Cheapest Is dearest, though far from professional: A qualitative study on the use of social media during the Federal Election 2021 in Germany

Like in other areas, the importance of social media in the German political communication landscape has rapidly grown in recent years. The purpose of this study is to examine how the communication professionals of the different parties of the German Bundestag describe and characterize the role of social media in their political communication, especially in the last federal election in 2021. This research fills a critical gap by investigating 13 semiopen qualitative interviews with both political and strategic officials of the eight parties represented in the German Bundestag. By doing so, it provides insights into current and future social media practices and their level of professionalization in the German political sphere. Both the sample and focus of this study are, to our knowledge, unique in their nature. The results indicate that, while social media is seen as one of the most important channels to both inform and communicate with potential voters, the professionalization in the field seems to be on a relatively low level. Namely, both strategic and political professionals criticize a lack of human, time, and financial resources. Therefore, the parties lack behind in their practices, particularly considering the newest trends and possibilities of social media like big data, algorithms, or monitoring practices. These results suggest that previous assumptions regarding social media as a cheap and resource-efficient practice are outdated. However, the communicators voice future efforts to catch up on these topics. Further research is needed to investigate how the parties meet these intents

Fallstricke und Erfolgsfaktoren bei der Einführung digitaler Technologien in Kommunikationsabteilungen: Eine qualitative Studie zu den CommTech-Erfahrungen von Kommunikationsverantwortlichen, Beratungen und Softwareanbietern in Deutschland

Ergebnisbericht zu einer qualitativen Studie bei Entscheiden in Kommunikationsabteilungen von Unternehmen, Beratungen und Technologiedienstleistern in Deutschland zur Einführung digitaler Technologien (CommTech) in den Arbeitsprozessen der Unternehmenskommunikation

Fallstricke und Erfolgsfaktoren bei der Einführung digitaler Technologien in Kommunikationsabteilungen: Eine qualitative Studie zu den CommTech-Erfahrungen von Kommunikationsverantwortlichen, Beratungen und Softwareanbietern in Deutschland

Ergebnisbericht zu einer qualitativen Studie bei Entscheiden in Kommunikationsabteilungen von Unternehmen, Beratungen und Technologiedienstleistern in Deutschland zur Einführung digitaler Technologien (CommTech) in den Arbeitsprozessen der Unternehmenskommunikation

Fallstricke und Erfolgsfaktoren bei der Einführung digitaler Technologien in Kommunikationsabteilungen: Eine qualitative Studie zu den CommTech-Erfahrungen von Kommunikationsverantwortlichen, Beratungen und Softwareanbietern in Deutschland

Ergebnisbericht zu einer qualitativen Studie bei Entscheiden in Kommunikationsabteilungen von Unternehmen, Beratungen und Technologiedienstleistern in Deutschland zur Einführung digitaler Technologien (CommTech) in den Arbeitsprozessen der Unternehmenskommunikation

Enrichment of anaerobic nitrate-dependent methanotrophic ‘Candidatus Methanoperedens nitroreducens’ archaea from an Italian paddy field soil

Paddy fields are a significant source of methane and contribute up to 20% of total methane emissions from wetland ecosystems. These inundated, anoxic soils featuring abundant nitrogen compounds and methane are an ideal niche for nitrate-dependent anaerobic methanotrophs. After 2 years of enrichment with a continuous supply of methane and nitrate as the sole electron donor and acceptor, a stable enrichment dominated by ‘Candidatus Methanoperedens nitroreducens’ archaea and ‘Candidatus Methylomirabilis oxyfera’ NC10 phylum bacteria was achieved. In this community, the methanotrophic archaea supplied the NC10 phylum bacteria with the necessary nitrite through nitrate reduction coupled to methane oxidation. The results of qPCR quantification of 16S ribosomal RNA (rRNA) gene copies, analysis of metagenomic 16S rRNA reads, and fluorescence in situ hybridization (FISH) correlated well and showed that after 2 years, ‘Candidatus Methanoperedens nitroreducens’ had the highest abundance of (2.2 ± 0.4 × 108) 16S rRNA copies per milliliter and constituted approximately 22% of the total microbial community. Phylogenetic analysis showed that the 16S rRNA genes of the dominant microorganisms clustered with previously described ‘Candidatus Methanoperedens nitroreducens ANME2D’ (96% identity) and ‘Candidatus Methylomirabilis oxyfera’ (99% identity) strains. The pooled metagenomic sequences resulted in a high-quality draft genome assembly of ‘Candidatus Methanoperedens nitroreducens Vercelli’ that contained all key functional genes for the reverse methanogenesis pathway and nitrate reduction. The diagnostic mcrA gene was 96% similar to ‘Candidatus Methanoperedens nitroreducens ANME2D’ (WP_048089615.1) at the protein level. The ‘Candidatus Methylomirabilis oxyfera’ draft genome contained the marker genes pmoCAB, mdh, and nirS and putative NO dismutase genes. Whole-reactor anaerobic activity measurements with methane and nitrate revealed an average methane oxidation rate of 0.012 mmol/h/L, with cell-specific methane oxidation rates up to 0.57 fmol/cell/day for ‘Candidatus Methanoperedens nitroreducens’. In summary, this study describes the first enrichment and draft genome of methanotrophic archaea from paddy field soil, where these organisms can contribute significantly to the mitigation of methane emissions.BT/Environmental Biotechnolog

Mutations in GRM6 Cause Autosomal Recessive Congenital Stationary Night Blindness with a Distinctive Scotopic 15-Hz Flicker Electroretinogram

PURPOSE: Congenital stationary night blindness (CSNB) is a group of nonprogressive retinal disorders characterized by impaired night vision that occurs in autosomal dominant, autosomal recessive, or X-linked forms. Autosomal recessive (ar)CSNB seems to be very rare. Mice lacking the metabotropic glutamate receptor 6 (Grm6) have a defect in signal transmission from the photoreceptors to ON-bipolar cells. In the current study, the human orthologue (GRM6) was screened as a likely candidate for arCSNB. METHODS: arCSNB individuals of five families were screened for mutations in GRM6. Subsequently, they were examined with standard and 15-Hz flicker electroretinography (ERG). These recordings were compared with those of patients with X-linked CSNB1. RESULTS: Affected individuals in three of five families carried either compound heterozygous or homozygous mutations in GRM6. Strikingly, all of them displayed a distinctive abnormality of the rod pathway signals on scotopic 15-Hz flicker ERG. CONCLUSIONS: The novel profile identified in this study suggests the existence of more than two rod pathways. The distinctive ERG feature was not observed in patients with X-linked CSNB1 and additional affected individuals with unknown molecular defect. These observations will help to discriminate autosomal recessive from X-linked recessive cases by ERG and molecular genetic analysis

Volume of subcortical brain regions in social anxiety disorder: mega-analytic results from 37 samples in the ENIGMA-Anxiety Working Group

There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls. Volumetric data from 37 international samples with 1115 SAD patients and 2775 controls were obtained from ENIGMA-standardized protocols for image segmentation and quality assurance. Linear mixed-effects analyses were adjusted for comparisons across seven subcortical regions in each hemisphere using family-wise error (FWE)-correction. Mixed-effects d effect sizes were calculated. In the full sample, SAD patients showed smaller bilateral putamen volume than controls (left: d = −0.077, pFWE = 0.037; right: d = −0.104, pFWE = 0.001), and a significant interaction between SAD and age was found for the left putamen (r = −0.034, pFWE = 0.045). Smaller bilateral putamen volumes (left: d = −0.141, pFWE < 0.001; right: d = −0.158, pFWE < 0.001) and larger bilateral pallidum volumes (left: d = 0.129, pFWE = 0.006; right: d = 0.099, pFWE = 0.046) were detected in adult SAD patients relative to controls, but no volumetric differences were apparent in adolescent SAD patients relative to controls. Comorbid anxiety disorders and age of SAD onset were additional determinants of SAD-related volumetric differences in subcortical regions. To conclude, subtle volumetric alterations in subcortical regions in SAD were detected. Heterogeneity in age and clinical characteristics may partly explain inconsistencies in previous findings. The association between alterations in subcortical volumes and SAD illness progression deserves further investigation, especially from adolescence into adulthood

Brain-based classification of youth with anxiety disorders: transdiagnostic examinations within the ENIGMA-Anxiety database using machine learning

Neuroanatomical findings on youth anxiety disorders are notoriously difficult to replicate, small in effect size and have limited clinical relevance. These concerns have prompted a paradigm shift toward highly powered (that is, big data) individual-level inferences, which are data driven, transdiagnostic and neurobiologically informed. Here we built and validated supervised neuroanatomical machine learning models for individual-level inferences, using a case–control design and the largest known neuroimaging database on youth anxiety disorders: the ENIGMA-Anxiety Consortium (N = 3,343; age = 10–25 years; global sites = 32). Modest, yet robust, brain- based classifications were achieved for specific anxiety disorders (panic disorder), but also transdiagnostically for all anxiety disorders when patients were subgrouped according to their sex, medication status and symptom severity (area under the receiver operating characteristic curve, 0.59–0.63). Classifications were driven by neuroanatomical features (cortical thickness, cortical surface area and subcortical volumes) in fronto- striato-limbic and temporoparietal regions. This benchmark study within a large, heterogeneous and multisite sample of youth with anxiety disorders reveals that only modest classification performances can be realistically achieved with machine learning using neuroanatomical data