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Background Single birth cohort studies have been the basis for many discoveries about early life risk factors for childhood asthma but are limited in scope by sample size and characteristics of the local environment and population. The Children’s Respiratory and Environmental Workgroup (CREW) was established to integrate multiple established asthma birth cohorts and to investigate asthma phenotypes and associated causal pathways (endotypes), focusing on how they are influenced by interactions between genetics, lifestyle, and environmental exposures during the prenatal period and early childhood. Methods and results CREW is funded by the NIH Environmental influences on Child Health Outcomes (ECHO) program, and consists of 12 individual cohorts and three additional scientific centers. The CREW study population is diverse in terms of race, ethnicity, geographical distribution, and year of recruitment. We hypothesize that there are phenotypes in childhood asthma that differ based on clinical characteristics and underlying molecular mechanisms. Furthermore, we propose that asthma endotypes and their defining biomarkers can be identified based on personal and early life environmental risk factors. CREW has three phases: 1) to pool and harmonize existing data from each cohort, 2) to collect new data using standardized procedures, and 3) to enroll new families during the prenatal period to supplement and enrich extant data and enable unified systems approaches for identifying asthma phenotypes and endotypes. Conclusions The overall goal of CREW program is to develop a better understanding of how early life environmental exposures and host factors interact to promote the development of specific asthma endotypes.

Recent advances in fluorescence microscopy techniques and tissue clearing, labeling, and staining provide unprecedented opportunities to investigate brain structure and function. These experiments’ images make it possible to catalog brain cell types and define their location, morphology, and connectivity in a native context, leading to a better understanding of normal development and disease etiology. Consistent annotation of metadata is needed to provide the context necessary to understand, reuse, and integrate these data. This report describes an effort to establish metadata standards for three-dimensional (3D) microscopy datasets for use by the Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative and the neuroscience research community. These standards were built on existing efforts and developed with input from the brain microscopy community to promote adoption. The resulting 3D Microscopy Metadata Standards (3D-MMS) includes 91 fields organized into seven categories: Contributors, Funders, Publication, Instrument, Dataset, Specimen, and Image. Adoption of these metadata standards will ensure that investigators receive credit for their work, promote data reuse, facilitate downstream analysis of shared data, and encourage collaboration.

Selecting and implementing a tissue clearing protocol is challenging. Established more than 100 years ago, tissue clearing is still a rapidly evolving field of research. There are currently many published protocols to choose from, and each performs better or worse across a range of key evaluation factors (e.g., speed, cost, tissue stability, fluorescence quenching). Additionally, tissue clearing protocols are often optimized for specific experimental contexts, and applying an existing protocol to a new problem can require a lengthy period of adaptation by trial and error. Although the primary literature and review articles provide a useful starting point for optimization, there is growing recognition that results can vary dramatically with changes to tissue type or antibody used. To help address this issue, we have developed a novel, freely available repository of tissue clearing protocols named T-CLEARE (Tissue CLEAring protocol REpository; https://doryworkspace.org/doryviz ). T-CLEARE incorporates community responses to an open survey designed to capture details not commonly found in the scientific literature, including modifications to published protocols required for specific use cases and instances when tissue clearing protocols did not perform well (negative results). The goal of T-CLEARE is to help the community share evaluations and modifications of tissue clearing protocols for various tissue types and potentially identify best-in-class methods for a given application.

Identifying relevant studies and harmonizing datasets are major hurdles for data reuse. Common Data Elements (CDEs) can help identify comparable study datasets and reduce the burden of retrospective data harmonization, but they have not been required, historically. The collaborative team at PhenX and dbGaP developed an approach to use PhenX variables as a set of CDEs to link phenotypic data and identify comparable studies in dbGaP. Variables were identified as either comparable or related, based on the data collection mode used to harmonize data across mapped datasets. We further added a CDE data field in the dbGaP data submission packet to indicate use of PhenX and annotate linkages in the future. Some 13,653 dbGaP variables from 521 studies were linked through PhenX variable mapping. These variable linkages have been made accessible for browsing and searching in the repository through dbGaP CDE-faceted search filter and the PhenX variable search tool. New features in dbGaP and PhenX enable investigators to identify variable linkages among dbGaP studies and reveal opportunities for cross-study analysis.

The disparate measurement protocols used to collect study data are an intrinsic barrier to combining information from environmental health studies. Using standardized measurement protocols and data standards for environmental exposures addresses this gap by improving data collection quality and consistency. To assess the prevalence of environmental exposures in National Institutes of Health (NIH) public data repositories and resources and to assess the commonality of the data elements, we analyzed clinical measures and exposure assays by comparing the Caribbean Consortium for Research in Environmental and Occupational Health study with selected NIH environmental health resources and studies. Our assessment revealed that (1) environmental assessments are widely collected in these resources, (2) biological assessments are less prevalent, and (3) NIH resources can help identify common data for meta-analysis. We highlight resources to help link environmental exposure data across studies to support data sharing. Including NIH data standards in environmental health research facilitates comparing and combining study data, and the use of NIH resources and adoption of standard measures will allow integration of multiple studies and increase the scientific impact of individual studies.

Purpose The PhenX Toolkit ( www.phenxtoolkit.org ), an online catalog of recommended measurement protocols, facilitates cross-study analyses for research with human participants. The PhenX Steering Committee recommended genomic medicine implementation as a new research domain, with the following scope: genomic knowledge and education (both patients and providers); implementation science; changes in management and treatment; return of results; patient outcomes; and ethical, legal, and social issues (ELSI) associated with genomic research. Methods A seven-member expert Working Group convened in October 2019 to identify well-established measurement protocols for a new genomic medicine implementation domain and used the established PhenX consensus process to select measurement protocols for inclusion in the PhenX Toolkit. Results The Working Group recommended 15 measurement protocols for inclusion in the PhenX Toolkit, with priority given to those with empirical evidence supporting validity. Consortia funded by the National Institutes of Health, and particularly the National Human Genome Research Institute, proved critical in identifying protocols with established utility in this research domain, and identified protocols that were developed through a rigorous process for scope elements that lacked formally validated protocols. Conclusion Use of these protocols, which were released in September 2020, can facilitate standard data collection for genomic medicine implementation research.

The use of standard measures and common data elements in the conduct of tobacco regulatory research (TRR) will improve data comparability and facilitate cross-study analyses and replication of findings to inform the regulatory decisions and actions of the US Food and Drug Administration (FDA) Center for Tobacco Products (CTP). This overview paper introduces the PhenX (consensus measures for Phenotypes and eXposures) initiative to identify common measures and common data elements for use in TRR which have been disseminated in the PhenX Toolkit (https://www.phenxtoolkit.org/). It describes the work of the scientific panel that provided guidance to the project and the TRR Core Collection of measures recommended for use by investigators conducting human-subject tobacco regulatory or related tobacco control research. The use of PhenX TRR measures will promote collaborative research and facilitate data interoperability and validation of outcome assessments to inform the FDA CTP’s regulatory activities.

Introduction: The PhenX Toolkit, an online resource of well-established measures of phenotypes and exposures, now has 16 new measures recommended for assessing rare genetic conditions. Materials and Methods: These measures and their protocols were selected by a working group of domain experts with input from the scientific community. Results: The measures, which cover life stages from birth through adulthood, include clinical scales, characterization of rare genetic conditions, bioassays, and questionnaires. Most are broadly applicable to rare genetic conditions (e.g., family history, growth charts, bone age, and body proportions). Some protocols (e.g., sweat chloride test) target specific conditions. Discussion: The rare genetic condition measures complement the existing measures in the PhenX Toolkit that cover anthropometrics, demographics, mental health, and reproductive history. They are directed at research pertaining to common and complex diseases. PhenX measures are publicly available and are recommended to help standardize assessments across a range of biomedical study designs. To facilitate incorporation of measures into human subjects’ research, the Toolkit offers data collection worksheets and compatible data dictionaries. Conclusion: Widespread use of standard PhenX measures in clinical, translational, and epidemiological research will enable more uniform cross-study comparisons and increase statistical power with the potential for enhancing scientific discovery. Genet Med advance online publication 12 January 2017

In conjunction with an enhanced system for Agrobacterium-mediated plant transformation, a new binary bacterial artificial chromosome (BIBAC) vector has been developed that is capable of transferring at least 150 kb of foreign DNA into a plant nuclear genome. The transferred DNA appears to be intact in the majority of transformed tobacco plants analyzed and is faithfully inherited in the progeny. The ability to introduce high molecular weight DNA into plant chromosomes should accelerate gene identification and genetic engineering of plants and may lead to new approaches in studies of genome organization.

The fifth AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI) will provide a venue for researchers and educators to discuss pedagogical issues and share resources related to teaching AI and using AI in education across a variety of cur- ricular levels (K-12 through postgraduate training), with an emphasis on undergraduate and graduate teaching and learning. The nomina- tion form is available at www.aaai.org/Awards/ feigenbaum.php. 2015 Special Award Nominations AAAI is pleased to announce the continuation of its two special awards in 2015, and is cur- rently seeking nominations for the 2015 AAAI Classic Paper Award, and the AAAI Distin- guished Service Award.