Background: Despite early diagnosis and compliance with phenylalanine (Phe)-restricted diets, many individuals with phenylketonuria (PKU) still exhibit neurological changes and experience deficits in working memory and other executive functions. Suboptimal choline intake may contribute to these impairments, but this relationship has not been previously investigated in PKU. The objective of this study was to determine if choline intake is correlated with working memory performance, and if this relationship is modified by diagnosis and metabolic control.
Methods: This was a cross-sectional study that included 40 adults with PKU and 40 demographically matched healthy adults. Web-based neurocognitive tests were used to assess working memory performance and 3-day dietary records were collected to evaluate nutrient intake. Recent and historical blood Phe concentrations were collected as measures of metabolic control.
Results: Working memory performance was 0.32 z-scores (95% CI 0.06, 0.58) lower, on average, in participants with PKU compared to participants without PKU, and this difference was not modified by total choline intake (F[1,75] = 0.85, p = 0.36). However, in a subgroup with complete historical blood Phe data, increased total choline intake was related to improved working memory outcomes among participants with well controlled PKU (Phe = 360 µmol/L) after adjusting for intellectual ability and mid-childhood Phe concentrations (average change in working memory per 100 mg change in choline = 0.11; 95% CI 0.02, 0.20; p = 0.02). There also was a trend, albeit nonsignificant (p = 0.10), for this association to be attenuated with increased Phe concentrations.
Conclusions: Clinical monitoring of choline intake is essential for all individuals with PKU but may have important implications for working memory functioning among patients with good metabolic control. Results from this study should be confirmed in a larger controlled trial in people living with PKU.
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http://dx.doi.org/10.1186/s13023-023-02842-y | DOI Listing |
Humans excel at applying learned behavior to unlearned situations. A crucial component of this generalization behavior is our ability to compose/decompose a whole into reusable parts, an attribute known as compositionality. One of the fundamental questions in robotics concerns this characteristic: How can linguistic compositionality be developed concomitantly with sensorimotor skills through associative learning, particularly when individuals only learn partial linguistic compositions and their corresponding sensorimotor patterns? To address this question, we propose a brain-inspired neural network model that integrates vision, proprioception, and language into a framework of predictive coding and active inference on the basis of the free-energy principle.
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January 2025
Equipe de Recherche Contextes et Acteurs de l'Education (ERCAé), Université d'Orléans, Orléans, France.
Recent research has revealed the widespread effects of emotion on cognitive functions and memory. However, the influence of emotional valence on verbal short-term memory remains largely unexplored, especially in children. This study measured the effect of emotional valence on word immediate serial recall in 4-6-year-old French children ( = 124).
View Article and Find Full Text PDFFront Neurosci
January 2025
Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States.
Introduction: , a protein kinase located on human chromosome 21, plays a role in postembryonic neuronal development and degeneration. Alterations to have been consistently associated with cognitive functioning and neurodevelopmental disorders (e.g.
View Article and Find Full Text PDFClin Neuropsychiatry
December 2024
IRCCS Stella Maris Foundation, Pisa, Italy.
Objective: To describe the relationship between executive functions (EF) and symptom's severity, behavioral problems, and adaptive functioning in autistic preschoolers.
Method: Seventy-six autistic preschoolers (age-range: 37-72 months; SD: 8.67 months) without intellectual disability were assessed.
Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi
December 2024
Anhui Provincial Center for Disease Control and Prevention, Hefei, Anhui 230601, China.
Objective: To predict the areas of snail spread in Anhui Province from 1977 to 2023 using machine learning models, and to compare the effectiveness of different machine learning models for prediction of areas of snail spread, so as to provide insights into investigating the trends in areas of snail spread.
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