Typical pseudo-relevance feedback methods assume the topretrieved documents are relevant and use these pseudo-relevant documents to expand terms. The initial retrieval set can, however, contain a great deal of noise. In this paper, we present a clusterbased resampling method to select better pseudo-relevant documents based on the relevance model. The main idea is to use document clusters to find dominant documents for the initial retrieval set, and to repeatedly feed the documents to emphasize the core topics of a query. Experimental results on large-scale web TREC collections show significant improvements over the relevance model. For justification of the resampling approach, we examine relevance density of feedback documents. A higher relevance density will result in greater retrieval accuracy, ultimately approaching true relevance feedback. The resampling approach shows higher relevance density than the baseline relevance model on all collections, resulting in better retrieval accuracy in pseudo-relevance feedback. This result indicates that the proposed method is effective for pseudo-relevance feedback.
α
1D
-Adrenergic receptors (ARs) are key regulators of cardiovascular system function that increase blood pressure and promote vascular remodeling. Unfortunately, little information exists about the signaling pathways used by this important G protein-coupled receptor (GPCR). We recently discovered that α
1D
-ARs form a “signalosome” with multiple members of the dystrophin-associated protein complex (DAPC) to become functionally expressed at the plasma membrane and bind ligands. However, the molecular mechanism by which the DAPC imparts functionality to the α
1D
-AR signalosome remains a mystery. To test the hypothesis that previously unidentified molecules are recruited to the α
1D
-AR signalosome, we performed an extensive proteomic analysis on each member of the DAPC. Bioinformatic analysis of our proteomic data sets detected a common interacting protein of relatively unknown function, α-catulin. Coimmunoprecipitation and blot overlay assays indicate that α-catulin is directly recruited to the α
1D
-AR signalosome by the C-terminal domain of α-dystrobrevin-1 and not the closely related splice variant α-dystrobrevin-2. Proteomic and biochemical analysis revealed that α-catulin supersensitizes α
1D
-AR functional responses by recruiting effector molecules to the signalosome. Taken together, our study implicates α-catulin as a unique regulator of GPCR signaling and represents a unique expansion of the intricate and continually evolving array of GPCR signaling networks.
Mammalian MBNL (muscleblind-like) proteins are regulators of alternative splicing and have been implicated in myotonic dystrophy, the most common form of adult onset muscular dystrophy. MBNL3 functions as an inhibitor of muscle differentiation and is expressed in proliferating muscle precursor cells but not in differentiated skeletal muscle. Here we demonstrate that MBNL3 regulates the splicing pattern of the muscle transcription factor myocyte enhancer factor 2 (Mef2) by promoting exclusion of the alternatively spliced -exon. Expression of the transcriptionally more active (؉) isoform of Mef2D was sufficient to overcome the inhibitory effects of MBNL3 on muscle differentiation. These data suggest that MBNL3 antagonizes muscle differentiation by disrupting Mef2 -exon splicing. MBNL3 regulates Mef2D splicing by directly binding to intron 7 downstream of the alternatively spliced exon in the pre-mRNA. The RNA binding activity of MBNL3 requires the CX 7 CX 4 -6 CX 3 H zinc finger domains. Using a cell culture model of myotonic dystrophy and myotonic dystrophy patient tissue, we have evidence that expression of CUG expanded RNAs can lead to an increase in MBNL3 expression and a decrease in Mef2D -exon splicing. These studies suggest that elevating MBNL3 activity in myogenic cells could lead to muscle degeneration disorders such as myotonic dystrophy.
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