Fast model based feature matching technique applied to airport lighting

The use of image processing techniques to assess the performance of airport landing lighting using images of it collected from an aircraft-mounted camera is documented. In order to assess the performance of the lighting, it is necessary to uniquely identify each luminaire within an image and then track the luminaires through the entire sequence and store the relevant information for each luminaire, that is, the total number of pixels that each luminaire covers and the total grey level of these pixels. This pixel grey level can then be used for performance assessment. The authors propose a robust model-based (MB) featurematching technique by which the performance is assessed. The development of this matching technique is the key to the automated performance assessment of airport lighting. The MB matching technique utilises projective geometry in addition to accurate template of the 3D model of a landing-lighting system. The template is projected onto the image data and an optimum match found, using nonlinear least-squares optimisation. The MB matching software is compared with standard feature extraction and tracking techniques known within the community, these being the Kanade–Lucus–Tomasi (KLT) and scaleinvariant feature transform (SIFT) techniques. The new MB matching technique compares favourably with the SIFT and KLT feature-tracking alternatives. As such, it provides a solid foundation to achieve the central aim of this research which is to automatically assess the performance of airport lighting.

Modelling the MAPK signalling pathway using a two-stage identification algorithm

Signal transduction pathways describe the dynamics of cellular response to input signalling molecules at receptors on the cell membrane. The Mitogen-Activated Protein Kinase (MAPK) cascade is one of such pathways that are involved in many important cellular processes including cell growth and proliferation. This paper describes a black-box model of this pathway created using an advanced two-stage identification algorithm. Identification allows us to capture the unique features and dynamics of the pathway and also opens up the possibility of regulatory control design. In the approach described, an optimal model is obtained by performing model subset selection in two stages, where the terms are first determined by a forward selection method and then modified using a backward selection model refinement. The simulation results demonstrate that the model selected using the two-stage algorithm performs better than with the forward selection method alone.

Comparative analysis of synovial fluid and plasma proteomes in juvenile arthritis - Proteomic patterns of joint inflammation in early stage disease

Synovial fluid is a potential source of novel biomarkers for many arthritic disorders involving joint inflammation, including juvenile idiopathic arthritis. We first compared the distinctive protein ‘fingerprints’ of local inflammation in synovial fluid with systemic profiles within matched plasma samples. The synovial fluid proteome at the time of joint inflammation was then evaluated across clinical subgroups to identify early disease associated proteins. We measured the synovial fluid and plasma proteomes using the two-dimensional fluorescence difference gel electrophoresis approach. Image analysis software was used to highlight the expression levels of joint and subgroup associated proteins across the study cohort (n = 32). A defined subset of 30 proteins had statistically significant differences (p < 0.05) between sample types such that synovial fluid could be differentiated from plasma. Furthermore distinctive synovial proteome expression patterns segregate patient subgroups. Protein expression patterns localized in the chronically inflamed joint therefore have the potential to identify patients more likely to suffer disease which will spread from a single joint to multiple joints. The proteins identified could act as criteria to prevent disease extension by more aggressive therapeutic intervention directed at an earlier stage than is currently possible.

The Impact of Admissions for the Management of End-stage renal disease on hospital bed occupancy

BACKGROUND:

End-stage renal disease (ESRD) is increasingly prevalent but the inpatient costs associated with this condition are poorly defined due to limitations with data extraction and failure to differentiate between hospitalisation for renal and non-renal disease reasons. The impact of admissions primarily for the management of ESRD on hospital bed utilisation was assessed over a 5-year period in a large teaching hospital.

METHODS:

All admission episodes were reviewed and the ESRD group was identified by a primary International Classification of Diseases code for ESRD or a non-specific primary renal failure code with a secondary code for ESRD. The frequency and duration of hospitalisation and contribution to bed day occupancy of this group with ESRD was determined.

RESULTS:

There were 70,808 patients responsible for a total of 116,915 admissions and 919,212 bed days over the study period. Of these, 988 (1.4%) patients were admitted for the management of ESRD, accounting for 2,387 (2.0%) of admissions and utilisation of 23,011 (2.5%) bed days. After adjustment for age and gender, those admitted for ESRD management were significantly more likely to have a prolonged admission exceeding 30 days (odds ratio 1.46, 95% confidence interval 1.23-1.72, p < 0.001). When the admission was an emergency rather than an elective event, the patient was 4.6 times more likely to be hospitalised for over 30 days.

CONCLUSIONS:

Persons admitted for ESRD management are hospitalised more frequently and for longer than the overall inpatient population, occupying a substantial number of bed days.

Short interfering RNA-mediated gene silencing in Globodera pallida and Meloidogyne incognita infective stage juveniles

The analysis of gene function through RNA interference (RNAi)-based reverse genetics in plant parasitic nematodes (PPNs) remains inexplicably reliant on the use of long double-stranded RNA (dsRNA) silencing triggers; a practice inherently disadvantageous due to the introduction of superfluous dsRNA sequence. increasing chances of aberrant or off-target gene silencing through interactions between nascent short interfering RNAs (siRNAs) and non-cognate mRNA targets. Recently, we have shown that non-nematode, long dsRNAs have a propensity to elicit profound impacts on the phenotype and migrational abilities of both root knot and cyst nematodes. This study presents, to our knowledge for the first time, gene-specific knockdown of FMRFamide-like peptide (flp) transcripts, using discrete 21 bp siRNAs in potato cyst nematode Globodera pallida, and root knot nematode Meloidogyne incognita infective (J2) stage juveniles. Both knockdown at the transcript level through quantitative (q)PCR analysis and functional data derived from migration assay, indicate that siRNAs targeting certain areas of the FMRFamide-like peptide (FLP) transcripts are potent and specific in the silencing of gene function. In addition, we present a method of manipulating siRNA activity through the management of strand thermodynamics. Initial evaluation of strand thermodynamics as a determinant of RNA-induced Silencing Complex (RISC) strand selection (inferred from knockdown efficacy) in the siRNAs presented here suggested that the purported influence of 5' stand stability on guide incorporation may be somewhat promiscuous. However, we have found that on strategically incorporating base mismatches in the sense strand of a G. pallida-specific siRNA we could specifically increase or decrease the knockdown of its target (specific to the antisense strand), presumably through creating more favourable thermodynamic profiles for incorporation of either the sense (non-target-specific) or antisense (target-specific) strand into a cleavage-competent RISC. Whilst the efficacy of similar approaches to siRNA modification has been demonstrated in the context of Drosophila whole-cell lysate preparations and in mammalian cell cultures, it remained to be seen how these sense strand mismatches may impact on gene silencing in vivo, in relation to different targets and in different sequence contexts. This work presents the first application of such an approach in a whole organism; initial results show promise. (C) 2009 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.