Total column CO_2 measurements at Darwin, Australia – site description and calibration against in situ aircraft profiles

An automated Fourier Transform Spectroscopic (FTS) solar observatory was established in Darwin, Australia in August 2005. The laboratory is part of the Total Carbon Column Observing Network, and measures atmospheric column abundances of CO_2 and O_2 and other gases. Measured CO_2 columns were calibrated against integrated aircraft profiles obtained during the TWP-ICE campaign in January–February 2006, and show good agreement with calibrations for a similar instrument in Park Falls, Wisconsin. A clear-sky low airmass relative precision of 0.1% is demonstrated in the CO2 and O2 retrieved column-averaged volume mixing ratios. The 1% negative bias in the FTS X_(CO_2) relative to the World Meteorological Organization (WMO) calibrated in situ scale is within the uncertainties of the NIR spectroscopy and analysis

Carbon dioxide column abundances at the Wisconsin Tall Tower site

We have developed an automated observatory for measuring atmospheric column abundances of CO_2 and O_2 using near-infrared spectra of the Sun obtained with a high spectral resolution Fourier Transform Spectrometer (FTS). This is the first dedicated laboratory in a new network of ground-based observatories named the Total Carbon Column Observing Network. This network will be used for carbon cycle studies and validation of spaceborne column measurements of greenhouse gases. The observatory was assembled in Pasadena, California, and then permanently deployed to northern Wisconsin during May 2004. It is located in the heavily forested Chequamegon National Forest at the WLEF Tall Tower site, 12 km east of Park Falls, Wisconsin. Under clear sky conditions, ∼0.1% measurement precision is demonstrated for the retrieved column CO_2 abundances. During the Intercontinental Chemical Transport Experiment–North America and CO_2 Boundary Layer Regional Airborne Experiment campaigns in summer 2004, the DC-8 and King Air aircraft recorded eight in situ CO_2 profiles over the WLEF site. Comparison of the integrated aircraft profiles and CO_2 column abundances shows a small bias (∼2%) but an excellent correlation

Methane retrievals from Greenhouse Gases Observing Satellite (GOSAT) shortwave infrared measurements: Performance comparison of proxy and physics retrieval algorithms

We compare two conceptually different methods for determining methane column-averaged mixing ratios image from Greenhouse Gases Observing Satellite (GOSAT) shortwave infrared (SWIR) measurements. These methods account differently for light scattering by aerosol and cirrus. The proxy method retrieves a CO_2 column which, in conjunction with prior knowledge on CO_2 acts as a proxy for scattering effects. The physics-based method accounts for scattering by retrieving three effective parameters of a scattering layer. Both retrievals are validated on a 19-month data set using ground-based X_CH_4 at 12 stations of the Total Carbon Column Observing Network (TCCON), showing comparable performance: for the proxy retrieval we find station-dependent retrieval biases from −0.312% to 0.421% of X_CH_4 a standard deviation of 0.22% and a typical precision of 17 ppb. The physics method shows biases between −0.836% and −0.081% with a standard deviation of 0.24% and a precision similar to the proxy method. Complementing this validation we compared both retrievals with simulated methane fields from a global chemistry-transport model. This identified shortcomings of both retrievals causing biases of up to 1ings and provide a satisfying validation of any methane retrieval from space-borne SWIR measurements, in our opinion it is essential to further expand the network of TCCON stations

The capture of extracellular vesicles endogenously released by xenotransplanted tumours induces an inflammatory reaction in the premetastatic niche

The capture of tumour-derived extracellular vesicles (TEVs) by cells in the tumour microenvironment (TME) contributes to metastasis and notably to the formation of the pre-metastatic niche (PMN). However, due to the challenges associated with modelling release of small EVs in vivo, the kinetics of PMN formation in response to endogenously released TEVs have not been examined. Here, we have studied the endogenous release of TEVs in mice orthotopically implanted with metastatic human melanoma (MEL) and neuroblastoma (NB) cells releasing GFP-tagged EVs (GFTEVs) and their capture by host cells to demonstrate the active contribution of TEVs to metastasis. Human GFTEVs captured by mouse macrophages in vitro resulted in transfer of GFP vesicles and the human exosomal miR-1246. Mice orthotopically implanted with MEL or NB cells showed the presence of TEVs in the blood between 5 and 28 days after implantation. Moreover, kinetic analysis of TEV capture by resident cells relative to the arrival and outgrowth of TEV-producing tumour cells in metastatic organs demonstrated that the capture of TEVs by lung and liver cells precedes the homing of metastatic tumour cells, consistent with the critical roles of TEVs in PMN formation. Importantly, TEV capture at future sites of metastasis was associated with the transfer of miR-1246 to lung macrophages, liver macrophages, and stellate cells. This is the first demonstration that the capture of endogenously released TEVs is organotropic as demonstrated by the presence of TEV-capturing cells only in metastatic organs and their absence in non-metastatic organs. The capture of TEVs in the PMN induced dynamic changes in inflammatory gene expression which evolved to a pro-tumorigenic reaction as the niche progressed to the metastatic state. Thus, our work describes a novel approach to TEV tracking in vivo that provides additional insights into their role in the earliest stages of metastatic progression.The authors would like to thank Mrs. J. Rosenberg for her help in the formatting of the manuscript, and the personnel of the Core Facilities of the Saban Research Institute at Children's Hospital Los Angeles (Flow Cytometry, Extracellular Vesicle, Cell Imaging, and Animal Imaging Cores) for their expertise and assistance. This work was supported by National Institutes of Health/National Cancer Institute grant R01 CA207983 to Y.A. DeClerck

Atmospheric carbon dioxide retrieved from the Greenhouse gases Observing SATellite (GOSAT): Comparison with ground-based TCCON observations and GEOS-Chem model calculations

We retrieved column-averaged dry air mole fractions of atmospheric carbon dioxide (X_CO_2) from backscattered short-wave infrared (SWIR) sunlight measured by the Japanese Greenhouse gases Observing SATellite (GOSAT). Over two years of X_CO_2 retrieved from GOSAT is compared with X_CO_2 inferred from collocated SWIR measurements by seven ground-based Total Carbon Column Observing Network (TCCON) stations. The average difference between GOSAT and TCCON X_CO_2 for individual TCCON sites ranges from −0.87 ppm to 0.77 ppm with a mean value of 0.1 ppm and standard deviation of 0.56 ppm. We find an average bias between all GOSAT and TCCON X_CO_2 retrievals of −0.20 ppm with a standard deviation of 2.26 ppm and a correlation coefficient of 0.75. One year of XCO2 was retrieved from GOSAT globally, which was compared to global 3-D GEOS-Chem chemistry transport model calculations. We find that the latitudinal gradient, seasonal cycles, and spatial variability of GOSAT and GEOS-Chem agree well in general with a correlation coefficient of 0.61. Regional differences between GEOS-Chem model calculations and GOSAT observations are typically less than 1 ppm except for the Sahara and central Asia where a mean difference between 2 to 3 ppm is observed, indicating regional biases in the GOSAT X_CO_2 retrievals unobserved by the current TCCON network. Using a bias correction scheme based on linear regression these regional biases are significantly reduced, approaching the required accuracy for surface flux inversions

Visceral leishmaniasis with cardiac involvement in a dog: a case report

A dog presented with cutaneous nodules, enlarged lymph nodes and oedema in limbs, face and abdomen. The diagnosis of visceral leishmaniasis was established by identification of Leishmania amastigotes within macrophages from skin and popliteal lymph node biopsies. At necropsy, lesions were found in different organs, but it was particularly striking to observe large areas of pallor in the myocardium. Histological examination revealed an intense chronic inflammatory reaction in many organs, and numerous macrophages were found to contain amastigote forms of Leishmania. The inflammatory reaction was especially severe in the heart, where large areas of the myocardium appeared infiltrated with huge numbers of mononuclear immune cells, causing cardiac muscle atrophy and degeneration. Despite the severe inflammation, the number of parasitized macrophages was low in the myocardium, as revealed by immunohistochemical staining of Leishmania amastigotes. Because cardiac involvement is not usually described in this condition, this dog represents a very rare case of canine visceral leishmaniasis with affection of the myocardium

VaRank: a simple and powerful tool for ranking genetic variants:

Background. Most genetic disorders are caused by single nucleotide variations (SNVs) or small insertion/deletions (indels). High throughput sequencing has broadened the catalogue of human variation, including common polymorphisms, rare variations or disease causing mutations. However, identifying one variation among hundreds or thousands of others is still a complex task for biologists, geneticists and clinicians. Results. We have developed VaRank, a command-line tool for the ranking of genetic variants detected by high-throughput sequencing. VaRank scores and prioritizes variants annotated either by Alamut Batch or SnpEff. A barcode allows users to quickly view the presence/absence of variants (with homozygote/heterozygote status) in analyzed samples. VaRank supports the commonly used VCF input format for variants analysis thus allowing it to be easily integrated into NGS bioinformatics analysis pipelines. VaRank has been successfully applied to disease-gene identification as well as to molecular diagnostics setup for several hundred patients. Conclusions. VaRank is implemented in Tcl/Tk, a scripting language which is platform-independent but has been tested only on Unix environment. The source code is available under the GNU GPL, and together with sample data and detailed documentation can be downloaded from http://www.lbgi.fr/VaRank/