6 resultados para disease mapping

em University of Queensland eSpace - Australia


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We developed an anatomical mapping technique to detect hippocampal and ventricular changes in Alzheimer disease (AD). The resulting maps are sensitive to longitudinal changes in brain structure as the disease progresses. An anatomical surface modeling approach was combined with surface-based statistics to visualize the region and rate of atrophy in serial MRI scans and isolate where these changes link with cognitive decline. Fifty-two high-resolution MRI scans were acquired from 12 AD patients (age: 68.4 +/- 1.9 years) and 14 matched controls (age: 71.4 +/- 0.9 years), each scanned twice (2.1 +/- 0.4 years apart). 3D parametric mesh models of the hippocampus and temporal horns were created in sequential scans and averaged across subjects to identify systematic patterns of atrophy. As an index of radial atrophy, 3D distance fields were generated relating each anatomical surface point to a medial curve threading down the medial axis of each structure. Hippocampal atrophic rates and ventricular expansion were assessed statistically using surface-based permutation testing and were faster in AD than in controls. Using color-coded maps and video sequences, these changes were visualized as they progressed anatomically over time. Additional maps localized regions where atrophic changes linked with cognitive decline. Temporal horn expansion maps were more sensitive to AD progression than maps of hippocampal atrophy, but both maps correlated with clinical deterioration. These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials. (C) 2004 Elsevier Inc. All rights reserved.

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Background: There is increasing evidence that many populations in the developing world are in epidemiologic transition with the subsequent emergence of more affluent disease states. The Heart of Soweto Study will systematically investigate the emergence of heart disease (HD) in a large urban population in South Africa. Methods: Part of the conurbation of Johannesburg, South Africa, Soweto is a predominantly Black African community of I million individuals. During an initial two year period, all individuals presenting to the local Baragwanath Hospital (3500 beds) with any form of HD will be studied. Demographic and diagnostic coding data in those with pre-established HD will form an abbreviated clinical registry of > 12,000 prevalent cases. Similarly, socio-demographic, clinical and diagnostic data (e.g. echocardiography and ECG) in newly diagnosed patients will form a more detailed clinical registry of > 5000 incident cases. Sub-studies of the relationship between HIV status and H D and the optimal management of chronic heart failure will also be performed. Results: These data will provide a unique insight into the causes and consequences of a broad spectrum of HD-related conditions in a developing world community in epidemiologic transition. Initially documented Population rates, in addition to detailed examinations of the underlying risk factors and causes of HD-related morbidity/mortality will provide an important platform for future stages of the study: a community-based, population screening program and culturally specific primary and secondary programs of care. Conclusion: There is an urgent need to systematically track the emergence of HD in the developing world. Initially involving more than 15,000 individuals, the unique Heart of Soweto Study has the potential to provide a wealth of information in this regard. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

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Distal spinal muscular atrophy is a heterogeneous group of neuromuscular disorders caused by progressive anterior born cell degeneration and characterized by progressive motor weakness and muscular atrophy, predominantly in the distal parts of the limbs. Here we report on chronic autosomal recessive distal spinal muscular atrophy in a large, inbred family with onset at various ages. Because this condition had some of the same clinical features as spinal muscular atrophy with respiratory distress, we tested the disease gene for linkage to chromosome 11q and mapped the disease locus to chromosome 11q13 in the genetic interval that included the spinal muscular atrophy with respiratory distress gene (D11S1889-D11S1321, Z(max) = 4.59 at theta = 0 at locus D11S4136). The sequencing of IGHMBP2, the human homologue of the mouse neuromuscular degeneration gene (nmd) that accounts for spinal muscular atrophy with respiratory distress, failed to detect any mutation in our chronic distal spinal muscular atrophy patients, suggesting that spinal muscular atrophy with respiratory distress and chronic distal spinal muscular atrophy are caused by distinct genes located in the so-me chromosomal region. In addition, the high intrafamilial variability in age at onset raises the question of whether nonallelic modifying genes could be involved in chronic distal spinal muscular atrophy.

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The I-3 gene from the wild tomato species Lycopersicon pennellii confers resistance to race 3 of the devastating vascular wilt pathogen Fusarium oxysporum f. sp. lycopersici. As an initial step in a positional cloning strategy for the isolation of I-3, we converted restriction fragment length polymorphism and conserved orthologue set markers, known genes and a resistance gene analogue (RGA) mapping to the I-3 region into PCR-based sequence characterised amplified region (SCAR) and cleaved amplified polymorphic sequence (CAPS) markers. Additional PCR-based markers in the I-3 region were generated using the randomly amplified DNA fingerprinting (RAF) technique. SCAR, CAPS and RAF markers were used for high-resolution mapping around the I-3 locus. The I-3 gene was localised to a 0.3-cM region containing a RAF marker, eO6, and an RGA, RGA332. RGA332 was cloned and found to correspond to a putative pseudogene with at least two loss-of-function mutations. The predicted pseudogene belongs to the Toll interleukin-1 receptor-nucleotide-binding site-leucine-rich-repeat sub-class of plant disease resistance genes. Despite the presence of two RGA332 homologues in L. esculentum, DNA gel blot and PCR analysis suggests that no other homologues are present in lines carrying I-3 that could be alternative candidates for the gene.

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Fusarium wilt of tomato, caused by the fungal pathogen, Fusarium oxysporum f. sp. lycopersici (Fol), is an economically damaging disease that results in huge losses in Australia and other countries worldwide. The I-3 gene, which confers resistance to Fol race 3, has been described in wild tomato, Lycopersicon pennellii, accessions LA716 and PI414773. We are pursuing the isolation of I-3 from LA716 by map-based cloning. We have constructed a high-resolution map of the I-3 region and have identified markers closely flanking I-3 as well as markers co-segregating with I-3. In addition, construction of a physical map based on these markers has been initiated. This review describes the context of our research and our progress towards isolating the I-3 gene. It also describes some important practical outcomes of our work, including the development and use of a PCR-based marker for marker-assisted selection for I-3, and the finding that the I-3 gene from LA716 is different to that from PI1414773, which we have now designated I-7. Tomato varieties combining I-3 and I-7 have been developed and are currently being introduced into commercial production to further safeguard tomato crops against Fusarium wilt.

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Quantitative databases are limited to information identified as important by their creators, while databases containing natural language are limited by our ability to analyze large unstructured bodies of text. Leximancer is a tool that uses semantic mapping to develop concept maps from natural language. We have applied Leximancer to educational based pathology case notes to demonstrate how real patient records or databases of case studies could be analyzed to identify unique relationships. We then discuss how such analysis could be used to conduct quantitative analysis from databases such as the Coronary Heart Disease Database.