Publications by authors named "A A Abughazaleh"

Purpose: Microsurgical reconstruction, including vascularized lymph node transfer (VLNT) and lymphaticovenous anastomosis (LVA), have emerged as promising treatment options for chronic breast cancer-related lymphedema (BCRL). Despite their clinical relevance, the precise timelines for patient improvement following these interventions remain rather unexplored. Therefore, the goal of this study was to compare the long-term outcomes and improvement patterns over time of VLNT versus LVA to lay open potential differences and aid in personalized counseling of future patients.

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Expanded agriculture production is required to support the world's population but can impose substantial environmental and climate change costs, particularly with intensifying animal production and protein demand. Shifting from an animal- to a plant-based protein diet has numerous health benefits. Soybean (Glycine max [L.

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Background: Laboratory-scale experiments have shown that treatment with selective lignin-degrading white-rot fungi improves the nutritional value and ruminal degradability of lignocellulosic biomass (LCB). However, the lack of effective field-applicable pasteurization methods has long been recognized as a major obstacle for scaling up the technique for fungal treatment of large quantities of LCB for animal feeding. In this study, wheat straw (an LCB substrate) was subjected to four field-applicable pasteurization methods - hot-water, formaldehyde fumigation, steam, and hydrated lime - and cultured with Pleurotus ostreatus grain spawn for 10, 20, and 30 days under solid-state fermentation.

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The increasing number of melanoma patients makes it necessary to develop best possible strategies for prognosis assessment in order to recommend appropriate therapy and follow-up. The prognostic significance of tumor cell pigmentation has not been fully elucidated. Hematoxylin and eosin (H&E)-stained sections of 775 melanomas diagnosed between 2012 and 2015 were independently assessed for melanin pigment abundance by two investigators, and the impact on melanoma-specific survival was calculated.

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Background: The increasing number of melanoma patients makes it necessary to establish new strategies for prognosis assessment to ensure follow-up care. Deep-learning-based image analysis of primary melanoma could be a future component of risk stratification.

Objectives: To develop a risk score for overall survival based on image analysis through artificial intelligence (AI) and validate it in a test cohort.

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