Dragon09/odtu_chatbot huggingface dataset:
evolutionary robustness of cell polarity during molecular diversification

cells are often viewed as intricate machines in which specific proteins work together in a tightly coordinated fashion to give rise to cellular functions surprisingly however some proteins that are essential for core cellular functions in one species are absent in closely related species while the core function itself is maintained how this robustness is achieved while the underlying molecular networks dramatically diversify during evolution is currently not understood as a postdoc i showed that the polarity network in yeast can evolutionarily adapt to the loss of an important protein by losing three more proteins my lab showed that these losses repair polarity through a collective adaptive response affecting many cellular processes rather than only a few proteins how do intricate cellular networks collectively achieve such evolutionary robustness we will address this question with a library of experimentally evolved polarity networks in budding yeast to 1 investigate how general a collective adaptive response is 2 examine which spatiotemporal aspects of polarity establishment are evolutionary robust 3 determine how changes in i protein copynumbers ii posttranslational modifications ptms and iii buffering by selforganization contribute to evolutionary robustness and 4 dissect the molecular mechanisms we will use transposon sequencing to identify the cellular processes involved live cell microscopy to compare the robustness of various aspects of polarity and mass spectrometry to compare changes in gene expression ptms and interaction partners we will use multiscale simulations rooted in statistical physics and constrained by our experimental results to dissect how molecular changes propagate through the polarity network to achieve evolutionary robustness our approach will go beyond yeast polarity because it can be applied to any functional protein network to deepen our understanding of how life works and evolves
sustainable transition to the agile and green enterprise

sustainability and the transition to a lowcarbon more resourceefficient and circular economy are key in ensuring the longterm competitiveness of the european union eu economy sustainability has long been at the heart of the european union project and the eu treaties give recognition to its social and environmental dimensions advanced industrial technologies are at the heart of the industrial revolution shaping the future of production and value chains it opens opportunities for companies to shape a new wave of economic growth more than 75 percent of european industrial smes indicate that the main barrier for the implementation of advanced technologies is the lack of financial resources and access to considerable investment opportunitiesthe stage project will create the sustainability transition ecosystem train sustainability advisors and provide highquality innovation and sustainability assessment decentralised training courses and innovation support and sustainability transition services to more than 2000 european industrial smes during the project duration transforming them into the agile and green enterprises competitive and sustainable leaders of the european industrial economy stage will achieve the grant amount multiplier of 100x with private finance during the project
how digital money is shaping the future of political collectivities a comparative perspective from latin america

over the last decade digital innovations have transformed a fundamental aspect of our societies money these innovations have brought new actors to the realm of issuing currencies leading to what some have defined as the end of an era in which money was defined by the state digimoney will study two of these developments on one hand cryptocurrencies thanks to blockchain technology these would allow a decentralized and stateindependent access to money on the other hand central bank digital currencies cbdcs these would serve to reaffirm state regulatory power in the face of private and antistate monetary initiatives in short while cbdcs seek to uphold the nationstate political structures cryptocurrencies aim to transcend them through an anthropological approach digimoney main objective is to study the critical role of digital money in shaping both established and emerging forms of political collectivities instead of treating money as a purely market catalyst as orthodox economic theory often does projects originality lies in its analysis of money as a battleground where diverse political collectivities attempt to reaffirm their power and trace the boundaries of their presence and sovereignty to achieve this digimoney research will be developed in two countries that constitute paradigmatic cases in relation to each digital currency mexico where the state is on the verge of launching its cbdc and venezuela the third country in the world with the highest volume of cryptocurrencies transactions by integrating an outstanding international research environment and developing an adapted training program the candidate will qualify as a leading researcher in a new and promising field of research at the crossroads of anthropology of money and political economy of money furthermore he will acquire new writing communicative and management skills that will allow him to reach a position of professional excellence and independence
neutrino flavor transformations in dense astrophysical environments

this project neutrae is aimed to advance our understanding on lingering puzzles on the flavor evolution of neutrinos and their implication in particle and nuclear astrophysics neutrinos are characterized by their flavors that can change as they propagate in a phenomenon known as neutrino flavor oscillations the oscillations in vacuum and ordinary matter are well understood and confirmed by several experiments astrophysical compact objects such as corecollapse supernovae and the violent merger event of two neutron stars or a neutron star and a black hole are profuse sources of neutrinos in those astrophysical environments the neutrino flux becomes so intense that the flavor interference of neutrinos with each other has to be taken into account this nonlinear effect coupling neutrinos propagating in different directions and with different energies is known as collective neutrino oscillations accounting for the collective neutrino oscillations in simulations of astrophysical environments requires a quantum kinetic transport it remains a tremendous challenge due to the highdimensionality of the problem and the vastly different scales for flavor and hydrodynamical evolution the impact of neutrino flavor transitions on those compact objects remains elusive without efficient and sophisticated treatments i propose the project neutrae providing a pipeline to study the impact of collective neutrino oscillations in astrophysical environments it consists of three steps performing neutrino quantum kinetic simulations developing numerically effective schemes that can be incorporated in stateofthe art hydrodynamical simulations and assessing the impact of neutrino flavor transformations on heavy element nucleosynthesis and its electromagnetic signatures neutrae will also commit to significant advance on dynamical evolution of astrophysical compact objects
deciphering the dynamicplasticity and heterogeneity of cancerassociated fibroblasts

cancerassociated fibroblasts cafs are one of the most abundant and versatile cell types in the tumour microenvironment tme where they crosstalk with stromal cells and actively participate in tumour development because of their assumed protumourigenic functions cafs have long been considered an attractive therapeutic target however recent evidence indicates that multiple caf subpopulations showing inflammatory myofibroblastic vascular antigenpresenting and immunosuppressive phenotypes coexist within the same tumour with some promoting and other restricting tumour growth thus making their targeting challenging how cafs change dynamically as cancers evolve and how this may affect the overall tumour heterogeneity remains unaddressed therefore the main goal of dynamhet is to elucidate the origin and evolution of caf heterogeneity and to decipher the mediators and mechanisms that regulate caf plasticity as the tumour advances this is crucial for the development of effective therapies aimed at reprogramming cafs towards therapeutically favourable phenotypes and will constitute a great breakthrough in the field of oncology hence dynamhet aims to 1 decipher the origin of caf heterogeneity by performing clonal tracing and by generating and characterising caf subtypes starting from human induced pluripotent stem cells 2 dissect caftme crosstalk by generating 3d patientderived organoids and spheroids and by analysing their secretome and transcriptomic profiles using high throughput technologies and computational analysis and 3 reprogramme cafs by genetic manipulation in favour of therapeutically advantageous subpopulations as a novel therapeutic approach dynamhet is an ambitious and feasible project that stands as a pioneer in the new concept of deciphering the origin and reprogramming the dynamic heterogeneity of cafs towards the development of innovative precision medicine approaches in cancer
smart sustainable cities moving forward with digital twins

the transition to smart and sustainable cities is a key strategic aim at both the european and portugal levels and a un sustainable development goal sdg in support of this goal nova ims and its nova cidade urban analytics lab have invested in developing research expertise in the areas of urban intelligence and analytics for the last few years city digital twins is a new area of research that can contribute to improving solutions for city governance and decisionmaking across mobility environment energy security and the reduction of carbon emissions the nextcity project intends to enhance nova imss scientific and technological excellence in city digital twins namely in all their stages of development data collection and integration analysis prediction and simulation data visualization and data governance to be used in novel strategies for smart sustainable cities in addition it aims to raise its research profile and excellence by twinning with 2 wellestablished institutions university jaume i es and ku leuven be with whom a consolidated strategic research approach will be developed to ensure the exploitation of the nextcity results namely through joint research initiatives that can leverage the outcomes of the exploratory research project proposed this will allow for mutual learning and knowledge transfer activities crossfertilization and networking opportunities for increased research collaborations nextcity includes staff exchanges workshops summer schools and the city digital twin conference to provide the necessary basis to create a true centre of expertise in portugal within a new european network of researchers in this way nextcity will both advance portuguese scientific and research capabilities while disseminating knowledge to the wider community to support the creation of new technology industries and apply the latest tools to help smart municipalities address the challenges to come in what concern urban planning
graphs without labels multimodal structure learning without human supervision

multimodal learning focuses on training models with data in more than one modality such as videos capturing visual and audio information or documents containing image and text current approaches use such data to train largescale deep learning models without human supervision by sampling pairwise data eg an imagetext pair from a website and train the network eg to identify matching vs not matching pairs to learn better representationswe argue that multimodal learning can do more by combining information from different sources multimodal models capture crossmodal semantic entities and as most multimodal documents are a collection of connected modalities and topics multimodal models should allow us to capture the inherent highlevel topology of such data the goal of the following project is to learn semantic structures from multimodal data to capture longrange concepts and relations in multimodal data via multimodal and selfsupervision learning without human annotation we will represent this information in form of a graph considering latent semantic concepts as nodes and their connectivity as edges based on this structure we will extend current unimodal approaches to capture and process data from different modalities in a single structure finally we will explore the challenges and opportunities of the proposed idea with respect to their impact on two main challenges in machine learning dataefficient learning and fairness in labelfree learningby bridging the gap between those two parallel trends multimodal supervision and graphbased representations we combine their strengths of generating and processing topological data which will not only allow to build new applications and tools but also opens new ways of processing and understanding largescale data that are outofreach at the moment
probing new physics with four top quarks

at the large hadron collider lhc protons are collided at the highest possible energy to generate subatomic elementary particles we use the results of these collisions to understand our universe at the most fundamental level many theorists believe that new physics exists at a very high energy the top quark is the heaviest elementary particle known to date with unique properties it is therefore naturally suspected to have hidden connections with new physicsthe simultaneous production of four topquarks tttt is the most energetic process accessible with the lhc making it a unique place to search for heavy new physics which are less likely to appear elsewhere the first evidence of these extremely rare events was only revealed last year and we know very little about them with the worldrecord energy at lhc run3 136 tev we expect 20 higher tttt events production rate this offers a timely opportunity to further study this processwith an aim to find new physics we will study tttt events in unprecedented detail with the atlas experiment at the lhc we will measure the inclusive production rate and the kinematic properties of these events we will use the measured results to probe new physics with unique approaches that do not rely on new physics predictions made upon specific assumptions which could be wrong the results have the potential to reveal new physics that are too energetic and beyond the reach of the lhc this will be the first time this is done for tttt events the measured tttt event kinematics will be corrected to remove effects from the detector resolution and acceptance this allows theorists to directly test their new physics predictions against the experimental results continuously generating impact in the relevant scientific community we will combine the results of tttt events with those of other types of events containing top quarks to build a global picture of the top quark in terms of its subtle connections to new physics
the genomic impact of ancient structural variants on species extinction

in this proposal i seek to quantify the impact of structural variants on species genome diversity and extinction by sequencing ancient genomes of extinct megafauna structural variants are large genomic rearrangements capable of significantly affecting gene function and fitness while in previous work i have investigated the genomes of extinct species at the single nucleotide polymorphism snp level the accurate identification of structural variants has been hampered by molecular and computational challenges thus impeding their incorporation into genomic extinction research recent advancements in longread sequencing technologies have led to considerable improvements in accuracy and affordability making it feasible to characterize structural variants at population level scale in nonmodel organisms despite the fragmented nature of ancient dna our preliminary results show that millions of ancient dna sequences exceeding 500 basepairs in length can be obtained from extraordinarily wellpreserved samples this project capitalizes on these samples combined with stateoftheart sequencing technologies to recover highquality longread sequencing data from ancient specimens and subsequently reconstruct extinct genomes denovo focussing on megafaunal that went extinct during the late pleistocene this project will examine the evolution of structural variants under scenarios of increased genetic drift and reduced selection at unprecedent resolution moreover the project will pioneer the direct quantification of withinspecies structural variant changes through time and provide new insights into genetic variants within previously unassembled genomic segments by expanding our understanding of the genetic role of structural variants on extinction events we will contribute valuable insights into the genetic determinants beyond snps that influence species diversity adaptations survival and eventual extinction
transcriptional footprints of cancer dependency shock as a computational tool for early anticancer drug discovery

the oncogenic shock model has been introduced to describe the interplay between prosurvival and proapoptotic signals that follow an oncogenes inactivation and lead to cancer cell deathin my recent work i demonstrated that identifying novel cancer dependencies through systematic computational analyses of crispr functional genetic screens and multiomic data is an excellent means to discover and prioritise new anticancer therapeutic targets here i extend the oncogenic shock concept to any cancer dependency gene i call cancer dependency shock depshock the signal dynamics interplay that follows the ablation of any gene essential for cancer cell survival ie cancer dependency gene any depshock triggers the sudden inactivation of prosurvival pathways and activates death inducing signals with both events impacting downstreaming transcription factors leaving a measurable gene expression footprint my hypothesis is that each depshock footprint can be deconvoluted to infer transcriptional markers of signals that emanate from a dependency gene and drive cancer cell survival through the constitutive activity of specific biological pathways here i propose to investigate this hypothesis across tissues canonical oncogenic addictions and novel candidate cancer therapeutic targets to this aim i plan to establish an experimentalcomputational platform for the generation and the analysis of unprecedented transcriptional datasets obtained at singlecell resolution upon genetic perturbation of a rationally selected panel of cancer cell lines and therapeutically relevant dependency genes my overarching goal will be to study the information content of the depshock footprints and their potential use as computational tools in early anticancer drug discovery through new statistical and machinelearning methods delivering mechanistically grounded therapeutic markers and hints for the design of combinatorial therapies
generating mrnahnf4alipid nanoparticles for curing pancreatic cancerassociated cachexia cac in identified patients at risk

cancerassociated cachexia cac is a multifactorial syndrome causing significant morbidity and mortality in cancer patients and indicates a poor prognosis nearly 80 of cancer patients experience cac which directly accounts for almost 20 of all cancer deaths mainly in patients with pancreatic adenocarcinoma pdac clinically cac manifests as weight loss and wasting of skeletal muscle mass thus cac patients experience reduced physical emotional and social wellbeing leading to increased use of healthcare resources the massive phenotypic manifestations point to a significant imbalance in the systemic metabolism of cac patients unlike starvation cac cannot be reversed by standard nutritional interventions and currently there are no biomarkers for identifying patients at risk for cac and no effective therapeutic modalities with our erc 818943 we identified changes in liver metabolism during extra hepatic carcinogenesis we now demonstrate that these metabolic changes occur early precede cac and can be diagnosed by routine liver biochemical profile we generated a biochemical liver score that can identify pdac patients at risk for cac irrespective of disease stage at diagnosis furthermore we find that these metabolic changes in the liver are mediated by early infiltrating immune cells that lead to hnf4a depletion in hepatocytes independent of liver metastasis importantly we find that reexpressing hnf4a with adeno associated virus aav8 preserves liver metabolism in pdac mouse models and alleviates cac we hence hypothesize that generating liverspecific mrna of hnf4a will be highly therapeutically beneficial for pdac patients identified by our liver score to be at risk for cac in this poc we will generate and test the efficiency of novel hnf4amrnalnps in preventing or alleviating cac in pdac mouse models when successful our optimized construct will undoubtedly serve identified pdac and other cancer patients at risk for cac
forgotten dreams of maos ousted class an intimate ethnography on how the chinese intelligentsia survived the mao zedong era

this project combines history anthropology and politics to complicate official representations of chinese history told by the current regime of power starting from my own family history which sits at the core of this research forgotten dreams of maos ousted class is guided by the stories of my chinese grandfather and finnish grandmother as a mixedracial couple of the intelligentsia class at a time of political transformation when an imagined socialist future seemed within grasp in a novel enquiry to reconceptualize how collective memory is transmitted this first ever stateoftheart ethnographic project documents and analyses silenced stories of grievous loss and trauma of the chinese educated elite to reconsider what lurks beneath the nations autocratically monitored socialist dream that holds postmao chinese society together my threeyear postdoctoral project is an intimate ethnography that bridges ethnography and biography to offer a new methodological approach to studying the transmission of loss by state violence in contemporary history professor alisse waterston the supervisor for the outgoing phase at city university of new york cuny and professor maarit forde the supervisor for the return phase at helsinki university hu will support my work and mentor me to deliver an innovative and novel intimate ethnography monograph that combines methodology and theory politics and ethnography the personal and the historic