ABSTRACT We present astrophysical false positive probability calculations for every Kepler Object of Interest (KOI)-the first large-scale demonstration of a fully automated transiting planet ...validation procedure. Out of 7056 KOIs, we determine that 1935 have probabilities <1% of being astrophysical false positives, and thus may be considered validated planets. Of these, 1284 have not yet been validated or confirmed by other methods. In addition, we identify 428 KOIs that are likely to be false positives, but have not yet been identified as such, though some of these may be a result of unidentified transit timing variations. A side product of these calculations is full stellar property posterior samplings for every host star, modeled as single, binary, and triple systems. These calculations use vespa, a publicly available Python package that is able to be easily applied to any transiting exoplanet candidate.
ABSTRACT The K2 Mission uses the Kepler spacecraft to obtain high-precision photometry over 80 day campaigns in the ecliptic plane. The Ecliptic Plane Input Catalog (EPIC) provides coordinates, ...photometry, and kinematics based on a federation of all-sky catalogs to support target selection and target management for the K2 mission. We describe the construction of the EPIC, as well as modifications and shortcomings of the catalog. Kepler magnitudes (Kp) are shown to be accurate to 0.1 mag for the Kepler field, and the EPIC is typically complete to Kp 17 (Kp 19 for campaigns covered by Sloan Digital Sky Survey). We furthermore classify 138,600 targets in Campaigns 1-8 ( 88% of the full target sample) using colors, proper motions, spectroscopy, parallaxes, and galactic population synthesis models, with typical uncertainties for G-type stars of 3% in , 0.3 dex in , 40% in radius, 10% in mass, and 40% in distance. Our results show that stars targeted by K2 are dominated by K-M dwarfs ( 41% of all selected targets), F-G dwarfs ( 36%), and K giants ( 21%), consistent with key K2 science programs to search for transiting exoplanets and galactic archeology studies using oscillating red giants. However, we find significant variation of the fraction of cool dwarfs with galactic latitude, indicating a target selection bias due to interstellar reddening and increased contamination by giant stars near the galactic plane. We discuss possible systematic errors in the derived stellar properties, and differences with published classifications for K2 exoplanet host stars. The EPIC is hosted at the Mikulski Archive for Space Telescopes (MAST): http://archive.stsci.edu/k2/epic/search.php.
The relative roles of the endosomal TLR3/7/8 versus the intracellular RNA helicases RIG-I and MDA5 in viral infection is much debated. We investigated the roles of each pattern recognition receptor ...in rhinovirus infection using primary bronchial epithelial cells. TLR3 was constitutively expressed; however, RIG-I and MDA5 were inducible by 8-12 h following rhinovirus infection. Bronchial epithelial tissue from normal volunteers challenged with rhinovirus in vivo exhibited low levels of RIG-I and MDA5 that were increased at day 4 post infection. Inhibition of TLR3, RIG-I and MDA5 by siRNA reduced innate cytokine mRNA, and increased rhinovirus replication. Inhibition of TLR3 and TRIF using siRNA reduced rhinovirus induced RNA helicases. Furthermore, IFNAR1 deficient mice exhibited RIG-I and MDA5 induction early during RV1B infection in an interferon independent manner. Hence anti-viral defense within bronchial epithelium requires co-ordinated recognition of rhinovirus infection, initially via TLR3/TRIF and later via inducible RNA helicases.
The Kepler Mission was designed to identify and characterize transiting planets in the Kepler Field of View and to determine their occurrence rates. Emphasis was placed on identification of ...Earth-size planets orbiting in the Habitable Zone of their host stars. Science data were acquired for a period of four years. Long-cadence data with 29.4 min sampling were obtained for ∼200,000 individual stellar targets in at least one observing quarter in the primary Kepler Mission. Light curves for target stars are extracted in the Kepler Science Data Processing Pipeline, and are searched for transiting planet signatures. A Threshold Crossing Event is generated in the transit search for targets where the transit detection threshold is exceeded and transit consistency checks are satisfied. These targets are subjected to further scrutiny in the Data Validation (DV) component of the Pipeline. Transiting planet candidates are characterized in DV, and light curves are searched for additional planets after transit signatures are modeled and removed. A suite of diagnostic tests is performed on all candidates to aid in discrimination between genuine transiting planets and instrumental or astrophysical false positives. Data products are generated per target and planet candidate to document and display transiting planet model fit and diagnostic test results. These products are exported to the Exoplanet Archive at the NASA Exoplanet Science Institute, and are available to the community. We describe the DV architecture and diagnostic tests, and provide a brief overview of the data products. Transiting planet modeling and the search for multiple planets on individual targets are described in a companion paper. The final revision of the Kepler Pipeline code base is available to the general public through GitHub. The Kepler Pipeline has also been modified to support the Transiting Exoplanet Survey Satellite (TESS) Mission which is expected to commence in 2018.
To validate currently used recurrence prediction models for renal cell carcinoma (RCC) by using prospective data from the ASSURE (ECOG-ACRIN E2805; Adjuvant Sorafenib or Sunitinib for Unfavorable ...Renal Carcinoma) adjuvant trial.
Eight RCC recurrence models (University of California at Los Angeles Integrated Staging System UISS; Stage, Size, Grade, and Necrosis SSIGN; Leibovich; Kattan; Memorial Sloan Kettering Cancer Center MSKCC; Yaycioglu; Karakiewicz; and Cindolo) were selected on the basis of their use in clinical practice and clinical trial designs. These models along with the TNM staging system were validated using 1,647 patients with resected localized high-grade or locally advanced disease (≥ pT1b grade 3 and 4/pTanyN1Mo) from the ASSURE cohort. The predictive performance of the model was quantified by assessing its discriminatory and calibration abilities.
Prospective validation of predictive and prognostic models for localized RCC showed a substantial decrease in each of the predictive abilities of the model compared with their original and externally validated discriminatory estimates. Among the models, the SSIGN score performed best (0.688; 95% CI, 0.686 to 0.689), and the UISS model performed worst (0.556; 95% CI, 0.555 to 0.557). Compared with the 2002 TNM staging system (C-index, 0.60), most models only marginally outperformed standard staging. Importantly, all models, including TNM, demonstrated statistically significant variability in their predictive ability over time and were most useful within the first 2 years after diagnosis.
In RCC, as in many other solid malignancies, clinicians rely on retrospective prediction tools to guide patient care and clinical trial selection and largely overestimate their predictive abilities. We used prospective collected adjuvant trial data to validate existing RCC prediction models and demonstrate a sharp decrease in the predictive ability of all models compared with their previous retrospective validations. Accordingly, we recommend prospective validation of any predictive model before implementing it into clinical practice and clinical trial design.
Single source and multiple donor (mixed) samples of human mitochondrial DNA were analyzed and compared using the MinION and the MiSeq platforms. A generalized variant detection strategy was employed ...to provide a cursory framework for evaluating the reliability and accuracy of mitochondrial sequences produced by the MinION. The feasibility of long-read phasing was investigated to establish its efficacy in quantitatively distinguishing and deconvolving individuals in a mixture. Finally, a proof-of-concept was demonstrated by integrating both platforms in a hybrid assembly that leverages solely mixture data to accurately reconstruct full mitochondrial genomes.
ABSTRACT We present results of the final Kepler Data Processing Pipeline search for transiting planet signals in the full 17-quarter primary mission data set. The search includes a total of 198,709 ...stellar targets, of which 112,046 were observed in all 17 quarters and 86,663 in fewer than 17 quarters. We report on 17,230 targets for which at least one transit signature is identified that meets the specified detection criteria: periodicity, minimum of three observed transit events, detection statistic (i.e., signal-to-noise ratio) in excess of the search threshold, and passing grade on three statistical transit consistency tests. Light curves for which a transit signal is identified are iteratively searched for additional signatures after a limb-darkened transiting planet model is fitted to the data and transit events are removed. The search for additional planets adds 16,802 transit signals for a total of 34,032; this far exceeds the number of transit signatures identified in prior pipeline runs. There was a strategic emphasis on completeness over reliability for the final Kepler transit search. A comparison of the transit signals against a set of 3402 well-established, high-quality Kepler Objects of Interest yields a recovery rate of 99.8%. The high recovery rate must be weighed against a large number of false-alarm detections. We examine characteristics of the planet population implied by the transiting planet model fits with an emphasis on detections that would represent small planets orbiting in the habitable zone of their host stars.
Risk stratification for localized renal cell carcinoma (RCC) relies heavily on retrospective models, limiting their generalizability to contemporary cohorts.
To introduce a contemporary RCC ...prognostic model, developed using prospective, highly annotated data from a phase III adjuvant trial.
The model utilizes outcome data from the ECOG-ACRIN 2805 (ASSURE) RCC trial.
The primary outcome for the model is disease-free survival (DFS), with overall survival (OS) and early disease progression (EDP) as secondary outcomes. Model performance was assessed using discrimination and calibration tests.
A total of 1735 patients were included in the analysis, with 887 DFS events occurring over a median follow-up of 9.6 yr. Five common tumor variables (histology, size, grade, tumor necrosis, and nodal involvement) were included in each model. Tumor histology was the single most powerful predictor for each model outcome. The C-statistics at 1 yr were 78.4% and 81.9% for DFS and OS, respectively. Degradation of the DFS, DFS validation set, and OS model's discriminatory ability was seen over time, with a global c-index of 68.0% (95% confidence interval or CI 65.5, 70.4), 68.6% 65.1%, 72.2%, and 69.4% (95% CI 66.9%, 71.9%, respectively. The EDP model had a c-index of 75.1% (95% CI 71.3, 79.0).
We introduce a contemporary RCC recurrence model built and internally validated using prospective and highly annotated data from a clinical trial. Performance characteristics of the current model exceed available prognostic models with the added benefit of being histology inclusive and TNM agnostic.
Important decisions, including treatment protocols, clinical trial eligibility, and life planning, rest on our ability to predict cancer outcomes accurately. Here, we introduce a contemporary renal cell carcinoma prognostic model leveraging high-quality data from a clinical trial. The current model predicts three outcome measures commonly utilized in clinical practice and exceeds the predictive ability of available prognostic models.
We introduce a contemporary renal cell carcinoma prognostic model with an emphasis on clinical applicability and generalizability by leveraging high-quality data from a clinical trial (ECOG-ACRIN 2805). The current model exceeds the predictive ability of currently available prognostic models.
We provide updates to the Kepler planet candidate sample based upon nearly two years of high-precision photometry (i.e., Q1-Q8). From an initial list of nearly 13,400 threshold crossing events, 480 ...new host stars are identified from their flux time series as consistent with hosting transiting planets. Potential transit signals are subjected to further analysis using the pixel-level data, which allows background eclipsing binaries to be identified through small image position shifts during transit. We also re-evaluate Kepler Objects of Interest (KOIs) 1-1609, which were identified early in the mission, using substantially more data to test for background false positives and to find additional multiple systems. Combining the new and previous KOI samples, we provide updated parameters for 2738 Kepler planet candidates distributed across 2017 host stars. From the combined Kepler planet candidates, 472 are new from the Q1-Q8 data examined in this study. The new Kepler planet candidates represent ~40% of the sample with R sub(P) ~ 1 R sub(+ in circle) and represent ~40% of the low equilibrium temperature (T sub(eq) < 300 K) sample. We review the known biases in the current sample of Kepler planet candidates relevant to evaluating planet population statistics with the current Kepler planet candidate sample.
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