University of South Florida

About: University of South Florida is a education organization based out in Tampa, Florida, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 34231 authors who have published 72644 publications receiving 2538044 citations. The organization is also known as: USF.

The structure of the presenilin 1 (S182) gene and identification of six novel mutations in early onset AD families

Abstract: Genetic linkage studies place a gene causing early onset familial Alzheimer's disease (FAD) on chromosome 14q24.3 (refs 1–4). Five mutations within the S182 (Presenilin 1: PS–1) gene, which maps to this region, have recently been reported in several early onset FAD kindreds5. We have localized the PS-1 gene to a 75 kb region and present the structure of this gene, evidence for alternative splicing and describe six novel mutations in early onset FAD pedigrees all of which alter residues conserved in the STM26 (Presenilin 2: PS-2) gene.

Solving the Korteweg-de Vries equation by its bilinear form: Wronskian solutions

Abstract: A broad set of sufficient conditions consisting of systems of linear partial differential equations is presented which guarantees that the Wronskian determinant solves the Korteweg-de Vries equation in the bilinear form. A systematical analysis is made for solving the resultant linear systems of second-order and third-order partial differential equations, along with solution formulas for their representative systems. The key technique is to apply variation of parameters in solving the involved non-homogeneous partial differential equations. The obtained solution formulas provide us with a comprehensive approach to construct the existing solutions and many new solutions including rational solutions, solitons, positons, negatons, breathers, complexitons and interaction solutions of the Korteweg-de Vries equation.

Orderly order in protein intrinsic disorder distribution: disorder in 3500 proteomes from viruses and the three domains of life

Abstract: Intrinsically disordered proteins and intrinsically disordered protein regions are highly abundant in nature. However, the quantitative and qualitative measures of protein intrinsic disorder in species with known genomes are still not available. Furthermore, although the correlation between high fraction of disordered residues and advanced species has been reported, the details of this correlation and the connection between the disorder content and proteome complexity have not been reported as of yet. To fill this gap, we analysed entire proteomes of 3484 species from three domains of life (archaea, bacteria and eukaryotes) and from viruses. Our analysis revealed that the evolution process is characterized by distinctive patterns of changes in the protein intrinsic disorder content. We are showing here that viruses are characterized by the widest spread of the proteome disorder content (the percentage of disordered residues ranges from 7.3% in human coronavirus NL63 to 77.3% in Avian carcinoma virus). For several organisms, a clear correlation is seen between their disorder contents and habitats. In multicellular eukaryotes, there is a weak correlation between the complexity of an organism (evaluated as a number of different cell types) and its overall disorder content. For both the prokaryotes and eukaryotes, the disorder content is generally independent of the proteome size. However, disorder shows a sharp increase associated with the transition from prokaryotic to eukaryotic cells. This suggests that the increased disorder content in eukaryotic proteomes might be used by nature to deal with the increased cell complexity due to the appearance of the various cellular compartments.

Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants

Abstract: Background: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. Methods: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. Results: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. Conclusions: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.