The specification and modulation of cell-type specific dendritic morphologies plays a pivotal role in nervous system development, connectivity, structural plasticity, and function. Regulation of gene expression is controlled by a wide variety of cellular and molecular mechanisms, of which two major types are transcription factors (TFs) and microRNAs (miRNAs). In Drosophila, dendritic complexity of dendritic arborization (da) sensory neurons of the peripheral nervous system are known to be regulated by two transcription factors Cut and Knot, although much remains unknown about the molecular mechanisms and regulatory networks via which they regulate the final arbor shape through spatio-temporal modulation of dendritic development and dynamics. Here we use bioinformatics analysis of transcriptomic data to identify putative genomic targets of these TFs with a particular emphasis on those that effect neuronal cytoskeletal architecture. We use transcriptomic, as well as data from various genomic and protein interaction databases, to build a weighted functional gene regulatory network for Knot, to identify the biological pathways and downstream genes that this TF regulates. To corroborate bioinformatics network predictions, knot putative targets, which classify into neuronal and cytoskeletal functional groups, have been experimentally validated by in vivo genetic perturbations to elucidate their role in Knot-mediated Class IV (CIV) dendritogenesis. MicroRNAs (miRNAs) have emerged as key post-transcriptional regulators of gene expression, however identification of biologically-relevant target genes for this epigenetic regulatory mechanism remains a significant challenge. To address this knowledge gap, we have developed a novel R based tool, IntramiR-ExploreR, that facilitates integrated discovery of miRNA targets by incorporating target databases and novel target prediction algorithm to arrive at high confidence intragenic miRNA target predictions. We have explored the efficacy of this tool using D.melanogaster as a model organism for bioinformatics analyses and functional validation, and identified targets for 83 intragenic miRNAs. Predicted targets were validated, using in vivo genetic perturbation. Moreover, we are constructing interaction maps of intragenic miRNAs focusing on neural tissues to uncover regulatory codes via which these molecules regulate gene expression to direct cellular development.

Understanding the fundamental mechanisms of solidification and the relative significance of different parameters governing these mechanisms is of vital importance for controlling the evolution of microstructure during solidification, and consequently, for improving the efficacy of a casting process. Towards achieving this goal, the present work attempts to study the effect of convection and shrinkage on solidification and microstructure formation primarily through the development of computational models which are complemented with experimental investigations and analytical solutions. Convection strongly influences the solutal and thermal distribution adjacent to the solidification interface and affects the growth rate and morphology of dendrites. To investigate this, a numerical model based on the enthalpy method is developed for binary alloy dendrite growth in presence of convection. The model results are validated with corresponding predictions using level-set method and micro-solvability theory. Subsequently, the model is applied for studying the effect of convection on the growth morphology of single dendrites. Results show that the presence of flow significantly affects the thermo-solutal distribution and consequently the growth rate and morphology of dendrites. Parametric studies performed using the model predict that thermal and solutal Peclet number and melt undercooling strongly influence the tip velocity of dendrites. Additionally, an analytical model is developed to quantify the effect of convection on dendrite tip velocity through the definition of an equivalent undercooling. An expression for this equivalent undercooling is derived in terms of the flow Nusselt and Sherwood numbers and the analytical equivalent undercooling values are compared with corresponding predictions obtained using the numerical model. Subsequently, the interaction of multiple dendrites growing in close proximity is studied. It is observed that the presence of neighbouring dendrites strongly influences the thermo-solutal distribution in the domain leading to significant changes in growth pattern. The effect of seed density on the growth morphology is investigated and it is observed that a higher initial seeding density leads to more spherical dendritic structure. Comparison with results from chilled casting of Al-6.5% Cu alloy with and without grain refiners show qualitative similarity in both the cases. The next part of the thesis presents a eutectic solidification model developed using the general enthalpy-based framework for dendritic solidification. New parameters and rules are defined and suitable modifications are made to incorporate the physics of eutectic solidification and account for the additional complexities arising due to the presence of multiple solid phases. The model simulates the presence of buoyancy driven convection and its interaction with the solidification process. i The model predictions are found to be in good agreement with the Jackson-Hunt theory. At first, the model is applied to simulate regular eutectic growth in a purely diffusive environment and it is observed that the model predicts the variation in interface profile with change in lamella width similar to those observed in experimental studies on eutectic solidification. Subsequently, a few case studies are performed to demonstrate the ability of the model in handling complex scenarios of eutectic growth such as width selection, lamella division and presence of solutal buoyancy. It is observed that solutal buoyancy gives rise to flow cells ahead of the eutectic interface facilitating the transfer of solute between the two phases. Apart from forced and natural convection, another important factor affecting solidification is the presence of shrinkage. Currently, solidification shrinkage is mostly modelled using empirical relations and criteria functions. In the present work, a phenomenological model for shrinkage driven convection is developed by incorporating the mechanism of solidification shrinkage in an existing framework of enthalpy based macro-scale solidification model. The effect of shrinkage flow on the free surface deformation is accounted for by using the volume-of-fluid method. The results predicted by the model are found to be in excellent agreement with analytical solutions for one-dimensional solidification with unequal phase densities. A set of controlled experiments are designed and executed for validating the numerical model. The experiments involve in-situ X-ray imaging of casting of pure aluminium in a rectangular cavity. The numerical predictions for solidification rate, free surface movement and temperature profiles are compared with corresponding experimental results obtained from the in-situ X-ray images and thermocouple data. Subsequent case studies, performed using the model, show significant influence of applied heat flux and mould geometry on the formation of shrinkage cavities. The shrinkage flow model provides the foundation for development of a generalized model to accurately predict the formation and morphology of internal porosity. The validated macro-scale shrinkage model is extended to the microscopic scale to study the influence of shrinkage flow on the growth rate of dendrites. Results demonstrate that shrinkage driven convection towards the dendrite strongly influences the solutal and thermal distribution adjacent to the solidification interface and consequently decreases the growth rate of the dendrite. Additionally, an analytical model is developed to quantify the effect of shrinkage driven convection through the definition of an equivalent undercooling for shrinkage flow. The present models provide significant physical insight into various mechanisms governing the process of solidification. Moreover, due to their similar framework, the individual models have the potential to be an effective foundation for the development of a generalized multi-scale solidification model incorporating the presence of important phenomena such as shrinkage and convection.

Calpains, a highly conserved family of calcium-dependent cysteine proteases, are divided in two groups; classical and non-conventional calpains. Calpain-1 and calpain-2, the classical ones, are ubiquitously expressed and abundant in the CNS. Findings through different experimental approaches, predominantly pharmacological calpain inhibitors, proposed the necessity of the proteases for the modulation of various biological events particularly in the CNS, or a functional link between calpain and neurodegeneration. Significant functions associated with calpain activity are neuronal proliferation/differentiation, signal transduction, apoptosis, and synaptic plasticity; or neuronal death in Alzheimer’s disease, Huntington’s disease, Parkinson’s disease, and ischemic stroke. However, due to limited insights of the approaches taken, such as non-specificity of the inhibitors, the exact roles of calpains in the CNS and the key mechanisms underlying them remain controversial. Calpain-1/calpain-2 germline knock-out are embryonic lethal at a very early stage hindering the use of these lines as mouse models for CNS studies. Accordingly, this thesis research introduced a unique brain-specific calpain-1/calpain-2 knock-out and explored the role of the proteases in brain development/function and in neuronal death. The first set of analyses examined how the elimination of calpain-1/calpain-2 activities in mouse brain impacts CNS development in general and synaptic plasticity in CA1 neurons of hippocampus. CNS-specific elimination of CAPNS1, the common small subunit, abolished calpain-1/calpain-2 activities in mouse brain. In contrast to Calpain-1/calpain-2 germ line knock-outs, the brain-specific knock-outs are viable and the general development of mouse brain is normal. However, morphology of dendrites in pyramidal neurons of the hippocampal CA1 region showed significantly decreased dendritic branching complexity and spine density. Consistent with dendrite morphological abnormalities, electrophysiological analyses revealed a significant decrease in field excitatory postsynaptic potentials, long term potentiation, and learning and memory in the hippocampal CA1 neurons of the mutants. In the second part of this research we investigated the direct role of the calpains in neuronal death and their potential downstream targets in in vitro models of PD and ischemic stroke. Our findings indicated that ablation of calpains activity improves survival of different types of neurons against mitochondrial toxin 1-methyl-4-phenylpyridinium (MPP+), glutamate, and hypoxia. Importantly, we demonstrated an increase in p35-cleavage to p25, a cyclin dependent kinase 5 (Cdk5) activator, and that restoration of p25 significantly suppresses the neuronal survival associated with calpain deficiency. Taken together, this work unequivocally establishes two central roles of calpain-1/calpain-2 in CNS function in plasticity and neuronal death.

After dendrite transection, two primary injury current pathways may acount for cell death: (1) the lesion current at the site of injury and (2) the voltage sensitive calcium channels along the dendrite. Lesions were made with a laser microbeam in mouse spinal monolayer cell cultures. Polylysine was tried as a positively charged "molecular bandage" to block the lesion current. The calcium channel blockers, verapamil and nifedipine, were used to reduce the calcium channel current. Control toxicity curves were obtained for all three compounds. The results show that neither verapamil, nifedipine, nor polylysine (MW: 3,300) protect nerve cells after dendrite amputation 100 ptm from the soma. The data also indicate that these compounds do not slow the process of cell death after such physical trauma.

Här undersöks en strategi som behandlar dendrittillväxt på en solid litiumanod i ett litiumbatteri. Med hjälp av täthetfunktionalsteori adsorberades fyra flytande kristaller på litiumytan vilket ledde till en gränsskiktsstabilisering. Denna stabilisering har i en tidigare rapport länkats till dendrittillväxt i en fasfältsmodell. Fasfältsmodellen replikerades ej i denna rapport utan det ses som ett eventuellt nästa steg. Molekylerna interagerade starkt med ytan och de beräknade adsorptionsenergierna hade stor inverkan på litiumytans gränsskiktsenergi. De flytande kristallernas fas simulerades också, vilken hade en beräknad kohesivenergi i samma storleksordning som flytande vatten. Denna energi var lägre än adsorptionsenergierna, vilket tyder på att det finns en drivkraft för molekylerna att interagera med ytan. Vidare så undersöktes redoxstabiliteten hos molekylerna, där det visade sig att två av molekylerna hade LUMO-energier under Ferminivån hos litium. Dessa molekyler är således inte stabila nära litiumytan, utan kommer eventuellt ta del i elektrokemiska reaktioner. Slutligen så undersöktes diffusionsbarriären hos adsorberade litiumatomer. Här jämfördes barriären mellan fall då molekyler var adsorberade och inte, och det visade sig att med adsorberade molekyler så är diffusionsbarriären högre. / A strategy to suppress the growth of dendrites on solid state lithium anodes was investigated. Using density functional theory, four liquid crystal molecules were adsorbed on a solid lithium surface leading to an interfacial stabilization. This stabilization has earlier been used as a descriptor in a phase-field model which investigated dendrite suppression. The replication of this phase-field model was out of the scope of this thesis and left as future work. The LC molecules interacted strongly with the surface, and the calculated adsorption energies had an considerable impact on the interfacial energies of the lithium surface. A liquid crystal phase was also simulated, with a cohesive energy of the same magnitude as liquid water. This energy was lower than the adsorption energies, indicating that there is a driving force for the LC molcules to adsorb to the surface. Furthermore, the redox stability of the molecules in the proximity of the lithium surface was investigated, where two of them had LUMO energies below the Fermi level of lithium. Those two molecules were thus not considered sufficiently stable to not take part in any electrochemical reactions with solid lithium. Finally, the surface diffusion barrier of adsorbed lithium atoms was investigated. The barrier with and without the liquid crystals adsorbed to the surface was compared, which showed that the diffusion barrier was even higher with the molecules adsorbed.

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This study has two parts. In the first part we develop a computational approach to the solution of an inverse modelling problem concerning the material properties of electrolytes used in Lithium-ion batteries. The dependence of the diffusion coefficient and the transference number on the concentration of Lithium ions is reconstructed based on the concentration data obtained from an in-situ NMR imaging experiment. This experiment is modelled by a system of 1D time-dependent Partial Differential Equations (PDE) describing the evolution of the concentration of Lithium ions with prescribed initial concentration and fluxes at the boundary. The material properties that appear in this model are reconstructed by solving a variational optimization problem in which the least-square error between the experimental and simulated concentration values is minimized. The uncertainty of the reconstruction is characterized by assuming that the material properties are random variables and their probability distribution estimated using a novel combination of Monte-Carlo approach and Bayesian statistics. In the second part of this study, we carefully analyze a number of secondary effects such as ion pairing and dendrite growth that may influence the estimation of the material properties and develop mathematical models to include these effects. We then use reconstructions of material properties based on inverse modelling along with their uncertainty estimates as a framework to validate or invalidate the models. The significance of certain secondary effects is assessed based on the influence they have on the reconstructed material properties. / Thesis / Doctor of Philosophy (PhD)

京都大学 / 新制・課程博士 / 博士(エネルギー科学) / 甲第24713号 / エネ博第456号 / 新制||エネ||85(附属図書館) / 京都大学大学院エネルギー科学研究科エネルギー基礎科学専攻 / (主査)教授 野平 俊之, 教授 萩原 理加, 教授 佐川 尚 / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DFAM