2025-07-03 15:31 |
[DZNE-2025-00778]
Journal Article
Haase, R. ; Pinetz, T. ; Kobler, E. ; et al
Deep Learning-Based Signal Amplification of T1-Weighted Single-Dose Images Improves Metastasis Detection in Brain MRI.
Double-dose contrast-enhanced brain imaging improves tumor delineation and detection of occult metastases but is limited by concerns about gadolinium-based contrast agents' effects on patients and the environment. The purpose of this study was to test the benefit of a deep learning-based contrast signal amplification in true single-dose T1-weighted (T-SD) images creating artificial double-dose (A-DD) images for metastasis detection in brain magnetic resonance imaging.In this prospective, multicenter study, a deep learning-based method originally trained on noncontrast, low-dose, and T-SD brain images was applied to T-SD images of 30 participants (mean age ± SD, 58.5 ± 11.8 years; 23 women) acquired externally between November 2022 and June 2023. [...]
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2025-07-03 15:28 |
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2025-07-03 15:27 |
[DZNE-2025-00776]
Journal Article (Review Article)
Falgàs, N. ; Maure-Blesa, L. ; Ances, B. ; et al
Genetically determined Alzheimer's disease research advances: The Down Syndrome & Autosomal Dominant Alzheimer's Disease 2024 Conference.
The Down syndrome-associated Alzheimer's disease (DSAD) autosomal dominant Alzheimer's disease (ADAD) 2024 Conference in Barcelona, convened under an Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART) grant through the Down syndrome and Alzheimer's disease (AD) Professional Interest Area (PIA), brought together global researchers to foster collaboration and knowledge exchange between the fields of DSAD and ADAD.This article provides a synthesis review of the conference proceedings, summarizing key discussions on biomarkers, natural history models, clinical trials, and ethical considerations in anti-amyloid therapies.A total of 211 attendees from 16 countries joined the meeting. Global researchers presented on disease mechanisms, therapeutic developments, and patient care strategies. [...]
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2025-07-03 15:24 |
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2025-07-03 13:30 |
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2025-07-03 13:29 |
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2025-07-03 11:00 |
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2025-07-03 10:44 |
[DZNE-2025-00771]
Journal Article
Büschgens, L. ; Hempel, N. ; Methi, A. ; et al
Behavioral assessment and gene expression changes in a mouse model with dysfunctional STAT1 signaling.
Signal transduction via the Signal Transducer and Activator of Transcription 1 (STAT1) pathway is indispensable for mediating the intracellular effects of interferon-α (IFN-α), interferon-γ (IFN-γ) and other cytokines in the brain and, thereby, crucial for antiviral and antibacterial responses during potential life-threatening CNS infections. However, the role of STAT1 signaling beyond the known IFN-α and IFN-γ effects in immediate antimicrobial defense is highly context-dependent, and studies in the existing literature using STAT1-targeted mouse models under normal physiological conditions remain scarce.Here, we characterized a STAT1 targeted-disruption mouse model in the absence of infectious stimuli by employing established behavioral testing paradigms and immunohistochemical stainings, as well as bulk hippocampal transcriptomic and proteomic analyses.While we found neither overt behavioral alterations nor immunohistochemical changes with respect to microglial phagocytosis or proliferation, significant alterations were detected in gene and protein expression profiles implicated in neuroinflammatory processes and neuroprotection.In summary, this study highlights the complex and context-dependent role of STAT1-mediated signaling even in the absence of any detectable behavioral and neuropathological changes..
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2025-07-03 10:42 |
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2025-07-03 10:40 |
[DZNE-2025-00769]
Journal Article
Breimann, S. ; Kamp, F. ; Basset, G. ; et al
Charting γ-secretase substrates by explainable AI.
Proteases recognize substrates by decoding sequence information-an essential cellular process elusive when recognition motifs are absent. Here, we unravel this problem for γ-secretase, an intramembrane-cleaving protease associated with Alzheimer's disease and cancer, by developing Comparative Physicochemical Profiling (CPP), a sequence-based algorithm for identifying interpretable physicochemical features. [...]
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