Neuronal Expression of Neural Nitric Oxide Synthase (nNOS) Protein is Suppressed by an Antisense RNA Transcribed from an NOS Pseudogene

Here, we show that a nitric oxide synthase (NOS) pseudogene is expressed in the CNS of the snail Lymnaea stagnalis. The pseudo-NOS transcript includes a region of significant antisense homology to a previously reported neuronal NOS (nNOS)-encoding mRNA. This suggested that the pseudo-NOS transcript acts as a natural antisense regulator of nNOS protein synthesis. In support of this, we show that both the nNOS-encoding and the pseudo-NOS transcripts are coexpressed in giant identified neurons (the cerebral giant cells) in the cerebral ganglion. Moreover, reverse transcription-PCR experiments on RNA isolated from the CNS establish that stable RNA-RNA duplex molecules do form between the two transcripts in vivo. Using an in vitro translation assay, we further demonstrate that the antisense region of the pseudogene transcript prevents the translation of nNOS protein from the nNOS-encoding mRNA. By analyzing NOS RNA and nNOS protein expression in two different identified neurons, we find that when both the nNOS-encoding and the pseudo-NOS transcripts are present in the same neuron, nNOS enzyme activity is substantially suppressed. Importantly, these results show that a natural antisense mechanism can mediate the translational control of nNOS expression in the Lymnaea CNS. Our findings also suggest that transcribed pseudogenes are not entirely without purpose and are a potential source of a new class of regulatory gene in the nervous system

Immunogene therapy with fusogenic nanoparticles modulates macrophage response to Staphylococcus aureus.

The incidence of adverse effects and pathogen resistance encountered with small molecule antibiotics is increasing. As such, there is mounting focus on immunogene therapy to augment the immune system's response to infection and accelerate healing. A major obstacle to in vivo gene delivery is that the primary uptake pathway, cellular endocytosis, results in extracellular excretion and lysosomal degradation of genetic material. Here we show a nanosystem that bypasses endocytosis and achieves potent gene knockdown efficacy. Porous silicon nanoparticles containing an outer sheath of homing peptides and fusogenic liposome selectively target macrophages and directly introduce an oligonucleotide payload into the cytosol. Highly effective knockdown of the proinflammatory macrophage marker IRF5 enhances the clearance capability of macrophages and improves survival in a mouse model of Staphyloccocus aureus pneumonia

Optimal design of quadratic electromagnetic exciter

The vibration acceleration of collecting plates, which is the core indicator of rapping performance in an electrostatic precipitator’s vibration rapping process, is determined by magnetic force of a quadratic electromagnetic exciter. The larger exciter provides the larger magnetic force, but the installation space for the exciter is limited. Accordingly, this paper presents the optimal design of quadratic electromagnetic exciter to maximize the magnetic force with constraint that the size of exciter is constant. A design optimization problem was formulated in order to find the quadratic electromagnetic exciter shape parameters that maximized the magnetic force. The magnetic force of the quadratic electromagnetic exciter was evaluated using the commercial electromagnetic analysis software “MAXWELL”. For efficient design, we employed metamodel-based design optimization using design of experiments (DOE), metamodels, and an optimization algorithm equipped in PIAnO (Process Integration, Automation and Optimization), a commercial PIDO (Process Integration and Design Optimization) tool. Using the proposed design approach, the optimal magnetic force was increased by 1.68 % compared to the initial one. This result demonstrates the effectiveness of the established analysis and design procedure for the quadratic electromagnetic exciter

Accurate Distance Estimation between Things: A Self-correcting Approach

This paper suggests a method to measure the physical distance between an IoT device (a Thing) and a mobile device (also a Thing) using BLE (Bluetooth Low-Energy profile) interfaces with smaller distance errors. BLE is a well-known technology for the low-power connectivity and suitable for IoT devices as well as for the proximity with the range of several meters. Apple has already adopted the technique and enhanced it to provide subdivided proximity range levels. However, as it is also a variation of RSS-based distance estimation, Apple's iBeacon could only provide immediate, near or far status but not a real and accurate distance. To provide more accurate distance using BLE, this paper introduces additional self-correcting beacon to calibrate the reference distance and mitigate errors from environmental factors. By adopting self-correcting beacon for measuring the distance, the average distance error shows less than 10% within the range of 1.5 meters. Some considerations are presented to extend the range to be able to get more accurate distances

THE EFFECT OF SHOULDER MOBILITY ON AGONIST AND SYNERGIST DURING SHOULDER PRESS

The purpose of this study was to investigate the effect of shoulder mobility score on agonist and synergist muscle activation during shoulder press and to provide an underpinning fundamental to optimize the training effect while reducing the risk of injuries when instructing training in the field. The participants were divided to two different groups according to individual shoulder mobility score which is part of the Functional Movement Screen (FMS). There were five participants in the score of 3 group (upper group) and six included in the group with the score of less than 3 (lower group). The results of this study revealed that the shoulder mobility score showed a negative correlation with the ratio of the left and right latissimus dorsi/anterior deltoid muscle activation in the concentric contraction phase (

Screening for Early Gastric Cancer Using a Noninvasive Urine Metabolomics Approach

The early detection of gastric cancer (GC) could decrease its incidence and mortality. However, there are currently no accurate noninvasive markers for GC screening. Therefore, we developed a noninvasive diagnostic approach, employing urine nuclear magnetic resonance (NMR) metabolomics, to discover putative metabolic markers associated with GC. Changes in urine metabolite levels during oncogenesis were evaluated using samples from 103 patients with GC and 100 age- and sex-matched healthy controls. Approximately 70% of the patients with GC (n = 69) had stage I GC, with the majority (n = 56) having intramucosal cancer. A multivariate statistical analysis of the urine NMR data well discriminated between the patient and control groups and revealed nine metabolites, including alanine, citrate, creatine, creatinine, glycerol, hippurate, phenylalanine, taurine, and 3-hydroxybutyrate, that contributed to the difference. A diagnostic performance test with a separate validation set exhibited a sensitivity and specificity of more than 90%, even with the intramucosal cancer samples only. In conclusion, the NMR-based urine metabolomics approach may have potential as a convenient screening method for the early detection of GC and may facilitate consequent endoscopic examination through risk stratification