Rapid inflammasome activation is attenuated in post-myocardial infarction monocytes

Inflammasomes are crucial gatekeepers of the immune response, but their maladaptive activation associates with inflammatory pathologies. Besides canonical activation, monocytes can trigger non-transcriptional or rapid inflammasome activation that has not been well defined in the context of acute myocardial infarction (AMI). Rapid transcription-independent inflammasome activation induced by simultaneous TLR priming and triggering stimulus was measured by caspase-1 (CASP1) activity and interleukin release. Both classical and intermediate monocytes from healthy donors exhibited robust CASP1 activation, but only classical monocytes produced high mature interleukin-18 (IL18) release. We also recruited a limited number of coronary artery disease (CAD, n=31) and AMI (n=29) patients to evaluate their inflammasome function and expression profiles. Surprisingly, monocyte subpopulations isolated from blood collected during percutaneous coronary intervention (PCI) from AMI patients presented diminished CASP1 activity and abrogated IL18 release despite increased NLRP3 gene expression. This unexpected attenuated rapid inflammasome activation was accompanied by a significant increase of TNFAIP3 and IRAKM expression. Moreover, TNFAIP3 protein levels of circulating monocytes showed positive correlation with high sensitive troponin T (hsTnT), implying an association between TNFAIP3 upregulation and the severity of tissue injury. We suggest this monocyte attenuation to be a protective phenotype aftermath following a very early inflammatory wave in the ischemic area. Damage-associated molecular patterns (DAMPs) or other signals trigger a transitory negative feedback loop within newly recruited circulating monocytes as a mechanism to reduce post-injury tissue damage

Development and characterization of superparamagnetic coatings

Since 2005, Magnetic Particle Imaging (MPI) is handled as a key technology with great potential in medical applications as an imaging method [1]. The superparamagnetic iron oxide nanoparticles (SPIONs) which are already used as a tracer in MPI, combined with various polymers, are being investigated in order to enhance this potential. A combination of polymers such as polyethylene (PE) and polyurethane (PU) and SPIONs could be used as a coating for medical devices, or added to semi-rigid polyurethane for the production of surgical instruments [2]. This would be of great interest, since the method provides high sensitivity with simultaneous high spatial resolution and three-dimensional imaging in real time. Therefore various superparamagnetic coatings were developed, tested and characterized. Finally SPIONs and various polymers were combined directly and used for MPI-compatible models

Characterization of morphological surface activities derived from near-continuous terrestrial lidar time series

The Earth's landscapes are shaped by processes eroding, transporting and depositing material over various timespans and spatial scales. To understand these surface activities and mitigate potential hazards they inflict (e.g., the landward movement of a shoreline), knowledge is needed on the occurrences and impact of these activities. Near-continuous terrestrial laser scanning enables the acquisition of large datasets of surface morphology, represented as three-dimensional point cloud time series. Exploiting the full potential of this large amount of data, by extracting and characterizing different types of surface activities, is challenging. In this research we use a time series of 2,942 point clouds obtained over a sandy beach in The Netherlands. We investigate automated methods to extract individual surface activities present in this dataset and cluster them into groups to characterize different types of surface activities. We show that, first extracting 2,021 spatiotemporal segments of surface activity using an object detection algorithm, and second, clustering these segments with a Self-organizing Map (SOM) in combination with hierarchical clustering, allows for the unsupervised identification and characterization of different types of surface activities present on a sandy beach. The SOM enables us to find events displaying certain type of surface activity, while it also enables the identification of subtle differences between different events belonging to one specific surface activity. Hierarchical clustering then allows us to find and characterize broader groups of surface activity, even if the same type of activity occurs at different points in space or time. Coastal EngineeringOptical and Laser Remote Sensin