Topological and Algebraic Properties of Chernoff Information between Gaussian Graphs

In this paper, we want to find out the determining factors of Chernoff information in distinguishing a set of Gaussian graphs. We find that Chernoff information of two Gaussian graphs can be determined by the generalized eigenvalues of their covariance matrices. We find that the unit generalized eigenvalue doesn't affect Chernoff information and its corresponding dimension doesn't provide information for classification purpose. In addition, we can provide a partial ordering using Chernoff information between a series of Gaussian trees connected by independent grafting operations. With the relationship between generalized eigenvalues and Chernoff information, we can do optimal linear dimension reduction with least loss of information for classification.Comment: Submitted to Allerton2018, and this version contains proofs of the propositions in the pape

Characterization of lncRNA–miRNA–mRNA Network to Reveal Potential Functional ceRNAs in Bovine Skeletal Muscle

There is growing evidence that non-coding RNAs are emerging as critical regulators of skeletal muscle development. In order to reveal their functional roles and regulatory mechanisms, we constructed a lncRNA–miRNA–mRNA network according to the ceRNA (competitive endogenous RNA) theory, using our high-throughput sequencing data. Subsequently, the network analysis, GO (Gene Ontology) analysis, and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis were performed for functional annotation and exploration of lncRNA ceRNAs. The results uncovered a scale-free characteristics network which exhibited high functional specificity for bovine skeletal muscle development: co-expression lncRNAs were significantly enriched in muscle development related biological processes and the Wnt signaling pathway. Furthermore, GSEA (Gene Set Enrichment Analysis) indicated that the risk score has a tendency to associate with myogenesis, and differentially expressed RNAs were validated by qPCR, further confirming the credibility of our network. In summary, this study provides insights into lncRNA-mediated ceRNA function and mechanisms in bovine skeletal muscle development and will expand our understanding of lncRNA biology in mammals

Treatment patterns of patients diagnosed with major headache disorders: A retrospective claims analysis

Objective: To describe patient characteristics, treatment patterns, and health care costs among patients diagnosed with major headache disorders overall and by type (tension-type headache [TTH], migraine, cluster headache [CH], or \u3e1 primary headache type), and secondarily to evaluate drug treatment patterns among triptan initiators with a major headache diagnosis. Methods: Using US claims data from January 2012 through December 2017, we identified adults with evidence of a major headache disorder: TTH, migraine, or CH; the first diagnosis date was deemed the index date. To evaluate triptan use specifically, patients who initiated triptans were identified; the first triptan claim date was deemed the index date. Patient characteristics, treatment patterns (concomitant treatments, adherence, number of fills), and annual health care costs data were obtained. Results: Of the 418,779 patients diagnosed with major headache disorders, the following 4 cohorts were created: TTH (8%), migraine (87%), CH (1%), and \u3e1 primary headache type (4%). The majority used analgesic (54–73%) and psychotropic (57–81%) drugs, primarily opioids (36–53%). Headache-related costs accounted for one-fifth of all-cause costs. Of the 229,946 patients who initiated triptans, the following 7 study cohorts were analyzed: sumatriptan (68%), rizatriptan (21%), eletriptan (5%), zolmitriptan (3%), naratriptan (2%), frovatriptan (1%), and almotriptan ( Conclusion: The primary headache disorder treatment paradigm is complex, with significant variability. Predominant concomitant use of opioids and switching to opioids is of concern, necessitating solutions to minimize opioid use. Switching to non-oral/fast-acting or targeted preventive therapies should be considered

Chernoff information between Gaussian trees

In this paper, we deal with Gaussian graphical classifiaction problem. We aim to provide a systematic study of the relationship between Chernoff information and topological, as well as algebraic properties of the corresponding Gaussian graphs for the underlying graphical testing problems. We first show the relationship between Chernoff information and generalized eigenvalues of the associated covariance matrices. It is then proved that Chernoff information between two Gaussian trees sharing certain local subtree structures can be transformed into that of two smaller trees. In this way, we provide a sequence of equivalent Gaussian tree pairs in terms of Chernoff Information. Under our proposed grafting operations, bottleneck Gaussian trees, namely, Gaussian trees connected by one such operation, can thus be simplified into two 3-node Gaussian trees. Thereafter, we provide a thorough study about how Chernoff information changes when small differences are accumulated into bigger ones via concatenated grafting operations, as well as partial ordering. In the end, we propose an optimal linear dimension reduction method based on generalized eigenvalues for the purpose of classification, which is proved to achieve maximum Chernoff information among all linear transformations

Near-Ir Two-Photon Fluorescent Sensor For K\u3csup\u3e+\u3c/sup\u3e Imaging In Live Cells

A new two-photon excited fluorescent K+ sensor is reported. The sensor comprises three moieties, a highly selective K+ chelator as the K+ recognition unit, a boron-dipyrromethene (BODIPY) derivative modified with phenylethynyl groups as the fluorophore, and two polyethylene glycol chains to afford water solubility. The sensor displays very high selectivity (\u3e52-fold) in detecting K+ over other physiological metal cations. Upon binding K+, the sensor switches from nonfluorescent to highly fluorescent, emitting red to near-IR (NIR) fluorescence. The sensor exhibited a good two-photon absorption cross section, 500 GM at 940 nm. Moreover, it is not sensitive to pH in the physiological pH range. Time-dependent cell imaging studies via both one- and two-photon fluorescence microscopy demonstrate that the sensor is suitable for dynamic K+ sensing in living cells

Comparative Research on the Thermophysical Properties of Nano-Sized La2(Zr0.7Ce0.3)2O7 Synthesized by Different Routes

La2(Zr0.7Ce0.3)2O7 has been regarded as an ideal candidate for the next generation of thermal barrier coatings (TBCs) due to its prominent superiority. In this paper, the nano-sized La2(Zr0.7Ce0.3)2O7 was synthesized using two different synthetic routes: sol-gel and hydrothermal processes. Various techniques were utilized to assess the differences in the relevant thermophysical properties created by the different synthetic methods. According to the investigations, both samples exhibited pyrochlore structures with an excellent thermal stability. The sample synthesized via the hydrothermal method showed a more uniform particle size and morphology than that obtained through the sol-gel technique. The former also possessed a better sinter-resistance property, a more outstanding TEC (thermal expansion coefficient) and thermal conductivity, and a larger activation energy for crystal growth than the latter. The micro-strain of both samples showed an interesting change as the temperature increased, and 1200 °C was the turning point. Additionally, relative mechanisms were discussed in detail