Influenza A virus has two major envelope glycoproteins: HA and neuraminidase (NA). HA binds to sialic acid moieties of glycoconjugates of the host respiratory cells to initiate infection, whereas NA facilitates the release of progeny viruses from infected cells by cleaving sialosides. It is well documented that binding preference is a major determinant of influenza virus host range and avian viruses preferentially bind Neu5Acα(2,3)Gal, whereas human viruses bind Neu5Acα(2,6)Gal. This difference in specificity represents a barrier for transmission of avian viruses into humans. Glycan arrays have been used to assess influenza A virus receptor specificity. However, the currently available glycan arrays contain only a fraction of the glycans found on human airway epithelial cells and cannot uncover glycan binding specificities. Thus, we propose to develop an array that contains glycans representative of the structures found in human airways, since it is a priority in order to understand the biology of influenza virus transmission and pathogenesis. In addition, it has been described that there are two pathways by which influenza virus enters cells. It is believed that some N-glycans serve as attachment factors for concentrating virus particles on the surface of the host cells. However, only specific cell surface proteins modified by appropriate N-glycans can facilitate cell entry. The elucidation of the influenza virus receptor structure will unveil the mechanism at molecular level by which virus enters the cell. To this end, we will develop an experiment, which allows us to identify glycoprotein receptors of flu virus using cell surface glycan editing. The full comprehension of multi-branched glycans, along with the identification of the glycoproteins receptors of influenza virus, will allow the development of new and more efficient glycan-based therapeutics.

Forecasting the magnitude of future global warming is among the great scientific challenges. Model estimates of long-term warming resulting from a doubling of the CO2 concentration relative to the pre-industrial era range between 1.5 and 4.5 °C. This large uncertainty may represent the difference between the melting or conservation of large continental ice sheets, and between habitable and inhabitable regions. NESSC, the Netherlands Earth System Science Center, addresses climate-related research questions, dealing with past, present and future interactions between the geosphere, biosphere, hydrosphere, cryosphere and atmosphere. Specifically, NESSC studies the response of the Earth System to perturbations and will merge information obtained from past climate, using climate proxies, with data and models for the modern climate. NESSC brings together renowned experts in the fields of palaeoclimate proxies, climate reconstructions, biogeochemistry, microbiology, and theory and modelling of climate. These experts join forces to obtain novel insights in climate research. All scientists involved have ample experience with supervising PhD students and leading successful research groups. Through COFUND NESSC will expand its research and training programme internationally, with an additional 13 Early Stage Researchers. NESSC will significantly advance our understanding of the Earth System functioning in the future. The COFUND programme is tightly connected with multiple national and international partner organisations, each providing complementary research and/or training. Through COFUND NESSC will maintain and further expand its excellent worldwide position.

Our daily lives are full of decisions for which we could take an infinite time in order to decide as accurately as possible. However, different speed and accuracy constraints, tied to the type of decisions, the decision-maker and his environment, are limiting the time allocated. How decision-makers deal with this speed-accuracy tradeoff is an important cornerstone for the sciences studying decision making such as psychology, cognitive neuroscience and artificial intelligence. One particularly successful proposal of formal decision-making models is to assume that decision-makers are reducing or increasing decision thresholds to adapt to the speed and accuracy constraints. But recent evidence shows that this strategy is insufficient to explain the full range of behavioral and physiological data in decision tasks. The present proposal suggests, based on new studies, that speed-accuracy tradeoff is achieved by varying the reliance on three different response strategies: guessing, immediate evidence accumulation and delayed evidence accumulation. Using an interdisciplinary approach, involving experimental psychology, mathematical psychology along with cognitive neuroscience and artificial intelligence, the project aims at providing a broadly applicable framework to detect, measure, and estimate the reliance on the three strategies along with the description of the psychological processes behind these. This project will train a promising cognitive psychologist and neuroscientist to apply advanced methods in a unique and fruitful research environment linking the four disciplines. It will also provide the host organisation with new tools to study latent cognitive processes in cognitive tasks. Overall, the project will constitute an innovative approach to decision making with broad applicability, likely to increase the description and predictions we can make of behavior and psychological processes involved in decision making, in conjunction with inter-individual differences.

Increases in cultural and linguistic diversity worldwide pose major challenges for universities to promote diversity, equity, and inclusion (DEI). Universities prioritize safety on campuses, but that process is severely hindered as many students of color face racial microaggressions daily, which impairs interethnic relationships and socio-academic adjustment. Thus although diversity is often expected to enhance inclusion and academic excellence of ethnic minorities, it is paradoxically linked to their exclusion and academic failure instead. This raises the question: How can universities create sustainable academic communities that promote DEI for all students? A promising method is living-learning communities (LLCs) which, unlike traditional residential housings, are specialized social settings centered on distinct academic themes that connect students’ experiences. LLC advocates argue that students develop a strong sense of belonging, learn how to think critically about social justice, and take multiple perspectives and develop a greater connection and better communication with other students. If this is true, do LLCs help prevent racial microaggressions among students who participate in such communities? And if so, how? That is, what are the key mechanisms? This study answers these questions through an innovative social network approach. Findings and mechanisms may be applicable to develop network interventions for integrated communities.