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Design, Synthesis, and Biological Activity of Rhodium Metalloinsertors
Get PDFDeficiencies in the mismatch repair (MMR) pathway are associated with several types of cancers, as well as resistance to commonly used chemotherapeutics. Rhodium metalloinsertors have been found to bind DNA mismatches with high affinity and specificity in vitro, and also exhibit cell-selective cytotoxicity, targeting MMR-deficient cells over MMR-proficient cells.
Here we examine the biological fate of rhodium metalloinsertors bearing dipyridylamine ancillary ligands. These complexes are shown to exhibit accelerated cellular uptake which permits the observation of various cellular responses, including disruption of the cell cycle and induction of necrosis, which occur preferentially in the MMR-deficient cell line. These cellular responses provide insight into the mechanisms underlying the selective activity of this novel class of targeted anti-cancer agents.
In addition, ten distinct metalloinsertors with varying lipophilicities are synthesized and their mismatch binding affinities and biological activities studied. While they are found to have similar binding affinities, their cell-selective antiproliferative and cytotoxic activities vary significantly. Inductively coupled plasma mass spectrometry (ICP-MS) experiments show that all of these metalloinsertors localize in the nucleus at sufficient concentrations for binding to DNA mismatches. Furthermore, metalloinsertors with high rhodium localization in the mitochondria show toxicity that is not selective for MMR-deficient cells. This work supports the notion that specific targeting of the metalloinsertors to nuclear DNA gives rise to their cytotoxic and antiproliferative activities that are selective for cells deficient in MMR.
To explore further the basis of the unique selectivity of the metlloinsertors in targeting MMR-deficient cells, experiments were conducted using engineered NCI-H23 lung adenocarcinoma cells that contain a doxycycline-inducible shRNA which suppresses the expression of the MMR gene MLH1. Here we use this new cell line to further validate rhodium metalloinsertors as compounds capable of differentially inhibiting the proliferation of MMR-deficient cancer cells over isogenic MMR-proficient cells. General DNA damaging agents, such as cisplatin and etoposide, in contrast, are less effective in the induced cell line defective in MMR.
Finally, we describe a new subclass of metalloinsertors with enhanced potency and selectivity, in which the complexes show Rh-O coordination. In particular, it has been found that both Δ and Λ enantiomers of [Rh(chrysi)(phen)(DPE)]2+ bind to DNA with similar affinities, suggesting a possible different binding conformation than previous metalloinsertors. Remarkably, all members of this new family of compounds have significantly increased potency in a range of cellular assays; indeed, all are more potent than the FDA-approved anticancer drugs cisplatin and MNNG. Moreover, these activities are coupled with high levels of selectivity for MMR-deficient cells.</p
A Retrofitting Framework for Pre-Northridge Steel Moment-Frame Buildings
Get PDFIn the 1994 Mw 6.7 Northridge and 1995 Mw 6.9 Kobe earthquakes,
steel moment-frame buildings were exposed to an unexpected flaw. The commonly utilized
welded unreinforced flange, bolted web connections
were observed to experience brittle fractures in a number of buildings, even at
low levels of seismic demand. A majority of these buildings have not been retrofitted
and may be susceptible to structural collapse in a major earthquake.
This dissertation presents a case study of retrofitting a 20-story pre-Northridge steel
moment-frame building. Twelve retrofit schemes are developed that present some
range in degree of intervention. Three retrofitting techniques are considered: upgrading
the brittle beam-to-column moment resisting connections, and implementing either conventional
or buckling-restrained brace elements within the existing moment-frame bays.
The retrofit schemes include some that are designed to the
basic safety objective of ASCE-41 Seismic Rehabilitation of Existing Buildings.
Detailed finite element models of the base line building and the retrofit schemes
are constructed. The models include considerations of brittle
beam-to-column moment resisting connection fractures, column splice fractures,
column baseplate fractures, accidental contributions from ``simple'' non-moment resisting
beam-to-column connections to the lateral force-resisting system, and composite
actions of beams with the overlying floor system.
In addition, foundation interaction is included through nonlinear translational springs
underneath basement columns.
To investigate the effectiveness of the retrofit schemes, the building models are
analyzed under ground motions from three large magnitude simulated earthquakes that
cause intense shaking in the greater Los Angeles metropolitan area, and under
recorded ground motions from actual earthquakes.
It is found that retrofit schemes that convert the existing moment-frames into braced-frames
by implementing either conventional or buckling-restrained braces are effective in limiting
structural damage and mitigating structural collapse. In the three simulated earthquakes,
a 20% chance of simulated collapse is realized at PGV of around 0.6 m/s for the base line model,
but at PGV of around 1.8 m/s for some of the retrofit schemes. However, conventional braces are observed
to deteriorate rapidly. Hence, if a braced-frame that employs conventional braces survives
a large earthquake, it is questionable how much service the braces provide in potential
aftershocks.</p
Efficient Methods for Stochastic Optimal Control
Get PDFThe Hamilton Jacobi Bellman (HJB) equation is central to stochastic optimal control (SOC) theory, yielding the optimal solution to general problems specified by known dynamics and a specified cost functional. Given the assumption of quadratic cost on the control input, it is well known that the HJB reduces to a particular partial differential equation (PDE). While powerful, this reduction is not commonly used as the PDE is of second order, is nonlinear, and examples exist where the problem may not have a solution in a classical sense. Furthermore, each state of the system appears as another dimension of the PDE, giving rise to the curse of dimensionality. Since the number of degrees of freedom required to solve the optimal control problem grows exponentially with dimension, the problem becomes intractable for systems with all but modest dimension.
In the last decade researchers have found that under certain, fairly non-restrictive structural assumptions, the HJB may be transformed into a linear PDE, with an interesting analogue in the discretized domain of Markov Decision Processes (MDP). The work presented in this thesis uses the linearity of this particular form of the HJB PDE to push the computational boundaries of stochastic optimal control.
This is done by crafting together previously disjoint lines of research in computation. The first of these is the use of Sum of Squares (SOS) techniques for synthesis of control policies. A candidate polynomial with variable coefficients is proposed as the solution to the stochastic optimal control problem. An SOS relaxation is then taken to the partial differential constraints, leading to a hierarchy of semidefinite relaxations with improving sub-optimality gap. The resulting approximate solutions are shown to be guaranteed over- and under-approximations for the optimal value function. It is shown that these results extend to arbitrary parabolic and elliptic PDEs, yielding a novel method for Uncertainty Quantification (UQ) of systems governed by partial differential constraints. Domain decomposition techniques are also made available, allowing for such problems to be solved via parallelization and low-order polynomials.
The optimization-based SOS technique is then contrasted with the Separated Representation (SR) approach from the applied mathematics community. The technique allows for systems of equations to be solved through a low-rank decomposition that results in algorithms that scale linearly with dimensionality. Its application in stochastic optimal control allows for previously uncomputable problems to be solved quickly, scaling to such complex systems as the Quadcopter and VTOL aircraft. This technique may be combined with the SOS approach, yielding not only a numerical technique, but also an analytical one that allows for entirely new classes of systems to be studied and for stability properties to be guaranteed.
The analysis of the linear HJB is completed by the study of its implications in application. It is shown that the HJB and a popular technique in robotics, the use of navigation functions, sit on opposite ends of a spectrum of optimization problems, upon which tradeoffs may be made in problem complexity. Analytical solutions to the HJB in these settings are available in simplified domains, yielding guidance towards optimality for approximation schemes. Finally, the use of HJB equations in temporal multi-task planning problems is investigated. It is demonstrated that such problems are reducible to a sequence of SOC problems linked via boundary conditions. The linearity of the PDE allows us to pre-compute control policy primitives and then compose them, at essentially zero cost, to satisfy a complex temporal logic specification.</p
Velocity Resolved - Scalar Modeled Simulations of High Schmidt Number Turbulent Transport
Get PDFThe objective of this thesis is to develop a framework to conduct velocity resolved - scalar modeled (VR-SM) simulations, which will enable accurate simulations at higher Reynolds and Schmidt (Sc) numbers than are currently feasible. The framework established will serve as a first step to enable future simulation studies for practical applications. To achieve this goal, in-depth analyses of the physical, numerical, and modeling aspects related to Sc>>1 are presented, specifically when modeling in the viscous-convective subrange. Transport characteristics are scrutinized by examining scalar-velocity Fourier mode interactions in Direct Numerical Simulation (DNS) datasets and suggest that scalar modes in the viscous-convective subrange do not directly affect large-scale transport for high Sc. Further observations confirm that discretization errors inherent in numerical schemes can be sufficiently large to wipe out any meaningful contribution from subfilter models. This provides strong incentive to develop more effective numerical schemes to support high Sc simulations. To lower numerical dissipation while maintaining physically and mathematically appropriate scalar bounds during the convection step, a novel method of enforcing bounds is formulated, specifically for use with cubic Hermite polynomials. Boundedness of the scalar being transported is effected by applying derivative limiting techniques, and physically plausible single sub-cell extrema are allowed to exist to help minimize numerical dissipation. The proposed bounding algorithm results in significant performance gain in DNS of turbulent mixing layers and of homogeneous isotropic turbulence. Next, the combined physical/mathematical behavior of the subfilter scalar-flux vector is analyzed in homogeneous isotropic turbulence, by examining vector orientation in the strain-rate eigenframe. The results indicate no discernible dependence on the modeled scalar field, and lead to the identification of the tensor-diffusivity model as a good representation of the subfilter flux. Velocity resolved - scalar modeled simulations of homogeneous isotropic turbulence are conducted to confirm the behavior theorized in these a priori analyses, and suggest that the tensor-diffusivity model is ideal for use in the viscous-convective subrange. Simulations of a turbulent mixing layer are also discussed, with the partial objective of analyzing Schmidt number dependence of a variety of scalar statistics. Large-scale statistics are confirmed to be relatively independent of the Schmidt number for Sc>>1, which is explained by the dominance of subfilter dissipation over resolved molecular dissipation in the simulations. Overall, the VR-SM framework presented is quite effective in predicting large-scale transport characteristics of high Schmidt number scalars, however, it is determined that prediction of subfilter quantities would entail additional modeling intended specifically for this purpose. The VR-SM simulations presented in this thesis provide us with the opportunity to overlap with experimental studies, while at the same time creating an assortment of baseline datasets for future validation of LES models, thereby satisfying the objectives outlined for this work
Multi-Model Inference Ranking and Applications to Physics at the Large Hadron Collider
Get PDFIn the measurement of the Higgs Boson decaying into two photons the parametrization of an appropriate background model is essential for fitting the Higgs signal mass peak over a continuous background. This diphoton background modeling is crucial in the statistical process of calculating exclusion limits and the significance of observations in comparison to a background-only hypothesis. It is therefore ideal to obtain knowledge of the physical shape for the background mass distribution as the use of an improper function can lead to biases in the observed limits. Using an Information-Theoretic (I-T) approach for valid inference we apply Akaike Information Criterion (AIC) as a measure of the separation for a fitting model from the data. We then implement a multi-model inference ranking method to build a fit-model that closest represents the Standard Model background in 2013 diphoton data recorded by the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC). Potential applications and extensions of this model-selection technique are discussed with reference to CMS detector performance measurements as well as in potential physics analyses at future detectors
Role of Conformational Changes in G Protein-Coupled Receptor Activation
Get PDFTransmembrane signal transduction is achieved by activation of G protein-coupled receptors (GPCRs) like the human cannabinoid type 1 (CB1) receptor, the human cannabinoid type 2 (CB2) receptor, and the human mu-opioid receptor. These receptors exist in the membrane in an ensemble of conformations each of which might bind to different signaling molecules and cause different physiological effects. Understanding the structural basis of their activation will eventually help us in designing drugs that target these receptors with potentially minimal undesirable side effects. CB1 is of particular interest because it is located in the central nervous system and modulates hunger, making it an attractive anti-obesity drug target. In this receptor, mutating a single residue, threonine 210, to isoleucine in the third transmembrane (TM3) domain makes it far more active than the wild-type (WT) receptor, whereas mutating it to alanine makes it fully inactive. CB1 is difficult to model because it has a small sequence identity with the receptors that have been crystallized. We used the first principles-based GEnSeMBLE method to predict 3D structures of these receptors representing the fully inactive to highly constitutively active states. With this software, we quickly found a set of low energy receptor conformations by sampling trillions of helix orientations. Differences in the intracellular surface explain experimental differences in activation for the CB1 receptor and its mutants. These predictions were validated by designing double mutants that were expected to switch the inactive T210A to WT levels of activation and expected to switch the very active L207A to T210A levels of activation. These predictions were first verified computationally then experimentally with GTPgammaS assays. The accuracy of our predictions indicate that the GEnSeMBLE method is a useful procedure for predicting GPCR structures at various activation states. Known inverse agonists were docked to these predicted CB1 receptor structures, and the resulting complexes were inserted into a solvated lipid bilayer for 50 ns of NPT molecular dynamics with NAMD software. The inverse agonist preferentially binds to a pre-activated CB1 state, but during MD, traits of the inactive structure start to form suggesting that the ligand induces conformational changes
Phase Transformations and Entropy of Non-Equilibrium Materials
Get PDFTime-resolved vibrational spectra through the glass transition in the bulk metallic glass CuZr were acquired with inelastic neutron scattering. Vibrational density of states (DOS) in ranges as small as 4K were extracted from continuous heating through the glass transition. For each temperature interval, the vibrational entropy is calculated from the DOS. This provides a detailed characterization of how the vibrational entropy contributes to the large jump in heat capacity that characterizes the glass transition in amorphous materials. This change in heat capacity has been attributed to combinations of configurational and vibrational entropy. However, the role of vibrational entropy in this transition has never been demonstrated for all vibrational modes in an amorphous material. This work provides the first experimental measurement of the change in vibrational entropy through the glass transition. We found the unique contributions of both the vibrational and configurational entropy and find that the change in vibrational entropy can be bound at less than 0.01 kB per atom. By elimination, this means that the configurational entropy is dominant, putting to rest a controversial debate over the role of entropy through the glass transition.
The changes in vibrational entropy during the early stages of chemical unmixing was studied in a nanocrystalline fcc solid solution of 6%-Fe in Cu. Material prepared by high-energy ball milling was annealed at temperatures from 200 to 360°C to induce chemical unmixing. Nuclear resonant inelastic x-ray scattering spectra yield the phonon partial density of states (pDOS) of 57Fe. The pDOS of the as-prepared material is that of an fcc crystal. In the earliest stages of unmixing, the features of the pDOS broaden, with only small changes in average phonon frequencies, until the bcc phase begins to form. The chemical state of the material was characterized by three-dimensional atom probe microscopy, Mӧssbauer spectrometry, and x-ray powder diffractometry. The unmixing was heterogeneous, with iron atoms forming iron-rich zones that thicken with further annealing. The vibrational entropy calculated from the pDOS underwent little change during the early stage of unmixing, but decreased rapidly when the bcc phase formed in the material.
Electrochemical cycling of lithium ion batteries causes fundamental structural changes and the formation of new phases in cathode materials. The reversibility of these transitions is often critical to the viability of cathode materials for long-term performance. The cycle lives for cathodes of nanocrystalline iron trifluoride (FeF3) were measured in rechargeable lithium batteries at different depths of discharge. When the discharge was limited to less than one Li+ ion per FeF3, both the cycle life and energy efficiency were considerably greater than when converting FeF3 into Fe and LiF in deep discharge. An in situ X-ray diffractometry (XRD) study of the FeF3 cathode during its initial discharge to LiFeF3 showed a continuous change of the FeF3 diffraction pattern, indicating Li+ insertion into the rhombohedral FeF3 causing distortion of its lattice parameters. Electrochemical cycling is most reversible when this mechanism occurs in the absence of other changes in the crystal structure. </p
Biochemical Studies of Postsynaptic Density Signaling Proteins With a Focus on synGAP and PDZ Domains
Get PDFMemory storage in the brain involves adjustment of the strength of existing synapses and formation of new neural networks. A key process underlying memory formation is synaptic plasticity, the ability of excitatory synapses to strengthen or weaken their connections in response to patterns of activity between their connected neurons. Synaptic plasticity is governed by the precise pattern of Ca²⁺ influx through postsynaptic N-methyl-D-aspartate-type glutamate receptors (NMDARs), which can lead to the activation of the small GTPases Ras and Rap. Differential activation of Ras and Rap acts to modulate synaptic strength by promoting the insertion or removal of 2-amino-3-(3-hydroxy-5-methyl-isoxazol-4-yl)propanoic acid receptors (AMPARs) from the synapse. Synaptic GTPase activating protein (synGAP) regulates AMPAR levels by catalyzing the inactivation of GTP-bound (active) Ras or Rap. synGAP is positioned in close proximity to the cytoplasmic tail regions of the NMDAR through its association with the PDZ domains of PSD-95. SynGAP’s activity is regulated by the prominent postsynaptic protein kinase, Ca²⁺/calmodulin-dependent protein kinase II (CaMKII) and cyclin-dependent kinase 5 (CDK5), a known binding partner of CaMKII. Modulation of synGAP’s activity by phosphorylation may alter the ratio of active Ras to Rap in spines, thus pushing the spine towards the insertion or removal of AMPARs, subsequently strengthening or weakening the synapse. To date, all biochemical studies of the regulation of synGAP activity by protein kinases have utilized impure preparations of membrane bound synGAP. Here we have clarified the effects of phosphorylation of synGAP on its Ras and Rap GAP activities by preparing and utilizing purified, soluble recombinant synGAP, Ras, Rap, CaMKII, CDK5, PLK2, and CaM. Using mass spectrometry, we have confirmed the presence of previously identified CaMKII and CDK5 sites in synGAP, and have identified novel sites of phosphorylation by CaMKII, CDK5, and PLK2. We have shown that the net effect of phosphorylation of synGAP by CaMKII, CDK5, and PLK2 is an increase in its GAP activity toward HRas and Rap1. In contrast, there is no effect on its GAP activity toward Rap2. Additionally, by assaying the GAP activity of phosphomimetic synGAP mutants, we have been able to hypothesize the effects of CDK5 phosphorylation at specific sites in synGAP. In the course of this work, we also found, unexpectedly, that synGAP is itself a Ca²⁺/CaM binding protein. While Ca²⁺/CaM binding does not directly affect synGAP activity, it causes a conformational change in synGAP that increases the rate of its phosphorylation and exposes additional phosphorylation sites that are inaccessible in the absence of Ca²⁺/CaM.
The postsynaptic density (PSD) is an electron-dense region in excitatory postsynaptic neurons that contains a high concentration of glutamate receptors, cytoskeletal proteins, and associated signaling enzymes. Within the PSD, three major classes of scaffolding molecules function to organize signaling enzymes and glutamate receptors. PDZ domains present in the Shank and PSD-95 scaffolds families serve to physically link AMPARs and NMDARs to signaling molecules in the PSD. Because of the specificity and high affinity of PDZ domains for their ligands, I reasoned that these interacting pairs could provide the core components of an affinity chromatography system, including affinity resins, affinity tags, and elution agents. I show that affinity columns containing the PDZ domains of PSD-95 can be used to purify active PDZ domain-binding proteins to very high purity in a single step. Five heterologously expressed neuronal proteins containing endogenous PDZ domain ligands (NMDAR GluN2B subunit Tail, synGAP, neuronal nitric oxide synthase PDZ domain, cysteine rich interactor of PDZ three and cypin) were purified using PDZ domain resin, with synthetic peptides having the sequences of cognate PDZ domain ligands used as elution agents. I also show that conjugation of PDZ domain-related affinity tags to Proteins Of Interest (POIs) that do not contain endogenous PDZ domains or ligands does not alter protein activity and enables purification of the POIs on PDZ domain-related affinity resins.</p
Development of Semicrystalline Morphology of Poly(L-lactic Acid) during Processing of a Vascular Scaffold
Get PDFNew and promising treatments for coronary heart disease are enabled by vascular scaffolds made of poly(L-lactic acid) (PLLA), as demonstrated by Abbott Vascular’s bioresorbable vascular scaffold. PLLA is a semicrystalline polymer whose degree of crystallinity and crystalline microstructure depend on the thermal and deformation history during processing. In turn, the semicrystalline morphology determines scaffold strength and biodegradation time. However, spatially-resolved information about the resulting material structure (crystallinity and crystal orientation) is needed to interpret in vivo observations.
The first manufacturing step of the scaffold is tube expansion in a process similar to injection blow molding. Spatial uniformity of the tube microstructure is essential for the consistent production and performance of the final scaffold. For implantation into the artery, solid-state deformation below the glass transition temperature is imposed on a laser-cut subassembly to crimp it into a small diameter. Regions of localized strain during crimping are implicated in deployment behavior.
To examine the semicrystalline microstructure development of the scaffold, we employed complementary techniques of scanning electron and polarized light microscopy, wide-angle X-ray scattering, and X-ray microdiffraction. These techniques enabled us to assess the microstructure at the micro and nano length scale. The results show that the expanded tube is very uniform in the azimuthal and axial directions and that radial variations are more pronounced. The crimping step dramatically changes the microstructure of the subassembly by imposing extreme elongation and compression. Spatial information on the degree and direction of chain orientation from X-ray microdiffraction data gives insight into the mechanism by which the PLLA dissipates the stresses during crimping, without fracture. Finally, analysis of the microstructure after deployment shows that it is inherited from the crimping step and contributes to the scaffold’s successful implantation in vivo.</p
Catechol 2,3-Dioxygenase-Assisted Cleavage of Aromatics by "Anaerobic" Termite Gut Spirochetes and Genomic Evidence of a Complete Meta-Pathway
Get PDFThe termite hindgut microbial ecosystem functions like a miniature lignocellulose-metabolizing natural bioreactor, has significant implications to nutrient cycling in the terrestrial environment, and represents an array of microbial metabolic diversity. Deciphering the intricacies of this microbial community to obtain as complete a picture as possible of how it functions as a whole, requires a combination of various traditional and cutting-edge bioinformatic, molecular, physiological, and culturing approaches. Isolates from this ecosystem, including Treponema primitia str. ZAS-1 and ZAS-2 as well as T. azotonutricium str. ZAS-9, have been significant resources for better understanding the termite system. While not all functions predicted by the genomes of these three isolates are demonstrated in vitro, these isolates do have the capacity for several metabolisms unique to spirochetes and critical to the termite system’s reliance upon lignocellulose. In this thesis, work culturing, enriching for, and isolating diverse microorganisms from the termite hindgut is discussed. Additionally, strategies of members of the termite hindgut microbial community to defend against O2-stress and to generate acetate, the “biofuel” of the termite system, are proposed. In particular, catechol 2,3-dioxygenase and other meta-cleavage catabolic pathway genes are described in the “anaerobic” termite hindgut spirochetes T. primitia str. ZAS-1 and ZAS-2, and the first evidence for aromatic ring cleavage in the phylum (division) Spirochetes is also presented. These results suggest that the potential for O2-dependent, yet nonrespiratory, metabolisms of plant-derived aromatics should be re-evaluated in termite hindgut communities. Potential future work is also illustrated