Quorum sensing is a unique bacterial communication system which permits bacteria to synchronize their behaviour in accordance with the population density. The operation of this communication network involves the use of diffusible autoinducer molecules, termed N-acylhomoserine lactones (AHLs). Serratia spp. are well known for their use of quorum sensing to regulate the expression of various genes. In this study, we aimed to characterized the AHL production of a bacterium designated as strain RB-25 isolated from a former domestic waste landfill site. It was identified as Serratia fonticola using matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry analysis and this was confirmed by 16S ribosomal DNA sequencing. High resolution triple quadrupole liquid chromatography-mass spectrometry analysis of S. fonticola strain RB-25 spent culture supernatant indicated the existence of three AHLs namely: N-butyryl-L-homoserine lactone (C4-HSL), N-hexanoyl-L-homoserine lactone (C6-HSL) and N-(3-oxohexanoyl) homoserine-lactone (3-oxo-C6 HSL). This is the first report of the production of these AHLs in S. fonticola.
Image corner detection is a fundamental task in computer vision. Many applications require reliable detectors to accurately detect corner points, commonly achieved by using image contour information. The curvature definition is sensitive to local variation and edge aliasing, and available smoothing methods are not sufficient to address these problems properly. Hence, we propose Mean Projection Transform (MPT) as a corner classifier and parabolic fit approximation to form a robust detector. The first step is to extract corner candidates using MPT based on the integral properties of the local contours in both the horizontal and vertical directions. Then, an approximation of the parabolic fit is calculated to localize the candidate corner points. The proposed method presents fewer false-positive (FP) and false-negative (FN) points compared with recent standard corner detection techniques, especially in comparison with curvature scale space (CSS) methods. Moreover, a new evaluation metric, called accuracy of repeatability (AR), is introduced. AR combines repeatability and the localization error (Le) for finding the probability of correct detection in the target image. The output results exhibit better repeatability, localization, and AR for the detected points compared with the criteria in original and transformed images.
Wireless Body Sensor Networks (WBSNs) constitute a subset of Wireless Sensor Networks (WSNs) responsible for monitoring vital sign-related data of patients and accordingly route this data towards a sink. In routing sensed data towards sinks, WBSNs face some of the same routing challenges as general WSNs, but the unique requirements of WBSNs impose some more constraints that need to be addressed by the routing mechanisms. This paper identifies various issues and challenges in pursuit of effective routing in WBSNs. Furthermore, it provides a detailed literature review of the various existing routing protocols used in the WBSN domain by discussing their strengths and weaknesses.
The discovery of quorum sensing in Proteobacteria and its function in regulating virulence determinants makes it an attractive alternative towards attenuation of bacterial pathogens. In this study, crude extracts of Phyllanthus amarus Schumach. & Thonn, a traditional Chinese herb, were screened for their anti-quorum sensing properties through a series of bioassays. Only the methanolic extract of P. amarus exhibited anti-quorum sensing activity, whereby it interrupted the ability of Chromobacterium violaceum CVO26 to response towards exogenously supplied N-hexanoylhomoserine lactone and the extract reduced bioluminescence in E. coli [pSB401] and E. coli [pSB1075]. In addition to this, methanolic extract of P. amarus significantly inhibited selected quorum sensing-regulated virulence determinants of Pseudomonas aeruginosa PA01. Increasing concentrations of the methanolic extracts of P. amarus reduced swarming motility, pyocyanin production and P. aeruginosa PA01 lecA::lux expression. Our data suggest that P. amarus could be useful for attenuating pathogens and hence, more local traditional herbs should be screened for its anti-quorum sensing properties as their active compounds may serve as promising anti-pathogenic drugs.
Combined computational and experimental strategies for the systematic design of chemical sensor arrays using carbonitrile neutral receptors are presented. Binding energies of acetonitrile, n-pentylcarbonitrile and malononitrile with Ca(II), Mg(II), Be(II) and H⁺ have been investigated with the B3LYP, G3, CBS-QB3, G4 and MQZVP methods, showing a general trend H⁺ > Be(II) > Mg(II) > Ca(II). Hydrogen bonding, donor-acceptor and cation-lone pair electron simple models were employed in evaluating the performance of computational methods. Mg(II) is bound to acetonitrile in water by 12.5 kcal/mol, and in the gas phase the receptor is more strongly bound by 33.3 kcal/mol to Mg(II) compared to Ca(II). Interaction of bound cations with carbonitrile reduces the energies of the MOs involved in the proposed σ-p conjugated network. The planar malononitrile-Be(II) complex possibly involves a π-network with a cationic methylene carbon. Fabricated potentiometric chemical sensors show distinct signal patterns that can be exploited in sensor array applications.
Interest in the cognitive radio sensor network (CRSN) paradigm has gradually grown among researchers. This concept seeks to fuse the benefits of dynamic spectrum access into the sensor network, making it a potential player in the next generation (NextGen) network, which is characterized by ubiquity. Notwithstanding its massive potential, little research activity has been dedicated to the network layer. By contrast, we find recent research trends focusing on the physical layer, the link layer and the transport layers. The fact that the cross-layer approach is imperative, due to the resource-constrained nature of CRSNs, can make the design of unique solutions non-trivial in this respect. This paper seeks to explore possible design opportunities with wireless sensor networks (WSNs), cognitive radio ad-hoc networks (CRAHNs) and cross-layer considerations for implementing viable CRSN routing solutions. Additionally, a detailed performance evaluation of WSN routing strategies in a cognitive radio environment is performed to expose research gaps. With this work, we intend to lay a foundation for developing CRSN routing solutions and to establish a basis for future work in this area.
Human motion is a daily and rhythmic activity. The exoskeleton concept is a very positive scientific approach for human rehabilitation in case of lower limb impairment. Although the exoskeleton shows potential, it is not yet applied extensively in clinical rehabilitation. In this research, a fuzzy based control algorithm is proposed for lower limb exoskeletons during sit-to-stand and stand-to-sit movements. Surface electromyograms (EMGs) are acquired from the vastus lateralis muscle using a wearable EMG sensor. The resultant acceleration angle along the z-axis is determined from a kinematics sensor. Twenty volunteers were chosen to perform the experiments. The whole experiment was accomplished in two phases. In the first phase, acceleration angles and EMG data were acquired from the volunteers during both sit-to-stand and stand-to-sit motions. During sit-to-stand movements, the average acceleration angle at activation was 11°-48° and the EMG varied from -0.19 mV to +0.19 mV. On the other hand, during stand-to-sit movements, the average acceleration angle was found to be 57.5°-108° at the activation point and the EMG varied from -0.32 mV to +0.32 mV. In the second phase, a fuzzy controller was designed from the experimental data. The controller was tested and validated with both offline and real time data using LabVIEW.
A simple visual ethanol biosensor based on alcohol oxidase (AOX) immobilised onto polyaniline (PANI) film for halal verification of fermented beverage samples is described. This biosensor responds to ethanol via a colour change from green to blue, due to the enzymatic reaction of ethanol that produces acetaldehyde and hydrogen peroxide, when the latter oxidizes the PANI film. The procedure to obtain this biosensor consists of the immobilization of AOX onto PANI film by adsorption. For the immobilisation, an AOX solution is deposited on the PANI film and left at room temperature until dried (30 min). The biosensor was constructed as a dip stick for visual and simple use. The colour changes of the films have been scanned and analysed using image analysis software (i.e., ImageJ) to study the characteristics of the biosensor's response toward ethanol. The biosensor has a linear response in an ethanol concentration range of 0.01%-0.8%, with a correlation coefficient (r) of 0.996. The limit detection of the biosensor was 0.001%, with reproducibility (RSD) of 1.6% and a life time up to seven weeks when stored at 4 °C. The biosensor provides accurate results for ethanol determination in fermented drinks and was in good agreement with the standard method (gas chromatography) results. Thus, the biosensor could be used as a simple visual method for ethanol determination in fermented beverage samples that can be useful for Muslim community for halal verification.
Proteobacteria produce N-acylhomoserine lactones as signaling molecules, which will bind to their cognate receptor and activate quorum sensing-mediated phenotypes in a population-dependent manner. Although quorum sensing signaling molecules can be degraded by bacteria or fungi, there is no reported work on the degradation of such molecules by basidiomycetous yeast. By using a minimal growth medium containing N-3-oxohexanoylhomoserine lactone as the sole source of carbon, a wetland water sample from Malaysia was enriched for microbial strains that can degrade N-acylhomoserine lactones, and consequently, a basidiomycetous yeast strain WW1C was isolated. Morphological phenotype and molecular analyses confirmed that WW1C was a strain of Trichosporon loubieri. We showed that WW1C degraded AHLs with N-acyl side chains ranging from 4 to 10 carbons in length, with or without oxo group substitutions at the C3 position. Re-lactonisation bioassays revealed that WW1C degraded AHLs via a lactonase activity. To the best of our knowledge, this is the first report of degradation of N-acyl-homoserine lactones and utilization of N-3-oxohexanoylhomoserine as carbon and nitrogen source for growth by basidiomycetous yeast from tropical wetland water; and the degradation of bacterial quorum sensing molecules by an eukaryotic yeast.
A novel method for the rapid modification of fullerene for subsequent enzyme attachment to create a potentiometric biosensor is presented. Urease was immobilized onto the modified fullerene nanomaterial. The modified fullerene-immobilized urease (C60-urease) bioconjugate has been confirmed to catalyze the hydrolysis of urea in solution. The biomaterial was then deposited on a screen-printed electrode containing a non-plasticized poly(n-butyl acrylate) (PnBA) membrane entrapped with a hydrogen ionophore. This pH-selective membrane is intended to function as a potentiometric urea biosensor with the deposition of C60-urease on the PnBA membrane. Various parameters for fullerene modification and urease immobilization were investigated. The optimal pH and concentration of the phosphate buffer for the urea biosensor were 7.0 and 0.5 mM, respectively. The linear response range of the biosensor was from 2.31 × 10-3 M to 8.28 × 10-5 M. The biosensor's sensitivity was 59.67 ± 0.91 mV/decade, which is close to the theoretical value. Common cations such as Na+, K+, Ca2+, Mg2+ and NH4+ showed no obvious interference with the urea biosensor's response. The use of a fullerene-urease bio-conjugate and an acrylic membrane with good adhesion prevented the leaching of urease enzyme and thus increased the stability of the urea biosensor for up to 140 days.
Klebsiella pneumoniae is one of the most common Gram-negative bacterial pathogens in clinical practice. It is associated with a wide range of disorders, ranging from superficial skin and soft tissue infections to potentially fatal sepsis in the lungs and blood stream. Quorum sensing, or bacterial cell-cell communication, refers to population density-dependent gene expression modulation. Quorum sensing in Proteobacteria relies on the production and sensing of signaling molecules which are mostly N-acylhomoserine lactones. Here, we report the identification of a multidrug resistant clinical isolate, K. pneumoniae strain CSG20, using matrix-assisted laser desorption ionization-time-of-flight (MALDI-TOF) mass spectrometry. We further confirmed quorum sensing activity in this strain with the use of high resolution tandem liquid chromatography quadrupole mass spectrometry and provided evidence K. pneumoniae strain CSG20 produced N-hexanoyl-homoserine lactone (C6-HSL). To the best of our knowledge, this is the first report on the production of N-hexanoylhomoserine lactone (C6-HSL) in clinical isolate K. pneumoniae.
Bacterial cell-to-cell communication (quorum sensing) refers to the regulation of bacterial gene expression in response to changes in microbial population density. Quorum sensing bacteria produce, release and respond to chemical signal molecules called autoinducers. Bacteria use two types of autoinducers, namely autoinducer-1 (AI-1) and autoinducer-2 (AI-2) where the former are N-acylhomoserine lactones and the latter is a product of the luxS gene. Most of the reported literatures show that the majority of oral bacteria use AI-2 for quorum sensing but rarely the AI-1 system. Here we report the isolation of Pseudomonas putida strain T2-2 from the oral cavity. Using high resolution mass spectrometry, it is shown that this isolate produced N-octanoylhomoserine lactone (C8-HSL) and N-dodecanoylhomoserine lactone (C12-HSL) molecules. This is the first report of the finding of quorum sensing of P. putida strain T2-2 isolated from the human tongue surface and their quorum sensing molecules were identified.
A nanocrystalline SnO2 thin film was synthesized by a chemical bath method. The parameters affecting the energy band gap and surface morphology of the deposited SnO2 thin film were optimized using a semi-empirical method. Four parameters, including deposition time, pH, bath temperature and tin chloride (SnCl2·2H2O) concentration were optimized by a factorial method. The factorial used a Taguchi OA (TOA) design method to estimate certain interactions and obtain the actual responses. Statistical evidences in analysis of variance including high F-value (4,112.2 and 20.27), very low P-value (<0.012 and 0.0478), non-significant lack of fit, the determination coefficient (R2 equal to 0.978 and 0.977) and the adequate precision (170.96 and 12.57) validated the suggested model. The optima of the suggested model were verified in the laboratory and results were quite close to the predicted values, indicating that the model successfully simulated the optimum conditions of SnO2 thin film synthesis.
For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.
An efficient and low cost optical method for directly measuring the concentration of homogenous biological solutes is proposed and demonstrated. The proposed system operates by Fresnel reflection, with a flat-cleaved single-mode fiber serving as the sensor probe. A laser provides a 12.9 dBm sensor signal at 1,550 nm, while a computer-controlled optical power meter measures the power of the signal returned by the probe. Three different mesenchymal stem cell (MSC) lines were obtained, sub-cultured and trypsinized daily over 9 days. Counts were measured using a haemocytometer and the conditioned media (CM) was collected daily and stored at -80 °C. MSCs release excretory biomolecules proportional to their growth rate into the CM, which changes the refractive index of the latter. The sensor is capable of detecting changes in the number of stem cells via correlation to the change in the refractive index of the CM, with the measured power loss decreasing approximately 0.4 dB in the CM sample per average 1,000 cells in the MSC subculture. The proposed system is highly cost-effective, simple to deploy, operate, and maintain, is non-destructive, and allows reliable real-time measurement of various stem cell proliferation parameters.
In the bacteria kingdom, quorum sensing (QS) is a cell-to-cell communication that relies on the production of and response to specific signaling molecules. In proteobacteria, N-acylhomoserine lactones (AHLs) are the well-studied signaling molecules. The present study aimed to characterize the production of AHL of a bacterial strain A9 isolated from a Malaysian tropical soil. Strain A9 was identified as Burkholderia sp. using matrix-assisted laser desorption ionization-time-of-flight mass spectrometry and 16S rDNA nucleotide sequence analysis. AHL production by A9 was detected with two biosensors, namely Chromobacterium violaceum CV026 and Escherichia coli [pSB401]. Thin layer chromatography results showed N-hexanoylhomoserine lactone (C6-HSL) and N-octanoylhomoserine lactone (C8-HSL) production. Unequivocal identification of C6-HSL and C8-HSL was achieved by high resolution triple quadrupole liquid chromatography-mass spectrometry analysis. We have demonstrated that Burkholderia sp. strain A9 produces AHLs that are known to be produced by other Burkholderia spp. with CepI/CepR homologs.
G-Quadruplex (G-4) structures are formed when G-rich DNA sequences fold into intra- or intermolecular four-stranded structures in the presence of metal ions. G-4-hemin complexes are often effective peroxidase-mimicking DNAzymes that are applied in many detection systems. This work reports the application of a G-rich daunomycin-specific aptamer for the development of an antibody-antigen detection assay. We investigated the ability of the daunomycin aptamer to efficiently catalyze the hemin-dependent peroxidase activity independent of daunomycin. A reporter probe consisting of biotinylated antigen and daunomycin aptamer coupled to streptavidin gold nanoparticles was successfully used to generate a colorimetric readout. In conclusion, the daunomycin aptamer can function as a robust alternative DNAzyme for the development of colorimetric assays.
Bacterial communication or quorum sensing (QS) is achieved via sensing of QS signaling molecules consisting of oligopeptides in Gram-positive bacteria and N-acyl homoserine lactones (AHL) in most Gram-negative bacteria. In this study, Enterobacteriaceae isolates from Batavia lettuce were screened for AHL production. Enterobacter asburiae, identified by matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS) was found to produce short chain AHLs. High resolution triple quadrupole liquid chromatography mass spectrometry (LC/MS) analysis of the E. asburiae spent supernatant confirmed the production of N-butanoyl homoserine lactone (C4-HSL) and N-hexanoyl homoserine lactone (C6-HSL). To the best of our knowledge, this is the first report of AHL production by E. asburiae.
Sensing of the application environment is the main purpose of a wireless sensor network. Most existing energy management strategies and compression techniques assume that the sensing operation consumes significantly less energy than radio transmission and reception. This assumption does not hold in a number of practical applications. Sensing energy consumption in these applications may be comparable to, or even greater than, that of the radio. In this work, we support this claim by a quantitative analysis of the main operational energy costs of popular sensors, radios and sensor motes. In light of the importance of sensing level energy costs, especially for power hungry sensors, we consider compressed sensing and distributed compressed sensing as potential approaches to provide energy efficient sensing in wireless sensor networks. Numerical experiments investigating the effectiveness of compressed sensing and distributed compressed sensing using real datasets show their potential for efficient utilization of sensing and overall energy costs in wireless sensor networks. It is shown that, for some applications, compressed sensing and distributed compressed sensing can provide greater energy efficiency than transform coding and model-based adaptive sensing in wireless sensor networks.
Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above.