ENIGMA and the individual: Predicting factors that affect the brain in 35 countries worldwide.

In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) - a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date - of schizophrenia and major depression - ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others(1), ENIGMA's genomic screens - now numbering over 30,000 MRI scans - have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants - and genetic variants in general - may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures - from tens of thousands of people - that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far.

Economic and Social Upgrading in Global Value Chains and Industrial Clusters: Why Governance Matters

© 2014, Springer Science+Business Media Dordrecht.The burgeoning literature on global value chains (GVCs) has recast our understanding of how industrial clusters are shaped by their ties to the international economy, but within this context, the role played by corporate social responsibility (CSR) continues to evolve. New research in the past decade allows us to better understand how CSR is linked to industrial clusters and GVCs. With geographic production and trade patterns in many industries becoming concentrated in the global South, lead firms in GVCs have been under growing pressure to link economic and social upgrading in more integrated forms of CSR. This is leading to a confluence of “private governance” (corporate codes of conduct and monitoring), “social governance” (civil society pressure on business from labor organizations and non-governmental organizations), and “public governance” (government policies to support gains by labor groups and environmental activists). This new form of “synergistic governance” is illustrated with evidence from recent studies of GVCs and industrial clusters, as well as advances in theorizing about new patterns of governance in GVCs and clusters.

Advanced Aerogel Composites for Oil Remediation and Recovery

Oil spills in marine environments often damage marine and coastal life if not remediated rapidly and efficiently. In spite of the strict enforcement of environmental legislations (i.e., Oil Pollution Act 1990) following the Exxon Valdez oil spill (June 1989; the second biggest oil spill in U.S. history), the Macondo well blowout disaster (April 2010) released 18 times more oil. Strikingly, the response methods used to contain and capture spilled oil after both accidents were nearly identical, note that more than two decades separate Exxon Valdez (1989) and Macondo well (2010) accidents.

The goal of this dissertation was to investigate new advanced materials (mechanically strong aerogel composite blankets-Cabot® Thermal Wrap™ (TW) and Aspen Aerogels® Spaceloft® (SL)), and their applications for oil capture and recovery to overcome the current material limitations in oil spill response methods. First, uptake of different solvents and oils were studied to answer the following question: do these blanket aerogel composites have competitive oil uptake compared to state-of-the-art oil sorbents (i.e., polyurethane foam-PUF)? In addition to their competitive mechanical strength (766, 380, 92 kPa for Spaceloft, Thermal Wrap, and PUF, respectively), our results showed that aerogel composites have three critical advantages over PUF: rapid (3-5 min.) and high (more than two times of PUF’s uptake) oil uptake, reusability (over 10 cycles), and oil recoverability (up to 60%) via mechanical extraction. Chemical-specific sorption experiments showed that the dominant uptake mechanism of aerogels is adsorption to the internal surface, with some contribution of absorption into the pore space.

Second, we investigated the potential environmental impacts (energy and chemical burdens) associated with manufacturing, use, and disposal of SL aerogel and PUF to remove the oil (i.e., 1 m3 oil) from a location (i.e., Macondo well). Different use (single and multiple use) and end of life (landfill, incinerator, and waste-to-energy) scenarios were assessed, and our results demonstrated that multiple use, and waste-to-energy choices minimize the energy and material use of SL aerogel. Nevertheless, using SL once and disposing via landfill still offers environmental and cost savings benefits relative to PUF, and so these benefits are preserved irrespective of the oil-spill-response operator choices.

To inform future aerogel manufacture, we investigated the different laboratory-scale aerogel fabrication technologies (rapid supercritical extraction (RSCE), CO2 supercritical extraction (CSCE), alcohol supercritical extraction (ASCE)). Our results from anticipatory LCA for laboratory-scaled aerogel fabrication demonstrated that RSCE method offers lower cumulative energy and ecotoxicity impacts compared to conventional aerogel fabrication methods (CSCE and ASCE).

The final objective of this study was to investigate different surface coating techniques to enhance oil recovery by modifying the existing aerogel surface chemistries to develop chemically responsive materials (switchable hydrophobicity in response to a CO2 stimulus). Our results showed that studied surface coating methods (drop casting, dip coating, and physical vapor deposition) were partially successful to modify surface with CO2 switchable chemical (tributylpentanamidine), likely because of the heterogeneous fiber structure of the aerogel blankets. A possible solution to these non-uniform coatings would be to include switchable chemical as a precursor during the gel preparation to chemically attach the switchable chemical to the pores of the aerogel.

Taken as a whole, the implications of this work are that mechanical deployment and recovery of aerogel composite blankets is a viable oil spill response strategy that can be deployed today. This will ultimately enable better oil uptake without the uptake of water, potential reuse of the collected oil, reduced material and energy burdens compared to competitive sorbents (e.g., PUF), and reduced occupational exposure to oiled sorbents. In addition, sorbent blankets and booms could be deployed in coastal and open-ocean settings, respectively, which was previously impossible.

Child work and labour among orphaned and abandoned children in five low and middle income countries.

BACKGROUND: The care and protection of the estimated 143,000,000 orphaned and abandoned children (OAC) worldwide is of great importance to global policy makers and child service providers in low and middle income countries (LMICs), yet little is known about rates of child labour among OAC, what child and caregiver characteristics predict child engagement in work and labour, or when such work infers with schooling. This study examines rates and correlates of child labour among OAC and associations of child labour with schooling in a cohort of OAC in 5 LMICs. METHODS: The Positive Outcomes for Orphans (POFO) study employed a two-stage random sampling survey methodology to identify 1480 single and double orphans and children abandoned by both parents ages 6-12 living in family settings in five LMICs: Cambodia, Ethiopia, India, Kenya, and Tanzania. Regression models examined child and caregiver associations with: any work versus no work; and with working <21, 21-27, and 28+ hours during the past week, and child labour (UNICEF definition). RESULTS: The majority of OAC (60.7%) engaged in work during the past week, and of those who worked, 17.8% (10.5% of the total sample) worked 28 or more hours. More than one-fifth (21.9%; 13% of the total sample) met UNICEF's child labour definition. Female OAC and those in good health had increased odds of working. OAC living in rural areas, lower household wealth and caregivers not earning an income were associated with increased child labour. Child labour, but not working fewer than 28 hours per week, was associated with decreased school attendance. CONCLUSIONS: One in seven OAC in this study were reported to be engaged in child labour. Policy makers and social service providers need to pay close attention to the demands being placed on female OAC, particularly in rural areas and poor households with limited income sources. Programs to promote OAC school attendance may need to focus on the needs of families as well as the OAC.

Reason, risk, and reward: Models for libraries and other stakeholders in an evolving scholarly publishing ecosystem

Scholarly publishing, and scholarly communication more generally, are based on patterns established over many decades and even centuries. Some of these patterns are clearly valuable and intimately related to core values of the academy, but others were based on the exigencies of the past, and new opportunities have brought into question whether it makes sense to persist in supporting old models. New technologies and new publishing models raise the question of how we should fund and operate scholarly publishing and scholarly communication in the future, moving away from a scarcity model based on the exchange of physical goods that restricts access to scholarly literature unless a market-based exchange takes place. This essay describes emerging models that attempt to shift scholarly communication to a more open-access and mission-based approach and that try to retain control of scholarship by academics and the institutions and scholarly societies that support them. It explores changing practices for funding scholarly journals and changing services provided by academic libraries, changes instituted with the end goal of providing more access to more readers, stimulating new scholarship, and removing inefficiencies from a system ready for change. © 2014 by the American Anthropological Association.

CPAG: software for leveraging pleiotropy in GWAS to reveal similarity between human traits links plasma fatty acids and intestinal inflammation.

Meta-analyses of genome-wide association studies (GWAS) have demonstrated that the same genetic variants can be associated with multiple diseases and other complex traits. We present software called CPAG (Cross-Phenotype Analysis of GWAS) to look for similarities between 700 traits, build trees with informative clusters, and highlight underlying pathways. Clusters are consistent with pre-defined groups and literature-based validation but also reveal novel connections. We report similarity between plasma palmitoleic acid and Crohn's disease and find that specific fatty acids exacerbate enterocolitis in zebrafish. CPAG will become increasingly powerful as more genetic variants are uncovered, leading to a deeper understanding of complex traits. CPAG is freely available at www.sourceforge.net/projects/CPAG/.

The 2015 Bioinformatics Open Source Conference (BOSC 2015).

The Bioinformatics Open Source Conference (BOSC) is organized by the Open Bioinformatics Foundation (OBF), a nonprofit group dedicated to promoting the practice and philosophy of open source software development and open science within the biological research community. Since its inception in 2000, BOSC has provided bioinformatics developers with a forum for communicating the results of their latest efforts to the wider research community. BOSC offers a focused environment for developers and users to interact and share ideas about standards; software development practices; practical techniques for solving bioinformatics problems; and approaches that promote open science and sharing of data, results, and software. BOSC is run as a two-day special interest group (SIG) before the annual Intelligent Systems in Molecular Biology (ISMB) conference. BOSC 2015 took place in Dublin, Ireland, and was attended by over 125 people, about half of whom were first-time attendees. Session topics included "Data Science;" "Standards and Interoperability;" "Open Science and Reproducibility;" "Translational Bioinformatics;" "Visualization;" and "Bioinformatics Open Source Project Updates". In addition to two keynote talks and dozens of shorter talks chosen from submitted abstracts, BOSC 2015 included a panel, titled "Open Source, Open Door: Increasing Diversity in the Bioinformatics Open Source Community," that provided an opportunity for open discussion about ways to increase the diversity of participants in BOSC in particular, and in open source bioinformatics in general. The complete program of BOSC 2015 is available online at http://www.open-bio.org/wiki/BOSC_2015_Schedule.

Bayesian Model Averaging in the M-Open Framework

This chapter presents a model averaging approach in the M-open setting using sample re-use methods to approximate the predictive distribution of future observations. It first reviews the standard M-closed Bayesian Model Averaging approach and decision-theoretic methods for producing inferences and decisions. It then reviews model selection from the M-complete and M-open perspectives, before formulating a Bayesian solution to model averaging in the M-open perspective. It constructs optimal weights for MOMA:M-open Model Averaging using a decision-theoretic framework, where models are treated as part of the ‘action space’ rather than unknown states of nature. Using ‘incompatible’ retrospective and prospective models for data from a case-control study, the chapter demonstrates that MOMA gives better predictive accuracy than the proxy models. It concludes with open questions and future directions.