ORCID Profile
0000-0003-0736-9751
Current Organisation
RMIT University
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Publisher: Public Library of Science (PLoS)
Date: 03-2023
DOI: 10.1371/JOURNAL.PONE.0282426
Abstract: The increasing incidence of type 1 diabetes (T1D) in children is a growing global concern. It is known that genetic and environmental factors contribute to childhood T1D. An optimal model to predict the development of T1D in children using Key Performance Indicators (KPIs) would aid medical practitioners in developing intervention plans. This paper for the first time has built a model to predict the risk of developing T1D and identify its significant KPIs in children aged (0-14) in Saudi Arabia. Machine learning methods, namely Logistic Regression, Random Forest, Support Vector Machine, Naive Bayes, and Artificial Neural Network have been utilised and compared for their relative performance. Analyses were performed in a population-based case-control study from three Saudi Arabian regions. The dataset (n = 1,142) contained demographic and socioeconomic status, genetic and disease history, nutrition history, obstetric history, and maternal characteristics. The comparison between case and control groups showed that most children (cases = 68% and controls = 88%) are from urban areas, 69% (cases) and 66% (control) were delivered after a full-term pregnancy and 31% of cases group were delivered by caesarean, which was higher than the controls ( χ 2 = 4.12, P-value = 0.042). Models were built using all available environmental and family history factors. The efficacy of models was evaluated using Area Under the Curve, Sensitivity, F Score and Precision. Full logistic regression outperformed other models with Accuracy = 0.77, Sensitivity, F Score and Precision of 0.70, and AUC = 0.83. The most significant KPIs were early exposure to cow’s milk (OR = 2.92, P = 0.000), birth weight Kg (OR = 3.11, P = 0.007), residency(rural) (OR = 3.74, P = 0.000), family history (first and second degree), and maternal age years. The results presented here can assist healthcare providers in collecting and monitoring influential KPIs and developing intervention strategies to reduce the childhood T1D incidence rate in Saudi Arabia.
Publisher: Wiley
Date: 24-02-2020
DOI: 10.1002/OBY.22722
Publisher: Elsevier BV
Date: 05-2007
DOI: 10.1016/J.DRUGALCDEP.2006.10.016
Abstract: Like other psychostimulant drugs, acute exposure to benzylpiperazine (BZP) increases dopaminergic neurotransmission, producing hyperactivity and stereotypy. The consequences of repeated BZP exposure have not however been investigated. The effects of acute and repeated BZP and meth hetamine (MA) exposure on locomotor activity and stereotypy were measured in order to determine whether there was sensitization and cross-sensitization between these two psychostimulant drugs. The effects of acute treatment with MA (0.0, 0.5, 1.0 and 2.0 mg/kg, intraperitoneal (IP)) or BZP (0.0, 5.0, 10.0, 20.0 and 40.0 mg/kg, IP) on locomotor activity and stereotypy were determined. Effects of repeated exposure were determined in other groups that received five daily injections of 2.0 mg/kg MA, 20.0 mg/kg BZP or vehicle. Following a 2-day withdrawal period, rats from each treatment group received either a low dose MA (0.5 mg/kg) or BZP (10.0 mg/kg). MA and BZP produced dose-dependent hyperactivity and stereotypy. Repeated MA and BZP resulted in a potentiated locomotor but not stereotypy response. Following the withdrawal period, MA pretreated rats exhibited a sensitized locomotor and stereotypy response to the low dose MA and a conditioned response to saline. BZP pretreated rats also demonstrated a sensitized locomotor response to the low dose of BZP and MA. The present findings indicate that repeated exposure to BZP results in sensitization and cross-sensitization to MA.
Publisher: Wiley
Date: 21-07-2015
DOI: 10.1111/BJU.13176
Abstract: To examine the patterns of care and outcomes for metastatic renal cell carcinoma (mRCC) in Australia, where there are limited reimbursed treatment options. In particular, we aim to explore prescribing patterns for first-line systemic treatment, the practice of an initial watchful-waiting approach, and the use of systemic treatments in elderly patients. Patients with mRCC undergoing treatment between 2006 and 2012 were identified from four academic hospitals in Victoria and Australian Capital Territory. Demographic, clinicopathological, treatment, and survival data were recorded by chart review. Descriptive statistics were used to report findings. Survival was estimated by the Kaplan-Meier method and compared using the log-rank test. The study was supported by a grant from Pfizer Australia. Our study identified 212 patients with mRCC for analysis. Patients were predominantly of clear cell histology (75%), Eastern Cooperative Oncology Group performance status 90 days before initiating treatment these patients had a median OS of 56.3 months. Elderly patients (50 patients aged ≥70 years) were more likely to receive BSC alone than younger patients (46% vs 16%, P < 0.001). Of those who received systemic therapy, elderly patients were also more likely to have upfront dose reductions (30% vs 8%, P = 0.03). Our study of patients with mRCC treated in Australian centres showed that sunitinib was the most commonly prescribed systemic treatment between 2006 and 2012, associated with survival outcomes similar to pivotal studies. We also found that an initial watchful-waiting approach is commonly adopted without apparent detriment to survival. And finally, we found that age has an impact on the prescribing of systemic therapy.
Publisher: SAGE Publications
Date: 11-2007
Abstract: N-benzylpiperazine (BZP) is the active ingredient in recreational `party' or `p.e.p.' pills, which are used to provide a stimulant, euphoric effect akin to that of methylenedioxymeth hetamine (MDMA, `ecstasy'). BZP predominantly affects dopamine neurotransmission in a similar fashion to known `drugs of abuse', such as meth hetamine and cocaine, which strongly suggests BZP has abuse liability. BZP is illegal in many countries including the United States of America and Australia, yet it remains legal in the United Kingdom, Canada and New Zealand. There has been little research, to date, on the neurological consequences of high dose or chronic exposure of BZP. Here we provide a comprehensive review of the information currently available on BZP and suggest a need for further research into the mechanisms of action, long-term effects and potentially addictive properties of BZP.
Publisher: CSIRO Publishing
Date: 2020
DOI: 10.1071/WR19216
Abstract: Abstract Context. Feral cats (Felis catus) pose a significant threat to Australia’s native species and feral cat control is, therefore, an important component of threatened species management and policy. Australia’s Threatened Species Strategy articulates defined targets for feral cat control. Yet, currently, little is known about who is engaged in feral cat control in Australia, what motivates them, and at what rate they are removing feral cats from the environment. Aims. We aim to document who is engaging in feral cat control in Australia, how many cats they remove and to estimate the number of feral cats killed in a single year. Furthermore, we seek to better understand attitudes towards feral cat control in Australia. Methods. We used a mixed methods approach combining quantitative and qualitative techniques. Feral cat control data were obtained from existing data repositories and via surveys targeting relevant organisations and in iduals. A bounded national estimate of the number of feral cats killed was produced by combining estimates obtained from data repositories and surveys with modelled predictions for key audience segments. Attitudes towards feral cat control were assessed by exploring qualitative responses to relevant survey questions. Key results. We received information on feral cat control from three central repositories, 134 organisations and 2618 in iduals, together removing more than 35000 feral cats per year. When including projections to national populations of key groups, the estimated number of feral cats removed from the environment in the 2017–2018 financial year was 316030 (95% CI: 297742–334318). Conclusions. In iduals and organisations make a significant, and largely unrecorded, contribution to feral cat control. Among in iduals, there is a strong awareness of the impact of feral cats on Australia’s bio ersity. Opposition to feral cat control focussed largely on ethical concerns and doubts about its efficacy. Implications. There is significant interest in, and commitment to, feral cat control among some groups of Australian society, beyond the traditional conservation community. Yet more information is needed about control methods and their effectiveness to better understand how these efforts are linked to threatened species outcomes.
Publisher: Public Library of Science (PLoS)
Date: 28-02-2022
DOI: 10.1371/JOURNAL.PONE.0264118
Abstract: The rising incidence of type 1 diabetes (T1D) among children is an increasing concern globally. A reliable estimate of the age at onset of T1D in children would facilitate intervention plans for medical practitioners to reduce the problems with delayed diagnosis of T1D. This paper has utilised Multiple Linear Regression (MLR), Artificial Neural Network (ANN) and Random Forest (RF) to model and predict the age at onset of T1D in children in Saudi Arabia (S.A.) which is ranked as the 7th for the highest number of T1D and 5th in the world for the incidence rate of T1D. De-identified data between (2010-2020) from three cities in S.A. were used to model and predict the age at onset of T1D. The best subset model selection criteria, coefficient of determination, and diagnostic tests were deployed to select the most significant variables. The efficacy of models for predicting the age at onset was assessed using multi-prediction accuracy measures. The average age at onset of T1D is 6.2 years and the most common age group for onset is (5-9) years. Most of the children in the s le (68%) are from urban areas of S.A., 75% were delivered after a full term pregnancy length and 31% were delivered through a cesarean section. The models of best fit were the MLR and RF models with R 2 = (0.85 and 0.95), the root mean square error = (0.25 and 0.15) and mean absolute error = (0.19 and 0.11) respectively for logarithm of age at onset. This study for the first time has utilised MLR, ANN and RF models to predict the age at onset of T1D in children in S.A. These models can effectively aid health care providers to monitor and create intervention strategies to reduce the impact of T1D in children in S.A.
No related grants have been discovered for Alice Johnstone.