980 resultados para Target Selection


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Point and click interactions using a mouse are an integral part of computer use for current desktop systems. Compared with younger users though, older adults experience greater difficulties performing cursor positioning tasks, and this can present limitations to using a computer easily and effectively. Target expansion is a technique for improving pointing performance, where the target dynamically grows as the cursor approaches. This has the advantage that targets conserve screen real estate in their unexpanded state, yet can still provide the benefits of a larger area to click on. This paper presents two studies of target expansion with older and younger participants, involving multidirectional point-select tasks with a computer mouse. Study 1 compares static versus expanding targets, and Study 2 compares static targets with three alternative techniques for expansion. Results show that expansion can improve times by up to 14%, and reduce error rates by up to 50%. Additionally, expanding targets are beneficial even when the expansion happens late in the movement, i.e. after the cursor has reached the expanded target area or even after it has reached the original target area. Participants’ subjective feedback on the target expansion are generally favorable, and this lends further support for the technique.

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Genetic instability is thought to be responsible for the numerous genotypic changes that occur during neoplastic transformation and metastatic progression. To explore the role of genetic instability at the level of point mutations during mammary tumor development and malignant progression, we combined transgenic mouse models of mutagenesis detection and oncogenesis. Bitransgenic mice were generated that carried both a bacteriophage lambda transgene to assay mutagenesis and a polyomavirus middle T oncogene, mammary gland-targeted expression of which led to metastatic mammary adenocarcinomas. We developed a novel assay for the detection of mutations in the lambda transgene that selects for phage containing forward mutations only in the lambda cII gene, using an hfl- bacterial host. In addition to the relative ease of direct selection, the sensitivity of this assay for both spontaneous and chemically induced mutations was comparable to the widely used mutational target gene, lambda lacI, making the cII assay an attractive alternative for mutant phage recovery for any lambda-based mouse mutagenesis assay system. The frequencies of lambda cII- mutants were not significantly different in normal mammary epithelium, primary mammary adenocarcinomas, and pulmonary metastases. The cII mutational spectra in these tissues consisted mostly of G/C-->A/T transitions, a large fraction of which occurred at CpG dinucleotides. These data suggest that, in this middle T oncogene model of mammary tumor progression, a significant increase in mutagenesis is not required for tumor development or for metastatic progression.

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An in vitro genetic system was developed as a rapid means for studying the specificity determinants of RNA-binding proteins. This system was used to investigate the origin of the RNA-binding specificity of the mammalian spliceosomal protein U1A. The U1A domain responsible for binding to U1 small nuclear RNA was locally mutagenized and displayed as a combinatorial library on filamentous bacteriophage. Affinity selection identified four U1A residues in the mutagenized region that are important for specific binding to U1 hairpin II. One of these residues (Leu-49) disproportionately affects the rates of binding and release and appears to play a critical role in locking the protein onto the RNA. Interestingly, a protein variant that binds more tightly than U1A emerged during the selection, showing that the affinity of U1A for U1 RNA has not been optimized during evolution.

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The quick detection of abrupt (unknown) parameter changes in an observed hidden Markov model (HMM) is important in several applications. Motivated by the recent application of relative entropy concepts in the robust sequential change detection problem (and the related model selection problem), this paper proposes a sequential unknown change detection algorithm based on a relative entropy based HMM parameter estimator. Our proposed approach is able to overcome the lack of knowledge of post-change parameters, and is illustrated to have similar performance to the popular cumulative sum (CUSUM) algorithm (which requires knowledge of the post-change parameter values) when examined, on both simulated and real data, in a vision-based aircraft manoeuvre detection problem.

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In Arabidopsis thaliana (Arabidopsis), DICER-LIKE1 (DCL1) functions together with the double-stranded RNA binding protein (dsRBP), DRB1, to process microRNAs (miRNAs) from their precursor transcripts prior to their transfer to the RNA-induced silencing complex (RISC). miRNA-loaded RISC directs RNA silencing of cognate mRNAs via ARGONAUTE1 (AGO1)-catalyzed cleavage. Short interefering RNAs (siRNAs) are processed from viral-derived or transgene-encoded molecules of doublestranded RNA (dsRNA) by the DCL/dsRBP partnership, DCL4/DRB4, and are also loaded to AGO1-catalyzed RISC for cleavage of complementary mRNAs. Here, we use an artificial miRNA (amiRNA) technology, transiently expressed in Nicotiana benthamiana, to produce a series of amiRNA duplexes with differing intermolecular thermostabilities at the 5′ end of duplex strands. Analyses of amiRNA duplex strand accumulation and target transcript expression revealed that strand selection (amiRNA and amiRNA*) is directed by asymmetric thermostability of the duplex termini. The duplex strand possessing a lower 59 thermostability was preferentially retained by RISC to guide mRNA cleavage of the corresponding target transgene. In addition, analysis of endogenous miRNA duplex strand accumulation in Arabidopsis drb1 and drb2345 mutant plants revealed that DRB1 dictates strand selection, presumably by directional loading of the miRNA duplex onto RISC for passenger strand degradation. Bioinformatic and Northern blot analyses of DCL4/DRB4-dependent small RNAs (miRNAs and siRNAs) revealed that small RNAs produced by this DCL/dsRBP combination do not conform to the same terminal thermostability rules as those governing DCL1/DRB1-processed miRNAs. This suggests that small RNA processing in the DCL1/DRB1-directed miRNA and DCL4/DRB4-directed sRNA biogenesis pathways operates via different mechanisms.

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Background: Display technologies which allow peptides or proteins to be physically associated with the encoding DNA are central to procedures which involve screening of protein libraries in vitro for new or altered function. Here we describe a new system designed specifically for the display of libraries of diverse, functional proteins which utilises the DNA binding protein nuclear factor κB (NF-κB) p50 to establish a phenotype–genotype link between the displayed protein and the encoding gene. Results: A range of model fusion proteins to either the amino- or carboxy-terminus of NF-κB p50 have been constructed and shown to retain the picomolar affinity and DNA specificity of wild-type NF-κB p50. Through use of an optimal combination of binding buffer and DNA target sequence, the half-life of p50–DNA complexes could be increased to over 47 h, enabling the competitive selection of a variety of protein–plasmid complexes with enrichment factors of up to 6000-fold per round. The p50-based plasmid display system was used to enrich a maltose binding protein complex to homogeneity in only three rounds from a binary mixture with a starting ratio of 1:108 and to enrich to near homogeneity a single functional protein from a phenotype–genotype linked Escherichia coli genomic library using in vitro functional selections. Conclusions: A new display technology is described which addresses the challenge of functional protein display. The results demonstrate that plasmid display is sufficiently sensitive to select a functional protein from large libraries and that it therefore represents a useful addition to the repertoire of display technologies.

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Background Display technologies which allow peptides or proteins to be physically associated with the encoding DNA are central to procedures which involve screening of protein libraries in vitro for new or altered function. Here we describe a new system designed specifically for the display of libraries of diverse, functional proteins which utilises the DNA binding protein nuclear factor κB (NF-κB) p50 to establish a phenotype-genotype link between the displayed protein and the encoding gene. Results A range of model fusion proteins to either the amino- or carboxy-terminus of NF-κB p50 have been constructed and shown to retain the picomolar affinity and DNA specificity of wild-type NF-κB p50. Through use of an optimal combination of binding buffer and DNA target sequence, the half-life of p50-DNA complexes could be increased to over 47 h, enabling the competitive selection of a variety of protein-plasmid complexes with enrichment factors of up to 6000-fold per round. The p50-based plasmid display system was used to enrich a maltose binding protein complex to homogeneity in only three rounds from a binary mixture with a starting ratio of 1:108 and to enrich to near homogeneity a single functional protein from a phenotype-genotype linked Escherichia coli genomic library using in vitro functional selections. Conclusions A new display technology is described which addresses the challenge of functional protein display. The results demonstrate that plasmid display is sufficiently sensitive to select a functional protein from large libraries and that it therefore represents a useful addition to the repertoire of display technologies.

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Rapid diagnostic tests (RDTs) represent important tools to diagnose malaria infection. To improve understanding of the variable performance of RDTs that detect the major target in Plasmodium falciparum, namely, histidine-rich protein 2 (HRP2), and to inform the design of better tests, we undertook detailed mapping of the epitopes recognized by eight HRP-specific monoclonal antibodies (MAbs). To investigate the geographic skewing of this polymorphic protein, we analyzed the distribution of these epitopes in parasites from geographically diverse areas. To identify an ideal amino acid motif for a MAb to target in HRP2 and in the related protein HRP3, we used a purpose-designed script to perform bioinformatic analysis of 448 distinct gene sequences from pfhrp2 and from 99 sequences from the closely related gene pfhrp3. The frequency and distribution of these motifs were also compared to the MAb epitopes. Heat stability testing of MAbs immobilized on nitrocellulose membranes was also performed. Results of these experiments enabled the identification of MAbs with the most desirable characteristics for inclusion in RDTs, including copy number and coverage of target epitopes, geographic skewing, heat stability, and match with the most abundant amino acid motifs identified. This study therefore informs the selection of MAbs to include in malaria RDTs as well as in the generation of improved MAbs that should improve the performance of HRP-detecting malaria RDTs.

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Cane fibre content has increased over the past ten years. Some of that increase can be attributed to new varieties selected for release. This paper reviews the existing methods for quantifying the fibre characteristics of a variety, including fibre content and fibre quality measurements – shear strength, impact resistance and short fibre content. The variety selection process is presented and it is reported that fibre content has zero weighting in the current selection index. An updated variety selection approach is proposed, potentially replacing the existing selection process relating to fibre. This alternative approach involves the use of a more complex mill area level model that accounts for harvesting, transport and processing equipment, taking into account capacity, efficiency and operational impacts, along with the end use for the bagasse. The approach will ultimately determine a net economic value for the variety. The methodology lends itself to a determination of the fibre properties that have a significant impact on the economic value so that variety tests can better target the critical properties. A low-pressure compression test is proposed as a good test to provide an assessment of the impact of a variety on milling capacity. NIR methodology is proposed as a technology to lead to a more rapid assessment of fibre properties, and hence the opportunity to more comprehensively test for fibre impacts at an earlier stage of variety development.

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Spoken word production is assumed to involve stages of processing in which activation spreads through layers of units comprising lexical-conceptual knowledge and their corresponding phonological word forms. Using high-field (4T) functional magnetic resonance imagine (fMRI), we assessed whether the relationship between these stages is strictly serial or involves cascaded-interactive processing, and whether central (decision/control) processing mechanisms are involved in lexical selection. Participants performed the competitor priming paradigm in which distractor words, named from a definition and semantically related to a subsequently presented target picture, slow picture-naming latency compared to that with unrelated words. The paradigm intersperses two trials between the definition and the picture to be named, temporally separating activation in the word perception and production networks. Priming semantic competitors of target picture names significantly increased activation in the left posterior temporal cortex, and to a lesser extent the left middle temporal cortex, consistent with the predictions of cascaded-interactive models of lexical access. In addition, extensive activation was detected in the anterior cingulate and pars orbitalis of the inferior frontal gyrus. The findings indicate that lexical selection during competitor priming is biased by top-down mechanisms to reverse associations between primed distractor words and target pictures to select words that meet the current goal of speech.

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How does the presence of a categorically related word influence picture naming latencies? In order to test competitive and noncompetitive accounts of lexical selection in spoken word production, we employed the picture–word interference (PWI) paradigm to investigate how conceptual feature overlap influences naming latencies when distractors are category coordinates of the target picture. Mahon et al. (2007. Lexical selection is not by competition: A reinterpretation of semantic interference and facilitation effects in the picture-word interference paradigm. Journal of Experimental Psychology. Learning, Memory, and Cognition, 33(3), 503–535. doi:10.1037/0278-7393.33.3.503) reported that semantically close distractors (e.g., zebra) facilitated target picture naming latencies (e.g., HORSE) compared to far distractors (e.g., whale). We failed to replicate a facilitation effect for within-category close versus far target–distractor pairings using near-identical materials based on feature production norms, instead obtaining reliably larger interference effects (Experiments 1 and 2). The interference effect did not show a monotonic increase across multiple levels of within-category semantic distance, although there was evidence of a linear trend when unrelated distractors were included in analyses (Experiment 2). Our results show that semantic interference in PWI is greater for semantically close than for far category coordinate relations, reflecting the extent of conceptual feature overlap between target and distractor. These findings are consistent with the assumptions of prominent competitive lexical selection models of speech production.

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Spatial data analysis has become more and more important in the studies of ecology and economics during the last decade. One focus of spatial data analysis is how to select predictors, variance functions and correlation functions. However, in general, the true covariance function is unknown and the working covariance structure is often misspecified. In this paper, our target is to find a good strategy to identify the best model from the candidate set using model selection criteria. This paper is to evaluate the ability of some information criteria (corrected Akaike information criterion, Bayesian information criterion (BIC) and residual information criterion (RIC)) for choosing the optimal model when the working correlation function, the working variance function and the working mean function are correct or misspecified. Simulations are carried out for small to moderate sample sizes. Four candidate covariance functions (exponential, Gaussian, Matern and rational quadratic) are used in simulation studies. With the summary in simulation results, we find that the misspecified working correlation structure can still capture some spatial correlation information in model fitting. When the sample size is large enough, BIC and RIC perform well even if the the working covariance is misspecified. Moreover, the performance of these information criteria is related to the average level of model fitting which can be indicated by the average adjusted R square ( [GRAPHICS] ), and overall RIC performs well.