Provenance is information describing the lineage of an object, such as a dataset or biological material. Since these objects can be passed between organizations, each organization can document only parts of the objects life cycle. As a result, interconnection of distributed provenance parts forms distributed provenance chains. Dependant on the actual provenance content, complete provenance chains can provide traceability and contribute to reproducibility and FAIRness of research objects. In this paper, we define a lightweight provenance model based on W3C PROV that enables generation of distributed provenance chains in complex, multi-organizational environments. The application of the model is demonstrated with a use case spanning several steps of a real-world research pipeline - starting with the acquisition of a specimen, its processing and storage, histological examination, and the generation/collection of associated data (images, annotations, clinical data), ending with training an AI model for the detection of tumor in the images. The proposed model has become an open conceptual foundation of the currently developed ISO 23494 standard on provenance for biotechnology domain.
- Publication type
- Journal Article MeSH
Brain stimulation has emerged as an effective treatment for a wide range of neurological and psychiatric diseases. Parkinson's disease, epilepsy, and essential tremor have FDA indications for electrical brain stimulation using intracranially implanted electrodes. Interfacing implantable brain devices with local and cloud computing resources have the potential to improve electrical stimulation efficacy, disease tracking, and management. Epilepsy, in particular, is a neurological disease that might benefit from the integration of brain implants with off-the-body computing for tracking disease and therapy. Recent clinical trials have demonstrated seizure forecasting, seizure detection, and therapeutic electrical stimulation in patients with drug-resistant focal epilepsy. In this paper, we describe a next-generation epilepsy management system that integrates local handheld and cloud-computing resources wirelessly coupled to an implanted device with embedded payloads (sensors, intracranial EEG telemetry, electrical stimulation, classifiers, and control policy implementation). The handheld device and cloud computing resources can provide a seamless interface between patients and physicians, and realtime intracranial EEG can be used to classify brain state (wake/sleep, preseizure, and seizure), implement control policies for electrical stimulation, and track patient health. This system creates a flexible platform in which low demand analytics requiring fast response times are embedded in the implanted device and more complex algorithms are implemented in offthebody local and distributed cloud computing environments. The system enables tracking and management of epileptic neural networks operating over time scales ranging from milliseconds to months.
- Publication type
- Journal Article MeSH
The distributed nature of modern research emphasizes the importance of collecting and sharing the history of digital and physical material, to improve the reproducibility of experiments and the quality and reusability of results. Yet, the application of the current methodologies to record provenance information is largely scattered, leading to silos of provenance information at different granularities. To tackle this fragmentation, we developed the Common Provenance Model, a set of guidelines for the generation of interoperable provenance information, and to allow the reconstruction and the navigation of a continuous provenance chain. This work presents the first version of the model, available online, based on the W3C PROV Data Model and the Provenance Composition pattern.
- MeSH
- Biological Science Disciplines * MeSH
- Reproducibility of Results MeSH
- Publication type
- Journal Article MeSH
The amplitudes of distortion-product otoacoustic emissions (DPOAEs) may abruptly decrease even though the stimulus level is relatively high. These notches observed in the DPOAE input/output functions or distortion-product grams have been hypothesized to be due to destructive interference between wavelets generated by distributed sources of the nonlinear-distortion component of DPOAEs. In this paper, simulations with a smooth cochlear model and its analytical solution support the hypothesis that destructive interference between individual wavelets may lead to the amplitude notches and explain the cause for onset and offset amplitude overshoots in the DPOAE signal measured for intensity pairs in the notches.
- MeSH
- Acoustic Stimulation MeSH
- Cochlea physiology MeSH
- Humans MeSH
- Otoacoustic Emissions, Spontaneous * MeSH
- Models, Theoretical * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Keywords
- nový web, intranet,
- MeSH
- Web Browser * MeSH
- Humans MeSH
- Computer Communication Networks * MeSH
- General Practitioners * MeSH
- Check Tag
- Humans MeSH
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The pulse-respiration quotient (heart rate divided by the respiration rate, PRQ = HR/RR) is a parameter capturing the complex state of cardiorespiratory interactions. We analysed 482 single PRQ values obtained from measurement on 134 healthy adult subjects (49 men, 85 women, age: 24.7 ± 3.4, range: 20-46 years) during rest. We found that the distribution of PRQ values (i) has a global maximum at around a value of 4 (median: 4.19) and (ii) follows a lognormal distribution function. A multimodality of the distribution, associated with several PRQ attractor states was not detected by our group-level based analysis. In summary, our analysis shows that in healthy humans the resting-state PRQ is around 4 and lognormally distributed. This finding supports claims about the special role of the 4 to 1 cardiorespiratory coupling in particular and the PRQ in general for physiological and medical views and applications. To the best of our knowledge, our study is the largest conducted so far in healthy adult humans about reference values of the PRQ during a resting-state at day.
- MeSH
- Respiratory Rate physiology MeSH
- Adult MeSH
- Blood Pressure physiology MeSH
- Middle Aged MeSH
- Humans MeSH
- Young Adult MeSH
- Rest physiology MeSH
- Reference Standards MeSH
- Heart Rate physiology MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Young Adult MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
The dark ocean microbiota represents the unknown majority in the global ocean waters. The SAR202 cluster belonging to the phylum Chloroflexi was the first microbial lineage discovered to specifically inhabit the aphotic realm, where they are abundant and globally distributed. The absence of SAR202 cultured representatives is a significant bottleneck towards understanding their metabolic capacities and role in the marine environment. In this work, we use a combination of metagenome-assembled genomes from deep-sea datasets and publicly available single-cell genomes to construct a genomic perspective of SAR202 phylogeny, metabolism and biogeography. Our results suggest that SAR202 cluster members are medium sized, free-living cells with a heterotrophic lifestyle, broadly divided into two distinct clades. We present the first evidence of vertical stratification of these microbes along the meso- and bathypelagic ocean layers. Remarkably, two distinct species of SAR202 cluster are highly abundant in nearly all deep bathypelagic metagenomic datasets available so far. SAR202 members metabolize multiple organosulfur compounds, many appear to be sulfite-oxidizers and are predicted to play a major role in sulfur turnover in the dark water column. This concomitantly suggests an unsuspected availability of these nutrient sources to allow for the high abundance of these microbes in the deep sea.
- MeSH
- Chloroflexi classification genetics isolation & purification metabolism MeSH
- Phylogeny MeSH
- Genomics MeSH
- Metagenome MeSH
- Metagenomics MeSH
- Microbiota MeSH
- Seawater microbiology MeSH
- Oceans and Seas MeSH
- Sulfur metabolism MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Oceans and Seas MeSH
