Aromatic l-amino acid decarboxylase : histochemical localization in rat kidney and lack of effect of dietary potassium or sodium loading on enzyme distribution

Utilizing a mono-specific antiserum produced in rabbits to hog kidney aromatic L-amino acid decarboxylase (AADC), the enzyme was localized in rat kidney by immunoperoxidase staining. AADC was located predominantly in the proximal convoluted tubules; there was also weak staining in the distal convoluted tubules and collecting ducts. An increase in dietary potassium or sodium intake produced no change in density or distribution of AADC staining in kidney. An assay of AADC enzyme activity showed no difference in cortex or medulla with chronic potassium loading. A change in distribution or activity of renal AADC does not explain the postulated dopaminergic modulation of renal function that occurs with potassium or sodium loading.

Towards persistent localization and mapping with a continuous appearance-based topology

Appearance-based localization can provide loop closure detection at vast scales regardless of accumulated metric error. However, the computation time and memory requirements of current appearance-based methods scale not only with the size of the environment but also with the operation time of the platform. Additionally, repeated visits to locations will develop multiple competing representations, which will reduce recall performance over time. These properties impose severe restrictions on long-term autonomy for mobile robots, as loop closure performance will inevitably degrade with increased operation time. In this paper we present a graphical extension to CAT-SLAM, a particle filter-based algorithm for appearance-based localization and mapping, to provide constant computation and memory requirements over time and minimal degradation of recall performance during repeated visits to locations. We demonstrate loop closure detection in a large urban environment with capped computation time and memory requirements and performance exceeding previous appearance-based methods by a factor of 2. We discuss the limitations of the algorithm with respect to environment size, appearance change over time and applications in topological planning and navigation for long-term robot operation.

Capping computation time and storage requirements for appearance-based localization with CAT-SLAM

Appearance-based localization is increasingly used for loop closure detection in metric SLAM systems. Since it relies only upon the appearance-based similarity between images from two locations, it can perform loop closure regardless of accumulated metric error. However, the computation time and memory requirements of current appearance-based methods scale linearly not only with the size of the environment but also with the operation time of the platform. These properties impose severe restrictions on longterm autonomy for mobile robots, as loop closure performance will inevitably degrade with increased operation time. We present a set of improvements to the appearance-based SLAM algorithm CAT-SLAM to constrain computation scaling and memory usage with minimal degradation in performance over time. The appearance-based comparison stage is accelerated by exploiting properties of the particle observation update, and nodes in the continuous trajectory map are removed according to minimal information loss criteria. We demonstrate constant time and space loop closure detection in a large urban environment with recall performance exceeding FAB-MAP by a factor of 3 at 100% precision, and investigate the minimum computational and memory requirements for maintaining mapping performance.

Sensitivity of the NMR density matrix to pulse sequence parameters : a simplified analytic approach

We present a formalism for the analysis of sensitivity of nuclear magnetic resonance pulse sequences to variations of pulse sequence parameters, such as radiofrequency pulses, gradient pulses or evolution delays. The formalism enables the calculation of compact, analytic expressions for the derivatives of the density matrix and the observed signal with respect to the parameters varied. The analysis is based on two constructs computed in the course of modified density-matrix simulations: the error interrogation operators and error commutators. The approach presented is consequently named the Error Commutator Formalism (ECF). It is used to evaluate the sensitivity of the density matrix to parameter variation based on the simulations carried out for the ideal parameters, obviating the need for finite-difference calculations of signal errors. The ECF analysis therefore carries a computational cost comparable to a single density-matrix or product-operator simulation. Its application is illustrated using a number of examples from basic NMR spectroscopy. We show that the strength of the ECF is its ability to provide analytic insights into the propagation of errors through pulse sequences and the behaviour of signal errors under phase cycling. Furthermore, the approach is algorithmic and easily amenable to implementation in the form of a programming code. It is envisaged that it could be incorporated into standard NMR product-operator simulation packages.

Analysis of acoustic emission data for accurate damage assessment for structural health monitoring applications

Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.

Are plasmons responsible for the Raman signal enhancement observed with gold nanoparticle sensors?

The electromagnetic enhancement that occurs in surface enhanced Raman scattering (SERS) substrates containing gold nanoparticles (NPs) is believed to arise through the generation of localised surface plasmons. We present results that show no SERS signals are obtained when 25 nm diameter gold NPs layered quartz substrates exposed to 2-aminopyridine are illuminated with plasmon resonant 532 nm radiation, but SERS signals are observed when the same samples are illuminated with non-resonant 785 nm radiation.

Fast power line detection and localization using steerable filter for active UAV guidance

In this paper we present a fast power line detection and localisation algorithm as well as propose a high-level guidance architecture for active vision-based Unmanned Aerial Vehicle (UAV) guidance. The detection stage is based on steerable filters for edge ridge detection, followed by a line fitting algorithm to refine candidate power lines in images. The guidance architecture assumes an UAV with an onboard Gimbal camera. We first control the position of the Gimbal such that the power line is in the field of view of the camera. Then its pose is used to generate the appropriate control commands such that the aircraft moves and flies above the lines. We present initial experimental results for the detection stage which shows that the proposed algorithm outperforms two state-of-the-art line detection algorithms for power line detection from aerial imagery.

In vitro and in vivo studies on protease-activated receptor-2

Protease-activated receptor-2 (PAR2) is a G protein coupled receptor (GPCR) that is activated by proteolytic cleavage of its amino terminal domain by trypsin-like serine proteases. Cleavage of this receptor exposes a neoepitope, termed the tethered ligand (TL), which binds intramolecularly within the receptor to stimulate signal transduction via coupled G proteins. PAR2-mediated signal transduction is also experimentally stimulated by hexapeptides (agonist peptides; APs) that are homologous to the TL sequence. Due to the irreversible nature of PAR2 proteolysis, downstream signal transduction is tightly regulated. Following activation, PAR2 is rapidly uncoupled from downstream signalling by the post-translational modifications phosphorylation and ubiquination which facilitate interactions with â- arrestin. This scaffolding protein couples PAR2 to the internalisation machinery initiating its desensitisation and trafficking through the early and late endosomes followed by receptor degradation. PAR2 is widely expressed in mammalian tissues with key roles for this receptor in cardiovascular, respiratory, nervous and musculoskeletal systems. This receptor has also been linked to pathological states with aberrant expression and signalling noted in several cancers. In prostate cancer, PAR2 signalling induces migration and proliferation of tumour derived cell lines, while elevated receptor expression has been noted in malignant tissues. Importantly, a role for this receptor has also been suggested in prostate cancer bone metastasis as coexpression of PAR2 and a proteolytic activator has been demonstrated by immunohistochemical analysis. Based on these data, the primary focus of this project has been on two aspects of PAR2 biology. The first is characterisation of cellular mechanisms that regulate PAR2 signalling and trafficking. The second aspect is the role of this receptor in prostate cancer bone metastasis. In addition, to permit these studies, it was first necessary to evaluate the specificity of the commercially available anti-PAR2 antibodies SAM11, C17, N19 and H99. The evaluation of the four commercially available antibodies was assessed using four techniques: immunoprecipitation; Western blot analysis; immunofluorescence; and flow cytometry. These approaches demonstrated that three of the antibodies efficiently detect ectopically expressed PAR2 by each of these techniques. A significant finding from this study was that N19 was the only antibody able to specifically detect N-glycosylated endogenous PAR2 by Western blot analysis. This analysis was performed on lysates from prostate cancer derived cell lines and tissue derived from wildtype and PAR2 knockout mice. Importantly, further evaluation demonstrated that this antibody also efficiently detects endogenous PAR2 at the cell surface by flow cytometry. The anti-PAR2 antibody N19 was used to explore the in vitro role of palmitoylation, the post-translational addition of palmitate, in PAR2 signalling, trafficking, cell surface expression and desensitization. Significantly, use of the palmitoylation inhibitor 2-bromopalmitate indicated that palmitate addition is important in trafficking of PAR2 endogenously expressed by prostate cancer cell lines. This was supported by palmitate labelling experiments using two approaches which showed that PAR2 stably expressed by CHO cells is palmitoylated and that palmitoylation occurs on cysteine 361. Another key finding from this study is that palmitoylation is required for optimal PAR2 signalling as Ca2+ flux assays indicated that in response to trypsin agonism, palmitoylation deficient PAR2 is ~9 fold less potent than wildtype receptor with a reduction of about 33% in the maximum signal induced via the mutant receptor. Confocal microscopy, flow cytometry and cell surface biotinylation analyses demonstrated that palmitoylation is required for efficient cell surface expression of PAR2. Importantly, this study also identified that palmitoylation of this receptor within the Golgi apparatus is required for efficient agonist-induced rab11amediated trafficking of PAR2 to the cell surface. Interestingly, palmitoylation is also required for receptor desensitization, as agonist-induced â-arrestin recruitment and receptor degradation were markedly reduced in CHO-PAR2-C361A cells compared with CHO-PAR2 cells. Collectively, these data provide new insights on the life cycle of PAR2 and demonstrate that palmitoylation is critical for efficient signalling, trafficking, cell surface localization and degradation of this receptor. This project also evaluated PAR2 residues involved in ligand docking. Although the extracellular loop (ECL)2 of PAR2 is known to be required for agonist-induced signal transduction, the binding pocket for receptor agonists remains to be determined. In silico homology modelling, based on a crystal structure for the prototypical GPCR rhodopsin, and ligand docking were performed to identify PAR2 transmembrane (TM) amino acids potentially involved in agonist binding. These methods identified 12 candidate residues that were mutated to examine the binding site of the PAR2 TL, revealed by trypsin cleavage, as well as of the soluble ligands 2f-LIGRLO-NH2 and GB110, which are both structurally based on the AP SLIGRLNH2. Ligand binding was evaluated from the impact of the mutated residues on PAR2-mediated calcium mobilisation. An important finding from these experiments was that mutation of residues Y156 and Y326 significantly reduced 2f-LIGRLO-NH2 and GB110 agonist activity. L307 was also important for GB110 activity. Intriguingly, mutation of PAR2 residues did not alter trypsin-induced signalling to the same extent as for the soluble agonists. The reason for this difference remains to be further examined by in silico and in vitro experimentation and, potentially, crystal structure studies. However, these findings identified the importance of TM domains in PAR2 ligand docking and will enhance the design of both PAR2 agonists and potentially agents to inhibit signalling (antagonists). The potential importance of PAR2 in prostate cancer bone metastasis was examined using a mouse model. In patients, prostate cancer bone metastases cause bone growth by disrupting bone homeostasis. In an attempt to mimic prostate cancer growth in bone, PAR2 responsive 22Rv1 prostate cancer cells, which form mixed osteoblastic and osteolytic lesions, were injected into the proximal aspect of mouse tibiae. A role for PAR2 was assessed by treating these mice with the recently developed PAR2 antagonist GB88. As controls, animals bearing intra-tibial tumours were also treated with vehicle (olive oil) or the prostate cancer chemotherapeutic docetaxel. The effect of these treatments on bone was examined radiographically and by micro-CT. Consistent with previous studies, 22Rv1 tumours caused osteoblastic periosteal spicule formation and concurrent osteolytic bone loss. Significantly, blockade of PAR2 signalling reduced the osteoblastic and osteolytic phenotype of 22Rv1 tumours in bone. No bone defects were detected in mice treated with docetaxel. These qualitative data will be followed in the future by quantitative micro-CT analysis as well as histology and histomorphometry analysis of already collected tissues. Nonetheless, these preliminary experiments highlight a potential role for PAR2 in prostate cancer growth in bone. In summary, in vitro studies have defined mechanisms regulating PAR2 activation, downstream signalling and trafficking and in vivo studies point to a potential role for this receptor in prostate cancer bone metastasis. The outcomes of this project are that a greater understanding of the biology of PAR2 may lead to the development of strategies to modulate the function of this receptor in disease.

Human Kallikrein 4 signal peptide induces cytotoxic T cell responses in healthy donors and prostate cancer patients.

Immunotherapy is a promising new treatment for patients with advanced prostate and ovarian cancer, but its application is limited by the lack of suitable target antigens that are recognized by CD8+ cytotoxic T lymphocytes (CTL). Human kallikrein 4 (KLK4) is a member of the kallikrein family of serine proteases that is significantly overexpressed in malignant versus healthy prostate and ovarian tissue, making it an attractive target for immunotherapy. We identified a naturally processed, HLA-A*0201-restricted peptide epitope within the signal sequence region of KLK4 that induced CTL responses in vitro in most healthy donors and prostate cancer patients tested. These CTL lysed HLA-A*0201+ KLK4 + cell lines and KLK4 mRNA-transfected monocyte-derived dendritic cells. CTL specific for the HLA-A*0201-restricted KLK4 peptide were more readily expanded to a higher frequency in vitro compared to the known HLA-A*0201-restricted epitopes from prostate cancer antigens; prostate-specific antigen (PSA), prostate-specific membrane antigen (PSMA) and prostatic acid phosphatase (PAP). These data demonstrate that KLK4 is an immunogenic molecule capable of inducing CTL responses and identify it as an attractive target for prostate and ovarian cancer immunotherapy.

A practical signal processing approach for condition monitoring of low speed machinery using Peak-Hold-Down-Sample algorithm

A simple and effective down-sample algorithm, Peak-Hold-Down-Sample (PHDS) algorithm is developed in this paper to enable a rapid and efficient data transfer in remote condition monitoring applications. The algorithm is particularly useful for high frequency Condition Monitoring (CM) techniques, and for low speed machine applications since the combination of the high sampling frequency and low rotating speed will generally lead to large unwieldy data size. The effectiveness of the algorithm was evaluated and tested on four sets of data in the study. One set of the data was extracted from the condition monitoring signal of a practical industry application. Another set of data was acquired from a low speed machine test rig in the laboratory. The other two sets of data were computer simulated bearing defect signals having either a single or multiple bearing defects. The results disclose that the PHDS algorithm can substantially reduce the size of data while preserving the critical bearing defect information for all the data sets used in this work even when a large down-sample ratio was used (i.e., 500 times down-sampled). In contrast, the down-sample process using existing normal down-sample technique in signal processing eliminates the useful and critical information such as bearing defect frequencies in a signal when the same down-sample ratio was employed. Noise and artificial frequency components were also induced by the normal down-sample technique, thus limits its usefulness for machine condition monitoring applications.

Signal patterns of piston slap of a four-cylinder diesel engine

This paper presents an experimental study on the vibration signal patterns associated with a simulated piston slap test of a four-cylinder diesel engine. It is found that a simulated worn-off piston results in an increase in vibration RMS peak amplitudes associated with the major mechanical events of the corresponding cylinder (i.e., inlet and exhaust valve closing and combustion of Cylinder 1). This then led to an increase of overall vibration amplitude of the time domain statistical features such as RMS, Crest Factor, Skewness and Kurtosis in all loading conditions. The simulated worn-off piston not only increased the impact amplitude of piston slap during the engine combustion, it also produced a distinct impulse response during the air induction stroke of the cylinder attributing to an increase of lateral impact force as a result of piston reciprocating motion and the increased clearance between the worn-off piston and the cylinder. The unique signal patterns of piston slap disclosed in this paper can be utilized to assist in the development of condition monitoring tools for automated diagnosis of similar diesel engine faults in practical applications.