A Paleoindian campsite has been uncovered in stratified prehistoric deposits in Caverna da Pedra Pintada at Monte Alegre in the Brazilian Amazon. Fifty-six radiocarbon dates on carbonized plant remains and 13 luminescence dates on lithics and sediment indicate a late Pleistocene age contemporary with North American Paleoindians. Paintings, triangular bifacial spear points, and other tools in the cave document a culture distinct from North American cultures. Carbonized tree fruits and wood and faunal remains reveal a broad-spectrum economy of humid tropical forest and riverine foraging. The existence of this and related cultures east of the Andes changes understanding of the migrations and ecological adaptations of early foragers.

The Collaborative Initiative on Fetal Alcohol Spectrum Disorders (CIFASD) was created in 2003 to further understanding of fetal alcohol spectrum disorders. Clinical and basic science projects collect data across multiple sites using standardized methodology. This paper describes the methodology being used by the clinical projects that pertain to assessment of children and adolescents. Domains being addressed are dysmorphology, neurobehavior, 3D facial imaging, and brain imaging.

Research-networking tools use data-mining and social networking to enable expertise discovery, matchmaking and collaboration, which are important facets of team science and translational research. Several commercial and academic platforms have been built, and many institutions have deployed these products to help their investigators find local collaborators. Recent studies, though, have shown the growing importance of multiuniversity teams in science. Unfortunately, the lack of a standard data-exchange model and resistance of universities to share information about their faculty have presented barriers to forming an institutionally supported national network. This case report describes an initiative, which, in only 6 months, achieved interoperability among seven major research-networking products at 28 universities by taking an approach that focused on addressing institutional concerns and encouraging their participation. With this necessary groundwork in place, the second phase of this effort can begin, which will expand the network's functionality and focus on the end users.

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The early Neolithic of the west Mediterranean The archaeological complex known as the early Neolithic in the west Mediterranean represents the arrival of Neolithic traits in western Europe. Dating to around 5000 BC (Evin 1987), this complex is marked by the appearance of pottery, ground stone tools, and transvcrse projectile points. It continues for about a millennium until middle Neolithic villages, such as Villeneuve-Toulousane, begin to appear. The early Neolithic is characterized by a transitional agricultural subsistence economy. At Aude Valley cave sites, domesticated sheep first appear in aceramic Mesolithic layers with typical Tardenoisian tool assemblages and fauna (Geddes 1983). Examination of these sheep remains show that this strain originated in the Near East (Geddes 1985). Early Neolithic deposits (as defined by the presence of ceramics) are found at many of the same Mesolithic sites and contain similar lithic assemblages as well as a continuation of mixed hunted and domesticated fauna. The presumably novel open-air coastal sites of this period, such as Leucate-Corrège (Guilaine et al. 1984), also appear to represent a mixed economy. Since there is no sudden apparent shift in settlement pattern or economy associated with the early Neolithic, this period appears to be best characterized as a time of gradual transition from hunting and gathering to agriculture.

Many previous attempts by fetal alcohol spectrum disorders researchers to compare data across multiple prospective and retrospective human studies have failed due to both structural differences in the collected data as well as difficulty in coming to agreement on the precise meaning of the terminology used to describe the collected data. Although some groups of researchers have an established track record of successfully integrating data, attempts to integrate data more broadly amongst different groups of researchers have generally faltered. Lack of tools to help researchers share and integrate data has also hampered data analysis. This situation has delayed improving diagnosis, intervention, and treatment before and after birth. We worked with various researchers and research programs in the Collaborative Initiative on Fetal Alcohol Spectrum Disorders (CI-FASD) to develop a set of common data dictionaries to describe the data to be collected, including definitions of terms and specification of allowable values. The resulting data dictionaries were the Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access Author ManuscriptAlcohol. Author manuscript; available in PMC 2011 November 1. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript basis for creating a central data repository (CI-FASD Central Repository) and software tools to input and query data. Data entry restrictions ensure that only data which conform to the data dictionaries reach the CI-FASD Central Repository. The result is an effective system for centralized and unified management of the data collected and analyzed by the initiative, including a secure, long-term data repository. CI-FASD researchers are able to integrate and analyze data of different types, collected using multiple methods, and collected from multiple populations, and data are retained for future reuse in a secure, robust repository.

This paper proposes the creation and application of maturity models to guide institutional strategic investment in research informatics and information technology (research IT) and to provide the ability to measure readiness for clinical and research infrastructure as well as sustainability of expertise. Conducting effective and efficient research in health science increasingly relies upon robust research IT systems and capabilities. Academic health centers are increasing investments in health IT systems to address operational pressures, including rapidly growing data, technological advances, and increasing security and regulatory challenges associated with data access requirements. Current approaches for planning and investment in research IT infrastructure vary across institutions and lack comparable guidance for evaluating investments, resulting in inconsistent approaches to research IT implementation across peer academic health centers as well as uncertainty in linking research IT investments to institutional goals. Maturity models address these issues through coupling the assessment of current organizational state with readiness for deployment of potential research IT investment, which can inform leadership strategy. Pilot work in maturity model development has ranged from using them as a catalyst for engaging medical school IT leaders in planning at a single institution to developing initial maturity indices that have been applied and refined across peer medical schools.

In the USA, the national cyberinfrastructure refers to a system of research supercomputer and other IT facilities and the high speed networks that connect them. These resources have been heavily leveraged by scientists in disciplines such as high energy physics, astronomy, and climatology, but until recently they have been little used by biomedical researchers. We suggest that many of the ‘Big Data’ challenges facing the medical informatics community can be efficiently handled using national-scale cyberinfrastructure. Resources such as the Extreme Science and Discovery Environment, the Open Science Grid, and Internet2 provide economical and proven infrastructures for Big Data challenges, but these resources can be difficult to approach. Specialized web portals, support centers, and virtual organizations can be constructed on these resources to meet defined computational challenges, specifically for genomics. We provide examples of how this has been done in basic biology as an illustration for the biomedical informatics community.