Ultrabright fluorescent microsphere and its novel application for improving the sensitivity of immunochromatographic assay.

Fluorescent microsphere (FM) is widely used as probe in immunochromatographic assay (ICA). However, the performance of conventional FM is limited because of the aggregation-caused quenching effect. Herein, we compared a kind of conventional FM (DMFFM, loading DMF) with novel aggregation-induced emission FM (AIEFM, loading TCBPE). The fluorescence intensity of DMFFM initially increased and then decreased as the concentrations of the loading DMF increased. The fluorescence intensity of AIEFM increased as the concentrations of the loading TCBPE increased and retained a high value. AIEFM was compared with two commercial FMs purchased from Ocean (OFM) and Merk (MFM). The maximum fluorescence intensity and relative quantum yield of AIEFM was approximately 5 and 4.5 times higher than those of two commercial FMs. We used the novel AIEFM as a probe to improve the sensitivity of ICA. When Escherichia coli O157:H7 was detected as the target, the limit of detection of ICA based on AIEFM, OFM and MFM were 3.98 × 103 CFU/mL, 4.48 × 104 and 2.78 × 104 CFU/mL, respectively. The ICA of AIEFM had 11 and 7 times improvement in sensitivity compared with that of OFM and MFM. Our results could be used as a basis for novel probes in practical ICA applications.

Planar-shape prototype generation using a tree-based random greedy algorithm.

A prototype is representative of a set of similar objects. This paper proposes an approach that formulates the problem of prototype generation as finding the mean from a given set of objects, where the prototype solution must satisfy certain constraints. These constraints describe the important perceptual features of the sample shapes that the proposed prototype must retain. The contour prototype generated from a set of planar objects was used as an example of the approach, and the corners were used as the perceptual features to be preserved in the proposed prototype shape. However, finding a prototype solution for more than two contours is computationally intractable. A tree-based approach is therefore proposed in which an efficient greedy random algorithm is used to obtain a good approximation of the proposed prototype and analyze the expected complexity of the algorithm. The proposed prototype-generation process for hand-drawn patterns is described and discussed in this paper.