8,826 research outputs found

    Hidden in the dark:Seeking the vanished polycylic aromatic hydrocarbons in planet-forming discs

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    The origin of life is closely linked to the formation of planetary systems, and both are fundamental drivers of modern astronomical research. Especially carbon is of interest as it is the building block of life as we know.In the interstellar medium, about 15 % of carbon is locked in the form of polycyclic aromatic hydrocarbons (PAHs). The infrared signals of these complex molecules have been observed in numerous astrophysical environments. Their detection in planet-forming discs is of particular interest, as these are the birth-sites of exoplanets. By understanding the evolution of PAHs during planet formation, it is possible to trace a large fraction of carbon. Additionally, the signals of PAHs can reveal crucial information about planet-forming discs themselves to better understand planet formation.This thesis particularly focuses on the formation of molecular clusters of PAHs bound by van der Walls forces in planet forming discs. We analysed the stability of PAH clusters against stellar UV radiation from young stars and modelled their dissociation rates. Further, we model the evolution of clusters in the presence of dust grains, as they interact through freeze-out. Then, we investigate the depletion of observable gas-phase PAHs which has been observed in many discs. Next, we simulate observations and discuss the amount of retrievable information from spectra. Finally, we investigate the interaction of PAHs with stellar X-rays from T Tauri discs and their influence on the destruction of PAHs and PAH clusters

    Graduate Catalog of Studies, 2023-2024

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    Multi-epoch machine learning for galaxy formation

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    In this thesis I utilise a range of machine learning techniques in conjunction with hydrodynamical cosmological simulations. In Chapter 2 I present a novel machine learning method for predicting the baryonic properties of dark matter only subhalos taken from N-body simulations. The model is built using a tree-based algorithm and incorporates subhalo properties over a wide range of redshifts as its input features. I train the model using a hydrodynamical simulation which enables it to predict black hole mass, gas mass, magnitudes, star formation rate, stellar mass, and metallicity. This new model surpasses the performance of previous models. Furthermore, I explore the predictive power of each input property by looking at feature importance scores from the tree-based model. By applying the method to the LEGACY N-body simulation I generate a large volume mock catalog of the quasar population at z=3. By comparing this mock catalog with observations, I demonstrate that the IllustrisTNG subgrid model for black holes is not accurately capturing the growth of the most massive objects. In Chapter 3 I apply my method to investigate the evolution of galaxy properties in different simulations, and in various environments within a single simulation. By comparing the Illustris, EAGLE, and TNG simulations I show that subgrid model physics plays a more significant role than the choice of hydrodynamics method. Using the CAMELS simulation suite I consider the impact of cosmological and astrophysical parameters on the buildup of stellar mass within the TNG and SIMBA models. In the final chapter I apply a combination of neural networks and symbolic regression methods to construct a semi-analytic model which reproduces the galaxy population from a cosmological simulation. The neural network based approach is capable of producing a more accurate population than a previous method of binning based on halo mass. The equations resulting from symbolic regression are found to be a good approximation of the neural network

    Converging organoids and extracellular matrix::New insights into liver cancer biology

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    Brittle-viscous deformation cycles at the base of the seismogenic zone in the continental crust

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    The main goal of the study was to determine the dynamical cycle of ductile-brittle deformation and to characterise the fluid pathways at different scales of a brittle-viscous fault zone active at the base of the seismogenic crust. Object of analysis are samples from the sinistral strike-slip fault zone BFZ045 from Olkiluoto (SW Finland), located at the site of a deep geological repository for nuclear waste. Combined microstructural analysis, electron backscatter diffraction (EBSD), and mineral chemistry were applied to reconstruct the variations in pressure, temperature, fluid pressure, and differential stress that mediated deformation and strain localization along BFZ045 across the BDTZ. Ductile deformation took place at 400-500° C and 3-4 kbar, and recrystallized grain size piezometry for quartz document a progressive increase in differential stress during mylonitization, from ca. 50 MPa to ca. 120 MPa. The increase in differential stress was localised towards the shear zone center, which was eventually overprinted by brittle deformation in a narrowing shear zone. Cataclastic deformation occurred under lower T conditions down to T ≥ 320° C and was not further overprinted by mylonitic creep. Porosity estimates were obtained through the combination of x-ray micro-computed tomography (µCT), mercury intrusion porosimetry, He pycnometry, and microstructural analysis. Low porosity values (0.8-4.4%) for different rock type, 2-20 µm pore size, representative of pore connectivity, and microstructural observation suggest a relationship to a dynamical cycle of fracturing and sealing mechanism, mostly controlled by ductile deformation. Similarly, the observation from fracture orientation analysis indicates that the mylonitic precursor of BFZ045 played an important role in the localization of the brittle deformation. This thesis highlights that the ductile-brittle deformation cycle in BFZ045 was controlled by transient oscillations in fluid pressure in a narrowing shear zone deforming at progressively higher differential stress during cooling

    Converging organoids and extracellular matrix::New insights into liver cancer biology

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    Primary liver cancer, consisting primarily of hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), is a heterogeneous malignancy with a dismal prognosis, resulting in the third leading cause of cancer mortality worldwide [1, 2]. It is characterized by unique histological features, late-stage diagnosis, a highly variable mutational landscape, and high levels of heterogeneity in biology and etiology [3-5]. Treatment options are limited, with surgical intervention the main curative option, although not available for the majority of patients which are diagnosed in an advanced stage. Major contributing factors to the complexity and limited treatment options are the interactions between primary tumor cells, non-neoplastic stromal and immune cells, and the extracellular matrix (ECM). ECM dysregulation plays a prominent role in multiple facets of liver cancer, including initiation and progression [6, 7]. HCC often develops in already damaged environments containing large areas of inflammation and fibrosis, while CCA is commonly characterized by significant desmoplasia, extensive formation of connective tissue surrounding the tumor [8, 9]. Thus, to gain a better understanding of liver cancer biology, sophisticated in vitro tumor models need to incorporate comprehensively the various aspects that together dictate liver cancer progression. Therefore, the aim of this thesis is to create in vitro liver cancer models through organoid technology approaches, allowing for novel insights into liver cancer biology and, in turn, providing potential avenues for therapeutic testing. To model primary epithelial liver cancer cells, organoid technology is employed in part I. To study and characterize the role of ECM in liver cancer, decellularization of tumor tissue, adjacent liver tissue, and distant metastatic organs (i.e. lung and lymph node) is described, characterized, and combined with organoid technology to create improved tissue engineered models for liver cancer in part II of this thesis. Chapter 1 provides a brief introduction into the concepts of liver cancer, cellular heterogeneity, decellularization and organoid technology. It also explains the rationale behind the work presented in this thesis. In-depth analysis of organoid technology and contrasting it to different in vitro cell culture systems employed for liver cancer modeling is done in chapter 2. Reliable establishment of liver cancer organoids is crucial for advancing translational applications of organoids, such as personalized medicine. Therefore, as described in chapter 3, a multi-center analysis was performed on establishment of liver cancer organoids. This revealed a global establishment efficiency rate of 28.2% (19.3% for hepatocellular carcinoma organoids (HCCO) and 36% for cholangiocarcinoma organoids (CCAO)). Additionally, potential solutions and future perspectives for increasing establishment are provided. Liver cancer organoids consist of solely primary epithelial tumor cells. To engineer an in vitro tumor model with the possibility of immunotherapy testing, CCAO were combined with immune cells in chapter 4. Co-culture of CCAO with peripheral blood mononuclear cells and/or allogenic T cells revealed an effective anti-tumor immune response, with distinct interpatient heterogeneity. These cytotoxic effects were mediated by cell-cell contact and release of soluble factors, albeit indirect killing through soluble factors was only observed in one organoid line. Thus, this model provided a first step towards developing immunotherapy for CCA on an individual patient level. Personalized medicine success is dependent on an organoids ability to recapitulate patient tissue faithfully. Therefore, in chapter 5 a novel organoid system was created in which branching morphogenesis was induced in cholangiocyte and CCA organoids. Branching cholangiocyte organoids self-organized into tubular structures, with high similarity to primary cholangiocytes, based on single-cell sequencing and functionality. Similarly, branching CCAO obtain a different morphology in vitro more similar to primary tumors. Moreover, these branching CCAO have a higher correlation to the transcriptomic profile of patient-paired tumor tissue and an increased drug resistance to gemcitabine and cisplatin, the standard chemotherapy regimen for CCA patients in the clinic. As discussed, CCAO represent the epithelial compartment of CCA. Proliferation, invasion, and metastasis of epithelial tumor cells is highly influenced by the interaction with their cellular and extracellular environment. The remodeling of various properties of the extracellular matrix (ECM), including stiffness, composition, alignment, and integrity, influences tumor progression. In chapter 6 the alterations of the ECM in solid tumors and the translational impact of our increased understanding of these alterations is discussed. The success of ECM-related cancer therapy development requires an intimate understanding of the malignancy-induced changes to the ECM. This principle was applied to liver cancer in chapter 7, whereby through a integrative molecular and mechanical approach the dysregulation of liver cancer ECM was characterized. An optimized agitation-based decellularization protocol was established for primary liver cancer (HCC and CCA) and paired adjacent tissue (HCC-ADJ and CCA-ADJ). Novel malignancy-related ECM protein signatures were found, which were previously overlooked in liver cancer transcriptomic data. Additionally, the mechanical characteristics were probed, which revealed divergent macro- and micro-scale mechanical properties and a higher alignment of collagen in CCA. This study provided a better understanding of ECM alterations during liver cancer as well as a potential scaffold for culture of organoids. This was applied to CCA in chapter 8 by combining decellularized CCA tumor ECM and tumor-free liver ECM with CCAO to study cell-matrix interactions. Culture of CCAO in tumor ECM resulted in a transcriptome closely resembling in vivo patient tumor tissue, and was accompanied by an increase in chemo resistance. In tumor-free liver ECM, devoid of desmoplasia, CCAO initiated a desmoplastic reaction through increased collagen production. If desmoplasia was already present, distinct ECM proteins were produced by the organoids. These were tumor-related proteins associated with poor patient survival. To extend this method of studying cell-matrix interactions to a metastatic setting, lung and lymph node tissue was decellularized and recellularized with CCAO in chapter 9, as these are common locations of metastasis in CCA. Decellularization resulted in removal of cells while preserving ECM structure and protein composition, linked to tissue-specific functioning hallmarks. Recellularization revealed that lung and lymph node ECM induced different gene expression profiles in the organoids, related to cancer stem cell phenotype, cell-ECM integrin binding, and epithelial-to-mesenchymal transition. Furthermore, the metabolic activity of CCAO in lung and lymph node was significantly influenced by the metastatic location, the original characteristics of the patient tumor, and the donor of the target organ. The previously described in vitro tumor models utilized decellularized scaffolds with native structure. Decellularized ECM can also be used for creation of tissue-specific hydrogels through digestion and gelation procedures. These hydrogels were created from both porcine and human livers in chapter 10. The liver ECM-based hydrogels were used to initiate and culture healthy cholangiocyte organoids, which maintained cholangiocyte marker expression, thus providing an alternative for initiation of organoids in BME. Building upon this, in chapter 11 human liver ECM-based extracts were used in combination with a one-step microfluidic encapsulation method to produce size standardized CCAO. The established system can facilitate the reduction of size variability conventionally seen in organoid culture by providing uniform scaffolding. Encapsulated CCAO retained their stem cell phenotype and were amendable to drug screening, showing the feasibility of scalable production of CCAO for throughput drug screening approaches. Lastly, Chapter 12 provides a global discussion and future outlook on tumor tissue engineering strategies for liver cancer, using organoid technology and decellularization. Combining multiple aspects of liver cancer, both cellular and extracellular, with tissue engineering strategies provides advanced tumor models that can delineate fundamental mechanistic insights as well as provide a platform for drug screening approaches.<br/

    The Gemini Planet Imager Exoplanet Survey : giant planet and brown dwarf demographics from 10 to 100 au

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    We present a statistical analysis of the first 300 stars observed by the Gemini Planet Imager Exoplanet Survey. This subsample includes six detected planets and three brown dwarfs; from these detections and our contrast curves we infer the underlying distributions of substellar companions with respect to their mass, semimajor axis, and host stellar mass. We uncover a strong correlation between planet occurrence rate and host star mass, with stars M* > 1.5 M⊙ more likely to host planets with masses between 2 and 13MJup and semimajor axes of 3–100 au at 99.92% confidence. We fit a double power-law model in planet mass (m) and semimajor axis (a) for planet populations around high-mass stars (M* > 1.5 M⊙) of the form d2N/(dm da) ∝ mα aβ, finding α = −2.4 ± 0.8 and β = −2.0 ± 0.5, and an integrated occurrence rate of 9+5-4% between 5–13MJup and 10–100 au. A significantly lower occurrence rate is obtained for brown dwarfs around all stars, with 0.8+0.8-0.5% of stars hosting a brown dwarf companion between 13–80MJup and 10–100 au. Brown dwarfs also appear to be distributed differently in mass and semimajor axis compared to giant planets; whereas giant planets follow a bottom-heavy mass distribution and favor smaller semimajor axes, brown dwarfs exhibit just the opposite behaviors. Comparing to studies of short-period giant planets from the radial velocity method, our results are consistent with a peak in occurrence of giant planets between ∼1 and 10 au. We discuss how these trends, including the preference of giant planets for high-mass host stars, point to formation of giant planets by core/pebble accretion, and formation of brown dwarfs by gravitational instability.Peer reviewe

    Graduate Catalog of Studies, 2023-2024

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    Non-invasive and non-intrusive diagnostic techniques for gas-solid fluidized beds – A review

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    Gas-solid fluidized-bed systems offer great advantages in terms of chemical reaction efficiency and temperature control where other chemical reactor designs fall short. For this reason, they have been widely employed in a range of industrial application where these properties are essential. Nonetheless, the knowledge of such systems and the corresponding design choices, in most cases, rely on a heuristic expertise gained over the years rather than on a deep physical understanding of the phenomena taking place in fluidized beds. This is a huge limiting factor when it comes to the design, the scale-up and the optimization of such complex units. Fortunately, a wide array of diagnostic techniques has enabled researchers to strive in this direction, and, among these, non-invasive and non-intrusive diagnostic techniques stand out thanks to their innate feature of not affecting the flow field, while also avoiding direct contact with the medium under study. This work offers an overview of the non-invasive and non-intrusive diagnostic techniques most commonly applied to fluidized-bed systems, highlighting their capabilities in terms of the quantities they can measure, as well as advantages and limitations of each of them. The latest developments and the likely future trends are also presented. Neither of these methodologies represents a best option on all fronts. The goal of this work is rather to highlight what each technique has to offer and what application are they better suited for
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