Operational Implementation of the Healthy Communities Study How Communities Shape Children’s Health

The Healthy Communities Study (HCS) is examining how characteristics of community programs and policies targeting childhood obesity are related to childhood diet, physical activity, and obesity outcomes. The study involves selected districts and public schools in 130 communities; families recruited through schools; and data collected at the community, school, household, and child levels. Data collection took place in two waves—Wave 1 in Spring 2012 and Wave 2 from 2013 to 2015—with analysis to be completed by August 2016. This paper describes operational elements of the HCS, including recruitment activities, field operations, training of data collectors, human subjects protection, and quality assurance and quality control procedures. Experienced trainers oversaw and conducted all training, including training of: (1) district and school recruitment staff; (2) telephone interviewers for household screening and recruitment; (3) field data collectors for conducting household data collection; and (4) community liaisons for conducting key informant interviews, document abstraction, and community observations. The study team developed quality assurance and quality control procedures that were implemented for all aspects of the study. Planning and operationalizing a study of this complexity and magnitude, with multiple functional teams, required frequent communication and strong collaboration among all study partners to ensure timely and effective decision making

Mixed-Method Evaluation of a Community Pharmacy Antimicrobial Stewardship Intervention (PAMSI)

The community pharmacy antimicrobial stewardship intervention (PAMSI) is multi-faceted and underpinned by behavioural science, consisting of the TARGET Antibiotic Checklist, staff e-Learning, and patient-facing materials. This mixed-method study evaluated the effect of PAMSI on community pharmacy staffs' self-reported antimicrobial stewardship (AMS) behaviours. Data collection included staff pre- and post-intervention questionnaires, qualitative interviews, and TARGET Antibiotic Checklists. Quantitative data were analysed by a multivariate ordinal linear mixed effect model; qualitative data were analysed thematically. A total of 101 staff participated from 66 pharmacies, and six completed semi-structured interviews. The statistical model indicated very strong evidence ( < 0.001) that post-intervention, staff increased their antibiotic appropriateness checks and patient advice, covering antibiotic adherence, antibiotic resistance, infection self-care, and safety-netting. Staff reported feeling empowered to query antibiotic appropriateness with prescribing clinicians. The TARGET Antibiotic Checklist was completed with 2043 patients. Topics patients identified as requiring advice from the pharmacy team included symptom duration, alcohol and food consumption guidance, antibiotic side-effects, and returning unused antibiotics to pharmacies. Pharmacy staff acknowledged the need for improved communication across the primary care pathway to optimise antimicrobial use, and PAMSI has potential to support this ambition if implemented nationally. To support patients not attending a pharmacy in person, an online information tool will be developed

LSST Science Book, Version 2.0

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over 20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a total point-source depth of r~27.5. The LSST Science Book describes the basic parameters of the LSST hardware, software, and observing plans. The book discusses educational and outreach opportunities, then goes on to describe a broad range of science that LSST will revolutionize: mapping the inner and outer Solar System, stellar populations in the Milky Way and nearby galaxies, the structure of the Milky Way disk and halo and other objects in the Local Volume, transient and variable objects both at low and high redshift, and the properties of normal and active galaxies at low and high redshift. It then turns to far-field cosmological topics, exploring properties of supernovae to z~1, strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and how these different probes may be combined to constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at http://www.lsst.org/lsst/sciboo

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Comprehensive Screening of Eight Known Causative Genes in Congenital Hypothyroidism With Gland-in-Situ.

CONTEXT: Lower TSH screening cutoffs have doubled the ascertainment of congenital hypothyroidism (CH), particularly cases with a eutopically located gland-in-situ (GIS). Although mutations in known dyshormonogenesis genes or TSHR underlie some cases of CH with GIS, systematic screening of these eight genes has not previously been undertaken. OBJECTIVE: Our objective was to evaluate the contribution and molecular spectrum of mutations in eight known causative genes (TG, TPO, DUOX2, DUOXA2, SLC5A5, SLC26A4, IYD, and TSHR) in CH cases with GIS. Patients, Design, and Setting: We screened 49 CH cases with GIS from 34 ethnically diverse families, using next-generation sequencing. Pathogenicity of novel mutations was assessed in silico. PATIENTS, DESIGN, AND SETTING: We screened 49 CH cases with GIS from 34 ethnically diverse families, using next-generation sequencing. Pathogenicity of novel mutations was assessed in silico. RESULTS: Twenty-nine cases harbored likely disease-causing mutations. Monogenic defects (19 cases) most commonly involved TG (12), TPO (four), DUOX2 (two), and TSHR (one). Ten cases harbored triallelic (digenic) mutations: TG and TPO (one); SLC26A4 and TPO (three), and DUOX2 and TG (six cases). Novel variants overall included 15 TG, six TPO, and three DUOX2 mutations. Genetic basis was not ascertained in 20 patients, including 14 familial cases. CONCLUSIONS: The etiology of CH with GIS remains elusive, with only 59% attributable to mutations in TSHR or known dyshormonogenesis-associated genes in a cohort enriched for familial cases. Biallelic TG or TPO mutations most commonly underlie severe CH. Triallelic defects are frequent, mandating future segregation studies in larger kindreds to assess their contribution to variable phenotype. A high proportion (∼41%) of unsolved or ambiguous cases suggests novel genetic etiologies that remain to be elucidated.This study made use of data generated by the UK10K Project and we acknowledge the contribution of the UK10K Consortium. This work was supported by Wellcome Trust Grants 100585/Z/12/Z (to N.S.), and 095564/Z/11/Z (to V.K.C.) and the National Institute for Health Research Cambridge Biomedical Research Center (to V.K.C., N.S.). E.G.S and C.A.A. are supported by the Wellcome Trust (098051). Funding for the UK10K Project was provided by the Wellcome Trust under award WT091310

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment