Luxembourg National Research Fund

This project aims to uncover the interdependencies between economic concentration, labor mobility, housing market developments and inequality. It focuses on the economy of Luxembourg and the Greater Region, characterized by high economic growth, booming housing prices and dynamic labor mobility (through both immigration and cross-border commuting), features that can also be observed in other regional poles of growth around the world. The project aims to shed light on the sustainability, drivers and distributional effects of the core-periphery developments observed in the Greater Region. This requires to collect and merge data from several sources as well as to develop state-of-the-art empirical and theoretical methods to understand causation links and interactions between variables. The project proceeds in three steps. A first work-package focuses on the determinants of labor mobility and consists of two tasks: (i) collecting and harmonizing data on cross-border mobility, housing prices, economic opportunities in the Greater Region between 2005 and 2020; (ii) developing an empirical strategy to understand workers’ joint decision to commute or to change residence. A second work-package examines the welfare and distributional impacts of labor mobility and the implied housing market developments by: (i) empirically assessing the role of massive labor inflows on the domestic labor market, (ii) estimating the effects of economic growth and labor mobility on real estate prices. Finally, the last work-package explores the interdependencies between growth, labor mobility and housing market developments in a general equilibrium setting. It consists of two tasks: (i) quantifying the welfare and distributional implications of the Luxembourg “growth miracle” using a macroeconomic model accounting for various interactions; (ii) using the model to anticipate future trends and investigate the consequences of policy reforms as well as changes in the sociodemographic and economic environments in the Greater Region.

This research program proposes extensions of the use of the Cross-Nested Logit approach to the modelling of location choices. The CNL allows to better capture the stochastic structure of these choices through the use of overlapping nests of alternative locations and to account for deviations from the property of independence of irrelevant alternatives. The research program extends the recent work of Beine, Bierlaire and Docquier (2021). This work might be seen as pioneer work that allows to address important issues like the substitutions across alternative destinations. It nevertheless leaves many issues unaddressed. In this research program, we tackle the most pressing issues of the use of the CNL. It will first evaluate the transferability of the CNL to other contexts than the particular case of India. It will develop the technique of alternative sampling to include a comprehensive set of destinations within the CNL. It will improve the specifications, in particular by modelling perceptions of individuals through latent variables and it will evaluate the relevance of using preparation plans for migration rather than pure intentions in capturing self-selection factors of mobility. The program will run for a period of 36 months and will feature a close collaboration between two teams, one located at the University of Luxembourg and one located in Lausanne at the Ecole Polytechnique Fédérale.

Growing economic inequality and low social mobility raise important concerns about social cohesion; and require tracing individuals back to their social origins to address inequality of opportunity that can affect their potential to succeed in life. ORIGINS will expand and deepen our knowledge on the causes of inequality and its persistence by studying the influence of social origins on individual socioeconomic trajectories. Unpacking the origins of existing inequalities and the way in which they are passed on from parents to children is key for understanding their consequences for social cohesion in the long run.

ORIGINS focuses on three key stages of the family life cycle along which parental choices may exert a long run influence on the well-being of their offspring: (i) through parental marital choices, (ii) through offspring childbearing and childrearing and (iii) through offspring entry into the labour market. ORIGINS will provide the first evidence on the role of parental mating choices and the role of parental labour market networks for children’s life cycle earnings; and will offer a unifying framework for the relative impact of genetic endowments and environments provided by parents on several child outcomes such as education, earnings and wealth, offering new insights on an old question with the aim to reconcile previously inconclusive evidence.

ORIGINS has two distinctive features: (i) it deploys high quality register data from Denmark that enable linking parents to their children across their entire life on several socioeconomic outcomes such as education, income and wealth; and (ii) it develops an innovative econometric framework to apply these data based on a model of intrafamily labour earnings dynamics. Although Denmark is a welfare state with generous support of childcare and education, it is well documented that family background still matters for individual success. Detecting the mechanisms of intergenerational mobility in the context of Denmark, can therefore offer important insights for higher inequality and lower social mobility countries including Luxembourg, which is one of the countries with the lowest degree of social mobility across generations in Europe.

Gaining a firm understanding of the extent to which different aspects of social origins matter for the observed intergenerational persistence and socio-economic inequalities, can inform policy makers designing public policies to support disadvantaged children, and address low social mobility and existing inequalities

Extreme temperatures have become more frequent over recent decades, with the trend expected to continue into the future. Prior evidence has shown that extreme temperatures alter the way in which individuals allocate their time between leisure and work, which can have important implications for the labor market and well-being. A much less explored phenomenon is whether extreme temperatures have an effect on how individuals arrange their time within the leisure and work dimensions. In the leisure domain, it is important to understand the effect of temperature on social interactions, as these are an important determinant of employment and well-being. In the work domain, it is important to understand the effect of temperature on worktime arrangements, as these can influence productivity and career advancement.

This project is divided into three work packages (WPs), and provides evidence on the causal impacts of extreme temperatures on (i) social interactions and (ii) worktime arrangements, as well as (iii) whether these effects have long-term implications for well-being.

WP1 examines the causal impact of extreme temperatures on social interactions, by studying whether extreme temperatures alter the amount of time individuals spend alone, and with family and friends. The analysis relies on daily-individual data from the American Time Use survey (ATUS) linked with county-daily data on U.S. weather conditions obtained from the National Oceanic and Atmospheric Administration (NOAA), which acts as the source of identification. In WP1, we also offer an explanation of possible temperature effects on joint time use, using a theoretical model that provides testable implications, which we investigate using ATUS data. WP2 examines the causal effect of extreme temperatures on individuals’ worktime organization across three main dimensions: (i) place of work, (ii) work schedules, and (iii) number and length of breaks taken during work. The analysis, which explores heterogeneity by industry and level of education, is based on a sample of individuals who work on the time diary completion date taken from ATUS data, which we combine with variation in temperature on the time diary completion date and month prior to it, at the U.S. county level. WP3 provides novel evidence on the short, medium, and long-term causal effects of extreme temperatures on flexible types of employment, life satisfaction and mental health. The analysis uses two large panel datasets from the U.S. Panel Study of Income Dynamics and the German Socio-Economic Panel surveys that follow individuals on an annual basis over a 30-year period. We combine these two panels with data from the NOAA and German Weather Service on yearly temperature distributions across U.S and German counties, respectively. Estimating the analysis separately for each of these countries allows to study whether the dynamic effects of extreme temperatures on type of employment and well-being differ between the U.S. and European contexts.

The scientific contribution of the project is to provide novel evidence on the causal effects of extreme temperatures on social interactions and worktime organization as well as on their dynamic implications for type of employment and well-being. This will contribute to the design of more efficient public policies addressing the potential detrimental effects of extreme temperatures on the examined outcomes, thus leading to better functioning labor markets and increased welfare. The results of the project may also assist policy-makers by providing insights for future discussions on climate change using a perspective that has not previously been explored. The contributions of the project are relevant for any advanced economy, given that global warming is an international phenomenon.

The digitalization of economic activities is one of the major transformations of developed economies over the last decade. Digitalization changes the task content of occupations and modifies the portfolio of skills required on labor markets. This gives rise to hiring difficulties that now represent one of the top challenges cited by employers.

Digitalization affects labor market tightness in a specific way. The adoption of new digital technologies increases the number of skills required on labor markets without completely removing the older ones. Thereby, the labor demand for the corresponding occupations grows faster than the labor supply and explains a part of hiring difficulties observed on labor markets. This project aims at documenting this mechanism and at investigating its labor market implications on workers and firms.

In this project, we will take advantage of new digital tools to study the labor market effects of digitalization. In particular, we will use large online job posting databases collected with web-scraping alike algorithms to measure labor market tightness. Our contribution will then consist in developing an instrumental variable approach to assess the causal effects of labor market tightness on workers and firms. We will build on this identification strategy to document the labor market impacts of hiring difficulties that have mostly been overlooked in the academic literature. We will first use this approach to investigate the causal impact of recruitment challenges on wage inequalities in France. We will also exploit this setting to study its effect on firms’ productivity and innovation in Luxembourg. In addition, we will explore the mitigation strategies adopted by firms to cope with recruitment challenges. In particular, we will compare the results associated with firms’ training, outsourcing, and the recruitment of foreign-born workers. Comparing the French and the Luxembourgish contexts will add to our understanding since the labor market structures in each country are very different. Finally, we will document the cause driving the positive relationship between labor market tightness and the demand for foreign skilled workers in the United States.

Letterboxes, representing shell companies, are an emblematic symbol for a form of international capitalism that has come under increasing scrutiny in recent years and serve as a focal point for international criticism of the Luxembourgish financial system. LETTERBOX is an innovative project that mixes recent questions in financial history with cutting-edge digital history. The banking crisis of 2007/2008 and the ensuing increasing public debt as well as the scandalisation of financial practices (Luxleaks, Panama Leaks, Paradise Papers, OpenLux) has put the question of fiscal tax optimisation at the forefront of societal discussions. In these narratives, Luxembourg, through flexible legislation on companies, plays a pivotal function. Thanks to a unique digitised corpus – Annexe du Mémorial et Mémorial C (1929-2016) – LETTERBOX will situate Luxembourg in a global financial geography and unveil the local ecology of lawyers, notaries and accountancies in a historical perspective. This is however only possible to achieve by incorporating computational means that allow one to automatically annotate and extract persons, places and organisations as a basis for analysis and exploration and so unveil these hidden infrastructures. LETTERBOX will build on the existing know-how of the C2DH in the extraction of entities in large-scale corpora and will refine existing as well as new analytical approaches for analysing the data through specific interfaces. The project will make extensive use of co-design principles in order to develop interfaces that are tailor made for cross-referencing heterogeneous structured, semi-structured and unstructured data.

One of the most noteworthy secondary effects of the ongoing covid-19 pandemic has been the sudden emergence of large-scale teleworking. It was striking to see how sanitary considerations could – within days – radically transform the way in which large parts of the European population performed their work. As such, teleworking in pandemic times has raised fundamental questions on the essence of “the office” as both a social and material phenomenon.

By taking a historical approach, BUREU will contribute to our understanding of the roots of current society’s complex relationship with “the office”. Concretely, we will explore the office buildings of the European Union in Luxembourg, Brussels, and Strasbourg. The EU and its legal predecessors have been unique in history: singular in the way an additional, before non-existent political layer affecting the lives of all Europeans was given shape; singular in the way a transnational administrative framework was created; and singular in the way far-reaching plans for political integration and piecemeal organizational expansion were to be reconciled in office architecture. By investigating this latter dimension, with a specific focus on EU office interiors (1950s – early 2000s), BUREU will not only add to research on the histories of office architecture and cultures of office work, but also to research on the history of European integration.

We will develop an innovative analytical framework which combines historiographical approaches on (a) the office as a “technical-organizational complex” and (b) the role of material infrastructures as driving forces behind European integration processes. Using a set of metaphors from the field of informatics, we contend that EU office interiors were “interfaces” where the material dimension of architecture (“hardware”) and the immaterial managerial programme (“software”) met. We hypothesize that managerial programmes (a) functioned as normative ideological frameworks for the creation of “efficiency”, and (b) had an impact on interior design choices, as well as on the administrative work performed in the office buildings. For a selection of five EU institutions (Parliament, Commission, Council, Court, and European Investment Bank), we will analyse which design choices were made regarding the office interiors, and if these were perceived as successful. This way, we will be able to answer the question if the EU’s political aim of operational efficiency also found a counterpart in the organization’s office interiors.

In order to understand how EU office buildings were (re)designed with the aim of enabling operational efficiency, and how the impact of office architecture on the EU’s administrative functioning was perceived, we will look at the epistemic communities involved in these processes. We will take into account the discourses and activities of (a) architectural clients, (b) various professional groups vying for influence and power in the sphere of office development and/or design (architects, managerial specialists, etc.), and (c) a crucial category of users (the so-called “Heads of unit”, who had the discretionary power to take decisions on spatially-related organizational matters). Our empirical component will be based on archival sources and oral history.

By combining the specific expertise of the PI (digital history and the history of technology), the co-PI (history of architectural expert networks and political European history), and the postdoctoral researcher (history of government office buildings), we ensure to meet the conceptual challenges coming with our methodological approach.

Since the end of the Cold War, international courts and tribunals enjoying jurisdiction over complaints by private persons against sovereign states have played an increasingly important role. This is especially true in Europe, which is often said to have pioneered this practice in the 1950s. It is true that post-WWII gave rise to the European Court of Justice (ECJ) in Luxembourg and the European Court of Human Rights (ECtHR) in Strasbourg. It is also true that the first generation of European integration lawyers heavily insisted on the novelty of post-WWII European supranational courts and tribunals, thus shaping an institutional narrative that is now firmly established.

Empirical evidence shows that this narrative needs to be largely qualified. Indeed, both within the colonial context and in interwar Europe, several treaty regimes had already established internationally composed judicial or quasi-judicial institutions endowed with jurisdiction over claims by private persons and groups regarding individual rights against sovereign states. In other words, a form of supranational judicial practice had already developed well before the 1950s. Despite their pioneering role and their direct links with the architects of post-WWII courts and tribunals, these early international courts have today largely disappeared from collective memories.

FoMeSA aims to assess the continuities and discontinuities between these institutions and present-day European and international courts. By reviving the forgotten memories of the international and European legal community, by offering new historical comparisons and inviting the public to explore ways of re-integrating them into institutional memories, it will also contribute to present-day debates on the role and legitimacy of international courts and tribunals.

Buildings account for a significant part of global energy demand and greenhouse gas emission (GHGE). Renewable energies and associated technologies are key to long-term climate change mitigation, as they provide new ways to produce, store and control how energy is used. However, it is not only a matter of using renewable technologies, but also of optimizing the charging/discharging strategy of local storage units (e.g., during off-peak times, it could be sensible to draw power from the electrical grid rather than from the battery to power the loads, as it may result in lower GHGE and costs in the medium run). A number of optimization models have been proposed in the literature, and, although they may differ in terms of required infrastructure and targeted fitness goals, they are often faced with two major drawbacks:

– Computational complexity: charging optimization models are known to be NP-hard, and require Machine Learning to forecast future parameters like anticipated energy demands. Due to the large computational needs, most of the approaches rely on Cloud computing (using powerful computational servers), but this model suffers from several weaknesses such as limited bandwidth resources and latency, along with privacy concerns (e.g., inhabitants’ energy consumption profiles are sensitive data);

– Sub-optimal system level performance: most of the state-of-the-art optimization models are designed based on individual goals/constraints, leading to optimal charging actions at the household (nanogrid) level, but not necessarily at the global level (e.g., considering a shared goal at the microgrid or grid level such as minimizing electricity providers’ procurement costs, or complying with CO2 regulations). This leads to the dilemma of sacrificing some of the individuals’ profits for the collective social welfare, which can be formalized as a distributed charging optimization problem.

To overcome these limitations, the LightGridSEED project, standing for “Lightweight collaborative nanogrid controllers for global Greehouse gaS Emission rEDuction”, is committed to investigate and design a new type of controller at the household (nanogrid) level empowered with four key abilities: (a1) Self-adaptive: it can self-adapt to any changes occurring in its environment; (a2) Eco-friendly: it can act in a sustainable way; (a3) Sociable: it can interact and collaborate with other controllers to achieve a global (shared) goal; (a4) Robust: it can overcome uncertainties and disturbances through coalition and collaborative efforts. Towards these desired abilities, two research questions aim to be addressed:

RQ1: How edge (fog) computing can be efficiently integrated into future nanogrid controllers to make them highly self-adaptive (a1)?
RQ2: How blockchain technology and distributed optimization theory can be combined in an eco-friendly manner (a2) to empower future nanogrid controllers with high social (a3) and collaborative robustness (a4) abilities?

From a scientific viewpoint, LightGriSEED contributes to extend the state-of-the-art in two-respects. First, it investigates novel combinations of model compression techniques and offloading/transfer learning strategies using Deep Learning (DL), whose key challenge is to optimize how to devise edge computing architecture to achieve the best performance of DL training and inference under the multiple constraints of networking, computing power, communication and energy consumption. Second, it investigates how to mitigate the impacts that the blockchains used in prosumer energy markets could have on the overall system performance (from a CO2, computational delay and financial viewpoint). The theories and algorithms developed in the project are experimentally tested and validated based on (i) secondary (scientific) data to allow for scientific benchmarking; (ii) real-life data coming from real-life renewable houses located in Biekerech/Saeul in collaboration with Energipark s.a.

FINCITY is a multidisciplinary research project that focusses on how major global events coincide with broader processes of economic restructuring and financialisation in Luxembourg, Frankfurt, and Dublin—three of Europe’s most significant financial centres. More specifically, it aims to understand how these cities and other major European financial centres have been restructured in response to Brexit— which has expelled a large number of financial services firms from the UK, and COVID-19— which has redistributed population away from major urban centres toward smaller agglomerations (McCarthy and Smith, 2020), and fundamentally altered the ‘labourscape’ in favour of telework (Belzunegui-Eraso and Erro-Garcés, 2020). The project is inspired by the dual nature of current conditions in continental European financial centres. On one hand, Brexit acts as a centripetal force, attracting large numbers of firms and employees to Luxembourg, Frankfurt, and Dublin (among other cities). To date, 7,600 financial sector jobs and €1.5 trillion in assets have relocated from London (Jones, 2021). According to The Financial Times, Luxembourg “has emerged as one of the biggest winners from the shift out of the UK: 72 companies, nearly all of them in financial services announced plans to relocate their EU operations from London” (Stafford, 2020). Similar figures support the migration of firms and their employees to the Dutch and German financial hubs. On the other hand, COVID-19 acts as a centrifugal force, with strong evidence suggesting that the cumulative impacts of telecommuting, firm restructuring, long-distance commuting, and firm decentralisation are likely to cause de-agglomeration. Within Europe, a recent EU report found that while only 15% of employees had teleworked before the pandemic, 25% of jobs were ‘teleworkable’ (Fana et al., 2020). Of the EU member states, Luxembourg has the highest proportion of jobs fit for telework (Fana et al., 2020). Similar patterns have emerged in the United States, where cities such as Austin, Texas, and Boise, Idaho, have absorbed a large number of Silicon Valley firms and workers, many of whom may never return to the office. In Europe, further decentralisation is possible if banks’ back-office staff are permanently dislocated from central offices. To explore the socio-spatial impacts of the current state of affairs, this project first builds an updated profile of each financial centre by investigating how the corporate geography of banks and financial services firms has changed over the past five years. Firm-level data will be compiled from various proprietary databases with a view to understand how Brexit and COVID-19 have reoriented the character and composition of advanced producer services within each city. Second, the reorientation of each city’s services agglomeration will be related to its spatial impact through a detailed investigation of local property markets as key indicators. The nature of commercial property has changed considerably with a pivot to teleworking, larger floorplates (allowing for distancing) and the requirements of global firms whose footprint extends far beyond the walls of their offices. Residential property has also been brought into sharper relief, with a greater preference for working from home, meaning that proximity to urban centres is potentially less important than space. Based on a combination of empirical data, extensive stakeholder interviews and focus group meetings, we interrogate which changes may play out in each market’s property sector, and how these relate to both global and industry trends. Finally, given the importance of regulation, the project concludes by investigating how policymakers have responded to these multiple crises and their significance for urban policies.

Food systems play a complex role in the current environmental crisis: they are simultaneously victims of climate change, one of its causes, and they can represent one of the possible solutions to tackle it. If cities want to develop sustainably, then, they have to start thinking seriously about what they eat. A growing number of citizen-led initiatives in cities, and a much more limited number of initiatives by city administrations, are attempting to transform urban food systems to make them more sustainable. However, their impact and scope remain limited. Furthermore, consumers’ demands for more sustainable food risk adding a further, also moral, burden on food producers who already struggle between market imperatives and changing environmental conditions. If those initiatives fail to integrate the different needs and perspectives of food producers, they in fact risk digging even deeper divides within food systems, leaving many food producers behind and stifling their willingness to embrace sustainable solutions. The goal of the SUSINU project is to conceive and design alternative food systems as a way to tackle the current environmental crisis. Specifically, SUSINU aims to contribute to the development of urban food systems that are 1) actively promoted by urban policymakers; 2) more sustainable, in that they can adapt to and at the same time mitigate climate change; and 3) more inclusive in that they integrate the perspectives of different typologies of food producers. In the context of two cities in Luxembourg and in Switzerland, SUSINU assesses current urban food policies, analyses the role and experiences of food producers in them, and together with policymakers and key stakeholders, collaboratively develops innovative alternatives for urban food policies and systems. The project adopts a relational perspective on cities and food systems, applying a mix of qualitative methods within a transformative research approach. The project thus enriches current academic and public debates on sustainable food systems, especially in three regards: 1) it innovatively reflects on how to translate a relational understanding of cities into effective, sustainable and inclusive urban food policies; 2) it actively mobilises urban policymakers in these reflections, thereby challenging their common neglect of food issues; and 3) it rebalances the mainly consumer-oriented focus of alternative food initiatives by focusing on food producers and by actively integrating their perspectives into the design of urban food policies.

The pandemic has revealed preferences for greater levels of teleworking (working from home). With many workers and employers in favour of more teleworking post-pandemic, this will have consequences for how cities organise themselves. Therefore, the impact of teleworking on urban structures in the post-pandemic city requires further empirical testing for Europe. Teleworking decreases commuting costs, making longer commutes more affordable. Lower commuting costs increase the household budget for housing enabling people to move to larger less expensive houses in the suburbs. These factors will influence the population density profile. Teleworking may cause greater levels of dispersion and sprawl, with cities becoming less compact, challenging the sustainability levels of cities. This project contributes in several innovative ways. Firstly, we contribute to the teleworking literature adopting a nomothetic approach common in urban analytics; we simultaneously examine the internal urban structure under several scenarios for a large sample of European cities (400+). Secondly, we contribute to the scaling literature by providing the first examination of house price profiles and their gradients with a focus on the internal structure of cities. Thirdly, we challenge the current definition of cities, which use a functional urban area approach and commuting thresholds. With less commuting, these definitions no longer seem appropriate. Teleworkers have greater residential choice expanding the fringe distance and city extent. Several important research questions are addressed. How is residential choice and commuting distance affected by teleworking? Will house prices decrease in the centre and increase in the periphery? Will teleworking have a differential impact on density profiles across the city size distribution (small cities versus big cities) and across regions? To address these questions, this project will examine the internal structure of cities using a monocentric approach from city science and urban analytics, GIS methods, web-scraping techniques, hedonic models and data simulations. Commuting costs and house prices are used as tools to simulate changes in the density gradient and profile. Different teleworking scenarios are analysed, reflecting the teleworking potential of the city (share of jobs in retail, professional services etc.), on the density profiles of cities. Using a large sample has the additional advantage of providing statistical significance and generalisable results. From our results, we can say with a greater level of certainty what the impact of teleworking on density is for European cities. One of the major outputs from the project will be a dashboard that will disseminate the results, research and data to both an expert and non-expert audience supporting open-source reproducible research.

The transition towards affordable, secure and clean energy is a key pervasive societal need and challenge, which requires bridging several knowledge gaps. To bridge some of these gaps, this project proposes a new approach to manage on short-term the overall electrical grid in a secure manner, making optimal use of the energy flexibility of various distributed energy resources (DER), e.g. renewable energy sources (e.g. wind, solar), which are present in active distribution systems (ADSs) managed by distribution system operators (DSOs). These DER are typically not visible to the transmission system operator (TSO), which is a major loss of opportunity because they can be effective additional control means to enhance secure operation of the transmission grid and reduce its operation cost. Currently the necessary knowledge and methodologies to make use of this flexibility for maintaining security are under development.

The project addresses this timely research gap by responding in an integrated way three fundamental questions:
Q1: What enhancement of probabilistic security metric is needed to factor in ADS flexibility?
Q2: How should a DSO quantify the flexibility of an ADS (meeting the ADS constraints) at the interface with the TSO in terms of active/reactive powers capability chart over time?
Q3: How to extend the TSO’ security management tool, i.e. security-constrained optimal power flow (SCOPF), to incorporate in a scalable way the enhanced security metric and ADS flexibility at TSO-DSOs interfaces in a look-ahead (multi-period) short-term timeframe?

A specific objective corresponds to each research question, as follows:
O1: Develop an enhanced risk-based security metric accounting for ADS flexibility.
O2: Design a methodology to compute the active/reactive power chart of an ADS at the interface with the TSO.
O3: Develop a tractable methodology for short-term multi-period SCOPF-based security management embedding the enhanced security metric and active/reactive power chart at TSO-DSO interfaces.

The new proposed security management approach raises scientific and computational challenges such as: intrinsic problem complexity in terms of comprehensiveness and diversity of relevant features to incorporate, and thereby the suitable problem formulation, and the large problems size, unmanageable by state-of-the-art solvers.
The project is unconventional in two fundamental aspects: (i) it proposes two new (nested) frameworks: the holistic security management approach (not addressed so far), including an enhanced security risk metric, and ADSs flexibility provision at TSO-DSOs interfaces (timely topic) to support security (partially explored), and (ii) it explores suitable methodologies (trading off accuracy and speed) with various original features to solve these problems.

The project tackles challenging major research and industry needs, which are often neglected in academic research: the integration of security in operation and the complex nature of doing so in a holistic manner, including TSO and DSOs. The most important impact on the academia is to generate new knowledge in terms of security criteria and the associated look-ahead optimization routines, which could change the manner in which power systems will be operated.

The impact on the industry lies on (i) bringing further evidence that computationally tractable and sufficiently accurate models are possible to address security management in a holistic way, (ii) prove quantitatively that a departure from the deterministic N-1 criterion is necessary in the context of large shares of RES, and (iii) assess the project benefits on real-world data provided by CREOS, the TSO/DSO in Luxembourg, in addition to abundant open-source data sets from the literature. The impact on the industry will be analyzed with CREOS, ENTSO-E and Croatian DSO.

The project will allow accommodating more renewable energy in the power system in a cost-effective manner while maintaining system security.

In Europe, as well as around the globe, increasing resource efficiency to enable sustainable economies is a pressing issue. The transition towards a more circular economy is seen as a key element to achieve a high degree of resource efficiency. Material cycles, where waste is minimized and turned into resources, can be used in production processes and thereby increase overall resource productivity. Environmental impacts often decrease with increasing circularity, but there are also tipping points, where more recycling does not lead to better environmental performance. In addition, conventional models often consider infinite recycling loops with no loss of quality, which has recently appeared as not representative of real-world processes (where collection, sorting, quality, purity… are almost always overestimated). Additionally, implementing circularity measures in long-lived potentially leads to the treatment and/or reintroduction of legacy contaminants.

Based on this context and identified research gaps in the state of the art, the consortium, composed of researchers from LIST and the University of Kassel, aims at answering the following research question: what are the potential sustainability issues arising, over time, with the increasing reuse, recycling, and reprocessing of materials, in particular in the case of plastics and the hazardous substances they may contain, in buildings and infrastructure? The objectives are three-fold: 1. To develop a consistent assessment framework for considering material flow dynamics and life cycle impacts of long-living anthropogenic resource systems, 2. To (simultaneously) model substance, goods, and product cycles in order to quantitatively and qualitatively account for recycling loops and issues of downcycling, with uncertainty considerations, in relation with past and current substance regulations, allowing for a policy analysis on legacy contaminants, 3. To apply the developed model to material use in the B&I sector in two case studies on plastics, from a material perspective (PVC) first, and then from a product (tubes and pipes) perspective, to illustrate its use as a circular economy decision-support tool. The proposed research will enable assessments of circular economy strategies integrating material efficiency and environmental impacts from a systemic perspective. The model will allow for a comprehensive evaluation of re-use, recycling and other waste utilization options, which is essential to raise recycling levels (as required by EU policy directives) and at the same time improve environmental performance whereby efforts for (and impacts of) enhanced recycling must not offset gains by secondary production. The team at University of Kassel will lead tasks related to system dynamics modelling, as well as data collection. LIST will coordinate the project, enrich the model with environmental impact assessment modules, as well as developing the software. The outcomes of the project will be of relevance to the scientific community (ensured by the scientific advisors), the stakeholders of the B&I sector (guaranteed by their involvement in the projects from the outset and several participatory workshops), as well as policymakers and the public.

Environmental, Social and Governance (ESG) metrics overwhelmingly rely on company-disclosed policies that are then used to assess companies’ exposure to financially relevant ESG-related risks and opportunities. The absence of widely-accepted standards that define a company’s ESG profile further exacerbates the bias resulting from self-reported data. Our suggested research project´s overarching objective is to promote the understanding of the role of public and private sources of financing in the efficient allocation of capital aimed at the transition of the world economy to a sustainable path. The goal will be reached by the following fivefold contribution:

(1) Identify the fundamental sustainability impact of a company through the products and services it offers along the dimensions of the 17 UN Sustainable Development Goals (SDGs);

(2) Evaluate the extent of the divergence between self-reported sustainability practices of companies and estimates of their fundamental sustainability and investigate the implications stemming from that disagreement on the misallocation of capital to sustainable projects and companies;

(3) Assess the sustainability footprint of ESG-labelled Exchange Traded Funds (ETFs) through the companies they hold, investigate the dimensions of ESG score metrics that are material for investor flows and quantify the potential for capital misallocation due to mismatch with funds’ stated objectives or ESG labels;

(4) Provide a framework for the assessment of the sustainability alignment of infrastructure assets and the role of ESG considerations in the flow of institutional investor capital to the asset class;

(5) Provide a modelling framework to address the implications of company sustainability scores and their divergence on corporate bond values and the pricing of credit risk.

Nanocelluloses are nanosized features of crystalline or fibrillar form that exert interesting intrinsic properties such as high surface area, crystallinity, wettability and mechanical strength. As a common practice, nanocellulose is formed through the hydrolysis of cellulose by means of acidic or enzymatic media. Nanocelluloses are deployed as active or inert fillers in functional nanomaterials and nanoscaffolds for a broad range of applications. Owing to their nanoscale size and good wettability, nanocelluloses can also be applied as solid interface stabilising agents known as Pickering particles.

Green chemistry inspired solvents such as deep eutectic solvents (DES) have gained a lot of ground against organic solvents as they are inexpensive, low vapour pressure, non-flammable, chemically and electrochemically stable, recyclable, biodegradable, water neutral and toxicologically well-characterised. Besides, DES can be naturally synthesised by sustainable bioresources (e.g. primary metabolites of plants and microorganisms), i.e., NADES. Transformation of recalcitrant biomass resources, e.g. wood, paper, agri-food side streams or food waste etc., into added-value products via DES deployed biorefinery strategies is an emerging field of research innovation actions.

DEEPCELL project aims at exploring the potential of combined NADES – physical processing (microwave, ultrasound and micro-fluidisation) strategies for green transforming microcrystalline or microfibrillar forms of cellulose-rich substrates (e.g. obtained from industrial waste side streams such as wood, paper or agri-food waste) into Pickering particles for nutraceutical, cosmetic or drug delivery applications. An optimisation plan based on a Design of Experiments – Artificial Neural Networks (DoE-ANNs) approach will be adopted to define the optimum conditions for producing cellulose nanocrystals and nanofibrils of desirable intrinsic properties i.e., morphological aspects, wettability and cytotoxicity. A Life-Cycle Analysis driven jack-knifing strategy will be implemented for identifying nanocellulose candidates of minimal ecological footprint. The LCA screened cellulose nanocrystals and nanofibrils will be fully characterised in terms of their chemical structure, molecular, interfacial, and self-assembly NADES endowed properties. For the first time, NADES/physical processing obtained nanocelluloses will be tested for their Pickering particle interface stabilising efficiency in o/w emulsions of nutraceutical/drug delivery purpose. The interface stabilising role of the nanocellulose will be tested under accelerated storage conditions and simulated in-vitro digestion conditions. The biocompatibility, e.g. cytotoxicity, proteomic response, cell barrier integrity, mucoadhesion, and the ability of nanocellulose to modulate the uptake of a model drug compound (squalene), will be tested using a triculture (Caco-2, HT-29 and Raji B cells) model of the human intestinal epithelium. Also, the ability of the nanocellulose particles to affect the species diversity of a synthetic model of the gut microbial ecosystem will be investigated. Conventionally produced cellulose nanocrystals and nanofibrils, e.g. concentrated acid and cellulase assisted hydrolysis, will be employed as reference Pickering particles material.
DEEPCELL aspires to provide proof-in-principle evidence of the feasibility of NADES combined with soft processing unit operations for the production of sustainable, ecologically resilient, biocompatible and biologically active Pickering particles.

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease in the aging population. Mutations in the gene encoding for the leucine-rich-repeat-kinase-2 (LRRK2) protein, especially the G2019S, have been identified as a cause for a familial form of the pathology and a risk factor for the development of sporadic PD. The cause of the disease is still obscure but aging has been unanimously recognized as the major risk factor associated with its development. Aging is a physiological condition but it is likely that changes in the cellular hallmarks of healthy aging, together with other contributing factors, might predispose to the development of PD.

In this project, we aim at studying an aspect of cellular aging, called senescence, in one of the most abundant cell types of the brain, the astrocytes. We hypothesize that defects in autophagy and mitophagy in astrocytes determine the acquisition of a senescent phenotype, especially in a LRRK2-G2019S background. We will study how autophagy and mitophagy dynamics change in young and aged astrocytes derived from induced pluripotent stem cells. We will then pharmacologically modulate mitophagy and autophagy to prove whether this reduces/prevents senescence occurrence in LRRK2-G2019S astrocytes. To evaluate how mitophagy and autophagy modulation can affect astrocytes in a more complex 3D system, we will use brain organoids. We postulate that autophagy-induced astrocyte senescence can be toxic to surrounding neurons but reversible upon treatment. We will characterize the LRRK2-G2019S organoids for the potential rescue of astrocyte senescence and the resulting neuronal degeneration following the autophagy/mitophagy activators.

The obtained data will allow us to clearly define the role of astrocytic senescence in PD and to establish whether its modulation can represent a therapeutic option for PD.

Growing evidence indicates that patients with Type 2 Diabetes (T2D) have an increased risk of developing Parkinson’s disease (PD). These two age-related chronic diseases share similar alterations in essential biological processes and molecular networks, suggesting common mechanisms underlying their pathogenesis. In this light, is not surprising that common anti-diabetic drugs such as Metformin and Exenatide have been highlighted as potential causative PD therapeutics.

Mutations in the PARK6 gene encoding the mitochondrial kinase PINK1 are the second most frequent cause of autosomal recessive early onset PD. Functional studies on disease-causing PINK1 mutations significantly contributed to understand the cellular dysfunctions leading to neurodegeneration, unravelling common molecular mechanisms also implicated in the more frequent sporadic PD (i.e. impaired mitochondrial function and quality control). Based on the compelling evidence implicating PINK1 also in T2D, we decided to use complementary PINK1-deficient cellular models (PINK1-mutant iPSC-derived dopaminergic neurons and PINK1-silenced pancreatic β-cells) as prototype to decipher the cellular alterations leading to neurodegeneration in PD and β-cells failure in T2D, trying to clarify the functional interdependencies between the two diseases.

Our preliminary data suggest that impaired expression of the transcription factor NR4A3 could represent a missing link between PINK1 deficiency and insulin dysmetabolism, potentially coupling insufficient insulin secretion from the β-cells with neuronal insulin resistance and neurodegeneration. Nevertheless, the upstream signals regulating NR4A3 activity as well as the panel of genes controlled by the transcription factor in both dopaminergic neurons and pancreatic β-cells remain largely uncharacterized to date. Thus, the specific objectives of PINK1-DiaPDs project are: (i) To characterize the molecular and metabolic alterations linking PINK1 deficiency to decreased NR4A3 expression in both iPSC-derived neurons and pancreatic β-cells; (ii) To identify and validate the molecular effectors (i.e. NR4A3 target genes) linking impaired PINK1-NR4A3 axis to neuronal dysfunction and pancreatic β-cell failure; (iii) To rescue the phenotypic alterations observed in PINK1-mutant neurons and in PINK1-depleted pancreatic β-cells by re-activating (genetically or pharmacologically) the expression of NR4A3 or newly-discovered downstream targets.

Findings obtained in PINK1-DiaPDs will provide new insight into the mechanistic and pathophysiological interplay between PD and T2D, allowing the identification of novel potential therapeutic targets and thus contributing to patient-based biomedical research in both research fields.

Cytotoxic lymphocytes (CLs) are key anti-tumor immune effector cells. They physically interact with prospective target cells through a highly specialized cell-to-cell interface termed immunological synapse. This interface is indispensable for recognition of cancer cells and activation of CL cytolytic functions. Recently, we established that cancer cell intrinsic resistance to CL-mediated killing correlates with fast and massive accumulation of actin filaments to the immunological synapse or “actin response”. Remarkably, inhibition of the actin response is sufficient to restore cancer cell susceptibility to CL-mediated killing in vitro and a potent anti-tumor immune response in vivo.

Conversely, enhancing the capacity of cancer cells to mount an actin response translates into tumor immune evasion, both in vitro and in vivo. Super resolution microscopy and ultrastructure investigations revealed that the actin response consists of many actin-rich filopodial protrusions projecting into the synaptic cleft and that are heavily decorated with the immune checkpoint molecule PD-L1. In the SYNAPODIA project, we aim at characterizing the molecular identity and functions of these newly discovered synaptic protrusions. Based on our preliminary data, we propose that they critically contribute to immune checkpoint activation by driving PD-L1 polarization toward conjugated CLs.

In addition, we aim at understanding how this synaptic evasion mechanism alters the tumor immune landscape in vivo. Finally, we will evaluate the therapeutic potential of targeting the actin response and synaptic filopodia in combination with immune checkpoint blockade therapy.

The risk of viral epidemics and pandemics has undeniably increased in the recent decades due to global changes affecting inter-connectivity, climate and human-animal interface. Notably, several epidemics or pandemics marked the last 20 years, such as those caused by SARS-CoV-1, MERS-CoV, several influenza, Ebola, Zika and lastly SARS-CoV-2. All these viruses originated in animals, before favorable environmental conditions were created to promote species jump and further human-to-human transmission. While many viruses may circulate silently in the population until breaking out, traditional infectious disease surveillance systems detect outbreaks on the basis of clinical symptoms and thus fail to timely identify the critical places and times of viral disease emergence.

Innovative surveillance and early warning tools are thus urgently needed to more efficiently control and prevent viral threat spread. In this context, the main objective of the VIRALERT project is to set up the initial phase of the epidemic preparedness program at the national scale, through the implementation of an enhanced environmental surveillance allowing early detection of viral epidemics. The originality of the system proposed relies on the integration of two complementary environmental compartments characteristic of human and animal populations, by combining the monitoring of wastewater and surface water.

While wastewater-based epidemiology has long proven its feasibility and usefulness for enteric virus surveillance, mounting evidence suggests a much wider applicability to provide essential public health data on non-enteric viruses: wastewater monitoring showed good correlation but also interestingly increasing SARS-CoV-2 transmission in the population ahead of population screening data. The current pandemic has also altered health-seeking behavior and promoted telemedicine, likely durably affecting traditional sentinel surveillance. Non-pharmaceutical interventions, such as social distancing, limited interactions and enhanced hygiene implemented to slow down the COVID-19 pandemic, have disturbed the spread of endemic viruses, resulting in lower herd immunity, larger pools of susceptible and more severe epidemics in the near future. In complement freshwater-based epidemiology will be explored as a pioneering tool to reflect the viral diversity of major animal reservoirs and epidemic prevention.

We therefore propose to take environmental surveillance to the next level by (i) broadening the spectra of viral species monitored beyond human enteric viruses, (ii) monitoring the post-COVID-19 effect on endemic viral populations as an early warning system for future epidemics and (iii) extending it to more reservoirs in an integrated manner to cover human and animal populations. To that purpose, viral populations in wastewater and aquatic environment will be characterized using three complementary molecular techniques to cover the spectrum from a highly targeted approach with little information on virus diversity (RT-qPCR) to a targeted approach with sequence data to unbiased metagenomics for viral communities.

Focus will be made on virus families with high epidemic or pandemic potential, i.e. Coronaviridae, Orthomyxoviridae, Flaviviridae, Caliciviridae, Picornaviridae and Hepeviridae. The results emerging from this state-of-the art project will decrease disease burden, improve public health and the well-being of the Luxembourg population by paving the way to a strategic cost effective national prevention resource for viral disease surveillance and possibly beyond.

A balanced immune system is important for organismal survival because it allows reactivity against pathogens while preventing self-destructive immune reactions driving autoimmunity or chronic inflammation. A devastating disease whose treatment would benefit greatly from new therapies able to dial back self-reactive immune responses is the autoimmune disease multiple sclerosis (MS), which affects the central nervous system (CNS).

MS is the most common cause of irreversible disability and subsequent inability to work, especially in young adults. A crucial step in the development of autoimmune diseases is the generation of inflammatory T cells, which often arise when inflammatory and tolerogenic T cell responses are not balanced. A key subset of inflammatory T cells in MS is the T helper (Th) 17 cell population, which has been detected in the blood and CNS of MS patients. However, although Th17 cells first came to light in the context of autoimmunity, it is now clear that they can also play a role in protective immune responses against extracellular pathogens. For example, Th17 cells are important for defense against certain gastrointestinal bacterial infections. An innovative concept for the treatment of diseases characterized by excessive inflammation, be it induced by autoimmunity or pathogen attack, is the manipulation of metabolism in Th17 inflammatory T cells. This approach may contribute to the development of new therapies for inflammatory diseases that constitute a great unmet medical need.

Our group is intensively involved in the elucidation and study of metabolic pathways in T cells. Crucially, metabolism is differentially controlled in different Th cell subsets. Recently, we have shown that the antioxidant glutathione (GSH) regulates the metabolism of conventional T cells and regulatory T cells in an almost opposing manner. Our most recent data suggest that GSH has another divergent role in regulating the metabolism of Th17 cells and thus influences their function. Our proposal presents experiments designed to elucidate how GSH operates in Th17 cells and how it might be manipulated.

Another aspect of the proposed research project addresses glucose usage in Th17 cells and its impact on inflammation. In our preliminary work we have shown that glucose flux into the TCA cycle influences the activity of Th17 cells. We now plan to investigate these metabolic pathways in Th17 cells with the aim of discovering novel subset-specific pathways and targets that may offer new therapeutic options for the treatment of inflammatory diseases. To this end, we will exploit various mouse models of human diseases characterized by excessive inflammation, including bacterial infection and the induction of MS-like disease. We will characterize Th17 cell metabolism in vitro and in vivo and align our findings with the corresponding perturbations in our various disease models. Armed with this knowledge, we will target Th17-specific metabolic and/or signaling pathways associated with protective or damaging Th17 responses and evaluate the consequences. Successful completion of our project may result in novel treatment strategies for inflammatory diseases and will unravel novel principles of metabolic regulation in this important T cell subset.

Cancer is a major cause of death in Europe and causes high financial burden for the public health sector. Immunotherapy has remarkable outcomes in patients, but response rates are limited in solid tumors. With its nutritional restrictions, hypoxia, and suppressive environment, the tumor microenvironment (TME) represents a great barrier for efficient T cell responses. A hallmark of cancer is to hijack metabolic processes of highly proliferating cells. Metabolic similarities between CD8 T cells and cancer cells raise the need for pharmaceutical interventions, which specifically enhance CD8 T cell metabolism, but not cancer cell metabolism.

With this proposal we aim to identify compounds targeting T cell metabolism, which can increase the anti-tumor response. In order to answer this question, we will use the Ludwig metabolic library. This library contains 240 compounds, which are commercially available and a significant portion is FDA approved. In brief, we will mimic the TME in vitro using glutamine deprivation and perform high throughput sequencing in order to identify and characterize metabolic pathways, which boost T cell metabolism and effector function. We will also test the effect of the identified compounds of interest on the outcome of an in vivo murine melanoma model, B16F10. This model will allow us to assess the in vivo relevance of the identified compounds, as well as their suitability for systemic treatment. We will rule out compounds which boost cancer cell metabolism in addition to CD8 T cell metabolism. Moreover, we will test if pre-treatment with the identified compounds will enhance the activity of adoptively transferred anti-cancer T cells. To this end, we will test if our results can be validated using human CD8 T cells.

This unique setup promises a fast translation of the compounds into the clinic and future applications for the treatment of cancer patients. In conclusion we aim to identify compounds, which can boost the efficacy of immunotherapy by enhancing CD8 T cell responses, without boosting cancer cells.

Accumulation and mismanagement of heavy metals and undegradable material in specialized neuromelanin (NM)–containing organelles of dopaminergic neurons are known to play a key role in Parkinson’s disease (PD). Previous work yielded a quantitative understanding of the ultrastructure and metal distribution in NM organelles of human substantia nigra (SN) relevant for understanding the underlying pathological mechanisms. Another pigmented catecholaminergic region early and heavily targeted in PD is locus ceruleus (LC). However, basic cellular research especially on the role of iron and NM is lacking for this small noradrenergic area in the brainstem that can hardly be investigated with routine biochemical analyses. Knowing structure and composition of NM organelles in LC neurons would provide information on neurodegenerative process of these neurons and suggest novel perspectives for diagnosis and therapeutic strategies, e.g. through following experiments on model systems and human tissues.

To this end in this project we will investigate LC neurons of healthy and PD affected subjects with existing correlative immunohistochemistry and quantitative analytical electron microscopy as well as imaging secondary ion mass spectrometry (SIMS) methods targeting elemental and molecular fingerprints of NM organelles and metal accumulations. In parallel, we will improve sensitivity and resolution of these methods by using the npSCOPE, a new high resolution prototype cryo-SIMS instrument platform allowing the simultaneous investigation of ultrastructural features and elemental composition within one instrument and close-to native tissue. Thus, a multimodal imaging approach will be developed that allows investigation of individual LC specimen with special focus on the composition of NM organelles, accumulation of metals and other key markers for PD, including water soluble molecules and lipids. Correlation of clinical/histological data with elemental/molecular information on LC specimen will give valuable insight into the mechanisms of aging and PD.
Especially the recognition of possible accumulations of iron or other metals in LC, which are not yet known to take place, would open perspectives for future therapy developments, e.g. involving iron-chelating disease-modifying agents. Modern magnetic resonance imaging (MRI) can also take advantage of NM and Fe-related contrast mechanisms. NM generation, redistribution and finally their removal thus aid in diagnosis of PD. The data gained from our in situ analyses can therefore in future be used to improve and further develop resolution and contrast of such NM-specific and iron-specific MRI procedures for diagnosis, assessing the disease progression and response to therapy.

This multifaceted investigation will highly benefit from the interdisciplinary team consisting of Luxemburgish clinical and research neuropathologists from the Laboratoire National de Santé (LNS), Luxembourg Institute of Health (LIH) and Luxembourg Centre for Systems Biomedicine (LCSB, Prof.Michel Mittelbronn) as well as (neuro)melanin experts from the Institute of Biomedical Technologies at the National Research Council (ITB-CNR, Prof. Luigi Zecca) in Italy and the Luxembourg Institute of Science and Technology (LIST, Dr. Antje Biesemeier). In addition, LIST’s SIMS instrument developers will provide novel equipment for improved orientation and correlative chemical imaging with optimized sensitivity and lateral resolution (< 20 nm for SIMS). Together, they will work on a better molecular characterization of NM pigment in ageing and its role in PD. On the long hand, that approach can be useful to analyse also other (metal-associated) neurodegenerative disorders like Alzheimer’s disease.

All human cells need oxygen for energy production by oxidative phosphorylation. If the oxygen levels are low, cells switch from oxidative phosphorylation to glycolysis. The Hif1α subunit of the transcription factor HIF-1 is essential for this regulatory switch. The switch is regulated by the oxygen level-dependent formation of hydroxyproline on the Hif1α subunit, which in turn is recognized by the VHL-E3 ligase leading to Hif1α’s degradation by the ubiquitin-proteasome system. In recent years other pathways for the regulation of Hif1α emerged, including other degradation pathways or the modulation of translation, leading to higher expression of Hif1α.

As one of the metabolic master regulators for metabolic switching from hypoxic to normoxic conditions and vice versa, Hif1α is important for disease progression prediction. Hif1α has been related to shifting the metabolic programs on the inner parts of solid tumors, like gliomas, lung tumors, and colon carcinomas, by modulating the tumors ability to survive treatment by chemotherapeutic.

Ubiquitination is one of the major cellular signaling pathways. Unlike other signaling pathways, ubiquitin can transmit different signals depending on the target protein’s modification by attaching a single ubiquitin moiety or forming a ubiquitin chain, consisting of several ubiquitins connected covalently to each other. Ubiquitin modification is catalyzed by a multi-enzyme cascade and can be negatively regulated by deubiquitinating enzymes, which cut the ubiquitin modification from the target or disassembling the ubiquitin chains.

Using a newly developed screening technology, Prisma, we identified a significant number of new interaction partners of Hif1α, many of which belong to the ubiquitin signaling system and the ubiquitin-proteasome degradation system. The screen identified three E3 ligases, which have not been reported as interactors before, connecting Hif1α degradation to new degradation pathways. The characterization of these new degradation pathways for Hif1α will allow targeting Hif1α by different means.

A second class of proteins related to ubiquitin signaling is a number of deubiquitinases, which were also identified as Hif1α interactors. Nine different hydrolases were identified on the screen, pointing to a complicated negative regulation of Hif1α. Deubiquitinases are single-molecule enzymes, and recent inhibitor development allows the direct targeting of several of these enzymes, allowing the modulation of ubiquitin signaling.

The Prisma screening technology allows the identification of the interaction site within Hif1α and can quantify the interactome changes induced by small post-translational modifications like phosphorylations, acetylations, or methylations. The Prisma screen with Hif1α revealed several phosphorylation sites, which are necessary for the recruitment of deubiquitinases to a specific site in Hif1α. The proposed project will study the impact of these PTMs on the function and regulation of Hif1α stability and the impact on metabolic switching.

Post-translational modifications are often understudied concerning diseases, as the detection of PTMs in disease material is difficult and can only be done using protein-based technologies. We will investigate the presence of the different known Hif1α modifications using targeted proteomics on the Luxembourgish colon carcinoma cohort. Here we will focus our efforts on measuring the PTMs important for ubiquitin signaling and characterize their presence in the samples in the normoxic and hypoxic parts of the tumor.

The following interdisciplinary proposal aims at investigating treatment resistance mechanisms in Glioblastoma (GBM). GBM is the most aggressive and incurable brain tumor with a dismissal prognosis of 12-15 months. Recent studies, including ours, have shown that GBM cells display very strong intrinsic plasticity and adapt reversibly to dynamic microenvironmental conditions, forming a very dynamic ecosystem. The role of GBM plasticity in creating resistant states upon treatment is currently less understood. We hypothesize that high plasticity allows GBM cells to adapt towards drug resistant states upon treatment. We posit that treatment can simultaneously modulate cells within tumor microenvironment, leading to an overall resistant GBM ecosystem.

This proposal is based on our complementary expertise in GBM biology and computational methods for deconvolution of the complex biological systems. By combining state-of-the art preclinical models, transcriptomic analyses at the single and bulk cell level and powerful deconvolution methods we aim to unravel mechanisms that shape treatment resistance in GBM. First we will assess transcriptomic changes upon treatment in our GBM patient-derived orthotopic xenografts (PDOXs). We will investigate transcriptomic adaptation at the single cell level within tumor cells and subpopulations forming tumor microenvironment. By comparing longitudinal models derived from patients prior and after treatment we will reveal long-term stable changes. Direct treatment of PDOXs will allow investigation of transcriptomic transitions towards resistant states at the moment of treatment. We will next investigate presence of treatment tolerant and resistant states in GBM patient tumors.

Advanced systems biology methods tailored to single cell transcriptomic datasets will reveal signatures of treatment resistant states and their regulators. We will further apply our consensus Independent Component Analysis (consICA), a reference-free deconvolution method, to assess treatment resistance signatures based on wide published and unpublished single cell and bulk transcriptomic datasets. consICA will further allow linking independent molecular signals from tumor and TME subpopulations to clinical outcomes such as patient treatment history and survival. The identified treatment resistance signatures will be validated at the protein level. Finally we will explore potential drugs targeting treatment resistance states and test their efficacy in 3D organoids ex vivo.

Our analyses will elucidate potential therapeutic targets for innovative combinatory treatment strategies. Assessing tumor composition prior and after treatment may further reveal predictive biomarkers of response at the level of individual genes and biological processes and may lead to improved stratification of patients for personalized therapies. Our scripts will be shared via website interface available to researchers with minimal computational skills. Our methodology will be accessible for a wider use, e.g. analysis transcriptomic datasets obtained during clinical trials for identification of biomarkers of responders and non-responders upon targeted therapies.

After cardiovascular diseases, cancer represents the second biggest death causing disease. Especially, when tumours start to metastasise, life expectation strongly decreases and clinical treatment options are limited. Hence, a thorough understanding of when, how and why cancer cells become metastatic is urgently needed in order to improve clinical intervention strategies. Based on profound preliminary data we have identified cellular metabolism as an essential component and driver of metastasis formation.

More specifically, we have uncovered that (i) serine catabolism with formate overflow promotes invasion and metastasis and (ii) that antifolates reduce only growth properties but not the motility potential of cancer cells. We have demonstrated that such sustained motility potential depends on serine metabolism. In 1cFlex we are going to uncover in detail how serine synthesis and one-carbon metabolism contribute to chemoresistance and metastasis formation. By using novel tool compounds, a panel of genetic cell models and in vivo mouse models, we aim to identify the best strategy on how to target this pathway to reduce cancer cell motility and metastatic dissemination.

In summary, we aim to exploit a metabolic bottleneck that can be targeted to prevent disease development and most importantly, decrease metastasis formation.

In most OECD countries, an increasing number of children aged 0-2 are spending a greater amount of their time in formal early childcare (ECC). ECC is generally recognized as an effective mean to expand skills that are important for the development of treated children as well as for income and educational opportunities. The scientific evidence on the subject is, however, inconclusive, because children with different characteristics and background of origin may benefit differently from ECC attendance.

The goal of this project is to provide innovative causal evidence about the effect of different margins (in term of coverage, affordability and quality) of ECC attendance on the cognitive and non-cognitive development of the treated children. The project cares specifically about (but does not limit to) the group of children with a disadvantaged family background, for which we can interpret positive returns to ECC attendance as improving efficiency in human capital accumulation as well as equalizing educational and income opportunities.

Evaluating the causal effects of ECC expansion is a difficult exercise, insofar children are not randomly allocated into formal ECC facilities offering homogenous levels of care quality. Rather, parents select into care, depending for instance on the alternative means of care available at home, and chose the ECC facility quality level that better matches with their characteristics, (female) labor supply and income. In this project, we rely on the introduction of a generous ECC voucher in Luxembourg in 2009 to generate quasi-experimental variation in ECC assignment across the population of children born in the country about 2007-2012. For identification, we combine features of the reform (which improved affordability for low-income families and contextually raised equilibrium ECC supply) with a rich and innovative data infrastructure, gathering information from educational and fiscal register for the universe of the relevant population alongside survey data for a matched sample.

We contribute to the literature along three lines. First, we exploit geographic variability in the expansion of ECC equilibrium supply to estimate (within a DiD setting) the effect of new slots created on development of treated children when in primary school. Second, we exploit discontinuities in the voucher scheme around several remuneration thresholds to estimate (within a RDD design) the effects of rising ECC affordability on children performances, along the distribution of family income.

Third, we develop a structural equilibrium model (rationalizing the children to ECC provider empirical matches) that endogenizes parental sorting, in order to analyze whether returns on ECC attendance differ along the lines of quality of ECC centers and family characteristics.

Reading is a complex cognitive and cultural ability, which needs to be acquired via instruction. It involves orthographic, phonologic, and semantic representations of words. After learning to decode letters into sounds, the child must develop automatic and fast word recognition, i.e. words are recognized “at a glance”, and considered to be stored and retrieved from an orthographic lexicon. Little is known on what characterizes the emergence of such lexical representations at the neural level in typical and dyslexic children or adults, in natural settings or when they learn new words. Here, using a highly sensitive paradigm that combines frequency-tagging and EEG recordings (Fast Periodic Visual Stimulation, FPVS), as well as behavioral tests, we aim at understanding how words are represented in the brain.

We will focus on 10-years-old children, an age at which fluency in reading is reached with high variability, and adults, both typical and dyslexics. FPVS allows to assess automatic and implicit discrimination between categories of stimuli. This powerful approach will be applied to answer several research questions without requiring any linguistic task, that may influence brain networks activated when seeing words:

(1) What drives and characterize the emergence of lexical responses for known words, both in children and in adults, typical and dyslexics?
(2) Do irregular and regular words entail similar brain responses?
(3) Are some teaching methods more efficient than others for learning irregular words?

First, we expect automatic neural responses to words among pseudowords to emerge at 10 years-old and to be related to behavioral reading fluency and vocabulary both in children and in adults. Further, comparing dyslexics to age-matched and younger children will help characterize this neurodevelopmental disorder at the brain level as reflecting hypoactivation, maturational delay or compensatory mechanisms. Second, in opaque languages like French, some words are difficult to read because they contain irregularities in the letters-to-sounds mappings. Studying if irregular words entail specific neural responses, both in children and in adults, typical and dyslexics, will help understand the nature of representations underlying reading. Finally, by focusing on learning new words, we will examine the impact of pre-existing vocabulary knowledge (meaning and spoken form), as well as teaching method, on the novel neural representations created both in children and in adults.

Our project will have a wide pedagogic and societal impact. Our results and their consequences for teaching will be disseminated not only to the scientific community but also to teachers and education actors.