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Metabolic dysregulation in vitamin E and carnitine shuttle energy mechanisms associate with human frailty
Nicholas Rattray, Drupad Trivedi, Yun Xu, Tarani Chandola, Caroline Johnson, Alan Marshall, Krisztina Mekli, Zahra Rattray, Gindo Tampubolon, Bram Vanhoutte, Iain R. White, Frederick Wu, Neil Pendleton, James Nazroo, Royston Goodacre, 2019, original scientific article

Abstract: Global ageing poses a substantial economic burden on health and social care costs. Enabling a greater proportion of older people to stay healthy for longer is key to the future sustainability of health, social and economic policy. Frailty and associated decrease in resilience plays a central role in poor health in later life. In this study, we present a population level assessment of the metabolic phenotype associated with frailty. Analysis of serum from 1191 older individuals (aged between 56 and 84 years old) and subsequent longitudinal validation (on 786 subjects) was carried out using liquid and gas chromatography-mass spectrometry metabolomics and stratified across a frailty index designed to quantitatively summarize vulnerability. Through multivariate regression and network modelling and mROC modeling we identified 12 significant metabolites (including three tocotrienols and six carnitines) that differentiate frail and non-frail phenotypes. Our study provides evidence that the dysregulation of carnitine shuttle and vitamin E pathways play a role in the risk of frailty.
Keywords: metabolomics, frailty, ageing, LC-MS, serum
Published in RUNG: 08.11.2019; Views: 3181; Downloads: 90
.pdf Full text (2,35 MB)

3.
A map-matching algorithm dealing with sparse cellular fingerprint observations
Andrea Dalla Torre, Paolo Gallo, Donatella Gubiani, Chris Marshall, Angelo Montanari, Federico Pittino, Andrea Viel, 2019, original scientific article

Abstract: The widespread availability of mobile communication makes mobile devices a resource for the collection of data about mobile infrastructures and user mobility. In these contexts, the problem of reconstructing the most likely trajectory of a device on the road network on the basis of the sequence of observed locations (map-matching problem) turns out to be particularly relevant. Different contributions have demonstrated that the reconstruction of the trajectory of a device with good accuracy is technically feasible even when only a sparse set of GNSS positions is available. In this paper, we face the problem of coping with sparse sequences of cellular fingerprints. Compared to GNSS positions, cellular fingerprints provide coarser spatial information, but they work even when a device is missing GNSS positions or is operating in an energy saving mode. We devise a new map-matching algorithm, that exploits the well-known Hidden Markov Model and Random Forests to successfully deal with noisy and sparse cellular observations. The performance of the proposed solution has been tested over a medium-sized Italian city urban environment by varying both the sampling of the observations and the density of the fingerprint map as well as by including some GPS positions into the sequence of fingerprint observations.
Keywords: Map-matching algorithm, trajectory, cellular fingerprint, Hidden Markov Model
Published in RUNG: 11.06.2019; Views: 3267; Downloads: 97
.pdf Full text (3,93 MB)

4.
Map matching with sparse cellular fingerprint observations
Andrea Viel, Donatella Gubiani, Paolo Gallo, Angelo Montanari, Andrea Dalla Torre, Federico Pittino, Chris Marshall, 2018, published scientific conference contribution

Keywords: map matching, fingerprint, trajectories
Published in RUNG: 09.12.2018; Views: 3582; Downloads: 0
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5.
Dealing with network changes in cellular fingerprint positioning systems
Andrea Viel, Paolo Gallo, Angelo Montanari, Donatella Gubiani, Andrea Dalla Torre, Federico Pittino, Chris Marshall, 2017, published scientific conference contribution

Abstract: Besides being a fundamental infrastructure for communication, cellular networks are exploited for positioning through signal fingerprinting. Maintaining the fingerprint database consistent and up-to-date is a challenging task in many fingerprint positioning systems, e.g., in those populated by a crowd-sourcing effort. To this end, detecting and tracking the changes in the configurations of cellular networks over time is recognized as a relevant problem. In this paper, we show that to cope with this problem we can successfully exploit information provided by Timing Advance (TA). As a by-product, we prove that TA can improve the fingerprint candidate selection phase, reducing the number of fingerprints to provide as input to positioning algorithms. The effectiveness of the proposed improvements has been tested on a fingerprint positioning system with a large fingerprint dataset collected over a period of 2 years.
Keywords: fingerprint positioning systems, cellular communication networks, network changes
Published in RUNG: 13.06.2018; Views: 3857; Downloads: 0
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