Showing papers by "Ioannis Xenarios published in 2001"

Complement facilitates early prion pathogenesis.

Abstract: New-variant Creutzfeldt-Jakob disease and scrapie are typically initiated by extracerebral exposure to the causative agent, and exhibit early prion replication in lymphoid organs. In mouse scrapie, depletion of B-lymphocytes prevents neuropathogenesis after intraperitoneal inoculation, probably due to impaired lymphotoxin-dependent maturation of follicular dendritic cells (FDCs), which are a major extracerebral prion reservoir. FDCs trap immune complexes with Fc-gamma receptors and C3d/C4b-opsonized antigens with CD21/CD35 complement receptors. We examined whether these mechanisms participate in peripheral prion pathogenesis. Depletion of circulating immunoglobulins or of individual Fc-gamma receptors had no effect on scrapie pathogenesis if B-cell maturation was unaffected. However, mice deficient in C3, C1q, Bf/C2, combinations thereof or complement receptors were partially or fully protected against spongiform encephalopathy upon intraperitoneal exposure to limiting amounts of prions. Splenic accumulation of prion infectivity and PrPSc was delayed, indicating that activation of specific complement components is involved in the initial trapping of prions in lymphoreticular organs early after infection.

Mining literature for protein–protein interactions

Abstract: Motivation: A central problem in bioinformatics is how to capture information from the vast current scientific literature in a form suitable for analysis by computer. We address the special case of information on protein‐protein interactions, and show that the frequencies of words in Medline abstracts can be used to determine whether or not a given paper discusses protein‐protein interactions. For those papers determined to discuss this topic, the relevant information can be captured for the Database of Interacting Proteins. Furthermore, suitable gene annotations can also be captured. Results: Our Bayesian approach scores Medline abstracts for probability of discussing the topic of interest according to the frequencies of discriminating words found in the abstract. More than 80 discriminating words (e.g. complex, interaction, two-hybrid) were determined from a training set of 260 Medline abstracts corresponding to previously validated entries in the Database of Interacting Proteins. Using these words and a log likelihood scoring function, ∼2000 Medline abstracts were identified as describing interactions between yeast proteins. This approach now forms the basis for the rapid expansion of the Database of Interacting Proteins.