Elusive boundaries: using an attribute framework to describe systems for population physical activity promotion.

The cost of physical inactivity is alarming, and calls for whole-of-system approaches to population physical activity promotion (PPAP) are increasing. One innovative approach to PPAP is to use a framework of interdependent attributes and associated dimensions of effective systems for chronic disease prevention. Describing system boundaries can be an elusive task, and this article reports on using an attribute framework as a first step in describing and then assessing and strengthening a provincial system for PPAP in British Columbia, Canada. Interviews were conducted with provincial stakeholders to gather perspectives regarding attributes of the system. Following this, two workshops were facilitated to document important stories about the current system for PPAP and link story themes with attributes. Results from interviews and workshops were summarized into key findings and a set of descriptive statements. One hundred and twenty-one statements provide depth, breadth and scope to descriptions of the system through the lens of an adapted framework including four attributes: (i) implementation of desired actions, (ii) resources, (iii) leadership and (iv) collaborative capacity. The attribute framework was a useful tool to guide a whole-of-system approach and turn elusive boundaries into rich descriptors of a provincial system for PPAP. Immediate implications for our research are to translate descriptive statements into variables, then assess the system through group model building and identify leverage points from a causal loop diagram to strengthen the system. Future application of this approach in other contexts, settings and health promotion and disease prevention topics is recommended.

A scoping review of complex systems methods used in population physical activity research: do they align with attributes of a whole system approach?

BACKGROUND: Complex systems approaches are increasingly used in health promotion and noncommunicable disease prevention research, policy and practice. Questions emerge as to the best ways to take a complex systems approach, specifically with respect to population physical activity (PA). Using an Attributes Model is one way to understand complex systems. We aimed to examine the types of complex systems methods used in current PA research and identify what methods align with a whole system approach as reflected by an Attributes Model. METHODS: A scoping review was conducted and two databases were searched. Twenty-five articles were selected and data analysis was based upon the following: the complex systems research methods used, research aims, if participatory methods were used and evidence of discussion regarding attributes of systems. RESULTS: There were three groups of methods used: system mapping, simulation modelling and network analysis. System mapping methods appeared to align best with a whole system approach to PA promotion because they largely aimed to understand complex systems, examined interactions and feedback among variables, and used participatory methods. Most of these articles focused on PA (as opposed to integrated studies). Simulation modelling methods were largely focused on examining complex problems and identifying interventions. These methods did not generally focus on PA or use participatory methods. While network analysis articles focused on examining complex systems and identifying interventions, they did not focus on PA nor use participatory methods. All attributes were discussed in some way in the articles. Attributes were explicitly reported on in terms of findings or were part of discussion and conclusion sections. System mapping methods appear to be well aligned with a whole system approach because these methods addressed all attributes in some way. We did not find this pattern with other methods. CONCLUSIONS: Future research using complex systems methods may benefit from applying the Attributes Model in conjunction with system mapping methods. Simulation modelling and network analysis methods are seen as complementary and could be used when system mapping methods identify priorities for further investigation (e.g. what interventions to implement or how densely connected relationships are in systems).

Does ozone inhalation cause adverse metabolic effects in humans? A systematic review.

We utilized a practical, transparent approach for systematically reviewing a chemical-specific evidence base. This approach was used for a case study of ozone inhalation exposure and adverse metabolic effects (overweight/obesity, Type 1 diabetes [T1D], Type 2 diabetes [T2D], and metabolic syndrome). We followed the basic principles of systematic review. Studies were defined as "Suitable" or "Supplemental." The evidence for Suitable studies was characterized as strong or weak. An overall causality judgment for each outcome was then determined as either causal, suggestive, insufficient, or not likely. Fifteen epidemiologic and 33 toxicologic studies were Suitable for evidence synthesis. The strength of the human evidence was weak for all outcomes. The toxicologic evidence was weak for all outcomes except two: body weight, and impaired glucose tolerance/homeostasis and fasting/baseline hyperglycemia. The combined epidemiologic and toxicologic evidence was categorized as weak for overweight/obesity, T1D, and metabolic syndrome,. The association between ozone exposure and T2D was determined to be insufficient or suggestive. The streamlined approach described in this paper is transparent and focuses on key elements. As systematic review guidelines are becoming increasingly complex, it is worth exploring the extent to which related health outcomes should be combined or kept distinct, and the merits of focusing on critical elements to select studies suitable for causal inference. We recommend that systematic review results be used to target discussions around specific research needs for advancing causal determinations.

Factors affecting interpretation of national biomonitoring data from multiple countries: BPA as a case study.

INTRODUCTION: The use of biomonitoring data as an indicator of national levels of human exposure to environmental chemicals has grown in importance and prevalence. Nationally representative urinary bisphenol A (BPA) data are now available for Canada, the United States and Korea. Here we address the following questions: Are urinary BPA data from these countries comparable? What can be discerned regarding geographic and/or temporal similarities or differences? Are there generalizable lessons to be learned regarding comparison of biomonitoring results from different countries? METHODS: We examined underlying methods and resultant urinary BPA data from national surveys of three countries: Canada (Canadian Health Measures Survey, CHMS, 2009-2015); United States (National Health and Nutrition Examination Survey, NHANES, 2009-2014); and Korea (Korean National Environmental Health Survey, KoNEHS, 2009-2014). We estimated BPA daily intakes on both a volume- and creatinine-adjusted basis. RESULTS: The three countries use similar methods for analyzing urine samples for BPA and participate in external proficiency testing with acceptable results. Field blanks are only used in the CHMS program. There were program-specific differences in fasting times of participants. Median urinary BPA levels in Canada remained relatively constant over the three cycles (1.1-1.2 ng/ml), while US levels decreased (from 1.9 to 1.3 ng/ml) and Korean levels increased (from 0.7 to 1.1 ng/ml) over similar time periods. The most recent survey year data indicate that levels do not differ substantially across countries. Canadian urinary BPA levels have been stable; the subtle, non-significant decrease in intakes may be due to higher body weight in the more recent Canadian surveys. In contrast, the decrease in intakes in the US appears to be due to decreases in urinary BPA as body weights in the US have been stable. Estimated 95th percentile intakes are over an order of magnitude below current health-based guidance values. DISCUSSION: Our assessment of urinary BPA data from Canada, the US and Korea indicates that methodological differences, methods for dilution adjustment, and population characteristics should be carefully considered when interpreting biomonitoring data. Despite the plethora of publications describing issues with use of creatinine levels for urinary dilution adjustment, there have been no major methodological advances that would assist in interpreting urinary chemical data. A combination of biomonitoring and traditional exposure assessment approaches may be needed to fully assess human exposures to BPA and other chemicals. CONCLUSIONS: National biomonitoring surveys provide important information on population levels of chemicals such as BPA and can assist in understanding temporal and geographic similarities, differences, and trends. However, caution must be exercised when using these data to draw anything but broad conclusions, due to both intercountry methodological differences and factors affecting urinary chemical levels that are still poorly understood. While the issues raised in this paper do not appear to be a major concern specifically for the national-scale monitoring of BPA described here, they must be considered when comparing data for other chemicals measured as part of both national and smaller-scale biomonitoring-based research as well as for BPA data from other studies.

ExpoQual: Evaluating measured and modeled human exposure data.

Recent rapid technological advances are producing exposure data sets for which there are no available data quality assessment tools. At the same time, regulatory agencies are moving in the direction of data quality assessment for environmental risk assessment and decision-making. A transparent and systematic approach to evaluating exposure data will aid in those efforts. Any approach to assessing data quality must consider the level of quality needed for the ultimate use of the data. While various fields have developed approaches to assess data quality, there is as yet no general, user-friendly approach to assess both measured and modeled data in the context of a fit-for-purpose risk assessment. Here we describe ExpoQual, an instrument developed for this purpose which applies recognized parameters and exposure data quality elements from existing approaches for assessing exposure data quality. Broad data streams such as quantitative measured and modeled human exposure data as well as newer and developing approaches can be evaluated. The key strength of ExpoQual is that it facilitates a structured, reproducible and transparent approach to exposure data quality evaluation and provides for an explicit fit-for-purpose determination. ExpoQual was designed to minimize subjectivity and to include transparency in aspects based on professional judgment. ExpoQual is freely available on-line for testing and user feedback (exposurequality.com).

Nonprimary PCI at hospitals without cardiac surgery on-site: Consistent outcomes for all?

BACKGROUND: The CPORT-E trial showed the noninferiority of nonprimary percutaneous coronary intervention (PCI) at hospitals without cardiac surgery on-site (SoS) compared with hospitals with SoS for 6-week mortality and 9-month major adverse cardiac events (MACE). However, target vessel revascularization (TVR) was increased at non-SoS hospitals. Therefore, we aimed to determine the consistency of the CPORT-E trial findings across the spectrum of enrolled patients. METHODS: Post hoc subgroup analyses of 6-week mortality and 9-month MACE, defined as the composite of death, Q-wave myocardial infarction, or TVR, were performed. Patients with and without 9-month TVR and rates of related outcomes were compared. RESULTS: There was no interaction between SoS status and clinically relevant subgroups for 6-week mortality or 9-month MACE (P for any interaction=.421 and .062, respectively). In addition to increased 9-month rates of TVR and diagnostic catheterization at hospitals without SoS, non-TVR was also increased (2.7% vs 1.9%, P=.002); there was no difference in myocardial infarction-driven TVR, non-TVR, or diagnostic catheterization. Predictors of 9-month TVR included intra-aortic balloon pump use, any index PCI complication, and 3-vessel PCI, whereas predictors of freedom from TVR included SoS, discharge on a P2Y12 inhibitor, and stent implantation. CONCLUSIONS: The noninferiority of nonprimary PCI at non-SoS hospitals was consistent across clinically relevant subgroups. Elective PCI at an SoS hospital conferred a TVR benefit which may be related to a lower rate of referral for diagnostic catheterization for reasons other than myocardial infarction.

Systematic review of the literature on triclosan and health outcomes in humans.

The ability of epidemiologic evidence to inform regulatory decisions is largely dependent on the coherence and quality of the published literature. This systematic review examines the quality and consistency of studies assessing health outcomes associated with exposure to triclosan (TCS), an antimicrobial chemical with a short physiologic half-life. We used elements of the Biomonitoring, Environmental Epidemiology, and Short-Lived Chemicals instrument to evaluate aspects of study quality. Each methodological domain - overall design, exposure assessment, and data analysis - was categorized according to three tiers where Tier 1 indicated the highest quality. We also examined consistency of methods, results and reporting as considerations for weight of evidence (WOE) assessment. Studies were considered sufficiently comparable if they addressed the same or similar research questions. Forty-two studies met the criteria for inclusion. Only one randomized cross-over clinical trial of TCS was assigned to Tier 1 for all three domains. Most other studies were assigned to Tier 3 for at least one domain. Although the available literature examined more than 100 different health endpoints and reported hundreds of different measures of association, few studies were considered comparable. For reported measures of association, most were not significantly different from the null; the few statistically significant results represented isolated findings without a discernable across- or within-study pattern. We conclude that the current body of epidemiologic literature does not allow a meaningful WOE assessment due to methodological limitations of individual studies and lack of inter-study consistency. On the other hand, methodologically stronger studies may be used to inform future research.

Effectiveness of viable cryopreserved placental membranes for management of diabetic foot ulcers in a real world setting.

In a multicenter randomized controlled trial (RCT), the use of viable cryopreserved placental membrane (vCPM) for chronic diabetic foot ulcers (DFUs) resulted in a higher proportion of wound closure in comparison to good wound care: 62% versus 21% (p < 0.01). However, patients in RCTs are not representative of daily physician practice. Healthcare databases serve as a valuable tool to evaluate therapy effectiveness and to supplement evidence from RCTs. The objective of this study was to evaluate the effectiveness of vCPM for DFU management using Net Health's WoundExpert® electronic health records (EHR). The primary endpoint was the proportion of DFUs that achieved complete closure. Other endpoints included time and number of grafts to closure, probability of wound closure by week 12, and the number of wound-related infections and amputations. De-identified EHR data for 360 patients with 441 wounds treated with vCPM were extracted from the database. Average patient age was 63.7 years with a mean wound size of 5.1 cm2 and an average wound duration of 102 days prior to vCPM treatment. For evaluation of clinical outcomes, 350 DFUs larger than 0.25 cm2 at baseline were analyzed. Closure at the end of treatment was achieved in 59.4% of wounds with a median treatment duration of 42.0 days and 4 applications of vCPM. The probability of wound closure at week 12 was 71%, and the number of amputations and wound-related infections was 13 (3.0%) and 9 (2.0%), respectively. Data also demonstrated a correlation between wound size and closure rate as well as a correlation between > 50% wound area reduction by week 4 and wound closure by week 12. The results of this study mirror previous RCT efficacy data, supporting the benefits of vCPM for DFU management. These results can also influence policy and treatment decisions regarding advanced vCPM technology.

Heparin versus bivalirudin for non-primary percutaneous coronary intervention: A post-Hoc analysis of the CPORT-E trial.

OBJECTIVES: To compare bivalirudin to heparin during non-primary percutaneous coronary intervention (PCI). BACKGROUND: The optimal anticoagulant to support PCI remains uncertain. METHODS: We performed a propensity score-based analysis comparing clinical outcomes of patients receiving heparin to those receiving bivalirudin during non-primary PCI. RESULTS: Of 18,867 patients in the Cardiovascular Patient Outcomes Research Team Non-Primary PCI (CPORT-E) trial, we selected 7,913 patients undergoing non-staged PCI of whom 57.3% received heparin and 42.7% received bivalirudin. In-hospital myocardial infarction occurred in 4.4% of patients receiving bivalirudin and 3.0% of patients receiving heparin (relative risk [RR] 1.5, 95% confidence interval [CI] 1.1-2.1, P = 0.022); this difference persisted at 6 weeks (5.0% vs. 3.6%, RR 1.4, 95% CI 1.0-1.8, P = 0.041). There was no difference in all-cause mortality either in-hospital (0.2% vs. 0.1% for heparin vs. bivalirudin, P = 0.887) or at 6 weeks (0.5% vs. 0.7%, P = 0.567). In-hospital bleeding requiring transfusion occurred in 0.9% of patients receiving bivalirudin and 1.9% of patients receiving heparin (RR 0.4, 95% CI 0.3-0.7, P <0.001), but there was no difference at 6 weeks (2.7% for heparin vs. 1.9% for bivalirudin, RR 0.7, 95% CI 0.5-1.0, P = 0.062). CONCLUSIONS: In patients undergoing non-primary PCI at hospitals without on-site cardiac surgery, bivalirudin was associated with a decreased risk of in-hospital bleeding requiring transfusion and an increased risk of in-hospital MI compared to heparin. © 2017 Wiley Periodicals, Inc.

Critical and systematic evaluation of data for estimating human exposures to 2,4-dichlorophenoxyacetic acid (2,4-D) - quality and generalizability.

The herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) has been commercially available since the 1940's. Despite decades of data on 2,4-D in food, air, soil, and water, as well as in humans, the quality the quality of these data has not been comprehensively evaluated. Using selected elements of the Biomonitoring, Environmental Epidemiology, and Short-lived Chemicals (BEES-C) instrument (temporal variability, avoidance of sample contamination, analyte stability, and urinary methods of matrix adjustment), the quality of 156 publications of environmental- and biomonitoring-based 2,4-D data was examined. Few publications documented steps were taken to avoid sample contamination. Similarly, most studies did not demonstrate the stability of the analyte from sample collection to analysis. Less than half of the biomonitoring publications reported both creatinine-adjusted and unadjusted urine concentrations. The scope and detail of data needed to assess temporal variability and sources of 2,4-D varied widely across the reviewed studies. Exposures to short-lived chemicals such as 2,4-D are impacted by numerous and changing external factors including application practices and formulations. At a minimum, greater transparency in reporting of quality control measures is needed. Perhaps the greatest challenge for the exposure community is the ability to reach consensus on how to address problems specific to short-lived chemical exposures in observational epidemiology investigations. More extensive conversations are needed to advance our understanding of human exposures and enable interpretation of these data to catch up to analytical capabilities. The problems defined in this review remain exquisitely difficult to address for chemicals like 2,4-D, with short and variable environmental and physiological half-lives and with exposures impacted by numerous and changing external factors.

SubClonal Hierarchy Inference from Somatic Mutations: Automatic Reconstruction of Cancer Evolutionary Trees from Multi-region Next Generation Sequencing.

Recent improvements in next-generation sequencing of tumor samples and the ability to identify somatic mutations at low allelic fractions have opened the way for new approaches to model the evolution of individual cancers. The power and utility of these models is increased when tumor samples from multiple sites are sequenced. Temporal ordering of the samples may provide insight into the etiology of both primary and metastatic lesions and rationalizations for tumor recurrence and therapeutic failures. Additional insights may be provided by temporal ordering of evolving subclones--cellular subpopulations with unique mutational profiles. Current methods for subclone hierarchy inference tightly couple the problem of temporal ordering with that of estimating the fraction of cancer cells harboring each mutation. We present a new framework that includes a rigorous statistical hypothesis test and a collection of tools that make it possible to decouple these problems, which we believe will enable substantial progress in the field of subclone hierarchy inference. The methods presented here can be flexibly combined with methods developed by others addressing either of these problems. We provide tools to interpret hypothesis test results, which inform phylogenetic tree construction, and we introduce the first genetic algorithm designed for this purpose. The utility of our framework is systematically demonstrated in simulations. For most tested combinations of tumor purity, sequencing coverage, and tree complexity, good power (≥ 0.8) can be achieved and Type 1 error is well controlled when at least three tumor samples are available from a patient. Using data from three published multi-region tumor sequencing studies of (murine) small cell lung cancer, acute myeloid leukemia, and chronic lymphocytic leukemia, in which the authors reconstructed subclonal phylogenetic trees by manual expert curation, we show how different configurations of our tools can identify either a single tree in agreement with the authors, or a small set of trees, which include the authors' preferred tree. Our results have implications for improved modeling of tumor evolution and the importance of multi-region tumor sequencing.

Multiclass cancer classification based on gene expression comparison.

As the complexity and heterogeneity of cancer is being increasingly appreciated through genomic analyses, microarray-based cancer classification comprising multiple discriminatory molecular markers is an emerging trend. Such multiclass classification problems pose new methodological and computational challenges for developing novel and effective statistical approaches. In this paper, we introduce a new approach for classifying multiple disease states associated with cancer based on gene expression profiles. Our method focuses on detecting small sets of genes in which the relative comparison of their expression values leads to class discrimination. For an m-class problem, the classification rule typically depends on a small number of m-gene sets, which provide transparent decision boundaries and allow for potential biological interpretations. We first test our approach on seven common gene expression datasets and compare it with popular classification methods including support vector machines and random forests. We then consider an extremely large cohort of leukemia cancer patients to further assess its effectiveness. In both experiments, our method yields comparable or even better results to benchmark classifiers. In addition, we demonstrate that our approach can integrate pathway analysis of gene expression to provide accurate and biological meaningful classification.

Temporal trends in bisphenol A exposure in the United States from 2003-2012 and factors associated with BPA exposure: Spot samples and urine dilution complicate data interpretation.

Nationally representative data on urinary levels of BPA and its metabolites in the United States from the 2003-2004 to 2011-2012 National Health and Nutrition Examination Surveys (NHANES) were used to estimate daily BPA intakes and examine temporal trends. Additionally, NHANES data on lifestyle/demographic/dietary factors previously reported to be associated with BPA exposures were examined to assess the resiliency of the reported associations (whether the association is maintained across the five surveys). Finally, various approaches for addressing issues with the use of BPA concentration data from spot urine samples were examined for their effect on trends and associations. Three approaches were assessed here: (i) use of generic literature-based 24-h urine excretion volumes, (ii) use of creatinine adjustments, and (iii) use of individual urine flow rate data from NHANES. Based on 2011-2012 NHANES urinary BPA data and assumptions described in this paper, the median daily intake for the overall population is approximately 25 ng/kg day; median intake estimates were approximately two to three orders of magnitude below current health-based guidance values. Estimates of daily BPA intake have decreased significantly compared to those from the 2003-2004 NHANES. Estimates of associations between lifestyle/demographic/dietary factors and BPA exposure revealed inconsistencies related to both NHANES survey year and the three approaches listed above; these results demonstrate the difficulties in interpreting urinary BPA data, despite efforts to account for urine dilution and translation of spot sample data to 24-h data. The results further underscore the importance of continued research on how to best utilize urinary measures of environmental chemicals in exposure research. Until a consensus is achieved regarding the best biomonitoring approaches for assessing exposures to short-lived chemicals using urine samples, research on factors associated with BPA exposures should include - and report results from - assessments using both volume-based urinary BPA and creatinine-adjusted urinary BPA data.

Number sense across the lifespan as revealed by a massive Internet-based sample.

It has been difficult to determine how cognitive systems change over the grand time scale of an entire life, as few cognitive systems are well enough understood; observable in infants, adolescents, and adults; and simple enough to measure to empower comparisons across vastly different ages. Here we address this challenge with data from more than 10,000 participants ranging from 11 to 85 years of age and investigate the precision of basic numerical intuitions and their relation to students' performance in school mathematics across the lifespan. We all share a foundational number sense that has been observed in adults, infants, and nonhuman animals, and that, in humans, is generated by neurons in the intraparietal sulcus. Individual differences in the precision of this evolutionarily ancient number sense may impact school mathematics performance in children; however, we know little of its role beyond childhood. Here we find that population trends suggest that the precision of one's number sense improves throughout the school-age years, peaking quite late at ∼30 y. Despite this gradual developmental improvement, we find very large individual differences in number sense precision among people of the same age, and these differences relate to school mathematical performance throughout adolescence and the adult years. The large individual differences and prolonged development of number sense, paired with its consistent and specific link to mathematics ability across the age span, hold promise for the impact of educational interventions that target the number sense.

Randomized controlled effectiveness trial of executive function intervention for children on the autism spectrum.

BACKGROUND: Unstuck and On Target (UOT) is an executive function (EF) intervention for children with autism spectrum disorders (ASD) targeting insistence on sameness, flexibility, goal-setting, and planning through a cognitive-behavioral program of self-regulatory scripts, guided/faded practice, and visual/verbal cueing. UOT is contextually-based because it is implemented in school and at home, the contexts in which a child uses EF skills. METHODS: To evaluate the effectiveness of UOT compared with a social skills intervention (SS), 3rd-5th graders with ASD (mean IQ = 108; UOT n = 47; SS n = 20) received interventions delivered by school staff in small group sessions. Students were matched for gender, age, race, IQ, ASD symptomotolgy, medication status, and parents' education. Interventions were matched for 'dose' of intervention and training. Measures of pre-post change included classroom observations, parent/teacher report, and direct child measures of problem-solving, EF, and social skills. Schools were randomized and evaluators, but not parents or teachers, were blinded to intervention type. RESULTS: Interventions were administered with high fidelity. Children in both groups improved with intervention, but mean change scores from pre- to postintervention indicated significantly greater improvements for UOT than SS groups in: problem-solving, flexibility, and planning/organizing. Also, classroom observations revealed that participants in UOT made greater improvements than SS participants in their ability to follow rules, make transitions, and be flexible. Children in both groups made equivalent improvements in social skills. CONCLUSIONS: These data support the effectiveness of the first contextually-based EF intervention for children with ASD. UOT improved classroom behavior, flexibility, and problem-solving in children with ASD. Individuals with variable background/training in ASD successfully implemented UOT in mainstream educational settings.

Follow the Arrows: Using a Co-Created Causal Loop Diagram to Explore Leverage Points to Strengthen Population Physical Activity Promotion in British Columbia, Canada.

BACKGROUND: Population physical activity promotion (PPAP) is one of the most effective noncommunicable disease prevention strategies, yet coordination is lacking around the world. Whole-of-system approaches and complex systems methods are called for to advance PPAP. This paper reports on a project which (1) used an Attributes Framework with system mapping (group model building and causal loop diagramming of feedback loops) and (2) identified potential leverage points to address the challenge of effective coordination of multisectoral PPAP in British Columbia. METHODS: Key findings from stakeholder interviews and workshops described the current system for PPAP in terms of attributes and dimensions in the framework. These were translated into variables and used in group model building. Participants prioritized the importance of variables to address the coordination challenge and then created causal loop diagrams in 3 small groups. One collective causal loop diagram was created, and top priority variables and associated feedback loops were highlighted to explore potential leverage points. RESULTS: Leverage points included the relationships and feedback loops among priority variables: political leadership, visible policy support and governance, connectivity for knowledge translation, collaborative multisector grants, multisector collaboration, and integrating co-benefits. Leveraging and altering "vicious" cyclical patterns to increase coordinated multisector PPAP are key. CONCLUSIONS: The Attributes Framework, group model building and causal loop diagrams, and emergent feedback loops were useful to explore potential leverage points to address the challenge of multisectoral coordination of PPAP. Future research could apply the same methods in other jurisdictions and compare and contrast resultant frameworks, variables, feedback loops, and leverage points.

From policy to practice: implementation of physical activity and food policies in schools.

PURPOSE: Public policies targeting the school setting are increasingly being used to address childhood obesity; however, their effectiveness depends on their implementation. This study explores the factors which impeded or facilitated the implementation of publicly mandated school-based physical activity and nutrition guidelines in the province of British Columbia (BC), Canada. METHODS: Semi-structured interviews were conducted with 50 school informants (17 principals - 33 teacher/school informants) to examine the factors associated with the implementation of the mandated Daily Physical Activity (DPA) and Food and Beverage Sales in Schools (FBSS) guidelines. Coding used a constructivist grounded theory approach. The first five transcripts and every fifth transcript thereafter were coded by two independent coders with discrepancies reconciled by a third coder. Data was coded and analysed in the NVivo 9 software. Concept maps were developed and current theoretical perspectives were integrated in the later stages of analysis. RESULTS: The Diffusion of Innovations Model provided an organizing framework to present emergent themes. With the exception of triability (not relevant in the context of mandated guidelines/policies), the key attributes of the Diffusion of Innovations Model (relative advantage, compatibility, complexity, and observability) provided a robust framework for understanding themes associated with implementation of mandated guidelines. Specifically, implementation of the DPA and FBSS guidelines was facilitated by perceptions that they: were relatively advantageous compared to status quo; were compatible with school mandates and teaching philosophies; had observable positive impacts and impeded when perceived as complex to understand and implement. In addition, a number of contextual factors including availability of resources facilitated implementation. CONCLUSIONS: The enactment of mandated policies/guidelines for schools is considered an essential step in improving physical activity and healthy eating. However, policy makers need to: monitor whether schools are able to implement the guidelines, support schools struggling with implementation, and document the impact of the guidelines on students' behaviors. To facilitate the implementation of mandated guidelines/policies, the Diffusion of Innovations Model provides an organizational framework for planning interventions. Changing the school environment is a process which cannot be undertaken solely by passive means as we know that such approaches have not resulted in adequate implementation.

Improving infant exposure and health risk estimates: using serum data to predict polybrominated diphenyl ether concentrations in breast milk.

Women in the United States have breast milk concentrations of polybrominated diphenyl ethers (PBDEs) that are among the highest in the world, leading to concerns over the potential health implications to breastfeeding infants during critical stages of growth and development. Developing cost-effective and sustainable methods for assessing chemical exposures in infants is a high priority to federal agencies and local communities. PBDE data are available in nationally representative serum samples but not in breast milk. As a method to predict PBDE concentrations in U.S. breast milk, we present the development of congener-specific linear regression partitioning models and their application to U.S. serum data. Models were developed from existing paired milk and serum data and applied to 2003-2004 NHANES serum data for U.S. women. Highest estimated median U.S. breast milk concentrations were for BDE-47 (30.6 ng/g lipid) and BDE-99 (6.1 ng/g lipid) with the median concentration of Σ7PBDEs estimated at 54.2 ng/g lipid. Predictions of breast milk PBDE concentration were consistent with reported concentrations from 11 similarly timed U.S. studies. When applied to NHANES data, these models provide a sustainable method for estimating population-level concentrations of PBDEs in U.S. breast milk and should improve exposure estimates in breastfeeding infants.

New genes involved in cancer identified by retroviral tagging.

Retroviral insertional mutagenesis in BXH2 and AKXD mice induces a high incidence of myeloid leukemia and B- and T-cell lymphoma, respectively. The retroviral integration sites (RISs) in these tumors thus provide powerful genetic tags for the discovery of genes involved in cancer. Here we report the first large-scale use of retroviral tagging for cancer gene discovery in the post-genome era. Using high throughput inverse PCR, we cloned and analyzed the sequences of 884 RISs from a tumor panel composed primarily of B-cell lymphomas. We then compared these sequences, and another 415 RIS sequences previously cloned from BXH2 myeloid leukemias and from a few AKXD lymphomas, against the recently assembled mouse genome sequence. These studies identified 152 loci that are targets of retroviral integration in more than one tumor (common retroviral integration sites, CISs) and therefore likely to encode a cancer gene. Thirty-six CISs encode genes that are known or predicted to be genes involved in human cancer or their homologs, whereas others encode candidate genes that have not yet been examined for a role in human cancer. Our studies demonstrate the power of retroviral tagging for cancer gene discovery in the post-genome era and indicate a largely unrecognized complexity in mouse and presumably human cancer.

CellCover Defines Conserved Cell Types and Temporal Progression in scRNA-seq Data across Mammalian Neocortical Development.

Accurate identification of cell classes across the tissues of living organisms is central in the analysis of growing atlases of single-cell RNA sequencing (scRNA-seq) data across biomedicine. Such analyses are often based on the existence of highly discriminating "marker genes" for specific cell classes which enables a deeper functional understanding of these classes as well as their identification in new, related datasets. Currently, marker genes are defined by methods that serially assess the level of differential expression (DE) of individual genes across landscapes of diverse cells. This serial approach has been extremely useful, but is limited because it ignores possible redundancy or complementarity across genes, that can only be captured by analyzing several genes at the same time. We wish to identify discriminating panels of genes. To efficiently explore the vast space of possible marker panels, leverage the large number of cells often sequenced, and overcome zero-inflation in scRNA-seq data, we propose viewing panel selection as a variation of the "minimal set-covering problem" in combinatorial optimization which can be solved with integer programming. In this formulation, the covering elements are genes, and the objects to be covered are cells of a particular class, where a cell is covered by a gene if that gene is expressed in that cell. Our method, CellCover, identifies a panel of marker genes in scRNA-seq data that covers one class of cells within a population. We apply this method to generate covering marker gene panels which characterize cells of the developing mouse neocortex as postmitotic neurons are generated from neural progenitor cells (NPCs). We show that CellCover captures cell class-specific signals distinct from those defined by DE methods and that CellCover's compact gene panels can be expanded to explore cell type specific function.Transfer learning experiments exploring these covering panels across in vivo mouse, primate, and human scRNA-seq datasets demonstrate that CellCover identifies markers of conserved cell classes in neurogenesis, as well as markers of temporal progression in the molecular identity of these cell types across development of the mammalian neocortex. The gene covering panels we identify across cell types and developmental time can be freely explored in visualizations across all the public data we use in this report at with NeMo Analytics [1] through https://nemoanalytics.org/p?l=CellCover . The code for CellCover is written in R and the Gurobi R interface and is available at [2].