Loss of C9orf72 perturbs the Ran-GTPase gradient and generates compositionally diverse cytoplasmic Importin β-1 granules in motor and cortical neurons in vivo

Repeat expansions in C9orf72 cause Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal Dementia (FTD) eliciting toxic effects through generation of RNA foci, dipeptide repeat proteins and/or loss of C9orf72 protein. Defects in nucleocytoplasmic transport (NCT) have been implicated as a pathogenic mechanism underlying repeat expansion toxicity. Here, we show that loss of C9orf72 causes neuronal specific phenotypes, disrupting the Ran-GTPase gradient both in vitro and in vivo. We describe compositionally different types of cytoplasmic Importin β-1 granules that exhibit neuronal subtype-specific properties in vivo. We show that the abundance of Importin β-1 granules is increased in the context of C9orf72 deficiency, disrupting interactions with nuclear pore complex proteins. These granules appear to bud from the nuclear envelope and are co-immunoreactive for G3BP1 and K63-ubiquitin. These findings link loss of C9orf72 protein to gain-of-function mechanisms and defects in NCT.

Performance of UAV-to-Ground FSO Communications with APD and Pointing Errors

Recently, a combination of unmanned aerial vehicles (UAVs) and free-space optics (FSO) has been investigated as a potential method for high data-rate front-haul communication links. The aim of this work was to address the performance of UAV-to-ground station-based FSO communications in terms of the symbol error rate (SER). The system proposes utilizing subcarrier intensity modulation and an avalanche photo-diode (APD) to combat the joint effects of atmospheric turbulence conditions and pointing error due to the UAV’s fluctuations. In the proposed system model, the FSO transmitter (Tx) is mounted on the UAV flying over the monitoring area, whereas the FSO receiver (Rx) is placed on either the ground or top of a high building. Unlike previous works related to this topic, we considered combined channel parameters that affect the system performance such as transmitted power, link loss, various atmospheric turbulence conditions, pointing error loss, and the total noise at the APD receiver. Numerical results have shown that, for the best system SER performance, the value of an average APD gain at the Rx can be selected, varying from 18 to 30, whereas the equivalent beam waist radius at the Tx should be in a range from 2 to 2.2 cm in order to decrease the effects from the UAV’s fluctuations.

Loss of Pseudouridine Synthases in the RluA Family Causes Hypersensitive Nociception in Drosophila

Nociceptive neurons of Drosophila melanogaster larvae are characterized by highly branched dendritic processes whose proper morphogenesis relies on a large number of RNA-binding proteins. Post-transcriptional regulation of RNA in these dendrites has been found to play an important role in their function. Here, we investigate the neuronal functions of two putative RNA modification genes, RluA-1 and RluA-2, which are predicted to encode pseudouridine synthases. RluA-1 is specifically expressed in larval sensory neurons while RluA-2 expression is ubiquitous. Nociceptor-specific RNAi knockdown of RluA-1 caused hypersensitive nociception phenotypes, which were recapitulated with genetic null alleles. These were rescued with genomic duplication and nociceptor-specific expression of UAS-RluA-1-cDNA. As with RluA-1, RluA-2 loss of function mutants also displayed hyperalgesia. Interestingly, nociceptor neuron dendrites showed a hyperbranched morphology in the RluA-1 mutants. The latter may be a cause or a consequence of heightened sensitivity in mutant nociception behaviors.

Fibrocystin Is Essential to Cellular Control of Adhesion and Epithelial Morphogenesis

Mutations of the Pkhd1 gene cause autosomal recessive polycystic kidney disease (ARPKD). Pkhd1 encodes fibrocystin/polyductin (FPC), a ciliary type I membrane protein of largely unknown function, suggested to affect adhesion signaling of cells. Contributions of epithelial cell adhesion and contractility to the disease process are elusive. Here, we link loss of FPC to defective epithelial morphogenesis in 3D cell culture and altered cell contact formation. We study Pkhd1-silenced Madin-Darby Canine Kidney II (MDCKII) cells using an epithelial morphogenesis assay based on micropatterned glass coverslips. The assay allows analysis of cell adhesion, polarity and lumen formation of epithelial spheroids. Pkhd1 silencing critically affects the initial phase of the morphogenesis assay, leading to a reduction of correctly polarized spheroids by two thirds. Defects are characterized by altered cell adhesion and centrosome positioning of FPC-deficient cells in their 1-/2-cell stages. When myosin II inhibitor is applied to reduce cellular tension during the critical early phase of the assay, Pkhd1 silencing no longer inhibits formation of correctly polarized epithelia. We propose that altered sensing and cell interaction of FPC-deficient epithelial cells promote progressive epithelial defects in ARPKD.

A Novel Route Deviation and Optimization Algorithm Using Simulation-Optimization and Energy Efficient Constraints for Minimizing Link-Loss and Loop Problems in Wireless Sensor Network

Wireless and mobile devices and networks are an integral part of today’s life. With the advancement of technology, a large number of smart devices with advanced computational and communicational types of equipment are designed and developed. With these advancements, the availability of services over these devices is required to be of high quality for ensuring better experiences day by day. Thus, network performance improvement with minimum path loss and optimized packet delivery without loops is a major concern to integrate the existing network infrastructure with advanced and future networks. This work has designed a novel route deviation and optimization algorithm with simulation optimization and energy efficiency constraints. The simulation-optimization approach is considered to have minimum link losses and avoid the loop problem. Whereas, local and global simulation optimization processes are followed to identify the best possibilities in route identification in consideration with local and network environment settings. The proposed approach is statistically found to have a minimum error rate and optimizes the performance with computational and communicational overheads. In results, a minimum of 10 seconds and a maximum of 150 seconds are observed before a device using the proposed approach gets utilized fully. Thus, the proposed approach is very effective for link loss and loop problems in wireless sensor networks. Further, an improvement of 135 (approx.) is observed in the proposed approach.

Link Loss Inference Algorithm with Network Topology Aware in Communication Networks

When there are many suspected loss links, the links in the path with a higher pass rate are assumed to be nondrop packet links or assuming that the link with the largest number of shares is a loss link, but this assumption lacks valid proof. In order to overcome these shortcomings, this paper proposes a link loss inference algorithm with network topology aware. The network model is established based on the historical data of the network operation and network topology characteristics. A weighted relative entropy ranking method is proposed to quantify the suspected packet loss links in each independent subset. The packet loss rate of the packet loss link is obtained by solving the unique solution of the simplified nonsingular matrix. Through simulation experiments, it is verified that the proposed algorithm has achieved better results in terms of congestion link determination and link loss rate estimation accuracy.

Models for Eco-evolutionary Extinction Vortices and their Detection

The smaller a population is, the faster it looses genetic variation due to genetic drift. Loss of genetic variation can reduce population growth rate, making populations even smaller and more vulnerable to loss of genetic variation, and so on. Ultimately, the population can be driven to extinction by this “eco-evolutionary extinction vortex”. So far, extinction vortices due to loss of genetic variation have been mainly described verbally. However, quantitative models are needed to better understand when such vortices arise and to develop methods for detecting them. Here we propose quantitative eco-evolutionary models, both individual-based simulations and analytic approximations, that link loss of genetic variation and population decline. Our models assume stochastic population dynamics and multi-locus genetics with different forms of balancing selection. Using mathematical analysis and simulations, we identify parameter combinations that exhibit strong interactions between population size and genetic variation as populations decline to extinction and match our definition of an eco-evolutionary vortex, i.e. the per-capita population decline rates and per-locus fixation rates increase with decreasing population size and number of polymorphic loci. We further highlight cues and early warning signals that may be useful in identifying populations undergoing an eco-evolutionary extinction vortex.