1,508 research outputs found

    The Solar Neighborhood. XXXIV. A Search for Planets Orbiting Nearby M Dwarfs using Astrometry

    Get PDF
    Astrometric measurements are presented for seven nearby stars with previously detected planets: six M dwarfs (GJ 317, GJ 667C, GJ 581, GJ 849, GJ 876, and GJ 1214) and one K dwarf (BD -10 3166). Measurements are also presented for six additional nearby M dwarfs without known planets, but which are more favorable to astrometric detections of low mass companions, as well as three binary systems for which we provide astrometric orbit solutions. Observations have baselines of three to thirteen years, and were made as part of the RECONS long-term astrometry and photometry program at the CTIO/SMARTS 0.9m telescope. We provide trigonometric parallaxes and proper motions for all 16 systems, and perform an extensive analysis of the astrometric residuals to determine the minimum detectable companion mass for the 12 M dwarfs not having close stellar secondaries. For the six M dwarfs with known planets, we are not sensitive to planets, but can rule out the presence of all but the least massive brown dwarfs at periods of 2 - 12 years. For the six more astrometrically favorable M dwarfs, we conclude that none have brown dwarf companions, and are sensitive to companions with masses as low as 1 MJupM_{Jup} for periods longer than two years. In particular, we conclude that Proxima Centauri has no Jovian companions at orbital periods of 2 - 12 years. These results complement previously published M dwarf planet occurrence rates by providing astrometrically determined upper mass limits on potential super-Jupiter companions at orbits of two years and longer. As part of a continuing survey, these results are consistent with the paucity of super-Jupiter and brown dwarf companions we find among the over 250 red dwarfs within 25 pc observed longer than five years in our astrometric program.Comment: 18 pages, 5 figures, 4 tables, accepted for publication in A

    A Three Monoclonal Antibody Combination Potently Neutralizes Multiple Botulinum Neurotoxin Serotype E Subtypes.

    Get PDF
    Human botulism is most commonly caused by botulinum neurotoxin (BoNT) serotypes A, B, and E. For this work, we sought to develop a human monoclonal antibody (mAb)-based antitoxin capable of binding and neutralizing multiple subtypes of BoNT/E. Libraries of yeast-displayed single chain Fv (scFv) antibodies were created from the heavy and light chain variable region genes of humans immunized with pentavalent-toxoid- and BoNT/E-binding scFv isolated by Fluorescence-Activated Cell Sorting (FACS). A total of 10 scFv were isolated that bound one or more BoNT/E subtypes with nanomolar-level equilibrium dissociation constants (KD). By diversifying the V-regions of the lead mAbs and selecting for cross-reactivity, we generated three scFv that bound all four BoNT/E subtypes tested at three non-overlapping epitopes. The scFvs were converted to IgG that had KD values for the different BoNT/E subtypes ranging from 9.7 nM to 2.28 pM. An equimolar combination of the three mAbs was able to potently neutralize BoNT/E1, BoNT/E3, and BoNT/E4 in a mouse neutralization assay. The mAbs have potential utility as therapeutics and as diagnostics capable of recognizing multiple BoNT/E subtypes. A derivative of the three-antibody combination (NTM-1633) is in pre-clinical development with an investigational new drug (IND) application filing expected in 2018

    The Resurgence of the Adora2b Receptor as an Immunotherapeutic Target in Pancreatic Cancer

    Get PDF
    Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense desmoplastic stroma that impedes drug delivery, reduces parenchymal blood flow, and suppresses the anti-tumor immune response. The extracellular matrix and abundance of stromal cells result in severe hypoxia within the tumor microenvironment (TME), and emerging publications evaluating PDAC tumorigenesis have shown the adenosine signaling pathway promotes an immunosuppressive TME and contributes to the overall low survival rate. Hypoxia increases many elements of the adenosine signaling pathway, resulting in higher adenosine levels in the TME, further contributing to immune suppression. Extracellular adenosine signals through 4 adenosine receptors (Adora1, Adora2a, Adora2b, Adora3). Of the 4 receptors, Adora2b has the lowest affinity for adenosine and thus, has important consequences when stimulated by adenosine binding in the hypoxic TME. We and others have shown that Adora2b is present in normal pancreas tissue, and in injured or diseased pancreatic tissue, Adora2b levels are significantly elevated. The Adora2b receptor is present on many immune cells, including macrophages, dendritic cells, natural killer cells, natural killer T cells, γδ T cells, B cells, T cells, CD

    Quasars and the Big Blue Bump

    Full text link
    We investigate the ultraviolet-to-optical spectral energy distributions (SEDs) of 17 active galactic nuclei (AGNs) using quasi-simultaneous spectrophotometry spanning 900-9000 Angstrom (rest frame). We employ data from the Far Ultraviolet Spectroscopic Explorer (FUSE), the Hubble Space Telescope (HST), and the 2.1-meter telescope at Kitt Peak National Observatory (KPNO). Taking advantage of the short-wavelength coverage, we are able to study the so-called "big blue bump," the region where the energy output peaks, in detail. Most objects exhibit a spectral break around 1100 Angstrom. Although this result is formally associated with large uncertainty for some objects, there is strong evidence in the data that the far-ultraviolet spectral region is below the extrapolation of the near-ultraviolet-optical slope, indicating a spectral break around 1100 Angstrom. We compare the behavior of our sample to those of non-LTE thin-disk models covering a range in black-hole mass, Eddington ratio, disk inclination, and other parameters. The distribution of ultraviolet-optical spectral indices redward of the break, and far-ultraviolet indices shortward of the break, are in rough agreement with the models. However, we do not see a correlation between the far-ultraviolet spectral index and the black hole mass, as seen in some accretion disk models. We argue that the observed spectral break is intrinsic to AGNs, although intrinsic reddening as well as Comptonization can strongly affect the far-ultraviolet spectral index. We make our data available online in digital format.Comment: 32 pages (10pt), 12 figures. Accepted for publication in Ap

    Cardiovascular magnetic resonance tagging of the right ventricular free wall for the assessment of long axis myocardial function in congenital heart disease

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Right ventricular ejection fraction (RV-EF) has traditionally been used to measure and compare RV function serially over time, but may be a relatively insensitive marker of change in RV myocardial contractile function. We developed a cardiovascular magnetic resonance (CMR) tagging-based technique with a view to rapid and reproducible measurement of RV long axis function and applied it in patients with congenital heart disease.</p> <p>Methods</p> <p>We studied 84 patients: 56 with repaired Tetralogy of Fallot (rTOF); 28 with atrial septal defect (ASD): 13 with and 15 without pulmonary hypertension (RV pressure > 40 mmHG by echocardiography). For comparison, 20 healthy controls were studied. CMR acquisitions included an anatomically defined four chamber cine followed by a cine gradient echo-planar sequence in the same plane with a labelling pre-pulse giving a tag line across the basal myocardium. RV tag displacement was measured with automated registration and tracking of the tag line together with standard measurement of RV-EF.</p> <p>Results</p> <p>Mean RV displacement was higher in the control (26 ± 3 mm) than in rTOF (16 ± 4 mm) and ASD with pulmonary hypertension (18 ± 3 mm) groups, but lower than in the ASD group without (30 ± 4 mm), P < 0.001. The technique was reproducible with inter-study bias ± 95% limits of agreement of 0.7 ± 2.7 mm. While RV-EF was lower in rTOF than in controls (49 ± 9% versus 57 ± 6%, P < 0.001), it did not differ between either ASD group and controls.</p> <p>Conclusions</p> <p>Measurements of RV long axis displacement by CMR tagging showed more differences between the groups studied than did RV-EF, and was reproducible, quick and easy to apply. Further work is needed to assess its potential use for the detection of longitudinal changes in RV myocardial function.</p

    AVIDa-hIL6: A Large-Scale VHH Dataset Produced from an Immunized Alpaca for Predicting Antigen-Antibody Interactions

    Full text link
    Antibodies have become an important class of therapeutic agents to treat human diseases. To accelerate therapeutic antibody discovery, computational methods, especially machine learning, have attracted considerable interest for predicting specific interactions between antibody candidates and target antigens such as viruses and bacteria. However, the publicly available datasets in existing works have notable limitations, such as small sizes and the lack of non-binding samples and exact amino acid sequences. To overcome these limitations, we have developed AVIDa-hIL6, a large-scale dataset for predicting antigen-antibody interactions in the variable domain of heavy chain of heavy chain antibodies (VHHs), produced from an alpaca immunized with the human interleukin-6 (IL-6) protein, as antigens. By leveraging the simple structure of VHHs, which facilitates identification of full-length amino acid sequences by DNA sequencing technology, AVIDa-hIL6 contains 573,891 antigen-VHH pairs with amino acid sequences. All the antigen-VHH pairs have reliable labels for binding or non-binding, as generated by a novel labeling method. Furthermore, via introduction of artificial mutations, AVIDa-hIL6 contains 30 different mutants in addition to wild-type IL-6 protein. This characteristic provides opportunities to develop machine learning models for predicting changes in antibody binding by antigen mutations. We report experimental benchmark results on AVIDa-hIL6 by using neural network-based baseline models. The results indicate that the existing models have potential, but further research is needed to generalize them to predict effective antibodies against unknown mutants. The dataset is available at https://avida-hil6.cognanous.com
    corecore