Comfort Providing Gender-Affirming Care and Preferences for Consultative Support Among Rural Pediatric Primary Care Providers.

Objective: To examine how specialist-to-pediatric primary care provider (PPCP) consultative support may impact PPCP comfort in providing gender-affirming care. Methods: PPCPs in West Virginia completed an electronic survey. T-tests compared comfort providing gender-affirming care and rank-sum tests compared the practicality of four consultative support modalities by time in practice and specialty. Results: Of 51 participants, 47.1% had been in practice for <10 years and 59.6% were trained in pediatrics. PPCPs with <10 years in practice and those trained in pediatrics were more comfortable providing gender-affirming care than those in practice >10 years and those trained in family medicine. PPCPs felt that telemedicine was more practical than tele-education, although they reported all consultative support modalities would increase comfort providing this care. Conclusions: Access to consultative support can increase PPCP comfort providing gender-affirming care, although certain modalities may be more effective for PPCPs with varying levels of experience and specialty training.

PERFect: PERmutation Filtering test for microbiome data.

The human microbiota composition is associated with a number of diseases including obesity, inflammatory bowel disease, and bacterial vaginosis. Thus, microbiome research has the potential to reshape clinical and therapeutic approaches. However, raw microbiome count data require careful pre-processing steps that take into account both the sparsity of counts and the large number of taxa that are being measured. Filtering is defined as removing taxa that are present in a small number of samples and have small counts in the samples where they are observed. Despite progress in the number and quality of filtering approaches, there is no consensus on filtering standards and quality assessment. This can adversely affect downstream analyses and reproducibility of results across platforms and software. We introduce PERFect, a novel permutation filtering approach designed to address two unsolved problems in microbiome data processing: (i) define and quantify loss due to filtering by implementing thresholds and (ii) introduce and evaluate a permutation test for filtering loss to provide a measure of excessive filtering. Methods are assessed on three "mock experiment" data sets, where the true taxa compositions are known, and are applied to two publicly available real microbiome data sets. The method correctly removes contaminant taxa in "mock" data sets, quantifies and visualizes the corresponding filtering loss, providing a uniform data-driven filtering criteria for real microbiome data sets. In real data analyses PERFect tends to remove more taxa than existing approaches; this likely happens because the method is based on an explicit loss function, uses statistically principled testing, and takes into account correlation between taxa. The PERFect software is freely available at https://github.com/katiasmirn/PERFect.

A Comparison of Base-calling Algorithms for Illumina Sequencing Technology.

Recent advances in next-generation sequencing technology have yielded increasing cost-effectiveness and higher throughput produced per run, in turn, greatly influencing the analysis of DNA sequences. Among the various sequencing technologies, Illumina is by far the most widely used platform. However, the Illumina sequencing platform suffers from several imperfections that can be attributed to the chemical processes inherent to the sequencing-by-synthesis technology. With the enormous amounts of reads produced, statistical methodologies and computationally efficient algorithms are required to improve the accuracy and speed of base-calling. Over the past few years, several papers have proposed methods to model the various imperfections, giving rise to accurate and/or efficient base-calling algorithms. In this article, we provide a comprehensive comparison of the performance of recently developed base-callers and we present a general statistical model that unifies a large majority of these base-callers.

Changes in vaginal community state types reflect major shifts in the microbiome.

Background: Recent studies of various human microbiome habitats have revealed thousands of bacterial species and the existence of large variation in communities of microorganisms in the same habitats across individual human subjects. Previous efforts to summarize this diversity, notably in the human gut and vagina, have categorized microbiome profiles by clustering them into community state types (CSTs). The functional relevance of specific CSTs has not been established. Objective: We investigate whether CSTs can be used to assess dynamics in the microbiome. Design: We conduct a re-analysis of five sequencing-based microbiome surveys derived from vaginal samples with repeated measures. Results: We observe that detection of a CST transition is largely insensitive to choices in methods for normalization or clustering. We find that healthy subjects persist in a CST for two to three weeks or more on average, while those with evidence of dysbiosis tend to change more often. Changes in CST can be gradual or occur over less than one day. Upcoming CST changes and switches to high-risk CSTs can be predicted with high accuracy in certain scenarios. Finally, we observe that presence of Gardnerella vaginalis is a strong predictor of an upcoming CST change. Conclusion: Overall, our results show that the CST concept is useful for studying microbiome dynamics.

Identifying Greater Sage-Grouse source and sink habitats for conservation planning in an energy development landscape.

Conserving a declining species that is facing many threats, including overlap of its habitats with energy extraction activities, depends upon identifying and prioritizing the value of the habitats that remain. In addition, habitat quality is often compromised when source habitats are lost or fragmented due to anthropogenic development. Our objective was to build an ecological model to classify and map habitat quality in terms of source or sink dynamics for Greater Sage-Grouse (Centrocercus urophasianus) in the Atlantic Rim Project Area (ARPA), a developing coalbed natural gas field in south-central Wyoming, USA. We used occurrence and survival modeling to evaluate relationships between environmental and anthropogenic variables at multiple spatial scales and for all female summer life stages, including nesting, brood-rearing, and non-brooding females. For each life stage, we created resource selection functions (RSFs). We weighted the RSFs and combined them to form a female summer occurrence map. We modeled survival also as a function of spatial variables for nest, brood, and adult female summer survival. Our survival-models were mapped as survival probability functions individually and then combined with fixed vital rates in a fitness metric model that, when mapped, predicted habitat productivity (productivity map). Our results demonstrate a suite of environmental and anthropogenic variables at multiple scales that were predictive of occurrence and survival. We created a source-sink map by overlaying our female summer occurrence map and productivity map to predict habitats contributing to population surpluses (source habitats) or deficits (sink habitat) and low-occurrence habitats on the landscape. The source-sink map predicted that of the Sage-Grouse habitat within the ARPA, 30% was primary source, 29% was secondary source, 4% was primary sink, 6% was secondary sink, and 31% was low occurrence. Our results provide evidence that energy development and avoidance of energy infrastructure were probably reducing the amount of source habitat within the ARPA landscape. Our source-sink map provides managers with a means of prioritizing habitats for conservation planning based on source and sink dynamics. The spatial identification of high value (i.e., primary source) as well as suboptimal (i.e., primary sink) habitats allows for informed energy development to minimize effects on local wildlife populations.

Investigating the performance of AIC in selecting phylogenetic models.

The popular likelihood-based model selection criterion, Akaike's Information Criterion (AIC), is a breakthrough mathematical result derived from information theory. AIC is an approximation to Kullback-Leibler (KL) divergence with the derivation relying on the assumption that the likelihood function has finite second derivatives. However, for phylogenetic estimation, given that tree space is discrete with respect to tree topology, the assumption of a continuous likelihood function with finite second derivatives is violated. In this paper, we investigate the relationship between the expected log likelihood of a candidate model, and the expected KL divergence in the context of phylogenetic tree estimation. We find that given the tree topology, AIC is an unbiased estimator of the expected KL divergence. However, when the tree topology is unknown, AIC tends to underestimate the expected KL divergence for phylogenetic models. Simulation results suggest that the degree of underestimation varies across phylogenetic models so that even for large sample sizes, the bias of AIC can result in selecting a wrong model. As the choice of phylogenetic models is essential for statistical phylogenetic inference, it is important to improve the accuracy of model selection criteria in the context of phylogenetics.

Statistical issues associated with modeling of synonymous mutation data.

The explosion of data in evolutionary bioinformatics has led to sometimes ad hoc, incomplete and even inaccurate data analyses. Taking dS data, namely, data on synonymous substitutions per synonymous sites, we go through a statistical analysis for modeling the time since duplications of genes. We explore the shortcomings of previous analyses, especially with a view towards their effect on inference for the gene duplication process. We present a statistical analysis which respects the assumptions of the models and the integrity of the data, and emphasize that exploratory data analysis, formulation of a data model, its estimation and finally, assessment of the model are important steps in a complete data analysis. Furthermore, for dS data, we develop Bayesian discrete-continuous mixture models and present analyses using two genomes.

Pediatric Gender Care in Primary Care Settings in West Virginia: Provider Knowledge, Attitudes, and Educational Experiences.

PURPOSE: Pediatric primary care providers (PPCPs) often care for gender diverse youth (GDY), particularly in rural areas, but little is known about their relevant knowledge, attitudes, or educational experiences regarding caring for this population. METHODS: This study surveyed PPCPs throughout the rural state of West Virginia using an online survey assessing 1) demographics, 2) knowledge, 3) attitudes, and 4) educational experiences. Knowledge and attitude scores were calculated and proportion-tests and t-tests were used to compare these scores by PPCP characteristics including age, time in practice, and training background. RESULTS: In total, 51 PPCPs from throughout the state completed the survey and 82% had cared for GDY in the prior year. Younger providers (

No evidence for a dilution effect of the non-native snail, Potamopyrgus antipodarum, on native snails.

The dilution effect can occur by a range of mechanisms and results in reduced parasite prevalence in host taxa. In invaded ecosystems, the dilution effect can benefit native species if non-native species, acting as resistant or less competent hosts, reduce rates of parasitic infections in native species. In field experiments, we assessed whether manipulating biomass of the non-native snail, Potamopyrgus antipodarum, caused a dilution effect by reducing trematode infections in three taxa of native snails. In contrast to many studies showing resistant or less competent non-native hosts can "dilute" or reduce infection rates, we found no evidence for a dilution effect reducing infection rates of any of the native snails. We suggest that a dilution effect may not have occurred because most trematode taxa are highly host specific, and thus the trematode transmission stages did not recognize the invasive snail as a possible host. In this case, community composition appears to be important in influencing the dilution effect.

Self-Concept in the Context of Diabetes Prevention: Development of the Lifestyle Health-Related Self-Concept Questionnaire.

PURPOSE: Understanding psychosocial factors in the context of lifestyle change is important to recognize distinctions in type 2 diabetes prevention behaviors. A relatively stable psychosocial feature, such as health-related self-concept (HRSC), may indicate factors that promote or repress positive health behaviors. The present study created a questionnaire specific to lifestyle change activities by modifying the Generalized Health-Related Self-Concept Questionnaire (G-HRSC). DESIGN: A modified lifestyle health-related self-concept (Lifestyle-HRSC) questionnaire was developed through creation of new items, context expert review of new items, and small and large sample test of new items. PARTICIPANTS: 101 college students completed the Lifestyle-HRSC. ANALYSIS: Kaiser-Meyer-Olkin (0.64) and Bartlett sphericity tests (χ2 = 6350.7 [ df = 3081], P < .01) indicated the sample met criteria for factor analysis. Principle component factor analysis was performed using varimax rotation with Kaiser normalization. RESULTS: Six factors were revealed: nutrition, social support, avoiding diabetes, physical activity, problem solving, and challenges related to being healthy. Item analysis was conducted to remove correlated and conceptually redundant items and to create the 31-item final questionnaire. CONCLUSION: The Lifestyle-HRSC provides additional knowledge regarding the relationship between self-concept and health as well as insights into the role of psychosocial factors in the context of diabetes prevention.

The vaginal microbiome and preterm birth.

The incidence of preterm birth exceeds 10% worldwide. There are significant disparities in the frequency of preterm birth among populations within countries, and women of African ancestry disproportionately bear the burden of risk in the United States. In the present study, we report a community resource that includes 'omics' data from approximately 12,000 samples as part of the integrative Human Microbiome Project. Longitudinal analyses of 16S ribosomal RNA, metagenomic, metatranscriptomic and cytokine profiles from 45 preterm and 90 term birth controls identified harbingers of preterm birth in this cohort of women predominantly of African ancestry. Women who delivered preterm exhibited significantly lower vaginal levels of Lactobacillus crispatus and higher levels of BVAB1, Sneathia amnii, TM7-H1, a group of Prevotella species and nine additional taxa. The first representative genomes of BVAB1 and TM7-H1 are described. Preterm-birth-associated taxa were correlated with proinflammatory cytokines in vaginal fluid. These findings highlight new opportunities for assessment of the risk of preterm birth.

Gender and the structure of self-rated health across the adult life span.

Despite the widespread use of self-rated health (SRH) in population health studies, the meaning of this holistic health judgment remains an open question. Gender differences in health, an issue of utmost importance in population research and policy, are often measured with SRH; the comparisons could be biased if men and women differ in how they form their health judgment. The aim of this study is to examine whether men and women differ in how health inputs predict their health rating across the adult life span. We use the 2002-2015 National Health Interview Survey data from US-born respondents aged 25-84. Ordered logistic models of SRH as a function of 24 health measures including medical conditions and symptoms, mental health, functioning, health care utilization, and health behaviors, all interacted with gender, test how the measures influence health ratings and the extent to which these influences differ by gender. Using a Bayesian approach, we then compare how closely a select health measure (K6 score) corresponds to SRH levels among men and women. We find little systematic gender difference in the structure of SRH: men and women use wide-ranging health-related frames of reference in a similar way when making health judgments, with some exceptions: mid-life and older men weigh physical functioning deficits and negative health behaviors more heavily than women. Women report worse SRH than men on average but this only holds through mid-adulthood and is reversed at older ages; moreover, the female disadvantage disappears when differences in socio-economic and health covariates are considered. Our findings suggest that the meaning of SRH is similar for women and men. Both groups use a broad range of health-related information in forming their health judgment. This conclusion strengthens the validity of SRH in measuring gender differences in health.

Long-Term BMI Trajectories and Health in Older Adults: Hierarchical Clustering of Functional Curves.

OBJECTIVE: This project contributes to the emerging research that aims to identify distinct body mass index (BMI) trajectory types in the population. We identify clusters of long-term BMI curves among older adults and determine how the clusters differ with respect to initial health. METHOD: Health and Retirement Study cohort (N = 9,893) with BMI information collected in up to 10 waves (1992-2010) is analyzed using a powerful cutting-edge approach: hierarchical clustering of BMI functions estimated via the Principal Analysis by Conditional Expectations (PACE) algorithm. RESULTS: Three BMI trajectory clusters emerged for each gender: stable, gaining, and losing. The initial health of the gaining and stable groups in both genders was comparable; the losing cluster experienced significantly poorer health at baseline. DISCUSSION: BMI trajectories among older adults cluster into distinct types in both genders, and the clusters vary substantially in initial health. Weight loss but not gain is associated with poor initial health in this age group.

Predictors for dioxin accumulation in residents living in Da Nang and Bien Hoa, Vietnam, many years after Agent Orange use.

Agent Orange (AO) was the main defoliant used by the US in Vietnam from 1961 to 1971; AO was contaminated with dioxin (2,3,7,8-tetrachlorodibenzo-p-dioxin, or TCDD). Three major dioxin "hot spots" remain from previous AO storage and use at former US bases at Bien Hoa, Da Nang, and Phu Cat, posing potential health risks for Vietnamese living on or near these hot spots. We evaluated potential risk factors contributing to serum TCDD levels in Vietnamese residents at and near contaminated sites in Da Nang and Bien Hoa, Vietnam. We used multiple linear regression to analyze possible associations of blood dioxin concentrations with demographic, socioeconomic, lifestyle, and dietary risk factors for residents living on or near these hot spots. For the Da Nang study, fish farming on the site, living on property flooded from monsoon rains, and age were among the factors showing significant positive associations with serum TCDD concentrations. For the Bien Hoa study, fish farmers working at this site and their immediate family members had significantly higher serum TCDD concentrations. Our results suggest that water-related activities, especially fish-farming, at the hot spots increased the risk of exposure to dioxin.

Lineage-specific differences in the amino acid substitution process.

In Darwinian evolution, mutations occur approximately at random in a gene, turned into amino acid mutations by the genetic code. Some mutations are fixed to become substitutions and some are eliminated from the population. Partitioning pairs of closely related species with complete genome sequences by average population size of each pair, we looked at the substitution matrices generated for these partitions and compared the substitution patterns between species. We estimated a population genetic model that relates the relative fixation probabilities of different types of mutations to the selective pressure and population size. Parameterizations of the average and distribution of selective pressures for different amino acid substitution types in different population size comparisons were generated with a Bayesian framework. We found that partitions in population size as well as in substitution type are required to explain the substitution data. Selection coefficients were found to decrease with increasingly radical amino acid substitution and with increasing effective population size. To further explore the role of underlying processes in amino acid substitution, we analyzed embryophyte (plant) gene families from TAED (The Adaptive Evolution Database), where solved structures for at least one member exist in the Protein Data Bank. Using PAML, we assigned branches to three categories: strong negative selection, moderate negative selection/neutrality, and positive diversifying selection. Focusing on the first and third categories, we identified sites changing along gene family lineages and observed the spatial patterns of substitution. Selective sweeps were expected to create primary sequence clustering under positive diversifying selection. Co-evolution through direct physical interaction was expected to cause tertiary structural clustering. Under both positive and negative selection, the substitution patterns were found to be nonrandom. Under positive diversifying selection, significant independent signals were found for primary and tertiary sequence clustering, suggesting roles for both selective sweeps and direct physical interaction. Under strong negative selection, the signals were not found to be independent. All together, a complex interplay of population genetic and protein thermodynamics forces is suggested.

Plasticity of animal genome architecture unmasked by rapid evolution of a pelagic tunicate.

Genomes of animals as different as sponges and humans show conservation of global architecture. Here we show that multiple genomic features including transposon diversity, developmental gene repertoire, physical gene order, and intron-exon organization are shattered in the tunicate Oikopleura, belonging to the sister group of vertebrates and retaining chordate morphology. Ancestral architecture of animal genomes can be deeply modified and may therefore be largely nonadaptive. This rapidly evolving animal lineage thus offers unique perspectives on the level of genome plasticity. It also illuminates issues as fundamental as the mechanisms of intron gain.