Resistance co-occurrence within first-line anti-tuberculosis (TB) drugs is a common phenomenon. Existing methods based on genetic data analysis of Mycobacterium tuberculosis (MTB) have been able to predict resistance of MTB to individual drugs, but have not considered the resistance co-occurrence and cannot capture latent structure of genomic data that corresponds to lineages.We used a large cohort of TB patients from 16 countries across six continents where whole-genome sequences for each isolate and associated phenotype to anti-TB drugs were obtained using drug susceptibility testing recommended by the World Health Organization. We then proposed an end-to-end multi-task model with deep denoising auto-encoder (DeepAMR) for multiple drug classification and developed DeepAMR_cluster, a clustering variant based on DeepAMR, for learning clusters in latent space of the data. The results showed that DeepAMR outperformed baseline model and four machine learning models with mean AUROC from 94.4% to 98.7% for predicting resistance to four first-line drugs [i.e. isoniazid (INH), ethambutol (EMB), rifampicin (RIF), pyrazinamide (PZA)], multi-drug resistant TB (MDR-TB) and pan-susceptible TB (PANS-TB: MTB that is susceptible to all four first-line anti-TB drugs). In the case of INH, EMB, PZA and MDR-TB, DeepAMR achieved its best mean sensitivity of 94.3%, 91.5%, 87.3% and 96.3%, respectively. While in the case of RIF and PANS-TB, it generated 94.2% and 92.2% sensitivity, which were lower than baseline model by 0.7% and 1.9%, respectively. t-SNE visualization shows that DeepAMR_cluster captures lineage-related clusters in the latent space.The details of source code are provided at http://www.robots.ox.ac.uk/∼davidc/code.php.Supplementary data are available at Bioinformatics online.
We extend the statistical analysis performed by Lissauer et al. in 2012, which demonstrates that the overwhelming majority of Kepler candidate multiple transiting systems (multis) represents true transiting planets, and we develop therefrom a procedure to validate large numbers of planet candidates in multis as bona fide exoplanets. We show that this statistical framework correctly estimates the abundance of false positives already identified around Kepler targets with multiple sets of transit-like signatures based on their abundance around targets with single sets of transit-like signatures. We estimate the number of multis that represent split systems of one or more planets orbiting each component of a binary star system. We use the high reliability rate for multis to validate more than one dozen particularly interesting multi-planet systems herein. Hundreds of additional multi-planet systems are validated in a companion paper by Rowe et al. We note that few very short period (P < 1.6 days) planets orbit within multiple transiting planet systems and discuss possible reasons for their absence. There also appears to be a shortage of planets with periods exceeding a few months in multis.
Eighty planetary systems of two or more planets are known to orbit stars other than the Sun. For most, the data can be sufficiently explained by non-interacting Keplerian orbits, so the dynamical interactions of these systems have not been observed. Here we present 4 sets of lightcurves from the Kepler spacecraft, which each show multiple planets transiting the same star. Departure of the timing of these transits from strict periodicity indicates the planets are perturbing each other: the observed timing variations match the forcing frequency of the other planet. This confirms that these objects are in the same system. Next we limit their masses to the planetary regime by requiring the system remain stable for astronomical timescales. Finally, we report dynamical fits to the transit times, yielding possible values for the planets' masses and eccentricities. As the timespan of timing data increases, dynamical fits may allow detailed constraints on the systems' architectures, even in cases for which high-precision Doppler follow-up is impractical.
Brain metastases (BMs) are diagnosed in 10%-40% of all patients with cancer, and the incidence continues to increase along with the number of long-term survivors. When BMs occur, they are often associated with a myriad of symptoms, including neurologic dysfunction and functional decline; both are difficult to manage and can be distressing for patients and their caregivers. Although clinically significant findings have not kept up with the rapid pace of scientific breakthroughs in understanding the mechanisms of BMs, novel approaches that affect the prognosis of patients with BMs have been introduced in clinical practice. At a Glance • Screening for brain metastases (BMs) is not routinely performed in patients with no neurologic symptoms. However, screening is indicated in lung cancer and possibly in the context of high-risk cancers. • Individual differences in patients warrant a personalized approach in the management of BMs. • Whole brain radiation therapy and steroids are considered to be the cornerstones of treatment for BMs.
We present a method to confirm the planetary nature of objects in systems with multiple transiting exoplanet candidates. This method involves a Fourier-Domain analysis of the deviations in the transit times from a constant period that result from dynamical interactions within the system. The combination of observed anti-correlations in the transit times and mass constraints from dynamical stability allow us to claim the discovery of four planetary systems Kepler-25, Kepler-26, Kepler-27, and Kepler-28, containing eight planets and one additional planet candidate.
We present the results of a search for planetary companions orbiting near hot Jupiter planet candidates (Jupiter-size candidates with orbital periods near 3 d) identified in the Kepler data through its sixth quarter of science operations. Special emphasis is given to companions between the 2∶1 interior and exterior mean-motion resonances. A photometric transit search excludes companions with sizes ranging from roughly two-thirds to five times the size of the Earth, depending upon the noise properties of the target star. A search for dynamically induced deviations from a constant period (transit timing variations) also shows no significant signals. In contrast, comparison studies of warm Jupiters (with slightly larger orbits) and hot Neptune-size candidates do exhibit signatures of additional companions with these same tests. These differences between hot Jupiters and other planetary systems denote a distinctly different formation or dynamical history.
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