As one of the major data analysis methods, statistical models play an important role in traffic safety analysis. A common situation associated with crash data is the phenomenon known as overdispersion which has been discussed and investigated frequently in recent years. As such, researchers have proposed several models, such as the Poisson Gamma (PG) or Negative Binomial (NB), the Poisson-lognormal, or the Poisson-Weibull, to handle the overdispersion. Unfortunately, very few models have been proposed for specifically analyzing the sources of dispersions in the data. Better understanding of sources of variation and overdispersion could help in managing safety, such as establishing relationships and applying appropriate treatments or countermeasures, more efficiently. Given the limitations of existing models for exploring the source of overdispersion of crash data, this research examined a new model function that could be applied to explore sources of extra variability through the use of the Generalized Waring (GW) models. This model, which was recently introduced by statisticians, divides the observed variability into three components: randomness, internal differences between road segments or intersections, and the variances caused by other external factors that have not been included as covariates in the model. To evaluate these models, GW models were examined using both simulated and empirical crash datasets, and the results were compared to the most commonly used NB model and the recently developed NB-Lindley models. For model parameter estimation, both the maximum likelihood method and a Bayesian approach were adopted for better comparison. A simulation study was used to show the better performance of this model compared to NB model for overdispersed data, and then an application in the empirical crash data illustrates its capability of modeling data sets with great accuracy and exploring the source of overdispersion. The performances of hotspot identification for these two kinds of models (i.e., GW models and NB models) were also examined and compared based on the estimated models from the empirical dataset. Finally, bias properties related to the choice of prior distributions for parameters in GW model were examined by using a simulation study. In addition, the suggestions on the choice of minimum sample size and priors were presented for different kinds of datasets.

Box and Jenkins methodologies have massively contributed to the analysis of time series data. However, the assumptions used in these methods impose constraints on the type of the data. As a result, difficulties arise when we apply those tools to a more generalized type of data (e.g. count, categorical or integer-valued data) rather than the classical continuous or more specifically Gaussian type. Papers in the literature proposed alternate methods to model discrete-valued time series data, among these methods is Pegram's operator (1980). We use this operator to build an AR(p) model for integer-valued time series (including both positive and negative integers). The innovations follow the differenced Poisson distribution, or Skellam distribution. While the model includes the usual AR(p) correlation structure, it can be made more general. In fact, the operator can be extended in a way where it is possible to have components which contribute to positive correlation, while at the same time have components which contribute to negative correlation. As an illustration, the process is used to model the change in a stock’s price, where three variations are presented: Variation I, Variation II and Variation III. The first model disregards outliers; however, the second and third include large price changes associated with the effect of large volume trades and market openings. Parameters of the model are estimated using Maximum Likelihood methods. We use several model selection criteria to select the best order for each variation of the model as well as to determine which is the best variation of the model. The most adequate order for all the variations of the model is $AR(3)$. While the best fit for the data is Variation II, residuals' diagnostic plots suggest that Variation III represents a better correlation structure for the model.

The generation of macrophages requires the coordinated responses to stimulatory and inhibitory signals that cell receive from their environment. While the up-regulation of macrophage production and survival is essential to fortify the immune system, their down-regulation is also vital to prevent macrophage related diseases and malignancy. Previous studies in goldfish showed that primary kidney macrophages release endogenous growth inducing factors into proliferative phase supernatant, which up-regulate their proliferation and survival. In this thesis, the effect of senescence phase supernatant (collected from goldfish primary kidney macrophage cultures) on goldfish primary kidney macrophages proliferation, survival and its impact on the ability of macrophages to tolerate H2O2 was analyzed. The results showed that the senescence phase supernatant down-regulated the proliferation and survival, and decreased the chemical tolerance of the cells. This indicated that the goldfish primary kidney macrophages promote targeted control of their proliferation and survival by secreting endogenous growth inhibitory factors in the senescence phase supernatant. / Physiology, Cell and Development Biology

国立情報学研究所で電子化したコンテンツを使用している。

国立情報学研究所で電子化したコンテンツを使用している。

Ziel der vorliegenden Arbeit war es, die Quartärstruktur des Tumorsuppressors p53 an Mitochondrien zu untersuchen. In vorangegangenen Untersuchungen der Arbeitsgruppe konnte festgestellt werden, dass der transkriptionsunabhängige Apoptoseweg von p53 an den Mitochondrien resistent war gegenüber dominant-negativer Hemmung durch mutiertes p53. Dadurch stellte sich die Frage, welche Mechanismen für diese Resistenz verantwortlich sind. Unter den zahlreichen, denkbaren Möglichkeiten erschienen zwei als wahrscheinlich: a) Der Mechanismus, der p53 nach Stress an die Mitochondrien transloziert, ist spezifisch für Wildtyp-Homotetramer; b) mitochondriales p53 liegt als Monomer vor. Für das experimentelle Vorgehen wurden HCT116 Colon-Adenokarzinomzellen und MCF-7 Mamaadenokarzinomzellen verwendet, die beide einen intakten p53- Apoptoseweg besitzen. Zudem wurden HCT116R175HPuro und HCT116R273HPuro verwendet, um die Eigenschaften von mutiertem p53 an Mitochondrien untersuchen zu können. Aus den Zellen wurden die Mitochondrien isoliert, um dann die mitochondrialen Proteine durch die beiden Crosslinker Bismaleimidohexan (BMH) und Glutaraldehyd (GLD) zu vernetzen. Durch einen Western Blot wurden die Proteine voneinander getrennt und detektiert. In Voruntersuchungen konnte gezeigt werden, dass Wildtyp-p53 im Gesamtzellextrakt von HCT116 Zellen, ebenso wie die p53 Mutanten, sowohl als Monomer als auch als Oligomer vorkommt. Außerdem konnte eine Methode etabliert werden, mit der es möglich war, Oligomere durch eine Vernetzung mit BMH sichtbar zu machen. Um zeigen zu können, dass die Methode für Proteine an Mitochondrien geeignet war, wurden Bax-Oligomere an den Mitochondrien nachgewiesen. Mit der etablierten Methode konnten dann im Gesamtzellextrakt p53-Oligomere und –Monomere nachgewiesen werden, während p53 an den Mitochondrien unter gleichen Bedingungen nur als Monomer vorlag. Um die erhaltenen Ergebnisse zu bestätigen, wurden die Experimente mit einem weiteren Crosslinker (Glutaraldehyd) wiederholt. Auch in diesen Untersuchungen konnte p53 als Monomer an den Mitochondrien nachgewiesen werden. Um zeigen zu können, dass diese vorliegenden Ergebnisse nicht nur für HCT116 Zellen gültig sind, wurden die beschriebenen Untersuchungen in einer weiteren Zelllinie vorgenommen. Die Ergebnisse bewiesen, dass auch in MCF-7 Zellen p53 vorwiegend als Monomer an den Mitochondrien vorkommt.

Ziel der Untersuchungen war es, im Rahmen einer umfangreichen Bestandsanalyse, mögliche Haupteinflüsse auf die Stoffwechselsituation der Kühe zu ermitteln. Die Frage, ob hochleistende Tiere stärker belastet sind, sollte näher beleuchtet werden. Dazu wurden bei 758 Tieren aus einem Bestand Gesundheitsstatus, Parität und Milchleistung in Beziehung zu Stoffwechsel-, Fruchtbarkeits-, Milchleistungsparametern und Körperkondition gesetzt. Die Parameter des Energiestoffwechsels und die Körperkondition decken eine Energiemangelsituation im untersuchten Bestand auf, deren Folge eine hohe Morbidität und unbefriedigende Fruchtbarkeit ist. Kühe hoher und niedriger Milchleistung haben die höchste Morbidität und die stärksten Abweichungen der Energiestoffwechselparameter (Freie Fettsäuren, Betahydroxybutyrat, Bilirubin). Unterschiede zwischen Kühen und Färsen bestehen häufig und bedürfen besonderer Beachtung im Herdenmanagement. Bei höheren Milchleistungen besteht ein stärkerer und längerer Körpermasseverlust, dementsprechend verschlechtern sich mit höherer Milchleistung die Fruchtbarkeitsparameter.

Most horse owners administer oral deworming medication to their horses on a set schedule, often six times per year. The deworming process involves using a plastic syringe to inject a thick paste into the horse's mouth. Most horse owners do not specifically train their horses to accept this procedure. Consequently, many horses resist the procedure and some horses engage in behaviors, such as head shaking, pulling away, or even rearing, that may be dangerous to humans or to themselves. This study used a negative reinforcement shaping procedure to train six horses to accept dewormer medication. The procedure consisted of a food sampling phase followed by three shaping phases that simulated the deworming task, first using only the experimenter's hand, then a small syringe, and finally a large syringe. Once the horse was acclimated to the syringe, the horse's preferred liquid food was delivered through the syringe at the end of each trial. By the end of the study, all participants successfully completed the procedure and were able to stand still with no or minimal head movements while being dewormed.

Abstract Introduction Most countries including Australia are experiencing an ageing of their population, with an increasing proportion of frail older persons requiring hospitalisation from acute illness. The aging process places the older person at risk of geriatric syndromes, such as falling, dependency in performance of Activities of Daily Living and instrumental Activities of Daily Living, confusion, bladder and bowel incontinence. New or deteriorating geriatric syndromes are a frequent occurrence among hospitalized older patients. Hospital associated factors associated with these outcomes include complications of medical therapies; polypharmacy and excessive bed rest. Few studies have been conducted into factors predicting risk of negative outcomes in older patients admitted to medical units of acute care teaching hospitals. If available, a screening tool with few predictive factors, able to be administered close to the time of admission could be used to identify patients at lower and higher risk. It is imperative that such a tool is developed empirically and tested for its accuracy in identifying patients at high risk. Aims of the research The first aim was to identify the proportion of patients aged ≥ 70 years, admitted to acute care medical units that experienced a negative outcome. These outcomes included falls during hospitalisation, presence of new or a significant decline in existing pressure ulcers, significant decline in independently performing Activities of Daily Living (ADLs), requiring increased care needs at discharge, readmission to hospital with 28 days of the index hospitalisation, bladder and bowel incontinence, and delirium. The second aim was to identify factors predicting the risk of two of these negative outcomes: requiring a higher level of care at discharge, and experiencing a decline in independently performing ADLs. Based on the predictive factors, two screening tools to identify patients at risk were developed and validated. Method A prospective cohort study of 413 acute general medical patients, aged ≥ 70 years and consecutively admitted to an acute care metropolitan 700-bed teaching hospital was conducted. Consenting patients expected to remain in hospital for more than 48 hours were included. Patients were excluded if they were admitted to intensive or coronary care units, admitted for terminal care only or were transferred from a general medical to another unit within 24 hours of admission to the ward. Trained research nurses assessed patients and used the interRAI Acute Care instrument to collect information on candidate predictive variables and negative outcomes. Patients were assessed within 36 hours of admission and at discharge to obtain information on predictive variables and negative outcomes. Patients were also followed daily to identify any instances of transient negative outcomes during hospitalisation and at 28 days following discharge to identify any instances of readmission to hospital. The 413 cases were randomly split into 309 cases in the development cohort and 104 cases in validation cohort. Logistic regression models were used to identify the predictive factors independently associated with two negative outcomes, requiring a higher level of care at discharge and experiencing a decline in independently performing ADLs. Findings At least one negative outcome was experienced by 53% of the development and 63% of the validation cohort. The most common negative outcomes experienced were: delirium (27%; 23%), a significant decline in ADLs (19%, 22%), requiring a higher level of care at discharge (16%, 16%), and readmission to hospital within 28 days of discharge (17%, 28%) in the development and validation cohorts respectively. The logistic regression analysis identified four independent factors associated with requiring higher levels of care at discharge: ‘short term memory problems’ (OR 4.21, 95% CI 1.79, 9.89; p=0.001); ‘dependence in toilet use’ (OR 3.51, 95% CI 1.14, 10.84; p=0.029); ‘dependence in hygiene’ (OR 2.76, 95% CI 1.16, 6.56; p=0.021), and ‘use of community services prior to admission’ (OR 2.41, 95% CI 1.12, 5.16; p= 0.024). A screening tool developed to assess patients at lower and higher risk had a sensitivity, specificity, positive predicted value (PPV) and negative predictive value (NPV) of 77.27%, 73.66%, 36.56% and 94.29% respectively. Reasonable accuracy was evident when tested in the validation sample. Sensitivity, specificity, PPV and NPV were 60%, 76.32%, 33.33% and 90.63% respectively. Predictive factors associated with a significant decline in ADLs were: ‘history of falling’(OR 2.21, 95% CI 1.12, 4.36; p= 0.023), ‘no interest in things enjoyed normally’ (OR 4.30, 95% CI 1.92, 9.64; p=0.000), ‘dependence in management of finances’ (OR 3.93, 95% CI 1.63, 9.48; p =0.002) and ‘hearing problems’ (OR 2.38, 95% CI 1.05, 5.39; p =0.038). The screening tool had sensitivity, specificity, PPV and NPV in the development cohort of 74.55%, 69.13%, 36.6% and 92% respectively and 45%, 65.79%, 25.7% and 82% respectively in the validation sample. Conclusion The tools require further validation in larger samples in diverse settings. Future research should focus on developing a screening tool that could predict risk of a number of negative outcomes to enhance the provision of quality patient care.

Corrigenda pasted onto front fly-leaf. / Bibliography: leaves 247-286. / xv, 286 leaves : ill. (some col.) ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / This thesis examines an aspect of the pathogenesis of a model extracellular enteric pathogen, the causative agent of human cholera. The export of TcpA (Toxin-Coregulated Pilus) and assembly of the TCP is explored as a paradigm of macromolecular export in Gram negative bacteria. TcpA is examined in detail in an attempt to define strictly conserved regions between species. The TCP of the emergent 0139 (Bengal) serotype is demonstrated to be of El Tor type. The possibily that proteases such as the soluble haemagglutinin (SHA) may have a detachase role centring on TCP dispersal/TcpA degradation is also discussed. / Thesis (Ph.D.)--University of Adelaide, Dept. of Microbiology, 1997