Pro-inflammatory signaling by IL-10 and IL-22: bad habit stirred up by interferons?

Interleukin (IL)-10 and IL-22 are key members of the IL-10 cytokine family that share characteristic properties such as defined structural features, usage of IL-10R2 as one receptor chain, and activation of signal transducer and activator of transcription (STAT)-3 as dominant signaling mode. IL-10, formerly known as cytokine synthesis inhibitory factor, is key to deactivation of monocytes/macrophages and dendritic cells. Accordingly, pre-clinical studies document its anti-inflammatory capacity. However, the outcome of clinical trials assessing the therapeutic potential of IL-10 in prototypic inflammatory disorders has been disappointing. In contrast to IL-10, IL-22 acts primarily on non-leukocytic cells, in particular epithelial cells of intestine, skin, liver, and lung. STAT3-driven proliferation, anti-apoptosis, and anti-microbial tissue protection is regarded a principal function of IL-22 at host/environment interfaces. In this hypothesis article, hidden/underappreciated pro-inflammatory characteristics of IL-10 and IL-22 are outlined and related to cellular priming by type I interferon. It is tempting to speculate that an inherent inflammatory potential of IL-10 and IL-22 confines their usage in tissue protective therapy and beyond that determines in some patients efficacy of type I interferon treatment

Neurophysiological Assessment of Affective Experience

In the field of Affective Computing the affective experience (AX) of the user during the interaction with computers is of great interest. The automatic recognition of the affective state, or emotion, of the user is one of the big challenges. In this proposal I focus on the affect recognition via physiological and neurophysiological signals. Long‐standing evidence from psychophysiological research and more recently from research in affective neuroscience suggests that both, body and brain physiology, are able to indicate the current affective state of a subject. However, regarding the classification of AX several questions are still unanswered. The principal possibility of AX classification was repeatedly shown, but its generalisation over different task contexts, elicitating stimuli modalities, subjects or time is seldom addressed. In this proposal I will discuss a possible agenda for the further exploration of physiological and neurophysiological correlates of AX over different elicitation modalities and task contexts

Connecting Brains and Bodies: Applying Physiological Computing to Support Social Interaction

Physiological and affective computing propose methods to improve human-machine interactions by adapting machines to the users' states. Recently, social signal processing (SSP) has proposed to apply similar methods to human-human interactions with the hope of better understanding and modeling social interactions. Most of the social signals employed are facial expressions, body movements and speech, but studies using physiological signals remain scarce. In this paper, we motivate the use of physiological signals in the context of social interactions. Specifically, we review studies which have investigated the relationship between various physiological indices and social interactions. We then propose two main directions to apply physiological SSP: using physiological signals of individual users as new social cues displayed in the group and using inter-user physiology to measure properties of the interactions such as conflict and social presence. We conclude that physiological measures have the potential to enhance social interactions and to connect peopl

Affective Brain-Computer Interfaces Neuroscientific Approaches to Affect Detection

The brain is involved in the registration, evaluation, and representation of emotional events, and in the subsequent planning and execution of adequate actions. Novel interface technologies – so-called affective brain-computer interfaces (aBCI) - can use this rich neural information, occurring in response to affective stimulation, for the detection of the affective state of the user. This chapter gives an overview of the promises and challenges that arise from the possibility of neurophysiology-based affect detection, with a special focus on electrophysiological signals. After outlining the potential of aBCI relative to other sensing modalities, the reader is introduced to the neurophysiological and neurotechnological background of this interface technology. Potential application scenarios are situated in a general framework of brain-computer interfaces. Finally, the main scientific and technological challenges that have to be solved on the way toward reliable affective brain-computer interfaces are discussed

Content-based Publish/Subscribe in Software-defined Networks

With SDN, content-based publish/subscribe can be implemented on the network layer instead of using an application layer broker network. We present two methods realizing notification distribution with OpenFlow and P4, respectively

Self-Management – Potentiale, Probleme, Perspektiven

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Gordon Moores Gesetz vom exponentiellen Wachstum der Transistordichte pro Quadrat-Zoll hat seit 1965 die IT-Industrie geprägt. Mit der damit einhergehenden Explosion der Rechnerleistung wurde die Software immer leistungsfähiger, und man ist dazu übergegangen, Rechnersysteme zu vernetzen und Anwendungen zu verteilen. Eine Folge dieser Entwicklungen ist die rapide zunehmende Komplexität der modernen Informationstechnologie. 40 Jahre nach Moores Entdeckung droht eben diese Tatsache, dem bisherigen exponentiellen Wachstum natürliche Grenzen zu setzen. Moderne, vernetzte Rechnersysteme, wie sie in der Industrie weit verbreitet sind, sind schon heute zu komplex als dass sie auf manuellem Wege, d.h., durch menschliche Administratoren, in einem optimalen Betriebszustand gehalten werden können. Die Folgen sind eine unzureichende Ausnutzung vorhandener Ressourcen, wiederkehrende Fehlerzustände und Lücken in der Absicherung gegen mutwillige Angriffe auf die System-Integrität. Dies führt zu erheblichen finanziellen Mehraufwendungen bzw. Verlusten. Ein permanent überfordertes Administrationspersonal, trägt durch eigene Fehler ein Übriges bei.Schenkt man den jüngst aufkeimenden Initiativen von IT-Giganten wie IBM, Microsoft und Sun Glauben, so heißt die Lösung dieser Misere automatisiertes Management. Vernetzte Rechnersysteme sollen sich auf lange Sicht selbst verwalten. Man erhofft sich hiervon ein effektiveres Management und eine Freistellung von Personal, welches sich dann um wichtigere Aufgaben kümmern kann.In diesem Beitrag beleuchten wir den aktuellen Stand und die Perspektiven im Bereich des Self-Managements. Des Weiteren diskutieren wir offene Fragen, welche auf dem Weg zu selbstverwaltenden Systemen zu lösen sind

Modality-specific Affective Responses and their Implications for Affective BCI

Reliable applications of multimodal affective brain-computer interfaces (aBCI) require a detailed understanding of the processes involved in emotions. To explore the modality-specific nature of affective responses, we studied neurophysiological responses of 24 subjects during visual, auditory, and audiovisual affect stimulation and obtained their subjective ratings. Coherent with literature, we found modality-specific responses in the EEG: parietal alpha power decreases during visual stimulation and increases during auditory stimulation, whereas more anterior alpha power decreases during auditory stimulation and increases during visual stimulation. We discuss the implications of these results for multimodal aBCI