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  • NYU Dataset

    CpG Oligodeoxynucleotides Improves Alzheimer’s Disease Pathology in Aged Squirrel Monkeys

    Authors
    Akash G. Patel
    Pramod N. Nehete
    Sara R. Krivoshik
    Xuewei Pei
    7 more author(s)...
    Description

    Previous studies showed that harnessing innate immunity via CpG oligodeoxynucleotides (ODNs) modulates age-related defects. This study used elderly female squirrel monkeys as model of sporadic Alzheimer’s disease pathology. Current immunotherapeutic trials for Alzheimer’s disease have amyloid-related imaging flaws, which are linked to the presence of cerebral amyloid angiopathy (CAA). Therefore, the...

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  • NYU Dataset

    Development of Long-Term Vagus Nerve Stimulation in Mouse Model

    Authors
    Ibrahim T. Mughrabi
    Jordan Hickman
    Naveen Jayaprakash
    Dane Thompson
    13 more author(s)...
    Description

    This study developed a scalable model for long-term vagus nerve stimulation (VNS) in mice. For this study, C57BL/6 mice were used in all experiments. The dataset includes histology and immunohistochemistry data as well as supplementary data tied to the publication. The supplementary data includes data that was used to assemble different figures in the publication, which contains data about heart rate...

    Subject
    Chronic Disease
    Neuroscience
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  • NYU Dataset

    Neural Circuitry for Maternal Oxytocin Release Induced by Infant Cries

    Authors
    Silvana Valtcheva
    Habon A. Issa
    Chloe J. Bair-Marshall
    Kathleen A. Martin
    4 more author(s)...
    Description

    Oxytocin is a neuropeptide released in the central nervous system, which is involved in a wide range of behaviors including reproduction, parental care, and pair bonding. In addition, peripheral oxytocin is important for milk ejection during nursing and uterine contractions during labor. Oxytocin is produced mainly in the paraventricular nucleus (PVN) and supraoptic nucleus of the hypothalamus. This...

    Subject
    Neuroscience
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  • NYU Dataset

    Mapping the Landscape of Histomorphological Cancer Phenotypes Using Self-Supervised Learning on Unannotated Pathology Slides

    Authors
    Adalberto Claudio Quiros
    Nicolas Coudray
    Anna H. Yeaton
    Xinyu Yang
    12 more author(s)...
    Description

    Histomorphological Phenotype Learning (HPL) was developed as a self-supervised methodology to discriminatory features in microscopy images to aid in cancer diagnosis and management. The methodology partitions whole slide images (WSIs) into meaningful Histomorphological Phenotype Clusters (HPCs) that can be used to define and quantify morphological phenotypes which recur within and between cases. HPL...

    Subject
    Cancer
    Chronic Disease
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