Prorenin accumulation and activation in human endothelial cells: importance of mannose 6-phosphate receptors

ACE inhibitors improve endothelial dysfunction, possibly by blocking endothelial angiotensin production. Prorenin, through its binding and activation by endothelial mannose 6-phosphate (M6P) receptors, may contribute to this production. Here, we investigated this possibility as well as prorenin activation kinetics, the nature of the prorenin-activating enzyme, and M6P receptor-independent prorenin binding. Human umbilical vein endothelial cells (HUVECs) were incubated with wild-type prorenin, K/A-2 prorenin (in which Lys42 is mutated to Ala, thereby preventing cleavage by known proteases), M6P-free prorenin, and nonglycosylated prorenin, with or without M6P, protease inhibitors, or angiotensinogen. HUVECs bound only M6P-containing prorenin (K(d) 0.9+/-0.1 nmol/L, maximum number of binding sites [B(max)] 1010+/-50 receptors/cell). At 37 degrees C, because of M6P receptor recycling, the amount of prorenin internalized via M6P receptors was >25 times B(max). Inside the cells, wild-type and K/A-2 prorenin were proteolytically activated to renin. Renin was subsequently degraded. Protease inhibitors interfered with the latter but not with prorenin activation, thereby indicating that the activating enzyme is different from any of the known prorenin-activating enzymes. Incubation with angiotensinogen did not lead to endothelial angiotensin generation, inasmuch as HUVECs were unable to internalize angiotensinogen. Most likely, therefore, in the absence of angiotensinogen synthesis or endocytosis, M6P receptor-mediated prorenin internalization by endothelial cells represents prorenin clearance

Comparison of narrow band and fluorescence molecular imaging to improve intraoperative tumour margin assessment in oral cancer surgery

Objective: New techniques have emerged to aid in preventing inadequate margins in oral squamous cell carcinoma (OSCC) surgery, but studies comparing different techniques are lacking. Here, we compared narrow band imaging (NBI) with fluorescence molecular imaging (FMI), to study which intraoperative technique best assesses the mucosal tumour margins.Materials and Methods: NBI was performed in vivo and borders were marked with three sutures. For FMI, patients received 75 mg of unlabelled cetuximab followed by 15 mg cetuximab-800CW intravenously-two days prior to surgery. The FMI borders were defined on the excised specimen. The NBI borders were correlated with the FMI outline and histopathology.Results: Sixteen patients were included, resulting in 31 NBI and 30 FMI measurements. The mucosal border was delineated within 1 mm of the tumour border in 4/31 (13 %) of NBI and in 16/30 (53 %) FMI cases (p = 0.0008), and within 5 mm in 23/31 (74 %) of NBI and in 29/30 (97 %) of FMI cases (p = 0.0048). The median distance between the tumour border and the imaging border was significantly greater for NBI (3.2 mm, range −6.1 to 12.8 mm) than for FMI (0.9 mm, range −3.0 to 7.4 mm; p = 0.028). Submucosal extension and previous irradiation reduced NBI accuracy.Conclusion: Ex vivo FMI performed more accurately than in vivo NBI in mucosal margin assessment, mainly because NBI cannot detect submucosal extension. NBI adequately identified the mucosal margin especially in early-stage and not previously irradiated tumours, and may therefore be preferable in these tumours for practical and cost-related reasons.</p

TNO at TRECVID 2013 : multimedia event detection and instance search

We describe the TNO system and the evaluation results for TRECVID 2013 Multimedia Event Detection (MED) and instance search (INS) tasks. The MED system consists of a bag-of-word (BOW) approach with spatial tiling that uses low-level static and dynamic visual features, an audio feature and high-level concepts. Automatic speech recognition (ASR) and optical character recognition (OCR) are not used in the system. In the MED case with 100 example training videos, support-vector machines (SVM) are trained and fused to detect an event in the test set. In the case with 0 example videos, positive and negative concepts are extracted as keywords from the textual event description and events are detected with the high-level concepts. The MED results show that the SIFT keypoint descriptor is the one which contributes best to the results, fusion of multiple low-level features helps to improve the performance, and the textual event-description chain currently performs poorly. The TNO INS system presents a baseline open-source approach using standard SIFT keypoint detection and exhaustive matching. In order to speed up search times for queries a basic map-reduce scheme is presented to be used on a multi-node cluster. Our INS results show above-median results with acceptable search times.This research for the MED submission was performed in the GOOSE project, which is jointly funded by the enabling technology program Adaptive Multi Sensor Networks (AMSN) and the MIST research program of the Dutch Ministry of Defense. The INS submission was partly supported by the MIME project of the creative industries knowledge and innovation network CLICKNL.peer-reviewe

A New Technique for the Calculation and 3D Visualisation of Magnetic Complexities on Solar Satellite Images

YesIn this paper, we introduce two novel models for processing real-life satellite images to quantify and then visualise their magnetic structures in 3D. We believe this multidisciplinary work is a real convergence between image processing, 3D visualization and solar physics. The first model aims to calculate the value of the magnetic complexity in active regions and the solar disk. A series of experiments are carried out using this model and a relationship has been indentified between the calculated magnetic complexity values and solar flare events. The second model aims to visualise the calculated magnetic complexities in 3D colour maps in order to identify the locations of eruptive regions on the Sun. Both models demonstrate promising results and they can be potentially used in the fields of solar imaging, space weather and solar flare prediction and forecasting

Animal models for COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the aetiological agent of coronavirus disease 2019 (COVID-19), an emerging respiratory infection caused by the introduction of a novel coronavirus into humans late in 2019 (frst detected in Hubei province, China). As of 18 September 2020, SARS-CoV-2 has spread to 215 countries, has infected more than 30 million people and has caused more than 950,000 deaths. As humans do not have pre-existing immunity to SARS-CoV-2, there is an urgent need to develop therapeutic agents and vaccines to mitigate the current pandemic and to prevent the re-emergence of COVID-19. In February 2020, the World Health Organization (WHO) assembled an international panel to develop animal models for COVID-19 to accelerate the testing of vaccines and therapeutic agents. Here we summarize the fndings to date and provides relevant information for preclinical testing of vaccine candidates and therapeutic agents for COVID-19.info:eu-repo/semantics/acceptedVersio