Prevalence of methicillin resistance and virulence determinants of Staphylococcus aureus in diabetic foot ulcers

Background Diabetic foot ulceration (DFU) is a multifactorial process and is responsible for considerable morbidity and contributes to the increasing cost of health care worldwide. The diagnosis and identification of these ulcers remains a complex problem. Bacterial infection is promoted in the diabetic foot wound by decreased vascular supply and impaired host immune response. As conventional clinical microbiological methods are time-consuming and only identifies about 1% of the wound microbiota, detection of bacteria present in DFUs using molecular methods is highly advantageous and efficient. The aim of this study was to assess the virulence and methicillin resistance profiles of Staphylococcus aureus detected in DFUs using DNA-based methods. Methods A total of 223 swab samples were collected from 30 patients from March to October 2012. Bacterial DNA was extracted from the swab samples using standard procedures and was used to perform polymerase chain reaction (PCR) using specific oligonucleotide primers. The products were visualized using agarose gel electrophoresis. Results S. aureus was detected in 44.8% of samples. 25% of the S. aureus was methicillin-resistant S. aureus harboring the mecA gene. The alpha-toxin gene was present in 85% of the S. aureus positive samples. 61% of the S. aureus present in DFU samples harbored the exfoliatin factor A gene. Both the fibronectin factor A and fibronectin factor B gene were detected in 71% and 74% of the S. aureus positive samples. Conclusions DNA-based detection and characterization of bacteria in DFUs are rapid and efficient and can assist in accurate, targeted antibiotic therapy of DFU infections. The majority of S. aureus detected in this study were highly virulent and also resistant to methicillin. Further studies are required to understand the role of S. aureus in DFU trajectory.

Kallikrein 4 (hK4) and prostate-specific antigen (PSA) are associated with the loss of E-cadherin and an epithelial-mesenchymal transition (EMT)-like effect in prostate cancer cells

Prostate-specific antigen (PSA) and the related kallikrein family of serine proteases are current or emerging biomarkers for prostate cancer detection and progression. Kallikrein 4 (KLK4/hK4) is of particular interest, as KLK4 mRNA has been shown to be elevated in prostate cancer. In this study, we now show that the comparative expression of hK4 protein in prostate cancer tissues, compared with benign glands, is greater than that of PSA and kallikrein 2 (KLK2/hK2), suggesting that hK4 may play an important functional role in prostate cancer progression in addition to its biomarker potential. To examine the roles that hK4, as well as PSA and hK2, play in processes associated with progression, these kallikreins were separately transfected into the PC-3 prostate cancer cell line, and the consequence of their stable transfection was investigated. PC-3 cells expressing hK4 had a decreased growth rate, but no changes in cell proliferation were observed in the cells expressing PSA or hK2. hK4 and PSA, but not hK2, induced a 2.4-fold and 1.7-fold respective increase, in cellular migration, but not invasion, through Matrigel, a synthetic extracellular matrix. We hypothesised that this increase in motility displayed by the hK4 and PSA-expressing PC-3 cells may be related to the observed change in structure in these cells from a typical rounded epithelial-like cell to a spindle-shaped, more mesenchymal-like cell, with compromised adhesion to the culture surface. Thus, the expression of E-cadherin and vimentin, both associated with an epithelial-mesenchymal transition (EMT), was investigated. E-cadherin protein was lost and mRNA levels were significantly decreased in PC-3 cells expressing hK4 and PSA (10-fold and 7-fold respectively), suggesting transcriptional repression of E-cadherin, while the expression of vimentin was increased in these cells. The loss of E-cadherin and associated increase in vimentin are indicative of EMT and provides compelling evidence that hK4, in particular, and PSA have a functional role in the progression of prostate cancer through their promotion of tumour cell migration.

A mood stabiliser and antiepileptic for preventing head and neck cancers?

Cancer rates have been increasing over the past 26 years, but earlier detection and increasingly more treatment options also mean more and more people are surviving cancer.

Improving robot vision models for object detection through interaction

We propose a method for learning specific object representations that can be applied (and reused) in visual detection and identification tasks. A machine learning technique called Cartesian Genetic Programming (CGP) is used to create these models based on a series of images. Our research investigates how manipulation actions might allow for the development of better visual models and therefore better robot vision. This paper describes how visual object representations can be learned and improved by performing object manipulation actions, such as, poke, push and pick-up with a humanoid robot. The improvement can be measured and allows for the robot to select and perform the `right' action, i.e. the action with the best possible improvement of the detector.

Evaluation of the performance of a dengue outbreak detection tool for China

An outbreak detection and response system, using time series moving percentile method based on historical data, in China has been used for identifying dengue fever outbreaks since 2008. For dengue fever outbreaks reported from 2009 to 2012, this system achieved a sensitivity of 100%, a specificity of 99.8% and a median time to detection of 3 days, which indicated that the system was a useful decision tool for dengue fever control and risk-management programs in China.

Detection of rain in acoustic recordings of the environment using machine learning techniques

This thesis is concerned with the detection and prediction of rain in environmental recordings using different machine learning algorithms. The results obtained in this research will help ecologists to efficiently analyse environmental data and monitor biodiversity.

Large-scale interlaboratory study to develop, analytically validate and apply highly multiplexed, quantitative peptide assays to measure cancer-relevant proteins in plasma

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens-to-hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma, and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and 7 control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to sub-nanogram/mL sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and inter-laboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy isotope labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an inter-laboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality c`ontrol measures, enables sensitive, specific, reproducible and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

Parallel attentive visual tracking

The research reported here addresses the problem of detecting and tracking independently moving objects from a moving observer in real-time, using corners as object tokens. Corners are detected using the Harris corner detector, and local image-plane constraints are employed to solve the correspondence problem. The approach relaxes the restrictive static-world assumption conventionally made, and is therefore capable of tracking independently moving and deformable objects. Tracking is performed without the use of any 3-dimensional motion model. The technique is novel in that, unlike traditional feature-tracking algorithms where feature detection and tracking is carried out over the entire image-plane, here it is restricted to those areas most likely to contain-meaningful image structure. Two distinct types of instantiation regions are identified, these being the “focus-of-expansion” region and “border” regions of the image-plane. The size and location of these regions are defined from a combination of odometry information and a limited knowledge of the operating scenario. The algorithms developed have been tested on real image sequences taken from typical driving scenarios. Implementation of the algorithm using T800 Transputers has shown that near-linear speedups are achievable, and that real-time operation is possible (half-video rate has been achieved using 30 processing elements).

Application of higher-order spectra for automated grading of diabetic maculopathy

Diabetic macular edema (DME) is one of the most common causes of visual loss among diabetes mellitus patients. Early detection and successive treatment may improve the visual acuity. DME is mainly graded into non-clinically significant macular edema (NCSME) and clinically significant macular edema according to the location of hard exudates in the macula region. DME can be identified by manual examination of fundus images. It is laborious and resource intensive. Hence, in this work, automated grading of DME is proposed using higher-order spectra (HOS) of Radon transform projections of the fundus images. We have used third-order cumulants and bispectrum magnitude, in this work, as features, and compared their performance. They can capture subtle changes in the fundus image. Spectral regression discriminant analysis (SRDA) reduces feature dimension, and minimum redundancy maximum relevance method is used to rank the significant SRDA components. Ranked features are fed to various supervised classifiers, viz. Naive Bayes, AdaBoost and support vector machine, to discriminate No DME, NCSME and clinically significant macular edema classes. The performance of our system is evaluated using the publicly available MESSIDOR dataset (300 images) and also verified with a local dataset (300 images). Our results show that HOS cumulants and bispectrum magnitude obtained an average accuracy of 95.56 and 94.39 % for MESSIDOR dataset and 95.93 and 93.33 % for local dataset, respectively.

From ImageNet to mining: Adapting visual object detection with minimal supervision

This paper presents visual detection and classification of light vehicles and personnel on a mine site.We capitalise on the rapid advances of ConvNet based object recognition but highlight that a naive black box approach results in a significant number of false positives. In particular, the lack of domain specific training data and the unique landscape in a mine site causes a high rate of errors. We exploit the abundance of background-only images to train a k-means classifier to complement the ConvNet. Furthermore, localisation of objects of interest and a reduction in computation is enabled through region proposals. Our system is tested on over 10km of real mine site data and we were able to detect both light vehicles and personnel. We show that the introduction of our background model can reduce the false positive rate by an order of magnitude.

Defining the InstaBooth: Facilitating debate and content creation from situated users

Through ubiquitous computing and location-based social media, information is spreading outside the traditional domains of home and work into the urban environment. Digital technologies have changed the way people relate to the urban form supporting discussion on multiple levels, allowing more citizens to be heard in new ways (Fredericks et al. 2013; Houghton et al. 2014; Caldwell et al. 2013). Face-to-face and digitally mediated discussions, facilitated by tangible and hybrid interaction, such as multi-touch screens and media façades, are initiated through a telephone booth inspired portable structure: The InstaBooth. The InstaBooth prototype employs a multidisciplinary approach to engage local communities in a situated debate on the future of their urban environment. With it, we capture citizens’ past stories and opinions on the use and design of public places. The way public consultations are currently done often engages only a section of the population involved in a proposed development; the more vocal citizens are not necessarily the more representative of the communities (Jenkins 2006). Alternative ways to engage urban dwellers in the debate about the built environment are explored at the moment, including the use of social media or online tools (Foth 2009). This project fosters innovation by providing pathways for communities to participate in the decision making process that informs the urban form. The InstaBooth promotes dialogue and mediation between a bottom-up and a top-down approach to urban design, with the aim of promoting community connectedness with the urban environment. The InstaBooth provides an engagement and discussion platform that leverages a number of locally developed display and interaction technologies in order to facilitate a dialogue of ideas and commentary. The InstaBooth combines multiple interaction techniques into a hybrid (digital and analogue) media space. Through the InstaBooth, urban design and architectural proposals are displayed encouraging commentary from visitors. Inside the InstaBooth, visitors can activate a multi-touch screen in order to browse media, write a note, or draw a picture to provide feedback. The purpose of the InstaBooth is to engage with a broader section of society, including those who are often marginalised. The specific design of the internal and external interfaces, the mutual relationship between these interfaces with regards to information display and interaction, and the question how visitors can engage with the system, are part of the research agenda of the project.

IdeaWall: Bridging the digital and non-digital worlds to facilitate distant collaboration

Creative and ad-hoc work often involves non-digital artifacts, such as whiteboards and post-it notes. The preferred method of brainstorming and idea development, while facilitating work among collocated participants, makes it particularly tricky to involve remote participants, not even mentioning cases where live social involvement is required and the number and location of remote participants can be vast. Our work has originally focused on large distributed teams in business entities. Vast majority of teams in large organizations are distributed teams. Our team of corporate researchers decided to identify state of the art technologies that could facilitate the scenarios mentioned above. This paper is an account of a research project in the area of enterprise collaboration, with a strong focus on the aspects of human computer interaction in mixed mode environments, especially in areas of collaboration where computers still play a secondary role. It is describing a currently running corporate research project. In this paper we signal the potential use of the technology in situation, where community involvement is either required or desirable. The goal of the paper is to initiate a discussion on the use of technologies, initially designed as supporting enterprise collaboration, in situation requiring community engagement. In other words, it is a contribution of technically focused research exploring the uses of the technology in areas such as social engagement and community involvement. © 2012 IEEE.

A semiautomatic method to identify vertebral end plate lesions (Schmorl's nodes)

Background Context There are differences in definitions of end plate lesions (EPLs), often referred to as Schmorl’s nodes, that may, to some extent, account for the large range of reported prevalence (3.8 to 76%). Purpose To develop a technique to measure the size, prevalence and location of EPLs in a consistent manner. Study Design/Setting This study proposed a method using a detection algorithm which was applied to five adolescent females (average age 15.1 years, range 13.0 to 19.2 years) with idiopathic scoliosis (average major Cobb angle 60°, range 55 to 67°). Methods Existing low-dose, computed tomography scans were segmented semi-automatically to extract 3D morphology of each vertebral endplate. Any remaining attachments to the posterior elements of adjacent vertebrae or endplates were then manually sectioned. An automatic algorithm was used to determine the presence and position of EPLs. Results EPLs were identified in 15 of the 170 (8.8%) endplates analysed with an average depth of 3.1mm. 11/15 of the EPLs were seen in the lumbar spine. The algorithm was found to be most sensitive to changes in the minimum EPL gradient at the edges of the EPL. Conclusions This study describes an imaging analysis technique for consistent measurement of the prevalence, location and size of EPLs. The technique can be used to analyse large populations without observer errors in EPL definitions.

Identifying vertebral end plate lesions (schmorl's nodes) using a semi-automatic method

INTRODUCTION There is a large range in the reported prevalence of end plate lesions (EPLs), sometimes referred to as Schmorl's nodes in the general population (3.8-76%). One possible reason for this large range is the differences in definitions used by authors. Previous research has suggested that EPLs may potentially be a primary disturbance of growth plates that leads to the onset of scoliosis. The aim of this study was to develop a technique to measure the size, prevalence and location of EPLs on Computed Tomography (CT) images of scoliosis patients in a consistent manner. METHODS A detection algorithm was developed and applied to measure EPLs for five adolescent females with idiopathic scoliosis (average age 15.1 years, average major Cobb 60°). In this algorithm, the EPL definition was based on the lesion depth, the distance from the edge of the vertebral body and the gradient of the lesion edge. Existing low-dose, CT scans of the patients' spines were segmented semi-automatically to extract 3D vertebral endplate morphology. Manual sectioning of any attachments between posterior elements of adjacent vertebrae and, if necessary, endplates was carried out before the automatic algorithm was used to determine the presence and position of EPLs. RESULTS EPLs were identified in 15 of the 170 (8.8%) endplates analysed with an average depth of 3.1mm. 73% of the EPLs were seen in the lumbar spines (11/15). A sensitivity study demonstrated that the algorithm was most sensitive to changes in the minimum gradient required at the lesion edge. CONCLUSION An imaging analysis technique for consistent measurement of the prevalence, location and size of EPLs on CT images has been developed. Although the technique was tested on scoliosis patients, it can be used to analyse other populations without observer errors in EPL definitions.