AimsAircraft noise disturbs sleep, and long-term exposure has been shown to be associated with increases in the prevalence of hypertension and an overall increased risk for myocardial infarction. The exact mechanisms responsible for these cardiovascular effects remain unclear.Methods and resultsWe performed a blinded field study in 75 healthy volunteers (mean age 26 years), who were exposed at home, in random order, to one control pattern (no noise) and two different noise scenarios [30 or 60 aircraft noise events per night with an average maximum sound pressure level (SPL) of 60 dB(A)] for one night each. We performed polygraphy during each study night. Noise caused a worsening in sleep quality (P < 0.0001). Noise60, corresponding to equivalent continuous SPLs of 46.3 dB (Leq) and representing environmental noise levels associated with increased cardiovascular events, caused a blunting in FMD (P = 0.016). As well, although a direct comparison among the FMD values in the noise groups (control: 10.4 ± 3.8%; Noise30: 9.7 ± 4.1%; Noise60: 9.5 ± 4.3%, P = 0.052) did not reach significance, a monotone dose-dependent effect of noise level on FMD was shown (P = 0.020). Finally, there was a priming effect of noise, i.e. the blunting in FMD was particularly evident when subjects were exposed first to 30 and then to 60 noise events (P = 0.006). Noise-induced endothelial dysfunction (ED) was reversed by the administration of Vitamin C (P = 0.0171). Morning adrenaline concentration increased from 28.3 ± 10.9 to 33.2 ± 16.6 and 34.1 ± 19.3 ng/L (P = 0.0099). Pulse transit time, reflecting arterial stiffness, was also shorter after exposure to noise (P = 0.003).ConclusionIn healthy adults, acute nighttime aircraft noise exposure dose-dependently impairs endothelial function and stimulates adrenaline release. Noise-induced ED may be in part due to increased production in reactive oxygen species and may thus be one mechanism contributing to the observed association of chronic noise exposure with cardiovascular disease.
In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.
Record linkage deals with detecting homonyms and mainly synonyms in data. The package RecordLinkage provides means to perform and evaluate different record linkage methods. A stochastic framework is implemented which calculates weights through an EM algorithm. The determination of the necessary thresholds in this model can be achieved by tools of extreme value theory. Furthermore, machine learning methods are utilized, including decision trees (rpart), bootstrap aggregating (bagging), ada boost (ada), neural nets (nnet) and support vector machines (svm). The generation of record pairs and comparison patterns from single data items are provided as well. Comparison patterns can be chosen to be binary or based on some string metrics. In order to reduce computation time and memory usage, blocking can be used. Future development will concentrate on additional and refined methods, performance improvements and input/output facilities needed for real-world application.
ZusammenfassungDie Verknüpfung verschiedener Datenquellen, genannt Datenlinkage oder auch Record Linkage, zur Beantwortung von wissenschaftlichen Fragestellungen findet in den letzten Jahren in Deutschland vermehrt Anwendung. Jedoch mangelt es bisher an publizierten Erfahrungen. Neue Projekte erarbeiten sich in der Regel autark voneinander das notwendige Handwerkszeug. Daher hat sich eine Gruppe von Forschern zusammengefunden, um ihre Erfahrungen zum Datenlinkage in Deutschland als mögliche Hilfestellung bzw. Anregung für Projekte, Gutachter sowie Datenschützer und Ethikkommissionen zusammenzustellen. Ziel dieser ersten Bestandsaufnahme zum Datenlinkage ist es deshalb, eine Unterstützung für zukünftige Projekte zu liefern, die Daten aus Deutschland auf individueller Ebene verknüpfen möchten. Neben den (datenschutz-)rechtlichen Rahmenbedingungen werden dabei auch praxisorientiert die Arten des Datenlinkage, deren Anwendungsfelder und Ansätze zur Vermeidung von Fehlern anhand von Beispielen dargestellt.
Availability of and access to data and biosamples are essential in medical and translational research, where their reuse and repurposing by the wider research community can maximize their value and accelerate discovery. However, sharing human-related data or samples is complicated by ethical, legal, and social sensitivities. The specific ethical and legal requirements linked to sensitive data are often unfamiliar to life science researchers who, faced with vast amounts of complex, fragmented, and sometimes even contradictory information, may not feel competent to navigate through it. In this case, the impulse may be not to share the data in order to safeguard against unintentional misuse. Consequently, helping data providers to identify relevant ethical and legal requirements and how they might address them is an essential and frequently neglected step in removing possible hurdles to data and sample sharing in the life sciences. Here, we describe the complex regulatory context and discuss relevant online tools—one which the authors co-developed—targeted at assisting providers of sensitive data or biosamples with ethical and legal questions. The main results are (1) that the different approaches of the tools assume different user needs and prior knowledge of ethical and legal requirements, affecting how a service is designed and its usefulness, (2) that there is much potential for collaboration between tool providers, and (3) that enriched annotations of services (e.g., update status, completeness of information, and disclaimers) would increase their value and facilitate quick assessment by users. Further, there is still work to do with respect to providing researchers using sensitive data or samples with truly ‘useful’ tools that do not require pre-existing, in-depth knowledge of legal and ethical requirements or time to delve into the details. Ultimately, separate resources, maintained by experts familiar with the respective fields of research, may be needed while—in the longer term—harmonization and increase in ease of use will be very desirable.
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