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1.
Dev Cell ; 56(20): 2871-2885.e6, 2021 10 25.
Article in English | MEDLINE | ID: mdl-34428430

ABSTRACT

The mechanism of vulnerability to pediatric low-grade gliomas (pLGGs)-the most common brain tumor in children-during development remains largely unknown. Using mouse models of neurofibromatosis type 1 (NF1)-associated pLGGs in the optic pathway (NF1-OPG), we demonstrate that NF1-OPG arose from the vulnerability to the dependency of Mek-Erk/MAPK signaling during gliogenesis of one of the two developmentally transient precursor populations in the optic nerve, brain-derived migrating glial progenitors (GPs), but not local progenitors. Hyperactive Erk/MAPK signaling by Nf1 loss overproduced GPs by disrupting the balance between stem-cell maintenance and gliogenesis of hypothalamic ventricular zone radial glia (RG). Persistence of RG-like GPs initiated NF1-OPG, causing Bax-dependent apoptosis in retinal ganglion cells. Removal of three Mek1/Mek2 alleles or transient post-natal treatment with a low-dose MEK inhibitor normalized differentiation of Nf1-/- RG-like GPs, preventing NF1-OPG formation and neuronal degeneration. We provide the proof-of-concept evidence for preventing pLGGs before tumor-associated neurological damage enters an irreversible phase.


Subject(s)
MAP Kinase Signaling System/physiology , Neurofibromatosis 1/therapy , Optic Nerve Glioma/therapy , Stem Cells/cytology , Animals , Brain Neoplasms/metabolism , Brain Neoplasms/therapy , Disease Models, Animal , Eye/metabolism , Mice , Neurofibromatosis 1/metabolism , Neurofibromatosis 1/pathology , Neuroglia/metabolism , Optic Nerve/pathology , Optic Nerve Glioma/metabolism , Optic Nerve Glioma/pathology
2.
Nutrients ; 11(3)2019 Mar 14.
Article in English | MEDLINE | ID: mdl-30875772

ABSTRACT

(1) Background: Smartphone dietary assessment apps can be acceptable and valid data collection methods but have predominantly been validated in highly educated women, and none specifically measured eating-out habits in young adults. (2) Methods: Participants recorded their food and beverage consumption for three days using the Eat and Track (EaT) app, and intakes were compared with three dietitian-administered 24-h recall interviews matched to the same days as the reference method. Wilcoxon signed-rank or t-tests, correlation coefficients and Bland⁻Altman plots assessed agreement between the two methods for energy and percentage energy from nutrients (%E). (3) Results: One hundred and eighty nine of 216 participants (54% females, 60% resided in higher socioeconomic areas, 49% university-educated) completed the study. There were significant differences in median energy intake between methods (p < 0.001), but the EaT app had acceptable agreement for most nutrient densities at the group level. Correlation coefficients ranged from r = 0.56 (%E fat) to 0.82 (%E sugars), and between 85% and 94% of participants were cross-classified into the same or adjacent quartiles. Bland⁻Altman plots showed wide limits of agreement but no obvious biases for nutrient densities except carbohydrate in males. (4) Conclusions: The EaT app can be used to assess group nutrient densities in a general population of 18-to-30-year olds.


Subject(s)
Diet Records , Diet Surveys/methods , Diet Surveys/standards , Mobile Applications , Smartphone , Adolescent , Adult , Australia , Energy Intake , Female , Humans , Male , Reproducibility of Results , Young Adult
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