10 resultados para Neural metabolism
em BORIS: Bern Open Repository and Information System - Berna - Suiça
Resumo:
In this paper two models for the simulation of glucose-insulin metabolism of children with Type 1 diabetes are presented. The models are based on the combined use of Compartmental Models (CMs) and artificial Neural Networks (NNs). Data from children with Type 1 diabetes, stored in a database, have been used as input to the models. The data are taken from four children with Type 1 diabetes and contain information about glucose levels taken from continuous glucose monitoring system, insulin intake and food intake, along with corresponding time. The influences of taken insulin on plasma insulin concentration, as well as the effect of food intake on glucose input into the blood from the gut, are estimated from the CMs. The outputs of CMs, along with previous glucose measurements, are fed to a NN, which provides short-term prediction of glucose values. For comparative reasons two different NN architectures have been tested: a Feed-Forward NN (FFNN) trained with the back-propagation algorithm with adaptive learning rate and momentum, and a Recurrent NN (RNN), trained with the Real Time Recurrent Learning (RTRL) algorithm. The results indicate that the best prediction performance can be achieved by the use of RNN.
Resumo:
Intra-arterial (IA) injection represents an experimental avenue for minimally invasive delivery of stem cells to the injured brain. It has however been reported that IA injection of stem cells carries the risk of reduction in cerebral blood flow (CBF) and microstrokes. Here we evaluate the safety of IA neural progenitor cell (NPC) delivery to the brain. Cerebral blood flow of rats was monitored during IA injection of single cell suspensions of NPCs after stroke. Animals received 1 × 10(6) NPCs either injected via a microneedle (microneedle group) into the patent common carotid artery (CCA) or via a catheter into the proximally ligated CCA (catheter group). Controls included saline-only injections and cell injections into non-stroked sham animals. Cerebral blood flow in the microneedle group remained at baseline, whereas in the catheter group a persistent (15 minutes) decrease to 78% of baseline occurred (P<0.001). In non-stroked controls, NPCs injected via the catheter method resulted in higher levels of Iba-1-positive inflammatory cells (P=0.003), higher numbers of degenerating neurons as seen in Fluoro-Jade C staining (P<0.0001) and ischemic changes on diffusion weighted imaging. With an appropriate technique, reduction in CBF and microstrokes do not occur with IA transplantation of NPCs.
Resumo:
Although extensive indirect evidence exists to suggest that the central dopaminergic system plays a significant role in the modulation of arousal, the functional effect of the dopaminergic influence on the regulation of the sleep-wake cycle remains unclear. Thirteen healthy volunteers and 15 unmedicated subjects with a history of major depressive disorder underwent catecholamine depletion (CD) using oral alpha-methyl-para-tyrosine in a randomized, placebo-controlled, double-blind, crossover study. The main outcome measures in both sessions were sleepiness (Stanford-Sleepiness-Scale), cerebral glucose metabolism (positron emission tomography), and serum prolactin concentration. CD consistently induced clinically relevant sleepiness in both groups. The CD-induced prolactin increase significantly correlated with CD-induced sleepiness but not with CD-induced mood and anxiety symptoms. CD-induced sleepiness correlated with CD-induced increases in metabolism in the medial and orbital frontal cortex, bilateral superior temporal cortex, left insula, cingulate motor area and in the vicinity of the periaqueductal gray. This study suggests that the association between dopamine depletion and sleepiness is independent of the brain reward system and the risk for depression. The visceromotor system, the cingulate motor area, the periaqueductal gray and the caudal hypothalamus may mediate the impact of the dopaminergic system on regulation of wakefulness and sleep.
Resumo:
Clinical studies indicate that exaggerated postprandial lipemia is linked to the progression of atherosclerosis, leading cause of Cardiovascular Diseases (CVD). CVD is a multi-factorial disease with complex etiology and according to the literature postprandial Triglycerides (TG) can be used as an independent CVD risk factor. Aim of the current study is to construct an Artificial Neural Network (ANN) based system for the identification of the most important gene-gene and/or gene-environmental interactions that contribute to a fast or slow postprandial metabolism of TG in blood and consequently to investigate the causality of postprandial TG response. The design and development of the system is based on a dataset of 213 subjects who underwent a two meals fatty prandial protocol. For each of the subjects a total of 30 input variables corresponding to genetic variations, sex, age and fasting levels of clinical measurements were known. Those variables provide input to the system, which is based on the combined use of Parameter Decreasing Method (PDM) and an ANN. The system was able to identify the ten (10) most informative variables and achieve a mean accuracy equal to 85.21%.
Resumo:
In this paper, a simulation model of glucose-insulin metabolism for Type 1 diabetes patients is presented. The proposed system is based on the combination of Compartmental Models (CMs) and artificial Neural Networks (NNs). This model aims at the development of an accurate system, in order to assist Type 1 diabetes patients to handle their blood glucose profile and recognize dangerous metabolic states. Data from a Type 1 diabetes patient, stored in a database, have been used as input to the hybrid system. The data contain information about measured blood glucose levels, insulin intake, and description of food intake, along with the corresponding time. The data are passed to three separate CMs, which produce estimations about (i) the effect of Short Acting (SA) insulin intake on blood insulin concentration, (ii) the effect of Intermediate Acting (IA) insulin intake on blood insulin concentration, and (iii) the effect of carbohydrate intake on blood glucose absorption from the gut. The outputs of the three CMs are passed to a Recurrent NN (RNN) in order to predict subsequent blood glucose levels. The RNN is trained with the Real Time Recurrent Learning (RTRL) algorithm. The resulted blood glucose predictions are promising for the use of the proposed model for blood glucose level estimation for Type 1 diabetes patients.
Resumo:
RATIONALE: Thyroid hormones and their interactions with catecholamines play a potentially important role in alterations of mood and cognition. OBJECTIVES: This study aimed to examine the neurobiological effects of catecholamine depletion on thyroid hormones by measuring endocrine and cerebral metabolic function in unmedicated subjects with remitted major depressive disorder (RMDD) and in healthy controls. METHODS: This was a randomized, placebo-controlled, and double-blind crossover trial that included 15 unmedicated RMDD subjects and 13 healthy control subjects. The participants underwent two 3-day-long sessions at 1-week intervals; each participant was randomly administered oral α-methyl-para-tyrosine in one session (catecholamine depletion) and an identical capsule containing hydrous lactose (sham depletion) in the other session prior to a [(18)F]-fluorodeoxyglucose positron emission tomography scan. RESULTS: Serum concentrations of free T3 (FT3), free T4 (FT4), and TSH were obtained and assessed with respect to their relationship to regional cerebral glucose metabolism. Both serum FT3 (P = 0.002) and FT4 (P = 0.0009) levels were less suppressed after catecholamine depletion compared with placebo treatment in the entire study sample. There was a positive association between both FT3 (P = 0.0005) and FT4 (P = 0.002) and depressive symptoms measured using the Montgomery-Åsberg Depression Rating Scale. The relative elevation in FT3 level was correlated with a decrease in regional glucose metabolism in the right dorsolateral prefrontal cortex (rDLPFC; P < 0.05, corrected). CONCLUSIONS: This study provided evidence of an association between a thyroid-catecholamine interaction and mood regulation in the rDLPFC.
Resumo:
White matter connects different brain areas and applies electrical insulation to the neuron’s axons with myelin sheaths in order to enable quick signal transmission. Due to its modulatory properties in signal conduction, white matter plays an essential role in learning, cognition and psychiatric disorders (Fields, 2008a). In respect thereof, the non-invasive investigation of white matter anatomy and function in vivo provides the unique opportunity to explore the most complex organ of our body. Thus, the present thesis aimed to apply a multimodal neuroimaging approach to investigate different white matter properties in psychiatric and healthy populations. On the one hand, white matter microstructural properties were investigated in a psychiatric population; on the other hand, white matter metabolic properties were assessed in healthy adults providing basic information about the brain’s wiring entity. As a result, three research papers are presented here. The first paper assessed the microstructural properties of white matter in relation to a frequent epidemiologic finding in schizophrenia. As a result, reduced white matter integrity was observed in patients born in summer and autumn compared to patients born in winter and spring. Despite the large genetic basis of schizophrenia, accumulating evidence indicates that environmental exposures may be implicated in the development of schizophrenia (A. S. Brown, 2011). Notably, epidemiologic studies have shown a 5–8% excess of births during winter and spring for patients with schizophrenia on the Northern Hemisphere at higher latitudes (Torrey, Miller, Rawlings, & Yolken, 1997). Although the underlying mechanisms are unclear, the seasonal birth effect may indicate fluctuating environmental risk factors for schizophrenia. Thus, exposure to harmful factors during foetal development may result in the activation of pathologic neural circuits during adolescence or young adulthood, increasing the risk of schizophrenia (Fatemi & Folsom, 2009). While white matter development starts during the foetal period and continues until adulthood, its major development is accomplished by the age of two years (Brody, Kinney, Kloman, & Gilles, 1987; Huang et al., 2009). This indicates a vulnerability period of white matter that may coincide with the fluctuating environmental risk factors for schizophrenia. Since microstructural alterations of white matter in schizophrenia are frequently observed, the current study provided evidence for the neurodevelopmental hypothesis of schizophrenia. In the second research paper, the perfusion of white matter showed a positive correlation between white matter microstructure and its perfusion with blood across healthy adults. This finding was in line with clinical studies indicating a tight coupling between cerebral perfusion and WM health across subjects (Amann et al., 2012; Chen, Rosas, & Salat, 2013; Kitagawa et al., 2009). Although relatively little is known about the metabolic properties of white matter, different microstructural properties, such as axon diameter and myelination, might be coupled with the metabolic demand of white matter. Furthermore, the ability to detect perfusion signal in white matter was in accordance with a recent study showing that technical improvements, such as pseudo-continuous arterial spin labeling, enabled the reliable detection of white matter perfusion signal (van Osch et al., 2009). The third paper involved a collaboration within the same department to assess the interrelation between functional connectivity networks and their underlying structural connectivity.
Resumo:
Background: Despite immense efforts into development of new antidepressant drugs, the increases of serotoninergic and catechominergic neurotransmission have remained the two major pharmacodynamic principles of current drug treatments for depression. Consequently, psychopathological or biological markers that predict response to drugs that selectively increase serotonin and/or catecholamine neurotransmission hold the potential to optimize the prescriber’s selection among currently available treatment options. The aim of this study was to elucidate the differential symptomatology and neurophysiology in response to reductions in serotonergic versus catecholaminergic neurotransmission in subjects at high risk of depression recurrence. Methods: Using identical neuroimaging procedures with [18F] fluorodeoxyglucose positron emission tomography after tryptophan depletion (TD) and catecholamine depletion (CD), subjects with remitted depression were compared to healthy controls in a double-blind, randomized, crossover design. Results: While TD induced significantly more depressed mood, sadness and hopelessness than CD, CD induced more inactivity, concentration difficulties, lassitude and somatic anxiety than TD. CD specifically increased glucose metabolism in the bilateral ventral striatum and decreased glucose metabolism in the bilateral orbitofrontal cortex, whereas TD specifically increased metabolism in the right prefrontal cortex and the posterior cingulate cortex (PCC). While we found direct associations between changes in brain metabolism and induced depressive symptoms following CD, the relationship between neural activity and symptoms was less clear after TD. Conclusions: In conclusion, this study showed that serotonin and catecholamines play common and differential roles in the pathophysiology of depression.
Resumo:
Despite immense efforts into development of new antidepressant drugs, the increases of serotoninergic and catecholaminergic neurotransmission have remained the two major pharmacodynamic principles of current drug treatments for depression. Consequently, psychopathological or biological markers that predict response to drugs that selectively increase serotonin and/or catecholamine neurotransmission hold the potential to optimize the prescriber's selection among currently available treatment options. The aim of this study was to elucidate the differential symptomatology and neurophysiology in response to reductions in serotonergic versus catecholaminergic neurotransmission in subjects at high risk of depression recurrence. Using identical neuroimaging procedures with [(18)F] fluorodeoxyglucose positron emission tomography after tryptophan depletion (TD) and catecholamine depletion (CD), subjects with remitted depression were compared with healthy controls in a double-blind, randomized, crossover design. Although TD induced significantly more depressed mood, sadness and hopelessness than CD, CD induced more inactivity, concentration difficulties, lassitude and somatic anxiety than TD. CD specifically increased glucose metabolism in the bilateral ventral striatum and decreased glucose metabolism in the bilateral orbitofrontal cortex, whereas TD specifically increased metabolism in the right prefrontal cortex and the posterior cingulate cortex. Although we found direct associations between changes in brain metabolism and induced depressive symptoms following CD, the relationship between neural activity and symptoms was less clear after TD. In conclusion, this study showed that serotonin and catecholamines have common and differential roles in the pathophysiology of depression.