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Open Access Publications from the University of California

Scholarly Works (6 results)

  • Thesis
  • Peer Reviewed
UC Irvine Electronic Theses and Dissertations (2014)

This thesis research project is comprised of a written document and choreographic work. The choreographic work was presented in the Claire Trevor Theatre at the University of California, Irvine on May 6 and 7, 2014. The presentation consisted of a half-hour length contemporary ballet piece entitled "LUMINOSITY: the quality of being intellectually brilliant, enlightened, inspired" created with the intention to abstractly illustrate the journey of the mind as it transitions from a state of fluctuating, destructive chaos to quiet stillness and then from quiet stillness to brilliant, spiritual enlightenment.

The supporting research paper examines the purpose of the mindful use of the breath advocated in western Hatha-Yoga practices and in the Pilates Method developed by Joseph H. Pilates. Breath awareness, a fundamental principle to these and many other mind-body and somatic practices, is explored to further understand the consequence an observance of the breath has on unifying the mind, body, and spirit of an individual. A particular focus is placed on the yogic philosophy that addresses the power of the breath to still fluctuations in the mind, reawaken awareness of the present moment, and deepen spirituality through that process. The philosophy of dance as a spiritual expression and healing art is addressed through the perspective of American modern dance forerunners, Ruth St. Denis and Isadora Duncan. The concepts of interiority and internal awareness are investigated throughout the choreographic process by integrating breath and meditation exercises, somatic-based improvisation, discussion, and self-reflection into each rehearsal. The choreographic investigation and findings from that study are documented in this work.

    Cover page: Rediscovering Breath: A Tool to Expand Awareness and Spirituality in Dance
    • Article
    • Peer Reviewed
    UC Irvine Previously Published Works (2016)
    Advances in self-assembly over the past decade have demonstrated that nano- and microscale particles can be organized into a large diversity of ordered three-dimensional (3D) lattices. However, the ability to generate different desired lattice types from the same set of particles remains challenging. Here, we show that nanoparticles can be assembled into crystalline and open 3D frameworks by connecting them through designed DNA-based polyhedral frames. The geometrical shapes of the frames, combined with the DNA-assisted binding properties of their vertices, facilitate the well-defined topological connections between particles in accordance with frame geometry. With this strategy, different crystallographic lattices using the same particles can be assembled by introduction of the corresponding DNA polyhedral frames. This approach should facilitate the rational assembly of nanoscale lattices through the design of the unit cell.
      Cover page: Lattice engineering through nanoparticle–DNA frameworks
      • Article
      • Peer Reviewed
      UC Irvine Previously Published Works (2015)
      Three-dimensional mesoscale clusters that are formed from nanoparticles spatially arranged in pre-determined positions can be thought of as mesoscale analogues of molecules. These nanoparticle architectures could offer tailored properties due to collective effects, but developing a general platform for fabricating such clusters is a significant challenge. Here, we report a strategy for assembling three-dimensional nanoparticle clusters that uses a molecular frame designed with encoded vertices for particle placement. The frame is a DNA origami octahedron and can be used to fabricate clusters with various symmetries and particle compositions. Cryo-electron microscopy is used to uncover the structure of the DNA frame and to reveal that the nanoparticles are spatially coordinated in the prescribed manner. We show that the DNA frame and one set of nanoparticles can be used to create nanoclusters with different chiroptical activities. We also show that the octahedra can serve as programmable interparticle linkers, allowing one- and two-dimensional arrays to be assembled with designed particle arrangements.
        Cover page: Prescribed nanoparticle cluster architectures and low-dimensional arrays built using octahedral DNA origami frames
        • Article
        • Peer Reviewed
        LBL Publications (2021)
        Versatile methods to organize proteins in space are required to enable complex biomaterials, engineered biomolecular scaffolds, cell-free biology, and hybrid nanoscale systems. Here, we demonstrate how the tailored encapsulation of proteins in DNA-based voxels can be combined with programmable assembly that directs these voxels into biologically functional protein arrays with prescribed and ordered two-dimensional (2D) and three-dimensional (3D) organizations. We apply the presented concept to ferritin, an iron storage protein, and its iron-free analog, apoferritin, in order to form single-layers, double-layers, as well as several types of 3D protein lattices. Our study demonstrates that internal voxel design and inter-voxel encoding can be effectively employed to create protein lattices with designed organization, as confirmed by in situ X-ray scattering and cryo-electron microscopy 3D imaging. The assembled protein arrays maintain structural stability and biological activity in environments relevant for protein functionality. The framework design of the arrays then allows small molecules to access the ferritins and their iron cores and convert them into apoferritin arrays through the release of iron ions. The presented study introduces a platform approach for creating bio-active protein-containing ordered nanomaterials with desired 2D and 3D organizations.
          Cover page: Designed and biologically active protein lattices
          • Article
          • Peer Reviewed
          UC San Francisco Previously Published Works (2020)
          The rate of disability accumulation varies across multiple sclerosis (MS) patients. Machine learning techniques may offer more powerful means to predict disease course in MS patients. In our study, 724 patients from the Comprehensive Longitudinal Investigation in MS at Brigham and Women's Hospital (CLIMB study) and 400 patients from the EPIC dataset, University of California, San Francisco, were included in the analysis. The primary outcome was an increase in Expanded Disability Status Scale (EDSS) ≥ 1.5 (worsening) or not (non-worsening) at up to 5 years after the baseline visit. Classification models were built using the CLIMB dataset with patients' clinical and MRI longitudinal observations in first 2 years, and further validated using the EPIC dataset. We compared the performance of three popular machine learning algorithms (SVM, Logistic Regression, and Random Forest) and three ensemble learning approaches (XGBoost, LightGBM, and a Meta-learner L). A "threshold" was established to trade-off the performance between the two classes. Predictive features were identified and compared among different models. Machine learning models achieved 0.79 and 0.83 AUC scores for the CLIMB and EPIC datasets, respectively, shortly after disease onset. Ensemble learning methods were more effective and robust compared to standalone algorithms. Two ensemble models, XGBoost and LightGBM were superior to the other four models evaluated in our study. Of variables evaluated, EDSS, Pyramidal Function, and Ambulatory Index were the top common predictors in forecasting the MS disease course. Machine learning techniques, in particular ensemble methods offer increased accuracy for the prediction of MS disease course.
            Cover page: Ensemble learning predicts multiple sclerosis disease course in the SUMMIT study.
            • Article
            • Peer Reviewed
            UC Irvine Previously Published Works (2016)
            Diamond lattices formed by atomic or colloidal elements exhibit remarkable functional properties. However, building such structures via self-assembly has proven to be challenging because of the low packing fraction, sensitivity to bond orientation, and local heterogeneity. We report a strategy for creating a diamond superlattice of nano-objects via self-assembly and demonstrate its experimental realization by assembling two variant diamond lattices, one with and one without atomic analogs. Our approach relies on the association between anisotropic particles with well-defined tetravalent binding topology and isotropic particles. The constrained packing of triangular binding footprints of truncated tetrahedra on a sphere defines a unique three-dimensional lattice. Hence, the diamond self-assembly problem is solved via its mapping onto two-dimensional triangular packing on the surface of isotropic spherical particles.
              Cover page: Diamond family of nanoparticle superlattices
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