Binaural beat (BB), as a non-invasive auditory beat stimulation type, has found its potential applications in cognitive domains. This review presents a proper summary to deepen our understanding of the soundness of the BB technique by looking into its applications, possible mechanisms of action, effectiveness, limitations, and potential side effects. BB has been claimed to improve cognitive and psychological functions such as memory, attention, stress, anxiety, motivation, and confidence. We have also looked into preclinical and clinical research studies that have been performed using BB and proposed changes in the brain following the application of BB stimulations, including EEG changes. This review also presents applications outside the cognitive domain and evaluates BB as a possible treatment method.
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http://dx.doi.org/10.32598/bcn.2022.1406.2 | DOI Listing |
Geroscience
January 2025
National Institute On Aging, Bethesda, MD, USA.
Photobiomodulation (PBM) therapy, a non-thermal light therapy using nonionizing light sources, has shown therapeutic potential across diverse biological processes, including aging and age-associated diseases. In 2023, scientists from the National Institute on Aging (NIA) Intramural and Extramural programs convened a workshop on the topic of PBM to discuss various proposed mechanisms of PBM action, including the stimulation of mitochondrial cytochrome C oxidase, modulation of cell membrane transporters and receptors, and the activation of transforming growth factor-β1. They also reviewed potential therapeutic applications of PBM across a range of conditions, including cardiovascular disease, retinal disease, Parkinson's disease, and cognitive impairment.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Endocrinology and Nutrition, Hospital de la Santa Creu i Sant Pau, IR-SANT PAU, CIBERER-U747 ISCIII, ENDO-ERN, Barcelona, Spain.
Increasing evidence supports the presence of oxytocin deficiency (OXT-D) in patients with hypopituitarism and hypothalamic damage (HHD), that might be associated with neuropsychological deficits and sexual dysfunction, leading to worse quality of life (QoL). Therefore, identifying a provocative test to diagnose an OXT-D will be important. Corticotropin-releasing hormone (CRH) is a candidate for such a test as it increases oxytocin secretion in animal models.
View Article and Find Full Text PDFPharmacogenomics
January 2025
School of Pharmacy, Faculty of Health and Behavioural Sciences, University of Queensland, Woolloongabba, Australia.
Aims: To ascertain and describe pharmacogenomic concepts included in the intended curriculum of accredited Australian medical schools.
Methods: Content analysis of curriculum learning objectives of Australian medical schools was conducted, focusing on keywords and phrases pertaining to pharmacogenomic education. Learning objectives related to pharmacogenomics were categorized using (1) undergraduate medical genomic competencies per the Association of Professors in Human and Medical Genetics (2) Bloom's Taxonomy for cognitive and knowledge dimensions and (3) knowledge translation (enabling science, translation science and clinical implementation).
Plast Reconstr Surg Glob Open
January 2025
Department of Computer Science, Johns Hopkins University, Baltimore, MD.
Artificial intelligence (AI) scribe applications in the healthcare community are in the early adoption phase and offer unprecedented efficiency for medical documentation. They typically use an application programming interface with a large language model (LLM), for example, generative pretrained transformer 4. They use automatic speech recognition on the physician-patient interaction, generating a full medical note for the encounter, together with a draft follow-up e-mail for the patient and, often, recommendations, all within seconds or minutes.
View Article and Find Full Text PDFAlzheimers Dement (N Y)
January 2025
Indiana Alzheimer Disease Research Center and Center for Neuroimaging, Department of Radiology and Imaging Sciences Indiana University School of Medicine Indianapolis Indiana USA.
Introduction: The exponential growth of genomic datasets necessitates advanced analytical tools to effectively identify genetic loci from large-scale high throughput sequencing data. This study presents Deep-Block, a multi-stage deep learning framework that incorporates biological knowledge into its AI architecture to identify genetic regions as significantly associated with Alzheimer's disease (AD). The framework employs a three-stage approach: (1) genome segmentation based on linkage disequilibrium (LD) patterns, (2) selection of relevant LD blocks using sparse attention mechanisms, and (3) application of TabNet and Random Forest algorithms to quantify single nucleotide polymorphism (SNP) feature importance, thereby identifying genetic factors contributing to AD risk.
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