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- Vergallo, A., et al.
(författare)
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Association of plasma YKL-40 with brain amyloid-β levels, memory performance, and sex in subjective memory complainers
- 2020
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Ingår i: Neurobiology of Aging. - : Elsevier BV. - 0197-4580. ; 96, s. 22-32
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Tidskriftsartikel (refereegranskat)abstract
- Neuroinflammation, a key early pathomechanistic alteration of Alzheimer's disease, may represent either a detrimental or a compensatory mechanism or both (according to the disease stage). YKL-40, a glycoprotein highly expressed in differentiated glial cells, is a candidate biomarker for in vivo tracking neuroinflammation in humans. We performed a longitudinal study in a monocentric cohort of cognitively healthy individuals at risk for Alzheimer's disease exploring whether age, sex, and the apolipoprotein E ε4 allele affect plasma YKL-40 concentrations. We investigated whether YKL-40 is associated with brain amyloid-β (Aβ) deposition, neuronal activity, and neurodegeneration as assessed via neuroimaging biomarkers. Finally, we investigated whether YKL-40 may predict cognitive performance. We found an age-associated increase of YKL-40 and observed that men display higher concentrations than women, indicating a potential sexual dimorphism. Moreover, YKL-40 was positively associated with memory performance and negatively associated with brain Aβ deposition (but not with metabolic signal). Consistent with translational studies, our results suggest a potentially protective effect of glia on incipient brain Aβ accumulation and neuronal homeostasis. © 2020 Elsevier Inc.
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- Vergallo, A., et al.
(författare)
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Plasma amyloid beta 40/42 ratio predicts cerebral amyloidosis in cognitively normal individuals at risk for Alzheimer's disease
- 2019
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Ingår i: Alzheimers & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 15:6, s. 764-775
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Blood-based biomarkers of pathophysiological brain amyloid beta (A beta) accumulation, particularly for preclinical target and large-scale interventions, are warranted to effectively enrich Alzheimer's disease clinical trials and management. Methods: We investigated whether plasma concentrations of the A beta(1-40)/A beta(1-42) ratio, assessed using the single-molecule array (Simoa) immunoassay, may predict brain A beta positron emission tomography status in a large-scale longitudinal monocentric cohort (N = 276) of older individuals with subjective memory complaints. We performed a hypothesis-driven investigation followed by a no-apriori hypothesis study using machine learning. Results: The receiver operating characteristic curve and machine learning showed a balanced accuracy of 76.5% and 81%, respectively, for the plasma A beta(1-40)/A beta(1-42) ratio. The accuracy is not affected by the apolipoprotein E (APOE) epsilon 4 allele, sex, or age. Discussion: Our results encourage an independent validation cohort study to confirm the indication that the plasma A beta(1-40)/A beta(1-42) ratio, assessed via Simoa, may improve future standard of care and clinical trial design. (C) 2019 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.
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- Babulal, Ganesh M, et al.
(författare)
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Perspectives on ethnic and racial disparities in Alzheimer's disease and related dementias: Update and areas of immediate need.
- 2019
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Ingår i: Alzheimer's & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 15:2, s. 292-312
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Tidskriftsartikel (refereegranskat)abstract
- Alzheimer's disease and related dementias (ADRDs) are a global crisis facing the aging population and society as a whole. With the numbers of people with ADRDs predicted to rise dramatically across the world, the scientific community can no longer neglect the need for research focusing on ADRDs among underrepresented ethnoracial diverse groups. The Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART; alz.org/ISTAART) comprises a number of professional interest areas (PIAs), each focusing on a major scientific area associated with ADRDs. We leverage the expertise of the existing international cadre of ISTAART scientists and experts to synthesize a cross-PIA white paper that provides both a concise "state-of-the-science" report of ethnoracial factors across PIA foci and updated recommendations to address immediate needs to advance ADRD science across ethnoracial populations.
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- Belman-Flores, J. M., et al.
(författare)
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Experimental study of R1234yf as a drop-in replacement for R134a in a domestic refrigerator
- 2017
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Ingår i: International journal of refrigeration. - : ELSEVIER SCI LTD. - 0140-7007 .- 1879-2081. ; 81, s. 1-11
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents an experimental study for three identical domestic refrigerators using R1234yf as a drop-in replacement for R134a. An alternative methodology was proposed to estimate the optimal mass charge for R1234yf; with the use of such methodology, new evidences were sought on the thermal behavior of the refrigerator compartments as well as at the heat exchangers. Additionally, energy performance for both refrigerants was measured, and, finally, a TEWI analysis was conducted. For the type of refrigerator evaluated, results showed that R1234yf presented an average (for the 3 refrigerators) of 0.4 degrees C for the fresh food compartment, and 1.2 degrees C for the freezer, among different charges with respect to R134a. The optimal charge for R1234yf was 92.2 g, which is about 7.8% lower than the one for R134a, which represents a small increase of 4% in energy consumption in comparison to R134a. Finally, the TEWI analysis for the R1234yf was 1.07% higher than the R134a.
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- De Baets, L., et al.
(författare)
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The interplay between symptoms of insomnia and pain in people with osteoarthritis: A narrative review of the current evidence
- 2023
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Ingår i: Sleep Medicine Reviews. - 1087-0792. ; 70
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Forskningsöversikt (refereegranskat)abstract
- Osteoarthritis (OA) is a leading cause of disability worldwide and clinical pain is the major symptom of OA. This clinical OA-related pain is firmly associated with symptoms of insomnia, which are reported in up to 81% of people with OA. Since understanding the association between both symptoms is critical for their appropriate management, this narrative review synthesizes the existing evidence in people with OA on i) the mechanisms underlying the association between insomnia symptoms and clinical OA-related pain, and ii) the effectiveness of conservative non-pharmacological treatments on insomnia symptoms and clinical OA-related pain. The evidence available identifies depressive symptoms, pain catastrophizing and pain self-efficacy as mechanisms partially explaining the cross-sectional association between insomnia symptoms and pain in people with OA. Furthermore, in comparison to treatments without a specific insomnia intervention, the ones including an insomnia intervention appear more effective for improving insomnia symptoms, but not for reducing clinical OA-related pain. However, at a withinperson level, treatment-related positive effects on insomnia symptoms are associated with a longterm pain reduction. Future longitudinal prospective studies offering fundamental insights into neurobiological and psychosocial mechanisms explaining the association between insomnia symptoms and clinical OA-related pain will enable the development of effective treatments targeting both symptoms.
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- Degas, A., et al.
(författare)
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A Survey on Artificial Intelligence (AI) and eXplainable AI in Air Traffic Management : Current Trends and Development with Future Research Trajectory
- 2022
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Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 12:3
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Forskningsöversikt (refereegranskat)abstract
- Air Traffic Management (ATM) will be more complex in the coming decades due to the growth and increased complexity of aviation and has to be improved in order to maintain aviation safety. It is agreed that without significant improvement in this domain, the safety objectives defined by international organisations cannot be achieved and a risk of more incidents/accidents is envisaged. Nowadays, computer science plays a major role in data management and decisions made in ATM. Nonetheless, despite this, Artificial Intelligence (AI), which is one of the most researched topics in computer science, has not quite reached end users in ATM domain. In this paper, we analyse the state of the art with regards to usefulness of AI within aviation/ATM domain. It includes research work of the last decade of AI in ATM, the extraction of relevant trends and features, and the extraction of representative dimensions. We analysed how the general and ATM eXplainable Artificial Intelligence (XAI) works, analysing where and why XAI is needed, how it is currently provided, and the limitations, then synthesise the findings into a conceptual framework, named the DPP (Descriptive, Predictive, Prescriptive) model, and provide an example of its application in a scenario in 2030. It concludes that AI systems within ATM need further research for their acceptance by end-users. The development of appropriate XAI methods including the validation by appropriate authorities and end-users are key issues that needs to be addressed. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
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| 28. |
- Festari, Cristina, et al.
(författare)
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European consensus for the diagnosis of MCI and mild dementia : Preparatory phase
- 2023
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Ingår i: Alzheimer's and Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 19:5, s. 1729-1741
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Etiological diagnosis of neurocognitive disorders of middle-old age relies on biomarkers, although evidence for their rational use is incomplete. A European task force is defining a diagnostic workflow where expert experience fills evidence gaps for biomarker validity and prioritization. We report methodology and preliminary results. Methods: Using a Delphi consensus method supported by a systematic literature review, 22 delegates from 11 relevant scientific societies defined workflow assumptions. Results: We extracted diagnostic accuracy figures from literature on the use of biomarkers in the diagnosis of main forms of neurocognitive disorders. Supported by this evidence, panelists defined clinical setting (specialist outpatient service), application stage (MCI-mild dementia), and detailed pre-assessment screening (clinical-neuropsychological evaluations, brain imaging, and blood tests). Discussion: The Delphi consensus on these assumptions set the stage for the development of the first pan-European workflow for biomarkers’ use in the etiological diagnosis of middle-old age neurocognitive disorders at MCI-mild dementia stages. Highlights: Rational use of biomarkers in neurocognitive disorders lacks consensus in Europe. A consensus of experts will define a workflow for the rational use of biomarkers. The diagnostic workflow will be patient-centered and based on clinical presentation. The workflow will be updated as new evidence accrues.
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| 29. |
- Hurter, C., et al.
(författare)
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Usage of more transparent and explainable conflict resolution algorithm : Air traffic controller feedback
- 2022
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Ingår i: Transportation Research Procedia. - : Elsevier B.V.. - 2352-1457 .- 2352-1465. ; 66:C, s. 270-278
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Tidskriftsartikel (refereegranskat)abstract
- Recently, Artificial intelligence (AI) algorithms have received increasable interest in various application domains including in Air Transportation Management (ATM). Different AI in particular Machine Learning (ML) algorithms are used to provide decision support in autonomous decision-making tasks in the ATM domain e.g., predicting air transportation traffic and optimizing traffic flows. However, most of the time these automated systems are not accepted or trusted by the intended users as the decisions provided by AI are often opaque, non-intuitive and not understandable by human operators. Safety is the major pillar to air traffic management, and no black box process can be inserted in a decision-making process when human life is involved. To address this challenge related to transparency of the automated system in the ATM domain, we investigated AI methods in predicting air transportation traffic conflict and optimizing traffic flows based on the domain of Explainable Artificial Intelligence (XAI). Here, AI models’ explainability in terms of understanding a decision i.e., post hoc interpretability and understanding how the model works i.e., transparency can be provided for air traffic controllers. In this paper, we report our research directions and our findings to support better decision making with AI algorithms with extended transparency.
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