A Farewell to Flat Biology. Three-dimensional Cell Culture Models in Cancer Drug Target Identification and Validation

Cells of epithelial origin, e.g. from breast and prostate cancers, effectively differentiate into complex multicellular structures when cultured in three-dimensions (3D) instead of conventional two-dimensional (2D) adherent surfaces. The spectrum of different organotypic morphologies is highly dependent on the culture environment that can be either non-adherent or scaffold-based. When embedded in physiological extracellular matrices (ECMs), such as laminin-rich basement membrane extracts, normal epithelial cells differentiate into acinar spheroids reminiscent of glandular ductal structures. Transformed cancer cells, in contrast, typically fail to undergo acinar morphogenic patterns, forming poorly differentiated or invasive multicellular structures. The 3D cancer spheroids are widely accepted to better recapitulate various tumorigenic processes and drug responses. So far, however, 3D models have been employed predominantly in the Academia, whereas the pharmaceutical industry has yet to adopt a more widely and routine use. This is mainly due to poor characterisation of cell models, lack of standardised workflows and high throughput cell culture platforms, and the availability of proper readout and quantification tools. In this thesis, a complete workflow has been established entailing well-characterised 3D cell culture models for prostate cancer, a standardised 3D cell culture routine based on high-throughput-ready platform, automated image acquisition with concomitant morphometric image analysis, and data visualisation, in order to enable large-scale high-content screens. Our integrated suite of software and statistical analysis tools were optimised and validated using a comprehensive panel of prostate cancer cell lines and 3D models. The tools quantify multiple key cancer-relevant morphological features, ranging from cancer cell invasion through multicellular differentiation to growth, and detect dynamic changes both in morphology and function, such as cell death and apoptosis, in response to experimental perturbations including RNA interference and small molecule inhibitors. Our panel of cell lines included many non-transformed and most currently available classic prostate cancer cell lines, which were characterised for their morphogenetic properties in 3D laminin-rich ECM. The phenotypes and gene expression profiles were evaluated concerning their relevance for pre-clinical drug discovery, disease modelling and basic research. In addition, a spontaneous model for invasive transformation was discovered, displaying a highdegree of epithelial plasticity. This plasticity is mediated by an abundant bioactive serum lipid, lysophosphatidic acid (LPA), and its receptor LPAR1. The invasive transformation was caused by abrupt cytoskeletal rearrangement through impaired G protein alpha 12/13 and RhoA/ROCK, and mediated by upregulated adenylyl cyclase/cyclic AMP (cAMP)/protein kinase A, and Rac/ PAK pathways. The spontaneous invasion model tangibly exemplifies the biological relevance of organotypic cell culture models. Overall, this thesis work underlines the power of novel morphometric screening tools in drug discovery.

L'Univers

1894/12/13 (Numéro 9682).

L'Univers

1903/12/13 (Numéro 13058).

L'Univers

1896/12/13 (Numéro 10559).

L'Univers

1883/12/13 (Numéro 5866).

Production of Mg(OH)2 from Mg-silicate rock for CO2 mineral sequestration

Sequestration of carbon dioxide in mineral rocks, also known as CO2 Capture and Mineralization (CCM), is considered to have a huge potential in stabilizing anthropogenic CO2 emissions. One of the CCM routes is the ex situ indirect gas/sold carbonation of reactive materials, such as Mg(OH)2, produced from abundantly available Mg-silicate rocks. The gas/solid carbonation method is intensively researched at Åbo Akademi University (ÅAU ), Finland because it is energetically attractive and utilizes the exothermic chemistry of Mg(OH)2 carbonation. In this thesis, a method for producing Mg(OH)2 from Mg-silicate rocks for CCM was investigated, and the process efficiency, energy and environmental impact assessed. The Mg(OH)2 process studied here was first proposed in 2008 in a Master’s Thesis by the author. At that time the process was applied to only one Mg-silicate rock (Finnish serpentinite from the Hitura nickel mine site of Finn Nickel) and the optimum process conversions, energy and environmental performance were not known. Producing Mg(OH)2 from Mg-silicate rocks involves a two-staged process of Mg extraction and Mg(OH)2 precipitation. The first stage extracts Mg and other cations by reacting pulverized serpentinite or olivine rocks with ammonium sulfate (AS) salt at 400 - 550 oC (preferably < 450 oC). In the second stage, ammonia solution reacts with the cations (extracted from the first stage after they are leached in water) to form mainly FeOOH, high purity Mg(OH)2 and aqueous (dissolved) AS. The Mg(OH)2 process described here is closed loop in nature; gaseous ammonia and water vapour are produced from the extraction stage, recovered and used as reagent for the precipitation stage. The AS reagent is thereafter recovered after the precipitation stage. The Mg extraction stage, being the conversion-determining and the most energy-intensive step of the entire CCM process chain, received a prominent attention in this study. The extraction behavior and reactivity of different rocks types (serpentinite and olivine rocks) from different locations worldwide (Australia, Finland, Lithuania, Norway and Portugal) was tested. Also, parametric evaluation was carried out to determine the optimal reaction temperature, time and chemical reagent (AS). Effects of reactor types and configuration, mixing and scale-up possibilities were also studied. The Mg(OH)2 produced can be used to convert CO2 to thermodynamically stable and environmentally benign magnesium carbonate. Therefore, the process energy and life cycle environmental performance of the ÅAU CCM technique that first produces Mg(OH)2 and the carbonates in a pressurized fluidized bed (FB) were assessed. The life cycle energy and environmental assessment approach applied in this thesis is motivated by the fact that the CCM technology should in itself offer a solution to what is both an energy and environmental problem. Results obtained in this study show that different Mg-silicate rocks react differently; olivine rocks being far less reactive than serpentinite rocks. In summary, the reactivity of Mg-silicate rocks is a function of both the chemical and physical properties of rocks. Reaction temperature and time remain important parameters to consider in process design and operation. Heat transfer properties of the reactor determine the temperature at which maximum Mg extraction is obtained. Also, an increase in reaction temperature leads to an increase in the extent of extraction, reaching a maximum yield at different temperatures depending on the reaction time. Process energy requirement for producing Mg(OH)2 from a hypothetical case of an iron-free serpentine rock is 3.62 GJ/t-CO2. This value can increase by 16 - 68% depending on the type of iron compound (FeO, Fe2O3 or Fe3O4) in the mineral. This suggests that the benefit from the potential use of FeOOH as an iron ore feedstock in iron and steelmaking should be determined by considering the energy, cost and emissions associated with the FeOOH by-product. AS recovery through crystallization is the second most energy intensive unit operation after the extraction reaction. However, the choice of mechanical vapor recompression (MVR) over the “simple evaporation” crystallization method has a potential energy savings of 15.2 GJ/t-CO2 (84 % savings). Integrating the Mg(OH)2 production method and the gas/solid carbonation process could provide up to an 25% energy offset to the CCM process energy requirements. Life cycle inventory assessment (LCIA) results show that for every ton of CO2 mineralized, the ÅAU CCM process avoids 430 - 480 kg CO2. The Mg(OH)2 process studied in this thesis has many promising features. Even at the current high energy and environmental burden, producing Mg(OH)2 from Mg-silicates can play a significant role in advancing CCM processes. However, dedicated future research and development (R&D) have potential to significantly improve the Mg(OH)2 process performance.

Analysis and validation of space averaged drag model for numerical simulations of gas-solid flows in fluidized beds

This thesis presents an approach for formulating and validating a space averaged drag model for coarse mesh simulations of gas-solid flows in fluidized beds using the two-fluid model. Proper modeling for fluid dynamics is central in understanding any industrial multiphase flow. The gas-solid flows in fluidized beds are heterogeneous and usually simulated with the Eulerian description of phases. Such a description requires the usage of fine meshes and small time steps for the proper prediction of its hydrodynamics. Such constraint on the mesh and time step size results in a large number of control volumes and long computational times which are unaffordable for simulations of large scale fluidized beds. If proper closure models are not included, coarse mesh simulations for fluidized beds do not give reasonable results. The coarse mesh simulation fails to resolve the mesoscale structures and results in uniform solids concentration profiles. For a circulating fluidized bed riser, such predicted profiles result in a higher drag force between the gas and solid phase and also overestimated solids mass flux at the outlet. Thus, there is a need to formulate the closure correlations which can accurately predict the hydrodynamics using coarse meshes. This thesis uses the space averaging modeling approach in the formulation of closure models for coarse mesh simulations of the gas-solid flow in fluidized beds using Geldart group B particles. In the analysis of formulating the closure correlation for space averaged drag model, the main parameters for the modeling were found to be the averaging size, solid volume fraction, and distance from the wall. The closure model for the gas-solid drag force was formulated and validated for coarse mesh simulations of the riser, which showed the verification of this modeling approach. Coarse mesh simulations using the corrected drag model resulted in lowered values of solids mass flux. Such an approach is a promising tool in the formulation of appropriate closure models which can be used in coarse mesh simulations of large scale fluidized beds.

L'Univers

1895/12/13 (Numéro 10197).

Bulletin officiel du Ministère de l'éducation nationale

1945/12/13 (N66).

La Jeunesse illustrée

1931/12/13 (N1471).

La Jeunesse illustrée

1903/12/13 (N42).

La Jeunesse illustrée

1925/12/13 (N1158).

La Jeunesse illustrée

1931/12/13 (N1471).

Novel Methods for Error Modeling and Parameter Identification of a Redundant Serial-Parallel Hybrid Robot

To obtain the desirable accuracy of a robot, there are two techniques available. The first option would be to make the robot match the nominal mathematic model. In other words, the manufacturing and assembling tolerances of every part would be extremely tight so that all of the various parameters would match the “design” or “nominal” values as closely as possible. This method can satisfy most of the accuracy requirements， but the cost would increase dramatically as the accuracy requirement increases. Alternatively, a more cost-effective solution is to build a manipulator with relaxed manufacturing and assembling tolerances. By modifying the mathematical model in the controller, the actual errors of the robot can be compensated. This is the essence of robot calibration. Simply put, robot calibration is the process of defining an appropriate error model and then identifying the various parameter errors that make the error model match the robot as closely as possible. This work focuses on kinematic calibration of a 10 degree-of-freedom (DOF) redundant serial-parallel hybrid robot. The robot consists of a 4-DOF serial mechanism and a 6-DOF hexapod parallel manipulator. The redundant 4-DOF serial structure is used to enlarge workspace and the 6-DOF hexapod manipulator is used to provide high load capabilities and stiffness for the whole structure. The main objective of the study is to develop a suitable calibration method to improve the accuracy of the redundant serial-parallel hybrid robot. To this end, a Denavit–Hartenberg (DH) hybrid error model and a Product-of-Exponential (POE) error model are developed for error modeling of the proposed robot. Furthermore, two kinds of global optimization methods, i.e. the differential-evolution (DE) algorithm and the Markov Chain Monte Carlo (MCMC) algorithm, are employed to identify the parameter errors of the derived error model. A measurement method based on a 3-2-1 wire-based pose estimation system is proposed and implemented in a Solidworks environment to simulate the real experimental validations. Numerical simulations and Solidworks prototype-model validations are carried out on the hybrid robot to verify the effectiveness, accuracy and robustness of the calibration algorithms.