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- Donaghy, P. C., et al.
(author)
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The relationship between plasma biomarkers and amyloid PET in dementia with Lewy bodies
- 2022
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In: Parkinsonism and Related Disorders. - : Elsevier BV. - 1353-8020. ; 101, s. 111-116
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Journal article (peer-reviewed)abstract
- Introduction: Amyloid-β (Aβ) deposition is common in dementia with Lewy bodies (DLB) and has been associated with more rapid disease progression. An effective biomarker that identified the presence of significant brain Aβ in people with DLB may be useful to identify and stratify participants for research studies and to inform prognosis in clinical practice. Plasma biomarkers are emerging as candidates to fulfil this role. Methods: Thirty-two participants with DLB had brain amyloid (18F-florbetapir) PET, of whom 27 also had an MRI to enable the calculation of 18F-florbetapir SUVR. Plasma Aβ42/40, phosphorylated tau (p-tau181), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) were measured using single molecule array (Simoa). The plasma biomarkers were investigated for correlation with 18F-florbetapir SUVR, discriminant ability to identify Aβ-positive cases based on a predefined SUVR threshold of 1.10 and correlation with subsequent cognitive decline over one year. Results: All four plasma markers significantly correlated with 18F-florbetapir SUVR (|β| = 0.40-0.49; p < .05). NfL had the greatest area under the receiver operating characteristic curve to identify Aβ-positive cases (AUROC 0.84 (95% CI 0.66, 1); β = 0.46, p = .001), whereas Aβ42/40 had the smallest (AUROC 0.73 (95% CI 0.52, 0.95); β = −0.47, p = .01). Accuracy was highest when combining all four biomarkers (AUROC 0.92 (95% CI 0.80, 1)). Lower plasma Aβ42/40 was significantly associated with more rapid decline in cognition (β = 0.53, p < .01). Conclusions: Plasma biomarkers have the potential to identify Aβ deposition in DLB. Further work in other cohorts is required to determine and validate optimal cut-offs for these biomarkers. © 2022 The Authors
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- Mulders, Peter C.R., et al.
(author)
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Structural changes induced by electroconvulsive therapy are associated with clinical outcome
- 2020
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In: Brain Stimulation. - : Elsevier BV. - 1935-861X. ; 13:3, s. 696-704
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Journal article (peer-reviewed)abstract
- Background: Electroconvulsive therapy (ECT) is the most effective treatment option for major depressive disorder, so understanding whether its clinical effect relates to structural brain changes is vital for current and future antidepressant research. Objective: To determine whether clinical response to ECT is related to structural volumetric changes in the brain as measured by structural magnetic resonance imaging (MRI) and, if so, which regions are related to this clinical effect. We also determine whether a similar model can be used to identify regions associated with electrode placement (unilateral versus bilateral ECT). Methods: Longitudinal MRI and clinical data (Hamilton Depression Rating Scale) was collected from 10 sites as part of the Global ECT-MRI research collaboration (GEMRIC). From 192 subjects, relative changes in 80 (sub)cortical areas were used as potential features for classifying treatment response. We used recursive feature elimination to extract relevant features, which were subsequently used to train a linear classifier. As a validation, the same was done for electrode placement. We report accuracy as well as the structural coefficients of regions included in the discriminative spatial patterns obtained. Results: A pattern of structural changes in cortical midline, striatal and lateral prefrontal areas discriminates responders from non-responders (75% accuracy, p < 0.001) while left-sided mediotemporal changes discriminate unilateral from bilateral electrode placement (81% accuracy, p < 0.001). Conclusions: The identification of a multivariate discriminative pattern shows that structural change is relevant for clinical response to ECT, but this pattern does not include mediotemporal regions that have been the focus of electroconvulsive therapy research so far.
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- Petrides, P., et al.
(author)
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Heterogeneous- and NUMA-aware scheduling for many-core architectures
- 2017
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In: SYSTOR 2017 - Proceedings of the 10th ACM International Systems and Storage Conference. - New York, NY, USA : ACM. ; , s. Article no. 2-
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Conference paper (peer-reviewed)abstract
- © 2017 ACM. As the number of cores increases in a single chip processor, several challenges arise: wire delays, contention for out-ofchip accesses, and core heterogeneity. In order to address these issues and the applications demands, future large-scale many-core processors are expected to be organized as a collection of NUMA clusters of heterogeneous cores. In this work we propose a scheduler that takes into account the non-uniform memory latency, the heterogeneity of the cores, and the contention to the memory controller to find the best matching core for the application's memory and compute requirements. Scheduler decisions are based on an on-line classification process that determines applications requirements either as memory- or compute-bound. We evaluate our proposed scheduler on the 48-core Intel SCC using applications from SPEC CPU2006 benchmark suite. Our results show that even when all cores are busy, migrating processes to cores that match better the requirements of applications results in overall performance improvement. In particular we observed a reduction of the execution time from 15% to 36% compared to a random static scheduling policy.
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