Dragon09/odtu_chatbot huggingface dataset:
advanced engineering of nitric oxide based therapeutics for triple negative breast cancer training network

nocancernet will focus on triple negative breast cancer tnbc and nitric oxide norelated therapeutic development tnbc accounts for 1020 breast cancers and is characterised by diagnosis at an early age and an aggressive phenotype it indeed develops incurable distant metastasis within the first 23 years in approximately 30 patients despite significant efforts tnbc treatment is limited to surgery and chemotherapy laying bare the urgent need for new targeted therapeutic development our network has demonstrated an important role for inducible nitric oxide synthase inos and no signalling in tnbc metastatic progression with efficacy of inos targeting demonstrated in a phase iii clinical trial of patients with distant metastasis based on nos yinyang effect on tumour biology inosno system can be targeted by either inhibiting inos and reducing the physiological levels of no which drive tumour progression or vice versa using no donating drugs to increase no to tumouricidal levels similar to immune cells nomediated tumour targeting the nocancernet doctoral network dn addresses two fundamental gaps in european training 1 a network where a core of doctoral candidates dcs can share a basic understanding of molecular target discovery models of tumour biology assessment drug synthesis and delivery developing diagnostics handling complex spatial imaging and omics expression data profiles and 2 solid interdisciplinary training in experimental computational and clinical research nocancernet will equip our dcs to understand the complexities of bench to bedside cancer research the importance of an interdisciplinary approach and an understanding of the fundamentals of related disciplines this will be of great importance in preparing dcs to work between academia industry and in clinical healthcare providers
investigating the functional roles of histone acylation cooccurrence on transcription in singlecells

regulation of transcription is orchestrated by a complex combination of histone posttranslational modifications ptms but how their cooccurrence in the same cell regulate gene expression is still poorly understood recently novel histone acylations have been identified namely propionylation pr and butyrylation bu they coexist with acetylation ac arise from cellular metabolism and are key candidates to finetune chromatin activity and transcription this project will answer fundamental questions on the role of acylations in gene regulation and their cooccurrence in single cells and provide novel insights into metabolic disorders propionic acidemia pa where histone acylations are alteredthrough this project i will generate the first genomewide histone acylation map in single cells functionally link their cooccurrence with gene expression and establish the impact of a metabolic disease on histone acylations and transcription our preliminary data showed that histone h4k16acprbu play key roles in chromatin activity and could thus regulate transcription and are impaired in livers of a pa mouse model i hypothesize that acylations cooccurrence will regulate transcription and altered propionylcoa metabolism in pa will impact h4k16 acylations and consequently transcriptionto achieve this i will develop an experimental and computational framework for singlecell simultaneous transcriptome and epigenome profiling scstepseq with this approach i will map h4k16acprbu and the transcriptome in singlecells and integrate epigenomic and transcriptomic changes in liver samples from pa mice this interdisciplinary project will address a fundamental question in epigenetics the functional relevance of histone ptms regulated by metabolic state in single cells advance the technology for singlecell multimodal epigenomic profiling and provide for the firsttime molecular understanding of histone acylations in a clinically relevant model
designing green and energyefficient antidewetting protocols for liquid chromatography

high performance liquid chromatography hplc is the leading separation technology in research and industry which often relies on potentially hazardous and environmentally harmful organic solvents water is the ideal environmentally friendly mobile phase which would open the way to green hplc however its broad applicability is hindered by the phenomenon of dewetting of the stationary phase the formation of bubbles in the hydrophobic nanoporous material which makes it unavailable to the substances that need to be separated retention loss nodry proposes to develop a unique experimentally validated simulation testbed based on the pi expertise in theory and simulation of dewetting of nanopores acquired in ercstg hygate these simulation tools will be deployed to rationally design hplc protocols capable of eliminating or alleviating the problem of dewetting in most hplc columns operating with pure water as the solvent thus opening the way to a green and energy efficient chromatography
enabling data enrichment pipelines for aidriven business products and services

enrichmydata provides a novel paradigm for building rich highquality and valuable datasets to feed big data aalytics and ai applications the paradigm consists in facilitating the specification and scalable execution of data enrichment pipelines with a focus on supporting various data enrichment operations such as discovery understanding selection cleaning transformation integration of big data from a variety of sources enrichmydata makes this paradigm easily accessible to a wide set of large and small organizations that encounter difficulties in the process of delivering suitable data to feed their data analytics solutions due to the lack of suitable tools and expertise to support cost effective and energyefficient management of data enrichment pipelines enrichmydata delivers a software toolbox consisting of tools and infrastructure services for settingup deploying executing and managing data enrichment pipelines the main exploitation targets the operation and monetization of the toolbox primarily in european markets enrichmydata validates its plan through a strong selection of complementary business cases offered by commercially focused organizations targeting development of novel products in a wide range of domains including digital marketing industry 40 medical devices maintenance public procurement innovation ecosystems and mineral processing the balanced consortium consists of 13 partners from 11 countries with a mixture of rdtechnology providers and business case providers enrichmydata gathers five large companies three smes two research institutes and three universities
population interconnectivity and technological trajectories in southern africa during the mis3 through replicable lithic analysis

our species emerged from gene flow between structured populations across various regions of africa this process entailed intermitted events of coalescence and fragmentation visible in late pleistocene archaeological records through changing patterns of lithic technological similarity in this framework the mis3 5928 ka is a particularly intriguing period because archaeologists working in southern africa have hypothesized that the marked regional variance in lithic technology is ascribable to cultural fragmentation and reduced information exchange among dispersed populations however it may also stem from the lack of a replicable system for recording and statistically analyzing lithic traits the rstone project seeks to address this research challenge by pursuing three primary objectives firstly it will develop a standardized method for recording lithic traits through comprehensive replicability experiments secondly it will utilize this established recording system to collect novel lithic data from seven welldated mis3 stratigraphic sequences across malawi mozambique namibia and south africa finally it will conduct a quantitative intersite comparison to explore technotypological similarities and differences and determine whether the observed variance follows a pattern of isolation by distance or if other factors such as geological constraints played a role in shaping the way in which human foragers produced stone tools this research will yield valuable opensource tools implemented in the r programming language and highresolution datasets in line with open science practices rstone will prioritize the transfer and sharing of these resources with a particular focus on engaging young african researchers the extensive collaboration network will ensure a robust dissemination of results while positioning the fellow as a key figure in exploring the intricate interplay between human cultural diversity and population dynamics during the pleistocene
from household allocations to global inequality new methods facts and policy implications

to understand and mitigate economic inequalities both locally and globally we need to acknowledge inequalities within households yet in most empirical studies such intrahousehold inequalities are disregarded mainly because we lack appropriate measurement tools and data not only is this problematic for inequality measurement this lack of understanding hampers the design of costeffective poverty reduction and child development policies this project has five general objectives first i will update the facts about inequalities through direct measurement of intrahousehold consumption allocations and relate these to spousal income contributions second i will develop and validate novel measures of parental resourceallocation preferences and use these to study whether children are likely to benefit more if mothers rather than fathers receive cash transfers third i will develop and validate novel measures of household decisionmaking and use these to investigate how targeted transfers shape womens empowerment fourth i will study whether cash transfers or an educational parenting program is most costefficient for child development fifth i will use an integrated framework and the new tools and data to refine our understanding of the mechanisms behind inequalities among adults and child development concretely the project will contribute to our knowledge in the following specific ways i will carry out an extensive data collection on intrahousehold allocations parentalallocation preferences and womens empowerment in ten very diverse countries one from each decile of the world income distribution i will engage in a local rct in tanzania on cash transfers and parenting which also involves extensive data collection on household consumption time use preferences and decisionmaking finally i will conduct lab experiments in chile india and tanzania so as to validate the parentalallocation preference and decision making measures
towards an integrated capability to explain and predict regional climate changes

the climate system is changing rapidly and some regions have seen increases in extremes beyond what is expected from climate model simulations to support targeted climate adaptation strategies expect will enable trustworthy assessments and predictions of regional climate change including extremes by developing a prototype operational capability for integrated attribution and prediction of climate this ambitious goal is closely aligned with the wcrp lighthouse activity on explaining and predicting earth system changeexpect will identify and quantify the mechanisms by which physical processes govern regional climatic changes including extremes on interannual to multidecadal time scales it will do so by exploiting newly available climate simulations and earth observations eos and by combining machine learning ml with physical methods the research will target fundamental knowledge gaps related to atmospheric circulation and landatmosphere interactions which represent major limitations in current climate predictions and projections and in particular in understanding changes in european summer extremesto underpin the research and benefitting the wider research community expect will develop tools to efficiently analyse a variety of large data sets in combination that are hosted in different repositories across institutions this will facilitate the exploitation of recent investments into highresolution climate models and eo data expect will further build data science capacity for the scientifically robust efficient and reproducible analysis of the massive data assets including novel ml approaches and provide training for the climate science community and the next generation of researchers in particularexpect will thus deliver significant scientific and technological advances for society and the climate science community that will last well beyond the project in support of wcrps strategic objectives
comprehensive solutions of healthcare improvement based on the global registry of stroke care quality

resq will build on the success of resq registry of stroke care quality currently used by many eu countries and 74 worldwide to improve stroke care quality by collecting and analyzing hospital discharge reports resq will revolutionize these improvements by capturing the whole patient pathway the solution will combine nlp with a clinicallyvalidated semantic model to automate ingestion of hospital discharge reports in different languages and assist with audit and feedback this will include creating a standard model for such reports and using ai to impute missing data further augmentations include the creation of two novel ai voice assistants one to help patients provide feedback on their health and the other to help physicians provide high quality carewe will integrate all these tools into resq this will be the basis for a european open stroke data platform an open research platform for data aggregation semantic harmonization and interoperability across european countries to promote the use and reuse of health data we will facilitate efforts to define a standard european stroke hospital discharge report exchange format as a tool for better secondary use of data and healthcare in general consortium legal partners will develop a comprehensive legal and ethical toolbox as guidance towards legal compliance this will boost wider adoption of such novel aibased solutions by integrating all current and proposed union legislation our clinical partners will provide medical records and steer the development to maximize clinical utility and validate final solutions resq will be deployed globally to solidify our position as european and global leader in quality improvement eventually we will guarantee citizens a similar level of quality control during hospitalizations as when flying in a commercial plane
next generation mechanistic models of retinal interneurons

ever since the work hodgkin and huxley models of neurons have been essential for our understanding of neural computations such models have been developed at diverse levels of realism from linearnonlinear cascade or blackbox models to detailed compartmental models while these approaches are commonly viewed as incompatible they have attractive strengths from an epistemic point of view in this project i propose to develop a new generation of hybrid mechanistic models that reconcile these levels of modelling they will consist of a compartmental model for the neuron of interest with inputs approximated by blackbox models i will leverage the power of these hybrid models to tackle one of the most challenging questions in visual neuroscience the staggering diversity of amacrine cells a major class of inhibitory interneurons in the vertebrate retina despite their diversity they are the least understood class of neurons in the retina in stark contrast to the remaining circuitry while in mouse more than 60 types of acs have been identified by single cell transcriptomics only a handful has been studied at depth i will build on the latest advances in machine learning to develop a framework for efficiently inferring the parameters of a hybrid mechanistic model to constrain the model parameters we will acquire twophoton calcium and voltage imaging data during natural stimulation further we will extend our framework to incorporate transcriptomic information about gene expression collected via patchseq into the inference procedure allowing us to map the amacrine cells to genetically defined types thus in this project i propose to develop a toolset to systematically uncover the role of retinal amacrine cells during natural visual computations and link it to its mechanistic basis providing a path forward to solving one of the key remaining mysteries of visual neuroscience
precision lethality to overcome clonal heterogeneity in highrisk neuroblastoma

tumors are heterogeneous in nature due to genetic instabilittumors are heterogeneous in nature due to genetic instability ongoing selection and variable microenvironments with local adaptation many tumors thus necessitate combinatorial drug treatments to reach all cells this is true also for neuroblastoma the most common extracranial solid pediatric tumor despite the wellknown importance of clonal heterogeneity most in vitro drug combination strategies including commonly used synergistic interaction do not quantify subclonal drug response here recently developed cell barcoding strategies will be used to monitor survival of thousands of individual subclones in neuroblastoma organoids under different drug perturbations this lineage tracing strategy allows identification of cell populations that survive a specific drug and to find other drugs that specifically target those cell populations i call this strategy precision lethalityin this research program two different precision lethality methodologies will be developed one where cell barcoding is used to identify drug combinations with low crossresistance and one that uses the possibility to express the barcode so it can be captured by single cell rna sequencing this allows assessing the transcriptional state before drug perturbation of cells that are known to be either drug resistant or drug sensitive combined with publicly available drug sensitivity data repositories this will be used to construct a deep learning model to predict drug sensitivities of individual cellssuccessful completion of this multidisciplinary research program will identify and verify new drugs to complement standard of care consolidation therapy for neuroblastoma i also envision that these studies will showcase to the broader cancer research community how cell barcoding can be used as a drug combination strategy to overcome clonal heterogeneity which would increase the chances of finding curative cancer treatments
training wind energy experts on digitalisation

training wind energy experts on digitalisation tweed doctoral network dn aims to train the next generation of excellent researchers equipped with a full set of technical and complementary skills to develop highimpact careers in wind energy digitalization this goal will be achieved through an outstanding researchforinnovation programme and a unique training programme that combines handson research training interactive schools and hackathons innovation management and placements with nonacademic partner organizations an integrated research program will be carried out alongside the development of a virtual wind energy data science hub that facilitates a virtual research environment to foster collaboration data sharing and testing of innovative solutions seeking drastic costofenergy reductions the network will provide an interdisciplinary and intersectoral context to foster creativity in transforming technological challenges into data science problems that can be solved to develop prototypes for commercial exploitation researchers will be trained in business innovation to extend their focus beyond the academic context to be able to identify addedvalue products or services through customer discovery and guidance from established researchers and entrepreneurs as a result a researchforinnovation mindset will be developed to provide enhanced career perspectives to the fellows equipped with a complete set of thematic technological and innovation skills moreover tweed network will accomplish the foundation of wind energy data science weds as a new research discipline across the eawe network to raise awareness exploit synergies and motivate future career choices the potential of dataintensive science as a new paradigm will allow reducing the cost of energy by as much as 13 during the project lifetime and 50 by 2050 by intelligent solutions not accessible to traditional wind energy specialists
european eddyrich esms

eddy rich earth system models eerie will develop a new generation of earth system models esms that are capable of explicitly representing a crucially important yet unexplored regime of the earth system the ocean mesoscale leveraging the latest advances in science and technology eerie will substantially improve the ability of such esms to faithfully represent the centennialscale evolution of the global climate especially its variability extremes and how tipping points may unfold under the influence of the ocean mesoscale model improvements include new dynamical cores new components particularly sea ice scaleaware parametrization and the complementary use of machine learning ml the technological challenge associated with this ambition is very high eeries goal is to achieve a simulation speed of up to 5 simulated years per day 5 sypds and to make efficient use reduction in power consumption by 50 of the preexascale supercomputers now available in europe the technological solutions that are to be leveraged in eerie are the use of reduced precision gpus ml and reduced io alongside model improvements eerie will develop innovative experimental simulation protocols that are suitable for the mesoscale to be pioneered on behalf of the global climate modelling community in preparation for the next ipcc eerie will produce useful and usable climate information that will contribute to national and international climate change assessments such as ipcc it will incorporate model variability and extremes within an integrated assessment model iam via a mlemulato and it will deliver storyline approaches to the consequences of climate tipping points and disease outbreaks