41 research outputs found

    Co-delivery of human cancer-testis antigens with adjuvant in protein nanoparticles induces higher cell-mediated immune responses.

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    Nanoparticles have attracted considerable interest as cancer vaccine delivery vehicles for inducing sufficient CD8+ T cell-mediated immune responses to overcome the low immunogenicity of the tumor microenvironment. Our studies described here are the first to examine the effects of clinically-tested human cancer-testis (CT) peptide epitopes within a synthetic nanoparticle. Specifically, we focused on two significant clinical CT targets, the HLA-A2 restricted epitopes of NY-ESO-1 and MAGE-A3, using a viral-mimetic packaging strategy. Our data shows that simultaneous delivery of a NY-ESO-1 epitope (SLLMWITQV) and CpG using the E2 subunit assembly of pyruvate dehydrogenase (E2 nanoparticle), resulted in a 25-fold increase in specific IFN-Îł secretion in HLA-A2 transgenic mice. This translated to a 15-fold increase in lytic activity toward target cancer cells expressing the antigen. Immunization with a MAGE-A3 epitope (FLWGPRALV) delivered with CpG in E2 nanoparticles yielded an increase in specific IFN-Îł secretion and cell lysis by 6-fold and 9-fold, respectively. Furthermore, combined delivery of NY-ESO-1 and MAGE-A3 antigens in E2 nanoparticles yielded an additive effect that increased lytic activity towards cells bearing NY-ESO-1+ and MAGE-A3+. Our investigations demonstrate that formulation of CT antigens within a nanoparticle can significantly enhance antigen-specific cell-mediated responses, and the combination of the two antigens in a vaccine can preserve the increased individual responses that are observed for each antigen alone

    Two to Five Truths in Non-Negative Matrix Factorization

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    In this paper, we explore the role of matrix scaling on a matrix of counts when building a topic model using non-negative matrix factorization. We present a scaling inspired by the normalized Laplacian (NL) for graphs that can greatly improve the quality of a non-negative matrix factorization. The results parallel those in the spectral graph clustering work of \cite{Priebe:2019}, where the authors proved adjacency spectral embedding (ASE) spectral clustering was more likely to discover core-periphery partitions and Laplacian Spectral Embedding (LSE) was more likely to discover affinity partitions. In text analysis non-negative matrix factorization (NMF) is typically used on a matrix of co-occurrence ``contexts'' and ``terms" counts. The matrix scaling inspired by LSE gives significant improvement for text topic models in a variety of datasets. We illustrate the dramatic difference a matrix scalings in NMF can greatly improve the quality of a topic model on three datasets where human annotation is available. Using the adjusted Rand index (ARI), a measure cluster similarity we see an increase of 50\% for Twitter data and over 200\% for a newsgroup dataset versus using counts, which is the analogue of ASE. For clean data, such as those from the Document Understanding Conference, NL gives over 40\% improvement over ASE. We conclude with some analysis of this phenomenon and some connections of this scaling with other matrix scaling methods

    Assessing changes in global fire regimes

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    PAGES, Past Global Changes, is funded by the Swiss Academy of Sciences and the Chinese Academy of Sciences and supported in kind by the University of Bern, Switzerland. Financial support was provided by the U.S. National Science Foundation award numbers 1916565, EAR-2011439, and EAR-2012123. Additional support was provided by the Utah Department of Natural Resources Watershed Restoration Initiative. SSS was supported by Brigham Young University Graduate Studies. MS was supported by National Science Centre, Poland (grant no. 2018/31/B/ST10/02498 and 2021/41/B/ST10/00060). JCA was supported by the European Union’s Horizon 2020 research and innovation program under the Marie SkƂodowska-Curie grant agreement No 101026211. PF contributed within the framework of the FCT-funded project no. UIDB/04033/2020. SGAF acknowledges support from Trond Mohn Stiftelse (TMS) and University of Bergen for the startup grant ‘TMS2022STG03’. JMP participation in this research was supported by the Forest Research Centre, a research unit funded by Fundação para a CiĂȘncia e a Tecnologia I.P. (FCT), Portugal (UIDB/00239/2020). A.-LD acknowledge PAGES, PICS CNRS 06484 project, CNRS-INSU, RĂ©gion Nouvelle-Aquitaine, University of Bordeaux DRI and INQUA for workshop support.Background The global human footprint has fundamentally altered wildfire regimes, creating serious consequences for human health, biodiversity, and climate. However, it remains difficult to project how long-term interactions among land use, management, and climate change will affect fire behavior, representing a key knowledge gap for sustainable management. We used expert assessment to combine opinions about past and future fire regimes from 99 wildfire researchers. We asked for quantitative and qualitative assessments of the frequency, type, and implications of fire regime change from the beginning of the Holocene through the year 2300. Results Respondents indicated some direct human influence on wildfire since at least ~ 12,000 years BP, though natural climate variability remained the dominant driver of fire regime change until around 5,000 years BP, for most study regions. Responses suggested a ten-fold increase in the frequency of fire regime change during the last 250 years compared with the rest of the Holocene, corresponding first with the intensification and extensification of land use and later with anthropogenic climate change. Looking to the future, fire regimes were predicted to intensify, with increases in frequency, severity, and size in all biomes except grassland ecosystems. Fire regimes showed different climate sensitivities across biomes, but the likelihood of fire regime change increased with higher warming scenarios for all biomes. Biodiversity, carbon storage, and other ecosystem services were predicted to decrease for most biomes under higher emission scenarios. We present recommendations for adaptation and mitigation under emerging fire regimes, while recognizing that management options are constrained under higher emission scenarios. Conclusion The influence of humans on wildfire regimes has increased over the last two centuries. The perspective gained from past fires should be considered in land and fire management strategies, but novel fire behavior is likely given the unprecedented human disruption of plant communities, climate, and other factors. Future fire regimes are likely to degrade key ecosystem services, unless climate change is aggressively mitigated. Expert assessment complements empirical data and modeling, providing a broader perspective of fire science to inform decision making and future research priorities.Peer reviewe

    Consistent patterns of common species across tropical tree communities

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    Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe

    Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science

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    It is well documented that the majority of adults, children and families in need of evidence-based behavioral health interventionsi do not receive them [1, 2] and that few robust empirically supported methods for implementing evidence-based practices (EBPs) exist. The Society for Implementation Research Collaboration (SIRC) represents a burgeoning effort to advance the innovation and rigor of implementation research and is uniquely focused on bringing together researchers and stakeholders committed to evaluating the implementation of complex evidence-based behavioral health interventions. Through its diverse activities and membership, SIRC aims to foster the promise of implementation research to better serve the behavioral health needs of the population by identifying rigorous, relevant, and efficient strategies that successfully transfer scientific evidence to clinical knowledge for use in real world settings [3]. SIRC began as a National Institute of Mental Health (NIMH)-funded conference series in 2010 (previously titled the “Seattle Implementation Research Conference”; $150,000 USD for 3 conferences in 2011, 2013, and 2015) with the recognition that there were multiple researchers and stakeholdersi working in parallel on innovative implementation science projects in behavioral health, but that formal channels for communicating and collaborating with one another were relatively unavailable. There was a significant need for a forum within which implementation researchers and stakeholders could learn from one another, refine approaches to science and practice, and develop an implementation research agenda using common measures, methods, and research principles to improve both the frequency and quality with which behavioral health treatment implementation is evaluated. SIRC’s membership growth is a testament to this identified need with more than 1000 members from 2011 to the present.ii SIRC’s primary objectives are to: (1) foster communication and collaboration across diverse groups, including implementation researchers, intermediariesi, as well as community stakeholders (SIRC uses the term “EBP champions” for these groups) – and to do so across multiple career levels (e.g., students, early career faculty, established investigators); and (2) enhance and disseminate rigorous measures and methodologies for implementing EBPs and evaluating EBP implementation efforts. These objectives are well aligned with Glasgow and colleagues’ [4] five core tenets deemed critical for advancing implementation science: collaboration, efficiency and speed, rigor and relevance, improved capacity, and cumulative knowledge. SIRC advances these objectives and tenets through in-person conferences, which bring together multidisciplinary implementation researchers and those implementing evidence-based behavioral health interventions in the community to share their work and create professional connections and collaborations

    26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

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    This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

    Engineering Virus-Mimicking Protein Nanoparticles for Cancer Immunotherapy

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    The immune system represents a powerful resource for the eradication of cancer. To harness the full potential of this sophisticated network to overcome the low immunogenicity of tumor cells, a sufficiently strong cytotoxic CD8 T cell (CTL)-mediated adaptive immune response is required, which is partly orchestrated by the professional antigen presenting cells of the innate immune system, most notably the dendritic cell (DC). Protein nanoparticles represent a potentially exceptional vaccination platform for cancer, as they have the ability to mimic viral infections, which are known potent inducers of CTL immunity. We have been exploring the E2 protein nanoparticle as a delivery platform for antigens and immune-stimulating compounds. The E2 nanoparticle was successfully packaged internally with endolysosomal-releasable immune-activating DNA (CpG) and surface functionalized with MHC I-restricted peptide epitopes. The virus-mimicking nanoparticle induced DC activation at a 25-fold lower concentration compared to free CpG and induced a 3-fold increase in cross-presentation of attached epitopes, compared to free forms of peptides or activators. Furthermore, we demonstrated that co-delivery of melanoma-associated epitopes and immune-activating CpG with E2 enhanced antigen specific CTL proliferation index by 1.5-fold with a concomitant 5-fold increase in IFN-Îł cytokine secretion, compared to unbound peptide and CpG. Remarkably, a single immunization with the multifunctional E2 nanoparticle increased the frequency of melanoma-specific CTL in vivo (120-fold increase in the lymph node and 30-fold increase in the spleen) and the CTL generated showed approximately three times the lytic capacity toward a gp100-expressing melanoma cell line, compared to unbound peptide and CpG immunization. We were also able to tune cellular and immunological interactions toward the E2 nanoparticle with surface display of poly(ethylene glycol) polymers, where PEGylation through various methods (native surface amines or a recombinantly introduced cysteine) was shown to decrease cell uptake by greater than 50% of both mouse and human cell lines. PEGylation was also shown to mediate moderate increases in complement activation (~35% C5a production, compared to a known activator), a humoral innate immune mechanism, whereas E2 itself did not cause complement activation. Surface display of CpG on PEGylated E2 nanoparticles was shown to specifically increase cellular uptake by antigen presenting cells. Fluorescently-labelled E2 was shown to preferentially drain to the lymph nodes after subcutaneous administration, and surface PEGylation allowed further diffusion to more distal locations and blood draining organs. In contrast, surface display of CpG caused increased proximal lymph node accumulation, and demonstrated superior retention, with ~ 10-fold increase in LN fluorescence after 48 hours over the other nanoparticles. Within the lymph nodes, ~50% of the nanoparticles were associated with antigen presenting cells, including dendritic cells. Altogether, our results demonstrate the potential of the E2 protein nanoparticle as a versatile virus-mimicking immunomodulatory cancer vaccine platform. We have developed a nanoparticle biomaterial for DC-targeting, lymph node retention, and superior induction of CTL-mediated responses against cancer
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