918 resultados para Gastrointestinal motility


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In the elderly, the risks for protein-energy malnutrition from older age, dementia, depression and living alone have been well-documented. Other risk factors including anorexia, gastrointestinal dysfunction, loss of olfactory and taste senses and early satiety have also been suggested to contribute to poor nutritional status. In Parkinson’s disease (PD), it has been suggested that the disease symptoms may predispose people with PD to malnutrition. However, the risks for malnutrition in this population are not well-understood. The current study’s aim was to determine malnutrition risk factors in community-dwelling adults with PD. Nutritional status was assessed using the Patient-Generated Subjective Global Assessment (PG-SGA). Data about age, time since diagnosis, medications and living situation were collected. Levodopa equivalent doses (LDED) and LDED per kg body weight (mg/kg) were calculated. Depression and anxiety were measured using the Beck’s Depression Inventory (BDI) and Spielberger Trait Anxiety questionnaire, respectively. Cognitive function was assessed using the Addenbrooke’s Cognitive Examination (ACE-R). Non-motor symptoms were assessed using the Scales for Outcomes in Parkinson's disease-Autonomic (SCOPA-AUT) and Modified Constipation Assessment Scale (MCAS). A total of 125 community-dwelling people with PD were included, average age of 70.2±9.3(35-92) years and average time since diagnosis of 7.3±5.9(0–31) years. Average body mass index (BMI) was 26.0±5.5kg/m2. Of these, 15% (n=19) were malnourished (SGA-B). Multivariate logistic regression analysis revealed that older age (OR=1.16, CI=1.02-1.31), more depressive symptoms (OR=1.26, CI=1.07-1.48), lower levels of anxiety (OR=.90, CI=.82-.99), and higher LDED per kg body weight (OR=1.57, CI=1.14-2.15) significantly increased malnutrition risk. Cognitive function, living situation, number of prescription medications, LDED, years since diagnosis and the severity of non-motor symptoms did not significantly influence malnutrition risk. Malnutrition results in poorer health outcomes. Proactively addressing the risk factors can help prevent declines in nutritional status. In the current study, older people with PD with depression and greater amounts of levodopa per body weight were at increased malnutrition risk.

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Ghrelin, the endogenous ligand for the GH secretagogue receptor (GHSR), is a peptide hormone with diverse physiological roles. Ghrelin regulates GH release, appetite and feeding, gut motility, and energy balance and also has roles in the cardiovascular, immune, and reproductive systems. Ghrelin and the GHSR are expressed in a wide range of normal and tumor tissues, and a fluorescein-labeled, truncated form of ghrelin is showing promise as a biomarker for prostate cancer. Plasma ghrelin levels are generally inversely related to body mass index and are unlikely to be useful as a biomarker for cancer, but may be useful as a marker for cancer cachexia. Some single nucleotide polymorphisms in the ghrelin and GHSR genes have shown associations with cancer risk; however, larger studies are required. Ghrelin regulates processes associated with cancer, including cell proliferation, apoptosis, cell migration, cell invasion, inflammation, and angiogenesis; however, the role of ghrelin in cancer is currently unclear. Ghrelin has predominantly antiinflammatory effects and may play a role in protecting against cancer-related inflammation. Ghrelin and its analogs show promise as treatments for cancer-related cachexia. Further studies using in vivo models are required to determine whether ghrelin has a role in cancer progression.

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Background: High levels of distress and need for self-care information by patients commencing chemotherapy suggest that current prechemotherapy education is suboptimal. We conducted a randomised, controlled trial of a prechemotherapy education intervention (ChemoEd) to assess impact on patient distress, treatment-related concerns, and the prevalence and severity of and bother caused by six chemotherapy side-effects. Patients and methods: One hundred and ninety-two breast, gastrointestinal, and haematologic cancer patients were recruited before the trial closing prematurely (original target 352). ChemoEd patients received a DVD, question-prompt list, self-care information, an education consultation ≥24 h before first treatment (intervention 1), telephone follow-up 48 h after first treatment (intervention 2), and a face-to-face review immediately before second treatment (intervention 3). Patient outcomes were measured at baseline (T1: pre-education) and immediately preceding treatment cycles 1 (T2) and 3 (T3). Results: ChemoEd did not significantly reduce patient distress. However, a significant decrease in sensory/psychological (P = 0.027) and procedural (P = 0.03) concerns, as well as prevalence and severity of and bother due to vomiting (all P = 0.001), were observed at T3. In addition, subgroup analysis of patients with elevated distress at T1 indicated a significant decrease (P = 0.035) at T2 but not at T3 (P = 0.055) in ChemoEd patients. Conclusions: ChemoEd holds promise to improve patient treatment-related concerns and some physical/psychological outcomes; however, further research is required on more diverse patient populations to ensure generalisability.

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A long-running issue in appetite research concerns the influence of energy expenditure on energy intake. More than 50 years ago, Otto G. Edholm proposed that "the differences between the intakes of food [of individuals] must originate in differences in the expenditure of energy". However, a relationship between energy expenditure and energy intake within any one day could not be found, although there was a correlation over 2 weeks. This issue was never resolved before interest in integrative biology was replaced by molecular biochemistry. Using a psychobiological approach, we have studied appetite control in an energy balance framework using a multi-level experimental system on a single cohort of overweight and obese human subjects. This has disclosed relationships between variables in the domains of body composition [fat-free mass (FFM), fat mass (FM)], metabolism, gastrointestinal hormones, hunger and energy intake. In this Commentary, we review our own and other data, and discuss a new formulation whereby appetite control and energy intake are regulated by energy expenditure. Specifically, we propose that FFM (the largest contributor to resting metabolic rate), but not body mass index or FM, is closely associated with self-determined meal size and daily energy intake. This formulation has implications for understanding weight regulation and the management of obesity.

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Cell invasion, characterised by moving fronts of cells, is an essential aspect of development, repair and disease. Typically, mathematical models of cell invasion are based on the Fisher–Kolmogorov equation. These traditional parabolic models can not be used to represent experimental measurements of individual cell velocities within the invading population since they imply that information propagates with infinite speed. To overcome this limitation we study combined cell motility and proliferation based on a velocity–jump process where information propagates with finite speed. The model treats the total population of cells as two interacting subpopulations: a subpopulation of left–moving cells, $L(x,t)$, and a subpopulation of right–moving cells, $R(x,t)$. This leads to a system of hyperbolic partial differential equations that includes a turning rate, $\Lambda \ge 0$, describing the rate at which individuals in the population change direction of movement. We present exact travelling wave solutions of the system of partial differential equations for the special case where $\Lambda = 0$ and in the limit that $\Lambda \to \infty$. For intermediate turning rates, $0 < \Lambda < \infty$, we analyse the travelling waves using the phase plane and we demonstrate a transition from smooth monotone travelling waves to smooth nonmonotone travelling waves as $\Lambda$ decreases through a critical value $\Lambda_{crit}$. We conclude by providing a qualitative comparison between the travelling wave solutions of our model and experimental observations of cell invasion. This comparison indicates that the small $\Lambda$ limit produces results that are consistent with experimental observations.

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Quantitative imaging methods to analyze cell migration assays are not standardized. Here we present a suite of two–dimensional barrier assays describing the collective spreading of an initially–confined population of 3T3 fibroblast cells. To quantify the motility rate we apply two different automatic image detection methods to locate the position of the leading edge of the spreading population after 24, 48 and 72 hours. These results are compared with a manual edge detection method where we systematically vary the detection threshold. Our results indicate that the observed spreading rates are very sensitive to the choice of image analysis tools and we show that a standard measure of cell migration can vary by as much as 25% for the same experimental images depending on the details of the image analysis tools. Our results imply that it is very difficult, if not impossible, to meaningfully compare previously published measures of cell migration since previous results have been obtained using different image analysis techniques and the details of these techniques are not always reported. Using a mathematical model, we provide a physical interpretation of our edge detection results. The physical interpretation is important since edge detection algorithms alone do not specify any physical measure, or physical definition, of the leading edge of the spreading population. Our modeling indicates that variations in the image threshold parameter correspond to a consistent variation in the local cell density. This means that varying the threshold parameter is equivalent to varying the location of the leading edge in the range of approximately 1–5% of the maximum cell density.

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Cell migration is a behaviour critical to many key biological effects, including wound healing, cancerous cell invasion and morphogenesis, the development of an organism from an embryo. However, given that each of these situations is distinctly different and cells are extremely complicated biological objects, interest lies in more basic experiments which seek to remove conflating factors and present a less complex environment within which cell migration can be experimentally examined. These include in vitro studies like the scratch assay or circle migration assay, and ex vivo studies like the colonisation of the hindgut by neural crest cells. The reduced complexity of these experiments also makes them much more enticing as problems to mathematically model, like done here. The primary goal of the mathematical models used in this thesis is to shed light on which cellular behaviours work to generate the travelling waves of invasion observed in these experiments, and to explore how variations in these behaviours can potentially predict differences in this invasive pattern which are experimentally observed when cell types or chemical environment are changed. Relevant literature has already identified the difficulty of distinguishing between these behaviours when using traditional mathematical biology techniques operating on a macroscopic scale, and so here a sophisticated individual-cell-level model, an extension of the Cellular Potts Model (CPM), is been constructed and used to model a scratch assay experiment. This model includes a novel mechanism for dealing with cell proliferations that allowed for the differing properties of quiescent and proliferative cells to be implemented into their behaviour. This model is considered both for its predictive power and used to make comparisons with the travelling waves which result in more traditional macroscopic simulations. These comparisons demonstrate a surprising amount of agreement between the two modelling frameworks, and suggest further novel modifications to the CPM that would allow it to better model cell migration. Considerations of the model’s behaviour are used to argue that the dominant effect governing cell migration (random motility or signal-driven taxis) likely depends on the sort of invasion demonstrated by cells, as easily seen by microscopic photography. Additionally, a scratch assay simulated on a non-homogeneous domain consisting of a ’fast’ and ’slow’ region is also used to further differentiate between these different potential cell motility behaviours. A heterogeneous domain is a novel situation which has not been considered mathematically in this context, nor has it been constructed experimentally to the best of the candidate’s knowledge. Thus this problem serves as a thought experiment used to test the conclusions arising from the simulations on homogeneous domains, and to suggest what might be observed should this non-homogeneous assay situation be experimentally realised. Non-intuitive cell invasion patterns are predicted for diffusely-invading cells which respond to a cell-consumed signal or nutrient, contrasted with rather expected behaviour in the case of random-motility-driven invasion. The potential experimental observation of these behaviours is demonstrated by the individual-cell-level model used in this thesis, which does agree with the PDE model in predicting these unexpected invasion patterns. In the interest of examining such a case of a non-homogeneous domain experimentally, some brief suggestion is made as to how this could be achieved.

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Invasion waves of cells play an important role in development, disease and repair. Standard discrete models of such processes typically involve simulating cell motility, cell proliferation and cell-to-cell crowding effects in a lattice-based framework. The continuum-limit description is often given by a reaction–diffusion equation that is related to the Fisher–Kolmogorov equation. One of the limitations of a standard lattice-based approach is that real cells move and proliferate in continuous space and are not restricted to a predefined lattice structure. We present a lattice-free model of cell motility and proliferation, with cell-to-cell crowding effects, and we use the model to replicate invasion wave-type behaviour. The continuum-limit description of the discrete model is a reaction–diffusion equation with a proliferation term that is different from lattice-based models. Comparing lattice based and lattice-free simulations indicates that both models lead to invasion fronts that are similar at the leading edge, where the cell density is low. Conversely, the two models make different predictions in the high density region of the domain, well behind the leading edge. We analyse the continuum-limit description of the lattice based and lattice-free models to show that both give rise to invasion wave type solutions that move with the same speed but have very different shapes. We explore the significance of these differences by calibrating the parameters in the standard Fisher–Kolmogorov equation using data from the lattice-free model. We conclude that estimating parameters using this kind of standard procedure can produce misleading results.

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Cell trajectory data is often reported in the experimental cell biology literature to distinguish between different types of cell migration. Unfortunately, there is no accepted protocol for designing or interpreting such experiments and this makes it difficult to quantitatively compare different published data sets and to understand how changes in experimental design influence our ability to interpret different experiments. Here, we use an individual based mathematical model to simulate the key features of a cell trajectory experiment. This shows that our ability to correctly interpret trajectory data is extremely sensitive to the geometry and timing of the experiment, the degree of motility bias and the number of experimental replicates. We show that cell trajectory experiments produce data that is most reliable when the experiment is performed in a quasi 1D geometry with a large number of identically{prepared experiments conducted over a relatively short time interval rather than few trajectories recorded over particularly long time intervals.

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BACKGROUND AND AIMS: Crohn's disease (CD) is an inflammatory bowel disease (IBD) caused by a combination of genetic, clinical, and environmental factors. Identification of CD patients at high risk of requiring surgery may assist clinicians to decide on a top-down or step-up treatment approach. METHODS: We conducted a retrospective case-control analysis of a population-based cohort of 503 CD patients. A regression-based data reduction approach was used to systematically analyse 63 genomic, clinical and environmental factors for association with IBD-related surgery as the primary outcome variable. RESULTS: A multi-factor model was identified that yielded the highest predictive accuracy for need for surgery. The factors included in the model were the NOD2 genotype (OR = 1.607, P = 2.3 × 10(-5)), having ever had perianal disease (OR = 2.847, P = 4 × 10(-6)), being post-diagnosis smokers (OR = 6.312, P = 7.4 × 10(-3)), being an ex-smoker at diagnosis (OR = 2.405, P = 1.1 × 10(-3)) and age (OR = 1.012, P = 4.4 × 10(-3)). Diagnostic testing for this multi-factor model produced an area under the curve of 0.681 (P = 1 × 10(-4)) and an odds ratio of 3.169, (95 % CI P = 1 × 10(-4)) which was higher than any factor considered independently. CONCLUSIONS: The results of this study require validation in other populations but represent a step forward in the development of more accurate prognostic tests for clinicians to prescribe the most optimal treatment approach for complicated CD patients.

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Skin cancer is one of the most commonly occurring cancer types, with substantial social, physical, and financial burdens on both individuals and societies. Although the role of UV light in initiating skin cancer development has been well characterized, genetic studies continue to show that predisposing factors can influence an individual's susceptibility to skin cancer and response to treatment. In the future, it is hoped that genetic profiles, comprising a number of genetic markers collectively involved in skin cancer susceptibility and response to treatment or prognosis, will aid in more accurately informing practitioners' choices of treatment. Individualized treatment based on these profiles has the potential to increase the efficacy of treatments, saving both time and money for the patient by avoiding the need for extensive or repeated treatment. Increased treatment responses may in turn prevent recurrence of skin cancers, reducing the burden of this disease on society. Currently existing pharmacogenomic tests, such as those that assess variation in the metabolism of the anticancer drug fluorouracil, have the potential to reduce the toxic effects of anti-tumor drugs used in the treatment of non-melanoma skin cancer (NMSC) by determining individualized appropriate dosage. If the savings generated by reducing adverse events negate the costs of developing these tests, pharmacogenomic testing may increasingly inform personalized NMSC treatment.

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Background & Aims: Peroxisome proliferator-activated receptor (PPAR) γ is a transcription factor, highly expressed in colonic epithelial cells, adipose tissue and macrophages, with an important role in the regulation of inflammatory pathways. The common PPARγ variants C161T and Pro12Ala have recently been associated with Ulcerative Colitis (UC) and an extensive UC phenotype respectively, in a Chinese population. PPARγ Pro12Ala variant homozygotes appear to be protected from the development of Crohn's disease (CD) in European Caucasians. Methods: A case-control study was performed for both variants (CD n=575, UC n=306, Controls n=360) using a polymerase chain reaction (PCR)-restriction fragment length polymorphism analysis in an Australian IBD cohort. A transmission disequilibrium test was also performed using CD trios for the PPARγ C161T variant. Genotype-phenotype analyses were also undertaken. Results: There was no significant difference in genotype distribution data or allele frequency between CD and UC patients and controls. There was no difference in allele transmission for the C161T variant. No significant relationship between the variants and disease location was observed. Conclusions: We were unable to replicate in a Caucasian cohort the recent association between PPARγ C161T and UC or between PPARγ Pro12Ala and an extensive UC phenotype in a Chinese population. There are significant ethnic differences in genetic susceptibility to IBD and its phenotypic expression.

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The ubiquitous chemical messenger molecule nitric oxide (NO) has been implicated in a diverse range of biological activities including neurotransmission, smooth muscle motility and mediation of nociception. Endogenous synthesis of NO by the neuronal isoform of the nitric oxide synthase gene family has an essential role within the central and peripheral nervous systems in addition to the autonomic innervation of cerebral blood vessels. To investigate the potential role of NO and more specifically the neuronal nitric oxide synthase (nNOS) gene in migraine susceptibility, we investigated two microsatellite repeat variants residing within the 5′ and 3′ regions of the nNOS gene. Population genomic evaluation of the two nNOS repeat variants indicated significant linkage disequilibrium between the two loci. Z-DNA conformational sequence structures within the 5′ region of the nNOS gene have the potential to enhance or repress gene promoter activity. We suggest that genetic analysis of this 5′ repeat variant is the more functional variant expressing gene wide information that could affect endogenous NO synthesis and potentially result in diseased states. However, no association with migraine (with or without aura) was seen in our extensive case-control cohort (n = 579 affected with matched controls), when both the 5′ and 3′ genetic variants were investigated.

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It has been reported that poor nutritional status, in the form of weight loss and resulting body mass index (BMI) changes, is an issue in people with Parkinson's disease (PWP). The symptoms resulting from Parkinson's disease (PD) and the side effects of PD medication have been implicated in the aetiology of nutritional decline. However, the evidence on which these claims are based is, on one hand, contradictory, and on the other, restricted primarily to otherwise healthy PWP. Despite the claims that PWP suffer from poor nutritional status, evidence is lacking to inform nutrition-related care for the management of malnutrition in PWP. The aims of this thesis were to better quantify the extent of poor nutritional status in PWP, determine the important factors differentiating the well-nourished from the malnourished and evaluate the effectiveness of an individualised nutrition intervention on nutritional status. Phase DBS: Nutritional status in people with Parkinson's disease scheduled for deep-brain stimulation surgery The pre-operative rate of malnutrition in a convenience sample of people with Parkinson's disease (PWP) scheduled for deep-brain stimulation (DBS) surgery was determined. Poorly controlled PD symptoms may result in a higher risk of malnutrition in this sub-group of PWP. Fifteen patients (11 male, median age 68.0 (42.0 – 78.0) years, median PD duration 6.75 (0.5 – 24.0) years) participated and data were collected during hospital admission for the DBS surgery. The scored PG-SGA was used to assess nutritional status, anthropometric measures (weight, height, mid-arm circumference, waist circumference, body mass index (BMI)) were taken, and body composition was measured using bioelectrical impedance spectroscopy (BIS). Six (40%) of the participants were malnourished (SGA-B) while 53% reported significant weight loss following diagnosis. BMI was significantly different between SGA-A and SGA-B (25.6 vs 23.0kg/m 2, p<.05). There were no differences in any other variables, including PG-SGA score and the presence of non-motor symptoms. The conclusion was that malnutrition in this group is higher than that in other studies reporting malnutrition in PWP, and it is under-recognised. As poorer surgical outcomes are associated with poorer pre-operative nutritional status in other surgeries, it might be beneficial to identify patients at nutritional risk prior to surgery so that appropriate nutrition interventions can be implemented. Phase I: Nutritional status in community-dwelling adults with Parkinson's disease The rate of malnutrition in community-dwelling adults (>18 years) with Parkinson's disease was determined. One hundred twenty-five PWP (74 male, median age 70.0 (35.0 – 92.0) years, median PD duration 6.0 (0.0 – 31.0) years) participated. The scored PG-SGA was used to assess nutritional status, anthropometric measures (weight, height, mid-arm circumference (MAC), calf circumference, waist circumference, body mass index (BMI)) were taken. Nineteen (15%) of the participants were malnourished (SGA-B). All anthropometric indices were significantly different between SGA-A and SGA-B (BMI 25.9 vs 20.0kg/m2; MAC 29.1 – 25.5cm; waist circumference 95.5 vs 82.5cm; calf circumference 36.5 vs 32.5cm; all p<.05). The PG-SGA score was also significantly lower in the malnourished (2 vs 8, p<.05). The nutrition impact symptoms which differentiated between well-nourished and malnourished were no appetite, constipation, diarrhoea, problems swallowing and feel full quickly. This study concluded that malnutrition in community-dwelling PWP is higher than that documented in community-dwelling elderly (2 – 11%), yet is likely to be under-recognised. Nutrition impact symptoms play a role in reduced intake. Appropriate screening and referral processes should be established for early detection of those at risk. Phase I: Nutrition assessment tools in people with Parkinson's disease There are a number of validated and reliable nutrition screening and assessment tools available for use. None of these tools have been evaluated in PWP. In the sample described above, the use of the World Health Organisation (WHO) cut-off (≤18.5kg/m2), age-specific BMI cut-offs (≤18.5kg/m2 for under 65 years, ≤23.5kg/m2 for 65 years and older) and the revised Mini-Nutritional Assessment short form (MNA-SF) were evaluated as nutrition screening tools. The PG-SGA (including the SGA classification) and the MNA full form were evaluated as nutrition assessment tools using the SGA classification as the gold standard. For screening, the MNA-SF performed the best with sensitivity (Sn) of 94.7% and specificity (Sp) of 78.3%. For assessment, the PG-SGA with a cut-off score of 4 (Sn 100%, Sp 69.8%) performed better than the MNA (Sn 84.2%, Sp 87.7%). As the MNA has been recommended more for use as a nutrition screening tool, the MNA-SF might be more appropriate and take less time to complete. The PG-SGA might be useful to inform and monitor nutrition interventions. Phase I: Predictors of poor nutritional status in people with Parkinson's disease A number of assessments were conducted as part of the Phase I research, including those for the severity of PD motor symptoms, cognitive function, depression, anxiety, non-motor symptoms, constipation, freezing of gait and the ability to carry out activities of daily living. A higher score in all of these assessments indicates greater impairment. In addition, information about medical conditions, medications, age, age at PD diagnosis and living situation was collected. These were compared between those classified as SGA-A and as SGA-B. Regression analysis was used to identify which factors were predictive of malnutrition (SGA-B). Differences between the groups included disease severity (4% more severe SGA-A vs 21% SGA-B, p<.05), activities of daily living score (13 SGA-A vs 18 SGA-B, p<.05), depressive symptom score (8 SGA-A vs 14 SGA-B, p<.05) and gastrointestinal symptoms (4 SGA-A vs 6 SGA-B, p<.05). Significant predictors of malnutrition according to SGA were age at diagnosis (OR 1.09, 95% CI 1.01 – 1.18), amount of dopaminergic medication per kg body weight (mg/kg) (OR 1.17, 95% CI 1.04 – 1.31), more severe motor symptoms (OR 1.10, 95% CI 1.02 – 1.19), less anxiety (OR 0.90, 95% CI 0.82 – 0.98) and more depressive symptoms (OR 1.23, 95% CI 1.07 – 1.41). Significant predictors of a higher PG-SGA score included living alone (β=0.14, 95% CI 0.01 – 0.26), more depressive symptoms (β=0.02, 95% CI 0.01 – 0.02) and more severe motor symptoms (OR 0.01, 95% CI 0.01 – 0.02). More severe disease is associated with malnutrition, and this may be compounded by lack of social support. Phase II: Nutrition intervention Nineteen of the people identified in Phase I as requiring nutrition support were included in Phase II, in which a nutrition intervention was conducted. Nine participants were in the standard care group (SC), which received an information sheet only, and the other 10 participants were in the intervention group (INT), which received individualised nutrition information and weekly follow-up. INT gained 2.2% of starting body weight over the 12 week intervention period resulting in significant increases in weight, BMI, mid-arm circumference and waist circumference. The SC group gained 1% of starting weight over the 12 weeks which did not result in any significant changes in anthropometric indices. Energy and protein intake (18.3kJ/kg vs 3.8kJ/kg and 0.3g/kg vs 0.15g/kg) increased in both groups. The increase in protein intake was only significant in the SC group. The changes in intake, when compared between the groups, were no different. There were no significant changes in any motor or non-motor symptoms or in "off" times or dyskinesias in either group. Aspects of quality of life improved over the 12 weeks as well, especially emotional well-being. This thesis makes a significant contribution to the evidence base for the presence of malnutrition in Parkinson's disease as well as for the identification of those who would potentially benefit from nutrition screening and assessment. The nutrition intervention demonstrated that a traditional high protein, high energy approach to the management of malnutrition resulted in improved nutritional status and anthropometric indices with no effect on the presence of Parkinson's disease symptoms and a positive effect on quality of life.

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Endometrial cancer is one of the most common female diseases in developed nations and is the most commonly diagnosed gynaecological cancer in Australia. The disease is commonly classified by histology: endometrioid or non-endometrioid endometrial cancer. While non-endometrioid endometrial cancers are accepted to be high-grade, aggressive cancers, endometrioid cancers (comprising 80% of all endometrial cancers diagnosed) generally carry a favourable patient prognosis. However, endometrioid endometrial cancer patients endure significant morbidity due to surgery and radiotherapy used for disease treatment, and patients with recurrent disease have a 5-year survival rate of less than 50%. Genetic analysis of women with endometrial cancer could uncover novel markers associated with disease risk and/or prognosis, which could then be used to identify women at high risk and for the use of specialised treatments. Proteases are widely accepted to play an important role in the development and progression of cancer. This PhD project hypothesised that SNPs from two protease gene families, the matrix metalloproteases (MMPs, including their tissue inhibitors, TIMPs) and the tissue kallikrein-related peptidases (KLKs) would be associated with endometrial cancer susceptibility and/or prognosis. In the first part of this study, optimisation of the genotyping techniques was performed. Results from previously published endometrial cancer genetic association studies were attempted to be validated in a large, multicentre replication set (maximum cases n = 2,888, controls n = 4,483, 3 studies). The rs11224561 progesterone receptor SNP (PGR, A/G) was observed to be associated with increased endometrial cancer risk (per A allele OR 1.31, 95% CI 1.12-1.53; p-trend = 0.001), a result which was initially reported among a Chinese sample set. Previously reported associations for the remaining 8 SNPs investigated for this section of the PhD study were not confirmed, thereby reinforcing the importance of validation of genetic association studies. To examine the effect of SNPs from the MMP and KLK families on endometrial cancer risk, we selected the most significantly associated MMP and KLK SNPs from genome-wide association study analysis (GWAS) to be genotyped in the GWAS replication set (cases n = 4,725, controls n = 9,803, 13 studies). The significance of the MMP24 rs932562 SNP was unchanged after incorporation of the stage 2 samples (Stage 1 per allele OR 1.18, p = 0.002; Combined Stage 1 and 2 OR 1.09, p = 0.002). The rs10426 SNP, located 3' to KLK10 was predicted by bioinformatic analysis to effect miRNA binding. This SNP was observed in the GWAS stage 1 result to exhibit a recessive effect on endometrial cancer risk, a result which was not validated in the stage 2 sample set (Stage 1 OR 1.44, p = 0.007; Combined Stage 1 and 2 OR 1.14, p = 0.08). Investigation of the regions imputed surrounding the MMP, TIMP and KLK genes did not reveal any significant targets for further analysis. Analysis of the case data from the endometrial cancer GWAS to identify genetic variation associated with cancer grade did not reveal SNPs from the MMP, TIMP or KLK genes to be statistically significant. However, the representation of SNPs from the MMP, TIMP and KLK families by the GWAS genotyping platform used in this PhD project was examined and observed to be very low, with the genetic variation of four genes (MMP23A, MMP23B, MMP28 and TIMP1) not captured at all by this technique. This suggests that comprehensive candidate gene association studies will be required to assess the role of SNPs from these genes with endometrial cancer risk and prognosis. Meta-analysis of gene expression microarray datasets curated as part of this PhD study identified a number of MMP, TIMP and KLK genes to display differential expression by endometrial cancer status (MMP2, MMP10, MMP11, MMP13, MMP19, MMP25 and KLK1) and histology (MMP2, MMP11, MMP12, MMP26, MMP28, TIMP2, TIMP3, KLK6, KLK7, KLK11 and KLK12). In light of these findings these genes should be prioritised for future targeted genetic association studies. Two SNPs located 43.5 Mb apart on chromosome 15 were observed from the GWAS analysis to be associated with increased endometrial cancer grade, results that were validated in silico in two independent datasets. One of these SNPs, rs8035725 is located in the 5' untranslated region of a MYC promoter binding protein DENND4A (Stage 1 OR 1.15, p = 9.85 x 10P -5 P, combined Stage 1 and in silico validation OR 1.13, p = 5.24 x 10P -6 P). This SNP has previously been reported to alter the expression of PTPLAD1, a gene involved in the synthesis of very long fatty acid chains and in the Rac1 signaling pathway. Meta-analysis of gene expression microarray data found PTPLAD1 to display increased expression in the aggressive non-endometrioid histology compared with endometrioid endometrial cancer, suggesting that the causal SNP underlying the observed genetic association may influence expression of this gene. Neither rs8035725 nor significant SNPs identified by imputation were predicted bioinformatically to affect transcription factor binding sites, indicating that further studies are required to assess their potential effect on other regulatory elements. The other grade- associated SNP, rs6606792, is located upstream of an inferred pseudogene, ELMO2P1 (Stage 1 OR 1.12, p = 5 x 10P -5 P; combined Stage 1 and in silico validation OR 1.09, p = 3.56 x 10P -5 P). Imputation of the ±1 Mb region surrounding this SNP revealed a cluster of significantly associated variants which are predicted to abolish various transcription factor binding sites, and would be expected to decrease gene expression. ELMO2P1 was not included on the microarray platforms collected for this PhD, and so its expression could not be investigated. However, the high sequence homology of ELMO2P1 with ELMO2, a gene important to cell motility, indicates that ELMO2 could be the parent gene for ELMO2P1 and as such, ELMO2P1 could function to regulate the expression of ELMO2. Increased expression of ELMO2 was seen to be associated with increasing endometrial cancer grade, as well as with aggressive endometrial cancer histological subtypes by microarray meta-analysis. Thus, it is hypothesised that SNPs in linkage disequilibrium with rs6606792 decrease the transcription of ELMO2P1, reducing the regulatory effect of ELMO2P1 on ELMO2 expression. Consequently, ELMO2 expression is increased, cell motility is enhanced leading to an aggressive endometrial cancer phenotype. In summary, these findings have identified several areas of research for further study. The results presented in this thesis provide evidence that a SNP in PGR is associated with risk of developing endometrial cancer. This PhD study also reports two independent loci on chromosome 15 to be associated with increased endometrial cancer grade, and furthermore, genes associated with these SNPs to be differentially expressed according in aggressive subtypes and/or by grade. The studies reported in this thesis support the need for comprehensive SNP association studies on prioritised MMP, TIMP and KLK genes in large sample sets. Until these studies are performed, the role of MMP, TIMP and KLK genetic variation remains unclear. Overall, this PhD study has contributed to the understanding of genetic variation involvement in endometrial cancer susceptibility and prognosis. Importantly, the genetic regions highlighted in this study could lead to the identification of novel gene targets to better understand the biology of endometrial cancer and also aid in the development of therapeutics directed at treating this disease.