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ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTToward orthogonal self-assembly of redox active molecules on platinum and gold: selective reaction of disulfide with gold and isocyanide with platinumJames J. Hickman, Paul E. Laibinis, David I. Auerbach, Chaofeng Zou, Timothy J. Gardner, George M. Whitesides, and Mark S. WrightonCite this: Langmuir 1992, 8, 2, 357–359Publication Date (Print):February 1, 1992Publication History Published online1 May 2002Published inissue 1 February 1992https://pubs.acs.org/doi/10.1021/la00038a005https://doi.org/10.1021/la00038a005research-articleACS PublicationsRequest reuse permissionsArticle Views786Altmetric-Citations128LEARN 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-Alertsclose Get e-Alerts

Population subgrouping has been suggested as means to improve coronary heart disease (CHD) risk assessment. We explored here how unsupervised data-driven metabolic subgrouping, based on comprehensive lipoprotein subclass data, would work in large-scale population cohorts.We applied a self-organizing map (SOM) artificial intelligence methodology to define subgroups based on detailed lipoprotein profiles in a population-based cohort (n = 5789) and utilised the trained SOM in an independent cohort (n = 7607). We identified four SOM-based subgroups of individuals with distinct lipoprotein profiles and CHD risk and compared those to univariate subgrouping by apolipoprotein B quartiles.The SOM-based subgroup with highest concentrations for non-HDL measures had the highest, and the subgroup with lowest concentrations, the lowest risk for CHD. However, apolipoprotein B quartiles produced better resolution of risk than the SOM-based subgroups and also striking dose-response behaviour.These results suggest that the majority of lipoprotein-mediated CHD risk is explained by apolipoprotein B-containing lipoprotein particles. Therefore, even advanced multivariate subgrouping, with comprehensive data on lipoprotein metabolism, may not advance CHD risk assessment.

Background Thromboelostograms (TEG) are indicators that reflect the dynamic changes in blood coagulation objectively. Compared with traditional coagulation tests, TEG are easy to perform; imparting a head start in determining patients’coagulation status. The aim of this study was to explore the role of thromboelastography as an early predictor of disease severity and as a prognostic factor in patients with haemorrhagic fever of renal syndrome (HFRS). Methods This was a retrospective study in which we collected clinical data from 342 patients with HFRS who were hospitalized from January 2017 to January 2021. The predictive value of laboratory parameters for HFRS criticalization was assessed via receiver operating characteristic (ROC) curves. After that, a model of criticalization was developed using stepwise analysis, subsequently, the model was evaluated and validated internally as well as externally. This study was approved by the Ethics Committee of the Hospital. Results The study population was categorized into critical and noncritical groups according to their condition during hospitalization, with a median age of 52.00 (39.00–61.50) years for the critical group and 39.00 (16.00–53.25) years for the noncritical group. Both groups had a large proportion of male patients (65.3% and 72.3%, respectively). The median duration of hospitalization was 15.00 (3.50–25.00) days in the critical group and 13.00 (10.00–17.25) days in noncritical group. In the critical group 40.8% of patients died. The incidence of bleeding was greater in critical patients (51.0%) than in noncritical patients (15.1%). The coagulation indices: CI, K, MA, R and angle were significantly different between the two groups (p < 0.05). Critical patients had higher levels of K and R and lower levels of CI, MA and angle. Multivariate analysis revealed that K, ALB, CK, SCR, angle, WBC and LYM were independently associated with disease severity in patients with HFRS. ROC curve analysis revealed that the criticality model equation had an AUC of 0.9058, a sensitivity of 88.9% and a specificity of 80.2%, which were better than that of any single parameter in predicting the patient’s outcome. The internal validation C index was 0.866, the GOF P value was 0.825, and the external validation AUC was 0.762, with a sensitivity of 71.4% and a specificity of 74.2%. The results of the calibration plots indicated that there was some agreement between the model-estimated HFRS critical illness rates and the final observed critical illness rates in the study population. Decision curve analysis indicated that the model had significant clinical utility and comparable net benefit over a range of threshold probabilities. Conclusion Critical HFRS have significantly abnormal coagulation function and high incidence of bleeding associated with poor outcome. A criticalization prediction model constructed on the basis of thromboelastography indices in early stages of the disease has a good predictive ability and may be helpful in the early identification of critically ill patients for timely clinical intervention and treatment.

Abstract Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed with different criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1 ), and provide replication of 11 previously reported loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease indicate shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. Only one locus differed in its association by diagnostic criteria, otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or Rotterdam criteria across common variants at 13 loci.

Abstract A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analysing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. We introduce metaCCA , a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness. Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA , using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Code is available at https://github.com/aalto-ics-kepaco .

A new physical model based on mesoscale self-assembly is developed to simulate indentation fracture in crystalline materials. Millimeter-scale hexagonal objects exhibiting atom-like potential functions were designed and allowed to self-assemble into two-dimensional (2D) aggregates at the interface between water and perfluorodecalin. Indentation experiments were performed on these aggregates, and the stresses and strains involved in these processes were evaluated. The stress field in the aggregates was analyzed theoretically using the 2D elastic Hertz solution. Comparison of the experimental results with theoretical analysis revealed that fracture develops in regions subjected to high shear stress and some, albeit low, tensile stress. The potential for the broader application of the model is illustrated using indentation of assemblies with point defects and adatoms introduced at predetermined locations, and using a two-phase aggregate simulating a compliant film on a stiff substrate.

Attention-deficit/hyperactivity disorder (ADHD) is a childhood-onset neurodevelopmental disorder with a significant public-health impact. Previously, we described a candidate gene study in a population-based birth cohort that demonstrated an association with ADHD-affected males and the dopamine receptor D2 (DRD2). The current study evaluates potential associations of dopamine receptor genes and Cloninger temperament traits within this same sample. Participants with stringent lifetime ADHD diagnoses were ascertained systematically from the genetically isolated Northern Finland 1986 Birth Cohort (n=9432), resulting in 178 cases and 157 controls. Markers in all known dopamine receptor genes were genotyped. We report an association of DRD2 with low Persistence in females (rs1079727 P=0.02, rs1124491 P=0.02, rs1800497 P=0.03). The associated DRD2 minor allelic haplotype (CAA, P=0.03) is the same haplotype we previously associated with ADHD in males in this birth cohort. The current study further supports previous results on the role of DRD2 in individuals with ADHD. Investigations suggest that DRD2 may have an impact on both males and females, but the particular outcome appears sex-specific, manifesting as ADHD in males and low Persistence in females. Furthermore, these findings suggest that the putative role of low Persistence as an endophenotype for ADHD deserves further investigation.

Curved-sided hexagrams with multiple equilibrium states have great potential in engineering applications such as foldable architectures, deployable aerospace structures, and shape-morphing soft robots. In Part I, the classical stability criterion based on energy variation was used to study the elastic stability of the curved-sided hexagram and identify the natural curvature range for stability of each state for circular and rectangular rod cross-sections. Here, we combine a multi-segment Kirchhoff rod model, finite element simulations, and experiments to investigate the transitions between four basic equilibrium states of the curved-sided hexagram. The four equilibrium states, namely the star hexagram, the daisy hexagram, the 3-loop line, and the 3-loop "8", carry uniform bending moments in their initial states, and the magnitudes of these moments depend on the natural curvatures and their initial curvatures. Transitions between these equilibrium states are triggered by applying bending loads at their corners or edges. It is found that transitions between the stable equilibrium states of the curved-sided hexagram are influenced by both the natural curvature and the loading position. Within a specific natural curvature range, the star hexagram, the daisy hexagram, and the 3-loop "8" can transform among one another by bending at different positions. Based on these findings, we identify the natural curvature range and loading conditions to achieve transition among these three equilibrium states plus a folded 3-loop line state for one specific ring having a rectangular cross-section. The results obtained in this part also validate the elastic stability range of the four equilibrium states of the curved-sided hexagram in Part I. We envision that the present work could provide a new perspective for the design of multi-functional deployable and foldable structures.