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MR imaging of proton beam-induced oxygen depletion.

Med Phys

January 2025

OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany.

Background: Previous studies have shown that in-beam magnetic resonance imaging (MRI) can be used to visualize a proton beam during the irradiation of liquid-filled phantoms. The beam energy- and current-dependent local image contrast observed in water was identified to be predominantly caused by beam-induced buoyant convection and associated flow effects. Besides this flow dependency, the MR signal change was found to be characterized by a change in the relaxation time of water, hinting at a radiochemical contribution, which was hypothesized to lie in oxygen depletion-evoked relaxation time lengthening.

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During the harvest of Ilex paraguariensis, approximately 2-5 tons per hectare of thick stems are left on the soil surface. The outer portion of these stems, referred to as the coproduct, constitutes 30% of the total residue mass. Although this coproduct has been partially characterized in terms of its phytochemical profile, its technological applications remain unexplored.

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Background/purpose: Studies have demonstrated a relation between hypercholesterolemia and development of apical periodontitis (AP), but the underlying mechanism is uncertain. 27-hydroxycholesterol (27HC), produced by cytochrome P450 27A1 (CYP27A1)-catalyzed hydroxylation of cholesterol, is known to possess pro-inflammatory activity. Felodipine is an anti-hypertensive agent able to inhibit CYP27A1.

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Background: Epidemiological investigations have revealed a significant association between alcohol consumption and chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS). Nevertheless, the potential mechanisms are still inadequately revealed. This research aimed to investigate the impact of alcohol on CP/CPPS using an animal model and to elucidate the underlying mechanisms.

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Introduction: Weeds are a major factor affecting crop yield and quality. Accurate identification and localization of crops and weeds are essential for achieving automated weed management in precision agriculture, especially given the challenges in recognition accuracy and real-time processing in complex field environments. To address this issue, this paper proposes an efficient crop-weed segmentation model based on an improved UNet architecture and attention mechanisms to enhance both recognition accuracy and processing speed.

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