Physiological and pathological human ocular perfusion characteristics

There were three principle aims to this thesis. Firstly, the acquisition protocols of clinical blood flow apparatus were investigated in order to optimise them for both cross-sectional and longitudinal application. Secondly, the effects of physiological factors including age and systematic circulation on ocular blood flow were investigated. Finally, the ocular perfusion characteristics of patients diagnosed with ocular diseases considered to be of a vascular origin were investigated. The principle findings of this work are:- 1) Optimisation of clinical investigationsPhotodiode sensitivity of the scanning laser Doppler flowmeter should be kept within a range of 70-150 DC when acquiring images of the retina and optic nerve head in order to optimise the reproducibility of capillary blood flow measures. Account of the physiological spatial variation in retinal blood flow measures can be made using standard analysis protocols of the scanning laser Doppler flowmeter combined with a local search strategy. Measurements of pulsatile ocular blood flow using the ocular blood flow analyser are reproducible, however this reproducibility can be improved when consecutive intraocular pressure pulses are used to calculate pulsatile ocular blood flow. Spectral analysis of the intraocular pressure pulse-wave is viable and identifies the first four harmonic components of the waveform. 2) Physiological variation in ocular perfusionAge results in a significant reduction in perfusion of the retinal microcirculation, which is not evident in larger vessel beds such as the choroid. Despite known asymmetry in the systemic vasculature, no evidence of interocular asymmetry in ocular perfusion is apparent. 3) Pathological variation in ocular perfusionIn primary open angle glaucoma, perfusion is reduced in the retinal microcirculation of patients classified as having early to moderate visual field defects. However, ocular pulsatility defects are masked when patients and subjects are matched for systemic variables (pulse rate and mean arterial pressure); differentiation is facilitated by the application of waveform analysis to the continuos intraocular pressure curve even in the early stages of disease. Diabetic patients with adequate glycaemic control, exhibit maintenance of macular blood flow, macular topography and visual function following phacoemulsification.

New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM)

LEÃO, Adriano de Castro; DÓRIA NETO, Adrião Duarte; SOUSA, Maria Bernardete Cordeiro de. New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM). Computers in Biology and Medicine, v. 39, p. 853-859, 2009

New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM)

LEÃO, Adriano de Castro; DÓRIA NETO, Adrião Duarte; SOUSA, Maria Bernardete Cordeiro de. New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM). Computers in Biology and Medicine, v. 39, p. 853-859, 2009

An association rule analysis framework for complex physiological and genetic data

Physiological and genetic information has been critical to the successful diagnosis and prognosis of complex diseases. In this paper, we introduce a support-confidence-correlation framework to accurately discover truly meaningful and interesting association rules between complex physiological and genetic data for disease factor analysis, such as type II diabetes (T2DM). We propose a novel Multivariate and Multidimensional Association Rule mining system based on Change Detection (MMARCD). Given a complex data set u i (e.g. u 1 numerical data streams, u 2 images, u 3 videos, u 4 DNA/RNA sequences) observed at each time tick t, MMARCD incrementally finds correlations and hidden variables that summarise the key relationships across the entire system. Based upon MMARCD, we are able to construct a correlation network for human diseases. © 2012 Springer-Verlag.

Physiological and symptomatic responses to cycling and walking in intermittent claudication

To shed light on the potential efficacy of cycling as a testing modality in the treatment of intermittent claudication (IC), this study compared physiological and symptomatic responses to graded walking and cycling tests in claudicants. Sixteen subjects with peripheral arterial disease (resting ankle: brachial index (ABI) < 0.9) and IC completed a maximal graded treadmill walking (T) and cycle (C) test after three familiarization tests on each mode. During each test, symptoms, oxygen uptake (VO2), minute ventilation (VE), respiratory exchange ratio (RER) and heart rate (HR) were measured, and for 10 min after each test the brachial and ankle systolic pressures were recorded. All but one subject experienced calf pain as the primary limiting symptom during T; whereas the symptoms were more varied during C and included thigh pain, calf pain and dyspnoea. Although maximal exercise time was significantly longer on C than T (690 +/- 67 vs. 495 +/- 57 s), peak VO2, peak VE and peak heart rate during C and T were not different; whereas peak RER was higher during C. These responses during C and T were also positively correlated (P < 0.05) with each other, with the exception of RER. The postexercise systolic pressures were also not different between C and T. However, the peak decline in ankle pressures from resting values after C and T were not correlated with each other. These data demonstrate that cycling and walking induce a similar level of metabolic and cardiovascular strain, but that the primary limiting symptoms and haemodynamic response in an individual's extremity, measured after exercise, can differ substantially between these two modes.

Cross-correlations between weather variables in Australia

The information on climate variations is essential for the research of many subjects, such as the performance of buildings and agricultural production. However, recorded meteorological data are often incomplete. There may be a limited number of locations recorded, while the number of recorded climatic variables and the time intervals can also be inadequate. Therefore, the hourly data of key weather parameters as required by many building simulation programmes are typically not readily available. To overcome this gap in measured information, several empirical methods and weather data generators have been developed. They generally employ statistical analysis techniques to model the variations of individual climatic variables, while the possible interactions between different weather parameters are largely ignored. Based on a statistical analysis of 10 years historical hourly climatic data over all capital cities in Australia, this paper reports on the finding of strong correlations between several specific weather variables. It is found that there are strong linear correlations between the hourly variations of global solar irradiation (GSI) and dry bulb temperature (DBT), and between the hourly variations of DBT and relative humidity (RH). With an increase in GSI, DBT would generally increase, while the RH tends to decrease. However, no such a clear correlation can be found between the DBT and atmospheric pressure (P), and between the DBT and wind speed. These findings will be useful for the research and practice in building performance simulation.

Identification of critical input variables for risk-based cost estimates for road maintenance and rehabilitation

An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

Predicting behaviour to reduce stroke risk in at-risk populations : the role of beliefs

Aims: Changing behaviour to reduce stroke risk is a difficult prospect made particularly complex because of psychological factors. This study examined predictors of intentions and behaviours to reduce stroke risk in a sample of at-risk individuals, seeking to find how knowledge and health beliefs influenced both intention and actual behaviour to reduce stroke risk. Methods: A repeated measures design was used to assess behavioural intentions at time 1 (T1) and subsequent behaviour (T2). One hundred and twenty six respondents completed an online survey at T1, and behavioural follow-up data were collected from approximately 70 participants 1 month later. Predictors were stroke knowledge, demographic variables, and beliefs about stroke that were derived from an expanded health belief model. Dependent measures were: exercise and weight loss, and intention to engage in these behaviours to reduce stroke risk. Findings: Multiple hierarchical regression analyses showed that, for exercise and weight loss respectively, different health beliefs predicted intention to control stroke risk. The most important exercise-related health beliefs were benefits, susceptibility, and self-efficacy; for weight loss, the most important beliefs were barriers, and to a lesser degree, susceptibility and subjective norm. Conclusions: Health beliefs may play an important role in stroke prevention, particularly beliefs about susceptibility because these emerged for both behaviours. Stroke education and prevention programmes that selectively target the health beliefs relevant to specific behaviours may prove most efficacious.

Using Trauma Injury Severity Score (TRISS) variables to predict length of hospital stay following trauma in New Zealand

Aim – To develop and assess the predictive capabilities of a statistical model that relates routinely collected Trauma Injury Severity Score (TRISS) variables to length of hospital stay (LOS) in survivors of traumatic injury. Method – Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until discharge from Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Cubic-root transformed LOS was analysed using two-level mixed-effects regression models. Results – 1498 eligible patients were identified, 1446 (97%) injured from a blunt mechanism and 52 (3%) from a penetrating mechanism. For blunt mechanism trauma, 1096 (76%) were male, average age was 37 years (range: 15-94 years), and LOS and TRISS score information was available for 1362 patients. Spearman’s correlation and the median absolute prediction error between LOS and the original TRISS model was ρ=0.31 and 10.8 days, respectively, and between LOS and the final multivariable two-level mixed-effects regression model was ρ=0.38 and 6.0 days, respectively. Insufficient data were available for the analysis of penetrating mechanism models. Conclusions – Neither the original TRISS model nor the refined model has sufficient ability to accurately or reliably predict LOS. Additional predictor variables for LOS and other indicators for morbidity need to be considered.