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We specifically assessed the processing and presentation for a part of these sequences and showed T-cell recognition on the surface of target mRNA-electroporated HLA-transduced K562 cells for three of the five peptides tested.
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Asialoglycoprotein receptor (ASGPR) is one of the recognition motifs on the surface of hepatocytes, which promote their adhesion to extracellular matrix in liver tissue and appropriate artificial surfaces.
Attributing to the SiO2 with the surface functional monomer and the QDs with functional group, SAs molecules are attracted to the QDs and bound to the SiO2 surface, hence accelerating the growth of homogeneous recognition sites on the surface of SiO2 and guaranteeing the distance between the recognition sites and the QDs.
Characterization and performance tests of the obtained products revealed that MIP@SiO2 not only had excellent selectivity to the target molecule MEL compared with NIP@SiO2, but also displayed absorption capacity superior to MIP due to the molecular recognition sites on the surface of silica gel.
However, PS remains a universal component of the recognition pattern on the surface of apoptotic cells [24], and recent studies have implicated several different macrophage receptors in the process of PS-dependent clearance of cell corpses [25], [26].
Moreover, additional recognition signals on the surface of apoptotic cells have also been shown to be involved in this process, including proteins such as annexin I and calreticulin [22], [23].
This is due to the presence on the apoptotic cell surface of Apoptotic Cell Associated Molecular Patterns (ACAMPs), which are recognized as "eat me" signals by pattern recognition receptors on the surface of phagocytes during the assembly of the phagocytic synapse [62].
The longer probes need the longer spacer to avoid the blocking of the molecular recognition site on the surface of AuNPs.
PAMPs and DAMPs are recognised as danger signals by pattern recognition receptors on the surface of immune, epithelial, endothelial and parenchymal cells.
This approach is based on the well established 'glycoside cluster effect', in which binding affinities can be dramatically increased by a clustering of both lectin binding sites and carbohydrate recognition units on the surface of cells or tissues [ 33].
Recognition of regions on the surface of one protein, that are similar to a binding site of another is crucial for the prediction of molecular interactions and for functional classifications.
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