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The number and surface area of CD3 clusters at the IS seem to show a different dependency to the TCR trigger when compared to their dwell time. Finally, the mode of full CG exocytosis appears to be independent of the TCR trigger.Surface receptor-mediated adhesion is a fundamental step in the recruitment of leukocytes and platelets, as well as platelet-leukocyte interactions. The surface receptor CD147 is crucially involved in host defense against self-derived and invading targets, as well as in thrombosis. In the current study, we describe the previously unknown interaction of CD147 with integrin αMβ2 (Mac-1) in this context. Using binding assays, we were able to show a stable interaction of CD147 with Mac-1 in vitro. Leukocytes from Mac-1-/- and CD147+/- mice showed a markedly reduced static adhesion to CD147- and Mac-1-coated surfaces, respectively, compared to wild-type mice. Similarly, we observed reduced rolling and adhesion of monocytes under flow conditions when cells were pre-treated with antibodies against Mac-1 or CD147. Additionally, as assessed by antibody inhibition experiments, CD147 mediated the dynamic adhesion of platelets to Mac-1-coated surfaces. The interaction of CD147 with Mac-1 is a previously undescribed mechanism facilitating the adhesion of leukocytes and platelets.Protein micropatterning is a powerful tool for spatial arrangement of transmembrane and intracellular proteins in living cells. The restriction of one interaction partner (the bait, e.g., the receptor) in regular micropatterns within the plasma membrane and the monitoring of the lateral distribution of the bait's interaction partner (the prey, e.g., the cytosolic downstream molecule) enables the in-depth examination of protein-protein interactions in a live cell context. This study reports on potential pitfalls and difficulties in data interpretation based on the enrichment of clathrin, which is a protein essential for clathrin-mediated receptor endocytosis. Using a highly modular micropatterning approach based on large-area micro-contact printing and streptavidin-biotin-mediated surface functionalization, clathrin was found to form internalization hotspots within the patterned areas, which, potentially, leads to unspecific bait/prey protein co-recruitment. We discuss the consequences of clathrin-coated pit formation on the quantitative analysis of relevant protein-protein interactions, describe controls and strategies to prevent the misinterpretation of data, and show that the use of DNA-based linker systems can lead to the improvement of the technical platform.In order to enhance the signal-to-noise ratio (SNR) of a distributed optical fiber vibration sensor based on coherent optical time domain reflectometry (COTDR), a high extinction ratio cascade structure of an acousto-optic modulator and semiconductor optical amplifier is applied. The prior time-frequency analysis and least mean square error algorithm are adopted in the COTDR system for amplitude demodulation and phase demodulation, in order to improve the SNR by noise elimination. The experimental results show that the adaptive filter based on the least mean square error algorithm could realize the extraction of a three-order sinusoidal harmonic signal from strong background noise along the optical fiber and the SNR improvement from 10.4 dB to 42.2 dB. The proposed demodulation algorithm is suitable for the detection of vibration signals with characteristic frequencies in the application of acoustic fault diagnosis for electromechanical devices.The development of MnO2-graphene (MnO2-GR) composite by microwave irradiation method and its application as an electrode material for the selective determination of serotonin (SE), popularly known as "happy chemical", is reported. Anchoring MnO2 nanoparticles on graphene, yielded MnO2-GR composite with a large surface area, improved electron transport, high conductivity and numerous channels for rapid diffusion of electrolyte ions. The composite was characterized by X-ray photoelectron spectroscopy (XPS), Raman spectroscopy and scanning electron microscopy (SEM) for assessing the actual composition, structure and morphology. The MnO2-GR composite modified glassy carbon electrode (GCE) exhibited an excellent electrochemical activity towards the detection of SE in phosphate buffer saline (PBS) at physiological pH of 7.0. Under optimum conditions, the modified electrode could be applied to the quantification of serotonin by square wave voltammetry over a wide linear range of 0.1 to 800 µM with the lowest detection limit of 10 nM (S/N = 3). The newly fabricated sensor also exhibited attractive features such as good anti-interference ability, high reproducibility and long-term stability.Classifying remote sensing images is vital for interpreting image content. Presently, remote sensing image scene classification methods using convolutional neural networks have drawbacks, including excessive parameters and heavy calculation costs. More efficient and lightweight CNNs have fewer parameters and calculations, but their classification performance is generally weaker. We propose a more efficient and lightweight convolutional neural network method to improve classification accuracy with a small training dataset. Inspired by fine-grained visual recognition, this study introduces a bilinear convolutional neural network model for scene classification. Veliparib First, the lightweight convolutional neural network, MobileNetv2, is used to extract deep and abstract image features. Each feature is then transformed into two features with two different convolutional layers. The transformed features are subjected to Hadamard product operation to obtain an enhanced bilinear feature. Finally, the bilinear feature after pooling and normalization is used for classification. Experiments are performed on three widely used datasets UC Merced, AID, and NWPU-RESISC45. Compared with other state-of-art methods, the proposed method has fewer parameters and calculations, while achieving higher accuracy. By including feature fusion with bilinear pooling, performance and accuracy for remote scene classification can greatly improve. This could be applied to any remote sensing image classification task.
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