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Retinal horizontal cells (HCs) are inhibitory neurons, which modulate the transmission of light-elicited signals from photoreceptors to bipolar cells in the outer retina. HCs of the same physiological type are extensively coupled via gap junctions. In the zebrafish retina, the population of HCs comprises up to four morphologically distinct subtypes. Four different connexins (Cx52.6, Cx52.7, Cx52.9 and Cx55.5) were detected in these cells with overlapping expression patterns. In this study, we show that Cx52.6 is alternatively spliced in the retina, resulting in an additional isoform, designated as Cx53.4, which differs from the originally described Cx52.6 only by the final C-terminal peptide (12 vs. 4 aa). Further protein sequence alignments revealed that Cx53.4 represents the counterpart of alternatively spliced mouse Cx57 and human Cx62. RT-PCR analyses of mRNA expression in different adult zebrafish tissues showed that Cx53.4 is expressed exclusively in the retina. The localization of Cx53.4 protein within the retina was analyzed using a specific antibody. Immunofluorescence analyses demonstrated that the expression of Cx53.4 is restricted to HCs of all four subtypes. Further, immunoelectron microscopy confirmed the presence of Cx53.4 in gap junctions between HC dendrites and between their axon terminals.

Wireless engineers and business planners commonly raise the question on where, when, and how millimeter-wave (mmWave) will be used in 5G and beyond. Since the next generation network is not just a new radio access standard, but instead an integration of networks for vertical markets with diverse applications, answers to the question depend on scenarios and use cases to be deployed. This paper gives four 5G mmWave deployment examples and describes in chronological order the scenarios and use cases of their probable deployment, including expected system architectures and hardware prototypes. The paper starts with 28 GHz outdoor backhauling for fixed wireless access and moving hotspots, which will be demonstrated at the PyeongChang winter Olympic games in 2018. The second deployment example is a 60 GHz unlicensed indoor access system at the Tokyo-Narita airport, which is combined with Mobile Edge Computing (MEC) to enable ultra-high speed content download with low latency. The third example is mmWave mesh network to be used as a micro Radio Access Network ({\mu}-RAN), for cost-effective backhauling of small-cell Base Stations (BSs) in dense urban scenarios. The last example is mmWave based Vehicular-to-Vehicular (V2V) and Vehicular-to-Everything (V2X) communications system, which enables automated driving by exchanging High Definition (HD) dynamic map information between cars and Roadside Units (RSUs). For 5G and beyond, mmWave and MEC will play important roles for a diverse set of applications that require both ultra-high data rate and low latency communications.

This paper discusses the unambiguous estimation of high-order BOC signals in the cloud based on signal snapshots gathered by low-end SDR receivers. In particular, the sensitivity and distortion problems are introduced, assessing the probability of false lock when using a conventional ML-based estimator (based on the search of the absolute maximum of the cross-correlation function) and a post-correlation ML-based estimator exploiting the a priori known distortion of the cross-correlation function introduced by the filtering stage of the SDR receiver. The simulation results show that, while distortion issues can be handled, sensitivity remains a problem at low C/No conditions and when limited snapshot lengths are considered., Peer Reviewed, Postprint (published version)