Publications by authors named "Hanna Gwendolyn Zimmermann"

Background: Hyperreflective retinal foci (HRF) visualized by optical coherence tomography (OCT) potentially represent clusters of microglia. We compared HRF frequencies and their association with retinal neurodegeneration between people with clinically isolated syndrome (pwCIS), multiple sclerosis (pwMS), aquaporin 4-IgG positive neuromyelitis optica spectrum disorder (pwNMOSD), and healthy controls (HC)-as well as between eyes with (ONeyes) and without a history of optic neuritis (ONeyes).

Methods: Cross-sectional data of pwCIS, pwMS, and pwNMOSD with previous ON and HC were acquired at Charité-Universitätsmedizin Berlin.

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The sequela of COVID-19 include a broad spectrum of symptoms that fall under the umbrella term post-COVID-19 condition or syndrome (PCS). Immune dysregulation, autoimmunity, endothelial dysfunction, viral persistence, and viral reactivation have been identified as potential mechanisms. However, there is heterogeneity in expression of biomarkers, and it is unknown yet whether these distinguish different clinical subgroups of PCS.

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Multiple sclerosis (MS) is an autoimmune inflammatory and neurodegenerative disease of the central nervous system (CNS) with increasing incidence and prevalence. MS is associated with inflammatory and metabolic disturbances that, as preliminary human and animal data suggest, might be mediated by disruption of circadian rhythmicity. Nutrition habits can influence the risk for MS, and dietary interventions may be effective in modulating MS disease course.

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Article Synopsis
  • Reliable biomarkers for conditions like Multiple Sclerosis, Alzheimer's, and Parkinson's are necessary but lacking, and intraretinal layer thickness from OCT images shows promise despite challenges in subtle changes and weak tissue gradients.
  • The proposed solution is a two-stage network called CCU-INSEG that effectively segments retinal tissues and eight intraretinal layers, using a refined method for post-processing and improved training techniques to address data imbalance.
  • The CCU-INSEG method demonstrates significant accuracy, achieving mean absolute errors of 2.3 μm and 2.6 μm compared to manual segmentation, and it outperforms existing methods, providing a more reliable approach for future research and clinical applications.
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