Omega-3 fatty acid (n-3 PUFA) intake is associated with improved mood and cognition, but randomized controlled trials addressing the causal nature of such relationships are less clear, especially in healthy, young adults. Stress is one potential mechanism by which n-3 PUFAs may influence mood. Thus the present aim is to evaluate the influence of n-3 PUFA supplementation on stress-induced changes to mood, cognition, and physiological stress markers in healthy, young adults. Using a double-blind, placebo-controlled design, 72 young adults were randomized to receive 2800mg/day fish oil (n=36, 23 females) or olive oil control (n=36, 22 females) for 35days. Subjects completed measures of mood and cognition before supplementation, and two times after supplementation: following an acute stressor or non-stressful control task. The stress induction was effective in that the stressor impaired mood, including augmenting feelings of tension, anger, confusion and anxiety, reduced accuracy on a cognitive task measuring attentional control and the ability to regulate emotion, and increased salivary cortisol and pro-inflammatory cytokine interleukin-1β (IL-1β). Rated anger and confusion increased with stress in the olive oil group, but remained stable in the fish oil group. However, fish oil had no further effects on mood, cognitive function, cortisol, or IL-1β. Fish oil exerted few effects in stressful and non-stressful situations, consistent with findings showing little influence of n-3 PUFA supplementation on mood and cognition in young, healthy individuals. Potential target populations who would more likely benefit from increased n-3 PUFA intake are discussed.
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http://dx.doi.org/10.1016/j.pbb.2015.02.018 | DOI Listing |
The current study aims to determine how the interactions between practice (distributed/focused) and mental capacity (high/low) in the cloud-computing environment (CCE) affect the development of reproductive health skills and cognitive absorption. The study employed an experimental design, and it included a categorical variable for mental capacity (low/high) and an independent variable with two types of activities (distributed/focused). The research sample consisted of 240 students from the College of Science and College of Applied Medical Sciences at the University of Hail's.
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December 2024
Center for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, 1001 S McAllister Ave, Tempe, AZ 85281, USA.
Alzheimer's disease (AD) and Alzheimer's Related Dementias (ADRD) are projected to affect 50 million people globally in the coming decades. Clinical research suggests that Mild Cognitive Impairment (MCI), a precursor to dementia, offers a critical window of opportunity for lifestyle interventions to delay or prevent the progression of AD/ADRD. Previous research indicates that lifestyle changes, including increased physical exercise, reduced caloric intake, and mentally stimulating activities, can reduce the risk of MCI.
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December 2024
Department of Psychology, University of Turin, 10124 Turin, Italy.
This study examines the relationship between cognitive and affective flexibility, two critical aspects of adaptability. Cognitive flexibility involves switching between activities as rules change, assessed through task-switching or neuropsychological tests and questionnaires. Affective flexibility, meanwhile, refers to shifting between emotional and non-emotional tasks or states.
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December 2024
College of Design and Innovation, Tongji University, Shanghai 200092, China.
As the global traffic environment becomes increasingly complex, driving safety issues have become more prominent, making manual-response driving warning systems (DWSs) essential. Augmented reality head-up display (AR-HUD) technology can project information directly, enhancing driver attention; however, improper design may increase cognitive load and affect safety. Thus, the design of AR-HUD driving warning interfaces must focus on improving attention and reducing cognitive load.
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December 2024
Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USA.
Understanding sleep stages is crucial for diagnosing sleep disorders, developing treatments, and studying sleep's impact on overall health. With the growing availability of affordable brain monitoring devices, the volume of collected brain data has increased significantly. However, analyzing these data, particularly when using the gold standard multi-lead electroencephalogram (EEG), remains resource-intensive and time-consuming.
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