A measurement of jet substructure observables is presented using data collected in 2016 by the ATLAS experiment at the LHC with proton-proton collisions at root s= 13 TeV. Large-radius jets groomed with the trimming and soft-drop algorithms are studied. Dedicated event selections are used to study jets produced by light quarks or gluons, and hadronically decaying top quarks and W bosons. The observables measured are sensitive to substructure, and therefore are typically used for tagging large-radius jets from boosted massive particles. These include the energy correlation functions and the N-subjettiness variables. The number of subjets and the Les Houches angularity are also considered. The distributions of the substructure variables, corrected for detector effects, are compared to the predictions of various Monte Carlo event generators. They are also compared between the large-radius jets originating from light quarks or gluons, and hadronically decaying top quarks and W bosons.

We propose that the application of network theory to established psychological personality conceptions has great potential to advance a biologically plausible model of human personality. Stable behavioral tendencies are conceived as personality “traits.” Such traits demonstrate considerable variability between individuals, and extreme expressions represent risk factors for psychological disorders. Although the psychometric assessment of personality has more than hundred years tradition, it is not yet clear whether traits indeed represent “biophysical entities” with specific and dissociable neural substrates. For instance, it is an open question whether there exists a correspondence between the multilayer structure of psychometrically derived personality factors and the organizational properties of traitlike brain systems. After a short introduction into fundamental personality conceptions, this article will point out how network neuroscience can enhance our understanding about human personality. We will examine the importance of intrinsic (task-independent) brain connectivity networks and show means to link brain features to stable behavioral tendencies. Questions and challenges arising from each discipline itself and their combination are discussed and potential solutions are developed. We close by outlining future trends and by discussing how further developments of network neuroscience can be applied to personality research.

1. Plant functional traits impact the fitness and environmental niche of plants. Major plant functional types have been characterized by their trait spectrum, and the environmental and phylogenetic imprints on traits have advanced several ecological fields. Yet, very few trait data on epiphytes, which represent almost 10% of vascular plants, are available. 2. We collated 76,561 trait observations for 2,882 species of vascular epiphytes and compared these to non-epiphytic herbs and trees to test hypotheses related to how the epiphytic habit affects traits, and if epiphytes occupy a distinct region in the global trait space. We also compared variation in traits among major groups of epiphytes, and investigated the coordination of traits in epiphytes, ground-rooted herbs and trees. 3. Epiphytes differ from ground-rooted plants mainly in traits related to water relations. Unexpectedly, we did not find lower leaf nutrient concentrations, except for nitrogen. Mean photosynthetic rates are much lower than in ground-rooted plants and lower than expected from the nitrogen concentrations. Trait syndromes clearly distinguish epiphytes from trees and from most non-epiphytic herbs. 4. Among the three largest epiphytic taxa, orchids differ from bromeliads and ferns mainly by having smaller and more numerous stomata, while ferns differ from bromeliads by having thinner leaves, higher nutrient concentrations, and lower water content and water use efficiency. 5. Trait networks differ among epiphytes, herbs and trees. While all have central nodes represented by SLA and mass-based photosynthesis, in epiphytes, traits related to plant water relations have stronger connections, and nutrients other than potassium have weaker connections to the remainder of the trait network. Whereas stem-specific density reflects mechanical support related to plant size in herbs and trees, in epiphytes it mostly reflects water storage and scales with leaf water content. 6. Synthesis. Our findings advance our understanding of epiphyte ecology, but we note that currently mainly leaf traits are available. Important gaps are root, shoot and whole plant, demographic and gas exchange traits. We suggest how future research might use available data and fill data gaps.

MSC besitzen vielfältige immunmodulatorische Eigenschaften, die sowohl über die Sekretion parakriner Signalmoleküle, wie Zytokine oder Wachstumsfaktoren, als auch über direkte Zell-Zell-Kontakte vermittelt werden. Durch Präkonditionierung, z.B. mit spezifischen Zytokinen, können die immunmodulatorischen Eigenschaften von MSC beeinflusst werden. Eine solche zielgerichtete Modifikation scheint insbesondere für therapeutische Anwendungen interessant. Eine Herausforderung auf dem Gebiet der MSC-Forschung ist die Diskrepanz zwischen vielversprechenden in vitro- und teilweise enttäuschenden in vivo-Ergebnissen. Für das ambitionierte Ziel eines breiten therapeutischen Einsatzes von MSC sind daher noch weitreichende Forschungen zum besseren Verständnis insbesondere der Interaktionen von MSC mit Zellen des Immunsystems notwendig. Ziel dieser Studie war es, Erkenntnisse über mögliche Prozesse zu gewinnen, die im Rahmen der Wundheilung bei Exposition von MSC mit proinflammatorischen Stimuli ablaufen. Im lokalen postoperativen Milieu treffen verschiedene proinflammatorische Faktoren sowie MSC und Zellen des Immunsystems aufeinander. Es wurde untersucht, ob die Präkonditionierung von MSC mit WS von Patienten nach tumorchirurgischen Eingriffen einen Einfluss auf das immunmodulatorische Potential hat. Hierbei konnte eine signifikante Erhöhung des immunsuppressiven Charakters von MSC unter WS-Präkonditionierung festgestellt werden. Gerade in unterschiedlichen immunologischen Milieus weisen MSC ein hohes Maß an Heterogenität in ihren Eigenschaften auf. Zukünftige Arbeiten sollten daher den Einfluss weiterer immunologischer Faktoren sowohl unter pro- als auch antiinflammatorischen Stimuli auf die durch MSC vermittelte Immunmodulation untersuchen. So können neue Möglichkeiten für eine effektive Präkonditionierung identifiziert werden, um die parakrine Variabilität in präklinischen und klinischen Studien zu minimieren und letztlich die therapeutische Wirksamkeit von MSC zu optimieren.

The spore-forming opportunistic enteropathogen Clostridioides difficile (C. difficile) has emerged as the most common cause of nosocomial antibiotic-associated diarrhea. Disruption of the healthy gut microbiota upon antibiotic therapy is the major risk factor for developing an infection. The symptoms can range from mild diarrhea to life threatening disease, such as colitis and tissue necrosis. The severity of infection is mediated by the expression of several virulence factors, including two major exotoxins. Many factors regulating C. difficile pathogenicity are unknown. In recent years, it appeared that small non-coding RNAs (sRNAs) and RNA-binding proteins (RBPs) are involved in post-transcriptional regulation of nearly every facet of bacterial life. Most research has been conducted in Gram-negative species, generating a big knowledge gap in Gram-positives such as C. difficile. Despite ongoing efforts to unravel the functions of selected sRNAs and the RNA chaperone Hfq, we have only scratched the surface of studying post-transcriptional control in this pathogen. In this study, the complexomic approach gradient profiling by sequencing (Grad-seq) was applied to draft the landscape of cellular RNA and protein complexes in C. difficile. The sedimentation profiles of 3,541 transcripts (~88% of annotated transcripts) and 1,867 proteins (~50% of annotated proteins) were captured. Comparative analysis of the profiles reproduced major ribonucleoprotein particles (RNPs) and protein-protein interactions (PPIs). Based on several examples, the potential use of Grad-seq to imply protein function and discover unknown regulatory RNAs was demonstrated. With an established pull-down approach, the proteins KhpA and KhpB were identified as common interaction partners of similar behaving sRNAs. By applying crosslinking immunoprecipitation followed by RNA-sequencing (CLIP seq), a pervasive targetome of KhpB was revealed, comprising over one-third of all annotated transcripts, including sRNAs, tRNAs and untranslated regions. The scope of RNA-binding suggests that KhpB is a second globally acting RBP in C. difficile, next to Hfq. The combination of transcriptome studies and phenotypic characterization suggests that KhpA and KhpB have several physiological functions including the regulation of toxins and metabolic pathways associated with pathogenesis. Overall, this work provides a comprehensive dataset for the discovery of PPIs and RNA-protein interactions in C. difficile. Further, this study establishes the foundation for studying two novel players in post-transcriptional regulation in this important human pathogen.