In the context of slow-fast behavioral variation, fast individuals are hypothesized to be those who prioritize speed over accuracy while slow individuals are those which do the opposite. Since energy metabolism is a critical component of neural and cognitive functioning, this predicts such differences in cognitive style to be reflected at the level of the brain. We tested this idea in honeybees by first classifying individuals into slow and fast cognitive phenotypes based on a learning assay and then measuring their brain respiration with high-resolution respirometry. Our results broadly show that inter-individual differences in cognition are reflected in differences in brain mass and accompanying energy use at the level of the brain and the whole animal. Larger brains had lower mass-specific energy usage and bees with larger brains had a higher metabolic rate. These differences in brain respiration and brain mass were, in turn, associated with cognitive differences, such that bees with larger brains were fast cognitive phenotypes whereas those with smaller brains were slow cognitive phenotypes. We discuss these results in the context of the role of energy in brain functioning and slow-fast decision making and speed accuracy trade-off.
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http://dx.doi.org/10.1242/jeb.247835 | DOI Listing |
Int J Geriatr Psychiatry
January 2025
Precision Neuroscience & Neuromodulation Program, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Background: Alzheimer's disease (AD) is characterized by impaired inhibitory circuitry and GABAergic dysfunction, which is associated with reduced fast brain oscillations in the gamma band (γ, 30-90 Hz) in several animal models. Investigating such activity in human patients could lead to the identification of novel biomarkers of diagnostic and prognostic value. The current study aimed to test a multimodal "Perturbation-based" transcranial Alternating Current Stimulation-Electroencephalography (tACS)-EEG protocol to detect how responses to tACS in AD patients correlate with patients' clinical phenotype.
View Article and Find Full Text PDFNutr Bull
January 2025
Curtin School of Population Health, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia.
Sarcopenic obesity (SO) is a body composition phenotype derived from the simultaneous presence in the same individual of an increase in fat mass and a decrease in skeletal muscle mass and/or function. Several protocols for the diagnosis of SO have been proposed in the last two decades making prevalence and disease risk estimates of SO heterogeneous and challenging to interpret. Dementia is a complex neurological disorder that significantly impacts patients, carers and healthcare systems.
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Pharmacy Department, Baotou Central Hospital, Baotou, 014040, Inner Mongolia, China.
Microglial polarization and ferroptosis are important pathological features in Alzheimer's disease (AD). Ghrelin, a brain-gut hormone, has potential neuroprotective effects in AD. This study aimed to explore the potential mechanisms by which ghrelin regulates the progression of AD, as well as the crosstalk between microglial polarization and ferroptosis.
View Article and Find Full Text PDFInt J Mol Sci
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Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, 08029 Barcelona, Spain.
High-throughput proteomic platforms are crucial to identify novel Alzheimer's disease (AD) biomarkers and pathways. In this study, we evaluated the reproducibility and reliability of aptamer-based (SomaScan 7k) and antibody-based (Olink Explore 3k) proteomic platforms in cerebrospinal fluid (CSF) samples from the Ace Alzheimer Center Barcelona real-world cohort. Intra- and inter-platform reproducibility were evaluated through correlations between two independent SomaScan assays analyzing the same samples, and between SomaScan and Olink results.
View Article and Find Full Text PDFNeurol Sci
January 2025
Center for Neurodegenerative Diseases (CEMAND), Department of Medicine, Surgery and Dentistry, "Scuola Medica Salernitana", University of Salerno, Salerno, Italy.
Due to the variety of clinical phenotypes and the massive clinical overlap with other neurodegenerative diseases, the diagnosis of Progressive Supranuclear Palsy (PSP) remains a major challenge. Notwithstanding, early and reliable clinical diagnosis of PSP is highly warranted for estimation of prognosis, appropriate allocation to therapeutic trials and development of new diagnostic tools. As reliable biomarkers are lacking, PSP diagnosis relies on the application of the clinical criteria promoted by the International Parkinson and Movement Disorder Society (MDS).
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