2,517 research outputs found

    TOWARDS THE RATIONAL DESIGN AND APPLICATION OF POLYMERS FOR GENE THERAPY: INTERNALIZATION AND INTRACELLULAR FATE

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    Gene therapy is an approach for the treatment of acquired cancers, infectious disease, degenerative disease, and inherited genetic indications. Developments in the fields of immunotherapies and CRISPR/Cas9 genome editing are revitalizing the efforts to move gene therapy to the forefront of modern medicine. However, slow progress and poor clinical outcomes have plagued the field due to regulatory and safety concerns associated with the flagship delivery vector, the recombinant virus. Immunogenicity and poor transduction in certain cell types severely limits the utility of viruses as a delivery agent of nucleic acids. As a result, significant efforts are being made to develop non-viral delivery systems that perform mechanistically similarly to viral delivery but lack immunogenic factors. Though safer, existing agents lack the efficacy inherent in the natural design of viral vectors. Clinical relevance of non-viral vectors will therefore depend on the ability to engineer optimized systems for cellular delivery in physiological environments. Progress in non-viral vector design for gene delivery requires a deep understanding of the various barriers associated with nucleic acid delivery, including cell surface interaction, internalization, endosomal escape, cytosolic transport, nuclear localization, unpackaging, etc. Further, it requires a knowledge of vector design properties (surface chemistry, charge, size, shape, etc.) and how these physical parameters affect interactions with the cellular environment. Of these interactions, charge is shown to govern how particles are internalized and subsequently processed, thereby affecting the intracellular fate and efficacy of delivery. Charge also affects the in-serum stability where negative zeta potential improves stability and circulation time. Therefore, it is important to understand the effects of polyplex charge and other parameters on the internalization and intracellular fate of polyplexes for gene therapy. In chapter 2, studies are performed to delineate the effects of polyplex charge on the cellular internalization and intracellular processing of polymer-mediated gene delivery. Charge is shown to affect the endocytic pathway involved in internalization, and the caveolin-dependent and macropinocytosis pathways lead to higher gene delivery efficacy, likely due to avoidance of acidified compartments such as late endosomes and lysosomes. In chapters 3-4, novel nanoparticles carrying DNA, RNA, and antioxidants are assessed for therapeutic effect with an emphasis on studying the internalization mechanisms and resulting effect on efficacy. Novel RNA delivery agents are shown to benefit from EGFR-targeting aptamer and nanoceria/PEI hybrids are demonstrated to provide simultaneous antioxidant and gene therapy. Finally, chapter 5 demonstrates the use of silencing RNA and CRISPR/Cas9 genome editing to study the prevalence of gene targets in vivo. The overall goal of this work is to contribute to the design and application of novel nanoparticles for gene delivery and offer insight into the engineering of novel polyplexes. It remains clear that route of internalization is key to successful gene delivery, and designing polyplexes to enter through non-acidified endocytic pathways is highly beneficial to transgene expression. This can be achieved through incorporation of surface chemistries that trigger internalization through targeted pathways and is the source of further work in the lab

    Search for Higgs Boson Production Beyond the Standard Model Using the Razor Kinematic Variables in pp Collisions at √s=8 TeV and Optimization of Higgs Boson Identification Using a Quantum Annealer

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    In the first part of this thesis we search for beyond the Standard Model physics through the search for anomalous production of the Higgs boson using the razor kinematic variables. We search for anomalous Higgs boson production using proton-proton collisions at center of mass energy √s=8 TeV collected by the Compact Muon Solenoid experiment at the Large Hadron Collider corresponding to an integrated luminosity of 19.8 fb-1. In the second part we present a novel method for using a quantum annealer to train a classifier to recognize events containing a Higgs boson decaying to two photons. We train that classifier using simulated proton-proton collisions at √s=8 TeV producing either a Standard Model Higgs boson decaying to two photons or a non-resonant Standard Model process that produces a two photon final state. The production mechanisms of the Higgs boson are precisely predicted by the Standard Model based on its association with the mechanism of electroweak symmetry breaking. We measure the yield of Higgs bosons decaying to two photons in kinematic regions predicted to have very little contribution from a Standard Model Higgs boson and search for an excess of events, which would be evidence of either non-standard production or non-standard properties of the Higgs boson. We divide the events into disjoint categories based on kinematic properties and the presence of additional b-quarks produced in the collisions. In each of these disjoint categories, we use the razor kinematic variables to characterize events with topological configurations incompatible with typical configurations found from standard model production of the Higgs boson. We observe an excess of events with di-photon invariant mass compatible with the Higgs boson mass and localized in a small region of the razor plane. We observe 5 events with a predicted background of 0.54 &#177; 0.28, which observation has a p-value of 10-3 and a local significance of 3.35&#963;. This background prediction comes from 0.48 predicted non-resonant background events and 0.07 predicted SM higgs boson events. We proceed to investigate the properties of this excess, finding that it provides a very compelling peak in the di-photon invariant mass distribution and is physically separated in the razor plane from predicted background. Using another method of measuring the background and significance of the excess, we find a 2.5&#963; deviation from the Standard Model hypothesis over a broader range of the razor plane. In the second part of the thesis we transform the problem of training a classifier to distinguish events with a Higgs boson decaying to two photons from events with other sources of photon pairs into the Hamiltonian of a spin system, the ground state of which is the best classifier. We then use a quantum annealer to find the ground state of this Hamiltonian and train the classifier. We find that we are able to do this successfully in less than 400 annealing runs for a problem of median difficulty at the largest problem size considered. The networks trained in this manner exhibit good classification performance, competitive with the more complicated machine learning techniques, and are highly resistant to overtraining. We also find that the nature of the training gives access to additional solutions that can be used to improve the classification performance by up to 1.2% in some regions.</p

    Quantum adiabatic machine learning by zooming into a region of the energy surface

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    Recent work has shown that quantum annealing for machine learning, referred to as QAML, can perform comparably to state-of-the-art machine learning methods with a specific application to Higgs boson classification. We propose QAML-Z, an algorithm that iteratively zooms in on a region of the energy surface by mapping the problem to a continuous space and sequentially applying quantum annealing to an augmented set of weak classifiers. Results on a programmable quantum annealer show that QAML-Z matches classical deep neural network performance at small training set sizes and reduces the performance margin between QAML and classical deep neural networks by almost 50% at large training set sizes, as measured by area under the receiver operating characteristic curve. The significant improvement of quantum annealing algorithms for machine learning and the use of a discrete quantum algorithm on a continuous optimization problem both opens a class of problems that can be solved by quantum annealers and suggests the approach in performance of near-term quantum machine learning towards classical benchmarks

    Optical response of electrons in a random potential

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    Using our recently developed Chebyshev expansion technique for finite-temperature dynamical correlation functions we numerically study the AC conductivity σ(ω)\sigma(\omega) of the Anderson model on large cubic clusters of up to 1003100^3 sites. Extending previous results we focus on the role of the boundary conditions and check the consistency of the DC limit, ω0\omega\to 0, by comparing with direct conductance calculations based on a Greens function approach in a Landauer B\"uttiker type setup.Comment: 2 pages, 3 figs, submitted to SCES'0

    The relationship between very high gravity fermentations and oxidative stress in the lager yeast Saccharomyces pastorianus

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    Very High Gravity fermentations are an increasingly attractive proposition within the brewing industry as a means of energy saving and optimising process efficiency. However, the use of very high gravity (>20°P) wort is associated with a range of biological stress factors. Ethanoic and osmotic stresses have been widely analysed along with oxidative stress in relation to propagation and early stage fermentation. The aim of this research was to investigate the impact of wort gravity on oxidative stress, and understand how this affects the plasma membrane at VHG. Finally the effect altered ergosterol content was analysed. The characteristics of Saccharomyces pastorianus strains were assessed for their ability to withstand the increased pressures of VHG (22°P) fermentations. VHG fermentations showed increase ethanol production at the expense of fermentation length, and increased ethanol production during VHG fermentations was offset by an increase in fermentation length. All fermentations were observed to accumulate ROS and increased antioxidant levels, with levels being furtherelevated in the VHG environment. Further analysis of S. pastorianus strains indicated that the levels of oxidative stress observed in fermentation had a negative effect on membrane fluidity and increased damage of the plasma membrane was observed. Analysis of ergosterol enriched yeast indicated that although fermentation rate was increased, a trade off with alcohol and biomass production was observed. Furthermore in response to oxidative stress, ergosterol enriched yeast showed reduced tolerance, decreased membrane fluidity and increased membrane damage. This work will give further insight into the response of lager yeast to oxidative stress present during VHG fermentations

    Evidence for power-law frequency dependence of intrinsic dielectric response in the CaCu3_{3}Ti4_{4}O12_{12}

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    We investigated the dielectric response of CaCu3_3Ti4_4O12_{12} (CCTO) thin films grown epitaxially on LaAlO3_3 (001) substrates by Pulsed Laser Deposition (PLD). The dielectric response of the films was found to be strongly dominated by a power-law in frequency, typical of materials with localized hopping charge carriers, in contrast to the Debye-like response of the bulk material. The film conductivity decreases with annealing in oxygen, and it suggests that oxygen deficit is a cause of the relatively high film conductivity. With increase of the oxygen content, the room temperature frequency response of the CCTO thin films changes from the response indicating the presence of some relatively low conducting capacitive layers to purely power law, and then towards frequency independent response with a relative dielectric constant ϵ102\epsilon'\sim10^2. The film conductance and dielectric response decrease upon decrease of the temperature with dielectric response being dominated by the power law frequency dependence. Below \sim80 K, the dielectric response of the films is frequency independent with ϵ\epsilon' close to 10210^2. The results provide another piece of evidence for an extrinsic, Maxwell-Wagner type, origin of the colossal dielectric response of the bulk CCTO material, connected with electrical inhomogeneity of the bulk material.Comment: v4: RevTeX, two-column, 9 pages, 7 figures; title modified, minor content change in p.7, reference adde

    Pressure-Induced Insulating State in Ba1-xRExIrO3 (RE = Gd, Eu) Single Crystals

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    BaIrO3 is a novel insulator with coexistent weak ferromagnetism, charge and spin density wave. Dilute RE doping for Ba induces a metallic state, whereas application of modest pressure readily restores an insulating state characterized by a three-order-of-magnitude increase of resistivity. Since pressure generally increases orbital overlap and broadens energy bands, a pressure-induced insulating state is not commonplace. The profoundly dissimilar responses of the ground state to light doping and low hydrostatic pressures signal an unusual, delicate interplay between structural and electronic degrees of freedom in BaIrO3

    Quantum adiabatic machine learning by zooming into a region of the energy surface

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    Recent work has shown that quantum annealing for machine learning, referred to as QAML, can perform comparably to state-of-the-art machine learning methods with a specific application to Higgs boson classification. We propose QAML-Z, an algorithm that iteratively zooms in on a region of the energy surface by mapping the problem to a continuous space and sequentially applying quantum annealing to an augmented set of weak classifiers. Results on a programmable quantum annealer show that QAML-Z matches classical deep neural network performance at small training set sizes and reduces the performance margin between QAML and classical deep neural networks by almost 50% at large training set sizes, as measured by area under the receiver operating characteristic curve. The significant improvement of quantum annealing algorithms for machine learning and the use of a discrete quantum algorithm on a continuous optimization problem both opens a class of problems that can be solved by quantum annealers and suggests the approach in performance of near-term quantum machine learning towards classical benchmarks

    Effect of Crystal-Field Splitting and Inter-Band Hybridization on the Metal-Insulator Transitions of Strongly Correlated Systems

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    We investigate a quarter-filled two-band Hubbard model involving a crystal-field splitting, which lifts the orbital degeneracy as well as an inter-orbital hopping (inter-band hybridization). Both terms are relevant to the realistic description of correlated materials such as transition-metal oxides. The nature of the Mott metal-insulator transition is clarified and is found to depend on the magnitude of the crystal-field splitting. At large values of the splitting, a transition from a two-band to a one-band metal is first found as the on-site repulsion is increased and is followed by a Mott transition for the remaining band, which follows the single-band (Brinkman-Rice) scenario well documented previously within dynamical mean-field theory. At small values of the crystal-field splitting, a direct transition from a two-band metal to a Mott insulator with partial orbital polarization is found, which takes place simultaneously for both orbitals. This transition is characterized by a vanishing of the quasiparticle weight for the majority orbital but has a first-order character for the minority orbital. It is pointed out that finite-temperature effects may easily turn the metallic regime into a bad metal close to the orbital polarization transition in the metallic phase.Comment: 12 pages, 10 figures One figure added. Text revised according to PRB proof. Appear in PRB 7

    Site-specific inductive and inhibitory activities of MMP-2 and MMP-3 orchestrate mammary gland branching morphogenesis

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    During puberty, mouse mammary epithelial ducts invade the stromal mammary fat pad in a wave of branching morphogenesis to form a complex ductal tree. Using pharmacologic and genetic approaches, we find that mammary gland branching morphogenesis requires transient matrix metalloproteinase (MMP) activity for invasion and branch point selection. MMP-2, but not MMP-9, facilitates terminal end bud invasion by inhibiting epithelial cell apoptosis at the start of puberty. Unexpectedly, MMP-2 also represses precocious lateral branching during mid-puberty. In contrast, MMP-3 induces secondary and tertiary lateral branching of ducts during mid-puberty and early pregnancy. Nevertheless, the mammary gland is able to develop lactational competence in MMP mutant mice. Thus, specific MMPs refine the mammary branching pattern by distinct mechanisms during mammary gland branching morphogenesis
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