179 research outputs found

    Value of flow cytometry for MRD-based relapse prediction in B-cell precursor ALL in a multicenter setting

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    PCR of TCR/Ig gene rearrangements is considered the method of choice for minimal residual disease (MRD) quantification in BCP-ALL, but flow cytometry analysis of leukemia-associated immunophenotypes (FCM-MRD) is faster and biologically more informative. FCM-MRD performed in 18 laboratories across seven countries was used for risk stratification of 1487 patients with BCP-ALL enrolled in the NOPHO ALL2008 protocol. When no informative FCM-marker was available, risk stratification was based on real-time quantitative PCR. An informative FCM-marker was found in 96.2% and only two patients (0.14%) had non-informative FCM and non-informative PCR-markers. The overall 5-year event-free survival was 86.1% with a cumulative incidence of relapse (CIR5y) of 9.5%. FCM-MRD levels on days 15 (HzR 4.0, p 10(-4) associated with a CIR5y = 22.1%. In conclusion, FCM-MRD performed in a multicenter setting is a clinically useful method for MRD-based treatment stratification in BCP-ALL.Peer reviewe

    Population genomics reveals that within-fungus polymorphism is common and maintained in populations of the mycorrhizal fungus Rhizophagus irregularis.

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    Arbuscular mycorrhizal (AM) fungi are symbionts of most plants, increasing plant growth and diversity. The model AM fungus Rhizophagus irregularis (isolate DAOM 197198) exhibits low within-fungus polymorphism. In contrast, another study reported high within-fungus variability. Experiments with other R. irregularis isolates suggest that within-fungus genetic variation can affect the fungal phenotype and plant growth, highlighting the biological importance of such variation. We investigated whether there is evidence of differing levels of within-fungus polymorphism in an R. irregularis population. We genotyped 20 isolates using restriction site-associated DNA sequencing and developed novel approaches for characterizing polymorphism among haploid nuclei. All isolates exhibited higher within-isolate poly-allelic single-nucleotide polymorphism (SNP) densities than DAOM 197198 in repeated and non-repeated sites mapped to the reference genome. Poly-allelic SNPs were independently confirmed. Allele frequencies within isolates deviated from diploids or tetraploids, or that expected for a strict dikaryote. Phylogeny based on poly-allelic sites was robust and mirrored the standard phylogeny. This indicates that within-fungus genetic variation is maintained in AM fungal populations. Our results predict a heterokaryotic state in the population, considerable differences in copy number variation among isolates and divergence among the copies, or aneuploidy in some isolates. The variation may be a combination of all of these hypotheses. Within-isolate genetic variation in R. irregularis leads to large differences in plant growth. Therefore, characterizing genomic variation within AM fungal populations is of major ecological importance

    Measures and Limits of Models of Fixation Selection

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    Models of fixation selection are a central tool in the quest to understand how the human mind selects relevant information. Using this tool in the evaluation of competing claims often requires comparing different models' relative performance in predicting eye movements. However, studies use a wide variety of performance measures with markedly different properties, which makes a comparison difficult. We make three main contributions to this line of research: First we argue for a set of desirable properties, review commonly used measures, and conclude that no single measure unites all desirable properties. However the area under the ROC curve (a classification measure) and the KL-divergence (a distance measure of probability distributions) combine many desirable properties and allow a meaningful comparison of critical model performance. We give an analytical proof of the linearity of the ROC measure with respect to averaging over subjects and demonstrate an appropriate correction of entropy-based measures like KL-divergence for small sample sizes in the context of eye-tracking data. Second, we provide a lower bound and an upper bound of these measures, based on image-independent properties of fixation data and between subject consistency respectively. Based on these bounds it is possible to give a reference frame to judge the predictive power of a model of fixation selection . We provide open-source python code to compute the reference frame. Third, we show that the upper, between subject consistency bound holds only for models that predict averages of subject populations. Departing from this we show that incorporating subject-specific viewing behavior can generate predictions which surpass that upper bound. Taken together, these findings lay out the required information that allow a well-founded judgment of the quality of any model of fixation selection and should therefore be reported when a new model is introduced

    The Interaction of Canine Plasminogen with Streptococcus pyogenes Enolase: They Bind to One Another but What Is the Nature of the Structures Involved?

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    For years it has been clear that plasminogen from different sources and enolase from different sources interact strongly. What is less clear is the nature of the structures required for them to interact. This work examines the interaction between canine plasminogen (dPgn) and Streptococcus pyogenes enolase (Str enolase) using analytical ultracentrifugation (AUC), surface plasmon resonance (SPR), fluorescence polarization, dynamic light scattering (DLS), isothermal titration calorimetry (ITC), and simple pull-down reactions. Overall, our data indicate that a non-native structure of the octameric Str enolase (monomers or multimers) is an important determinant of its surface-mediated interaction with host plasminogen. Interestingly, a non-native structure of plasminogen is capable of interacting with native enolase. As far as we can tell, the native structures resist forming stable mixed complexes

    Influence of Low-Level Stimulus Features, Task Dependent Factors, and Spatial Biases on Overt Visual Attention

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    Visual attention is thought to be driven by the interplay between low-level visual features and task dependent information content of local image regions, as well as by spatial viewing biases. Though dependent on experimental paradigms and model assumptions, this idea has given rise to varying claims that either bottom-up or top-down mechanisms dominate visual attention. To contribute toward a resolution of this discussion, here we quantify the influence of these factors and their relative importance in a set of classification tasks. Our stimuli consist of individual image patches (bubbles). For each bubble we derive three measures: a measure of salience based on low-level stimulus features, a measure of salience based on the task dependent information content derived from our subjects' classification responses and a measure of salience based on spatial viewing biases. Furthermore, we measure the empirical salience of each bubble based on our subjects' measured eye gazes thus characterizing the overt visual attention each bubble receives. A multivariate linear model relates the three salience measures to overt visual attention. It reveals that all three salience measures contribute significantly. The effect of spatial viewing biases is highest and rather constant in different tasks. The contribution of task dependent information is a close runner-up. Specifically, in a standardized task of judging facial expressions it scores highly. The contribution of low-level features is, on average, somewhat lower. However, in a prototypical search task, without an available template, it makes a strong contribution on par with the two other measures. Finally, the contributions of the three factors are only slightly redundant, and the semi-partial correlation coefficients are only slightly lower than the coefficients for full correlations. These data provide evidence that all three measures make significant and independent contributions and that none can be neglected in a model of human overt visual attention

    Strong Interaction Physics at the Luminosity Frontier with 22 GeV Electrons at Jefferson Lab

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    This document presents the initial scientific case for upgrading the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab (JLab) to 22 GeV. It is the result of a community effort, incorporating insights from a series of workshops conducted between March 2022 and April 2023. With a track record of over 25 years in delivering the world's most intense and precise multi-GeV electron beams, CEBAF's potential for a higher energy upgrade presents a unique opportunity for an innovative nuclear physics program, which seamlessly integrates a rich historical background with a promising future. The proposed physics program encompass a diverse range of investigations centered around the nonperturbative dynamics inherent in hadron structure and the exploration of strongly interacting systems. It builds upon the exceptional capabilities of CEBAF in high-luminosity operations, the availability of existing or planned Hall equipment, and recent advancements in accelerator technology. The proposed program cover various scientific topics, including Hadron Spectroscopy, Partonic Structure and Spin, Hadronization and Transverse Momentum, Spatial Structure, Mechanical Properties, Form Factors and Emergent Hadron Mass, Hadron-Quark Transition, and Nuclear Dynamics at Extreme Conditions, as well as QCD Confinement and Fundamental Symmetries. Each topic highlights the key measurements achievable at a 22 GeV CEBAF accelerator. Furthermore, this document outlines the significant physics outcomes and unique aspects of these programs that distinguish them from other existing or planned facilities. In summary, this document provides an exciting rationale for the energy upgrade of CEBAF to 22 GeV, outlining the transformative scientific potential that lies within reach, and the remarkable opportunities it offers for advancing our understanding of hadron physics and related fundamental phenomena.Comment: Updates to the list of authors; Preprint number changed from theory to experiment; Updates to sections 4 and 6, including additional figure

    Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

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