Publications

OBJECTIVES: This study examined the association between intake of whole vs refined grain and the risk of type 2 diabetes mellitus. METHODS: We used a food frequency questionnaire for repeated dietary assessments to prospectively evaluate the relation between whole-grain intake and the risk of diabetes mellitus in a cohort of 75,521 women aged 38 to 63 years without a previous diagnosis of diabetes or cardiovascular disease in 1984. RESULTS: During the 10-year follow-up, we confirmed 1879 incident cases of diabetes mellitus. When the highest and the lowest quintiles of intake were compared, the age and energy-adjusted relative risks were 0.62 (95% confidence interval [CI] = 0.53, 0.71, P trend < .0001) for whole grain, 1.31 (95% CI = 1.12, 1.53, P trend = .0003) for refined grain, and 1.57 (95% CI = 1.36, 1.82, P trend < .0001) for the ratio of refined- to whole-grain intake. These findings remained significant in multivariate analyses. The findings were most evident for women with a body mass index greater than 25 and were not entirely explained by dietary fiber, magnesium, and vitamin E. CONCLUSIONS: These findings suggest that substituting whole- for refined-grain products may decrease the risk of diabetes mellitus.

The dielectric response of a polymer matrix composite can be substantially modified and tuned within a broad frequency band by integrating within the material an artificial plasmon medium composed of periodically distributed, very thin, electrically conducting wires. In the microwave regime, such plasmon/polymer composites have been studied analytically, computationally, and experimentally. This work reports the design, fabrication, and characterization of similar composites for operation at terahertz frequencies. Such composites require significant reduction in the thickness and spacing of the wires. We used numerical modeling to design artificial effective plasmonic media with turn-on frequencies in the terahertz range. Prototype samples were produced by lithographically embedding very thin gold strips into a PDMS [poly(dimethylsiloxane)] matrix. These samples were characterized with a Fourier-transform infrared interferometer using the frequency-dependent transmission and Kramers-Kronig relations to determine the electromagnetic properties. We report the characterization results for a sample, demonstrating excellent agreement between theory, computer design, and experiment. To our knowledge this is the first demonstration of the possibility of creating composites with tuned dielectric response at terahertz frequencies.

The effect of metal substitution on the critical current densities of single-crystal PbxBi2-xSr2CaCu2O8 (x = 0 or x = 0.7) superconductors has been investigated. Substitution of lead was found to increase the average critical current density from 1 x 10(5) A/cm2 to 2 x 10(6) A/cm2 at 5 K in an applied magnetic field of 10 kilooersteds (1 oersted = 80 A/m). The order of magnitude increase in the critical current density was observed for temperatures up to the flux vortex lattice melting point; the flux lattice melting point was also found to increase to 30 K (from 22 K) in the lead-substituted materials. Diffraction and microscopy investigations of the structural parameters indicate that the fundamental atomic lattices are virtually the same for both materials. Scanning tunneling microscopy images demonstrate, however, that lead substitution causes significant disorder (or defects) in the one-dimensional superstructure found in Bi2Sr2CaCu2O8. Since crystal defects can increase the critical current density by pinning the motion of flux vortices, it is likely that this lead-induced disorder enhances vortex pinning. The lead-induced disorder is specific to the nonsuperconducting Bi-O layers, and thus our results suggest that chemical substitutions may be utilized to control selectively flux pinning and the critical current density in these materials.

Fifty-four (!) hydrogen bonds stabilize the single supramolecular aggregate (1) formed from the cooperative selfassembly of ten molecules. Compound 1, designated as Hub-(MMM)3 · 9 neohex(CA) by the authors—conventional nomenclature and even the drawing of structural formulae are overtaxed—, further demonstrates the potential of molecular self assembly as a strategy for the preparation of well-defined chemical nanostructures.

Abstract Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism 1–7 . This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases 8–11 . Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associations. We use detailed metabolic profiling of lipoprotein- and lipid-associated variants to better characterize how known lipid loci and novel loci affect lipoprotein metabolism at a granular level. We demonstrate the translational utility of comprehensively phenotyped molecular data, characterizing the metabolic associations of intrahepatic cholestasis of pregnancy. Finally, we observe substantial genetic pleiotropy for multiple metabolic pathways and illustrate the importance of careful instrument selection in Mendelian randomization analysis, revealing a putative causal relationship between acetone and hypertension. Our publicly available results provide a foundational resource for the community to examine the role of metabolism across diverse diseases.

No abstract is provided for this article.

Our work is motivated by the search for metabolite quantitative trait loci (QTL) in a cohort of more than 5000 people. There are 158 metabolites measured by NMR spectroscopy in the 31-year follow-up of the Northern Finland Birth Cohort 1966 (NFBC66). These metabolites, as with many multivariate phenotypes produced by high-throughput biomarker technology, exhibit strong correlation structures. Existing approaches for combining such data with genetic variants for multivariate QTL analysis generally ignore phenotypic correlations or make restrictive assumptions about the associations between phenotypes and genetic loci. We present a computationally efficient Bayesian seemingly unrelated regressions model for high-dimensional data, with cell-sparse variable selection and sparse graphical structure for covariance selection. Cell sparsity allows different phenotype responses to be associated with different genetic predictors and the graphical structure is used to represent the conditional dependencies between phenotype variables. To achieve feasible computation of the large model space, we exploit a factorisation of the covariance matrix. Applying the model to the NFBC66 data with 9000 directly genotyped single nucleotide polymorphisms, we are able to simultaneously estimate genotype-phenotype associations and the residual dependence structure among the metabolites. The R package BayesSUR with full documentation is available at https://cran.r-project.org/web/packages/BayesSUR/.

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTThe synthesis of aldose sugars from half-protected dialdehydes using rabbit muscle aldolaseChristopher W. Borysenko, Andreas Spaltenstein, Julie Ann Straub, and George M. WhitesidesCite this: J. Am. Chem. Soc. 1989, 111, 26, 9275–9276Publication Date (Print):December 1, 1989Publication History Published online1 May 2002Published inissue 1 December 1989https://pubs.acs.org/doi/10.1021/ja00208a046https://doi.org/10.1021/ja00208a046research-articleACS PublicationsRequest reuse permissionsArticle Views410Altmetric-Citations48LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-AlertscloseSupporting Info (1)»Supporting Information Supporting Information Get e-Alerts

This article describes a new procedure for generating and transmitting a message—a sequence of optical pulses—by aligning a mask (an opaque sheet containing transparent "windows") below a microfluidic channel in which flows an opaque continuous fluid containing transparent droplets. The optical mask encodes the message as a unique sequence of windows that can transmit or block light; the flow of transparent droplets in the channel converts this message into a sequence of optical pulses. The properties of the windows on the mask (e.g., their size, wavelength of transmittance, orientation of polarization) determine the information carried in these optical pulses (e.g., intensity, color, polarization). The structure of a transmitted signal depends on the number and spacing of droplets in the channel. Fourier transformation can deconvolve superimposed signals created by the flow of multiple droplets into the message that a single droplet would transmit. The research described in this contribution explores a new field at the intersection of chemistry, materials science, and information technology: infochemistry.