Role of human epicardial adipose tissue–derived miR-92a-3p in myocardial redox state

Background Visceral obesity is directly linked to increased cardiovascular risk, including heart failure. Objectives This study explored the ability of human epicardial adipose tissue (EAT)-derived microRNAs (miRNAs) to regulate the myocardial redox state and clinical outcomes. Methods This study screened for miRNAs expressed and released from human EAT and tested for correlations with the redox state in the adjacent myocardium in paired EAT/atrial biopsy specimens from patients undergoing cardiac surgery. Three miRNAs were then tested for causality in an in vitro model of cardiomyocytes. At a clinical level, causality/directionality were tested using genome-wide association screening, and the underlying mechanisms were explored using human biopsy specimens, as well as overexpression of the candidate miRNAs and their targets in vitro and in vivo using a transgenic mouse model. The final prognostic value of the discovered targets was tested in patients undergoing cardiac surgery, followed up for a median of 8 years. Results EAT miR-92a-3p was related to lower oxidative stress in human myocardium, a finding confirmed by using genetic regulators of miR-92a-3p in the human heart and EAT. miR-92a-3p reduced nicotinamide adenine dinucleotide phosphate (NADPH)-oxidase–derived superoxide (O2.–) by targeting myocardial expression of WNT5A, which regulated Rac1-dependent activation of NADPH oxidases. Finally, high miR-92a-3p levels in EAT were independently related with lower risk of adverse cardiovascular events. Conclusions EAT-derived miRNAs exert paracrine effects on the human heart. Indeed miR-92a-3p suppresses the wingless-type MMTV integration site family, member 5a/Rac1/NADPH oxidase axis and improves the myocardial redox state. EAT-derived miR-92a-3p is related to improved clinical outcomes and is a rational therapeutic target for the prevention and treatment of obesity-related heart disease

Pregnant and seeking asylum; exploring experiences ‘from booking to baby’

YesPregnant women seeking asylum in the UK may be particularly vulnerable with poor underlying health, more complex pregnancies and an increased risk of maternal and perinatal mortality. Studies have shown that some women seeking asylum have poor experiences of maternity care. This is despite the implementation of NICE guidelines to improve care for women with complex social factors. This article reports on a phenomenological study undertaken in West Yorkshire, aiming to explore the maternity care experiences of local pregnant asylum seeking women, to inform service development. Six women were interviewed over a three-month period. The findings focused more broadly on their experiences of living in the UK whilst being an asylum seeker and pregnant rather than focusing on maternity care, although this was included. Five key themes emerged: ‘pre-booking challenges’, ‘inappropriate accommodation’, ‘being pregnant and dispersed’, ‘being alone and pregnant’ and ‘not being asked or listened to’. These findings could be used as the basis for training midwives to understand how the difficulties women experience can impact on their health and social needs

EzArray: A web-based highly automated Affymetrix expression array data management and analysis system

<p>Abstract</p> <p>Background</p> <p>Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand.</p> <p>Results</p> <p>EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO) and allows instantaneous re-analysis of published array data.</p> <p>Conclusion</p> <p>EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from <url>http://www.ezarray.com/</url>.</p

Heterogeneity of pollen food allergy syndrome in seven Southern European countries: The @IT.2020 multicenter study

Background Pollen food allergy syndrome (PFAS) is a frequently underdiagnosed disease due to diverse triggers, clinical presentations, and test results. This is especially relevant in geographic areas with a broad spectrum of pollen sensitization, such as Southern Europe. Objectives To elucidate similarities and differences of PFAS in nine Southern European centers and identify associated characteristics and unique markers of PFAS. Methods As part of the @IT.2020 Multicenter Study, 815 patients with seasonal allergic rhinitis (SAR), aged 10-60 years, were recruited in seven countries. They completed questionnaires regarding SAR, comorbidities, family history, and PFAS, and underwent skin prick testing (SPT) and serum IgE testing. Results Of the 815 patients, 167 (20.5%) reported PFAS reactions. Most commonly, eliciting foods were kiwi (58, 34.7%), peach (43, 25.7%), and melon (26, 15.6%). Reported reactions were mostly local (216/319, 67.7%), occurring within 5 min of contact with elicitors (209/319, 65.5%). Associated characteristics included positive IgE to at least one panallergen (profilin, PR-10, or nsLTP) (p = 0.007), maternal PFAS (OR: 3.716, p = 0.026), and asthma (OR: 1.752, p = 0.073). Between centers, heterogeneity in prevalence (Marseille: 7.5% vs. Rome: 41.4%, p &lt; 0.001) and of clinical characteristics was apparent. Cypress played a limited role, with only 1/22 SPT mono-sensitized patients reporting a food reaction (p &lt; 0.073). Conclusions PFAS is a frequent comorbidity in Southern European SAR patients. Significant heterogeneity of clinical characteristics in PFAS patients among the centers was observed and may be related to the different pollen sensitization patterns in each geographic area. IgE to panallergen(s), maternal PFAS, and asthma could be PFAS-associated characteristics

The Annotation, Mapping, Expression and Network (AMEN) suite of tools for molecular systems biology

<p>Abstract</p> <p>Background</p> <p>High-throughput genome biological experiments yield large and multifaceted datasets that require flexible and user-friendly analysis tools to facilitate their interpretation by life scientists. Many solutions currently exist, but they are often limited to specific steps in the complex process of data management and analysis and some require extensive informatics skills to be installed and run efficiently.</p> <p>Results</p> <p>We developed the Annotation, Mapping, Expression and Network (AMEN) software as a stand-alone, unified suite of tools that enables biological and medical researchers with basic bioinformatics training to manage and explore genome annotation, chromosomal mapping, protein-protein interaction, expression profiling and proteomics data. The current version provides modules for (i) uploading and pre-processing data from microarray expression profiling experiments, (ii) detecting groups of significantly co-expressed genes, and (iii) searching for enrichment of functional annotations within those groups. Moreover, the user interface is designed to simultaneously visualize several types of data such as protein-protein interaction networks in conjunction with expression profiles and cellular co-localization patterns. We have successfully applied the program to interpret expression profiling data from budding yeast, rodents and human.</p> <p>Conclusion</p> <p>AMEN is an innovative solution for molecular systems biological data analysis freely available under the GNU license. The program is available via a website at the Sourceforge portal which includes a user guide with concrete examples, links to external databases and helpful comments to implement additional functionalities. We emphasize that AMEN will continue to be developed and maintained by our laboratory because it has proven to be extremely useful for our genome biological research program.</p

An unusual case of bacillary angiomatosis in the oral cavity of an AIDS patient who had no concomitant tegumentary lesions – case report and review

ABSTRACT Bacillary angiomatosis (BA) is an angioproliferative disease of immunocompromised patients that usually presents as vascular tumors in the skin and subcutaneous tissues. It is caused by chronic infections with either Bartonella henselae or B. quintana. Oral cavity BA is exceedingly rare and even rarer without simultaneous cutaneous disease. We report herein the case of a 51-year-old HIV-infected man who presented severe odynophagia and an eroded lesion on the hard palate that progressed to an oronasal fistula. No cutaneous lesions were recorded. Doxycycline led to complete resolution. To the best of our knowledge, only six previous cases of oral BA without tegumentary disease have been previously reported and none of them progressed to fistula

Validity, reliability, and responsiveness of daily monitoring visual analog scales in MASK-air®

Background: MASK-air® is an app that supports allergic rhinitis patients in disease control. Users register daily allergy symptoms and their impact on activities using visual analog scales (VASs). We aimed to assess the concurrent validity, reliability, and responsiveness of these daily VASs. Methods: Daily monitoring VAS data were assessed in MASK-air® users with allergic rhinitis. Concurrent validity was assessed by correlating daily VAS values with those of the EuroQol-5 Dimensions (EQ-5D) VAS, the Control of Allergic Rhinitis and Asthma Test (CARAT) score, and the Work Productivity and Activity Impairment Allergic Specific (WPAI-AS) Questionnaire (work and activity impairment scores). Intra-rater reliability was assessed in users providing multiple daily VASs within the same day. Test–retest reliability was tested in clinically stable users, as defined by the EQ-5D VAS, CARAT, or “VAS Work” (i.e., VAS assessing the impact of allergy on work). Responsiveness was determined in users with two consecutive measurements of EQ-5D-VAS or “VAS Work” indicating clinical change. Results: A total of 17,780 MASK-air® users, with 317,176 VAS days, were assessed. Concurrent validity was moderate–high (Spearman correlation coefficient range: 0.437–0.716). Intra-rater reliability intraclass correlation coefficients (ICCs) ranged between 0.870 (VAS assessing global allergy symptoms) and 0.937 (VAS assessing allergy symptoms on sleep). Test–retest reliability ICCs ranged between 0.604 and 0.878—“VAS Work” and “VAS asthma” presented the highest ICCs. Moderate/large responsiveness effect sizes were observed—the sleep VAS was associated with lower responsiveness, while the global allergy symptoms VAS demonstrated higher responsiveness. Conclusion: In MASK-air®, daily monitoring VASs have high intra-rater reliability and moderate–high validity, reliability, and responsiveness, pointing to a reliable measure of symptom loads

Insomnia and its correlates in a representative sample of the Greek population

<p>Abstract</p> <p>Background</p> <p>Insomnia is a major public health concern affecting about 10% of the general population in its chronic form. Furthermore, epidemiological surveys demonstrate that poor sleep and sleep dissatisfaction are even more frequent problems (10-48%) in the community. This is the first report on the prevalence of insomnia in Greece, a southeastern European country which differs in several socio-cultural and climatic aspects from the rest of European Community members. Data obtained from a national household survey (n = 1005) were used to assess the relationship between insomnia symptoms and a variety of sociodemographic variables, life habits, and health-related factors.</p> <p>Methods</p> <p>A self-administered questionnaire with questions pertaining to general health and related issues was given to the participants. The Short Form-36 (Mental Health subscale), the Athens Insomnia Scale (AIS) as a measure of insomnia-related symptoms, and the International Physical Activity Questionnaire (IPAQ) were also used for the assessment.</p> <p>Results</p> <p>The prevalence of insomnia in the total sample was 25.3% (n = 254); insomnia was more frequent in women than men (30.7% vs. 19.5%) and increased with age. Multiple regression analysis revealed a significant association of insomnia with low socio-economical status and educational level, physical inactivity, existence of a chronic physical or mental disease and increased number of hospitalizations in the previous year.</p> <p>Conclusions</p> <p>The present study confirms most findings reported from other developed countries around the world regarding the high prevalence of insomnia problems in the general population and their association with several sociodemographic and health-related predisposing factors. These results further indicate the need for more active interventions on the part of physicians who should suspect and specifically ask about such symptoms.</p

Treatment of allergic rhinitis during and outside the pollen season using mobile technology. A MASK study

Background: The analysis of mobile health (mHealth) data has generated innovative insights into improving allergic rhinitis control, but additive information is needed. A cross-sectional real-world observational study was undertaken in 17 European countries during and outside the estimated pollen season. The aim was to collect novel information including the phenotypic characteristics of the users. Methods: The Allergy Diary–MASK-air–mobile phone app, freely available via Google Play and App, was used to collect the data of daily visual analogue scales (VASs) for overall allergic symptoms and medication use. Fluticasone Furoate (FF), Mometasone Furoate (MF), Azelastine Fluticasone Proprionate combination (MPAzeFlu) and eight oral H1-antihistamines were studied. Phenotypic characteristics were recorded at entry. The ARIA severity score was derived from entry data. This was an a priori planned analysis. Results: 9037 users filled in 70,286 days of VAS in 2016, 2017 and 2018. The ARIA severity score was lower outside than during the pollen season. Severity was similar for all treatment groups during the pollen season, and lower in the MPAzeFlu group outside the pollen season. Days with MPAzeFlu had lower VAS levels and a higher frequency of monotherapy than the other treatments during the season. Outside the season, days with MPAzeFlu also had a higher frequency of monotherapy. The number of reported days was significantly higher with MPAzeFlu during and outside the season than with MF, FF or oral H1-antihistamines. Conclusions: This study shows that the overall efficacy of treatments is similar during and outside the pollen season and indicates that medications are similarly effective during the year

Unsupervised assessment of microarray data quality using a Gaussian mixture model

<p>Abstract</p> <p>Background</p> <p>Quality assessment of microarray data is an important and often challenging aspect of gene expression analysis. This task frequently involves the examination of a variety of summary statistics and diagnostic plots. The interpretation of these diagnostics is often subjective, and generally requires careful expert scrutiny.</p> <p>Results</p> <p>We show how an unsupervised classification technique based on the Expectation-Maximization (EM) algorithm and the naïve Bayes model can be used to automate microarray quality assessment. The method is flexible and can be easily adapted to accommodate alternate quality statistics and platforms. We evaluate our approach using Affymetrix 3' gene expression and exon arrays and compare the performance of this method to a similar supervised approach.</p> <p>Conclusion</p> <p>This research illustrates the efficacy of an unsupervised classification approach for the purpose of automated microarray data quality assessment. Since our approach requires only unannotated training data, it is easy to customize and to keep up-to-date as technology evolves. In contrast to other "black box" classification systems, this method also allows for intuitive explanations.</p