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Background— Circulating microRNAs ( miRNAs) are emerging as novel disease biomarkers. We aimed to explore the association between circulating miRNAs and the occurrence of acute myocardial infarction (AMI) in Chinese populations. Methods and Results— In the discovery stage, the plasma of 20 patients with AMI and 20 controls were pooled respectively and profiled by massively parallel sequencing. Seventy-seven miRNAs showed differential expression. Selected miRNAs were validated in 178 patients with AMI and 198 controls using quantitative reverse transcriptase polymerase chain reaction assays and further replicated in 150 patients with AMI and 150 controls. Results suggest that miR-320b and miR-125b levels were significantly lower in patients with AMI than in controls in both validation populations ( P <0.0001). Lower levels of miR-320b and miR-125b were associated with increased occurrence of AMI (adjusted odds ratio, 4.71; 95% confidence interval, 2.96–7.48 and odds ratio, 4.27; 95% confidence interval, 2.84–6.41, respectively). Addition of the 2 miRNAs to traditional risk factors led to a significant improvement in the area under the curve from 0.822 (95% confidence interval, 0.787–0.856) to 0.871 (95% confidence interval, 0.842–0.900), with a net reclassification improvement of 20.45% ( P <0.0001) and an integrated discrimination improvement of 0.16 ( P <0.0001) for patients with AMI. A functional study showed that miR-320b and miR-125b could regulate the expression profiles of genes enriched in several signal transduction pathways critical for coronary heart disease in human vascular endothelial cells. Conclusions— The plasma levels of miR-320b and miR-125b were significantly lower in patients with AMI when compared with controls, and these miRNAs may be involved in the pathogenesis of coronary heart disease.

During migration, asymmetrically polarized cells achieve motion by coordinating the protrusion and retraction of their leading and trailing edges, respectively. Although it is well known that local changes in the dynamics of actin cytoskeleton remodeling drive these processes, neither the cytoskeletal rheological properties of these migrating cells are well quantified nor is it understand how these rheological properties are regulated by underlying molecular processes. In this report, we have used soft lithography to create morphologically polarized cells in order to examine rheological differences between the front and rear zone of an NIH 3T3 cell posed for migration. In addition, we trapped superparamagnetic beads with optical tweezers and precisely placed them at specific locations on the immobilized cells. The beads were then allowed to endocytose overnight before magnetic tweezers experiments were performed to measure the local rheological properties of the leading and trailing edges. Our results indicate that the leading edge has an approximately 1.9 times higher shear modulus than the trailing edge and that this increase in shear modulus correlates with a greater density of filamentous actin, as measured by phalloidin-staining observed through quantitative 3D microscopy.

Objectives: To examine whether healthy lifestyle practices, which are primary prevention measures against major age-related chronic diseases, are associated with longer telomere length. Design: Cross-sectional study. Setting: The Nurses' Health Study, United States. Participants: The population of analysis consisted of 3,355 women who were free of cancer, diabetes, and cardiovascular disease at blood draw in 1990 and were selected as controls in multiple prospective case-control studies within the Nurses' Health Study cohort. Using self-administered questionnaires, these participants provided detailed information on lifestyle practices and dietary habits in 1988 or 1990. Main outcome measures: Z scores of leukocyte telomere length were derived among controls in each case-control study. We defined low-risk categories for five major modifiable factors: non-current smoking, maintaining a healthy body weight (18.5 kg/m2 ≤ body mass index < 24.9 kg/m2), engaging in regular moderate or vigorous physical activities (≥150 minutes/week), drinking alcohol in moderation (1 drink/week to <2 drinks/day), and eating a healthy diet (Alternate Healthy Eating Index score in top 50%). We calculated difference (%) of the z scores contrasting low-risk groups with reference groups to evaluate the association of interest. Results: Although none of the individual low-risk factors was significantly associated with longer leukocyte telomere length z scores, we observed a significant, monotonic relationship between the number of low-risk factors and the z scores. In comparison with women who had no low-risk factors, the leukocyte telomere length z scores were 15.4%, 21.8%, 23.3%, 24.5%, and 33.1% (P for trend = 0.04) higher for women who had 1 to 5 low-risk factors, respectively. Conclusion: Adherence to a healthy lifestyle defined by major modifiable factors may attenuate age-related declines in telomere length.

High-throughput technology for molecular biomarkers is increasingly producing multivariate phenotype data exhibiting strong correlation structures. Existing approaches for combining such data with genetic variants for multivariate Quantitative Trait Loci analysis generally either ignore correlation structure or make other restrictive assumptions about the associations between phenotypes and genetic loci. We present a Bayesian Variable Selection (BVS) model with sparse variable and covariance selection for high-dimensional seemingly unrelated regressions. The model includes a matrix of binary variable selection indicators for multivariate regression, thus allowing different phenotype responses to be associated with different genetic predictors (a seemingly unrelated regressions framework). A general covariance structure is allowed for the residuals relating to the conditional dependencies between phenotype variables. The covariance structure may be dense (unrestricted) or sparse, with a graphical modelling prior. The graphical structure amongst the multivariate responses can be estimated as part of the model. To achieve feasible computation of the large and complex model space, we exploit a factorisation of the covariance matrix parameter to enable faster computation using Markov Chain Monte Carlo (MCMC) methods. We are able to infer associations with thousands of candidate predictors multivariately on hundreds of responses. We illustrate the model using a dataset of 158 NMR spectroscopy measured metabolites and over 9000 Single Nucleotide Polymorphisms on chromosome 16, measured in a cohort of more than 5000 people.

This paper describes the patterning of poly(ethylene imine) (PEI) on a surface into structures having submicron edge resolution. This procedure consists of three steps: (1) formation of a reactive self-assembled monolayer (SAM) terminating in interchain carboxylic anhydride groups on gold and silver; (2) patterning of this SAM by microcontact printing (μCP) using a poly(dimethylsiloxane) (PDMS) stamp inked with PEI (this polymer contains primary and secondary amines that are reactive toward the anhydride groups); (3) hydrolysis of the unreacted anhydride groups with base and removal of noncovalently bound PEI. The patterned thin films of PEI are attached covalently to the SAM by amide bonds. The pendant, unreacted primary and secondary amines of the attached PEI can be used as reactive nucleophilic groups in further steps of chemical modification. This type of postmodification has been illustrated by allowing the amine groups of the covalently attached PEI to react with perfluorooctanoyl chloride, palmitoyl chloride, palmitic anhydride, and poly(styrene-alt-maleic anhydride). The PEI films and their derivatives were characterized using atomic force microscopy (AFM), scanning electron microscopy (SEM), polarized infrared external reflectance spectroscopy (PIERS), contact angles of water, and X-ray photoelectron spectroscopy (XPS).

Abstract Metabolomic age models have been proposed for the study of biological aging, however, they have not been widely validated. We aimed to assess the performance of newly developed and existing nuclear magnetic resonance spectroscopy (NMR) metabolomic age models for prediction of chronological age (CA), mortality, and age‐related disease. Ninety‐eight metabolic variables were measured in blood from nine UK and Finnish cohort studies ( N ≈31,000 individuals, age range 24–86 years). We used nonlinear and penalized regression to model CA and time to all‐cause mortality. We examined associations of four new and two previously published metabolomic age models, with aging risk factors and phenotypes. Within the UK Biobank ( N ≈102,000), we tested prediction of CA, incident disease (cardiovascular disease (CVD), type‐2 diabetes mellitus, cancer, dementia, and chronic obstructive pulmonary disease), and all‐cause mortality. Seven‐fold cross‐validated Pearson's r between metabolomic age models and CA ranged between 0.47 and 0.65 in the training cohort set (mean absolute error: 8–9 years). Metabolomic age models, adjusted for CA, were associated with C‐reactive protein, and inversely associated with glomerular filtration rate. Positively associated risk factors included obesity, diabetes, smoking, and physical inactivity. In UK Biobank, correlations of metabolomic age with CA were modest ( r = 0.29–0.33), yet all metabolomic model scores predicted mortality (hazard ratios of 1.01 to 1.06/metabolomic age year) and CVD, after adjustment for CA. While metabolomic age models were only moderately associated with CA in an independent population, they provided additional prediction of morbidity and mortality over CA itself, suggesting their wider applicability.

Abstract Background Psychoses, especially schizophrenia, are often preceded by cognitive deficits and psychosis risk states. Altered metabolic profiles have been found in schizophrenia. However, the associations between metabolic profiles and poorer cognitive performance and psychosis risk in the population remain to be determined. Methods Detailed molecular profiles were measured for up to 8976 individuals from two general population-based prospective birth cohorts: the Northern Finland Birth Cohort 1986 (NFBC 1986) and the Avon Longitudinal Study of Parents and Children (ALSPAC). A high-throughput nuclear magnetic resonance spectroscopy platform was used to quantify 70 metabolic measures at age 15–16 years in the NFBC 1986 and at ages 15 and 17 years in ALSPAC. Psychosis risk was assessed using the PROD-screen questionnaire at age 15–16 years in the NFBC 1986 or the psychotic-like symptoms assessment at age 17 years in ALSPAC. Cognitive measures included academic performance at age 16 years in both cohorts and general intelligence and executive function in ALSPAC. Logistic regression measured cross-sectional and longitudinal associations between metabolic measures and psychosis risk and cognitive performance, controlling for important covariates. Results Seven metabolic measures, primarily fatty acid (FA) measures, showed cross-sectional associations with general cognitive performance, four across both cohorts (low density lipoprotein diameter, monounsaturated FA ratio, omega-3 ratio and docosahexaenoic acid ratio), even after controlling for important mental and physical health covariates. Psychosis risk showed minimal metabolic associations. Conclusions FA ratios may be important in marking risk for cognitive deficits in adolescence. Further research is needed to clarify whether these biomarkers could be causal and thereby possible targets for intervention.

Abstract Background and Aims Prenatal exposure to maternal cigarette smoking ( PEMCS ) is associated with a higher probability of substance use in adolescence. We explore if externalizing behavior mediates this relationship, while controlling for a number of potential covariates of this mediation process. Methods We used data obtained in two geographically distinct community samples of adolescents. The first (cross‐sectional) sample consisted of 996 adolescents (12–18 years of age) recruited from the S aguenay Y outh S tudy ( SYS ) in C anada (47% with PEMCS ). The second (longitudinal) sample consisted of 1141 adolescents (49% with PEMCS ) from the N orthern F inland B irth C ohort ( NFBC 1986). In both samples, externalizing behavior and substance use were assessed during adolescence. In the NFBC 1986 cohort, externalizing behavior was also assessed in childhood. Results In both populations, PEMCS is associated with a higher likelihood of adolescent drug experimentation. In the NFBC 1986 cohort, exposed (versus non‐exposed) adolescents experiment with an extra 1.27 [B = 0.24, 95% confidence intervals (CI) = 0.15, 0.33 P < 0.001] drugs. In the SYS cohort, a clear protective effect of not being exposed is shown: non‐exposed (versus exposed) adolescents are 1.5 times [B = −0.42, 95% CI = −0.75, −0.09, P = 0.013] less likely to take drugs. These associations between PEMCS and drug experimentation remain in the multivariate and mediational analyses. Conclusions Prenatal exposure to maternal cigarette smoking appears to be associated with a higher probability of experimenting with drugs during adolescence, both directly and indirectly via externalizing behavior and the number of peers reported as using drugs.