Publications

Abstract Context: High retinol-binding protein 4 (RBP4) is thought to be associated with insulin resistance in humans. However, evidence from large-scale populations about the relationship between RBP4 and metabolic diseases is scarce. Objective: We evaluated plasma RBP4 distribution and its association with metabolic syndrome (MetS) among middle-aged and older Chinese. Research Design and Methods: We evaluated plasma RBP4 in a cross-sectional sample of 3289 Chinese aged from 50 to 70 yr in Beijing and Shanghai by using an in-house developed and validated sandwich ELISA. MetS was defined according to the updated National Cholesterol Education Program Adult Treatment Panel III criteria for Asian-Americans. Results: RBP4 levels were higher in male and Beijing residents, compared with female and Shanghai participants (both P < 0.001). RBP4 levels were associated positively with body mass index, waist circumference, triglycerides, total and low-density lipoprotein cholesterol, blood pressure, fasting insulin, and homeostatic model assessment of insulin resistance and negatively with high-density lipoprotein cholesterol and adiponectin (all P < 0.001). In the highest RBP4 quartile, the MetS risk was significantly higher (odds ratio 2.58; 95% confidence interval 2.08–3.20) than in the lowest quartile after adjustment for potential confounders. This association remained strong (odds ratio 2.25; 95% confidence interval 1.72–2.94) after further controlling for C-reactive protein, adiponectin, homeostatic model assessment of insulin resistance, and body mass index. Conclusions: This first large-scale population study shows that elevated RBP4 levels are strongly and independently associated with MetS. Prospective studies are needed to establish the role of RBP4 in the development of MetS and related diseases.

ADVERTISEMENT RETURN TO ISSUEPREVNoteNEXTCharacterization of Hydrogen-Bonded Aggregates in Chloroform by Electrospray Ionization Mass SpectrometryXueheng Cheng, Quanyin Gao, Richard D. Smith, Eric E. Simanek, Mathai Mammen, and George M. WhitesidesView Author Information Chemical Sciences Department and Environmental Molecular Sciences Laboratory, Pacific Northwest Laboratories, Richland, Washington 99352 Department of Chemistry, Harvard University, Cambridge, Massachusetts 02138 Cite this: J. Org. Chem. 1996, 61, 6, 2204–2206Publication Date (Web):March 22, 1996Publication History Received24 July 1995Revised7 December 1995Published online22 March 1996Published inissue 1 January 1996https://doi.org/10.1021/jo951345gCopyright © 1996 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views313Altmetric-Citations41LEARN 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 InReddit Read OnlinePDF (61 KB) Get e-AlertsSUBJECTS:Chemical structure,Dissociation,Ions,Mass spectrometry,Stability Get e-Alerts

Additional file 16: Table S12. Results of the investigation into associations between metabolic measures-related CpG sites and clinical outcomes. Listed are the CpG site-clinical outcome (previous myocardial infarction, prevalent type 2 diabetes, obesity and prevalent hypertension) results for both model 1: logistic regression model with clinical outcome as dependent variable and technically adjusted methylation value as independent variable, adjusted for the following covariates: age, sex, BMI, C-reactive protein levels, hemoglobin A1c levels (except for diabetes model), history of myocardial infarction (except for the myocardial infarction model), smoking status, current hypertension (except for the hypertension model), physical activity, white blood cell count and estimated proportions of white blood cell type; or model 2, which is additionally adjusted for intake of lipid-lowering drugs. P: p value of the association; OR: odds ratio for a 1 standard deviation increase in methylation; CI: confidence interval; FDR: false discovery rate p value based on the Benjamini–Hochberg method applied to each outcome and model separately; M1: model 1; M2: model 2. *Association investigated using the KORA F4 data in [15]; **Association investigated using the KORA F4 data in [25].

Abstract Background Evidence on type 2 diabetes onset age and duration on mortality risk has been limited by short follow‐up, inadequate control for confounding, missing repeated measurements, and inability to cover the full range of onset age, duration, and major causes of death. Moreover, scarce data dissect how type 2 diabetes onset age and duration shape life expectancy. Methods We evaluate prospectively these topics based on 270,075 eligible participants in the Nurses’ Health Studies and Health Professionals Follow‐up Study, leveraging repeated measurements throughout up to 40 years of follow‐up. Cox models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results In fully adjusted analyses, incident early onset type 2 diabetes (diagnosed <40 years of age) was associated with significantly higher mortality from all‐causes (HR, 95% CI was 3.16, 2.64–3.79; vs. individuals without type 2 diabetes), cardiovascular disease (6.56, 4.27–10.1), respiratory disease (3.43, 1.38–8.51), neurodegenerative disease (5.13, 2.09–12.6), and kidney disease (8.55, 1.98–36.9). The relative risk elevations declined dramatically with each higher decade of age at diagnosis for deaths from most of these causes, though the absolute risk difference increased continuously. A substantially higher cumulative incidence of mortality and a greater loss in life expectancy were associated with younger age at type 2 diabetes diagnosis. Longer disease duration was associated with generally higher relative and absolute risk of mortality. Conclusion Early onset of type 2 diabetes and longer disease duration are associated with substantially increased risk of all‐cause and cause‐specific mortality and greater loss in life expectancy.

Understanding the biological mechanisms behind multimorbidity patterns in adolescence is important as they may act as intermediary risk factor for long-term health. We aimed to explore relationship between prenatal exposures and adolescent's psycho-cardiometabolic intermediary traits mediated through epigenetic biomarkers, using structural equation modeling (SEM). We used data from mother-child dyads from pregnancy and adolescents at 16-17 years from two prospective cohorts: Northern Finland Birth Cohort 1986 (NFBC1986) and Raine Study from Australia. Factor analysis was applied to generate two different latent factor structures: (a) prenatal exposures and (b) adolescence psycho-cardiometabolic intermediary traits. Furthermore, three types of epigenetic biomarkers were included: (1) DNA methylation score for maternal smoking during pregnancy (DNAmMSS), (2) DNAm age estimate PhenoAge and (3) DNAm estimate for telomere length (DNAmTL). Similar factor structure was observed between both cohorts yielding three prenatal factors, namely BMI (Body Mass Index), SOP (Socio-Obstetric-Profile), and Lifestyle, and four adolescent factors: Anthropometric, Insulin-Triglycerides, Blood Pressure, and Mental health. In the SEM pathways, stronger direct effects of F1

A mid-infrared (mid-IR) label-free chemical sensor was developed using opto-nanofluidics consisting of a Si-liquid-Si slot-structure. A broadband mid-IR lightwave can be strongly confined within a nanofluidic capillary by utilizing the large refractive index contrast (Δn ~ 2) between the liquid core waveguide and the Si cladding. Through an optical-field enhancement together with a direct interaction between the probe light and the analyte, the sensitivity for chemical detection is increased by 50 times when compared to evanescent-wave sensing. This spectral characterization distinguished several common organic liquids (e.g., n-bromohexane, toluene, isopropanol) accurately, and could determine the ratio of chemical species (e.g., acetonitrile and ethanol) at low concentration (< 5 µL/mL) in a mixture through spectral scanning over their characteristic mid-IR absorption peaks. The combination of CMOS-compatible planar mid-IR microphotonics, and a high-throughput nanofluidic sensor system, provides a unique platform for chemical detection.