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Sökning: WFRF:(Shah Tejal)

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  • Chatterjee, Pratishtha, et al. (författare)
  • Plasma neurofilament light chain and amyloid-β are associated with the kynurenine pathway metabolites in preclinical Alzheimer's disease.
  • 2019
  • Ingår i: Journal of neuroinflammation. - 1742-2094. ; 16:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Blood markers indicative of neurodegeneration (neurofilament light chain; NFL), Alzheimer's disease amyloid pathology (amyloid-β; Aβ), and neuroinflammation (kynurenine pathway; KP metabolites) have been investigated independently in neurodegenerative diseases. However, the association of these markers of neurodegeneration and AD pathology with neuroinflammation has not been investigated previously. Therefore, the current study examined whether NFL and Aβ correlate with KP metabolites in elderly individuals to provide insight on the association between blood indicators of neurodegeneration and neuroinflammation.Correlations between KP metabolites, measured using liquid chromatography and gas chromatography coupled with mass spectrometry, and plasma NFL and Aβ concentrations, measured using single molecule array (Simoa) assays, were investigated in elderly individuals aged 65-90 years, with normal global cognition (Mini-Mental State Examination Score ≥ 26) from the Kerr Anglican Retirement Village Initiative in Ageing Health cohort.A positive correlation between NFL and the kynurenine to tryptophan ratio (K/T) reflecting indoleamine 2,3-dioxygenase activity was observed (r = .451, p < .0001). Positive correlations were also observed between NFL and kynurenine (r = .364, p < .0005), kynurenic acid (r = .384, p < .0001), 3-hydroxykynurenine (r = .246, p = .014), anthranilic acid (r = .311, p = .002), and quinolinic acid (r = .296, p = .003). Further, significant associations were observed between plasma Aβ40 and the K/T (r = .375, p < .0005), kynurenine (r = .374, p < .0005), kynurenic acid (r = .352, p < .0005), anthranilic acid (r = .381, p < .0005), and quinolinic acid (r = .352, p < .0005). Significant associations were also observed between plasma Aβ42 and the K/T ratio (r = .215, p = .034), kynurenic acid (r = .214, p = .035), anthranilic acid (r = .278, p = .006), and quinolinic acid (r = .224, p = .027) in the cohort. On stratifying participants based on their neocortical Aβ load (NAL) status, NFL correlated with KP metabolites irrespective of NAL status; however, associations between plasma Aβ and KP metabolites were only pronounced in individuals with high NAL while associations in individuals with low NAL were nearly absent.The current study shows that KP metabolite changes are associated with biomarker evidence of neurodegeneration. Additionally, the association between KP metabolites and plasma Aβ seems to be NAL status dependent. Finally, the current study suggests that an association between neurodegeneration and neuroinflammation manifests in the periphery, suggesting that preventing cytoskeleton cytotoxicity by KP metabolites may have therapeutic potential.
  • Jayaraman, Prem, et al. (författare)
  • Orchestrating Quality of Service in the Cloud of Things Ecosystem
  • 2015
  • Ingår i: 2015 IEEE International Symposium on Nanoelectronic and Information Systems. - Piscataway, NJ : IEEE Communications Society. - 9781467396912 ; , s. 185-190
  • Konferensbidrag (refereegranskat)abstract
    • Cloud of Things (CoT) is a vision inspired by Internet of Things (IoT) and cloud computing where the IoT devices are connected to the clouds via the Internet for datastorage, processing, analytics and visualization. CoT ecosystem will encompass heterogeneous clouds, networks and devices to provide seamless service delivery, for example, in smart cites. To enable efficient service delivery, there is a need to guarantee a certain level of quality of service from both cloud and networksperspective. This paper discusses the Cloud of Things, cloud computing, networks and new quality of service management research issues arising due to realisation of CoT ecosystem vision.
  • Shah, Tejal, et al. (författare)
  • Remote health care cyber-physical system : quality of service (QoS) challenges and opportunities
  • 2016
  • Ingår i: IET Cyber-Physical Systems: Theory & Applications. - : IET. - 2398-3396. ; 1:1, s. 40-48
  • Tidskriftsartikel (refereegranskat)abstract
    • There is a growing emphasis to find alternative non-traditional ways to manage patients to ease the burden on health care services largely fuelled by a growing demand from sections of population that is ageing. In-home remote patient monitoring applications harnessing technological advancements in the area of Internet of things (IoT), semantic web, data analytics, and cloud computing have emerged as viable alternatives. However, such applications generate large amounts of real-time data in terms of volume, velocity, and variety thus making it a big data problem. Hence, the challenge is how to combine and analyse such data with historical patient data to obtain meaningful diagnoses suggestions within acceptable time frames (considering quality of service (QoS)). Despite the evolution of big data processing technologies (e.g. Hadoop) and scalable infrastructure (e.g. clouds), there remains a significant gap in the areas of heterogeneous data collection, real-time patient monitoring, and automated decision support (semantic reasoning) based on well-defined QoS constraints. In this study, the authors review the state-of-the-art in enabling QoS for remote health care applications. In particular, they investigate the QoS challenges required to meet the analysis and inferencing needs of such applications and to overcome the limitations of existing big data processing tools.
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