Eosinophilic Heart Disease: A Case Report and Review of Literature (Poster).

Hypereosinophilic syndrome is a rare condition and present with nonspecific symptoms. Literature is limited. The involvement of myocardium has some peculiar features. Use of different diagnostic techniques such as echocardiography and MRI can help make the diagnosis of hypereosinophilic syndrome. We are presenting a case with review of the topic

Troponin Elevations After Electroconvulsive Therapy: The Need for Caution

BACKGROUND: Electroconvulsive therapy is used to treat patients with severe or resistant depression. Troponin elevations are associated with an adverse prognosis, and it is well known that central nervous system insults can cause biochemical evidence of cardiac injury. No study previously has studied this with electroconvulsive therapy. METHODS: Patients scheduled for electroconvulsive therapy were enrolled. Clinical information, an electrocardiogram, and a baseline sample for cardiac troponin I and T (cTnI and cTnT) were obtained. Electroconvulsive therapy was done with standard techniques. Subsequently, electrocardiograms and additional samples were obtained. cTnT was measured with the Roche assay and cTnI with the Dade Stratus equipment. Values above the 99th percentile were considered abnormal. RESULTS: Seventy patients completed the study. Four patients had elevated levels of cTn before treatment. In 3 patients, the elevations persisted. Four additional patients developed elevated cTn levels during electroconvulsive therapy. Two of the patients with cTn elevations died. No other events occurred during follow-up. CONCLUSIONS: Elevations of cTn occurred in 11.5% of patients treated with electroconvulsive therapy. Some of the elevations preceded therapy and some occurred during treatment. Given the adverse prognostic importance of cTn elevations in general, in addition to additional studies, an increased degree of medical scrutiny may be appropriate for this group of patients and for those receiving electroconvulsive therapy

An Adaptive Optics Survey of Stellar Variability at the Galactic Center

We present a $\approx 11.5$ year adaptive optics (AO) study of stellar variability and search for eclipsing binaries in the central $\sim 0.4$ pc ($\sim 10''$) of the Milky Way nuclear star cluster. We measure the photometry of 563 stars using the Keck II NIRC2 imager ($K'$-band, $\lambda_0 = 2.124 \text{ } \mu \text{m}$). We achieve a photometric uncertainty floor of $\Delta m_{K'} \sim 0.03$ ($\approx 3\%$), comparable to the highest precision achieved in other AO studies. Approximately half of our sample ($50 \pm 2 \%$) shows variability. $52 \pm 5\%$ of known early-type young stars and $43 \pm 4 \%$ of known late-type giants are variable. These variability fractions are higher than those of other young, massive star populations or late-type giants in globular clusters, and can be largely explained by two factors. First, our experiment time baseline is sensitive to long-term intrinsic stellar variability. Second, the proper motion of stars behind spatial inhomogeneities in the foreground extinction screen can lead to variability. We recover the two known Galactic center eclipsing binary systems: IRS 16SW and S4-258 (E60). We constrain the Galactic center eclipsing binary fraction of known early-type stars to be at least $2.4 \pm 1.7\%$. We find no evidence of an eclipsing binary among the young S-stars nor among the young stellar disk members. These results are consistent with the local OB eclipsing binary fraction. We identify a new periodic variable, S2-36, with a 39.43 day period. Further observations are necessary to determine the nature of this source.Comment: 69 pages, 28 figures, 12 tables. Accepted for publication in The Astrophysical Journa

Extensive error in the number of genes inferred from draft genome assemblies

Current sequencing methods produce large amounts of data, but genome assemblies based on these data are often woefully incomplete. These incomplete and error-filled assemblies result in many annotation errors, especially in the number of genes present in a genome. In this paper we investigate the magnitude of the problem, both in terms of total gene number and the number of copies of genes in specific families. To do this, we compare multiple draft assemblies against higher-quality versions of the same genomes, using several new assemblies of the chicken genome based on both traditional and next-generation sequencing technologies, as well as published draft assemblies of chimpanzee. We find that upwards of 40% of all gene families are inferred to have the wrong number of genes in draft assemblies, and that these incorrect assemblies both add and subtract genes. Using simulated genome assemblies of Drosophila melanogaster, we find that the major cause of increased gene numbers in draft genomes is the fragmentation of genes onto multiple individual contigs. Finally, we demonstrate the usefulness of RNA-Seq in improving the gene annotation of draft assemblies, largely by connecting genes that have been fragmented in the assembly process