634 resultados para Multiple testing
Resumo:
To identify multiple sclerosis (MS) susceptibility loci, we conducted a genome-wide association study (GWAS) in 1,618 cases and used shared data for 3,413 controls. We performed replication in an independent set of 2,256 cases and 2,310 controls, for a total of 3,874 cases and 5,723 controls. We identified risk-associated SNPs on chromosome 12q13-14 (rs703842, P = 5.4 x 10(-11); rs10876994, P = 2.7 x 10(-10); rs12368653, P = 1.0 x 10(-7)) and upstream of CD40 on chromosome 20q13 (rs6074022, P = 1.3 x 10(-7); rs1569723, P = 2.9 x 10(-7)). Both loci are also associated with other autoimmune diseases. We also replicated several known MS associations (HLA-DR15, P = 7.0 x 10(-184); CD58, P = 9.6 x 10(-8); EVI5-RPL5, P = 2.5 x 10(-6); IL2RA, P = 7.4 x 10(-6); CLEC16A, P = 1.1 x 10(-4); IL7R, P = 1.3 x 10(-3); TYK2, P = 3.5 x 10(-3)) and observed a statistical interaction between SNPs in EVI5-RPL5 and HLA-DR15 (P = 0.001).
Resumo:
Background Chaperonin 10 (Cpn10) is a mitochondrial molecule involved in protein folding. The aim of this study was to determine the safety profile of Cpn10 in patients with multiple sclerosis (MS). Methods A total of 50 patients with relapse-remitting or secondary progressive MS were intravenously administered 5 mg or 10 mg of Cpn10 weekly for 12 weeks in a double-blind, randomized, placebo controlled, phase II trial. Clinical reviews, including Expanded Disability Status Scale and magnetic resonance imaging (MRI) with Gadolinium, were undertaken every 4 weeks. Stimulation of patient peripheral blood mononuclear cells with lipopolysaccharide ex vivo was used to measure the in vivo activity of Cpn10. Results No significant differences in the frequency of adverse events were seen between treatment and placebo arms. Leukocytes from both groups of Cpn10-treated patients produced significantly lower levels of critical proinflammatory cytokines. A trend toward improvement in new Gadolinium enhancing lesions on MRI was observed, but this difference was not statistically significant. No differences in clinical outcome measures were seen. Conclusions Cpn10 is safe and well tolerated when administered to patients with MS for 3 months, however, a further extended phase II study primarily focused on efficacy is warranted.
Resumo:
OBJECTIVE: To examine a polymorphism within the 3' untranslated region of the leukemia inhibitory factor gene for an association with multiple sclerosis within an Australian case-control population. METHODS: A test group of 121 unrelated multiple sclerosis patients, of Caucasian origin, and 121 controls, matched for ethnicity, sex and age (+/-5 years) were included in the study. The LIF 3' UTR StuI polymorphism was genotyped by restriction fragment length polymorphism analysis. Statistical analysis of genotype and allele frequencies included Hardy-Weinberg law and conventional contingency table analysis incorporating the standard chi-squared test for independence. RESULTS: Allelic and genotype frequencies did not demonstrate a significant association between the case and control groups for the tested LIF 3' UTR StuI polymorphism. CONCLUSION: The results indicate that the LIF 3' UTR StuI polymorphism is not associated with multiple sclerosis, however we cannot exclude the hypothesis that other polymorphic alleles of LIF could be implicated in MS susceptibility.
Resumo:
Multiple Sclerosis (MS) is a central nervous system (CNS) chronic inflammatory demyelinating disease leading to various neurological disabilities. The disorder is more prevalent for women with a ratio of 3:2 female to male. Objectives: To investigate variation within the estrogen receptor 1 (ESR1) polymorphism gene in an Australian MS case-control population using two intragenic restriction fragment length polymorphisms; the G594A located in exon 8 detected with the BtgI restriction enzyme and T938C located in intron 1, detected with PvuII. One hundred and ten Australian MS patients were studied, with patients classified clinically as Relapsing Remitting MS (RR-MS), Secondary Progressive MS (SP-MS) or Primary Progressive MS (PP-MS). Also, 110 age, sex and ethnicity matched controls were investigated as a comparative group. No significant difference in the allelic distribution frequency was found between the case and control groups for the ESR1 PvuII (P = 0.50) and Btg1 (P = 0.45) marker. Our results do not support a role for these two ESR1 markers in multiple sclerosis susceptibility, however other markers within ESR1 should not be excluded for potential involvement in the disorder.
Resumo:
Multiple sclerosis (MS) is a serious neurological disorder affecting young Caucasian individuals, usually with an age of onset at 18 to 40 years old. Females account for approximately 60x of MS cases and the manifestation and course of the disease is highly variable from patient to patient. The disorder is characterised by the development of plaques within the central nervous system (CNS). Many gene expression studies have been undertaken to look at the specific patterns of gene transcript levels in MS. Human tissues and experimental mice were used in these gene-profiling studies and a very valuable and interesting set of data has resulted from these various expression studies. In general, genes showing variable expression include mainly immunological and inflammatory genes, stress and antioxidant genes, as well as metabolic and central nervous system markers. Of particular interest are a number of genes localised to susceptible loci previously shown to be in linkage with MS. However due to the clinical complexity of the disease, the heterogeneity of the tissues used in expression studies, as well as the variable DNA chips/membranes used for the gene profiling, it is difficult to interpret the available information. Although this information is essential for the understanding of the pathogenesis of MS, it is difficult to decipher and define the gene pathways involved in the disorder. Experiments in gene expression profiling in MS have been numerous and lists of candidates are now available for analysis. Researchers have investigated gene expression in peripheral mononuclear white blood cells (PBMCs), in MS animal models Experimental Allergic Encephalomyelitis (EAE) and post mortem MS brain tissues. This review will focus on the results of these studies.
Resumo:
Multiple sclerosis (MS) is a chronic neurological disease characterized by central nervous system (CNS) inflammation and demyelination. The C677T substitution variant in the methylenetetrahydrofolate reductase (MTHFR) gene has been associated with increased levels of circulating homocysteine and is a mild risk factor for vascular disease. Higher blood levels of homocysteine have also been reported in MS. Thus, the C677T mutation of the MTHFR gene may influence MS susceptibility. Noradrenaline, a neurotransmitter believed to play an immunosupressive role in neuroinflammatory disorders, is catabolized by catechol-O-methyl transferase (COMT). The COMT G158A substitution results in a three- to four-fold decreased activity of the COMT enzyme, which may influence CNS synaptic catecholamine breakdown and could also play a role in MS inflammation. We tested DNA from Australian MS patients and unaffected control subjects, matched for gender, age and ethnicity. Specifically, we genotyped the MTHFR C677T and the COMT G158A mutations. Genotype distributions showed that the homozygous mutant MTHFR genotype (T/T) and the COMT (H/H) genotype were slightly over-represented in the MS group (16% versus 11% and 24% versus 19%, respectively), but both variations failed to reach statistical significance (P=0.15 and P=0.32, respectively). Hence, results from the present study do not support a major role for either functional gene mutation in MS susceptibility.
Resumo:
In South and Southeast Asia, postharvest loss causes material waste of up to 66% in fruits and vegetables, 30% in oilseeds and pulses, and 49% in roots and tubers. The efficiency of postharvest equipment directly affects industrial-scale food production. To enhance current processing methods and devices, it is essential to analyze the responses of food materials under loading operations. Food materials undergo different types of mechanical loading during postharvest and processing stages. Therefore, it is important to determine the properties of these materials under different types of loads, such as tensile, compression, and indentation. This study presents a comprehensive analysis of the available literature on the tensile properties of different food samples. The aim of this review was to categorize the available methods of tensile testing for agricultural crops and food materials to investigate an appropriate sample size and tensile test method. The results were then applied to perform tensile tests on pumpkin flesh and peel samples, in particular on arc-sided samples at a constant loading rate of 20 mm min-1. The results showed the maximum tensile stress of pumpkin flesh and peel samples to be 0.535 and 1.45 MPa, respectively. The elastic modulus of the flesh and peel samples was 6.82 and 25.2 MPa, respectively, while the failure modulus values were 14.51 and 30.88 MPa, respectively. The results of the tensile tests were also used to develop a finite element model of mechanical peeling of tough-skinned vegetables. However, to study the effects of deformation rate, moisture content, and texture of the tissue on the tensile responses of food materials, more investigation needs to be done in the future.
Resumo:
In our laboratory, we have developed methods in real-time detection and quantitative-polymerase chain reaction (Q-PCR) to analyse the relative levels of gene expression in post mortem brain tissues. We have then applied this method to examine differences in gene activity between normal white matter (NWM) and plaque tissue from multiple sclerosis (MS) patients. Genes were selected based on their association with pathology and through identification by previously conducted global gene expression analysis. Plaque tissue was obtained from secondary progressive (SP) patients displaying chronic active, as well as acute pathologies; while NWM from the same location was obtained from age- and sex-matched controls (normal patients). In this study, we used both SYBR Green I supplementation and commercially available mixes to assess both comparative and absolute levels of gene activity. The results of both methods compared favourably for four of the five genes examined (P < 0.05, Pearsons), while differences in gene expression between chronic active and acute pathologies were also identified. For example, a >50-fold increase in osteopontin (Spp1) and inositol 1-4-5 phosphate 3 kinase B (Itpkb) levels in acute plaques contrasted with the 5-fold or less increase in chronic active plaques (P < 0.05, unpaired t test). By contrast, there was no significant difference in the levels of the MS marker and calcium-dependent protease (Calpain, Capns1) in MS plaque tissue. In summary, Q-PCR analysis using SYBR Green I has allowed us to economically obtain what may be clinically significant information from small amounts of the CNS, providing an opportunity for further clinical investigations.
Resumo:
Multiple Sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system (CNS) resulting in accumulating neurological disability. The disorder is more prevalent at higher latitudes. To investigate VDR gene variation using three intragenic restriction fragment length polymorphisms (Apa I, Taq I and Fok I) in an Australian MS case-control population. One hundred and four Australian MS patients were studied with patients classified clinically as Relapsing Remitting MS (RR-MS), Secondary Progressive MS (SP-MS) or Primary Progressive MS (PP-MS). Also, 104 age-, sex-, and ethnicity-matched controls were investigated as a comparative group. Our results show a significant difference of genotype distribution frequency between the case and control groups for the functional exon 9 VDR marker Taq I (p(Gen) = 0.016) and interestingly, a stronger difference for the allelic frequency (p(All) = 0.0072). The Apa I alleles were also found to be associated with MS (p(All) = 0.04) but genotype frequencies were not significantly different from controls (p(Gen) = 0.1). The Taq and Apa variants are in very strong and significant linkage disequilibrium (D' = 0.96, P < 0.0001). The genotypic associations are strongest for the progressive forms of MS (SP-MS and PP-MS). Our results support a role for the VDR gene increasing the risk of developing multiple sclerosis, particularly the progressive clinical subtypes of MS.
Resumo:
Multiple Sclerosis (MS) is a chronic neurological disease characterized by demyelination associated with infiltrating white blood cells in the central nervous system (CNS). Nitric oxide synthases (NOS) are a family of enzymes that control the production of nitric oxide. It is possible that neuronal NOS could be involved in MS pathophysiology and hence the nNOS gene is a potential candidate for involvement in disease susceptibility. The aim of this study was to determine whether allelic variation at the nNOS gene locus is associated with MS in an Australian cohort. DNA samples obtained from a Caucasian Australian population affected with MS and an unaffected control population, matched for gender, age and ethnicity, were genotyped for a microsatellite polymorphism in the promoter region of the nNOS gene. Allele frequencies were compared using chi-squared based statistical analyses with significance tested by Monte Carlo simulation. Allelic analysis of MS cases and controls produced a chi-squared value of 5.63 with simulated P = 0.96 (OR(max) = 1.41, 95% CI: 0.926-2.15). Similarly, a Mann-Whitney U analysis gave a non-significant P-value of 0.377 for allele distribution. No differences in allele frequencies were observed for gender or clinical course subtype (P > 0.05). Statistical analysis indicated that there is no association of this nNOS variant and MS and hence the gene does not appear to play a genetically significant role in disease susceptibility.
Resumo:
Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system (CNS) affecting most commonly the Caucasian population. Nitric oxide (NO) is a biological signaling and effector molecule and is especially important during inflammation. Inducible nitric oxide synthase (iNOS) is one of the three enzymes responsible for generating NO. It has been reported that there is an excessive production of NO in MS concordant with an increased expression of iNOS in MS lesions. This study investigated the role of a bi-allelic tetranucleotide polymorphism located in the promoter region of the human iNOS (NOS2A) gene in MS susceptibility. A group of MS patients (n = 101) were genotyped and compared to an age- and sex-matched group of healthy controls (n = 101). The MS group was subdivided into three subtypes, namely relapsing-remitting MS (RR-MS), secondary-progressive MS (SP-MS) and primary-progressive MS (PP-MS). Results of a chi-squared analysis and a Fisher's exact test revealed that allele and genotype distributions between cases and controls were not significantly different for the total population (chi(2) = 3.4, P(genotype) = 0.15; chi(2) = 3.4, P(allele) = 0.082) and for each subtype of MS (P > 0.05). This suggests that there is no direct association of this iNOS gene variant with MS susceptibility.
Resumo:
Multiple sclerosis (MS) is a complex autoimmune disorder of the CNS with both genetic and environmental contributing factors. Clinical symptoms are broadly characterized by initial onset, and progressive debilitating neurological impairment. In this study, RNA from MS chronic active and MS acute lesions was extracted, and compared with patient matched normal white matter by fluorescent cDNA microarray hybridization analysis. This resulted in the identification of 139 genes that were differentially regulated in MS plaque tissue compared to normal tissue. Of these, 69 genes showed a common pattern of expression in the chronic active and acute plaque tissues investigated (Pvalue<0.0001, ρ=0.73, by Spearman's ρ analysis); while 70 transcripts were uniquely differentially expressed (≥1.5-fold) in either acute or chronic active tissues. These results included known markers of MS such as the myelin basic protein (MBP) and glutathione S-transferase (GST) M1, nerve growth factors, such as nerve injury-induced protein 1 (NINJ1), X-ray and excision DNA repair factors (XRCC9 and ERCC5) and X-linked genes such as the ribosomal protein, RPS4X. Primers were then designed for seven array-selected genes, including transferrin (TF), superoxide dismutase 1 (SOD1), glutathione peroxidase 1 (GPX1), GSTP1, crystallin, alpha-B (CRYAB), phosphomannomutase 1 (PMM1) and tubulin β-5 (TBB5), and real time quantitative (Q)-PCR analysis was performed. The results of comparative Q-PCR analysis correlated significantly with those obtained by array analysis (r=0.75, Pvalue<0.01, by Pearson's bivariate correlation). Both chronic active and acute plaques shared the majority of factors identified suggesting that quantitative, rather than gross qualitative differences in gene expression pattern may define the progression from acute to chronic active plaques in MS.
Resumo:
This book provides a general framework for specifying, estimating, and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation, and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.
Resumo:
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.
Resumo:
Automated crowd counting has become an active field of computer vision research in recent years. Existing approaches are scene-specific, as they are designed to operate in the single camera viewpoint that was used to train the system. Real world camera networks often span multiple viewpoints within a facility, including many regions of overlap. This paper proposes a novel scene invariant crowd counting algorithm that is designed to operate across multiple cameras. The approach uses camera calibration to normalise features between viewpoints and to compensate for regions of overlap. This compensation is performed by constructing an 'overlap map' which provides a measure of how much an object at one location is visible within other viewpoints. An investigation into the suitability of various feature types and regression models for scene invariant crowd counting is also conducted. The features investigated include object size, shape, edges and keypoints. The regression models evaluated include neural networks, K-nearest neighbours, linear and Gaussian process regresion. Our experiments demonstrate that accurate crowd counting was achieved across seven benchmark datasets, with optimal performance observed when all features were used and when Gaussian process regression was used. The combination of scene invariance and multi camera crowd counting is evaluated by training the system on footage obtained from the QUT camera network and testing it on three cameras from the PETS 2009 database. Highly accurate crowd counting was observed with a mean relative error of less than 10%. Our approach enables a pre-trained system to be deployed on a new environment without any additional training, bringing the field one step closer toward a 'plug and play' system.