15,777 research outputs found

    Identifizierung prädiktiver und prognostischer Biomarker in unterschiedlichen Tumorkompartimenten des ösophagealen Adenokarzinoms

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    Das ösophageale Adenokarzinom zeigt eine global steigende Inzidenz und hat mit einer 5-Jahres-Überlebensrate von weniger als 25% eine schlechte Prognose. Personalisierte Therapieansätze sind selten und prognostische/prädiktive Biomarker des Tumormikromilieus sind unzureichend charakterisiert. Die kumulative Promotion nähert sich dieser Problematik in drei unterschiedlichen Schwerpunkten. 1. Zur Identifizierung Kompartiment-spezifischer Biomarker wurde eine Methode entwickelt, welche als kostengünstige Alternative zum sc-Seq Expressionsprofile individueller Zelltypen generiert. Dabei erfolgt die Extraktion der RNA nicht aus Einzelzellen, sondern aus flowzytometrisch-getrennten Zellkompartimenten. Die Separation der Proben in Epithelzellen, Immunzellen und Fibroblasten wurde durch verschiedene Verfahren validiert und eine suffiziente Ausbeute an RNA auch für kleine Gewebemengen gezeigt. 2. Biomarker des Immunzellkompartiments als therapeutische Angriffspunkte wurden in einem Patientenkollektiv von bis zu 551 Patienten auf ihre Bedeutung beim EAC überprüft. Es zeigte sich eine Expression der Immuncheckpoints LAG3, VISTA und IDO auf TILs durch IHC und RNA-Sonden basierte Verfahren in einem relevanten Anteil (LAG3: 11,4%, VISTA: 29%, IDO: 52,6%). Es konnte eine prognostisch günstige Bedeutung der VISTA, LAG3 und IDO Expression gezeigt werden. Durch den Vergleich von Genexpressionsprofilen aus therapienaiven und vorbehandelten Tumoren konnte zudem ein immunsuppressiver Effekt von neoadjuvanten Therapiekonzepten auf das Tumormikromilieu des EACs gezeigt werden. Dabei kam es zur verminderten Expression von Checkpoints und Anzahl TILs nach (Radio-) Chemotherapie. 3. Im Tumorzellkompartiment wurde die Rolle von Amplifikationen in ErbB-Rezeptor abhängigen Signalwegen durch FISH-Technik und Immunhistochemie evaluiert. Es fanden sich KRAS Amplifikationen in 17,1%, PIK3CA Amplifikationen in 5% sowie eine HER2/neu-Überexpression in 14,9% der untersuchten Tumore

    Four Lectures on the Random Field Ising Model, Parisi-Sourlas Supersymmetry, and Dimensional Reduction

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    Numerical evidence suggests that the Random Field Ising Model loses Parisi-Sourlas SUSY and the dimensional reduction property somewhere between 4 and 5 dimensions, while a related model of branched polymers retains these features in any dd. These notes give a leisurely introduction to a recent theory, developed jointly with A. Kaviraj and E. Trevisani, which aims to explain these facts. Based on the lectures given in Cortona and at the IHES in 2022.Comment: 55 pages, 11 figures; v2 - minor changes, mentioned forthcoming work by Fytas et a

    Modelling uncertainties for measurements of the H → γγ Channel with the ATLAS Detector at the LHC

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    The Higgs boson to diphoton (H → γγ) branching ratio is only 0.227 %, but this final state has yielded some of the most precise measurements of the particle. As measurements of the Higgs boson become increasingly precise, greater import is placed on the factors that constitute the uncertainty. Reducing the effects of these uncertainties requires an understanding of their causes. The research presented in this thesis aims to illuminate how uncertainties on simulation modelling are determined and proffers novel techniques in deriving them. The upgrade of the FastCaloSim tool is described, used for simulating events in the ATLAS calorimeter at a rate far exceeding the nominal detector simulation, Geant4. The integration of a method that allows the toolbox to emulate the accordion geometry of the liquid argon calorimeters is detailed. This tool allows for the production of larger samples while using significantly fewer computing resources. A measurement of the total Higgs boson production cross-section multiplied by the diphoton branching ratio (σ × Bγγ) is presented, where this value was determined to be (σ × Bγγ)obs = 127 ± 7 (stat.) ± 7 (syst.) fb, within agreement with the Standard Model prediction. The signal and background shape modelling is described, and the contribution of the background modelling uncertainty to the total uncertainty ranges from 18–2.4 %, depending on the Higgs boson production mechanism. A method for estimating the number of events in a Monte Carlo background sample required to model the shape is detailed. It was found that the size of the nominal γγ background events sample required a multiplicative increase by a factor of 3.60 to adequately model the background with a confidence level of 68 %, or a factor of 7.20 for a confidence level of 95 %. Based on this estimate, 0.5 billion additional simulated events were produced, substantially reducing the background modelling uncertainty. A technique is detailed for emulating the effects of Monte Carlo event generator differences using multivariate reweighting. The technique is used to estimate the event generator uncertainty on the signal modelling of tHqb events, improving the reliability of estimating the tHqb production cross-section. Then this multivariate reweighting technique is used to estimate the generator modelling uncertainties on background V γγ samples for the first time. The estimated uncertainties were found to be covered by the currently assumed background modelling uncertainty

    Discovering the hidden structure of financial markets through bayesian modelling

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    Understanding what is driving the price of a financial asset is a question that is currently mostly unanswered. In this work we go beyond the classic one step ahead prediction and instead construct models that create new information on the behaviour of these time series. Our aim is to get a better understanding of the hidden structures that drive the moves of each financial time series and thus the market as a whole. We propose a tool to decompose multiple time series into economically-meaningful variables to explain the endogenous and exogenous factors driving their underlying variability. The methodology we introduce goes beyond the direct model forecast. Indeed, since our model continuously adapts its variables and coefficients, we can study the time series of coefficients and selected variables. We also present a model to construct the causal graph of relations between these time series and include them in the exogenous factors. Hence, we obtain a model able to explain what is driving the move of both each specific time series and the market as a whole. In addition, the obtained graph of the time series provides new information on the underlying risk structure of this environment. With this deeper understanding of the hidden structure we propose novel ways to detect and forecast risks in the market. We investigate our results with inferences up to one month into the future using stocks, FX futures and ETF futures, demonstrating its superior performance according to accuracy of large moves, longer-term prediction and consistency over time. We also go in more details on the economic interpretation of the new variables and discuss the created graph structure of the market.Open Acces

    Targeting Fusion Proteins of HIV-1 and SARS-CoV-2

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    Viruses are disease-causing pathogenic agents that require host cells to replicate. Fusion of host and viral membranes is critical for the lifecycle of enveloped viruses. Studying viral fusion proteins can allow us to better understand how they shape immune responses and inform the design of therapeutics such as drugs, monoclonal antibodies, and vaccines. This thesis discusses two approaches to targeting two fusion proteins: Env from HIV-1 and S from SARS-CoV-2. The first chapter of this thesis is an introduction to viruses with a specific focus on HIV-1 CD4 mimetic drugs and antibodies against SARS-CoV-2. It discusses the architecture of these viruses and fusion proteins and how small molecules, peptides, and antibodies can target these proteins successfully to treat and prevent disease. In addition, a brief overview is included of the techniques involved in structural biology and how it has informed the study of viruses. For the interested reader, chapter 2 contains a review article that serves as a more in-depth introduction for both viruses as well as how the use of structural biology has informed the study of viral surface proteins and neutralizing antibody responses to them. The subsequent chapters provide a body of work divided into two parts. The first part in chapter 3 involves a study on conformational changes induced in the HIV-1 Env protein by CD4-mimemtic drugs using single particle cryo-EM. The second part encompassing chapters 4 and 5 includes two studies on antibodies isolated from convalescent COVID-19 donors. The former involves classification of antibody responses to the SARS-CoV-2 S receptor-binding domain (RBD). The latter discusses an anti-RBD antibody class that binds to a conserved epitope on the RBD and shows cross-binding and cross-neutralization to other coronaviruses in the sarbecovirus subgenus.</p

    Towards personalized immunotherapy : development of in vitro models for imaging natural killer cell behavior in the tumor microenvironment

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    Tremendous advances in the tumor immunology field have transformed immunotherapy from a promising approach to a standard clinical practice. However, a subset of cancer patients is non-responsive to immunotherapy. More research is therefore needed to understand the mechanisms underlying tumor resistance to immunotherapeutic treatments. The aim of this doctoral work was to develop new tools to study the mechanisms of cancer immunosurveillance and to test immunotherapeutic treatments in vitro. In this thesis, I describe the methods developed, and I discuss the main biological findings obtained by using these methods. The thesis is organized as follows. A short historical background of immunotherapy is provided in Chapter 1. Chapter 2 describes the principles of NK cell-mediated cancer immunosurveillance, and provides an overview on rare cancers, mainly focusing on sarcoma. The research aims are listed in Chapter 3. In Chapter 4, I describe the cell culture methods and cell analysis techniques relevant for my doctoral work. In Chapter 5, I describe the methods we developed to culture tumor spheroids in vitro using ultrasonic standing waves in microwell chips, focusing on the theory, design, and applications. Chapter 6 and Chapter 7 focus on the biological findings obtained using our platform in combination with traditional immunological methods, followed by future implementations discussed in Chapter 8. The constituent papers are provided at the end of the thesis. In Paper I, we combined the use of the microwell chip, ultrasonic standing waves and a protein-repellent polymer coating to enable the production of spheroids from multiple cell types. In absence of cell adhesion to the chip, spheroids could be collected and further analyzed by off-the-chip techniques. In Paper II, we designed a novel multichambered microwell chip to perform multiplexed fluorescence screening of two- or three-dimensional cell cultures. The platform allows the direct assessment of drug or immune cell cytotoxic efficacy, making it a promising tool for individualized cytotoxicity tests for personalized medicine. In Paper III, we investigate the function of PVR receptors in NK cells interacting with renal carcinoma spheroids, and the impact of PVR in NK cell-based cellular immunotherapy. We demonstrated that variations in PVR expression are primarily recognized by the inhibitory receptor TIGIT, while DNAM-1 strongly contributes to NK cell activation mainly through PVR-independent mechanisms. We performed NK cell-based cytotoxicity assays against renal carcinoma spheroids in the microwell chip. Anti-TIGIT treatment was effective only for TIGIThigh NK cells both when used as monotherapy or in combination with other drugs, suggesting that only a fraction of patients might respond to anti-TIGIT therapy. In Paper IV, a similar approach was used with primary sarcomas. We cultured patient-derived sarcoma spheroids and tested NK cell-based immunotherapy in the microwell chip, either alone or in combination with antibody therapy, and we identified promising treatment combinations. In Paper V, we applied the use of expansion microscopy to visualize NK cells infiltrating renal carcinoma spheroids. In conclusion, our multi-disciplinary work shows the development of new imaging-based platform and its use to study the mechanisms of NK cell-mediated tumor surveillance and for personalized therapy

    RNA pull-down-confocal nanoscanning (RP-CONA), a novel method for studying RNA/protein interactions in cell extracts that detected potential drugs for Parkinson’s disease targeting RNA/HuR complexes

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    MicroRNAs (miRNAs, miRs) are a class of small non-coding RNAs that regulate gene expression through specific base-pair targeting. The functional mature miRNAs usually undergo a two-step cleavage from primary miRNAs (pri-miRs), then precursor miRNAs (pre-miRs). The biogenesis of miRNAs is tightly controlled by different RNA-binding proteins (RBPs). The dysregulation of miRNAs is closely related to a plethora of diseases. Targeting miRNA biogenesis is becoming a promising therapeutic strategy. HuR and MSI2 are both RBPs. MiR-7 is post-transcriptionally inhibited by the HuR/MSI2 complex, through a direct interaction between HuR and the conserved terminal loop (CTL) of pri-miR-7-1. Small molecules dissociating pri-miR-7/HuR interaction may induce miR-7 production. Importantly, the miR-7 levels are negatively correlated with Parkinson’s disease (PD). PD is a common, incurable neurodegenerative disease causing serious motor deficits. A hallmark of PD is the presence of Lewy bodies in the human brain, which are inclusion bodies mainly composed of an aberrantly aggregated protein named α-synuclein (α-syn). Decreasing α-syn levels or preventing α-syn aggregation are under investigation as PD treatments. Notably, α-syn is negatively regulated by several miRNAs, including miR-7, miR-153, miR-133b and others. One hypothesis is that elevating these miRNA levels can inhibit α-syn expression and ameliorate PD pathologies. In this project, we identified miR-7 as the most effective α-syn inhibitor, among the miRNAs that are downregulated in PD, and with α-syn targeting potentials. We also observed potential post-transcriptional inhibition on miR-153 biogenesis in neuroblastoma, which may help to uncover novel therapeutic targets towards PD. To identify miR-7 inducers that benefit PD treatment by repressing α-syn expression, we developed a novel technique RNA Pull-down Confocal Nanoscaning (RP-CONA) to monitor the binding events between pri-miR-7 and HuR. By attaching FITC-pri-miR-7-1-CTL-biotin to streptavidin-coated agarose beads and incubating them in human cultured cell lysates containing overexpressed mCherry-HuR, the bound RNA and protein can be visualised as quantifiable fluorescent rings in corresponding channels in a confocal high-content image system. A pri-miR-7/HuR inhibitor can decrease the relative mCherry/FITC intensity ratio in RP-CONA. With this technique, we performed several small-scale screenings and identified that a bioflavonoid, quercetin can largely dissociate the pri-miR-7/HuR interaction. Further studies proved that quercetin was an effective miR-7 inducer as well as α-syn inhibitor in HeLa cells. To understand the mechanism of quercetin mediated α-syn inhibition, we tested the effects of quercetin treatment with miR-7-1 and HuR knockout HeLa cells. We found that HuR was essential in this pathway, while miR-7 hardly contributed to the α-syn inhibition. HuR can directly bind an AU-rich element (ARE) at the 3’ untranslated region (3’-UTR) of α-syn mRNA and promote translation. We believe quercetin mainly disrupts the ARE/HuR interaction and disables the HuR-induced α-syn expression. In conclusion, we developed and optimised RP-CONA, an on-bead, lysate-based technique detecting RNA/protein interactions, as well as identifying RNA/protein modulators. With RP-CONA, we found quercetin inducing miR-7 biogenesis, and inhibiting α-syn expression. With these beneficial effects, quercetin has great potential to be applied in the clinic of PD treatment. Finally, RP-CONA can be used in many other RNA/protein interactions studies

    Proof of Concept of Therapeutic Gene Modulation of MBNL1/2 in Myotonic Dystrophy

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    La distrofia miotónica tipo 1 es una enfermedad genética rara multisistémica que afecta a 1 de cada 3000-8000 personas. La causa molecular de la enfermedad proviene de repeticiones tóxicas “CTG” en el gen DMPK (DM Protein Kinase). Tras la transcripción, estas repeticiones forman una estructura de horquilla que se une con alta afinidad a la familia de proteínas MBNL (Muscleblind-like) que agota su función de regulación de la poliadenilación y el splicing alternativo postranscripcional en numerosos transcritos. La pérdida de función de MBNL provoca una cascada de efectos posteriores, que eventualmente conducen a síntomas clínicos que incluyen miotonía, debilidad y atrofia muscular, cataratas, disfunción cardíaca y trastorno cognitivo. La restauración de la función de la proteína MBNL es clave para aliviar los síntomas debilitantes de esta enfermedad. Se han utilizado oligonucleótidos antisentido (AON) para apuntar a las repeticiones de DMPK y liberar MBNL del secuestro, lo que da como resultado resultados terapéuticos prometedores en modelos celulares y animales de la enfermedad. Otro factor que interviene en la pérdida de función de las proteínas MBNL son los miRNAs que regulan su traducción. Aquí se muestra el uso de AON dirigidos a la actividad de miR-23b y miR-218, que se ha demostrado previamente que regulan directamente MBNL1 y MBNL2. Estos antimiRs recibieron modificaciones FANA para aumentar su entrega en las células y reducir la toxicidad. También se probaron los AON, denominados blockmiRs, que se unen de manera complementaria a los sitios de unión confirmados de miR-23b y miR-218 en los 3'-UTR de las transcripciones de MBNL1 y MBNL2. De esta manera, los miRNAs no pueden unirse y regular la traducción de MBNL, lo que aumenta la cantidad de proteína MBNL producida en una célula deficiente. Aquí se propone el uso de AON de nuevo diseño dirigidos a la actividad de miR-23b y miR-218 para regular MBNL1 y MBNL2 a través de (1) exploración del bloqueo de miRNA a través de FANA-antimiR AON in vitro, (2) exploración del bloqueo del sitio de unión de miRNA a través de la estrategia blockmiR in vitro e in vivo con el uso de modificaciones químicas de LNA, y (3) mejora de la química de la estrategia blockmiR mediante el uso de tecnología de péptidos de penetración celular in vitro e in vivo.Myotonic Dystrophy Type 1 is a multi-systemic rare genetic disease affecting 1 in 3000-8000 people. The molecular cause of the disease stems from toxic “CTG” repetitions in the DMPK (DM Protein Kinase) gene. Upon transcription, these repetitions form a hairpin structure that binds with high affinity to the MBNL (Muscleblind-like) family of proteins depleting their function of post-transcriptional alternative splicing and polyadenylation regulation on numerous transcripts. MBNL loss-of-function causes a cascade of downstream effects, which eventually lead to clinical symptoms including myotonia, muscle weakness and atrophy, cataracts, cardiac dysfunction, and cognitive disorder. The restoration of MBNL protein function is key to relieving the debilitating symptoms of this disease. Antisense oligonucleotides (AONs) have been used to target the DMPK repeats and release MBNL from sequestration resulting in promising therapeutic results in cellular and animal models of the disease. Another factor playing a role in the loss-of-function of MBNL proteins are the miRNAs that regulate their translation. Here is shown the use of AONs targeting miR-23b and miR-218 activity, which have been previously shown to directly regulate MBNL1 and MBNL2. These antimiRs were given FANA modifications to increase their delivery in cells and lower toxicity. Also tested are AONs, termed blockmiRs, that complementary bind to the confirmed binding sites of miR-23b and miR-218 in the 3’-UTRs of MBNL1 and MBNL2 transcripts. In this way, the miRNAs are unable to bind and regulate the translation of MBNL thereby augmenting the amount of MBNL protein made in an otherwise deficient cell. Proposed here is the use of newly designed AONs targeting miR-23b and miR-218 activity in order to regulate MBNL1 and MBNL2 through (1) exploration of miRNA blocking through FANA-antimiR AONs in vitro, (2) exploration of miRNA binding site blocking through blockmiR strategy in vitro and in vivo with the use of LNA chemical modifications, and (3) improvement of the chemistry of the blockmiR strategy through the use of cell penetrating peptide technology in vitro and in vivo

    Innovative Hybrid Approaches for Vehicle Routing Problems

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    This thesis deals with the efficient resolution of Vehicle Routing Problems (VRPs). The first chapter faces the archetype of all VRPs: the Capacitated Vehicle Routing Problem (CVRP). Despite having being introduced more than 60 years ago, it still remains an extremely challenging problem. In this chapter I design a Fast Iterated-Local-Search Localized Optimization algorithm for the CVRP, shortened to FILO. The simplicity of the CVRP definition allowed me to experiment with advanced local search acceleration and pruning techniques that have eventually became the core optimization engine of FILO. FILO experimentally shown to be extremely scalable and able to solve very large scale instances of the CVRP in a fraction of the computing time compared to existing state-of-the-art methods, still obtaining competitive solutions in terms of their quality. The second chapter deals with an extension of the CVRP called the Extended Single Truck and Trailer Vehicle Routing Problem, or simply XSTTRP. The XSTTRP models a broad class of VRPs in which a single vehicle, composed of a truck and a detachable trailer, has to serve a set of customers with accessibility constraints making some of them not reachable by using the entire vehicle. This problem moves towards VRPs including more realistic constraints and it models scenarios such as parcel deliveries in crowded city centers or rural areas, where maneuvering a large vehicle is forbidden or dangerous. The XSTTRP generalizes several well known VRPs such as the Multiple Depot VRP and the Location Routing Problem. For its solution I developed an hybrid metaheuristic which combines a fast heuristic optimization with a polishing phase based on the resolution of a limited set partitioning problem. Finally, the thesis includes a final chapter aimed at guiding the computational evaluation of new approaches to VRPs proposed by the machine learning community
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