Cutting edge: distinct glycolytic and lipid oxidative metabolic programs are essential for effector and regulatory CD4+ T cell subsets.

Stimulated CD4(+) T lymphocytes can differentiate into effector T cell (Teff) or inducible regulatory T cell (Treg) subsets with specific immunological roles. We show that Teff and Treg require distinct metabolic programs to support these functions. Th1, Th2, and Th17 cells expressed high surface levels of the glucose transporter Glut1 and were highly glycolytic. Treg, in contrast, expressed low levels of Glut1 and had high lipid oxidation rates. Consistent with glycolysis and lipid oxidation promoting Teff and Treg, respectively, Teff were selectively increased in Glut1 transgenic mice and reliant on glucose metabolism, whereas Treg had activated AMP-activated protein kinase and were dependent on lipid oxidation. Importantly, AMP-activated protein kinase stimulation was sufficient to decrease Glut1 and increase Treg generation in an asthma model. These data demonstrate that CD4(+) T cell subsets require distinct metabolic programs that can be manipulated in vivo to control Treg and Teff development in inflammatory diseases.

R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics

Nolan and Temple Lang argue that “the ability to express statistical computations is an es- sential skill.” A key related capacity is the ability to conduct and present data analysis in a way that another person can understand and replicate. The copy-and-paste workflow that is an artifact of antiquated user-interface design makes reproducibility of statistical analysis more difficult, especially as data become increasingly complex and statistical methods become increasingly sophisticated. R Markdown is a new technology that makes creating fully-reproducible statistical analysis simple and painless. It provides a solution suitable not only for cutting edge research, but also for use in an introductory statistics course. We present experiential and statistical evidence that R Markdown can be used effectively in introductory statistics courses, and discuss its role in the rapidly-changing world of statistical computation.

Nanostructured Metal Oxide Coatings for Electrochemical Energy Conversion and Storage Electrodes

The realization of an energy future based on safe, clean, sustainable, and economically viable technologies is one of the grand challenges facing modern society. Electrochemical energy technologies underpin the potential success of this effort to divert energy sources away from fossil fuels, whether one considers alternative energy conversion strategies through photoelectrochemical (PEC) production of chemical fuels or fuel cells run with sustainable hydrogen, or energy storage strategies, such as in batteries and supercapacitors. This dissertation builds on recent advances in nanomaterials design, synthesis, and characterization to develop novel electrodes that can electrochemically convert and store energy.

Chapter 2 of this dissertation focuses on refining the properties of TiO2-based PEC water-splitting photoanodes used for the direct electrochemical conversion of solar energy into hydrogen fuel. The approach utilized atomic layer deposition (ALD); a growth process uniquely suited for the conformal and uniform deposition of thin films with angstrom-level thickness precision. ALD’s thickness control enabled a better understanding of how the effects of nitrogen doping via NH3 annealing treatments, used to reduce TiO2’s bandgap, can have a strong dependence on TiO2’s thickness and crystalline quality. In addition, it was found that some of the negative effects on the PEC performance typically associated with N-doped TiO2 could be mitigated if the NH3-annealing was directly preceded by an air-annealing step, especially for ultrathin (i.e., < 10 nm) TiO2 films. ALD was also used to conformally coat an ultraporous conductive fluorine-doped tin oxide nanoparticle (nanoFTO) scaffold with an ultrathin layer of TiO2. The integration of these ultrathin films and the oxide nanoparticles resulted in a heteronanostructure design with excellent PEC water oxidation photocurrents (0.7 mA/cm2 at 0 V vs. Ag/AgCl) and charge transfer efficiency.

In Chapter 3, two innovative nanoarchitectures were engineered in order to enhance the pseudocapacitive energy storage of next generation supercapacitor electrodes. The morphology and quantity of MnO2 electrodeposits was controlled by adjusting the density of graphene foliates on a novel graphenated carbon nanotube (g-CNT) scaffold. This control enabled the nanocomposite supercapacitor electrode to reach a capacitance of 640 F/g, under MnO2 specific mass loading conditions (2.3 mg/cm2) that are higher than previously reported. In the second engineered nanoarchitecture, the electrochemical energy storage properties of a transparent electrode based on a network of solution-processed Cu/Ni cores/shell nanowires (NWs) were activated by electrochemically converting the Ni metal shell into Ni(OH)2. Furthermore, an adjustment of the molar percentage of Ni plated onto the Cu NWs was found to result in a tradeoff between capacitance, transmittance, and stability of the resulting nickel hydroxide-based electrode. The nominal area capacitance and power performance results obtained for this Cu/Ni(OH)2 transparent electrode demonstrates that it has significant potential as a hybrid supercapacitor electrode for integration into cutting edge flexible and transparent electronic devices.

Math 412 - Topology with Applications

Highlights of Data Expedition: • Students explored daily observations of local climate data spanning the past 35 years. • Topological Data Analysis, or TDA for short, provides cutting-edge tools for studying the geometry of data in arbitrarily high dimensions. • Using TDA tools, students discovered intrinsic dynamical features of the data and learned how to quantify periodic phenomenon in a time-series. • Since nature invariably produces noisy data which rarely has exact periodicity, students also considered the theoretical basis of almost-periodicity and even invented and tested new mathematical definitions of almost-periodic functions. Summary The dataset we used for this data expedition comes from the Global Historical Climatology Network. “GHCN (Global Historical Climatology Network)-Daily is an integrated database of daily climate summaries from land surface stations across the globe.” Source: https://www.ncdc.noaa.gov/oa/climate/ghcn-daily/ We focused on the daily maximum and minimum temperatures from January 1, 1980 to April 1, 2015 collected from RDU International Airport. Through a guided series of exercises designed to be performed in Matlab, students explore these time-series, initially by direct visualization and basic statistical techniques. Then students are guided through a special sliding-window construction which transforms a time-series into a high-dimensional geometric curve. These high-dimensional curves can be visualized by projecting down to lower dimensions as in the figure below (Figure 1), however, our focus here was to use persistent homology to directly study the high-dimensional embedding. The shape of these curves has meaningful information but how one describes the “shape” of data depends on which scale the data is being considered. However, choosing the appropriate scale is rarely an obvious choice. Persistent homology overcomes this obstacle by allowing us to quantitatively study geometric features of the data across multiple-scales. Through this data expedition, students are introduced to numerically computing persistent homology using the rips collapse algorithm and interpreting the results. In the specific context of sliding-window constructions, 1-dimensional persistent homology can reveal the nature of periodic structure in the original data. I created a special technique to study how these high-dimensional sliding-window curves form loops in order to quantify the periodicity. Students are guided through this construction and learn how to visualize and interpret this information. Climate data is extremely complex (as anyone who has suffered from a bad weather prediction can attest) and numerous variables play a role in determining our daily weather and temperatures. This complexity coupled with imperfections of measuring devices results in very noisy data. This causes the annual seasonal periodicity to be far from exact. To this end, I have students explore existing theoretical notions of almost-periodicity and test it on the data. They find that some existing definitions are also inadequate in this context. Hence I challenged them to invent new mathematics by proposing and testing their own definition. These students rose to the challenge and suggested a number of creative definitions. While autocorrelation and spectral methods based on Fourier analysis are often used to explore periodicity, the construction here provides an alternative paradigm to quantify periodic structure in almost-periodic signals using tools from topological data analysis.

Facet-embedded thin-film III-V edge-emitting lasers integrated with SU-8 waveguides on silicon.

A thin-film InGaAs/GaAs edge-emitting single-quantum-well laser has been integrated with a tapered multimode SU-8 waveguide onto an Si substrate. The SU-8 waveguide is passively aligned to the laser using mask-based photolithography, mimicking electrical interconnection in Si complementary metal-oxide semiconductor, and overlaps one facet of the thin-film laser for coupling power from the laser to the waveguide. Injected threshold current densities of 260A/cm(2) are measured with the reduced reflectivity of the embedded laser facet while improving single mode coupling efficiency, which is theoretically simulated to be 77%.

Plantar Loading During Cutting While Wearing a Rigid Carbon Fiber Insert.

Context : Stress fractures are one of the most common injuries in sports, accounting for approximately 10% of all overuse injuries. Treatment of fifth metatarsal stress fractures involves both surgical and nonsurgical interventions. Fifth metatarsal stress fractures are difficult to treat because of the risks of delayed union, nonunion, and recurrent injuries. Most of these injuries occur during agility tasks, such as those performed in soccer, basketball, and lacrosse. Objective : To examine the effect of a rigid carbon graphite footplate on plantar loading during 2 agility tasks. Design :  Crossover study. Setting : Laboratory. Patients or Other Participants : A total of 19 recreational male athletes with no history of lower extremity injury in the past 6 months and no previous metatarsal stress fractures were tested. Main Outcome Measure(s) :  Seven 45° side-cut and crossover-cut tasks were completed in a shoe with or without a full-length rigid carbon plate. Testing order between the shoe conditions and the 2 cutting tasks was randomized. Plantar-loading data were recorded using instrumented insoles. Peak pressure, maximum force, force-time integral, and contact area beneath the total foot, the medial and lateral midfoot, and the medial, middle, and lateral forefoot were analyzed. A series of paired t tests was used to examine differences between the footwear conditions (carbon graphite footplate, shod) for both cutting tasks independently (α = .05). Results : During the side-cut task, the footplate increased total foot and lateral midfoot peak pressures while decreasing contact area and lateral midfoot force-time integral. During the crossover-cut task, the footplate increased total foot and lateral midfoot peak pressure and lateral forefoot force-time integral while decreasing total and lateral forefoot contact area. Conclusions : Although a rigid carbon graphite footplate altered some aspects of the plantar- pressure profile during cutting in uninjured participants, it was ineffective in reducing plantar loading beneath the fifth metatarsal.