| 11. |
- Jansen, Willemijn J, et al.
(author)
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Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum.
- 2022
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In: JAMA neurology. - : American Medical Association (AMA). - 2168-6157 .- 2168-6149. ; 79:3, s. 228-243
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Journal article (peer-reviewed)abstract
- One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design.To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates.This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria.Alzheimer disease biomarkers detected on PET or in CSF.Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations.Among the 19097 participants (mean [SD] age, 69.1 [9.8] years; 10148 women [53.1%]) included, 10139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P=.04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P=.004), subjective cognitive decline (9%; 95% CI, 3%-15%; P=.005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P=.004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P=.18).This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.
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| 12. |
- Johnson, Michael, et al.
(author)
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Responsiveness to Change : How can the concept of Attractive Quality Enhance School Sustainability?
- 2022
-
In: Proceedings M2D2022: 9th International Conference on mechanics and materials in design. - 9789895475636 ; , s. 997-1014
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Conference paper (peer-reviewed)abstract
- The global COVID 19 pandemic created a challenge for organizations and schools worldwide that raised fundamental questions about the degree to which they are sustainable. Some schools struggled to adapt quickly to the needs of their stakeholders while others saw opportunity in the moment to create and innovate to generate new value for their customers and increase attractive quality. Sustainability can be defined as the responsiveness of a living system to change in its environment (Snyder and Snyder, 2021) and responsiveness as the quality of reacting quickly and positively. When faced with the pandemic, schools and organizations around the world were put to the test on how responsive they could be to changes in their complex environments and this turbulent time in history has forced educational leaders to ask how schools can create more sustainable practices. This paper presents a phenomenological study which examined what school leaders did to sustain attractive quality during the pandemic, specifically by evaluating responsiveness as a core capability. Findings were explored to better understand responsiveness and ask what lessons can be learned that will help inform a framework for developing sustainable quality in education.
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| 13. |
- Kry, Stephen F., et al.
(author)
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APM Task Group 329 : Reference dose specification for dose calculations: Dose-to-water or dose-to-muscle?
- 2020
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In: Medical Physics. - : Wiley. - 0094-2405 .- 2473-4209. ; 47:3, s. 52-64
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Journal article (peer-reviewed)abstract
- Linac calibration is done in water, but patients are comprised primarily of soft tissue. Conceptually, and specified in NRG/RTOG trials, dose should be reported as dose-to-muscle to describe the dose to the patient. Historically, the dose-to-water of the linac calibration was often converted to dose-to-muscle for patient calculations through manual application of a 0.99 dose-to-water to dose-to-muscle correction factor, applied during the linac clinical reference calibration. However, many current treatment planning system (TPS) dose calculation algorithms approximately provide dose-to-muscle (tissue), making application of a manual scaling unnecessary. There is little guidance on when application of a scaling factor is appropriate, resulting in highly inconsistent application of this scaling by the community. In this report we provide guidance on the steps necessary to go from the linac absorbed dose-to-water calibration to dose-to-muscle in patient, for various commercial TPS algorithms. If the TPS does not account for the difference between dose-to-water and dose-to-muscle, then TPS reference dose scaling is warranted. We have tabulated the major vendors' TPS in terms of whether they approximate dose-to-muscle or calculate dose-to-water and recommend the correction factor required to report dose-to-muscle directly from the TPS algorithm. Physicists should use this report to determine the applicable correction required for specifying the reference dose in their TPS to achieve this goal and should remain attentive to possible changes to their dose calculation algorithm in the future.
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| 14. |
- Murari, A., et al.
(author)
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A control oriented strategy of disruption prediction to avoid the configuration collapse of tokamak reactors
- 2024
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In: Nature Communications. - 2041-1723 .- 2041-1723. ; 15:1
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Journal article (peer-reviewed)abstract
- The objective of thermonuclear fusion consists of producing electricity from the coalescence of light nuclei in high temperature plasmas. The most promising route to fusion envisages the confinement of such plasmas with magnetic fields, whose most studied configuration is the tokamak. Disruptions are catastrophic collapses affecting all tokamak devices and one of the main potential showstoppers on the route to a commercial reactor. In this work we report how, deploying innovative analysis methods on thousands of JET experiments covering the isotopic compositions from hydrogen to full tritium and including the major D-T campaign, the nature of the various forms of collapse is investigated in all phases of the discharges. An original approach to proximity detection has been developed, which allows determining both the probability of and the time interval remaining before an incoming disruption, with adaptive, from scratch, real time compatible techniques. The results indicate that physics based prediction and control tools can be developed, to deploy realistic strategies of disruption avoidance and prevention, meeting the requirements of the next generation of devices.
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| 15. |
- Omenn, Gilbert S., et al.
(author)
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Research on the Human Proteome Reaches a Major Milestone : > 90% of Predicted Human Proteins Now Credibly Detected, According to the HUPO Human Proteome Project
- 2020
-
In: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 19:12, s. 4735-4746
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Journal article (peer-reviewed)abstract
- According to the 2020 Metrics of the HUPO Human Proteome Project (HPP), expression has now been detected at the protein level for >90% of the 19 773 predicted proteins coded in the human genome. The HPP annually reports on progress made throughout the world toward credibly identifying and characterizing the complete human protein parts list and promoting proteomics as an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2020-01 classified 17 874 proteins as PE1, having strong protein-level evidence, up 180 from 17 694 one year earlier. These represent 90.4% of the 19 773 predicted coding genes (all PE1,2,3,4 proteins in neXtProt). Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), was reduced by 230 from 2129 to 1899 since the neXtProt 2019-01 release. PeptideAtlas is the primary source of uniform reanalysis of raw mass spectrometry data for neXtProt, supplemented this year with extensive data from MassIVE. PeptideAtlas 2020-01 added 362 canonical proteins between 2019 and 2020 and MassIVE contributed 84 more, many of which converted PE1 entries based on non-MS evidence to the MS-based subgroup. The 19 Biology and Disease-driven B/D-HPP teams continue to pursue the identification of driver proteins that underlie disease states, the characterization of regulatory mechanisms controlling the functions of these proteins, their proteoforms, and their interactions, and the progression of transitions from correlation to coexpression to causal networks after system perturbations. And the Human Protein Atlas published Blood, Brain, and Metabolic Atlases.
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| 16. |
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| 17. |
- Panyard, Daniel J., et al.
(author)
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Post-GWAS multiomic functional investigation of the TNIP1 locus in Alzheimer's disease highlights a potential role for GPX3
- 2024
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In: ALZHEIMERS & DEMENTIA. - 1552-5260 .- 1552-5279.
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Journal article (peer-reviewed)abstract
- INTRODUCTION Recent genome-wide association studies (GWAS) have reported a genetic association with Alzheimer's disease (AD) at the TNIP1/GPX3 locus, but the mechanism is unclear. METHODS We used cerebrospinal fluid (CSF) proteomics data to test (n = 137) and replicate (n = 446) the association of glutathione peroxidase 3 (GPX3) with CSF biomarkers (including amyloid and tau) and the GWAS-implicated variants (rs34294852 and rs871269). RESULTS CSF GPX3 levels decreased with amyloid and tau positivity (analysis of variance P = 1.5 x 10(-5)) and higher CSF phosphorylated tau (p-tau) levels (P = 9.28 x 10(-7)). The rs34294852 minor allele was associated with decreased GPX3 (P = 0.041). The replication cohort found associations of GPX3 with amyloid and tau positivity (P = 2.56 x 10(-6)) and CSF p-tau levels (P = 4.38 x 10(-9)). DISCUSSION These results suggest variants in the TNIP1 locus may affect the oxidative stress response in AD via altered GPX3 levels.
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| 18. |
- Pecunia, Vincenzo, et al.
(author)
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Roadmap on energy harvesting materials
- 2023
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In: Journal of Physics. - : IOP Publishing. - 2515-7639. ; 6:4
-
Journal article (peer-reviewed)abstract
- Ambient energy harvesting has great potential to contribute to sustainable development and address growing environmental challenges. Converting waste energy from energy-intensive processes and systems (e.g. combustion engines and furnaces) is crucial to reducing their environmental impact and achieving net-zero emissions. Compact energy harvesters will also be key to powering the exponentially growing smart devices ecosystem that is part of the Internet of Things, thus enabling futuristic applications that can improve our quality of life (e.g. smart homes, smart cities, smart manufacturing, and smart healthcare). To achieve these goals, innovative materials are needed to efficiently convert ambient energy into electricity through various physical mechanisms, such as the photovoltaic effect, thermoelectricity, piezoelectricity, triboelectricity, and radiofrequency wireless power transfer. By bringing together the perspectives of experts in various types of energy harvesting materials, this Roadmap provides extensive insights into recent advances and present challenges in the field. Additionally, the Roadmap analyses the key performance metrics of these technologies in relation to their ultimate energy conversion limits. Building on these insights, the Roadmap outlines promising directions for future research to fully harness the potential of energy harvesting materials for green energy anytime, anywhere.
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| 19. |
- Snyder, Joel S., et al.
(author)
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#EEGManyLabs: Investigating the replicability of influential EEG experiments
- 2021
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In: Cortex. - : Elsevier. - 1973-8102 .- 0010-9452. ; 144, s. 213-229
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Journal article (peer-reviewed)abstract
- There is growing awareness across the neuroscience community that the replicability of findings about the relationship between brain activity and cognitive phenomena can be improved by conducting studies with high statistical power that adhere to well-defined and standardised analysis pipelines. Inspired by recent efforts from the psychological sciences, and with the desire to examine some of the foundational findings using electroencephalog-raphy (EEG), we have launched #EEGManyLabs, a large-scale international collaborative replication effort. Since its discovery in the early 20th century, EEG has had a profound in-fluence on our understanding of human cognition, but there is limited evidence on the replicability of some of the most highly cited discoveries. After a systematic search and se-lection process, we have identified 27 of the most influential and continually cited studies in the field. We plan to directly test the replicability of key findings from 20 of these studies in teams of at least three independent laboratories. The design and protocol of each replication effort will be submitted as a Registered Report and peer-reviewed prior to data collection. Prediction markets, open to all EEG researchers, will be used as a forecasting tool to examine which findings the community expects to replicate. This project will update our confidence in some of the most influential EEG findings and generate a large open access database that can be used to inform future research practices. Finally, through this international effort, we hope to create a cultural shift towards inclusive, high-powered multi-laboratory collaborations. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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| 20. |
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