Organizational factors influencing implementation of evidence-based practices for integrated treatment in behavioral health agencies.

Objective. In recent years, New Mexico has prioritized integrated treatment for cooccurring mental health and substance use disorders within its public behavioral health system. This report describes factors likely to be important when implementing evidence-based practices (EBPs) in community agencies. Methods. Our mixed-method research design consisted of observations, semistructured interviews, and surveys undertaken with employees at 14 agencies at baseline and after 18 months. We developed four-agency typologies based on iterative coding and analysis of observations and interviews. We then examined survey data from employees at the four exemplar agencies to validate qualitative findings. Results. Financial resources and strong leadership impacted agency capacity to train providers and implement EBPs. Quantitative analysis of service provider survey responses from these agencies (N = 38) supported qualitative findings and demonstrated significant mean score differences in leadership, organizational climate, and attitudes toward EBPs in anticipated directions. Conclusion. The availability of strong leadership and financial resources were key components to initial implementation success in this study of community agencies in New Mexico. Reliance only on external funding poses risks for sustainment when demoralizing work climates precipitate employee turnover. Strong agency leadership does not always compensate for deficient financial resources in vulnerable communities

Alterations in the gut microbiome implicate key taxa and metabolic pathways across inflammatory arthritis phenotypes

Musculoskeletal diseases affect up to 20% of adults worldwide. The gut microbiome has been implicated in inflammatory conditions, but large-scale metagenomic evaluations have not yet traced the routes by which immunity in the gut affects inflammatory arthritis. To characterize the community structure and associated functional processes driving gut microbial involvement in arthritis, the Inflammatory Arthritis Microbiome Consortium investigated 440 stool shotgun metagenomes comprising 221 adults diagnosed with rheumatoid arthritis, ankylosing spondylitis, or psoriatic arthritis and 219 healthy controls and individuals with joint pain without an underlying inflammatory cause. Diagnosis explained about 2% of gut taxonomic variability, which is comparable in magnitude to inflammatory bowel disease. We identified several candidate microbes with differential carriage patterns in patients with elevated blood markers for inflammation. Our results confirm and extend previous findings of increased carriage of typically oral and inflammatory taxa and decreased abundance and prevalence of typical gut clades, indicating that distal inflammatory conditions, as well as local conditions, correspond to alterations to the gut microbial composition. We identified several differentially encoded pathways in the gut microbiome of patients with inflammatory arthritis, including changes in vitamin B salvage and biosynthesis and enrichment of iron sequestration. Although several of these changes characteristic of inflammation could have causal roles, we hypothesize that they are mainly positive feedback responses to changes in host physiology and immune homeostasis. By connecting taxonomic alternations to functional alterations, this work expands our understanding of the shifts in the gut ecosystem that occur in response to systemic inflammation during arthritis

Parent-reported child appetite moderates relationships between child genetic obesity risk and parental feeding practices

BackgroundFood parenting practices are associated with child weight. Such associations may reflect the effects of parents' practices on children's food intake and weight. However, longitudinal, qualitative, and behavioral genetic evidence suggests these associations could, in some cases, reflect parents' response to children's genetic risk for obesity, an instance of gene–environment correlation. We tested for gene–environment correlations across multiple domains of food parenting practices and explored the role of parent-reported child appetite in these relationships.Materials and methodsData on relevant variables were available for N = 197 parent–child dyads (7.54 ± 2.67 years; 44.4% girls) participating in RESONANCE, an ongoing pediatric cohort study. Children's body mass index (BMI) polygenic risk score (PRS) were derived based on adult GWAS data. Parents reported on their feeding practices (Comprehensive Feeding Practices Questionnaire) and their child's eating behavior (Child Eating Behavior Questionnaire). Moderation effects of child eating behaviors on associations between child BMI PRS and parental feeding practices were examined, adjusting for relevant covariates.ResultsOf the 12 parental feeding practices, 2 were associated with child BMI PRS, namely, restriction for weight control (β = 0.182, p = 0.011) and teaching about nutrition (β = −0.217, p = 0.003). Moderation analyses demonstrated that when children had high genetic obesity risk and showed moderate/high (vs. low) food responsiveness, parents were more likely to restrict food intake to control weight.ConclusionOur results indicate that parents may adjust their feeding practices in response to a child's genetic propensity toward higher or lower bodyweight, and the adoption of food restriction to control weight may depend on parental perceptions of the child's appetite. Research using prospective data on child weight and appetite and food parenting from infancy is needed to further investigate how gene–environment relationships evolve through development

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe