Identification of essential operons with a rhamnose-inducible promoter in Burkholderia cenocepacia

Scanning of bacterial genomes to identify essential genes is of biological interest, for understanding the basic functions required for life, and of practical interest, for the identification of novel targets for new antimicrobial therapies. In particular, the lack of efficacious antimicrobial treatments for infections caused by the Burkholderia cepacia complex is causing high morbidity and mortality of cystic fibrosis patients and of patients with nosocomial infections. Here, we present a method based on delivery of the tightly regulated rhamnose-inducible promoter P(rhaB) for identifying essential genes and operons in Burkholderia cenocepacia. We demonstrate that different levels of gene expression can be achieved by using two vectors that deliver P(rhaB) at two different distances from the site of insertion. One of these vectors places P(rhaB) at the site of transposon insertion, while the other incorporates the enhanced green fluorescent protein gene (e-gfp) downstream from P(rhaB). This system allows us to identify essential genes and operons in B. cenocepacia and provides a new tool for systematically identifying and functionally characterizing essential genes at the genomic level.

Computational identification of self-inhibitory peptides from envelope proteins

Fusion process is known to be the initial step of viral infection and hence targeting the entry process is a promising strategy to design antiviral therapy. The self-inhibitory peptides derived from the enveloped (E) proteins function to inhibit the proteinprotein interactions in the membrane fusion step mediated by the viral E protein. Thus, they have the potential to be developed into effective antiviral therapy. Herein, we have developed a Monte Carlo-based computational method with the aim to identify and optimize potential peptide hits from the E proteins. The stability of the peptides, which indicates their potential to bind in situ to the E proteins, was evaluated by two different scoring functions, dipolar distance-scaled, finite, ideal-gas reference state and residue-specific all-atom probability discriminatory function. The method was applied to a-helical Class I HIV-1 gp41, beta-sheet Class II Dengue virus (DENV) type 2 E proteins, as well as Class III Herpes Simplex virus-1 (HSV-1) glycoprotein, a E protein with a mixture of a-helix and beta-sheet structural fold. The peptide hits identified are in line with the druggable regions where the self-inhibitory peptide inhibitors for the three classes of viral fusion proteins were derived. Several novel peptides were identified from either the hydrophobic regions or the functionally important regions on Class II DENV-2 E protein and Class III HSV-1 gB. They have potential to disrupt the proteinprotein interaction in the fusion process and may serve as starting points for the development of novel inhibitors for viral E proteins. 

A PLATE ASSAY FOR THE DETECTION OF ORGANOPHOSPHONATE MINERALIZATION BY ENVIRONMENTAL BACTERIA, AND ITS MODIFICATION AS AN ACTIVITY STAIN FOR IDENTIFICATION OF THE CARBON-PHOSPHORUS BOND-CLEAVAGE ENZYME PHOSPHONOACETATE HYDROLASE

A replica plate screening technique, based on the acid molybdate assay for detection of phosphate has been developed to permit the detection of microorganisms capable of mineralizing organophosphonates. The method was further adapted as the basis of an activity stain for the detection of the carbon - phosphorus bond cleavage enzyme phosphonoacetate hydrolase in PAGE gels.

Modelling 3D camera movement for vibration characterisation and multiple object identification with application to lighting assessment

Utilising cameras as a means to survey the surrounding environment is becoming increasingly popular in a number of different research areas and applications. Central to using camera sensors as input to a vision system, is the need to be able to manipulate and process the information captured in these images. One such application, is the use of cameras to monitor the quality of airport landing lighting at aerodromes where a camera is placed inside an aircraft and used to record images of the lighting pattern during the landing phase of a flight. The images are processed to determine a performance metric. This requires the development of custom software for the localisation and identification of luminaires within the image data. However, because of the necessity to keep airport operations functioning as efficiently as possible, it is difficult to collect enough image data to develop, test and validate any developed software. In this paper, we present a technique to model a virtual landing lighting pattern. A mathematical model is postulated which represents the glide path of the aircraft including random deviations from the expected path. A morphological method has been developed to localise and track the luminaires under different operating conditions. © 2011 IEEE.

Comparison of API20C with molecular identification of Candida spp isolated from bloodstream infections

A study was carried out to compare the API20C technology with polymerase chain reaction amplification and direct sequencing of the short internal transcribed spacer region 2 (ITS2) for the identification of 58 isolates of invasive candida species obtained from patients with bloodstream infections over the seven year period 1994 to 2000. Overall, there was only one disagreement between the phenotypic and genotypic identification, where the API scheme identified the isolate as C albicans but the molecular method identified it as C dubliniensis. This study demonstrated that the API20C method is useful in the identification of Candida spp isolated from blood culture and that molecular methods do not enhance identifications made using the API20C scheme. However, for correct reporting of C dubliniensis, an emerging bloodborne pathogen, it is recommended that all isolates identified as C albicans by the API20C scheme are further examined phenotypically and/or genotypically.

Community identity as resource and context: A mixed method investigation of coping and collective action in a disadvantaged community

Community identities enhance well-being through the provision of social support and feelings of collective efficacy as well as by acting as a basis for collective action and social change. However, the precise mechanisms through which community identity acts to enhance well-being are complicated by stigmatisation which potentially undermines solidarity and collective action. The present research examines a real-world stigmatised community group in order to investigate: (1) the community identity factors that act to enhance well-being, and (2) the consequences of community identity for community action. Study 1 consisted of a household survey conducted in disadvantaged areas of Limerick city in Ireland. Participants (n=322) completed measures of community identification, social support, collective efficacy, community action, and psychological well-being. Mediation analysis indicated that perceptions of collective efficacy mediated the relationship between identification and well-being. However, levels of self-reported community action were low and unrelated to community identification. In Study 2, twelve follow–up multiple-participant interviews with residents and community group workers were thematically analysed, revealing high levels of stigmatisation and opposition to identity-related collective action. These findings suggest the potential for stigma to reduce collective action through undermining solidarity and social support.

Robust Multimodal Person Identification With Limited Training Data

This paper presents a novel method of audio-visual feature-level fusion for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowledge about the corruption. Furthermore, we assume there are limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new multimodal feature representation and a modified cosine similarity are introduced to combine and compare bimodal features with limited training data, as well as vastly differing data rates and feature sizes. Optimal feature selection and multicondition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Experiments have been carried out on a bimodal dataset created from the SPIDRE speaker recognition database and AR face recognition database with variable noise corruption of speech and occlusion in the face images. The system's speaker identification performance on the SPIDRE database, and facial identification performance on the AR database, is comparable with the literature. Combining both modalities using the new method of multimodal fusion leads to significantly improved accuracy over the unimodal systems, even when both modalities have been corrupted. The new method also shows improved identification accuracy compared with the bimodal systems based on multicondition model training or missing-feature decoding alone.

Multiplex Solid-Phase PCR for Rapid Detection and Identification of Salmonella spp. at Sub-species

This study presents a solid-phase PCR (SP-PCR) for rapid detection, identification, and sub-typing of various Salmonella species, the major food-borne cause of salmonellosis. The target DNA is firstly amplified with PCR primers (one primer is labeled with fluorophores) in the liquid phase. Simultaneously on the solid phase, the amplified PCR amplicons interact with the nested DNA probes immobilized on the solid substrate as an array. If the immobilized probes match the sequence of the DNA templates they are extended by the polymerase and serve as template for the second strand elongation primed by the liquid phase primer thus generating new templates for the SP-PCR. After the reaction, PCR products labeled with fluorophores remain attached to the substrate and can be visualized directly by fluorescence readout devices. Using this method, S. enteritidis, S. typhimurium and S. dublin can be detected at the same time. The method offers several advantages over conventional multiplex PCR: less competition between different primer pairs thus increasing multiplexing capability, only single wavelength optical readout needed for the multiplexing detection, and less time-consuming owing to reduction of the post-PCR gel electrophoresis. The method will be useful for development of point-of-care devices for rapid detection and identification of Salmonella spp. A solid-phase PCR for rapid detection and identification of S. enteritidis, S. typhimurium and S. dublin is developed. The method offers advantages such as better multiplexing capability, only single wavelength optical readout needed, and less time-consuming.

A PCR-based method to distinguish fungi of the rice sheath-blight complex, Rhizoctonia solani, R. oryzae and R. oryzae-sativae

Identification of Rhizoctonia solani, R. oryzae and R. oryzae-sativae, components of the rice sheath disease complex, is extremely difficult and often inaccurate and as a result may hinder the success of extensive breeding programmes throughout Asia. In this study, primers designed from unique regions within the rDNA internal transcribed spacers have been used to develop a rapid PCR-based diagnostic test to provide an accurate identification of the species on rice. Tests on the specificity of the primers concerned showed that they provide the means for accurate identification of the Rhizoctonia species responsible for sheath diseases in rice.

A PCR-based method to characterise and identify benzimidazole resistance in Helminthosporium solani

Control of Helminthosporium solani, the cause of silver scurf in potato tubers, has been impaired by selection of benzimidazole-resistant strains as a result of repeated use of the fungicide thiabendazole. Identification of thiabendazole-resistant strains of H. solani by conventional techniques takes several weeks. Primers designed from conserved regions of the fungal beta-tubulin gene were used to PCR amplify and sequence a portion of the gene. A point mutation was detected at codon 198 in thiabendazole-resistant isolates causing a change in the amino acid sequence from glutamic acid to alanine or glutamine. Species-specific PCR primers designed to amplify this region were used in conjunction with a restriction endonuclease to cause cleavage in sensitive isolates only and thus provide a rapid diagnostic test to differentiate field isolates.

Meeting the Requirements of the CDM Regulations: Identification of Critical Success Factors of Small to Medium Sized Contractor’ Compliance in the UK Construction Industry

The Construction Design and Management (CDM) Regulations (2007) is one of the most important set of health and safety regulations in the construction industry today. The aim of this research is to examine critical success factors for CDM compliance in small to medium size contractors in the UK construction industry. The objectives of the research include the identification of critical barriers in doing so along with the identification of success factors where CDM is incorporated. A mixed method approach is adopted in the identification and categorisation of the various factors encompassing a literature review, interviews and questionnaire survey. The key finding which emerge is the lack of knowledge and understanding with regards the CDM regulations with the recommendation to encourage small and medium contractor compliance through illustrating the benefits attainable. The practicality of the research is evident based on the significant uptake in the CDM by larger contractors, yet the research indicates that further insight and guidance is required to educate and inform those working within small to medium sized contractors in the UK. Where such acknowledgement and compliance is adopted, it is envisaged that this sector will benefit from reduced incidents and accidents, increased productivity while ultimately leading to a safer and more productive industry as a whole.

Modal Extraction for Wind Turbines using Moving Window Subspace Identification

This paper proposes a method for wind turbine mode identification using the multivariable output error statespace (MOESP) identification algorithm. The paper incorporates a fast moving window QR decomposition and propagator method from array signal processing, yielding a moving window subspace identification algorithm. The algorithm assumes that the system order is known as a priori and remains constant during identification. For the purpose of extracting modal information for turbines modelled as a linear parameter varying (LPV) system, the algorithm is applicable since a nonlinear system can be approximated as a piecewise time invariant system in consecutive data windows. The algorithm is exemplified using numerical simulations which show that the moving window algorithm can track the modal information. The paper also demonstrates that the low computational burden of the algorithm, compared to conventional batch subspace identification, has significant implications for online implementation.

Identification and Validation of an Anthracycline/Cyclophosphamide–Based Chemotherapy Response Assay in Breast Cancer

Background: There is no method routinely used to predict response to anthracycline and cyclophosphamide–based chemotherapy in the clinic; therefore patients often receive treatment for breast cancer with no benefit. Loss of the Fanconi anemia/BRCA (FA/BRCA) DNA damage response (DDR) pathway occurs in approximately 25% of breast cancer patients through several mechanisms and results in sensitization to DNA-damaging agents. The aim of this study was to develop an assay to detect DDR-deficient tumors associated with loss of the FA/BRCA pathway, for the purpose of treatment selection.

Methods: DNA microarray data from 21 FA patients and 11 control subjects were analyzed to identify genetic processes associated with a deficiency in DDR. Unsupervised hierarchical clustering was then performed using 60 BRCA1/2 mutant and 47 sporadic tumor samples, and a molecular subgroup was identified that was defined by the molecular processes represented within FA patients. A 44-gene microarray-based assay (the DDR deficiency assay) was developed to prospectively identify this subgroup from formalin-fixed, paraffin-embedded samples. All statistical tests were two-sided.

Results: In a publicly available independent cohort of 203 patients, the assay predicted complete pathologic response vs residual disease after neoadjuvant DNA-damaging chemotherapy (5-fluorouracil, anthracycline, and cyclophosphamide) with an odds ratio of 3.96 (95% confidence interval [Cl] =1.67 to 9.41; P = .002). In a new independent cohort of 191 breast cancer patients treated with adjuvant 5-fluorouracil, epirubicin, and cyclophosphamide, a positive assay result predicted 5-year relapse-free survival with a hazard ratio of 0.37 (95% Cl = 0.15 to 0.88; P = .03) compared with the assay negative population.

Conclusions: A formalin-fixed, paraffin-embedded tissue-based assay has been developed and independently validated as a predictor of response and prognosis after anthracycline/cyclophosphamide–based chemotherapy in the neoadjuvant and adjuvant settings. These findings warrant further validation in a prospective clinical study.

Identification of damping in a bridge using a moving instrumented vehicle

In recent years, there has been a significant increase in the number of bridges which are being instrumented and monitored on an ongoing basis. This is in part due to the introduction of bridge management systems designed to provide a high level of protection to the public and early warning if the bridge becomes unsafe. This paper investigates a novel alternative; a low-cost method consisting of the use of a vehicle fitted with accelerometers on its axles to monitor the dynamic behaviour of bridges. A simplified half-car vehicle-bridge interaction model is used in theoretical simulations to test the effectiveness of the approach in identifying the damping ratio of the bridge. The method is tested for a range of bridge spans and vehicle velocities using theoretical simulations and the influences of road roughness, initial vibratory condition of the vehicle, signal noise, modelling errors and frequency matching on the accuracy of the results are investigated.

A drive-by inspection system via vehicle moving force identification

This paper presents a novel method to carry out monitoring of transport infrastructure such as pavements and bridges through the analysis of vehicle accelerations. An algorithm is developed for the identification of dynamic vehicle-bridge interaction forces using the vehicle response. Moving force identification theory is applied to a vehicle model in order to identify these dynamic forces between the vehicle and the road and/or bridge. A coupled half-car vehicle-bridge interaction model is used in theoretical simulations to test the effectiveness of the approach in identifying the forces. The potential of the method to identify the global bending stiffness of the bridge and to predict the pavement roughness is presented. The method is tested for a range of bridge spans using theoretical simulations and the influences of road roughness and signal noise on the accuracy of the results are investigated.