Adjustment of apnea-hypopnea index with severity of obstruction events enhances detection of sleep apnea patients with the highest risk of severe health consequences

Introduction Presently, the severity of obstructive sleep apnea (OSA) is estimated based on the apnea-hypopnea index (AHI). Unfortunately, AHI does not provide information on the severity of individual obstruction events. Previously, the severity of individual obstruction events has been suggested to be related to the outcome of the disease. In this study, we incorporate this information into AHI and test whether this novel approach would aid in discriminating patients with the highest risk. We hypothesize that the introduced adjusted AHI parameter provides a valuable supplement to AHI in the diagnosis of the severity of OSA. Methods This hypothesis was tested by means of retrospective follow-up (mean ± sd follow-up time 198.2 ± 24.7 months) of 1,068 men originally referred to night polygraphy due to suspected OSA. After exclusion of the 264 patients using CPAP, the remaining 804 patients were divided into normal (AHI < 5) and OSA (AHI ≥ 5) categories based on conventional AHI and adjusted AHI. For a more detailed analysis, the patients were divided into normal, mild, moderate, and severe OSA categories based on conventional AHI and adjusted AHI. Subsequently, the mortality and cardiovascular morbidity in these groups were determined. Results Use of the severity of individual obstruction events for adjustment of AHI led to a significant rearrangement of patients between severity categories. Due to this rearrangement, the number of deceased patients diagnosed to have OSA was increased when adjusted AHI was used as the diagnostic index. Importantly, risk ratios of all-cause mortality and cardiovascular morbidity were higher in moderate and severe OSA groups formed based on the adjusted AHI parameter than in those formed based on conventional AHI. Conclusions The adjusted AHI parameter was found to give valuable supplementary information to AHI and to potentially improve the recognition of OSA patients with the highest risk of mortality or cardiovascular morbidity.

The new Vancouver Chest Pain Rule using troponin as the only biomarker: An external validation study

Objectives To externally evaluate the accuracy of the new Vancouver Chest Pain Rule and to assess the diagnostic accuracy using either sensitive or highly sensitive troponin assays. Methods Prospectively collected data from 2 emergency departments (EDs) in Australia and New Zealand were analysed. Based on the new Vancouver Chest Pain Rule, low-risk patients were identified using electrocardiogram results, cardiac history, nitrate use, age, pain characteristics and troponin results at 2 hours after presentation. The primary outcome was 30-day diagnosis of acute coronary syndrome (ACS), including acute myocardial infarction, and unstable angina. Sensitivity, specificity, positive predictive values and negative predictive values were calculated to assess the accuracy of the new Vancouver Chest Pain Rule using either sensitive or highly sensitive troponin assay results. Results Of the 1635 patients, 20.4% had an ACS diagnosis at 30 days. Using the highly sensitive troponin assay, 212 (13.0%) patients were eligible for early discharge with 3 patients (1.4%) diagnosed with ACS. Sensitivity was 99.1% (95% CI 97.4-99.7), specificity was 16.1 (95% CI 14.2-18.2), positive predictive values was 23.3 (95% CI 21.1-25.5) and negative predictive values was 98.6 (95% CI 95.9-99.5). The diagnostic accuracy of the rule was similar using the sensitive troponin assay. Conclusions The new Vancouver Chest Pain Rule should be used for the identification of low risk patients presenting to EDs with symptoms of possible ACS, and will reduce the proportion of patients requiring lengthy assessment; however we recommend further outpatient investigation for coronary artery disease in patients identified as low risk.

Dynamic, invivo, real-time detection of retinal oxidative status in a model of elevated intraocular pressure using a novel, reversibly responsive, profluorescent nitroxide probe

Changes to the redox status of biological systems have been implicated in the pathogenesis of a wide variety of disorders including cancer, Ischemia-reperfusion (I/R) injury and neurodegeneration. In times of metabolic stress e.g. ischaemia/reperfusion, reactive oxygen species (ROS) production overwhelms the intrinsic antioxidant capacity of the cell, damaging vital cellular components. The ability to quantify ROS changes in vivo, is therefore essential to understanding their biological role. Here we evaluate the suitability of a novel reversible profluorescent probe containing a redox-sensitive nitroxide moiety (methyl ester tetraethylrhodamine nitroxide, ME-TRN), as an in vivo, real-time reporter of retinal oxidative status. The reversible nature of the probe's response offers the unique advantage of being able to monitor redox changes in both oxidizing and reducing directions in real time. After intravitreal administration of the ME-TRN probe, we induced ROS production in rat retina using an established model of complete, acute retinal ischaemia followed by reperfusion. After restoration of blood flow, retinas were imaged using a Micron III rodent fundus fluorescence imaging system, to quantify the redox-response of the probe. Fluorescent intensity declined during the first 60 min of reperfusion. The ROS-induced change in probe fluorescence was ameliorated with the retinal antioxidant, lutein. Fluorescence intensity in non-Ischemia eyes did not change significantly. This new probe and imaging technology provide a reversible and real-time response to oxidative changes and may allow the in vivo testing of antioxidant therapies of potential benefit to a range of diseases linked to oxidative stress

Electrochemical detection of benzo(a)pyrene and related DNA damage using DNA/hemin/nafion-graphene biosensor

A novel electrochemical biosensor, DNA/hemin/nafion–graphene/GCE, was constructed for the analysis of the benzo(a)pyrene PAH, which can produce DNA damage induced by a benzo(a)pyrene (BaP) enzyme-catalytic product. This biosensor was assembled layer-by-layer, and was characterized with the use of cyclic voltammetry, electrochemical impedance spectroscopy (EIS) and atomic force microscopy. Ultimately, it was demonstrated that the hemin/nafion–graphene/GCE was a viable platform for the immobilization of DNA. This DNA biosensor was treated separately in benzo(a)pyrene, hydrogen peroxide (H2O2) and in their mixture, respectively, and differential pulse voltammetry (DPV) analysis showed that an oxidation peak was apparent after the electrode was immersed in H2O2. Such experiments indicated that in the presence of H2O2, hemin could mimic cytochrome P450 to metabolize benzo(a)pyrene, and a voltammogram of its metabolite was recorded. The DNA damage induced by this metabolite was also detected by electrochemical impedance and ultraviolet spectroscopy. Finally, a novel, indirect DPV analytical method for BaP in aqueous solution was developed based on the linear metabolite versus BaP concentration plot; this method provided a new, indirect, quantitative estimate of DNA damage.

Hot spot detection and spatio-temporal dynamics of dengue in Queensland, Australia

Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992-1993. This study explored spatio-temporal distribution and clustering of locally-acquired dengue cases in Queensland State, Australia and identified target areas for effective interventions. A computerised locally-acquired dengue case dataset was collected from Queensland Health for Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Dengue hot spots were detected using SatScan method. Descriptive spatial analysis showed that a total of 2,398 locally-acquired dengue cases were recorded in central and northern regions of tropical Queensland. A seasonal pattern was observed with most of the cases occurring in autumn. Spatial and temporal variation of dengue cases was observed in the geographic areas affected by dengue over time. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in tropical Queensland, Australia. There is a clear evidence for the existence of statistically significant clusters of dengue and these clusters varied over time. These findings enabled us to detect and target dengue clusters suggesting that the use of geospatial information can assist the health authority in planning dengue control activities and it would allow for better design and implementation of dengue management programs.

A data mining approach for fault diagnosis: An application of anomaly detection algorithm

Rolling-element bearing failures are the most frequent problems in rotating machinery, which can be catastrophic and cause major downtime. Hence, providing advance failure warning and precise fault detection in such components are pivotal and cost-effective. The vast majority of past research has focused on signal processing and spectral analysis for fault diagnostics in rotating components. In this study, a data mining approach using a machine learning technique called anomaly detection (AD) is presented. This method employs classification techniques to discriminate between defect examples. Two features, kurtosis and Non-Gaussianity Score (NGS), are extracted to develop anomaly detection algorithms. The performance of the developed algorithms was examined through real data from a test to failure bearing. Finally, the application of anomaly detection is compared with one of the popular methods called Support Vector Machine (SVM) to investigate the sensitivity and accuracy of this approach and its ability to detect the anomalies in early stages.

Multimodal polymer nanoparticles with combined 19F magnetic resonance and optical detection for tunable, targeted, multimodal imagingin vivo

Understanding the complex nature of diseased tissue in vivo requires development of more advanced nanomedicines, where synthesis of multifunctional polymers combines imaging multimodality with a biocompatible, tunable, and functional nanomaterial carrier. Here we describe the development of polymeric nanoparticles for multimodal imaging of disease states in vivo. The nanoparticle design utilizes the abundant functionality and tunable physicochemical properties of synthetically robust polymeric systems to facilitate targeted imaging of tumors in mice. For the first time, high-resolution 19F/1H magnetic resonance imaging is combined with sensitive and versatile fluorescence imaging in a polymeric material for in vivo detection of tumors. We highlight how control over the chemistry during synthesis allows manipulation of nanoparticle size and function and can lead to very high targeting efficiency to B16 melanoma cells, both in vitro and in vivo. Importantly, the combination of imaging modalities within a polymeric nanoparticle provides information on the tumor mass across various size scales in vivo, from millimeters down to tens of micrometers.

Raman spectroscopy techniques for detection of energetic materials at high and low concentration

This thesis presents the development of a rapid, sensitive and reproducible spectroscopic method for the detection of TNT in forensic and environmental applications. Simple nano sensors prepared by cost effective methods were utilized as sensitive platforms for the detection of TNT by surface enhanced Raman spectroscopy. The optimization of the substrate and the careful selection of a suitable recognition molecule contributed to the significant improvements of sensitive and selective targeting over current detection methods. The work presented in this thesis paves the way for effective detection and monitoring of explosives residues in law enforcement and environmental health applications.

External auditors’ perceptions of cloud computing adoption in Australia

Adopting a multi-theoretical approach, I examine external auditors’ perceptions of the reasons why organizations do or do not adopt cloud computing. I interview forensic accountants and IT experts about the adoption, acceptance, institutional motives, and risks of cloud computing. Although the medium to large accounting firms where the external auditors worked almost exclusively used private clouds, both private and public cloud services were gaining a foothold among many of their clients. Despite the advantages of cloud computing, data confidentiality and the involvement of foreign jurisdictions remain a concern, particularly if the data are moved outside Australia. Additionally, some organizations seem to understand neither the technology itself nor their own requirements, which may lead to poorly negotiated contracts and service agreements. To minimize the risks associated with cloud computing, many organizations turn to hybrid solutions or private clouds that include national or dedicated data centers. To the best of my knowledge, this is the first empirical study that reports on cloud computing adoption from the perspectives of external auditors.

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Safety culture and speeding in the Australian heavy vehicle industry

Inappropriate speed and speeding are among the highest causes of crashes in the heavy vehicle industry. Truck drivers are subjected to a broad range of influences on their behaviour including industrial pressures, company monitoring and police enforcement. Further, drivers have a high level of autonomy over their own behaviour. As such it is important to understand how these external influences interact with commonly shared beliefs, attitudes and values of heavy vehicle drivers to influence their behaviour. The present study uses a re-conceptualisation of safety culture to explore the behaviours of driving at an inappropriate speed and speeding in the heavy vehicle industry. A series of case studies, consisting of interviews and ride-along observations, were conducted with three transport organisations to explore the effect of culture on safety in the heavy vehicle industry. Results relevant to inappropriate speed are reported and discussed. It was found that organisational management through monitoring, enforcement and payment, police enforcement, customer standards and vehicle design factors could all reduce the likelihood of driving at inappropriate speeds under some circumstances. However, due to weaknesses in the ability to accurately monitor appropriate speed, this behaviour was primarily influenced by cultural beliefs, attitudes and values. Truck drivers had a tendency to view speeding as relatively safe, had a desire to speed to save time and increase personal income, and thus often attempted to speed without detection. When drivers saw speeding as dangerous, however, they were more likely to drive safely. Implications for intervention are discussed.

Circulating tumor cell detection in high-risk non-metastatic prostate cancer

Purpose The detection of circulating tumor cells (CTCs) provides important prognostic information in men with metastatic prostate cancer. We aim to determine the rate of detection of CTCs in patients with high-risk non-metastatic prostate cancer using the CellSearch® method. Method Samples of peripheral blood (7.5 mL) were drawn from 36 men with newly diagnosed high-risk non-metastatic prostate cancer, prior to any initiation of therapy and analyzed for CTCs using the CellSearch® method. Results The median age was 70 years, median PSA was 14.1, and the median Gleason score was 9. The median 5-year risk of progression of disease using a validated nomogram was 39 %. Five out of 36 patients (14 %, 95 % CI 5–30 %) had CTCs detected in their circulation. Four patients had only 1 CTC per 7.5 mL of blood detected. One patient had 3 CTCs per 7.5 mL of blood detected, which included a circulating tumor microemboli. Both on univariate analysis and multivariate analysis, there were no correlations found between CTC positivity and the classic prognostic factors including PSA, Gleason score, T-stage and age. Conclusion This study demonstrates that patients with high-risk, non-metastatic prostate cancer present infrequently with small number of CTCs in peripheral blood. This finding is consistent with the limited literature available in this setting. Other CTC isolation and detection technologies with improved sensitivity and specificity may enable detection of CTCs with mesenchymal phenotypes, although none as yet have been validated for clinical use. Newer assays are emerging for detection of new putative biomarkers for prostate cancer. Correlation of disease control outcomes with CTC detection will be important.

Detection of anuran calling activity in long field recordings for bio-acoustic monitoring

This paper presents a system to analyze long field recordings with low signal-to-noise ratio (SNR) for bio-acoustic monitoring. A method based on spectral peak track, Shannon entropy, harmonic structure and oscillation structure is proposed to automatically detect anuran (frog) calling activity. Gaussian mixture model (GMM) is introduced for modelling those features. Four anuran species widespread in Queensland, Australia, are selected to evaluate the proposed system. A visualization method based on extracted indices is employed for detection of anuran calling activity which achieves high accuracy.

A road safety strategy for Norfolk Island, an Australian external territory

Norfolk Island is an Australian external territory in Oceania. The significant road safety reforms in Australia from the 1970s onward bypassed the island, and most road safety ‘silver bullets’ adopted in other Australian jurisdictions were not introduced. While legislative amendments in 2010 introduced mandatory seat belt wearing for vehicle occupants on Norfolk Island, other critical issues face the community including drink driving by residents and visitors, occupant protection for vehicle passengers, and the provision of a more protective road environment. The release of the first Norfolk Island road safety strategy 2014-2016 proposed, inter alia: • a lower BAC of 0.05 and the introduction of compulsory driver alcohol and drug testing by police; • targeted enforcement of occupant protection for vehicle passengers, particularly for passengers riding on vehicle tray backs; • education interventions to challenge values held by some members of the community that support unsafe road use; • ensuring that driver information, training and testing is adequate for all drivers; • identification and rectification of hazardous roadside infrastructure, particularly barrier protection at “high drop locations” within the road network; and • developing a specification for vehicle standards for vehicles imported into Norfolk Island. Norfolk Island is engaging in a process of integration with the Australian community, and wider issues relating to funding and resources have impacted on the implementation of the road safety strategy. The response to the strategy will be discussed, particularly in terms of current attempts to address drink driving and the provision of a safer road environment.