Publications by authors named "M Oswald"

Background And Purpose: Leptomeningeal collaterals have been associated with better outcomes in large-vessel stroke, but little is known about how the Circle of Willis (CoW) collaterals affect stroke outcomes. We aimed to determine the relationship between three anatomically distinct CoW subtypes and 90-day outcomes in acute ischemic stroke patients after successful revascularization via endovascular thrombectomy (EVT).

Materials And Methods: We performed a retrospective analysis of patients treated with successful EVT for large-vessel occlusion at a comprehensive stroke center between May 2016 and November 2023.

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Maternal antidepressant use has increased during the past 2 decades, with venlafaxine emerging as a common agent during pregnancy. Both venlafaxine and its active metabolite possess prolonged half-lives in adults; however, abrupt discontinuation may lead to withdrawal including irritability, jitteriness, lethargy, restlessness, and insomnia. The drug and its metabolite readily cross the placenta, posing additional considerations during pregnancy.

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Article Synopsis
  • - Human alpha-defensin antimicrobial peptides, specifically human neutrophil peptide 1 (HNP1) and human defensin 5 (HD5), significantly inhibit the effectiveness of adeno-associated virus (AAV2) vectors used in gene therapy by blocking infection and preventing the virus from reaching the nucleus.
  • - HD5 stops AAV2 from binding to cells, while HNP1 does not, but both defensins interfere with key viral processes that are necessary for the virus's success in infecting cells.
  • - These findings suggest a shared mechanism of action among alpha-defensins in neutralizing various non-enveloped viruses, which could lead to advancements in developing more effective gene therapy vectors that can overcome innate immune barriers.
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Fluorescence polarization (Fpol) imaging of methylene blue (MB) is a promising quantitative approach to thyroid cancer detection. Clinical translation of MB Fpol technology requires reduction of the data analysis time that can be achieved via deep learning-based automated cell segmentation with a 2D U-Net convolutional neural network. The model was trained and tested using images of pathologically diverse human thyroid cells and evaluated by comparing the number of cells selected, segmented areas, and Fpol values obtained using automated (AU) and manual (MA) data processing methods.

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