Learning signals of adverse drug-drug interactions from the unstructured text of electronic health records.

Drug-drug interactions (DDI) account for 30% of all adverse drug reactions, which are the fourth leading cause of death in the US. Current methods for post marketing surveillance primarily use spontaneous reporting systems for learning DDI signals and validate their signals using the structured portions of Electronic Health Records (EHRs). We demonstrate a fast, annotation-based approach, which uses standard odds ratios for identifying signals of DDIs from the textual portion of EHRs directly and which, to our knowledge, is the first effort of its kind. We developed a gold standard of 1,120 DDIs spanning 14 adverse events and 1,164 drugs. Our evaluations on this gold standard using millions of clinical notes from the Stanford Hospital confirm that identifying DDI signals from clinical text is feasible (AUROC=81.5%). We conclude that the text in EHRs contain valuable information for learning DDI signals and has enormous utility in drug surveillance and clinical decision support

Coupled climate model simulations of Mediterranean winter cyclones and large-scale flow patterns

The study aims to evaluate the ability of global, coupled climate models to reproduce the synoptic regime of the Mediterranean Basin. The output of simulations of the 9 models included in the IPCC CMIP3 effort is compared to the NCEP-NCAR reanalyzed data for the period 1961–1990. The study examined the spatial distribution of cyclone occurrence, the mean Mediterranean upper- and lower-level troughs, the inter-annual variation and trend in the occurrence of the Mediterranean cyclones, and the main large-scale circulation patterns, represented by rotated EOFs of 500 hPa and sea level pressure. The models reproduce successfully the two maxima in cyclone density in the Mediterranean and their locations, the location of the average upper- and lower-level troughs, the relative inter-annual variation in cyclone occurrences and the structure of the four leading large scale EOFs. The main discrepancy is the models' underestimation of the cyclone density in the Mediterranean, especially in its western part. The models' skill in reproducing the cyclone distribution is found correlated with their spatial resolution, especially in the vertical. The current improvement in model spatial resolution suggests that their ability to reproduce the Mediterranean cyclones would be improved as well

Can Planets Influence the Horizontal Branch Morphology?

As stars which have planetary systems evolve along the red giant branch and expand, they interact with the close planets. The planets deposit angular momentum and energy into the red giant stars' envelopes, both of which are likely to enhance mass loss on the red giant branch. The enhanced mass loss causes the star to become bluer as it turns to the horizontal branch. I propose that the presence of planetary systems, through this mechanism, can explain some anomalies in horizontal branch morphologies. In particular, planetary systems may be related to the ``second parameter'', which determines the distribution of horizontal branch stars on the Hertzsprung-Russel diagram. The proposed scenario predicts that surviving massive planets or brown dwarfs orbit many of the extreme blue horizontal branch stars, at orbital periods of tens days.Comment: 21 pages, preprint, uses aasms4.st

Neural computations of threat in the aftermath of combat trauma

By combining computational, morphological, and functional analyses, this study relates latent markers of associative threat learning to overt post-traumatic stress disorder (PTSD) symptoms in combat veterans. Using reversal learning, we found that symptomatic veterans showed greater physiological adjustment to cues that did not predict what they had expected, indicating greater sensitivity to prediction errors for negative outcomes. This exaggerated weighting of prediction errors shapes the dynamic learning rate (associability) and value of threat predictive cues. The degree to which the striatum tracked the associability partially mediated the positive correlation between prediction-error weights and PTSD symptoms, suggesting that both increased prediction-error weights and decreased striatal tracking of associability independently contribute to PTSD symptoms. Furthermore, decreased neural tracking of value in the amygdala, in addition to smaller amygdala volume, independently corresponded to higher PTSD symptom severity. These results provide evidence for distinct neurocomputational contributions to PTSD symptoms

Theoretical Considerations on the Properties of Accreting Millisecond Pulsars

We examine a number of evolutionary scenarios for the recently discovered class of accretion-powered millisecond X-ray pulsars in ultracompact binaries, including XTE J0929-314 and XTE J1751-305, with orbital periods of 43.6 and 42.4 minutes, respectively. We focus on a particular scenario that can naturally explain the present-day properties of these systems. This model invokes a donor star that was either very close to the TAMS (i.e., main-sequence turnoff) at the onset of mass transfer or had sufficient time to evolve during the mass-transfer phase. We have run a systematic set of detailed binary evolution calculations with a wide range of initial donor masses and degrees of (nuclear) evolution at the onset of mass transfer. In general, the models whose evolutionary tracks result in the best fits to these ultracompact binaries start mass transfer with orbital periods of ~15 hr, then decrease to a minimum orbital period of less than or about 40 minutes, and finally evolve back up to about 43 minutes. We also carry out a probability analysis based on the measured mass functions of XTE J0929-314 and XTE J1751-305, and combine this with the results of our binary evolution models and find that the donor stars currently have masses in the range of about 0.012 - 0.025 solar masses, and radii of about 0.042 - 0.055 solar radii, and that these radii are likely to be factors of about 1.1 - 1.3 times larger than the corresponding zero-temperature ones. We also find that the interiors of the donors are largely composed of helium and that the surface hydrogen abundances are almost certainly less than 10% (by mass).Comment: 16 pages, 6 figures, 3 table

Mitral regurgitation due to caseous calcification of the mitral annulus: two case reports

Caseous calcification is a rare variant of mitral annular calcification, occurring in about 0.06% of echocardiographic studies performed. It is usually a benign lesion, but it should be differentiated by abscess and tumors. Echocardiography is the most sensitive method to identify caseous calcification which appears typically as a round, calcified mass with an echo-lucent, liquid-like inner part

The Galactic Population of Low- and Intermediate-Mass X-ray Binaries

(abridged) We present the first study that combines binary population synthesis in the Galactic disk and detailed evolutionary calculations of low- and intermediate-mass X-ray binaries (L/IMXBs). We show that the formation probability of IMXBs with initial donor masses of 1.5--4 Msun is typically >~5 times higher than that of standard LMXBs, and suggest that the majority of the observed systems may have descended from IMXBs. Distributions at the current epoch of the orbital periods, donor masses, and mass accretion rates have been computed, as have orbital-period distributions of BMPs. Several significant discrepancies between the theoretical and observed distributions are discussed. The orbital-period distribution of observed BMPs strongly favors cases where the envelope of the neutron-star progenitor is more easily ejected during the common-envelope phase. However, this leads to a >~100-fold overproduction of the theoretical number of luminous X-ray sources relative to the total observed number of LMXBs. X-ray irradiation of the donor star may result in a dramatic reduction in the X-ray active lifetime of L/IMXBs, thus possibly resolving the overproduction problem, as well as the long-standing BMP/LMXB birthrate problem.Comment: 12 pages, emulateapj, submitted to Ap

Computation of protein geometry and its applications: Packing and function prediction

This chapter discusses geometric models of biomolecules and geometric constructs, including the union of ball model, the weigthed Voronoi diagram, the weighted Delaunay triangulation, and the alpha shapes. These geometric constructs enable fast and analytical computaton of shapes of biomoleculres (including features such as voids and pockets) and metric properties (such as area and volume). The algorithms of Delaunay triangulation, computation of voids and pockets, as well volume/area computation are also described. In addition, applications in packing analysis of protein structures and protein function prediction are also discussed.Comment: 32 pages, 9 figure

Annotation analysis for testing drug safety signals using unstructured clinical notes

BackgroundThe electronic surveillance for adverse drug events is largely based upon the analysis of coded data from reporting systems. Yet, the vast majority of electronic health data lies embedded within the free text of clinical notes and is not gathered into centralized repositories. With the increasing access to large volumes of electronic medical data-in particular the clinical notes-it may be possible to computationally encode and to test drug safety signals in an active manner.ResultsWe describe the application of simple annotation tools on clinical text and the mining of the resulting annotations to compute the risk of getting a myocardial infarction for patients with rheumatoid arthritis that take Vioxx. Our analysis clearly reveals elevated risks for myocardial infarction in rheumatoid arthritis patients taking Vioxx (odds ratio 2.06) before 2005.ConclusionsOur results show that it is possible to apply annotation analysis methods for testing hypotheses about drug safety using electronic medical records