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Sökning: (WFRF:(Vogel H.)) srt2:(2020-2024) > (2024)

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  • Mastenbroek, Sophie E., et al. (författare)
  • Disease progression modelling reveals heterogeneity in trajectories of Lewy-type α-synuclein pathology
  • 2024
  • Ingår i: Nature Communications. - 2041-1723. ; 15:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Lewy body (LB) diseases, characterized by the aggregation of misfolded α-synuclein proteins, exhibit notable clinical heterogeneity. This may be due to variations in accumulation patterns of LB neuropathology. Here we apply a data-driven disease progression model to regional neuropathological LB density scores from 814 brain donors with Lewy pathology. We describe three inferred trajectories of LB pathology that are characterized by differing clinicopathological presentation and longitudinal antemortem clinical progression. Most donors (81.9%) show earliest pathology in the olfactory bulb, followed by accumulation in either limbic (60.8%) or brainstem (21.1%) regions. The remaining donors (18.1%) initially exhibit abnormalities in brainstem regions. Early limbic pathology is associated with Alzheimer’s disease-associated characteristics while early brainstem pathology is associated with progressive motor impairment and substantial LB pathology outside of the brain. Our data provides evidence for heterogeneity in the temporal spread of LB pathology, possibly explaining some of the clinical disparities observed in Lewy body disease.
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  • Menkveld, Albert J., et al. (författare)
  • Nonstandard Errors
  • 2024
  • Ingår i: JOURNAL OF FINANCE. - : Wiley-Blackwell. - 0022-1082 .- 1540-6261. ; 79:3, s. 2339-2390
  • Tidskriftsartikel (refereegranskat)abstract
    • In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty-nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
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  • Resultat 1-4 av 4

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