424 resultados para Australian PhD data


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Lucerne (Medicago sativa L.) is autotetraploid, and predominantly allogamous. This complex breeding structure maximises the genetic diversity within lucerne populations making it difficult to genetically discriminate between populations. The objective of this study was to evaluate the level of random genetic diversity within and between a selection of Australian-grown lucerne cultivars, with tetraploid M. falcata included as a possible divergent control source. This diversity was evaluated using random amplified polymorphic DNA (RAPDs). Nineteen plants from each of 10 cultivars were analysed. Using 11 RAPD primers, 96 polymorphic bands were scored as present or absent across the 190 individuals. Genetic similarity estimates (GSEs) of all pair-wise comparisons were calculated from these data. Mean GSEs within cultivars ranged from 0.43 to 0.51. Cultivar Venus (0.43) had the highest level of intra-population genetic diversity and cultivar Sequel HR (0.51) had the lowest level of intra-population genetic diversity. Mean GSEs between cultivars ranged from 0.31 to 0.49, which overlapped with values obtained for within-cultivar GSE, thus not allowing separation of the cultivars. The high level of intra- and inter-population diversity that was detected is most likely due to the breeding of synthetic cultivars using parents derived from a number of diverse sources. Cultivar-specific polymorphisms were only identified in the M. falcata source, which like M. sativa, is outcrossing and autotetraploid. From a cluster analysis and a principal components analysis, it was clear that M. falcata was distinct from the other cultivars. The results indicate that the M. falcata accession tested has not been widely used in Australian lucerne breeding programs, and offers a means of introducing new genetic diversity into the lucerne gene pool. This provides a means of maximising heterozygosity, which is essential to maximising productivity in lucerne.

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The objective of this study was to determine the mortality rate and the functional outcomes of stroke patients admitted to the intensive care unit (ICU) and to identify predictors of poor outcome in this population. The records of all patients admitted to the ICU with the diagnosis of stroke between January 1994 and December 1999 were reviewed. Patients with subarachnoid haemorrhage were excluded. Data were collected on clinical and biological variables, risk factors for stroke and the presence of comorbidities. Mortality (ICU, in-hospital and three-month) and functional outcome were used as end-points. In the six-year-period, 61 patients were admitted to the ICU with either haemorrhagic or ischaemic stroke. Medical records were available for only 58 patients. There were 23 ischaemic and 35 haemorrhagic strokes. The ICU, in-hospital and three-month mortality rates were 36%, 47% and 52% respectively. There were no significant differences in the prevalence of premorbid risk factors between survivors and non-survivors. The mean Barthel score was significantly different between the independent and dependent survivors (94 +/- 6 vs 45 +/- 26, P < 0.001). A substantial number of patients with good functional outcomes had lower Rankin scores (92% vs 11%, P < 0.001). Only 46% of those who were alive at three months were functionally independent. Intensive care admission was associated with a high mortality rate and a high likelihood of dependent lifestyle after hospital discharge. Haemorrhagic stroke, fixed dilated pupil(s) and GCS < 10 during assessment were associated with increased mortality and poor functional outcome.

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Spatial and temporal variability in wheat production in Australia is dominated by rainfall occurrence. The length of historical production records is inadequate, however, to analyse spatial and temporal patterns conclusively. In this study we used modelling and simulation to identify key spatial patterns in Australian wheat yield, identify groups of years in the historical record in which spatial patterns were similar, and examine association of those wheat yield year groups with indicators of the El Nino Southern Oscillation (ENSO). A simple stress index model was trained on 19 years of Australian Bureau of Statistics shire yield data (1975-93). The model was then used to simulate shire yield from 1901 to 1999 for all wheat-producing shires. Principal components analysis was used to determine the dominating spatial relationships in wheat yield among shires. Six major components of spatial variability were found. Five of these represented near spatially independent zones across the Australian wheatbelt that demonstrated coherent temporal (annual) variability in wheat yield. A second orthogonal component was required to explain the temporal variation in New South Wales. The principal component scores were used to identify high- and low-yielding years in each zone. Year type groupings identified in this way were tested for association with indicators of ENSO. Significant associations were found for all zones in the Australian wheatbelt. Associations were as strong or stronger when ENSO indicators preceding the wheat season (April-May phases of the Southern Oscillation Index) were used rather than indicators based on classification during the wheat season. Although this association suggests an obvious role for seasonal climate forecasting in national wheat crop forecasting, the discriminatory power of the ENSO indicators, although significant, was not strong. By examining the historical years forming the wheat yield analog sets within each zone, it may be possible to identify novel climate system or ocean-atmosphere features that may be causal and, hence, most useful in improving seasonal forecasting schemes.

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The aim of this study was to review the published literature values for the selenium content of Australian foods. A secondary aim was to compare the results for Australian foods with food composition data from international sources to investigate the extent of geographical variation. Published food composition data sources for the selenium content in Australian foods were identified and assessed for data quality using established criteria. The selenium content is available for 148 individual food items. The highest values found are for fish (12.0-63.2 mug/100 g), meats (4.75-37.9 mug/100 g) and eggs (9.00-41.4 mug/100 g), followed by cereals (1.00-20.3 mug/100 g). Moderate levels are seen in dairy products (2.00-7.89 mug/100 g) while most fruits and vegetables have low levels (trace-3.27 mug/100 g). High selenium foods show the greatest level of geographical variation, with foods from the United States generally having higher selenium levels than Australian foods and foods from the United Kingdom and New Zealand having lower levels. This is the first attempt to review the available literature for selenium composition of Australian foods. These data serve as an interim measure for the assessment of selenium intake for use in epidemiological studies of diet-disease relationships. (C) 2002 Published by Elsevier Science Ltd.

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Back ground. Based on the well-described excess of schizophrenia births in winter and spring, we hypothesised that individuals with schizophrenia (a) would be more likely to be born during periods of decreased perinatal sunshine, and (b) those born during periods of less sunshine would have an earlier age of first registration. Methods. We undertook an ecological analysis of long-term trends in perinatal sunshine duration and schizophrenia birth rates based on two mental health registers (Queensland. Australia n = 6630; The Netherlands n = 24, 474). For each of the 480 months between 1931 and 1970, the agreement between slopes of the trends in psychosis and long-term sunshine duration series were assessed. Age at first registration was assessed by quartiles of long-term trends in perinatal sunshine duration, Males and females were assessed separately. Results. Both the Dutch and Australian data showed a statistically significant association between falling long-term trends in sunshine duration around the time of birth and rising schizophrenia birth rates for males only. In both the Dutch and Australian data there were significant associations between earlier age of first registration and reduced long-term trends in sunshine duration around the time of birth for both males and females, Conclusions. A measure of long-term trends in perinatal sunshine duration was associated with two epidemiological features of schizophrenia in two separate data sets. Exposures related to sunshine duration warrant further consideration in schizophrenia research. (C) 2002 Elsevier Science B.V. All rights reserved.

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Evaluation of the performance of the APACHE III (Acute Physiology and Chronic Health Evaluation) ICU (intensive care unit) and hospital mortality models at the Princess Alexandra Hospital, Brisbane is reported. Prospective collection of demographic, diagnostic, physiological, laboratory, admission and discharge data of 5681 consecutive eligible admissions (1 January 1995 to 1 January 2000) was conducted at the Princess Alexandra Hospital, a metropolitan Australian tertiary referral medical/surgical adult ICU. ROC (receiver operating characteristic) curve areas for the APACHE III ICU mortality and hospital mortality models demonstrated excellent discrimination. Observed ICU mortality (9.1%) was significantly overestimated by the APACHE III model adjusted for hospital characteristics (10.1%), but did not significantly differ from the prediction of the generic APACHE III model (8.6%). In contrast, observed hospital mortality (14.8%) agreed well with the prediction of the APACHE III model adjusted for hospital characteristics (14.6%), but was significantly underestimated by the unadjusted APACHE III model (13.2%). Calibration curves and goodness-of-fit analysis using Hosmer-Lemeshow statistics, demonstrated that calibration was good with the unadjusted APACHE III ICU mortality model, and the APACHE III hospital mortality model adjusted for hospital characteristics. Post hoc analysis revealed a declining annual SMR (standardized mortality rate) during the study period. This trend was present in each of the non-surgical, emergency and elective surgical diagnostic groups, and the change was temporally related to increased specialist staffing levels. This study demonstrates that the APACHE III model performs well on independent assessment in an Australian hospital. Changes observed in annual SMR using such a validated model support an hypothesis of improved survival outcomes 1995-1999.

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Study objective: To assess the representativeness of survey participants by systematically comparing volunteers in a national health and sexuality survey with the Australian population in terms of self reported health status (including the SF-36) and a wide range of demographic characteristics. Design: A cross sectional sample of Australian residents were compared with demographic data from the 1996 Australian census and health data from the 1995 National Health Survey. Setting: The Australian population. Participants: A stratified random sample of adults aged 18-59 years drawn from the Australian electoral roll, a compulsory register of voters. Interviews were completed with 1784 people, representing 40% of those initially selected (58% of those for whom a valid telephone number could be located). Main results: Participants were of similar age and sex to the national population. Consistent with prior research, respondents had higher socioeconomic status, more education, were more likely to be employed, and less likely to be immigrants. The prevalence estimates, means, and variances of self reported mental and physical health measures (for example, SF-36 subscales, women's health indicators, current smoking status) were similar to population norms. Conclusions: These findings considerably strengthen inferences about the representativeness of data on health status from volunteer samples used in health and sexuality surveys.

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Objectives: To study the influence of different diagnostic criteria on the prevalence of diabetes mellitus and characteristics of those diagnosed. Design and setting: Retrospective analysis of data from the general-practice-based Australian Diabetes Screening Study (January 1994 to June 1995). Participants: 5911 people with no previous diagnosis of diabetes, two or more symptoms or risk factors for diabetes, a random venous plasma glucose (PG) level > 5.5 mmol/L and a subsequent oral glucose tolerance test (OGTT) result. Main outcome measure: Prevalence of undiagnosed diabetes based on each of three sets of criteria: 1997 criteria of the American Diabetes Association (ADA), 1996 two-step screening strategy of the Australian Diabetes Society (ADS) (modified according to ADA recommendations about lowered diagnostic fasting PG level), and 1999 definition of the World Health Organization (WHO). Results: Prevalence estimates for undiagnosed diabetes using the American (ADA), Australian (ADS) and WHO criteria (95% CI) were 9.4% (8.7%-10.1%), 16.0% (15.3%-16.7%) and 18.1% (17.1%-19.1%), respectively. People diagnosed with diabetes by fasting PG level (common to all sets of criteria) were more likely to be male and younger than those diagnosed only by 2 h glucose challenge PG level (Australian and WHO criteria only). The Australian (ADS) stepwise screening strategy detected 88% of those who met the WHO criteria for diabetes, including about three-quarters of those with isolated post-challenge hyperglycaemia. Conclusion: The WHO criteria (which include an OGTT result) are preferable to the American (ADA) criteria (which rely totally on fasting PG level), as the latter underestimated the prevalence of undiagnosed diabetes by almost a half. The Australian (ADS) strategy identified most of those diagnosed with diabetes by WHO criteria.

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We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.

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What causes species richness to vary among different groups of organisms? Two hypotheses are that large geographical ranges and fast life history either reduce extinction rates or raise speciation rates, elevating a clade's rate of diversification. Here we present a comparative analysis of these hypotheses using data on the phylogenetic relationships, geographical ranges and life history of the terrestrial mammal fauna of Australia. By comparing species richness patterns to null models, we show that species are distributed nonrandomly among genera. Using sister-clade comparisons to control for clade age, we then find that faster diversification is significantly associated with larger geographical ranges and larger litters, but there is no evidence for an effect of body size or age at first breeding on diversification rates. We believe the most likely explanation for these patterns is that larger litters and geographical ranges increase diversification rates because they buffer species from extinction. We also discuss the possibility that positive effects of litter size and range size on diversification rates result from elevated speciation rates.

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We investigated the oviposition preference and larval performance of Helicoverpa armigera under laboratory conditions to determine if the oviposition preference of individual females on maize, cowpea and cotton correlates with offspring performance on the leaves of the same host plants. The host-plant preference hierarchy of females did not correlate with their offspring performance. Female moths chose host plants that contributed less to their offspring fitness. Plant effects accounted for the largest amount of variation in offspring performance, while the effects of female (family) was low. The offspring of most females (80%, n = 10) were broadly similar, but 20% (two out of 10), showed marked difference in their offspring performance across the host-plant species. Similarly, there was no relation between larval feeding preference and performance. However, like most laboratory experiments, our experi-mental design does not allow the evaluation of ecological factors (for example, natural enemies, host abundance, etc.) that can play an important role in larval performance in the field. Overall, the results highlight the importance of carrying out preference performance analysis on the individual or family level, rather than pooling individuals to obtain average population data.

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Measuring perceptions of customers can be a major problem for marketers of tourism and travel services. Much of the problem is to determine which attributes carry most weight in the purchasing decision. Older travellers weigh many travel features before making their travel decisions. This paper presents a descriptive analysis of neural network methodology and provides a research technique that assesses the weighting of different attributes and uses an unsupervised neural network model to describe a consumer-product relationship. The development of this rich class of models was inspired by the neural architecture of the human brain. These models mathematically emulate the neurophysical structure and decision making of the human brain, and, from a statistical perspective, are closely related to generalised linear models. Artificial neural networks or neural networks are, however, nonlinear and do not require the same restrictive assumptions about the relationship between the independent variables and dependent variables. Using neural networks is one way to determine what trade-offs older travellers make as they decide their travel plans. The sample of this study is from a syndicated data source of 200 valid cases from Western Australia. From senior groups, active learner, relaxed family body, careful participants and elementary vacation were identified and discussed. (C) 2003 Published by Elsevier Science Ltd.

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For zygosity diagnosis in the absence of genotypic data, or in the recruitment phase of a twin study where only single twins from same-sex pairs are being screened, or to provide a test for sample duplication leading to the false identification of a dizygotic pair as monozygotic, the appropriate analysis of respondents' answers to questions about zygosity is critical. Using data from a young adult Australian twin cohort (N = 2094 complete pairs and 519 singleton twins from same-sex pairs with complete responses to all zygosity items), we show that application of latent class analysis (LCA), fitting a 2-class model, yields results that show good concordance with traditional methods of zygosity diagnosis, but with certain important advantages. These include the ability, in many cases, to assign zygosity with specified probability on the basis of responses of a single informant (advantageous when one zygosity type is being oversampled); and the ability to quantify the probability of misassignment of zygosity, allowing prioritization of cases for genotyping as well as identification of cases of probable laboratory error. Out of 242 twins (from 121 like-sex pairs) where genotypic data were available for zygosity confirmation, only a single case was identified of incorrect zygosity assignment by the latent class algorithm. Zygosity assignment for that single case was identified by the LCA as uncertain (probability of being a monozygotic twin only 76%), and the co-twin's responses clearly identified the pair as dizygotic (probability of being dizygotic 100%). In the absence of genotypic data, or as a safeguard against sample duplication, application of LCA for zygosity assignment or confirmation is strongly recommended.

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Our previous studies have shown that two distinct genotypes of Sindbis (SIN) virus occur in Australia. One of these, the Oriental/Australian type, circulates throughout most of the Australian continent, whereas the recently identified south-west (SW) genetic type appears to be restricted to a distinct geographic region located in the temperate south-west of Australia. We have now determined the complete nucleotide and translated amino acid sequences of a SW isolate of SIN virus (SW6562) and performed comparative analyses with other SIN viruses at the genomic level. The genome of SW6562 is 11,569 nucleotides in length, excluding the cap nucleotide and poly (A) tail. Overall this virus differs from the prototype SIN virus (strain AR339) by 23% in nucleotide sequence and 12.5% in amino acid sequence. Partial sequences of four regions of the genome of four SW isolates were determined and compared with the corresponding sequences from a number of SIN isolates from different regions of the World. These regions are the non-structural protein (nsP3), the E2 gene, the capsid gene, and the repeated sequence elements (RSE) of the 3'UTR. These comparisons revealed that the SW SIN viruses were more closely related to South African and European strains than to other Australian isolates of SIN virus. Thus the SW genotype of SIN virus may have been introduced into this region of Australia by viremic humans or migratory birds and subsequently evolved independently in the region. The sequence data also revealed that the SW genotype contains a unique deletion in the RSE of the 3'UTR region of the genome. Previous studies have shown that deletions in this region of the SIN genome can have significant effects on virus replication in mosquito and avian cells, which may explain the restricted distribution of this genotype of SIN virus.