Syncope in a Population-Based Sample of Elderly Persons: Prevalence, Predisposing Risk Factors, and Precipitating Events

Syncope is a serious but potentially preventable occurrence commonly afflicting the elderly population. The objectives of this study were to estimate the incidence of syncope in the community-dwelling elderly population, to identify the clinical risk factors that predispose some elderly persons to syncope, and to describe situational factors and the morbidity associated with syncope. Study participants were members of the Project Safety cohort, representing a probability sample of non-institutionalized residents of New Haven, Connecticut aged 72 years or older. Age-restricted housing lists and utilities listings were used to generate an index of community dwellings from which 5,936 households were identified. Baseline interviews identified 1,436 eligible persons. From this group, 1,103 people were followed for a syncopal episode for a two year period. Syncope occurred in 6.3% of the subjects over the two year period. Many diverse baseline characteristics were associated with an increased risk for syncope including the presence of several chronic conditions, a history of syncope or dizziness, the use of certain medications, and impaired functional status. Clinical risk factors independently associated with syncope included a history of dizziness when rising from the sitting position (adjusted odds ratio 3.1; 95% confidence interval 1.6, 6.1), a history of syncope in past year (2.4; 1.1, 5.2), the use of glycosides, nitrates and/or calcium channel blockers (2.2; 1.3, 3.7), slow gait speed (1.5; 0.9, 2.7), and age \u3e78 years (1.5; 0.9, 2.6). Soft tissue injury was the most often reported injury while fractures were associated with 9.9% of syncopal events, representing 16% of those episodes associated with some injury. A multifactorial model for the etiology of syncope appears to best explain the occurrence of syncope in the elderly population. Therefore, a multidimensional risk strategy to stratify patients into different risk groups will enable directing risk reduction practices toward those patients who may most benefit

Actuation of chitosan-aptamer nanobrush borders for pathogen sensing

We demonstrate a sensing mechanism for rapid detection of Listeria monocytogenes in food samples using the actuation of chitosan-aptamer nanobrush borders. The bio-inspired soft material and sensing strategy mimic natural symbiotic systems, where low levels of bacteria are selectively captured from complex matrices. To engineer this biomimetic system, we first develop reduced graphene oxide/nanoplatinum (rGO-nPt) electrodes, and characterize the fundamental electrochemical behavior in the presence and absence of chitosan nanobrushes during actuation (pH-stimulated osmotic swelling). We then characterize the electrochemical behavior of the nanobrush when receptors (antibodies or DNA aptamers) are conjugated to the surface. Finally, we test various techniques to determine the most efficient capture strategy based on nanobrush actuation, and then apply the biosensors in a food product. Maximum cell capture occurs when aptamers conjugated to the nanobrush bind cells in the extended conformation (pH \u3c 6), followed by impedance measurement in the collapsed nanobrush conformation (pH \u3e 6). The aptamer-nanobrush hybrid material was more efficient than the antibody-nanobrush material, which was likely due to the relatively high adsorption capacity for aptamers. The biomimetic material was used to develop a rapid test (17 min) for selectively detecting L. monocytogenes at concentrations ranging from 9 to 107 CFU-mL-1 with no pre-concentration, and in the presence of other gram-positive cells (Listeria innocua and Staphylococcus aureus). Use of this bio-inspired material is among the most efficient for L. monocytogenes sensing to date, and does not require sample pretreatment, making nanobrush borders a promising new material for rapid pathogen detection in food

Elaboração de uma proposta para implementação de grupo de gestantes em uma unidade de saúde pública da periferia de Boa Vista-RR

TCC(especialização) - Universidade Federal de Santa Catarina. Centro de Ciências da Saúde. Programa de Pós-graduação em Enfermagem. Linhas de Cuidado em Saúde Materna, Neonatal e do LactanteIntrodução: A gestação é um período impar para a mulher, período onde manifestações biopsicossociais acontecem. Também é um momento no qual muitas dúvidas e inseguranças surgem e podem se tornar maus fatores para a evolução da gestação. A realização da assistência pré-natal é uma prática desenvolvida por muitos modelos de atenção primária. Por estes motivos, o acompanhamento de pré-natal, se tornou a principal arma e ação usada pelo Ministério da saúde, para reduzir os altos índices de mortalidade materno infantil no país. Objetivo: Elaborar uma proposta para implantação de Grupo de Gestantes em um Centro de Saúde da periferia de Boa Vista – RR. Metodologia: Serão convidadas todas as gestantes que fazem parte da área de abrangência do Centro de Saúde Asa Branca. Serão trabalhados com as gestantes assuntos pertinentes ao trabalho de parto, parto, puerpério e amamentação, utilizaremos equipamento de data show para exibição de slides e filmes e para demonstração de situações em que o recém- nascido seja exemplo, será utilizado bonecos. Conclusão: É sabido a importância do pré-natal para a gestação, porém é muito importante que as gestantes se sintam donas de sua gestação, donas de seu corpo. Por este motivo o grupo de gestante se mostra importante para que a mesma se apodere deste momento impar e seja protagonista nesta fase tão peculiar da feminilidade

Requirements engineering challenges and practices in large-scale agile system development

Context: Agile methods have become mainstream even in large-scale systems engineering companies that need to accommodate different development cycles of hardware and software. For such companies, requirements engineering is an essential activity that involves upfront and detailed analysis which can be at odds with agile development methods. Objective: This paper presents a multiple case study with seven large-scale systems companies, reporting their challenges, together with best practices from industry. We also analyze literature about two popular large-scale agile frameworks, SAFe (R) and LeSS, to derive potential solutions for the challenges. Methods: Our results are based on 20 qualitative interviews, five focus groups, and eight cross company workshops which we used to both collect and validate our results. Results: We found 24 challenges which we grouped in six themes, then mapped to solutions from SAFe (R), LeSS, and our companies, when available. Conclusion: In this way, we contribute a comprehensive overview of RE challenges in relation to largescale agile system development, evaluate the degree to which they have been addressed, and outline research gaps. We expect these results to be useful for practitioners who are responsible for designing processes, methods, or tools for large scale agile development as well as guidance for researchers

Molecular Tools for Adapting Viticulture to Climate Change

Adaptation of viticulture to climate change includes exploration of new geographical areas, new training systems, new management practices, or new varieties, both for rootstocks and scions. Molecular tools can be defined as molecular approaches used to study DNAs, RNAs, and proteins in all living organisms. We present here the current knowledge about molecular tools and their potential usefulness in three aspects of grapevine adaptation to the ongoing climate change. (i) Molecular tools for understanding grapevine response to environmental stresses. A fine description of the regulation of gene expression is a powerful tool to understand the physiological mechanisms set up by the grapevine to respond to abiotic stress such as high temperatures or drought. The current knowledge on gene expression is continuously evolving with increasing evidence of the role of alternative splicing, small RNAs, long non-coding RNAs, DNA methylation, or chromatin activity. (ii) Genetics and genomics of grapevine stress tolerance. The description of the grapevine genome is more and more precise. The genetic variations among genotypes are now revealed with new technologies with the sequencing of very long DNA molecules. High throughput technologies for DNA sequencing also allow now the genetic characterization at the same time of hundreds of genotypes for thousands of points in the genome, which provides unprecedented datasets for genotype-phenotype associations studies. We review the current knowledge on the genetic determinism of traits for the adaptation to climate change. We focus on quantitative trait loci and molecular markers available for developmental stages, tolerance to water stress/water use efficiency, sugar content, acidity, and secondary metabolism of the berries. (iii) Controlling the genome and its expression to allow breeding of better-adapted genotypes. High-density DNA genotyping can be used to select genotypes with specific interesting alleles but genomic selection is also a powerful method able to take into account the genetic information along the whole genome to predict a phenotype. Modern technologies are also able to generate mutations that are possibly interesting for generating new phenotypes but the most promising one is the direct editing of the genome at a precise location

Laser Scribed Graphene Biosensor for Detection of Biogenic Amines in Food Samples Using Locally Sourced Materials

In foods, high levels of biogenic amines (BA) are the result of microbial metabolism that could be affected by temperatures and storage conditions. Thus, the level of BA is commonly used as an indicator of food safety and quality. This manuscript outlines the development of laser scribed graphene electrodes, with locally sourced materials, for reagent-free food safety biosensing. To fabricate the biosensors, the graphene surface was functionalized with copper microparticles and diamine oxidase, purchased from a local supermarket; and then compared to biosensors fabricated with analytical grade materials. The amperometric biosensor exhibits good electrochemical performance, with an average histamine sensitivity of 23.3 µA/mM, a lower detection limit of 11.6 µM, and a response time of 7.3 s, showing similar performance to biosensors constructed from analytical grade materials. We demonstrated the application of the biosensor by testing total BA concentration in fish paste samples subjected to fermentation with lactic acid bacteria. Biogenic amines concentrations prior to lactic acid fermentation were below the detection limit of the biosensor, while concentration after fermentation was 19.24 ± 8.21 mg histamine/kg, confirming that the sensor was selective in a complex food matrix. The low-cost, rapid, and accurate device is a promising tool for biogenic amine estimation in food samples, particularly in situations where standard laboratory techniques are unavailable, or are cost prohibitive. This biosensor can be used for screening food samples, potentially limiting food waste, while reducing chances of foodborne outbreaks

INCOME SMOOTHING AND CORPORATE GOVERNANCE

Income smoothing is a strategy aimed at altering accounting results in order to reduce fluctuations. In the other hand, by adopting corporate governance mechanisms it may be possible to reduce information asymmetry and, consequently, reduce the possibility of smoothing results. The general objective of the present study was to investigate the relationship between the adoption of corporate governance mechanisms and income smoothing. Financial data were selected from 211 Brazilian public companies between 2000 and 2015. The firms were separated according to whether or not they adhered to B3’s differentiated corporate governance segments. Income smoothing was measured using both the model by Eckel (1981) and a version of the model proposed by Leuz et al., (2003). The analysis was performed using non-parametric Wilcoxon rank sum tests and descriptive analyses. Based on the descriptive analysis, it was not possible to state that the group of firms adhering to the corporate governance levels had a smaller proportion of companies that smooth results; and the hypothesis that the degree of income smoothing is lower for such companies was not confirmed. The assumption that levels of corporate governance reduce the possibility of income smoothing was not validated based on non-parametric tests. Based on the descriptive analysis, it was concluded that both the proportion of companies that smooth results, and the degree of smoothing by organizations following the B3’s corporate governance levels are not lower than the ones shown by companies that do not follow the levels

Universal Power Law in the Noise from a Crumpled Elastic Sheet

Using high-resolution digital recordings, we study the crackling sound emitted from crumpled sheets of mylar as they are strained. These sheets possess many of the qualitative features of traditional disordered systems including frustration and discrete memory. The sound can be resolved into discrete clicks, emitted during rapid changes in the rough conformation of the sheet. Observed click energies range over six orders of magnitude. The measured energy autocorrelation function for the sound is consistent with a stretched exponential C(t) ~ exp(-(t/T)^{b}) with b = .35. The probability distribution of click energies has a power law regime p(E) ~ E^{-a} where a = 1. We find the same power law for a variety of sheet sizes and materials, suggesting that this p(E) is universal.Comment: 5 pages (revtex), 10 uuencoded postscript figures appended, html version at http://rainbow.uchicago.edu/~krame

Post hoc support vector machine learning for impedimetric biosensors based on weak protein-ligand interactions

Impedimetric biosensors for measuring small molecules based on weak/transient interactions between bioreceptor and target analyte are a challenge for detection electronics, particularly in field studies or in analysis of complex matrices. Protein-ligand binding sensors have enormous potential for biosensing, but accuracy in complex solutions is a major challenge. There is a need for simple post hoc analytical tools that are not computationally expensive, yet provide near real time feedback on data derived from impedance spectra. Here, we show use of a simple, open source support vector machine learning algorithm for analyzing impedimetric data in lieu of using equivalent circuit analysis. We demonstrte two different protein-based biosensors to show that the tool can be used for various applications. We conclude with a mobile phone-based demonstration focused on measurement of acetone, an important biomarker related to onset of diabetic ketoacidosis. In all conditions tested, the open source classifier was capable of performing as well, or better, than equivalent circuit analysis for characterizing weak/transient interactions between a model ligand (acetone) and a small chemosensory protein derived from tsetse fly. In addition, the tool has a low computational requirement, facilitating use for mobile acquisition systems such as mobile phone. The protocol is deployed through Jupyter notebook (an open source computing environment available for mobile phone, tablet, or computer use) and the code was written in Python. For each of the applications we provide step-by-step instructions in English, Spanish, Mandarin, and Portuguese to facilitate widespread use. All codes were based on scikit-learn, an open source software machine learning library in the Python language, and were processed in Jupyter notebook, an open-source web application for Python. The tool can easily be integrated with mobile biosensor equipment for rapid detection, facilitating use by a broad range of impedimetric biosensor users. This post hoc analysis tool can serve as a launchpad for convergence of nanobiosensors in planetary health monitoring applications based on mobile phone hardware