The emergent integrated network structure of scientific research

The practice of scientific research is often thought of as individuals and small teams striving for disciplinary advances. Yet as a whole, this endeavor more closely resembles a complex system of natural computation, in which information is obtained, generated, and disseminated more effectively than would be possible by individuals acting in isolation. Currently, the structure of this integrated and innovative landscape of scientific ideas is not well understood. Here we use tools from network science to map the landscape of interconnected research topics covered in the multidisciplinary journal PNAS since 2000. We construct networks in which nodes represent topics of study and edges give the degree to which topics occur in the same papers. The network displays small-world architecture, with dense connectivity within scientific clusters and sparse connectivity between clusters. Notably, clusters tend not to align with assigned article classifications, but instead contain topics from various disciplines. Using a temporal graph, we find that small-worldness has increased over time, suggesting growing efficiency and integration of ideas. Finally, we define a novel measure of interdisciplinarity, which is positively associated with PNAS's impact factor. Broadly, this work suggests that complex and dynamic patterns of knowledge emerge from scientific research, and that structures reflecting intellectual integration may be beneficial for obtaining scientific insight

Evolutionary rates for multivariate traits: the role of selection and genetic variation.

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.A fundamental question in evolutionary biology is the relative importance of selection and genetic architecture in determining evolutionary rates. Adaptive evolution can be described by the multivariate breeders' equation (Δz(-)=Gβ), which predicts evolutionary change for a suite of phenotypic traits (Δz(-)) as a product of directional selection acting on them (β) and the genetic variance-covariance matrix for those traits (G ). Despite being empirically challenging to estimate, there are enough published estimates of G and β to allow for synthesis of general patterns across species. We use published estimates to test the hypotheses that there are systematic differences in the rate of evolution among trait types, and that these differences are, in part, due to genetic architecture. We find some evidence that sexually selected traits exhibit faster rates of evolution compared with life-history or morphological traits. This difference does not appear to be related to stronger selection on sexually selected traits. Using numerous proposed approaches to quantifying the shape, size and structure of G, we examine how these parameters relate to one another, and how they vary among taxonomic and trait groupings. Despite considerable variation, they do not explain the observed differences in evolutionary rates.J.H., T.T. and J.B.W. were supported by NERC, J.H. and J.B.W. by the BBSRC and J.H. by a University Royal Society Fellowship. W.P. was supported by an NERC studentship (awarded to J.H. and T.T.) and I.D. and W.P. were funded by NIH grant no. 1R01GM094424

Congenital knee dislocation: case report

Congenital knee dislocation of knee is a rare condition, with an uncertain incidence in sub-Saharan Africa. The present case report describes the care of a 14 day old female referred to our orthopaedic services with a congenital hyperextended knee deformity. The patient was managed non-operatively with serial manipulation and casting. At 6 months follow up the patient was able to achieve normal passive knee range of motion. The pathophysiology and treatment options of congenital knee dislocations are reviewed

Proton NMR Imaging of Green State Ceramics

High performance ceramic materials in advanced technology applications are becoming of increasing importance. As a result, the necessity of finding new quantitative non-destructive evaluation (QNDE) methods for ceramics is becoming increasingly apparent. This paper explores the applicability of proton NMR imaging to the QNDE of ceramic materials. While proton NMR imaging is clearly well developed in the area of medical applications (1), only a few experiments have been performed to determine the applicability of this technique to the analysis of ceramic bodies (2). Compared to the NMR imaging of soft tissues for medical applications, the magnetic interactions of protons in solids or semi-solids make high resolution image generation more difficult. These interactions both broaden the proton NMR lines and shorten the spin-spin relaxation times. As a result, larger encoding magnetic field gradients and faster gradient switching are required of a NMR imaging system to produce high resolution, high signal-to-noise ratio images of solids

The Importance of Meteorite Collections to Sample Return Missions: Past, Present, and Future Considerations

While much of the scientific community s current attention is drawn to sample return missions, it is the existing meteorite and cosmic dust collections that both provide the paradigms to be tested by these missions and the context for interpreting the results. Recent sample returns from the Stardust and Hayabusa missions provided us with new materials and insights about our Solar System history and processes. As an example, Stardust sampled CAIs among the population of cometary grains, requiring extensive and unexpected radial mixing in the early solar nebula. This finding would not have been possible, however, without extensive studies of meteoritic CAIs that established their high-temperature, inner Solar System formation. Samples returned by Stardust also revealed the first evidence of a cometary amino acid, a discovery that would not have been possible with current in situ flight instrument technology. The Hayabusa mission provided the final evidence linking ordinary chondrites and S asteroids, a hypothesis that developed from centuries of collection and laboratory and ground-based telescopic studies. In addition to these scientific findings, studies of existing meteorite collections have defined and refined the analytical techniques essential to studying returned samples. As an example, the fortuitous fall of the Allende CV3 and Murchison CM2 chondrites within months before the return of Apollo samples allowed testing of new state-of-the-art analytical facilities. The results of those studies not only prepared us to better study lunar materials, but unanticipated discoveries changed many of our concepts about the earliest history and processes of the solar nebula. This synergy between existing collections and future space exploration is certainly not limited to sample return missions. Laboratory studies confirmed the existence of meteorites from Mars and raised the provocative possibility of preservation of ancient microbial life. The laboratory studies in turn led to a new wave of Mars exploration that ultimately could lead to sample return focused on evidence for past or present life. This partnership between collections and missions will be increasingly important in the coming decades as we discover new questions to be addressed and identify targets for for both robotic and human exploration . Nowhere is this more true than in the ultimate search for the abiotic and biotic processes that produced life. Existing collections also provide the essential materials for developing and testing new analytical schemes to detect the rare markers of life and distinguish them from abiotic processes. Large collections of meteorites and the new types being identified within these collections, which come to us at a fraction of the cost of a sample return mission, will continue to shape the objectives of future missions and provide new ways of interpreting returned samples