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Generative adversarial network integrated with metabolomics identifies potential biomarkers related to quality changes of atemoya (Annona cherimola × Annona squamosa) stored at 10 and 25 °C.
Food Chem
December 2024
Department of Food Science and Technology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China. Electronic address:
Atemoya fruit deteriorates rapidly during post-harvest storage. A complete understanding of the metabolic mechanisms underlying this process is crucial for developing effective preservation strategies. Metabolomic approaches combined with machine learning offer new opportunities to identify quality-related biomarkers.
View Article and Find Full Text PDFPredicting phage-host interactions via feature augmentation and regional graph convolution.
Brief Bioinform
November 2024
Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan 430079, China.
Identifying phage-host interactions (PHIs) is a crucial step in developing phage therapy, which is the promising solution to addressing the issue of antibiotic resistance in superbugs. However, the lifestyle of phages, which strongly depends on their host for life activities, limits their cultivability, making the study of predicting PHIs time-consuming and labor-intensive for traditional wet lab experiments. Although many deep learning (DL) approaches have been applied to PHIs prediction, most DL methods are predominantly based on sequence information, failing to comprehensively model the intricate relationships within PHIs.
View Article and Find Full Text PDFWeighted Echo State Graph Neural Networks Based on Robust and Epitaxial Film Memristors.
Adv Sci (Weinh)
January 2025
College of Physics Science & Technology, School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, Hebei University, Baoding, 071002, China.
Hardware system customized toward the demands of graph neural network learning would promote efficiency and strong temporal processing for graph-structured data. However, most amorphous/polycrystalline oxides-based memristors commonly have unstable conductance regulation due to random growth of conductive filaments. And graph neural networks based on robust and epitaxial film memristors can especially improve energy efficiency due to their high endurance and ultra-low power consumption.
View Article and Find Full Text PDFAssociation between a geriatric measure tool and adverse outcomes among older adults treated in an emergency department: a retrospective cohort study.
Intern Emerg Med
January 2025
Emergency Department, National Institute of Medical Sciences and Nutrition Salvador Zubiran, Avenida Vasco de Quiróga No. 15, Colonia Belisario Domínguez Sección XVI, Alcaldía Tlalpan, CP 14080, Mexico City, Mexico.
The COVID-19 pandemic provided an ideal scenario for studying the care of the elderly population, we implemented a tool named the Geriatric Measure (GM) tool to determine the severity and need for hospitalization. The objective of the study is to evaluate if the results of a brief Geriatric Measure tool are associated with mortality and other outcomes among older adults with COVID-19 treated in the emergency department. Retrospective observational cohort study.
View Article and Find Full Text PDFMachine learning techniques for non-destructive estimation of plum fruit weight.
Sci Rep
January 2025
Crop and Horticultural Science Research Department, Mazandaran Agricultural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Tajrish, Iran.
Plum fruit fresh weight (FW) estimation is crucial for various agricultural practices, including yield prediction, quality control, and market pricing. Traditional methods for estimating fruit weight are often destructive, time-consuming, and labor-intensive. In this study, we addressed the problem of predicting plum FW using artificial intelligence (AI) methods based on fruit dimensions.
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