Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Deciphering the unconventional receptor binding and modulation activity of bat influenza A viruses (Bat Flu)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Immunity, Infection and Immunotherapy
Panel description: The immune system, related disorders and their mechanisms, biology of infectious agents and infection, biological basis of prevention and treatment of infectious diseases, innovative immunological tools and approaches, including therapies
Countries involved: Germany
Call: ERC Advanced Grant (ERC-2019-ADG, 2019)
Start date: 2020-11-01
End date: 2025-10-31
Duration (months): 60.0
Total project cost (EUR): 2499637.5
EU funding (EUR): 2499637.5
Participants: 1
Project status: SIGNED

Influenza A viruses (IAVs) are zoonotic pathogens that frequently cross the species barrier into humans, often causing severe morbidity and even global pandemics. This cross-species transmission is facilitated in large part by alterations in the interaction between the viral surface proteins hemagglutinin (HA) and neuraminidase (NA) and sialic acid, a ubiquitous glycan that serves as the cellular entry receptor. Although avian hosts have generally been thought to be the primary reservoir for all influenza A viruses, this dogma has recently been challenged by the identification of two novel IAV subtypes in bats, H17N10 and H18N11. Despite an otherwise high degree of functional homology to conventional IAVs, the surface proteins of bat IAVs demonstrate several unprecedented characteristics. Specifically, these proteins are unable to interact with sialic acid; rather, we recently showed that bat IAVs use the major histocompatibility complex class II (MHC-II) protein to gain entry into host cells. Unexpectedly, we observed that N11 downregulates surface expression of MHC-II, suggesting that it potentially harbors a receptor-destroying function. Most surprisingly, bat IAV could replicate to even higher titers the absence of functional NA, a capability which has never been observed among influenza viruses. These findings suggest that the surface glycoproteins of bat IAV may possess a structural plasticity that is much broader than that of conventional IAV. In light of the critical importance of the surface proteins for cross-species transmission of IAV, the goal of this project will be to probe this plasticity, first by determining the mode of interaction between H17/H18 and MHC-II and elucidating the mechanism of N10/N11-dependent downregulation of MHC-II, but most importantly by using forced evolution to explore the plasticity of IAV for new cellular entry factors. The insights from these studies will have a major impact on our understanding of influenza virus tropism.

Keywords: bat influenza viruses,receptor,mhc ii
Unravelling the developmental origins of parallel evolution (EvoOnRepeat)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Environmental Biology, Ecology and Evolution
Panel description: Ecology, biodiversity, environmental change, evolutionary biology, behavioural ecology, microbial ecology, marine biology, ecophysiology, theoretical developments and modelling
Countries involved: Sweden
Call: ERC STARTING GRANTS (ERC-2020-STG, 2020)
Start date: 2021-03-01
End date: 2026-02-28
Duration (months): 60.0
Total project cost (EUR): 1498198.88
EU funding (EUR): 1498198.88
Participants: 1
Project status: SIGNED

The diversity of life may seem endless. Yet, a closer look reveals that evolution often is on repeat. This is most striking when the same suite of characters evolves over and over again. One explanation for such parallel evolution is that development produces some phenotypes readily and frequently, while others are rare or impossible. Evolution must go where development leads. I have identified a rare opportunity to put the role of development in adaptive evolution to the test. At least six species of wall lizards have repeatedly evolved a complex syndrome, including striking coloration, stout bodies, large heads, and aggressive behaviour. All these traits develop from the same cell type, neural crest cells. I propose that this developmental coupling allows seemingly unrelated traits – colours, morphologies and behaviours – to vary together. As a result, variation is channelled down particular routes, resulting in parallel evolution. I will test this hypothesis by establishing ‘Evo-Devo 2.0’ – merging evolutionary and developmental biology in a comparative framework. Firstly, I will reveal if independent origins of the syndrome share the same transcriptional and epigenetic modifications of neural crest cells. Secondly, I will identify how parallelism at the phenotypic level is mirrored at the genomic level. Thirdly, I will use gene editing to functionally validate the results and reconstruct the evolutionary steps at the origin of the syndrome. If my hypothesis is correct, my insights will demonstrate that understanding development enables us to make evolution more predictable. Failure to attend to the arrival of the fittest has left us poorly equipped to predict how invasive species evolve, or if species will adapt to environmental challenges. My research will fill this explanatory gap by showing that it is possible to understand the rules by which individuals vary, and use this insight to explain why evolution proceeds some ways rather than others.

Keywords: evolutionary biology,evo devo,parallel evolution,comparative genomics,evolutionary genomics,crispr,cas9,transcriptomics,epigenetics,neural crest cells,lizards,cell sorting
Operation Optimization and Improved Reliability Solution for Electrical Substations (Subfailtec)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: Israel
Call: Stimulating the innovation potential of SMEs for a low carbon energy system (H2020-SMEINST-1-2015, 2015)
Start date: 2016-02-01
End date: 2016-04-30
Duration (months): 3.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

PDP Technologies Ltd. (PDP) is an Israeli company, seed-funded by Horizon GreenTech Ventures, an investment alliance of Alstom S.A, Rotem Industries & Gefen Investments. PDP provides innovative solutions to make the power system more effective based on Partial Discharge (PD) detection and analysis. PDP has developed a patent pending technology (Subfailtec) to predict, mainly, high voltage (HV) (>30KV) supply failures by monitoring electric substations (SUBs) (ca. 300.000 in the world) and predicting maintenance needs due to insulation wear. PDs are among the most common root causes of failures. PDs are detected by analysing the electromagnetic wave generated by them. Subfailtec is a continuous, non-invasive, cost effective and universal solution. It optimizes SUB maintenance and operation decisions, decreasing financial losses caused by sudden failures, typically emanating from 1%-4% of the network element’s and dependent on age, use and maintenance. Subfailtec will cover the need of grid owners and operators of reducing costs and increasing supply reliability, while generating jobs, by producing, installing and selling its solution. It is a fully scalable solution and has the same building blocks in all cases. The configurable number of antennas/receivers is driven by substation layout and size. The market price for Subfailtec is expected to be competitive and give a short return on investment (shorter than 1.5 years) by reducing CAPEX (for new, replacement, and refurbishment options), OPEX and cost of energy not supplied. Companies such as Alstom (Alstom grid equipment are present in more than 90% of power utilities worldwide), IEC (the main supplier of electric power in Israel) and BAZAN Ltd (Israel's largest Oil refinery) have expressed interest in the commercialisation of the Subfailtec solution.

Keywords: partial discharge,high voltage,substations,transformer switchgear,transmission,distribution,outage,reliability,electricity
β-Lactams as flaviviral NS3 protease inhibitors (LIsTEN)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: Germany
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-05-02
End date: 2019-05-31
Duration (months): 24.0
Total project cost (EUR): 171460.8
EU funding (EUR): 171460.8
Participants: 1
Project status: CLOSED

Flaviviral infections already represent a threat to 2.5 billion people living in tropical and sub-tropical regions. As a consequence of climate change and global warming in the near future these infections are expected to spread to areas with moderate climate and the possibility of disease outbreak will exist in Europe, especially around the Mediterranean and Adriatic coast, as well as in the United States of America and large parts of Asia. At the moment no medical treatment against flaviviral diseases is available. Recently, peptide-based compounds which act as flaviviral NS3 protease inhibitors, emerged as potent agents against dengue virus (DENV), Zika virus (ZIKV) and West Nile virus (WNV). These compounds consist of two to four natural or unnatural amino acids and act by binding to the active site of the protease. Accordingly, the incorporation of an electrophilic warhead, a moiety which would facilitate the covalent binding of the inhibitor to the catalytic serine residue, into the peptide inhibitor represents a valuable strategy for the improvement of potency of such inhibitors. The goal of the proposed project is to investigate the potential of β-lactams as electrophilic warheads in DENV, ZIKV and WNV protease inhibitors. For that purpose, new β-lactam derivatives will be synthesized, coupled to peptide inhibitors previously developed by the host group and their affinity to the target will be evaluated by biochemical assays. The most potent compounds will be characterized in more detail and their activity against dengue virus replication in cell culture, off-target binding, membrane permeability and metabolic stability will be studied. We expect the formation of a covalent bond between inhibitor and active site of the enzyme to significantly improve inhibitory activity by increasing binding affinity, as well as to ameliorate selectivity and reduce off-target binding.

Keywords: lactam,flavivirus,protease,covalent inhibition
Syntenin-phosphatidic acid interaction in exosome biogenesis and cell-cell communication: a structure-function based approach (EXOGENESIS)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: France
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2018-12-01
End date: 2020-11-30
Duration (months): 24.0
Total project cost (EUR): 173076.0
EU funding (EUR): 173076.0
Participants: 1
Project status: CLOSED

Cells communicate with their environment in various ways, including by secreting vesicles. Some of these extracellular vesicles originate from endosomes, are loaded with proteins, lipids and RNAs and are called exosomes. Exosomes emerge as important players in physiological cell-cell communication, but also in various systemic diseases. Understanding how cells control the selective incorporation of ‘messages’ in their exosomes is thus essential, and such fundamental new knowledge may allow us to better understand cancer spread for example. Recently syntenin, a small intracellular adaptor protein, was identified as essential for the biogenesis of presumably a distinct class of exosomes that might be important for cancer cell communication and systemic invasion. Based on preliminary work, this study aims to evaluate the role of the membrane lipid phosphatidic acid in the formation of syntenin exosomes, their loading with cargo and their function in intercellular communication. A structure-function based approach is used, allowing if successful to pave the way for rational and innovative drug intervention. The fellowship will offer the applicant the possibility to receive an intensive training in biochemistry, cellular, molecular biology and drug discovery as well as to acquire important secondary skills which will pave the way for his career as an independent researcher.

Keywords: exosome biogenesis,lipid binding studies,cell cell communication
Artificial Intelligence for Customer Service (USERBOT)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Italy
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2019-03-01
End date: 2019-08-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Userbot provides Artificial Intelligence for Customer Service. We have developed an innovative technology platform based on Machine Learning, Deep learning, Artificial Intelligence and Sentiment Analysis to interact with customers in a natural language on every digital channel. Userbot’s proprietary AI technology that reached TRL7 is developed internally and we are constantly improving it. We are currently working on the automation of customer acquisition and payments, as well as developing a special Agency dashboard. The basic AI remains one of the main areas of investment, optimizing and simplifying the AI model Training and improving the performance of Natural Language Processing. Our team is composed by seasoned experts with commercial and management experience, supported by 4 advisors with decades of experience in the sector. The Milan Polytechnic as partner and shareholder, allows us direct access to technology transfer to artificial intelligence research. Our success has already been remarkable. In the first 3 months of operation, we received numerous responses, in the Finance, Banking and Insurance sectors, as well as from Startups, SMEs and Public Authorities. Our service is currently used by companies such as Agos, Moovenda, Buzzoole, LeCicogne and PAs such as Regione Emilia Romagna and the Sesto Fiorentino Municipal Authority. In September 2017, we won the Artificial Intelligence Worldwide Software Vendor Selection, from more than 300 Startups and technology companies already established at international level and were awarded a contract with Agos Ducato S.p.A. Financially we can count on over half a million euros of investments. In March 2018, we achieved a capital increase of € 300,000 with some Business Angels that became part of the shareholders; whilst in July 2018, the equity crowdfunding on Crowdfundme raised € 200,000, with the entry of 131 new shareholders. The SME instrument phase 1 project is thoroughly aligned to Userbot’s strategy.

Keywords: chatbot,ai technology,natural language processing,machine learning,deep learning,artificial intelligence,sentiment analysis,customer service
Smart Loyalty Program: Using Data Science to Inspire the Next Purchase (PayLead)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: France
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-06-01
End date: 2019-09-30
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Credit and debit card transaction histories are a valuable source of information about their owners’ purchase patterns. This information can be used to accurately address promotional offers, called Card Linked Offers (CLO). Today, CLO performance is limited due to the nature of accessible information from credit cards: it is often fragmented and and is not customer-centric as it does not take into account habits / historic of purchase to develop personalized recommandations. It is basic coupon with no intelligence. PayLead is a French SME founded in 2016 developing a new approach - called Account-Linked Offer (ALO®) - that allows all transaction data to be collected, not only bank card payments. ALO is based on cross-checking transaction data with several external sources making it possible to improve prediction relevance and accuracy. This allows us to create smart loyalty programs based on precise patterns of spend propensity. The bidding of offers is based on profiling and targeting resulting from customer payment flow analysis at both the bank level and external partners (merchants, third-party solutions). Profiling is done on the basis of big data principles through machine learning algorithms and non-linear classifiers. The first commercial partnerships have been finalized to allow speed, critical mass of customers, users and partners in order to legitimize the offer in a very competitive market in terms of marketing and loyalty solution. We have validated our model, developing a profiling and decision-making engine for merchant based on machine learning, and we prepared us for scaling. We have built our tech platform and we are now ready to take off through the consolidation of stakeholders. We are currently deploying our solution with a major bank (BNP Paribas) and a major insurance group (Groupama). In 2023 we expect the have €23M of revenue and €13M of EBITDA. This phase I project will support further the development of our go-to-market strategy in Europe

Keywords: card linked offers,profiling and decision making engine,personalised offers,big data,machine learning
Chemical transformation of enzymatic hydrolysis lignin (EHL) with catalytic solvolysis to fuel commodities under mild conditions (EHLCATHOL)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Theme: Low-cost, low-carbon energy supply
Action type: Research and Innovation actions
Countries involved: Germany,Switzerland,Norway,Finland,France,France,Netherlands,Netherlands
Call: Developing the next generation of renewable energy technologies (H2020-LC-SC3-2020-RES-RIA, 2020)
Start date: 2020-11-01
End date: 2024-10-31
Duration (months): 48.0
Total project cost (EUR): 3999628.75
EU funding (EUR): 3999628.75
Participants: 8
Project status: SIGNED

Our EHLCATHOL action aims to completely transform via direct catalytic solvolysis, viz. using a fuel compatible solvent as one of the reactant to fully depolymerize, of a large volume Enzymatic Hydrolysis Lignin (EHL) waste of the 2G bioethanol production from lignocellulose biomass, to produce high performance fuel blends, i.e. high heating value jet-fuel, high octane gasoline and high cetane number diesel. The EHLCATHOL research will focus on gaining the knowledge for improving greatly the catalytic activity and stability, mechanism of suppressing recondensation steps, solvation of login, selectivity to fuel molecules, product separation, fuel performance enhancement, combustion of the EHL biofuel, as well as reducing the environmental impact of the emission, all needed to develop the novel EHL catalytic solvolysis technology exploiting the energy, around 40% of the lignocellulose feed, stored in EHL with the highest efficiency. Our consortium of Aalto, TUE, NTNU, LIKAT, EPFL, CNRS and VERTORO engages with the profound background in biofuel chemistry, catalysis, mechanism and kinetics, operando spectroscopy on organic reactions, fuel performance enhancement, combustion kinetics and modelling, reactor and process design, as well as distillation techniques. We will reveal and overcome the potential factors limiting the up-scaling of the processes, as well as exploit and test the new fuel products and determine their environmental impacts. Our target is to develop a novel technology that fully takes the advantage and utilizes the energy of the waste-EHL, transforms it to high quality liquid fuels applicable, e.g., in hybrid cars, heavy-duty transport vehicles, ships and jet airplanes, thus, doubling the energy efficiency of the 2G bioethanol production chain and contributing to achieve the targeted carbon neutral EU by 2050.

Keywords: enzymatic hydrolysis lignin,catalysis,lignin solvolysis,environmental impact,combustion performance
Crib with ARtificial InteLLigence fOr ASD diagnosis in Neonatal intensive care units (ASD-carillon)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Global Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Italy,Canada
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Duration (months): 30.0
Total project cost (EUR): 214760.16
EU funding (EUR): 214760.16
Participants: 2
Project status: CLOSED

Autism Spectrum Disorder (ASD) is a severe permanent neurodevelopmental disorder, affecting 1 in 59 children, worldwide. Researchers have reported a markedly increased prevalence of ASD in preterm populations. Performing early screening of ASD in Neonatal Intensive Care Units (NICUs) would be a unique opportunity to provide a prompt and proper intervention. However, no quantitative solutions are present in the literature. The project “Crib with ARtificial InteLLigence fOr ASD diagnosis in Neonatal intensive care units” (ASD-carillon) aims to design, implement and validate a smart crib for analyzing visual preference and motor patterns in preterm infants in NICUs for early ASD screening. The smart crib integrates a Monitoring Framework, consisting of RGB-D and thermal cameras, and sensors already available in NICUs (e.g., those in the cardiomonitor) for collecting infants data. The smart crib is equipped with an Artificial Intelligence (AI) engine, for processing these data and providing healthcare professionals with quantitative parameters for early ASD screening in NICUs. During the outgoing phase of the fellowship, the ER will benefit from the experience of Prof Zuomin Dong, from University of Victoria (UVic), in the field of sensors and intelligent system, to develop the Monitoring Framework and build the prototype of the smart crib. During the incoming phase, she will collaborate with her main mentor, Prof Emanuele Frontoni from Università Politecnica delle Marche (UNIVPM), to refine the AI Engine. Expert neonatologists as well as neuropsychiatrists from UNIVPM and UVic will be involved as clinical collaborators of ASD-carillon. In the last decades, there has been an increasingly growing number of manuscripts dealing with AI in medicine, but the AI potential in the field of ASD screening in NICUs has not being unlocked, yet. With ASD-carillon, the ER aims to fill this gap, while building the basis for a solid career in the field of AI in neonatology and ASD.

Keywords: neonatal intensive care units,preterm infants,autism spectrum disorder screening,machine learning,deep learning,medical image analysis,human behavior analysis