recapture field experiment we transplanted stick insects to native and novel host plants and directly measured allele frequency changes within a generation at 186 576 genetic loci. We observed substantial, genome-wide allele frequency changes during the experiment, most of which could be attributed to random mortality (genetic drift). However, we also documented that selection affected multiple genetic loci distributed across the genome, particularly in transplants to the novel host. Host-associated selection affecting the genome acted on both a known colour-pattern trait as well as other (unmeasured) phenotypes. We also found evidence that selection associated with elevation affected genome variation, although our experiment was not designed to test this. Our results illustrate how genomic data can identify previously underappreciated ecological sources and phenotypic targets of selection