Publications

Introduction: A plethora of indices have been investigated as optimal measures of carbohydrate quality in relation to risk of type 2 diabetes (T2D), but a systematic comparison has not been conducted. Hypothesis: We hypothesized that not all carbohydrate quality indices are equally associated with the risk of T2D. Methods: We investigated associations between twenty-two carbohydrate quality variables and T2D risk among 212,883 US adults with up to 32y of follow-up in the ongoing Nurses’ Health Study (NHS), NHS II, and the Health Professionals Follow-up Study. We used multivariable and BMI-adjusted Cox proportional hazards regression models. Results: Cereal fiber (comparing extreme quintiles of intake, RR:0.82, 95% CI:0.78, 0.87), whole fruit carbohydrates (RR:0.82, 95% CI:0.78, 0.87), glycemic index (RR:1.18, 95% CI:1.12, 1.24), and sugar-sweetened beverage (SSB) sugar (RR:1.23, 95% CI:1.17, 1.29) had the largest observed risk estimates of T2D (all P-trend<0.001). In addition, dietary glycemic load, starch, starchy vegetables, and potato and legume carbohydrates were positively associated (RR’s= 1.07 - 1.14), while whole grain carbohydrate intake was inversely associated with risk of T2D (RR= 0.94). Total and refined grain carbohydrates, added sugar, and non-starchy vegetables were not associated with risk of T2D. Ratios of carbohydrate or starch to total fiber or cereal fiber were all positively associated with risk of T2D (RR’s=1.11 - 1.33). The alternate Carbohydrate Quality Index (aCQI) (RR:0.73, 95% CI:0.69, 0.77) was more strongly associated with risk of T2D than the original CQI (RR:0.90, 95% CI:0.85, 0.95; both P-trend<0.001). Conclusion: Although many indices were associated with risk of T2D, higher intakes of cereal fiber and whole fruit carbohydrates, and lower intakes of glycemic index and sugar-sweetened beverage sugar had the lowest risk of T2D. The aCQI, comprising these four dietary variables and whole-grain carbohydrates, was strongly associated with risk of T2D and warrants further investigation.

Micromolding in capillaries (MIMIC)has been used to form patterned relief structures with lateral dimensions as small as ∼350 nm. The microstructure in the figure consists of polyaniline (on an insulating Si/SiO2 base) that has been converted into the emeraldine salt to yield a conductive microstructure that could subsequently be used as a patterned electrode in fabricating all-plastic field effect transistors.

This Communication demonstrates the generation of over 300 phase-separated systems-ranging from two to six phases-from mixtures of aqueous solutions of polymers and surfactants. These aqueous multiphase systems (MuPSs) form self-assembling, thermodynamically stable step-gradients in density using a common solvent, water. The steps in density between phases of a MuPS can be very small (Δρ ≈ 0.001 g/cm(3)), do not change over time, and can be tuned by the addition of co-solutes. We use two sets of similar objects, glass beads and pellets of different formulations of Nylon, to demonstrate the ability of MuPSs to separate mixtures of objects by differences in density. The stable interfaces between phases facilitate the convenient collection of species after separation. These results suggest that the stable, sharp step-gradients in density provided by MuPSs can enable new classes of fractionations and separations based on density.

The use of omniphobic "fluoroalkylated paper" as a substrate for inkjet printing of aqueous inks that are the precursors of electrically conductive patterns is described. By controlling the surface chemistry of the paper, it is possible to print high resolution, conductive patterns that remain conductive after folding and exposure to common solvents. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Background: Advances in metabolomics have allowed high-throughput metabolic profiling of large population samples. We aimed to identify circulating lipids and metabolites predictive of the risk for type 2 diabetes in young adults. Methods: Nuclear magnetic resonance metabolomics was used to quantify 229 metabolic measures in 10,938 individuals from four Finnish cohorts (mean age 35 years, range 24-45). Associations between baseline metabolites and diabetes onset during 7-15 years of follow-up (330 incident cases) were assessed by logistic regression adjusted for sex, baseline age and glucose. Findings: Out of 229 metabolic measures, 174 were associated with risk for incident diabetes in meta-analysis of the four cohorts (P<0.001; range of odds ratios (OR) per 1-SD: 0.41-1.85). Among the strongest biomarkers were increased concentrations of branched-chained and aromatic amino acids (OR: 1.54-1.74) and triglycerides in very-low-density lipoproteins (VLDL; OR 1.78), and lower levels of omega-6 fatty acids (OR 0.61) and free cholesterol within large high-density lipoprotein (HDL; OR 0.41). A biomarker score was derived in three of the cohorts, comprised of phenylalanine, free cholesterol in large HDL, and the ratio of cholesterol esters to total lipids in large VLDL. When validated in the fourth cohort, those in the upper quartile of the biomarker score had considerably higher 15-year-risk for diabetes compared to those in the lowest quartile (OR 16.1). Interpretation: Metabolic aberrations across multiple molecular pathways are predictive of the long-term risk of type 2 diabetes in young adults. Comprehensive metabolic profiling may facilitate targeting preventive interventions at young asymptomatic individuals at increased risk for type 2 diabetes. Disclosure A.V. Ahola-Olli: None. L. Mustelin: Employee; Self; Nightingale Health Ltd. M. Kalimeri: Employee; Self; Nightingale Health Oy. J. Kettunen: Other Relationship; Self; Nightingale Ltd. J.J. Jokelainen: None. J. Auvinen: None. K.S. Puukka: None. A.S. Havulinna: None. T. Lehtimäki: None. M. Kähönen: None. V. Salomaa: Other Relationship; Self; Novo Nordisk Inc.. M. Perola: None. M. Jarvelin: None. M. Ala-Korpela: None. P. Wurtz: Employee; Self; Nightingale Health. Stock/Shareholder; Self; Nightingale Health.

This paper describes a simple, versatile method of generating gradients in composition in solution or on surfaces using microfluidic systems. This method is based on controlled diffusive mixing of species in solutions that are flowing laminarly, at low Reynolds number, inside a network of microchannels. We demonstrate the use of this procedure to generate (1) gradients in the compositions of solutions, measured directly by colorimetric assays and (2) gradients in topography of the surfaces produced by generating concentration gradients of etching reagents, and then using these gradients to etch profiles into the substrate. The lateral dimensions of the gradients examined here, which went from 350 to 900 μm, are determined by the width of the microchannels. Gradients of different size, resolution, and shape have been generated using this method. The shape of the gradients can be changed continuously (dynamic gradients) by varying the relative flow velocities of the input streams of fluids. The method is experimentally simple and highly adaptable, and requires no special equipment except for an elastomeric relief structure that can be readily prepared by rapid prototyping. This technique provides a new platform with which to study phenomena that depend on gradients in concentration, especially dynamic phenomena in cell biology (chemotaxis and haptotaxis) and surface chemistry (nucleation and growth of crystals, etching, and Marangoni effects).

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