4,951 research outputs found

    Exact Post Model Selection Inference for Marginal Screening

    Full text link
    We develop a framework for post model selection inference, via marginal screening, in linear regression. At the core of this framework is a result that characterizes the exact distribution of linear functions of the response yy, conditional on the model being selected (``condition on selection" framework). This allows us to construct valid confidence intervals and hypothesis tests for regression coefficients that account for the selection procedure. In contrast to recent work in high-dimensional statistics, our results are exact (non-asymptotic) and require no eigenvalue-like assumptions on the design matrix XX. Furthermore, the computational cost of marginal regression, constructing confidence intervals and hypothesis testing is negligible compared to the cost of linear regression, thus making our methods particularly suitable for extremely large datasets. Although we focus on marginal screening to illustrate the applicability of the condition on selection framework, this framework is much more broadly applicable. We show how to apply the proposed framework to several other selection procedures including orthogonal matching pursuit, non-negative least squares, and marginal screening+Lasso

    Suppression of allergic airway inflammation by helminth-induced regulatory T cells

    Get PDF
    Allergic diseases mediated by T helper type (Th) 2 cell immune responses are rising dramatically in most developed countries. Exaggerated Th2 cell reactivity could result, for example, from diminished exposure to Th1 cell–inducing microbial infections. Epidemiological studies, however, indicate that Th2 cell–stimulating helminth parasites may also counteract allergies, possibly by generating regulatory T cells which suppress both Th1 and Th2 arms of immunity. We therefore tested the ability of the Th2 cell–inducing gastrointestinal nematode Heligmosomoides polygyrus to influence experimentally induced airway allergy to ovalbumin and the house dust mite allergen Der p 1. Inflammatory cell infiltrates in the lung were suppressed in infected mice compared with uninfected controls. Suppression was reversed in mice treated with antibodies to CD25. Most notably, suppression was transferable with mesenteric lymph node cells (MLNC) from infected animals to uninfected sensitized mice, demonstrating that the effector phase was targeted. MLNC from infected animals contained elevated numbers of CD4(+)CD25(+)Foxp3(+) T cells, higher TGF-β expression, and produced strong interleukin (IL)-10 responses to parasite antigen. However, MLNC from IL-10–deficient animals transferred suppression to sensitized hosts, indicating that IL-10 is not the primary modulator of the allergic response. Suppression was associated with CD4(+) T cells from MLNC, with the CD4(+)CD25(+) marker defining the most active population. These data support the contention that helminth infections elicit a regulatory T cell population able to down-regulate allergen induced lung pathology in vivo

    Structures of the DfsB protein family suggest a cationic, helical sibling lethal factor peptide

    Get PDF
    Bacteria have developed a variety of mechanisms for surviving harsh environmental conditions, nutrient stress and overpopulation. Paenibacillus dendritiformis produces a lethal protein (Slf) that is able to induce cell death in neighbouring colonies and a phenotypic switch in more distant ones. Slf is derived from the secreted precursor protein, DfsB, after proteolytic processing. Here, we present new crystal structures of DfsB homologues from a variety of bacterial species and a surprising version present in the yeast Saccharomyces cerevisiae. Adopting a four-helix bundle decorated with a further three short helices within intervening loops, DfsB belongs to a non-enzymatic class of the DinB fold. The structure suggests that the biologically active Slf fragment may possess a C-terminal helix rich in basic and aromatic residues that suggest a functional mechanism akin to that for cationic antimicrobial peptides

    Learning to reason over visual objects

    Full text link
    A core component of human intelligence is the ability to identify abstract patterns inherent in complex, high-dimensional perceptual data, as exemplified by visual reasoning tasks such as Raven's Progressive Matrices (RPM). Motivated by the goal of designing AI systems with this capacity, recent work has focused on evaluating whether neural networks can learn to solve RPM-like problems. Previous work has generally found that strong performance on these problems requires the incorporation of inductive biases that are specific to the RPM problem format, raising the question of whether such models might be more broadly useful. Here, we investigated the extent to which a general-purpose mechanism for processing visual scenes in terms of objects might help promote abstract visual reasoning. We found that a simple model, consisting only of an object-centric encoder and a transformer reasoning module, achieved state-of-the-art results on both of two challenging RPM-like benchmarks (PGM and I-RAVEN), as well as a novel benchmark with greater visual complexity (CLEVR-Matrices). These results suggest that an inductive bias for object-centric processing may be a key component of abstract visual reasoning, obviating the need for problem-specific inductive biases.Comment: ICLR 202

    Exploitation of NMR in the analysis and screening of fragment ligands for an Sh2 domain

    Get PDF
    A fragment-based approach to drug design has recently emerged in which small chemical groups that bind to adjacent sites on a receptor are identified, optimised, and linked together to generate a high-affinity lead compound. Due to its sensitivity, nuclear magnetic resonance (NMR) is a particularly useful technique for the detection of low-affinity fragment binding. An aim of this project was to explore further the utility of NMR with regards to fragment ligand binding using a well- understood model system - the Src Homology 2 (SH2) domain from v-Src kinase. This choice was supported by a large body of structural, functional, and thermodynamic data, coupled with a decade of pharmaceutical investigation into several SH2 domains. Our ongoing biophysical studies of v-Src SH2 required determination of the apo solution structure of this domain. A high quality structural ensemble was obtained using standard NMR techniques and a combination of manual and automated assignment methods. The internal hydrogen bonding, ionisation states, and backbone dynamics of the apo v-Src SH2 domain was also explored using NMR. The perturbation of v-Src SH2 backbone chemical shifts and dynamics by interaction with fragment ligands yielded insights into SH2 domain binding behaviour and specificity. Computational approaches were used to identify potential fragment ligands for v-Src SH2. A small library of these molecules were screened in vitro using a recently-proposed 19F-NMR competition screening approach, which was optimised for the detection of low-affinity fragments. Follow-up NMR and calorimetry experiments confirmed the screening results and provided further characterisation of the novel fragment ligands. Such compounds may be useful as phosphotyrosine mimetics in SH2-related drug design. A novel 31P-based screening experiment was also proposed. These studies have furthered our understanding of the SH2 domain, in terms of its binding specificity and drug design, and of the NMR screening approaches useful for fragment-based lead discovery
    corecore