Using airborne LiDAR Survey to explore historic-era archaeological landscapes of Montserrat in the eastern Caribbean

This article describes what appears to be the first archaeological application of airborne LiDAR survey to historic-era landscapes in the Caribbean archipelago, on the island of Montserrat. LiDAR is proving invaluable in extending the reach of traditional pedestrian survey into less favorable areas, such as those covered by dense neotropical forest and by ashfall from the past two decades of active eruptions by the Soufrière Hills volcano, and to sites in localities that are inaccessible on account of volcanic dangers. Emphasis is placed on two aspects of the research: first, the importance of ongoing, real-time interaction between the LiDAR analyst and the archaeological team in the field; and second, the advantages of exploiting the full potential of the three-dimensional LiDAR point cloud data for purposes of the visualization of archaeological sites and features

Improving the turnaround time of molecular profiling for advanced non-small cell lung cancer: Outcome of a new algorithm integrating multiple approaches

BACKGROUND Molecular tumor profiling to identify oncogenic drivers and actionable mutations has a profound impact on how lung cancer is treated. Especially in the subgroup of non-small cell lung cancer (NSCLC), molecular testing for certain mutations is crucial in daily clinical practice and is recommended by international guidelines. To date, a standardized approach to identify druggable genetic alterations are lacking. We have developed and implemented a new diagnostic algorithm to harmonize the molecular testing of NSCLC. PATIENTS AND METHODS In this retrospective analysis, we reviewed 119 patients diagnosed with NSCLC at the University Hospital Zurich. Tumor samples were analyzed using our standardized diagnostic algorithm: After the histological diagnosis was made, tissue samples were further analyzed by immunohistochemical stainings as well as the real-time PCR test Idylla™. Extracted DNA was further utilized for comprehensive genomic profiling (FoundationOne®CDx, F1CDx). RESULTS Out of the 119 patients were included in this study, 100 patients were diagnosed with non-squamous NSCLC (nsqNSCLC) and 19 with squamous NSCLC (sqNSCLC). The samples from the nsqNSCLC patients underwent testing by Idylla™ and were evaluated by immunohistochemistry (IHC). F1CDx analysis was run on 67 samples and 46 potentially actionable genomic alterations were detected. Ten patients received the indicated targeted treatment. The median time to test results was 4 days for the Idylla test, 5 days for IHC and 13 days for the F1CDx. CONCLUSION In patients with NSCLC, the implementation of a standardized molecular testing algorithm provided information on predictive markers for NSCLC within a few working days. The implementation of broader genomic profiling led to the identification of actionable targets, which would otherwise not have been discovered

Quantum Fluctuations Driven Orientational Disordering: A Finite-Size Scaling Study

The orientational ordering transition is investigated in the quantum generalization of the anisotropic-planar-rotor model in the low temperature regime. The phase diagram of the model is first analyzed within the mean-field approximation. This predicts at $T=0$ a phase transition from the ordered to the disordered state when the strength of quantum fluctuations, characterized by the rotational constant $\Theta$, exceeds a critical value $\Theta_{\rm c}^{MF}$. As a function of temperature, mean-field theory predicts a range of values of $\Theta$ where the system develops long-range order upon cooling, but enters again into a disordered state at sufficiently low temperatures (reentrance). The model is further studied by means of path integral Monte Carlo simulations in combination with finite-size scaling techniques, concentrating on the region of parameter space where reentrance is predicted to occur. The phase diagram determined from the simulations does not seem to exhibit reentrant behavior; at intermediate temperatures a pronounced increase of short-range order is observed rather than a genuine long-range order.Comment: 27 pages, 8 figures, RevTe

Post-stroke inhibition of induced NADPH oxidase type 4 prevents oxidative stress and neurodegeneration

Ischemic stroke is the second leading cause of death worldwide. Only one moderately effective therapy exists, albeit with contraindications that exclude 90% of the patients. This medical need contrasts with a high failure rate of more than 1,000 pre-clinical drug candidates for stroke therapies. Thus, there is a need for translatable mechanisms of neuroprotection and more rigid thresholds of relevance in pre-clinical stroke models. One such candidate mechanism is oxidative stress. However, antioxidant approaches have failed in clinical trials, and the significant sources of oxidative stress in stroke are unknown. We here identify NADPH oxidase type 4 (NOX4) as a major source of oxidative stress and an effective therapeutic target in acute stroke. Upon ischemia, NOX4 was induced in human and mouse brain. Mice deficient in NOX4 (Nox4(-/-)) of either sex, but not those deficient for NOX1 or NOX2, were largely protected from oxidative stress, blood-brain-barrier leakage, and neuronal apoptosis, after both transient and permanent cerebral ischemia. This effect was independent of age, as elderly mice were equally protected. Restoration of oxidative stress reversed the stroke-protective phenotype in Nox4(-/-) mice. Application of the only validated low-molecular-weight pharmacological NADPH oxidase inhibitor, VAS2870, several hours after ischemia was as protective as deleting NOX4. The extent of neuroprotection was exceptional, resulting in significantly improved long-term neurological functions and reduced mortality. NOX4 therefore represents a major source of oxidative stress and novel class of drug target for stroke therapy

Fluorescent carbon dioxide indicators

Over the last decade, fluorescence has become the dominant tool in biotechnology and medical imaging. These exciting advances have been underpinned by the advances in time-resolved techniques and instrumentation, probe design, chemical / biochemical sensing, coupled with our furthered knowledge in biology. Complementary volumes 9 and 10, Advanced Concepts of Fluorescence Sensing: Small Molecule Sensing and Advanced Concepts of Fluorescence Sensing: Macromolecular Sensing, aim to summarize the current state of the art in fluorescent sensing. For this reason, Drs. Geddes and Lakowicz have invited chapters, encompassing a broad range of fluorescence sensing techniques. Some chapters deal with small molecule sensors, such as for anions, cations, and CO2, while others summarize recent advances in protein-based and macromolecular sensors. The Editors have, however, not included DNA or RNA based sensing in this volume, as this were reviewed in Volume 7 and is to be the subject of a more detailed volume in the near future

Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data

Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. Complimentary large data sets of in situ RNA hybridization images for different stages of the fly embryo elucidate the spatial expression patterns. Results: Using a semi-supervised approach, constrained clustering with mixture models, we can find clusters of genes exhibiting spatio-temporal similarities in expression, or syn-expression. The temporal gene expression measurements are taken as primary data for which pairwise constraints are computed in an automated fashion from raw in situ images without the need for manual annotation. We investigate the influence of these pairwise constraints in the clustering and discuss the biological relevance of our results. Conclusion: Spatial information contributes to a detailed, biological meaningful analysis of temporal gene expression data. Semi-supervised learning provides a flexible, robust and efficient framework for integrating data sources of differing quality and abundance

Detailed spectral and morphological analysis of the shell type SNR RCW 86

Aims: We aim for an understanding of the morphological and spectral properties of the supernova remnant RCW~86 and for insights into the production mechanism leading to the RCW~86 very high-energy gamma-ray emission. Methods: We analyzed High Energy Spectroscopic System data that had increased sensitivity compared to the observations presented in the RCW~86 H.E.S.S. discovery publication. Studies of the morphological correlation between the 0.5-1~keV X-ray band, the 2-5~keV X-ray band, radio, and gamma-ray emissions have been performed as well as broadband modeling of the spectral energy distribution with two different emission models. Results:We present the first conclusive evidence that the TeV gamma-ray emission region is shell-like based on our morphological studies. The comparison with 2-5~keV X-ray data reveals a correlation with the 0.4-50~TeV gamma-ray emission.The spectrum of RCW~86 is best described by a power law with an exponential cutoff at $E_{cut}=(3.5\pm 1.2_{stat})$ TeV and a spectral index of $\Gamma$~$1.6\pm 0.2$. A static leptonic one-zone model adequately describes the measured spectral energy distribution of RCW~86, with the resultant total kinetic energy of the electrons above 1 GeV being equivalent to $\sim$0.1\% of the initial kinetic energy of a Type I a supernova explosion. When using a hadronic model, a magnetic field of $B$~100$\mu$G is needed to represent the measured data. Although this is comparable to formerly published estimates, a standard E$^{-2}$ spectrum for the proton distribution cannot describe the gamma-ray data. Instead, a spectral index of $\Gamma_p$~1.7 would be required, which implies that ~$7\times 10^{49}/n_{cm^{-3}}$erg has been transferred into high-energy protons with the effective density $n_{cm^{-3}}=n/ 1$ cm^-3. This is about 10\% of the kinetic energy of a typical Type Ia supernova under the assumption of a density of 1~cm^-3.Comment: accepted for publication by A&

The exceptionally powerful TeV gamma-ray emitters in the Large Magellanic Cloud

The Large Magellanic Cloud, a satellite galaxy of the Milky Way, has been observed with the High Energy Stereoscopic System (H.E.S.S.) above an energy of 100 billion electron volts for a deep exposure of 210 hours. Three sources of different types were detected: the pulsar wind nebula of the most energetic pulsar known N 157B, the radio-loud supernova remnant N 132D and the largest non-thermal X-ray shell - the superbubble 30 Dor C. The unique object SN 1987A is, surprisingly, not detected, which constrains the theoretical framework of particle acceleration in very young supernova remnants. These detections reveal the most energetic tip of a gamma-ray source population in an external galaxy, and provide via 30 Dor C the unambiguous detection of gamma-ray emission from a superbubble.Comment: Published in Science Magazine (Jan. 23, 2015). This ArXiv version has the supplementary online material incorporated as an appendix to the main pape

Molecular characterization of Miraflores peach variety and relatives using SSRs

The definitive version is published in: http://www.sciencedirect.com/science/journal/03044238Some traditional peach varieties, originated from the region of Aragón (Spain), were analysed by SSRs (Simple Sequence Repeats). The aim of this research was to characterize 19 clones related to ‘Miraflores’ variety, with unknown pedigrees, to assess their genetic diversity and to elucidate their possible relationships with 10 traditional peach varieties. Twenty SSR primer pairs with high levels of polymorphism, which have been previously developed for peach, were used in this study. A total of 46 alleles were obtained for all the microsatellites studied, ranging from one to six alleles per locus, with a mean value of 2.3 alleles per locus. Fourteen SSRs were polymorphic in the set of varieties studied and permitted to distinguish 16 different genotypes out of the 30 initially studied, although fourteen ‘Miraflores’ clones showed identical gel profiles. The genetic distance matrix was used to construct Neighbor joining cluster and to perform principal coordinate analysis which allowed the arrangement of all the genotypes according to their genetic relationships. The genetic relationships among these traditional peach varieties, and in particular among ‘Miraflores’ clones are discussed. The obtained results confirm that microsatellite markers are very useful for these purposes.We are thankful to T.N. Zhebentyayeva and G.L. Reighard for helpful comments on the manuscript. This research was funded by CICYT (Comisión Interministerial de Ciencia y Tecnología, AGL2002-04219 and AGL 2005-05533), INIA (Instituto Nacional de Investigación y Tecnología Agraria y Alimentación, RF03-014-C2), Bilateral Spain-France (HF03-273) and DGA (A28, A44) projects and co-funded by the European Regional Development Fund. M. Bouhadida was supported by a fellowship from the AECI (Agencia Española de Cooperación Internacional) of the Spanish Ministry of Foreign Affairs.Peer reviewe