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Wireless Mesh Networks (WMNs) can build a communications infrastructure using only routers (called mesh routers), making it possible to form networks over a wide area at low cost. The mesh routers cover clients (called mesh clients), allowing mesh clients to communicate with different nodes. Since the communication performance of WMNs is affected by the position of mesh routers, the communication performance can be improved by optimizing the mesh router placement. In this paper, we present a Coverage Construction Method (CCM) that optimizes mesh router placement. In addition, we propose an integrated optimization approach that combine Simulated Annealing (SA) and Delaunay Edges (DE) in CCM to improve the performance of mesh router placement optimization. The proposed approach can build and provide a communication infrastructure by WMNs in disaster environments. We consider a real scenario for the placement of mesh clients in an evacuation area of Kurashiki City, Japan. From the simulation results, we found that the proposed approach can optimize the placement of mesh routers in order to cover all mesh clients in the evacuation area. Additionally, the DECCM-based SA approach covers more mesh clients than the CCM-based SA approach on average and can improve network connectivity of WMNs.

Lipoarabinomannan (LAM) is a major antigen of Mycobacterium tuberculosis (MTB). In this report, we evaluated the ability of a novel immunoassay to measure concentrations of LAM in sputum as a biomarker of bacterial load prior to and during treatment in pulmonary tuberculosis (TB) patients. Phage display technology was used to isolate monoclonal antibodies binding to epitopes unique in LAM from MTB and slow-growing nontuberculous mycobacteria (NTM). Using these antibodies, a sandwich enzyme-linked immunosorbent assay (LAM-ELISA) was developed to quantitate LAM concentration. The LAM-ELISA had a lower limit of quantification of 15 pg/mL LAM, corresponding to 121 colony-forming units (CFUs)/mL of MTB strain H37Rv. It detected slow-growing NTMs but without cross-reacting to common oral bacteria. Two clinical studies were performed between the years 2013 and 2016 in Manila, Philippines, in patients without known human immunodeficiency virus (HIV) coinfection. In a case-control cohort diagnostic study, sputum specimens were collected from 308 patients (aged 17-69 years; 62% male) diagnosed as having pulmonary TB diseases or non-TB diseases, but who could expectorate sputum, and were then evaluated by smear microscopy, BACTEC MGIT 960 Mycobacterial Detection System (MGIT) and Lowenstein-Jensen (LJ) culture, and LAM-ELISA. Some sputum specimens were also examined by Xpert MTB/RIF. The LAM-ELISA detected all smear- and MTB-culture-positive samples (n = 70) and 50% (n = 29) of smear-negative but culture-positive samples (n = 58) (versus 79.3%; 46 positive cases by the Xpert MTB/RIF), but none from non-TB patients (n = 56). Among both LAM and MGIT MTB-culture-positive samples, log10-transformed LAM concentration and MGIT time to detection (TTD) showed a good inverse relationship (r = -0.803, p < 0.0001). In a prospective longitudinal cohort study, 40 drug-susceptible pulmonary TB patients (aged 18-69 years; 60% male) were enrolled during the first 56 days of the standard 4-drug therapy. Declines in sputum LAM concentrations correlated with increases of MGIT TTD in individual patients. There was a 1.29 log10 decrease of sputum LAM concentration, corresponding to an increase of 221 hours for MGIT TTD during the first 14 days of treatment, a treatment duration often used in early bactericidal activity (EBA) trials. Major limitations of this study include a relatively small number of patients, treatment duration up to only 56 days, lack of quantitative sputum culture CFU count data, and no examination of the correlation of sputum LAM to clinical cure. These results indicate that the LAM-ELISA can determine LAM concentration in sputum, and sputum LAM measured by the assay may be used as a biomarker of bacterial load prior to and during TB treatment. Additional studies are needed to examine the predictive value of this novel biomarker on treatment outcomes.

Wireless mesh networks (WMNs) are attracting a lot of attention from wireless network researchers. Node placement problems have been investigated for a long time in the optimization field due to numerous applications in location science. In our previous work, we evaluated WMN-GA system which is based on genetic algorithms (GAs) to find an optimal location assignment for mesh routers. In this paper, we evaluate the performance of four different distributions of mesh clients for two WMN architectures considering throughput, delay and energy metrics. For simulations, we used ns-3, optimized link state routing (OLSR) and hybrid wireless mesh protocols (HWMP). We compare the performance for Normal, Uniform, Exponential and Weibull distributions of mesh clients by sending multiple constant bit rate flows in the network. The simulation results show that for HWM protocol the throughput of Uniform distribution is higher than other distributions. However, for OLSR protocol, the throughput of Exponential distribution is better than other distributions. For both protocols, the delay and remaining energy are better for Weibull distribution.

Talking antisense: fukutin rescue in muscular dystrophy Fukuyama muscular dystrophy is caused by the insertion of a mobile genetic element, the SVA retrotransposon, into the non-coding region of the fukutin gene. Tatsushi Toda and colleagues show that this insertion truncates the fukutin transcript as a result of an abnormal splicing event, a situation known as pathogenic exon trapping. Fukutin function is restored by treatment of dystrophy mouse model cells or human patient cells with antisense oligonucleotides that prevent the abnormal splicing. The results have implications for other diseases that show SVA exon trapping. Fukuyama muscular dystrophy (FCMD; MIM253800), one of the most common autosomal recessive disorders in Japan, was the first human disease found to result from ancestral insertion of a SINE-VNTR- Alu (SVA) retrotransposon into a causative gene 1 , 2 , 3 . In FCMD, the SVA insertion occurs in the 3′ untranslated region (UTR) of the fukutin gene. The pathogenic mechanism for FCMD is unknown, and no effective clinical treatments exist. Here we show that aberrant messenger RNA (mRNA) splicing, induced by SVA exon-trapping, underlies the molecular pathogenesis of FCMD. Quantitative mRNA analysis pinpointed a region that was missing from transcripts in patients with FCMD. This region spans part of the 3′ end of the fukutin coding region, a proximal part of the 3′ UTR and the SVA insertion. Correspondingly, fukutin mRNA transcripts in patients with FCMD and SVA knock-in model mice were shorter than the expected length. Sequence analysis revealed an abnormal splicing event, provoked by a strong acceptor site in SVA and a rare alternative donor site in fukutin exon 10. The resulting product truncates the fukutin carboxy (C) terminus and adds 129 amino acids encoded by the SVA. Introduction of antisense oligonucleotides (AONs) targeting the splice acceptor, the predicted exonic splicing enhancer and the intronic splicing enhancer prevented pathogenic exon-trapping by SVA in cells of patients with FCMD and model mice, rescuing normal fukutin mRNA expression and protein production. AON treatment also restored fukutin functions, including O -glycosylation of α-dystroglycan (α-DG) and laminin binding by α-DG. Moreover, we observe exon-trapping in other SVA insertions associated with disease (hypercholesterolemia 4 , neutral lipid storage disease 5 ) and human-specific SVA insertion in a novel gene. Thus, although splicing into SVA is known 6 , 7 , 8 , we have discovered in human disease a role for SVA-mediated exon-trapping and demonstrated the promise of splicing modulation therapy as the first radical clinical treatment for FCMD and other SVA-mediated diseases.

The control of water levels in various environments is very important for predicting flooding and mitigating flood damages. Generally, water level device gauges are used to measure water levels, but the structural setting of reservoirs presents significant challenges for the installation of water level device gauges. Therefore, the solution to this problem is to apply image recognition methods using water level device gauges. In this paper, we present an intelligent water level estimation system considering water level device gauge image recognition and a Wireless Sensor Network (WSN). We carried out experiments in a water reservoir to evaluate the proposed system. From the experimental results, we found that the proposed system can estimate the water level via the object recognition of numbers and symbols on the water level device gauge.

Immune responses to parasitic pathogens are affected by the host physiological condition. High-density lipoprotein (HDL) and low-density lipoprotein (LDL) are transporters of lipids between the liver and peripheral tissues, and modulate pro-inflammatory immune responses. Pathogenic mycobacteria are parasitic intracellular bacteria that can survive within macrophages for a long period. Macrophage function is thus key for host defense against mycobacteria. These basic facts suggest possible effects of HDL and LDL on mycobacterial diseases, which have not been elucidated so far. In this study, we found that HDL and not LDL enhanced mycobacterial infections in human macrophages. Nevertheless, we observed that HDL remarkably suppressed production of tumor necrosis factor alpha (TNF-α) upon mycobacterial infections. TNF-α is a critical host-protective cytokine against mycobacterial diseases. We proved that toll-like receptor (TLR)-2 is responsible for TNF-α production by human macrophages infected with mycobacteria. Subsequent analysis showed that HDL downregulates TLR2 expression and suppresses its intracellular signaling pathways. This report demonstrates for the first time the substantial action of HDL in mycobacterial infections to human macrophages.

Objective Amyotrophic lateral sclerosis (ALS) is a devastating, incurable neurodegenerative disease. A subset of ALS patients manifests with early‐onset and complex clinical phenotypes. We aimed to elucidate the genetic basis of these cases to enhance our understanding of disease etiology and facilitate the development of targeted therapies. Methods Our research commenced with an in‐depth genetic and biochemical investigation of two specific families, each with a member diagnosed with early‐onset ALS (onset age of <40 years). This involved whole‐exome sequencing, trio analysis, protein structure analysis, and sphingolipid measurements. Subsequently, we expanded our analysis to 62 probands with early‐onset ALS and further included 440 patients with adult‐onset ALS and 1163 healthy controls to assess the prevalence of identified genetic variants. Results We identified heterozygous variants in the serine palmitoyltransferase long chain base subunit 2 (SPTLC2) gene in patients with early‐onset ALS. These variants, located in a region closely adjacent to ORMDL3, bear similarities to SPTLC1 variants previously implicated in early‐onset ALS. Patients with ALS carrying these SPTLC2 variants displayed elevated plasma ceramide levels, indicative of increased serine palmitoyltransferase (SPT) activity leading to sphingolipid overproduction. Interpretation Our study revealed novel SPTLC2 variants in patients with early‐onset ALS exhibiting frontotemporal dementia. The combination of genetic evidence and the observed elevation in plasma ceramide levels establishes a crucial link between dysregulated sphingolipid metabolism and ALS pathogenesis. These findings expand our understanding of ALS's genetic diversity and highlight the distinct roles of gene defects within SPT subunits in its development.

Wireless Mesh Networks (WMNs) have become an important networking infrastructure for providing cost-efficient broadband wireless connectivity. WMNs are showing their applicability in deployment of medical, transport and surveillance applications in urban areas, metropolitan, neighboring communities and municipal area networks. In this paper, we deal with connectivity and coverage problem of WMN. Because these problems are known to be NP-Hard, we propose and implement a system based on Genetic Algorithms (GAs). We evaluate the performance of the proposed system by different scenarios using different metrics such as client distribution, crossover rate, mutation rate, coverage area and giant component. The simulation results show that for 32 × 32 and 64 × 64 grid area, Linear Ranking is good selection operator and offers the best network connectivity and user coverage.

Wireless mesh networks (WMNs) are cost-efficient networks that have the potential to serve as an infrastructure for advanced location-based services. Location service is a desired feature for WMNs to support location-oriented applications. WMNs are also interesting infrastructures for supporting ubiquitous multimedia Internet access for mobile or fixed mesh clients. In order to efficiently support such services and offering QoS , the optimized placement of mesh router nodes is very important. Indeed, such optimized mesh placement can support location service managed in the mesh and keep the rate of location updates low. This node location-based problem has been shown to be NP-hard and thus is unlikely to be solvable in reasonable amount of time. Therefore, heuristic methods, such as genetic algorithms (GAs), are used as resolution methods. In this paper, we deal with the effect of population size for location-aware node placement in WMNs. Our WMN-GA system uses GA to determine the positions of the mesh routers and mesh clients in the grid area. We used a location-aware node placement of mesh router in cells of considered grid area to maximize network connectivity and user coverage. We evaluate the performance of the proposed and implemented WMN-GA system for low and high density of clients considering different distributions and considering giant component and number of covered users parameters. The simulation results show that for low-density networks, with the increasing of population size, GA obtains better result. However, with the increase in the population size, the GA needs more computational time. The proposed system has better performance in dense networks like hot spots for Weibull distribution when the population size is big.

In this paper, we evaluate the performance of two WMN architectures (infrastructure/backbone WMNs (I/B WMNs) and Hybrid WMN architectures) considering throughput, delay, jitter and fairness index metrics. For simulations, we used ns-3 and optimized link state routing. We compare the performance of distributed coordination function and enhanced distributed channel access (EDCA) for exponential and Weibull distributions of mesh clients by sending multiple constant bit rate flows in the network. The simulation results show that for exponential distribution, in case of Hybrid WMN, the throughput of both MAC protocols is higher than I/B WMN. For 30 flows, the throughput of EDCA in case of hybrid WMN is about 1.4 times higher than I/B WMN. For Weibull distribution, in case of I/B WMN, the throughput of both MAC protocols is higher than Hybrid WMN. For 30 flows, the throughput of EDCA in case of I/B WMN is about 2.6 times higher than Hybrid WMN. For exponential distribution, the delay and jitter of Hybrid WMN are lower than I/B WMN. For 20 flows, the delay of EDCA in case of hybrid WMN is about 10 times lower than I/B WMN. For Weibull distribution, the delay and jitter of both architectures are almost the same. However, for 10 flows, the delay of I/B WMN is lower compared with hybrid WMN. For exponential distribution, the fairness index of I/B WMN is a little bit higher than hybrid WMN. For Weibull distribution, the fairness index is almost the same for both WMN architectures.