348 research outputs found

    High-Affinity Small Molecule Inhibitors of T Cell Costimulation: Compounds for Immunotherapy

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    SummaryCostimulatory molecules are important regulators of T cell activation and thus favored targets for therapeutic manipulation of immune responses. One of the key costimulatory receptors is CD80, which binds the T cell ligands, CD28, and CTLA-4. We describe a set of small compounds that bind with high specificity and low nanomolar affinity to CD80. The compounds have relatively slow off-rates and block both CD28 and CTLA-4 binding, implying that they occlude the shared ligand binding site. The compounds inhibit proinflammatory cytokine release in T cell assays with submicromolar potency, and as such, they represent promising leads for the development of novel therapeutics for immune-mediated inflammatory disease. Our results also suggest that other predominantly β proteins, such as those that dominate the cell surface, may also be accessible as potentially therapeutic targets

    The Role of Compensatory Beliefs in Rationalizing Environmentally Detrimental Behaviors

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    Compensatory green beliefs (CGBs) reflect the idea that a pro-environmental behavior (e.g., recycling) can off-set the negative effects of an environmentally detrimental behavior (e.g., driving). It is thought that CGBs might help explain why people act in ways that appear to contradict their pro-environmental intentions, and inconsistently engage in pro-environmental behaviors. The present study sought to investigate the nature and use of CGBs. A series of interviews suggested that participants endorsed CGBs to: (a) reduce feelings of guilt with respect to (the assumed or actual) negative environmental impact of their actions, and (b) to defend their green credentials in social situations. Participants also justified detrimental behaviors on the basis of higher loyalties (e.g., family’s needs), or the perceived difficulty of performing more pro-environmental actions. In addition to shedding light on how, when, and why people might hold and use CGBs, the research also provides new insight into how CGBs should be assessed

    Evidence-Based Mental Health Programs in Schools: Barriers and Facilitators of Successful Implementation

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    Although schools can improve children’s access to mental health services, not all school-based providers are able to successfully deliver evidence-based practices. Indeed, even when school clinicians are trained in evidence-based practices (EBP), the training does not necessarily result in the implementation of those practices. This study explores factors that influence implementation of a particular EBP, Cognitive Behavioral Intervention for Trauma in Schools (CBITS). Semi-structured telephone interviews with 35 site administrators and clinicians from across the United States were conducted 6–18 months after receiving CBITS training to discuss implementation experiences. The implementation experiences of participants differed, but all reported similar barriers to implementation. Sites that successfully overcame such barriers differed from their unsuccessful counterparts by having greater organizational structure for delivering school services, a social network of other clinicians implementing CBITS, and administrative support for implementation. This study suggests that EBP implementation can be facilitated by having the necessary support from school leadership and peers

    Chemical diversity in a metal-organic framework revealed by fluorescence lifetime imaging

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    The presence and variation of chemical functionality and defects in crystalline materials, such as metal–organic frameworks (MOFs), have tremendous impact on their properties. Finding a means of identifying and characterizing this chemical diversity is an important ongoing challenge. This task is complicated by the characteristic problem of bulk measurements only giving a statistical average over an entire sample, leaving uncharacterized any diversity that might exist between crystallites or even within individual crystals. Here we show that by using fluorescence imaging and lifetime analysis, both the spatial arrangement of functionalities and the level of defects within a multivariable MOF crystal can be determined for the bulk as well as for the individual constituent crystals. We apply these methods to UiO-67, to study the incorporation of functional groups and their consequences on the structural features. We believe that the potential of the techniques presented here in uncovering chemical diversity in what is generally assumed to be homogeneous systems can provide a new level of understanding of materials properties

    Big-Data Science in Porous Materials: Materials Genomics and Machine Learning

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    By combining metal nodes with organic linkers we can potentially synthesize millions of possible metal organic frameworks (MOFs). At present, we have libraries of over ten thousand synthesized materials and millions of in-silico predicted materials. The fact that we have so many materials opens many exciting avenues to tailor make a material that is optimal for a given application. However, from an experimental and computational point of view we simply have too many materials to screen using brute-force techniques. In this review, we show that having so many materials allows us to use big-data methods as a powerful technique to study these materials and to discover complex correlations. The first part of the review gives an introduction to the principles of big-data science. We emphasize the importance of data collection, methods to augment small data sets, how to select appropriate training sets. An important part of this review are the different approaches that are used to represent these materials in feature space. The review also includes a general overview of the different ML techniques, but as most applications in porous materials use supervised ML our review is focused on the different approaches for supervised ML. In particular, we review the different method to optimize the ML process and how to quantify the performance of the different methods. In the second part, we review how the different approaches of ML have been applied to porous materials. In particular, we discuss applications in the field of gas storage and separation, the stability of these materials, their electronic properties, and their synthesis. The range of topics illustrates the large variety of topics that can be studied with big-data science. Given the increasing interest of the scientific community in ML, we expect this list to rapidly expand in the coming years.Comment: Editorial changes (typos fixed, minor adjustments to figures

    Stepwise Maturation of Lytic Granules during Differentiation and Activation of Human CD8+ T Lymphocytes

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    During differentiation, cytotoxic T lymphocytes (CTL) acquire their killing potential through the biogenesis and maturation of lytic granules that are secreted upon target cell recognition. How lytic granule load in lytic molecules evolves during CTL differentiation and which subsets of lytic granules are secreted following activation remains to be investigated. We set up a flow cytometry approach to analyze single lytic granules isolated from primary human CTL according to their size and molecular content. During CTL in vitro differentiation, a relatively homogeneous population of lytic granules appeared through the progressive loading of Granzyme B, Perforin and Granzyme A within LAMP1+ lysosomes. PMA/ionomycin-induced lytic granule exocytosis was preceded by a rapid association of the docking molecule Rab27a to approximately half of the lytic granules. Activated CTL were found to limit exocytosis by sparing lytic granules including some associated to Rab27a. Our study provides a quantification of key steps of lytic granule biogenesis and highlights the potential of flow cytometry to study organelle composition and dynamics
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