Here, we show that PHIST member PFE1605w binds the PfEMP1 intracellular segment directly with K-d = 5 +/- 0.6 mu M, comigrates with PfEMP1 during export, and locates in knobs. PHIST variants that
do not locate in knobs (MAL8P1.4) or bind PfEMP1 30 times more weakly (PFI1780w) used as controls VX-680 mouse did not display the same pattern. We resolved the first crystallographic structure of a PHIST protein and derived a partial model of the PHIST-PfEMP1 interaction from nuclear magnetic resonance. We propose that PFE1605w reinforces the PfEMP1-cytoskeletal connection in knobs and discuss the possible role of PHIST proteins as interaction hubs in the parasite exportome.-Oberli, A., Slater, L. M., Cutts, E., Brand, F., Mundwiler-Pachlatko, E., Rusch, S., Masik, M. F. G., Erat, M. C., Beck, H.-P., Vakonakis, I. A Plasmodium falciparum PHIST protein binds the virulence factor PfEMP1 and comigrates to knobs on the host cell surface.”
“Many text classifications depend on statistical term measures to implement document representation. Such document representations ignore the lexical
semantic contents of terms and the distilled mutual information, leading to text classification errors. This work proposed INCB28060 solubility dmso a document representation method, WordNet-based lexical semantic VSM, to solve the problem. Using WordNet, this method constructed a data structure of semantic-element information to characterize lexical semantic contents, and adjusted EM modeling to disambiguate word stems. Then, in the lexical-semantic space of corpus, lexical-semantic eigenvector of document representation was built by calculating the weight of each synset, and applied to a widely-recognized algorithm NWKNN. On text corpus Reuter-21578 and its adjusted version Selleckchem XMU-MP-1 of lexical replacement, the experimental results show that the lexical-semantic eigenvector performs F1 measure and scales of dimension better than term-statistic
eigenvector based on TF-IDF. Formation of document representation eigenvectors ensures the method a wide prospect of classification applications in text corpus analysis.”
“Background: Attention-deficit/hyperactivity disorder (ADHD) is a child hood-onset neuropsychiatric disease that persists into adulthood in at least 30% of patients. There is evidence suggesting that abnormal left-right brain asymmetries in ADHD patients may be involved in a variety of ADHD-related cognitive processes, including sustained attention, working memory, response inhibition and planning. Although mechanisms underlying cerebral lateralization are unknown, left-right cortical asymmetry has been associated with transcriptional asymmetry at embryonic stages and several genes differentially expressed between hemispheres have been identified.