Exploring Information Flow on Twitter: Social Network Analysis on Gender-Specific Medicine

To date, sex and gender differences play only a minor role in medical research and practice, thereby putting individuals’ health at risk. Gender-specific medicine, or the practice of taking these differences into account when conducting research and treating patients so far is being discussed primarily by experts. With people increasingly using social media such as Twitter for sharing and searching for health-related information online, Twitter can potentially educate about gender-specific medicine. However, little is known about the information circulation and the structure of interactions on the Twitter network discussing this topic. Results of a network analysis show that the network exhibits a community-structure, with information exchange being limited and concentrated in silos. This indicates that there is untapped potential for acquiring new information by users through interacting with individuals outside their community. Public health officials may benefit from this insight and tailor online campaigns to enhance awareness on gender-specific medicine

Investigating Innovation Diffusion in Gender-Specific Medicine: Insights from Social Network Analysis

The field of healthcare is characterized by constant innovation, with gender-specific medicine emerging as a new subfield that addresses sex and gender disparities in clinical manifestations, outcomes, treatment, and prevention of disease. Despite its importance, the adoption of gender-specific medicine remains understudied, posing potential risks to patient outcomes due to a lack of awareness of the topic. Building on the Innovation Decision Process Theory, this study examines the spread of information about gender-specific medicine in online networks. The study applies social network analysis to a Twitter dataset reflecting online discussions about the topic to gain insights into its adoption by health professionals and patients online. Results show that the network has a community structure with limited information exchange between sub-communities and that mainly medical experts dominate the discussion. The findings suggest that the adoption of gender-specific medicine might be in its early stages, focused on knowledge exchange. Understanding the diffusion of gender-specific medicine among medical professionals and patients may facilitate its adoption and ultimately improve health outcomes

Zur Galerie als frühneuzeitlicher Bautypus

Wie diese Arbeit zeigt lässt sich eine Entwicklung und ein Bedeutungswandel des Typus Galerie im mitteleuropäischen Raum feststellen. Ausgehend vom 14. Jahrhundert wurde die Raumform bis zu einem selbstständigen Bau weiterentwickelt. Das öffentliche Museum gegen Ende des 18. Jahrhunderts kann als letzte Entwicklungsstufe der Galerie gesehen werden. Der Fragestellung über die Herkunft der Galerie widmeten sich zuvor bereits einige Autoren, darunter Sigrid Kümmel, Frank Büttner und Wolfram Prinz. Eine kontinuierliche Entstehung des Raumes gab es laut ihnen nie. Es schien mir nicht ausreichend zu sein, in dieser Arbeit den Entwicklungssprung von einem offenen zu einem geschlossenen Raum zu suchen, denn die Funktion und Sinnhaftigkeit der Galerie war ausschlaggebend für die jahrhundertelange Beständigkeit der Raumform. Nach Prüfung diverser Quellen kristallisieren sich folgende Kennzeichen, die zur Begriffsdefinition „Galerie“ beitrugen, als wesentlich heraus: die bauliche Form, die Dekoration, die Ausstattung, die Funktion sowie der Sinn. Vereint zeigen sie die wesentlichen Charakteristika einer Galerie auf. Im Zuge der Arbeit stellte es sich als zielführend heraus, die programmatische Ausgestaltung des Raumes zu analysieren, um ihre Zweckbestimmung ableiten zu können. Meist diente die Galerie als „Ruhmeshalle“ des Bauherrn und als Festraum. Demnach war sie nie ein rein privates Rückzugsgebiet ihrer Bauherren. Der öffentliche Repräsentationscharakter ist eines jener Merkmale, die die Beständigkeit der Galerie über Jahrhunderte untermauerten. Hinzu kam die Funktion der Galerie als wissenschaftlicher Studienraum. Als nicht vordefiniert scheint die Lage der Galerie innerhalb des Baukomplexes gewesen zu sein. Eine genaue Regelung der Proportionen, der Deckengestaltung und der Belichtungssituation gab es im Laufe der Jahrhunderte nie

Analysis of correlation-based biomolecular networks from different omics data by fitting stochastic block models

Baum_et_al_2019_Supplementary_Figures.pdf: Supplementary Figures S1 and S2. Legends are included under each figure. sbm-for-correlation-based-networks-master.zip: Archived source code of R and Python functions for the analyses and example workflow description at time of publication. Files are maintained at https://gitlab.com/biomodlih/sbm-for-correlation-based-networks and https://gitlab.com/kabaum/sbm-for-correlation-based-networks

Direct imaging of the induced‐fit effect in molecular self‐assembly

Molecular recognition is a crucial driving force for molecular self‐assembly. In many cases molecules arrange in the lowest energy configuration following a lock‐and‐key principle. When molecular flexibility comes into play, the induced‐fit effect may govern the self‐assembly. Here, the self‐assembly of dicyanovinyl‐hexathiophene (DCV6T) molecules, a prototype specie for highly efficient organic solar cells, on Au(111) by using low‐temperature scanning tunneling microscopy and atomic force microscopy is investigated. DCV6T molecules assemble on the surface forming either islands or chains. In the islands the molecules are straight—the lowest energy configuration in gas phase—and expose the dicyano moieties to form hydrogen bonds with neighbor molecules. In contrast, the structure of DCV6T molecules in the chain assemblies deviates significantly from their gas‐phase analogues. The seemingly energetically unfavorable bent geometry is enforced by hydrogen‐bonding intermolecular interactions. Density functional theory calculations of molecular dimers quantitatively demonstrate that the deformation of individual molecules optimizes the intermolecular bonding structure. The intermolecular bonding energy thus drives the chain structure formation, which is an expression of the induced‐fit effect

DO THEY REALLY CARE ABOUT TARGETED POLITICAL ADS? INVESTIGATION OF USER PRIVACY CONCERNS AND PREFERENCES

Reliance on targeted political ads has skyrocketed in recent years, leading to negative reactions in media and society. Nonetheless, only few studies investigate user privacy concerns and their role in user acceptance decisions in the context of online political targeting. To fill this gap, in this study we explore the magnitude of privacy concerns towards targeted political ads compared to “tradi-tional” targeting in the product context. Surprisingly, we find no notable differences in privacy concerns between these use purposes. In the next step, user preferences over ad types are elicited with the help of a discrete choice experiment in the mobile app adoption context. Among others, our findings from simulations on the basis of a mixed logit model cautiously suggest that while targeted political advertising is perceived as somewhat less desirable by respondents, its presence does not consequentially deter users from choosing such an app, with user preferences being high-ly volatile. Together, these results contribute to a better understanding of users’ privacy concerns and preferences in the context of targeted political advertising online. Acknowledgment This work has been funded by the Federal Ministry of Education and Research of Germany (BMBF) under grant no. 16DII116 (“Deutsches Internet-Institut”)

LazyFox: Fast and parallelized overlapping community detection in large graphs

The detection of communities in graph datasets provides insight about a graph's underlying structure and is an important tool for various domains such as social sciences, marketing, traffic forecast, and drug discovery. While most existing algorithms provide fast approaches for community detection, their results usually contain strictly separated communities. However, most datasets would semantically allow for or even require overlapping communities that can only be determined at much higher computational cost. We build on an efficient algorithm, Fox, that detects such overlapping communities. Fox measures the closeness of a node to a community by approximating the count of triangles which that node forms with that community. We propose LazyFox, a multi-threaded version of the Fox algorithm, which provides even faster detection without an impact on community quality. This allows for the analyses of significantly larger and more complex datasets. LazyFox enables overlapping community detection on complex graph datasets with millions of nodes and billions of edges in days instead of weeks. As part of this work, LazyFox's implementation was published and is available as a tool under an MIT licence at https://github.com/TimGarrels/LazyFox.Comment: 17 pages, 5 figure

A Flexible Tool to Correct Superimposed Mass Isotopologue Distributions in GC-APCI-MS Flux Experiments

The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.SALSA (School of Analytical Sciences Adlershof, Albert-Einstein-Straße 5, 12489 Berlin, Germany)Peer Reviewe

Annexins as cell-type-specific markers in the developing chicken chorionallantoic membrane

Between day E8 and E12 of embryonic development, the chicken chorioallantoic membrane (CAM) undergoes massive structural rearrangement enabling calcium-uptake from the eggshell to supply the growing embryo. However, the contribution of the various cell types of the chorionic epithelium including the capillary covering (CC) cells, villus cavity (VC) cells, endothelial-like cells, and basal cells to this developmental program is largely unknown. In order to obtain markers for the different cell types in the chorionic epithelium, we determined the expression patterns of various calcium-binding annexins in the developing chicken CAM. By reverse transcription/polymerase chain reaction with primers deduced from nucleotide sequences available in various databases, the presence of annexin (anx)-1, anx-2, anx-5, and anx-6 was demonstrated at days E8 and E12. Quantitative immunoblotting with novel antibodies raised against the recombinant proteins revealed that anx-1 and anx-5 were significantly up-regulated at day E12, whereas anx-2 and anx-6 expression remained almost unchanged in comparison to levels at day E8. Immunohistochemistry of paraffin-embedded sections of E12 CAM revealed anx-1 in CC cells and VC cells. Anx-2 was localized in capillaries in the chorionic epithelium and in basal cells of the allantoic epithelium, whereas anx-6 was detected in basal cells or endothelial-like cells of the chorionic epithelium and in the media of larger vessels in the mesenchyme. A 2-day exposure of the CAM to a tumor cell spheroid resulted in strong proliferation of anx-1-expressing CC cells suggesting that these cells participate in the embryonic response to experimental intervention. Thus, annexins exhibit complementary expression patterns and represent appropriate cell markers for the further characterization of CAM development and the interpretation of results obtained when using CAM as an experimental mode

PEPerMINT: peptide abundance imputation in mass spectrometry-based proteomics using graph neural networks

Motivation Accurate quantitative information about protein abundance is crucial for understanding a biological system and its dynamics. Protein abundance is commonly estimated using label-free, bottom-up mass spectrometry (MS) protocols. Here, proteins are digested into peptides before quantification via MS. However, missing peptide abundance values, which can make up more than 50% of all abundance values, are a common issue. They result in missing protein abundance values, which then hinder accurate and reliable downstream analyses. Results To impute missing abundance values, we propose PEPerMINT, a graph neural network model working directly on the peptide level that flexibly takes both peptide-to-protein relationships in a graph format as well as amino acid sequence information into account. We benchmark our method against 11 common imputation methods on 6 diverse datasets, including cell lines, tissue, and plasma samples. We observe that PEPerMINT consistently outperforms other imputation methods. Its prediction performance remains high for varying degrees of missingness, different evaluation approaches, and differential expression prediction. As an additional novel feature, PEPerMINT provides meaningful uncertainty estimates and allows for tailoring imputation to the user’s needs based on the reliability of imputed values