Fatal Intracranial Hemorrhage Occurring after Oral Anticoagulant Treatment Initiation for Secondary Stroke Prevention in Patients with Atrial Fibrillation

BACKGROUND AND PURPOSE: In this pooled analysis of 7 multicenter cohorts we investigated potential differences in the incidence, characteristics and outcomes between intracranial hemorrhages (ICHs) associated with the use of non-vitamin K oral anticoagulants (NOAC-ICH) or vitamin K antagonists (VKA-ICH) in ischemic stroke (IS) patients after oral anticoagulant treatment initiation for atrial fibrillation (AF). METHODS: We included data from 4.912 eligible AF patients who were admitted in a stroke unit with IS or transient ischemic attack (TIA) and who were treated with either VKAs or NOACs within 3 months post-stroke. Fatal ICH was defined as death occurring during the first 30-days after ICH onset. We additionally performed a meta-analysis of available observational studies reporting 30-day mortality rates from NOAC-ICH or VKA-ICH onset. RESULTS: During 5970 patient-years of follow-up 71 participants had an ICH, of whom 20 were NOAC-ICH and 51 VKA-ICH. Patients in the two groups had comparable baseline characteristics, except for the higher prevalence of kidney disease in VKA-ICH patients. There was a non-significant higher number of fatal ICH in patients with VKA (11 events per 3,385 patient-years) than in those with NOAC (3 events per 2,623 patient-years; HR=0.32,95%CI:0.09-1.14). Three-month functional outcomes were similar (p>0.2) in the two groups. The meta-analysis showed a lower 30-day mortality risk for patients with NOAC-ICH compared to VKA-ICH (RR=0.70,95%CI:0.51-0.95). CONCLUSIONS: NOAC-ICH and VKA-ICH occurring during secondary stroke prevention of AF patients have comparable baseline characteristics and outcomes, except for the risk of fatal ICH within 30 days, which might be greater in VKA-ICH

Algebraic Comparison of Partial Lists in Bioinformatics

The outcome of a functional genomics pipeline is usually a partial list of genomic features, ranked by their relevance in modelling biological phenotype in terms of a classification or regression model. Due to resampling protocols or just within a meta-analysis comparison, instead of one list it is often the case that sets of alternative feature lists (possibly of different lengths) are obtained. Here we introduce a method, based on the algebraic theory of symmetric groups, for studying the variability between lists ("list stability") in the case of lists of unequal length. We provide algorithms evaluating stability for lists embedded in the full feature set or just limited to the features occurring in the partial lists. The method is demonstrated first on synthetic data in a gene filtering task and then for finding gene profiles on a recent prostate cancer dataset

Micro-computed tomography (μ-CT) as a potential tool to assess the effect of dynamic coating routes on the formation of biomimetic apatite layers on 3D-plotted biodegradable polymeric scaffolds

This work studies the influence of dynamic biomimetic coating procedures on the growth of bonelike apatite layers at the surface of starch/polycaprolactone (SPCL) scaffolds produced by a 3D-plotting technology. These systems are newly proposed for bone Tissue Engineering applications. After generating stable apatite layers through a sodium silicate-based biomimetic methodology the scaffolds were immersed in Simulated Body Fluid solutions (SBF) under static, agitation and circulating flow perfusion conditions, for different time periods. Besides the typical characterization techniques, Micro-Computed Tomography analysis (μ-CT) was used to assess scaffold porosity and as a new tool for mapping apatite content. 2D histomorphometric analysis was performed and 3D virtual models were created using specific softwares for CT reconstruction. By the proposed biomimetic routes apatite layers were produced covering the interior of the scaffolds, without compromising their overall morphology and interconnectivity. Dynamic conditions allowed for the production of thicker apatite layers as consequence of higher mineralizing rates, when comparing with static conditions. μ-CT analysis clearly demonstrated that flow perfusion was the most effective condition in order to obtain well-defined apatite layers in the inner parts of the scaffolds. Together with SEM, this technique was a useful complementary tool for assessing the apatite content in a non-destructive way

A study of some fundamental physicochemical variables on the morphology of mesoporous silica nanoparticles MCM-41 type

[EN] All variables affecting the morphology of mesoporous silica nanoparticles (MSN) should be carefully analyzed in order to truly tailored design their mesoporous structure according to their final use. Although complete control on MCM-41 synthesis has been already claimed, reproducibility and repeatability of results remain a big issue due to the lack of information reported in literature. Stirring rate, reaction volume, and system configuration (i.e., opened or closed reactor) are three variables that are usually omitted, making the comparison of product characteristics difficult. Specifically, the rate of solvent evaporation is seldom disclosed, and its influence has not been previously analyzed. These variables were systematically studied in this work, and they were proven to have a fundamental impact on final particle morphology. Hence, a high degree of circularity (C = 0.97) and monodispersed particle size distributions were only achieved when a stirring speed of 500 rpm and a reaction scale of 500 mL were used in a partially opened system, for a 2 h reaction at 80 degrees C. Well-shaped spherical mesoporous silica nanoparticles with a diameter of 95 nm, a pore size of 2.8 nm, and a total surface area of 954 m(2) g(-1) were obtained. Final characteristics made this product suitable to be used in biomedicine and nanopharmaceutics, especially for the design of drug delivery systems.This study was funded partially by Departamento Administrativo de Ciencia Tecnología e Innovación–COLCIENCIAS (recipient, Angela A. Beltrán-Osuna); Ministerio de Economía y Competitividad, MINECO, research number MAT2016-76039-C4-1-R (Recipient, José L. Gómez-Ribelles); and Universidad Nacional de Colombia, grant number DIB201010021438 (Recipient, Jairo E. Perilla).Beltrán-Osuna, A.; Gómez Ribelles, JL.; Perilla-Perilla, JE. (2017). 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Adsorption at cell surface and cellular uptake of silica nanoparticles with different surface chemical functionalizations: impact on cytotoxicity

International audienceSilica nanoparticles are particularly interesting for medical applications because of the high inertness and chemical stability of silica material. However, at the nanoscale their innocuousness must be carefully verified before clinical use. The aim of this study was to investigate the in vitro biological toxicity of silica nanoparticles depending on their surface chemical functionalization. To that purpose, three kinds of 50 nm fluorescent silica-based nanoparticles were synthesized: 1) sterically stabilized silica nanoparticles coated with neutral polyethylene glycol (PEG) molecules, 2) positively charged silica nanoparticles coated with amine groups and 3) negatively charged silica nanoparticles coated with carboxylic acid groups. RAW 264.7 murine macrophages were incubated for 20 hours with each kind of nanoparticles. Their cellular uptake and adsorption at the cell membrane were assessed by a fluorimetric assay and cellular responses were evaluated in terms of cytotoxicity, pro-inflammatory factor production and oxidative stress. Results showed that the highly positive charged nanoparticle, were the most adsorbed at cell surface and triggered more cytotoxicity than other nanoparticles types. To conclude, this study clearly demonstrated that silica nanoparticles surface functionalization represents a key parameter in their cellular uptake and biological toxicity

Low Prevalence of Chlamydia trachomatis Infection in Non-Urban Pregnant Women in Vellore, S. India

Objective: To determine the prevalence and risk factors for Chlamydia trachomatis (CT) infection in pregnant women and the rate of transmission of CT to infants. Methods: Pregnant women ($28 weeks gestation) in Vellore, South India were approached for enrollment from April 2009 to January 2010. After informed consent was obtained, women completed a socio-demographic, prenatal, and sexual history questionnaire. Endocervical samples collected at delivery were examined for CT by a rapid enzyme test and nucleic acid amplification test (NAAT). Neonatal nasopharyngeal and conjunctival swabs were collected for NAAT testing. Results: Overall, 1198 women were enrolled and 799 (67%) endocervical samples were collected at birth. Analyses were completed on 784 participants with available rapid and NAAT results. The mean age of women was 25.8 years (range 18– 39 yrs) and 22 % (95 % CI: 19.7–24.4%) were primigravida. All women enrolled were married; one reported.one sexual partner; and six reported prior STI. We found 71 positive rapid CT tests and 1/784 (0.1%; 95 % CI: 0–0.38%) true positive CT infection using NAAT. Conclusions: To our knowledge, this is the largest study on CT prevalence amongst healthy pregnant mothers in southern India, and it documents a very low prevalence with NAAT. Many false positive results were noted using the rapid test. Thes

DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines

BACKGROUND: DNA methylation is an essential epigenetic mechanism involved in gene regulation and disease, but little is known about the mechanisms underlying inter-individual variation in methylation profiles. Here we measured methylation levels at 22,290 CpG dinucleotides in lymphoblastoid cell lines from 77 HapMap Yoruba individuals, for which genome-wide gene expression and genotype data were also available. RESULTS: Association analyses of methylation levels with more than three million common single nucleotide polymorphisms (SNPs) identified 180 CpG-sites in 173 genes that were associated with nearby SNPs (putatively in cis, usually within 5 kb) at a false discovery rate of 10%. The most intriguing trans signal was obtained for SNP rs10876043 in the disco-interacting protein 2 homolog B gene (DIP2B, previously postulated to play a role in DNA methylation), that had a genome-wide significant association with the first principal component of patterns of methylation; however, we found only modest signal of trans-acting associations overall. As expected, we found significant negative correlations between promoter methylation and gene expression levels measured by RNA-sequencing across genes. Finally, there was a significant overlap of SNPs that were associated with both methylation and gene expression levels. CONCLUSIONS: Our results demonstrate a strong genetic component to inter-individual variation in DNA methylation profiles. Furthermore, there was an enrichment of SNPs that affect both methylation and gene expression, providing evidence for shared mechanisms in a fraction of genes

Detection of copy number variation from array intensity and sequencing read depth using a stepwise Bayesian model

Abstract Background Copy number variants (CNVs) have been demonstrated to occur at a high frequency and are now widely believed to make a significant contribution to the phenotypic variation in human populations. Array-based comparative genomic hybridization (array-CGH) and newly developed read-depth approach through ultrahigh throughput genomic sequencing both provide rapid, robust, and comprehensive methods to identify CNVs on a whole-genome scale. Results We developed a Bayesian statistical analysis algorithm for the detection of CNVs from both types of genomic data. The algorithm can analyze such data obtained from PCR-based bacterial artificial chromosome arrays, high-density oligonucleotide arrays, and more recently developed high-throughput DNA sequencing. Treating parameters--e.g., the number of CNVs, the position of each CNV, and the data noise level--that define the underlying data generating process as random variables, our approach derives the posterior distribution of the genomic CNV structure given the observed data. Sampling from the posterior distribution using a Markov chain Monte Carlo method, we get not only best estimates for these unknown parameters but also Bayesian credible intervals for the estimates. We illustrate the characteristics of our algorithm by applying it to both synthetic and experimental data sets in comparison to other segmentation algorithms. Conclusions In particular, the synthetic data comparison shows that our method is more sensitive than other approaches at low false positive rates. Furthermore, given its Bayesian origin, our method can also be seen as a technique to refine CNVs identified by fast point-estimate methods and also as a framework to integrate array-CGH and sequencing data with other CNV-related biological knowledge, all through informative priors.</p