Ein implantierbares Telemetriesystem zur Impedanzspektroskopie

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.Die kontinuierliche Überwachung des intrakorporalen Zustandes von Geweben beispielsweise zur Erkennung ischämischer Vorgänge nach gefäßchirurgischen Eingriffen oder im Rahmen der Rejektionsdiagnostik läßt sich durch bisher vorhandene Meßsysteme nur bedingt erreichen. Speziell die direkte Erfassung sensitiver Gewebeparameter über einen längeren Zeitraum ohne Belastung für den Patienten stellt in diesem Zusammenhang ein Problem dar. In der nachfolgenden Arbeit wird das Konzept eines implantierbaren Telemetriesystems vorgestellt, das die Bewertung des Gewebezustandes über die Messung der frequenzabhängigen Bioimpedanz ermöglicht. Besondere Beachtung wird der Auslegung und Umsetzung der einzelnen Systemkomponenten sowie der Vorstellung erster in vitro Messungen zur Evaluierung des Meßsystems geschenkt

Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison

Model-based global projections of future land use and land cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socio-economic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g. boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process as well as improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity

SOCS2-Induced Proteasome-Dependent TRAF6 Degradation: A Common Anti-Inflammatory Pathway for Control of Innate Immune Responses

Pattern recognition receptors and receptors for pro-inflammatory cytokines provide critical signals to drive the development of protective immunity to infection. Therefore, counter-regulatory pathways are required to ensure that overwhelming inflammation harm host tissues. Previously, we showed that lipoxins modulate immune response during infection, restraining inflammation during infectious diseases in an Aryl hydrocarbon receptor (AhR)/suppressors of cytokine signaling (SOCS)2-dependent-manner. Recently, Indoleamine-pyrrole 2,3- dioxygenase (IDO)-derived tryptophan metabolites, including L-kynurenine, were also shown to be involved in several counter-regulatory mechanisms. Herein, we addressed whether the intracellular molecular events induced by lipoxins mediating control of innate immune signaling are part of a common regulatory pathway also shared by L-kynurenine exposure. We demonstrate that Tumor necrosis factor receptor-associated factor (TRAF)6 – member of a family of adapter molecules that couple the TNF receptor and interleukin-1 receptor/Toll-like receptor families to intracellular signaling events essential for the development of immune responses – is targeted by both lipoxins and L-kynurenine via an AhR/SOCS2-dependent pathway. Furthermore, we show that LXA4- and L-kynurenine-induced AhR activation, its subsequent nuclear translocation, leading SOCS2 expression and TRAF6 Lys47-linked poly-ubiquitination and proteosome-mediated degradation of the adapter proteins. The in vitro consequences of such molecular interactions included inhibition of TLR- and cytokine receptor-driven signal transduction and cytokine production. Subsequently, in vivo proteosome inhibition led to unresponsiveness to lipoxins, as well as to uncontrolled pro-inflammatory reactions and elevated mortality during toxoplasmosis. In summary, our results establish proteasome degradation of TRAF6 as a key molecular target for the anti-inflammatory pathway triggered by lipoxins and L-kynurenine, critical counter-regulatory mediators in the innate and adaptive immune systems

Describing complex interactions of social-ecological systems for tipping point assessments: an analytical framework

Humans play an interconnecting role in social-ecological systems (SES), they are part of these systems and act as agents of their destruction and regulation. This study aims to provide an analytical framework, which combines the concept of SES with the concept of tipping dynamics. As a result, we propose an analytical framework describing relevant dynamics and feedbacks within SES based on two matrixes: the “tipping matrix” and the “cross-impact matrix.” We take the Southwestern Amazon as an example for tropical regions at large and apply the proposed analytical framework to identify key underlying sub-systems within the study region: the soil ecosystem, the household livelihood system, the regional social system, and the regional climate system, which are interconnected through a network of feedbacks. We consider these sub-systems as tipping elements (TE), which when put under stress, can cross a tipping point (TP), resulting in a qualitative and potentially irreversible change of the respective TE. By systematically assessing linkages and feedbacks within and between TEs, our proposed analytical framework can provide an entry point for empirically assessing tipping point dynamics such as “tipping cascades,” which means that the crossing of a TP in one TE may force the tipping of another TE. Policy implications: The proposed joint description of the structure and dynamics within and across SES in respect to characteristics of tipping point dynamics promotes a better understanding of human-nature interactions and critical linkages within regional SES that may be used for effectively informing and directing empirical tipping point assessments, monitoring or intervention purposes. Thereby, the framework can inform policy-making for enhancing the resilience of regional SES

Describing complex interactions of social-ecological systems for tipping point assessments: an analytical framework

Humans play an interconnecting role in social-ecological systems (SES), they are part of these systems and act as agents of their destruction and regulation. This study aims to provide an analytical framework, which combines the concept of SES with the concept of tipping dynamics. As a result, we propose an analytical framework describing relevant dynamics and feedbacks within SES based on two matrixes: the “tipping matrix” and the “cross-impact matrix.” We take the Southwestern Amazon as an example for tropical regions at large and apply the proposed analytical framework to identify key underlying sub-systems within the study region: the soil ecosystem, the household livelihood system, the regional social system, and the regional climate system, which are interconnected through a network of feedbacks. We consider these sub-systems as tipping elements (TE), which when put under stress, can cross a tipping point (TP), resulting in a qualitative and potentially irreversible change of the respective TE. By systematically assessing linkages and feedbacks within and between TEs, our proposed analytical framework can provide an entry point for empirically assessing tipping point dynamics such as “tipping cascades,” which means that the crossing of a TP in one TE may force the tipping of another TE. Policy implications: The proposed joint description of the structure and dynamics within and across SES in respect to characteristics of tipping point dynamics promotes a better understanding of human-nature interactions and critical linkages within regional SES that may be used for effectively informing and directing empirical tipping point assessments, monitoring or intervention purposes. Thereby, the framework can inform policy-making for enhancing the resilience of regional SES

The drivers and impacts of Amazon forest degradation

BACKGROUND: Most analyses of land-use and land-cover change in the Amazon forest have focused on the causes and effects of deforestation. However, anthropogenic disturbances cause degradation of the remaining Amazon forest and threaten their future. Among such disturbances, the most important are edge effects (due to deforestation and the resulting habitat fragmentation), timber extraction, fire, and extreme droughts that have been intensified by human-induced climate change. We synthesize knowledge on these disturbances that lead to Amazon forest degradation, including their causes and impacts, possible future extents, and some of the interventions required to curb them. ADVANCES: Analysis of existing data on the extent of fire, edge effects, and timber extraction between 2001 and 2018 reveals that 0.36 ×106 km2 (5.5%) of the Amazon forest is under some form of degradation, which corresponds to 112% of the total area deforested in that period. Adding data on extreme droughts increases the estimate of total degraded area to 2.5 ×106 km2, or 38% of the remaining Amazonian forests. Estimated carbon loss from these forest disturbances ranges from 0.05 to 0.20 Pg C year−1 and is comparable to carbon loss from deforestation (0.06 to 0.21 Pg C year−1). Disturbances can bring about as much biodiversity loss as deforestation itself, and forests degraded by fire and timber extraction can have a 2 to 34% reduction in dry-season evapotranspiration. The underlying drivers of disturbances (e.g., agricultural expansion or demand for timber) generate material benefits for a restricted group of regional and global actors, whereas the burdens permeate across a broad range of scales and social groups ranging from nearby forest dwellers to urban residents of Andean countries. First-order 2050 projections indicate that the four main disturbances will remain a major threat and source of carbon fluxes to the atmosphere, independent of deforestation trajectories. OUTLOOK: Whereas some disturbances such as edge effects can be tackled by curbing deforestation, others, like constraining the increase in extreme droughts, require additional measures, including global efforts to reduce greenhouse gas emissions. Curbing degradation will also require engaging with the diverse set of actors that promote it, operationalizing effective monitoring of different disturbances, and refining policy frameworks such as REDD+. These will all be supported by rapid and multidisciplinary advances in our socioenvironmental understanding of tropical forest degradation, providing a robust platform on which to co-construct appropriate policies and programs to curb it

The drivers and impacts of Amazon forest degradation

Approximately 2.5 × 10 6 square kilometers of the Amazon forest are currently degraded by fire, edge effects, timber extraction, and/or extreme drought, representing 38% of all remaining forests in the region. Carbon emissions from this degradation total up to 0.2 petagrams of carbon per year (Pg C year −1 ), which is equivalent to, if not greater than, the emissions from Amazon deforestation (0.06 to 0.21 Pg C year −1 ). Amazon forest degradation can reduce dry-season evapotranspiration by up to 34% and cause as much biodiversity loss as deforestation in human-modified landscapes, generating uneven socioeconomic burdens, mainly to forest dwellers. Projections indicate that degradation will remain a dominant source of carbon emissions independent of deforestation rates. Policies to tackle degradation should be integrated with efforts to curb deforestation and complemented with innovative measures addressing the disturbances that degrade the Amazon forest