Surface-bounded growth modeling applied to human mandibles

From a set of longitudinal three-dimensional scans of the same anatomical structure, we have accurately modeled the temporal shape and size changes using a linear shape model. On a total of 31 computed tomography scans of the mandible from six patients, 14851 semilandmarks are found automatically using shape features and a new algorithm called geometry-constrained diffusion. The semilandmarks are mapped into Procrustes space. Principal component analysis extracts a one-dimensional subspace, which is used to construct a linear growth model. The worst case mean modeling error in a cross validation study is 3.7 mm

Analyzing 2D gel images using a two-component empirical bayes model

<p>Abstract</p> <p>Background</p> <p>Two-dimensional polyacrylomide gel electrophoresis (2D gel, 2D PAGE, 2-DE) is a powerful tool for analyzing the proteome of a organism. Differential analysis of 2D gel images aims at finding proteins that change under different conditions, which leads to large-scale hypothesis testing as in microarray data analysis. Two-component empirical Bayes (EB) models have been widely discussed for large-scale hypothesis testing and applied in the context of genomic data. They have not been implemented for the differential analysis of 2D gel data. In the literature, the mixture and null densities of the test statistics are estimated separately. The estimation of the mixture density does not take into account assumptions about the null density. Thus, there is no guarantee that the estimated null component will be no greater than the mixture density as it should be.</p> <p>Results</p> <p>We present an implementation of a two-component EB model for the analysis of 2D gel images. In contrast to the published estimation method, we propose to estimate the mixture and null densities simultaneously using a constrained estimation approach, which relies on an iteratively re-weighted least-squares algorithm. The assumption about the null density is naturally taken into account in the estimation of the mixture density. This strategy is illustrated using a set of 2D gel images from a factorial experiment. The proposed approach is validated using a set of simulated gels.</p> <p>Conclusions</p> <p>The two-component EB model is a very useful for large-scale hypothesis testing. In proteomic analysis, the theoretical null density is often not appropriate. We demonstrate how to implement a two-component EB model for analyzing a set of 2D gel images. We show that it is necessary to estimate the mixture density and empirical null component simultaneously. The proposed constrained estimation method always yields valid estimates and more stable results. The proposed estimation approach proposed can be applied to other contexts where large-scale hypothesis testing occurs.</p

Probing the crossover in CO desorption from single crystal to nanoparticulate Ru model catalysts

cited By 10International audienceUsing model catalysts, we demonstrate that CO desorption from Ru surfaces can be switched from that typical of single crystal surfaces to one more characteristic of supported nanoparticles. First, the CO desorption behaviour from Ru nanoparticles supported on highly oriented pyrolytic graphite was studied. Both mass-selected and thermally evaporated nanoparticles were deposited. TPD spectra from the mass-selected nanoparticles exhibit a desorption peak located around 410 K with a broad shoulder extending from around 480 K to 600 K, while spectra obtained from thermally evaporated nanoparticles exhibit a single broad feature from ∼350 K to ∼450 K. A room temperature deposited 50 Å thick Ru film displays a characteristic nanoparticle-like spectrum with a broad desorption feature at ∼420 K and a shoulder extending from ∼450 K to ∼600 K. Subsequent annealing of this film at 900 K produced a polycrystalline morphology of flat Ru(001) terraces separated by monatomic steps. The CO desorption spectrum from this surface resembles that obtained on single crystal Ru(001) with two large desorption features located at 390 K and 450 K due to molecular desorption from terrace sites, and a much smaller peak at ∼530 K due to desorption of dissociatively adsorbed CO at step sites. In a second experiment, ion sputtering was used to create surface defects on a Ru(0 1 54) single crystal surface. A gradual shift away from the desorption spectrum typical of a Ru(001) surface towards one resembling desorption from supported Ru nanoparticles was observed with increasing sputter time. © 2011 the Owner Societies

Marine resource abundance drove pre-agricultural population increase in Stone Age Scandinavia

How climate and ecology affect key cultural transformations remains debated in the context of long-term socio-cultural development because of spatially and temporally disjunct climate and archaeological records. The introduction of agriculture triggered a major population increase across Europe. However, in Southern Scandinavia it was preceded by ~500 years of sustained population growth. Here we show that this growth was driven by long-term enhanced marine production conditioned by the Holocene Thermal Maximum, a time of elevated temperature, sea level and salinity across coastal waters. We identify two periods of increased marine production across trophic levels (P1 7600–7100 and P2 6400–5900 cal. yr BP) that coincide with markedly increased mollusc collection and accumulation of shell middens, indicating greater marine resource availability. Between ~7600–5900 BP, intense exploitation of a warmer, more productive marine environment by Mesolithic hunter-gatherers drove cultural development, including maritime technological innovation, and from ca. 6400–5900 BP, underpinned a ~four-fold human population growth

Polarimetric SAR Image Segmentation with B-Splines and a New Statistical Model

We present an approach for polarimetric Synthetic Aperture Radar (SAR) image region boundary detection based on the use of B-Spline active contours and a new model for polarimetric SAR data: the GHP distribution. In order to detect the boundary of a region, initial B-Spline curves are specified, either automatically or manually, and the proposed algorithm uses a deformable contours technique to find the boundary. In doing this, the parameters of the polarimetric GHP model for the data are estimated, in order to find the transition points between the region being segmented and the surrounding area. This is a local algorithm since it works only on the region to be segmented. Results of its performance are presented

Integrated Brain Atlas for Unbiased Mapping of Nervous System Effects Following Liraglutide Treatment

Light Sheet Fluorescence Microscopy (LSFM) of whole organs, in particular the brain, offers a plethora of biological data imaged in 3D. This technique is however often hindered by cumbersome non-Automated analysis methods. Here we describe an approach to fully automate the analysis by integrating with data from the Allen Institute of Brain Science (AIBS), to provide precise assessment of the distribution and action of peptide-based pharmaceuticals in the brain. To illustrate this approach, we examined the acute central nervous system effects of the glucagon-like peptide-1 (GLP-1) receptor agonist liraglutide. Peripherally administered liraglutide accessed the hypothalamus and brainstem, and led to activation in several brain regions of which most were intersected

Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage

Antimicrobial resistance (AMR) is a serious threat to global public health, but obtaining representative data on AMR for healthy human populations is difficult. Here, we use meta-genomic analysis of untreated sewage to characterize the bacterial resistome from 79 sites in 60 countries. We find systematic differences in abundance and diversity of AMR genes between Europe/North-America/Oceania and Africa/Asia/South-America. Antimicrobial use data and bacterial taxonomy only explains a minor part of the AMR variation that we observe. We find no evidence for cross-selection between antimicrobial classes, or for effect of air travel between sites. However, AMR gene abundance strongly correlates with socio-economic, health and environmental factors, which we use to predict AMR gene abundances in all countries in the world. Our findings suggest that global AMR gene diversity and abundance vary by region, and that improving sanitation and health could potentially limit the global burden of AMR. We propose metagenomic analysis of sewage as an ethically acceptable and economically feasible approach for continuous global surveillance and prediction of AMR.Peer reviewe

The Open Innovation in Science research field: a collaborative conceptualisation approach

Openness and collaboration in scientific research are attracting increasing attention from scholars and practitioners alike. However, a common understanding of these phenomena is hindered by disciplinary boundaries and disconnected research streams. We link dispersed knowledge on Open Innovation, Open Science, and related concepts such as Responsible Research and Innovation by proposing a unifying Open Innovation in Science (OIS) Research Framework. This framework captures the antecedents, contingencies, and consequences of open and collaborative practices along the entire process of generating and disseminating scientific insights and translating them into innovation. Moreover, it elucidates individual-, team-, organisation-, field-, and society‐level factors shaping OIS practices. To conceptualise the framework, we employed a collaborative approach involving 47 scholars from multiple disciplines, highlighting both tensions and commonalities between existing approaches. The OIS Research Framework thus serves as a basis for future research, informs policy discussions, and provides guidance to scientists and practitioners