969 resultados para (Herbert McLean),


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Hillel (Herbert) Meyerhof, born 1912

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1994 photo of Sassona (Sony) Meyerhof (1952-) married Baron;

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Verso: "Listening to new recordings. Berlin 1932"

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Handwritten on verso: Jetzt sind wir wieder vergnuegt und gluecklich zusammen. Herzlichst Deine (Illegible name Neni or Leni?)

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Standing l-r: George? son of Max Reiss?, Max Reiss, Harry Gould, Moritz Reiss, Joe Reiss, and Herbert Reiss; Seated l-r: Trude Reiss (wife of Herbert), Else Reiss (mother of Joe), Lily Friedlander Gould, Eva Fantl Gould, Trude Reiss (wife of Joe), and Marta Reiss (wife of Max)

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In political journalism, the battle over agenda-setting between journalists and their sources has been described using many metaphors and concepts. Herbert Gans saw it as a dance where the two parties competed for leadership, arguing that sources usually got the lead. We address the question of how social media, in particular Twitter, contribute to media agenda-building and agenda-setting by looking at how tweets are sourced in election campaign coverage in Australia, Norway and Sweden. Our findings show that the popularity of elite political sources is a common characteristic across all countries and media. Sourcing from Twitter reinforces the power of the political elites to set the agenda of the news media – they are indeed “still leading the dance”. Twitter content travels to the news media as opinions, comments, announcements, factual statements, and photos. Still, there are variations that must be explained both by reference to different political and cultural characteristics of the three countries, as well as by the available resources and journalistic profiles of each media outlet.

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Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 x 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 x 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.

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Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 +/- 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 +/- 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 +/- 0.06 s.e.), and ADHD and major depressive disorder (0.32 +/- 0.07 s.e.), low between schizophrenia and ASD (0.16 +/- 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.