Morphological characteristics of urban water bodies: mechanisms of change and implications for ecosystem function.

The size, shape, and connectivity of water bodies (lakes, ponds, and wetlands) can have important effects on ecological communities and ecosystem processes, but how these characteristics are influenced by land use and land cover change over broad spatial scales is not known. Intensive alteration of water bodies during urban development, including construction, burial, drainage, and reshaping, may select for certain morphometric characteristics and influence the types of water bodies present in cities. We used a database of over one million water bodies in 100 cities across the conterminous United States to compare the size distributions, connectivity (as intersection with surface flow lines), and shape (as measured by shoreline development factor) of water bodies in different land cover classes. Water bodies in all urban land covers were dominated by lakes and ponds, while reservoirs and wetlands comprised only a small fraction of the sample. In urban land covers, as compared to surrounding undeveloped land, water body size distributions converged on moderate sizes, shapes toward less tortuous shorelines, and the number and area of water bodies that intersected surface flow lines (i.e., streams and rivers) decreased. Potential mechanisms responsible for changing the characteristics of urban water bodies include: preferential removal, physical reshaping or addition of water bodies, and selection of locations for development. The relative contributions of each mechanism likely change as cities grow. The larger size and reduced surface connectivity of urban water bodies may affect the role of internal dynamics and sensitivity to catchment processes. More broadly, these results illustrate the complex nature of urban watersheds and highlight the need to develop a conceptual framework for urban water bodies.

Properties of InAlN/GaN Heterostructures Prepared by Molecular Beam Epitaxy

InAlN thin films and InAlN/GaN heterostructures have been intensively studied over recent years due to their applications in a variety of devices, including high electron mobility transistors (HEMTs). However, the quality of InAlN remains relatively poor with basic material and structural characteristics remain unclear.

Molecular beam epitaxy (MBE) is used to synthesize the materials for this research, as MBE is a widely used tool for semiconductor growth but has rarely been explored for InAlN growth. X-ray photoelectron spectroscopy (XPS) is used to determine the electronic and chemical characteristics of InAlN surfaces. This tool is used for the first time in application to MBE-grown InAlN and heterostructures for the characterization of surface oxides, the bare surface barrier height (BSBH), and valence band offsets (VBOs).

The surface properties of InAlN are studied in relation to surface oxide characteristics and formation. First, the native oxide compositions are studied. Then, methods enabling the effective removal of the native oxides are found. Finally, annealing is explored for the reliable growth of surface thermal oxides.

The bulk properties of InAlN films are studied. The unintentional compositional grading in InAlN during MBE growth is discovered and found to be affected by strain and relaxation. The optical characterization of InAlN using spectroscopy ellipsometry (SE) is also developed and reveals that a two-phase InAlN model applies to MBE-grown InAlN due to its natural formation of a nanocolumnar microstructure. The insertion of an AlN interlayer is found to mitigate the formation of this microstructure and increases mobility of whole structure by fivefold.

Finally, the synthesis and characterization of InAlN/GaN HEMT device structures are explored. The density and energy distribution of surface states are studied with relationships to surface chemical composition and surface oxide. The determination of the VBOs of InAlN/GaN structures with different In compositions are discussed at last.

Adaptive Brain-Computer Interface Systems For Communication in People with Severe Neuromuscular Disabilities

Brain-computer interfaces (BCI) have the potential to restore communication or control abilities in individuals with severe neuromuscular limitations, such as those with amyotrophic lateral sclerosis (ALS). The role of a BCI is to extract and decode relevant information that conveys a user's intent directly from brain electro-physiological signals and translate this information into executable commands to control external devices. However, the BCI decision-making process is error-prone due to noisy electro-physiological data, representing the classic problem of efficiently transmitting and receiving information via a noisy communication channel.

This research focuses on P300-based BCIs which rely predominantly on event-related potentials (ERP) that are elicited as a function of a user's uncertainty regarding stimulus events, in either an acoustic or a visual oddball recognition task. The P300-based BCI system enables users to communicate messages from a set of choices by selecting a target character or icon that conveys a desired intent or action. P300-based BCIs have been widely researched as a communication alternative, especially in individuals with ALS who represent a target BCI user population. For the P300-based BCI, repeated data measurements are required to enhance the low signal-to-noise ratio of the elicited ERPs embedded in electroencephalography (EEG) data, in order to improve the accuracy of the target character estimation process. As a result, BCIs have relatively slower speeds when compared to other commercial assistive communication devices, and this limits BCI adoption by their target user population. The goal of this research is to develop algorithms that take into account the physical limitations of the target BCI population to improve the efficiency of ERP-based spellers for real-world communication.

In this work, it is hypothesised that building adaptive capabilities into the BCI framework can potentially give the BCI system the flexibility to improve performance by adjusting system parameters in response to changing user inputs. The research in this work addresses three potential areas for improvement within the P300 speller framework: information optimisation, target character estimation and error correction. The visual interface and its operation control the method by which the ERPs are elicited through the presentation of stimulus events. The parameters of the stimulus presentation paradigm can be modified to modulate and enhance the elicited ERPs. A new stimulus presentation paradigm is developed in order to maximise the information content that is presented to the user by tuning stimulus paradigm parameters to positively affect performance. Internally, the BCI system determines the amount of data to collect and the method by which these data are processed to estimate the user's target character. Algorithms that exploit language information are developed to enhance the target character estimation process and to correct erroneous BCI selections. In addition, a new model-based method to predict BCI performance is developed, an approach which is independent of stimulus presentation paradigm and accounts for dynamic data collection. The studies presented in this work provide evidence that the proposed methods for incorporating adaptive strategies in the three areas have the potential to significantly improve BCI communication rates, and the proposed method for predicting BCI performance provides a reliable means to pre-assess BCI performance without extensive online testing.

Effect of microRNA modulation on bioartificial muscle function.

Cellular therapies have recently employed the use of small RNA molecules, particularly microRNAs (miRNAs), to regulate various cellular processes that may be altered in disease states. In this study, we examined the effect of transient muscle-specific miRNA inhibition on the function of three-dimensional skeletal muscle cultures, or bioartificial muscles (BAMs). Skeletal myoblast differentiation in vitro is enhanced by inhibiting a proliferation-promoting miRNA (miR-133) expressed in muscle tissues. As assessed by functional force measurements in response to electrical stimulation at frequencies ranging from 0 to 20 Hz, peak forces exhibited by BAMs with miR-133 inhibition (anti-miR-133) were on average 20% higher than the corresponding negative control, although dynamic responses to electrical stimulation in miRNA-transfected BAMs and negative controls were similar to nontransfected controls. Immunostaining for alpha-actinin and myosin also showed more distinct striations and myofiber organization in anti-miR-133 BAMs, and fiber diameters were significantly larger in these BAMs over both the nontransfected and negative controls. Compared to the negative control, anti-miR-133 BAMs exhibited more intense nuclear staining for Mef2, a key myogenic differentiation marker. To our knowledge, this study is the first to demonstrate that miRNA mediation has functional effects on tissue-engineered constructs.

Accelerating self-consistent field convergence with the augmented Roothaan-Hall energy function.

Based on Pulay's direct inversion iterative subspace (DIIS) approach, we present a method to accelerate self-consistent field (SCF) convergence. In this method, the quadratic augmented Roothaan-Hall (ARH) energy function, proposed recently by Høst and co-workers [J. Chem. Phys. 129, 124106 (2008)], is used as the object of minimization for obtaining the linear coefficients of Fock matrices within DIIS. This differs from the traditional DIIS of Pulay, which uses an object function derived from the commutator of the density and Fock matrices. Our results show that the present algorithm, abbreviated ADIIS, is more robust and efficient than the energy-DIIS (EDIIS) approach. In particular, several examples demonstrate that the combination of ADIIS and DIIS ("ADIIS+DIIS") is highly reliable and efficient in accelerating SCF convergence.

In vivo inhibition of elevated myocardial beta-adrenergic receptor kinase activity in hybrid transgenic mice restores normal beta-adrenergic signaling and function.

BACKGROUND: The clinical syndrome of heart failure (HF) is characterized by an impaired cardiac beta-adrenergic receptor (betaAR) system, which is critical in the regulation of myocardial function. Expression of the betaAR kinase (betaARK1), which phosphorylates and uncouples betaARs, is elevated in human HF; this likely contributes to the abnormal betaAR responsiveness that occurs with beta-agonist administration. We previously showed that transgenic mice with increased myocardial betaARK1 expression had impaired cardiac function in vivo and that inhibiting endogenous betaARK1 activity in the heart led to enhanced myocardial function. METHODS AND RESULTS: We created hybrid transgenic mice with cardiac-specific concomitant overexpression of both betaARK1 and an inhibitor of betaARK1 activity to study the feasibility and functional consequences of the inhibition of elevated betaARK1 activity similar to that present in human HF. Transgenic mice with myocardial overexpression of betaARK1 (3 to 5-fold) have a blunted in vivo contractile response to isoproterenol when compared with non-transgenic control mice. In the hybrid transgenic mice, although myocardial betaARK1 levels remained elevated due to transgene expression, in vitro betaARK1 activity returned to control levels and the percentage of betaARs in the high-affinity state increased to normal wild-type levels. Furthermore, the in vivo left ventricular contractile response to betaAR stimulation was restored to normal in the hybrid double-transgenic mice. CONCLUSIONS: Novel hybrid transgenic mice can be created with concomitant cardiac-specific overexpression of 2 independent transgenes with opposing actions. Elevated myocardial betaARK1 in transgenic mouse hearts (to levels seen in human HF) can be inhibited in vivo by a peptide that can prevent agonist-stimulated desensitization of cardiac betaARs. This may represent a novel strategy to improve myocardial function in the setting of compromised heart function.

Essential role of beta-adrenergic receptor kinase 1 in cardiac development and function.

The beta-adrenergic receptor kinase 1 (beta ARK1) is a member of the G protein-coupled receptor kinase (GRK) family that mediates the agonist-dependent phosphorylation and desensitization of G protein-coupled receptors. We have cloned and disrupted the beta ARK1 gene in mice by homologous recombination. No homozygote beta ARK1-/- embryos survive beyond gestational day 15.5. Prior to gestational day 15.5, beta ARK1-/- embryos display pronounced hypoplasia of the ventricular myocardium essentially identical to the "thin myocardium syndrome" observed upon gene inactivation of several transcription factors (RXR alpha, N-myc, TEF-1, WT-1). Lethality in beta ARK1-/- embryos is likely due to heart failure as they exhibit a > 70% decrease in cardiac ejection fraction determined by direct in utero intravital microscopy. These results along with the virtual absence of endogenous GRK activity in beta ARK1-/- embryos demonstrate that beta ARK1 appears to be the predominant GRK in early embryogenesis and that it plays a fundamental role in cardiac development.

Regions of the alpha 1-adrenergic receptor involved in coupling to phosphatidylinositol hydrolysis and enhanced sensitivity of biological function.

Regions of the hamster alpha 1-adrenergic receptor (alpha 1 AR) that are important in GTP-binding protein (G protein)-mediated activation of phospholipase C were determined by studying the biological functions of mutant receptors constructed by recombinant DNA techniques. A chimeric receptor consisting of the beta 2-adrenergic receptor (beta 2AR) into which the putative third cytoplasmic loop of the alpha 1AR had been placed activated phosphatidylinositol metabolism as effectively as the native alpha 1AR, as did a truncated alpha 1AR lacking the last 47 residues in its cytoplasmic tail. Substitutions of beta 2AR amino acid sequence in the intermediate portions of the third cytoplasmic loop of the alpha 1AR or at the N-terminal portion of the cytoplasmic tail caused marked decreases in receptor coupling to phospholipase C. Conservative substitutions of two residues in the C terminus of the third cytoplasmic loop (Ala293----Leu, Lys290----His) increased the potency of agonists for stimulating phosphatidylinositol metabolism by up to 2 orders of magnitude. These data indicate (i) that the regions of the alpha 1AR that determine coupling to phosphatidylinositol metabolism are similar to those previously shown to be involved in coupling of beta 2AR to adenylate cyclase stimulation and (ii) that point mutations of a G-protein-coupled receptor can cause remarkable increases in sensitivity of biological response.

Nucleolar organization, ribosomal DNA array stability, and acrocentric chromosome integrity are linked to telomere function.

The short arms of the ten acrocentric human chromosomes share several repetitive DNAs, including ribosomal RNA genes (rDNA). The rDNA arrays correspond to nucleolar organizing regions that coalesce each cell cycle to form the nucleolus. Telomere disruption by expressing a mutant version of telomere binding protein TRF2 (dnTRF2) causes non-random acrocentric fusions, as well as large-scale nucleolar defects. The mechanisms responsible for acrocentric chromosome sensitivity to dysfunctional telomeres are unclear. In this study, we show that TRF2 normally associates with the nucleolus and rDNA. However, when telomeres are crippled by dnTRF2 or RNAi knockdown of TRF2, gross nucleolar and chromosomal changes occur. We used the controllable dnTRF2 system to precisely dissect the timing and progression of nucleolar and chromosomal instability induced by telomere dysfunction, demonstrating that nucleolar changes precede the DNA damage and morphological changes that occur at acrocentric short arms. The rDNA repeat arrays on the short arms decondense, and are coated by RNA polymerase I transcription binding factor UBF, physically linking acrocentrics to one another as they become fusogenic. These results highlight the importance of telomere function in nucleolar stability and structural integrity of acrocentric chromosomes, particularly the rDNA arrays. Telomeric stress is widely accepted to cause DNA damage at chromosome ends, but our findings suggest that it also disrupts chromosome structure beyond the telomere region, specifically within the rDNA arrays located on acrocentric chromosomes. These results have relevance for Robertsonian translocation formation in humans and mechanisms by which acrocentric-acrocentric fusions are promoted by DNA damage and repair.

Using Helix-coil Models to Study Protein Unfolded States

An abstract of a thesis devoted to using helix-coil models to study unfolded states.\\

Research on polypeptide unfolded states has received much more attention in the last decade or so than it has in the past. Unfolded states are thought to be implicated in various

misfolding diseases and likely play crucial roles in protein folding equilibria and folding rates. Structural characterization of unfolded states has proven to be

much more difficult than the now well established practice of determining the structures of folded proteins. This is largely because many core assumptions underlying

folded structure determination methods are invalid for unfolded states. This has led to a dearth of knowledge concerning the nature of unfolded state conformational

distributions. While many aspects of unfolded state structure are not well known, there does exist a significant body of work stretching back half a century that

has been focused on structural characterization of marginally stable polypeptide systems. This body of work represents an extensive collection of experimental

data and biophysical models associated with describing helix-coil equilibria in polypeptide systems. Much of the work on unfolded states in the last decade has not been devoted

specifically to the improvement of our understanding of helix-coil equilibria, which arguably is the most well characterized of the various conformational equilibria

that likely contribute to unfolded state conformational distributions. This thesis seeks to provide a deeper investigation of helix-coil equilibria using modern

statistical data analysis and biophysical modeling techniques. The studies contained within seek to provide deeper insights and new perspectives on what we presumably

know very well about protein unfolded states. \\

Chapter 1 gives an overview of recent and historical work on studying protein unfolded states. The study of helix-coil equilibria is placed in the context

of the general field of unfolded state research and the basics of helix-coil models are introduced.\\

Chapter 2 introduces the newest incarnation of a sophisticated helix-coil model. State of the art modern statistical techniques are employed to estimate the energies

of various physical interactions that serve to influence helix-coil equilibria. A new Bayesian model selection approach is utilized to test many long-standing

hypotheses concerning the physical nature of the helix-coil transition. Some assumptions made in previous models are shown to be invalid and the new model

exhibits greatly improved predictive performance relative to its predecessor. \\

Chapter 3 introduces a new statistical model that can be used to interpret amide exchange measurements. As amide exchange can serve as a probe for residue-specific

properties of helix-coil ensembles, the new model provides a novel and robust method to use these types of measurements to characterize helix-coil ensembles experimentally

and test the position-specific predictions of helix-coil models. The statistical model is shown to perform exceedingly better than the most commonly used

method for interpreting amide exchange data. The estimates of the model obtained from amide exchange measurements on an example helical peptide

also show a remarkable consistency with the predictions of the helix-coil model. \\

Chapter 4 involves a study of helix-coil ensembles through the enumeration of helix-coil configurations. Aside from providing new insights into helix-coil ensembles,

this chapter also introduces a new method by which helix-coil models can be extended to calculate new types of observables. Future work on this approach could potentially

allow helix-coil models to move into use domains that were previously inaccessible and reserved for other types of unfolded state models that were introduced in chapter 1.

High-Resolution In Situ Oxygen-Argon Studies of Surface Biological and Physical Processes in the Polar Oceans

The Arctic Ocean and Western Antarctic Peninsula (WAP) are the fastest warming regions on the planet and are undergoing rapid climate and ecosystem changes. Until we can fully resolve the coupling between biological and physical processes we cannot predict how warming will influence carbon cycling and ecosystem function and structure in these sensitive and climactically important regions. My dissertation centers on the use of high-resolution measurements of surface dissolved gases, primarily O2 and Ar, as tracers or physical and biological functioning that we measure underway using an optode and Equilibrator Inlet Mass Spectrometry (EIMS). Total O2 measurements are common throughout the historical and autonomous record but are influenced by biological (net metabolic balance) and physical (temperature, salinity, pressure changes, ice melt/freeze, mixing, bubbles and diffusive gas exchange) processes. We use Ar, an inert gas with similar solubility properties to O2, to devolve distinct records of biological (O2/Ar) and physical (Ar) oxygen. These high-resolution measurements that expose intersystem coupling and submesoscale variability were central to studies in the Arctic Ocean, WAP and open Southern Ocean that make up this dissertation.

Key findings of this work include the documentation of under ice and ice-edge blooms and basin scale net sea ice freeze/melt processes in the Arctic Ocean. In the WAP O2 and pCO2 are both biologically driven and net community production (NCP) variability is controlled by Fe and light availability tied to glacial and sea ice meltwater input. Further, we present a feasibility study that shows the ability to use modeled Ar to derive NCP from total O2 records. This approach has the potential to unlock critical carbon flux estimates from historical and autonomous O2 measurements in the global oceans.