Circadian Clocks as Modulators of Metabolic Comorbidity in Psychiatric Disorders

Psychiatric disorders such as schizophrenia, bipolar disorder, and major depressive disorder are often accompanied by metabolic dysfunction symptoms, including obesity and diabetes. Since the circadian system controls important brain systems that regulate affective, cognitive, and metabolic functions, and neuropsychiatric and metabolic diseases are often correlated with disturbances of circadian rhythms, we hypothesize that dysregulation of circadian clocks plays a central role in metabolic comorbidity in psychiatric disorders. In this review paper, we highlight the role of circadian clocks in glucocorticoid, dopamine, and orexin/melanin-concentrating hormone systems and describe how a dysfunction of these clocks may contribute to the simultaneous development of psychiatric and metabolic symptoms

A Framework for Infrastructure-Free Indoor Localization Based on Pervasive Sound Analysis

Even as modern indoor positioning systems become more precise and computationally lightweight, most rely on specific infrastructure to be installed, leading to increased setup and maintenance costs. As such, multiple infrastructure-free solutions were devised relying on signals such as magnetic field, ambient light, and movement. In this paper, we propose a framework for determining the user's location through the sound recorded by the user's device. With this goal, we present two algorithms: SoundSignature and SoundSimilarity. With SoundSignature, we extract acoustic fingerprints from the recorded audio and employ them in a support vector machine classifier. With SoundSimilarity, where we employ a novel audio similarity measure to detect if users are in the same location as other users or microphone equipped devices. Both of these algorithms require no infrastructure and are computationally lightweight, thus allowing their use either in conjunction with other infrastructure-free technologies or standalone. The training of these algorithms requires nothing more than a smartphone or a similar device under normal usage conditions, eliminating the need of any dedicated equipment

Nutrition and Central Nervous System

Clinical studies have revealed that depression is accompanied by impaired brain function and cognitive performances or neurodegenerative processes. Moreover, accumulation of oxidative damage has been implicated in aging and various neurological disorders. This chapter aims to integrate the current knowledge on the relation between brain and diverse alterations in nutrition. The mammalian brain is a lipid-rich organ, where lipids content in gray matter is 36–40% lipid. However, the regulation of cholesterol transport from astrocytes to neurons still remains unclear, among other things. In addition to that, micronutrient status can affect cognitive function at all ages. Vitamin deficiency could influence memory function, and might contribute to cognitive impairment and dementia. Deficiency of vitamin A, folate, vitamins B6, B12, and minerals such as Fe and Zn are associated with prevalence of depressive symptoms according to several epidemiological studies. Experimental evidence suggests that resveratrol, vitamins A, C, E, D and folate may block oxidative stress and promote clearance of Aβ peptides. An adequate intake of fruit, nuts, vegetables, cereals, legumes, or fish can prevent the depletion. High dietary intake of saturated fat and low intake of vegetables may be associated with increased risk of Alzheimer’s disease. Supplementation of diets with omega-3 has been shown to have positive effects on cognitive function. The biochemical and molecular mechanism of these alterations of normal brain function has been described. Future studies should also examine how DNA repair deficiency occurs and affects the nervous system, because this could provide a rational basis for therapies in neurodegenerative diseases.Fil: Alvarez, Silvina Monica. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis; ArgentinaFil: Gomez, Nidia Noemí. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis; ArgentinaFil: Navigatore Fonzo, Lorena Silvina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis; ArgentinaFil: Sanchez, Emilse Silvina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis; ArgentinaFil: Gimenez, Maria Sofia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis; Argentin