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Waterlogging is a significant stressor for crops, particularly in lowland regions where soil conditions exacerbate the problem. Waterlogged roots experience hypoxia, disrupting oxidative phosphorylation and triggering metabolic reorganization to sustain energy production. Here, we investigated the metabolic aspects that differentiate two soybean sister lines contrasting for waterlogging tolerance.

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Deep learning has emerged as a powerful tool in medical imaging, particularly for corneal topographic map classification. However, the scarcity of labeled data poses a significant challenge to achieving robust performance. This study investigates the impact of various data augmentation strategies on enhancing the performance of a customized convolutional neural network model for corneal topographic map classification.

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Maternal Cannabis Use During Pregnancy and Neuropsychiatric Adverse Outcomes During Childhood and Early Adult Life.

J Clin Psychiatry

January 2025

Department of Psychiatry, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India, Department of Clinical Psychopharmacology and Neurotoxicology, National Institute of Mental Health and Neurosciences, Bangalore, India

Cannabis use during pregnancy is increasing; the study of adverse outcomes in cannabis-exposed pregnancies is therefore important. Previous articles in this series described increased risks of maternal adverse outcomes, fetal adverse outcomes, birth defects in newborns, and autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) in childhood. This article examines neuropsychiatric adverse outcomes in offspring gestationally exposed to cannabis.

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Background: The underreporting of vital statistics poses a problem for the quality of information. To address underreporting, Mexico implemented the "Intentional Search for Children Deaths" in 2002.

Objective: To analyze trends in the underreporting of deaths in neonates and children under 5 years of age (U5) from 1992 to 2022 at the national level and by state.

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Motivation: The drug-disease, gene-disease, and drug-gene relationships, as high-frequency edge types, describe complex biological processes within the biomedical knowledge graph. The structural patterns formed by these three edges are the graph motifs of (disease, drug, gene) triplets. Among them, the triangle is a steady and important motif structure in the network, and other various motifs different from the triangle also indicate rich semantic relationships.

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