Mobile Produce Markets: A Strategy for Increasing Access to Fruits and Vegetables Among Low Income Urban Residents

Mobile produce markets (MPM) are a community-based strategy to improve produce access in areas with few fruits and vegetables (FV) retail options. The purpose of this thesis is to assess the functionality of MPM in low-income urban neighborhoods. This thesis includes three studies. Study 1 investigates FV availability in areas around MPM locations (n=13). We found limited fresh FV availability in stores, but high prevalence of 100% juice, and canned FV and beans. Study 2 applied questionnaire data from MPM shoppers (n=143) to assess MPM experiences. Chi Square was used to compare shopping behaviors between older (≥ 60) and younger (18-59.9 years) adults. Separate logistic regression models were used to predict Electronic Benefit Transfer (EBT) use, money spent, shopping frequency, and distance travelled to MPM, with age, race/ethnicity, sex, living alone/with others, and EBT in models. Participants indicated positive experiences with five dimensions of access: availability (variety), accessibility (location), affordability (price), acceptability (freshness), and accommodation (EBT use). Older shoppers were more likely to be long-term shoppers (P=0.002) and use EBT (P=0.012). Living alone predicted EBT use (P=0.03), shopping weekly (P=0.03), and traveling \u3c 1 mile (P=0.02). In Study 3, we interviewed 16 farmers to investigate experiences and perceptions of local markets including MPM. Income and community interaction were prominent themes. Farmers identified community organizations as important liaisons to coordinate MPM distribution and communicate community needs. MPM offer a promising strategy for serving low-income and minority populations—to be organized by communities themselves and to bring needed food directly to neighborhoods

Verification of band offsets and electron effective masses in GaAsN/GaAs quantum wells : Spectroscopic experiment versus 10-band k.p modeling

Optical transitions in GaAs1-xNx/GaAs quantum wells (QWs) have been probed by two complementary techniques, modulation spectroscopy in a form of photoreflectance and surface photovoltage spectroscopy. Transition energies in QWs of various widths and N contents have been compared with the results of band structure calculations based on the 10-band k.p Hamiltonian. Due to the observation of higher order transitions in the measured spectra, the band gap discontinuities at the GaAsN/GaAs interface and the electron effective masses could be determined, both treated as semi-free parameters to get the best matching between the theoretical and experimental energies. We have obtained the chemical conduction band offset values of 86% for x = 1.2% and 83% for x = 2.2%, respectively. For these determined band offsets, the electron effective masses equal to about 0.09 m(o) in QWs with 1.2% N and 0.15 m(o) for the case of larger N content of 2.2%.Publisher PDFPeer reviewe

Combining Gene Expression Data from Different Generations of Oligonucleotide Arrays

Background: One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public repositories. Through a comparative analysis on a variety of datasets, a more comprehensive view of the underlying mechanism or structure can be obtained. However, as we discover in this work, continual changes in genomic sequence annotations and probe design criteria make it difficult to compare gene expression data even from different generations of the same microarray platform. Results: We first describe the extent of discordance between the results derived from two generations of Affymetrix oligonucleotide arrays, as revealed in cluster analysis and in identification of differentially expressed genes. We then propose a method for increasing comparability. The dataset we use consists of a set of 14 human muscle biopsy samples from patients with inflammatory myopathies that were hybridized on both HG-U95Av2 and HG-U133A human arrays. We find that the use of the probe set matching table for comparative analysis provided by Affymetrix produces better results than matching by UniGene or LocusLink identifiers but still remains inadequate. Rescaling of expression values for each gene across samples and data filtering by expression values enhance comparability but only for few specific analyses. As a generic method for improving comparability, we select a subset of probes with overlapping sequence segments in the two array types and recalculate expression values based only on the selected probes. We show that this filtering of probes significantly improves the comparability while retaining a sufficient number of probe sets for further analysis. Conclusions: Compatibility between high-density oligonucleotide arrays is significantly affected by probe-level sequence information. With a careful filtering of the probes based on their sequence overlaps, data from different generations of microarrays can be combined more effectively

Development of high-speed directly-modulated DFB and DBR lasers with surface gratings

The conventional distributed feedback and distributed Bragg reflector edge-emitting lasers employ buried gratings, which require two or more epitaxial growth steps. By using lateral corrugations of the ridge-waveguide as surface gratings the epitaxial overgrowth is avoided, reducing the fabrication complexity, increasing the yield and reducing the fabrication cost. The surface gratings are applicable to different materials, including Al-containing ones and can be easily integrated in complex device structures and photonic circuits. Single-contact and multiple contact edge-emitting lasers with laterally-corrugated ridge waveguide gratings have been developed both on GaAs and InP substrates with the aim to exploit the photon-photon resonance in order to extend their direct modulation bandwidth. The paper reports on the characteristics of such surface-grating-based lasers emitting both at 1.3 and 1.55 μm and presents the photon-photon resonance extended small-signal modulation bandwidth (> 20 GHz) achieved with a 1.6 mm long single-contact device under direct modulation. Similarly structured devices, with shorter cavity lengths are expected to exceed 40 GHz smallsignal modulation bandwidth under direct modulatio

Combining gene expression data from different generations of oligonucleotide arrays

BACKGROUND: One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public repositories. Through a comparative analysis on a variety of datasets, a more comprehensive view of the underlying mechanism or structure can be obtained. However, as we discover in this work, continual changes in genomic sequence annotations and probe design criteria make it difficult to compare gene expression data even from different generations of the same microarray platform. RESULTS: We first describe the extent of discordance between the results derived from two generations of Affymetrix oligonucleotide arrays, as revealed in cluster analysis and in identification of differentially expressed genes. We then propose a method for increasing comparability. The dataset we use consists of a set of 14 human muscle biopsy samples from patients with inflammatory myopathies that were hybridized on both HG-U95Av2 and HG-U133A human arrays. We find that the use of the probe set matching table for comparative analysis provided by Affymetrix produces better results than matching by UniGene or LocusLink identifiers but still remains inadequate. Rescaling of expression values for each gene across samples and data filtering by expression values enhance comparability but only for few specific analyses. As a generic method for improving comparability, we select a subset of probes with overlapping sequence segments in the two array types and recalculate expression values based only on the selected probes. We show that this filtering of probes significantly improves the comparability while retaining a sufficient number of probe sets for further analysis. CONCLUSIONS: Compatibility between high-density oligonucleotide arrays is significantly affected by probe-level sequence information. With a careful filtering of the probes based on their sequence overlaps, data from different generations of microarrays can be combined more effectively

Integration of heterogeneous expression data sets extends the role of the retinol pathway in diabetes and insulin resistance

Motivation: Type 2 diabetes is a chronic metabolic disease that involves both environmental and genetic factors. To understand the genetics of type 2 diabetes and insulin resistance, the DIabetes Genome Anatomy Project (DGAP) was launched to profile gene expression in a variety of related animal models and human subjects. We asked whether these heterogeneous models can be integrated to provide consistent and robust biological insights into the biology of insulin resistance. Results: We perform integrative analysis of the 16 DGAP data sets that span multiple tissues, conditions, array types, laboratories, species, genetic backgrounds and study designs. For each data set, we identify differentially expressed genes compared with control. Then, for the combined data, we rank genes according to the frequency with which they were found to be statistically significant across data sets. This analysis reveals RetSat as a widely shared component of mechanisms involved in insulin resistance and sensitivity and adds to the growing importance of the retinol pathway in diabetes, adipogenesis and insulin resistance. Top candidates obtained from our analysis have been confirmed in recent laboratory studies.National Institutes of Health (U.S.) (Roadmap for Medical Research, grant U54LM008748

Integration of Heterogeneous Expression Data Sets Extends the Role of the Retinol Pathway in Diabetes and Insulin Resistance

Motivation: Type 2 diabetes is a chronic metabolic disease that involves both environmental and genetic factors. To understand the genetics of type 2 diabetes and insulin resistance, the DIabetes Genome Anatomy Project (DGAP) was launched to profile gene expression in a variety of related animal models and human subjects. We asked whether these heterogeneous models can be integrated to provide consistent and robust biological insights into the biology of insulin resistance. Results: We perform integrative analysis of the 16 DGAP data sets that span multiple tissues, conditions, array types, laboratories, species, genetic backgrounds and study designs. For each data set, we identify differentially expressed genes compared with control. Then, for the combined data, we rank genes according to the frequency with which they were found to be statistically significant across data sets. This analysis reveals RetSat as a widely shared component of mechanisms involved in insulin resistance and sensitivity and adds to the growing importance of the retinol pathway in diabetes, adipogenesis and insulin resistance. Top candidates obtained from our analysis have been confirmed in recent laboratory studies. Contact: [email protected]

Effect of dielectric medium anisotropy on the polarization degree of emission from a single quantum dash

This research was supported by the Polish Ministry of Science and Higher Education/the National Science Center Grant No. 2011/02/A/ST3/00152. The experiments have partially been performed within the laboratory infrastructure financed by the Polish Ministry of Science and Higher Education Grant No. 6167/IA/119/2012.Excitonic emission from single InAs/InGaAlAs/InP quantum dashes has been investigated in the context of degree of linear polarization by post-growth modification of its surrounding dielectric medium. We present optical spectroscopy measurements on a symmetric squared pedestal structures (mesas), and asymmetric rectangular ones oriented parallel or perpendicular to the main in-plane axis of the dashes [1-10]. Polarization resolved microphotoluminescence shows a significant quantitative modification of the degree of linear polarization value from -20% up to 70%. These results have been confronted with calculations of the coupling between the exciton transition dipole moment and electromagnetic field distributed in the vicinity of a quantum dash inside a processed mesa.Postprin

Low energy and dynamical properties of a single hole in the t-Jz model

We review in details a recently proposed technique to extract information about dynamical correlation functions of many-body hamiltonians with a few Lanczos iterations and without the limitation of finite size. We apply this technique to understand the low energy properties and the dynamical spectral weight of a simple model describing the motion of a single hole in a quantum antiferromagnet: the $t-J_z$ model in two spatial dimension and for a double chain lattice. The simplicity of the model allows us a well controlled numerical solution, especially for the two chain case. Contrary to previous approximations we have found that the single hole ground state in the infinite system is continuously connected with the Nagaoka fully polarized state for $J_z \to 0$. Analogously we have obtained an accurate determination of the dynamical spectral weight relevant for photoemission experiments. For $J_z=0$ an argument is given that the spectral weight vanishes at the Nagaoka energy faster than any power law, as supported also by a clear numerical evidence. It is also shown that spin charge decoupling is an exact property for a single hole in the Bethe lattice but does not apply to the more realistic lattices where the hole can describe closed loop paths.Comment: RevTex 3.0, 40 pages + 16 Figures in one file self-extracting, to appear in Phys. Rev

Network-Based Analysis of Affected Biological Processes in Type 2 Diabetes Models

Type 2 diabetes mellitus is a complex disorder associated with multiple genetic, epigenetic, developmental, and environmental factors. Animal models of type 2 diabetes differ based on diet, drug treatment, and gene knockouts, and yet all display the clinical hallmarks of hyperglycemia and insulin resistance in peripheral tissue. The recent advances in gene-expression microarray technologies present an unprecedented opportunity to study type 2 diabetes mellitus at a genome-wide scale and across different models. To date, a key challenge has been to identify the biological processes or signaling pathways that play significant roles in the disorder. Here, using a network-based analysis methodology, we identified two sets of genes, associated with insulin signaling and a network of nuclear receptors, which are recurrent in a statistically significant number of diabetes and insulin resistance models and transcriptionally altered across diverse tissue types. We additionally identified a network of protein–protein interactions between members from the two gene sets that may facilitate signaling between them. Taken together, the results illustrate the benefits of integrating high-throughput microarray studies, together with protein–protein interaction networks, in elucidating the underlying biological processes associated with a complex disorder