Anti-CadN monoclonal antibody, clone 9C10

Drosophila N-cadherin (CadN) is an evolutionarily conserved classic cadherin which has a large, complex extracellular domain and a catenin-binding cytoplasmic domain. The CadN locus contains three modules of alternative exons (7a/b, 13a/b, and 18a/b) and undergoes alternative splicing to generate multiple isoforms. Using quantitative transcript analyses and green fluorescent protein-based cell sorting, we found that during development CadN alternative splicing is regulated in a temporal but not cell-type-specific fashion. In particular, exon 18b is predominantly expressed during early developmental stages, while exon 18a is prevalent at the late developmental and adult stages. All CadN isoforms share the same molecular architecture but have different sequences in their extracellular and transmembrane domains, suggesting functional diversity. In vitro quantitative cell aggregation assays revealed that all CadN isoforms mediate homophilic interactions, but the isoforms encoded by exon 18b have a higher adhesive activity than those by its alternative, 18a. Domain-swapping experiments further revealed that the different sequences in the transmembrane domains of isoforms are responsible for their differential adhesive activities. CadN alternative splicing might provide a novel mechanism to fine-tune its adhesive activity at different developmental stages or to restrict the use of high-affinity 18b-type isoforms at the adult stage.

Contactless exercise monitoring is a new trend that makes people feel more comfortable and unconstrained. However, the decrease in accuracy of the pulse rate measurement caused by large motion artifacts is an urgent problem to be solved. In this paper, we proposed a novel approach to monitor step count and improve the accuracy of remote pulse rate measurement based on the image detection method. We designed a chrominance-based adaptive filter and normalization (CADN) method and a domain selection scheme (DSS) to enhance the accuracy of contactless pulse rate measurement during exercise. Various exercises such as biking, stepping, and treadmill running were conducted to evaluate motion robustness of the proposed CADN + DSS and the accuracy of step counts. The results reveal that the detection rates of the proposed step count method are 99.52% and 99.77% for stepping and treadmill exercise, respectively. The pulse rate accuracy is compared with two state-of-the-art algorithms-chrominance and chrominance-based adaptive filter. The results show the proposed CADN+DSS method provides a lower discrepancy between the detected pulse rate and a ground-truth device (Polar H7) for all activities. We expand the scope of contactless measurement for physical activity detection and develop an unfettered step count and pulse rate measurement method in exercise. Therefore, step count and pulse rate can be measured synchronously without relying on any contact sensors.