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Drugs for Treatment of Neurological and Psychological Conditions
Published in Richard J. Sundberg, The Chemical Century, 2017
One approach to treatment of AD is based on the neurotransmitter ACh (see Section 17.1). One of the characteristics of AD is loss of cholinergic neurons in the basal forebrain. There is a decrease in the level ACh and the enzymes involved in formation and hydrolysis of ACh (see Section 8.3.3). The decrease in cholinergic function is correlated with formation and deposition of β-amyloid peptides. This and the hyperphosphorylation of tau, a protein associated with microtubules, are the most evident biochemical manifestations of AD. The deficit of cholinergic function has resulted in investigation of cholinesterase inhibitors as potential drugs for treatment of AD patients. Several drugs appear to have at least some benefit in the mild and moderate stages of the disease. The first to be introduced was tacrine, but it has largely been abandoned because of side effects, including hepatotoxicity. The other three approved drugs are donepezil, rivastigmine, and galantamine. The structures are shown in Scheme 17.10. None of these medications slows or alters the development of the disease but they do provide some temporary improvement in cognitive function.
Circadian System and Diurnal Activity
Published in Anthony N. Nicholson, The Neurosciences and the Practice of Aviation Medicine, 2017
Appreciating the interaction between the circadian and sleep systems is fundamental to solving the problems experienced by aircrew who have to cope with time-zone changes and with irregularity of rest and activity. Sleep appears to be generated by two broadly opposing mechanisms: the homeostatic drive for sleep and the circadian system that regulates wakefulness (Figure 2.3). Together they interact to consolidate sleep. The homeostatic drive describes a process whereby the drive for sleep increases the longer an individual has been awake. In contrast with the established anatomical location of the circadian clock within the SCN, the brain structures regulating the homeostatic sleep drive remain unclear. Studies suggest that a build-up of adenosine, a breakdown product of adenosine triphosphate, in specific brain regions could provide the molecular basis for sleep pressure (increased sleepiness) during wakefulness (Basheer et al., 2004; Wigren et al., 2007; Landolt, 2008). The basal forebrain has been implicated in this process, whilst other brain regions such as the amygdala, hippocampus and cerebral cortex appear not to be involved (Zeitzer et al., 2006; Christie et al., 2008; Krueger et al., 2008).
Physical Hazards of Space Exploration and the Biological Bases of Behavioral Health and Performance in Extreme Environments
Published in Lauren Blackwell Landon, Kelley J. Slack, Eduardo Salas, Psychology and Human Performance in Space Programs, 2020
Julia M. Schorn, Peter G. Roma
These two domains are the most “basic” as they serve the most essential biobehavioral functions, such as sleep–wakefulness and motor actions. Arousal/regulatory systems provide homeostatic regulation of sleep, wake, and arousal. When teams live and work in space, wakefulness and attention are required to correctly execute mission tasks and maintain mission systems, which could potentially have fatal consequences if poorly performed. Within the brain, the suprachiasmatic nucleus (SCN) in the hypothalamus is critical for regulating circadian rhythms and is known as the “master clock” (Dubocovich, 2007; Ebling, 1996). Our circadian rhythm is also influenced by external cues, the most prominent being light. Sunlight stimulates wakefulness while darkness is accompanied by melatonin production. Melatonin, the neurohormone associated with sleep, is suppressed when exposed to blue-enriched white light. Light-sensitive receptor cells in the retina project to the SCN. The pathway from light receptors to SCN eventually ends in the pineal gland, which secretes melatonin. The SCN also controls related functions, such as body temperature, hormone secretion, urine production, and blood pressure. The SCN also receives input of the neurotransmitter serotonin from the dorsal raphe nucleus in the brainstem, which attenuates light-induced shifts in circadian phase (Rosenwasser, 2009). Different neurotransmitters, namely acetylcholine and noradrenaline, project from the basal forebrain to different areas in the cortex and support sustained attention (Dalley et al., 2001; Sarter, Givens, & Bruno, 2001). Additionally, many hormones like cortisol, testosterone, and oxytocin also exhibit natural circadian rhythms and are associated with basic sleep–wake rhythms (Amico, Tenicela, Johnston, & Robinson, 1983; Haus, 2007). Circadian rhythm disturbances are associated with multiple psychiatric conditions, including major depression, schizophrenia, and bipolar disorder (Cohrs, 2008; Pilz et al., 2018; Vadnie & McClung, 2017).
Recent advances in devices for vagus nerve stimulation
Published in Expert Review of Medical Devices, 2018
Ann Mertens, Robrecht Raedt, Stefanie Gadeyne, Evelien Carrette, Paul Boon, Kristl Vonck
Although the exact mechanism of action of VNS remains unclear, it is known from preclinical studies that VNS affects brainstem (locus coeruleus, LC) and basal forebrain neuronal networks resulting in the release of norepinephrine and acetylcholine, neurotransmitters known to facilitate reorganization of cortical networks [22]. The paired delivery of VNS trains and rehabilitative limb movement was shown to augment task-specific plasticity in the motor cortex, providing the basis for a novel and potentially more effective rehabilitation treatment after stroke. This innovative approach is known as Paired Vagus Nerve Stimulation [23,24]. It is currently also being investigated for other indications such as tinnitus [25] and post-traumatic stress disorders [26,27] and could be a potential adjuvant to behavioral therapy for autism [28].
Exploration of ligand-induced protein conformational alteration, aggregate formation, and its inhibition: A biophysical insight
Published in Preparative Biochemistry and Biotechnology, 2018
Saima Nusrat, Rizwan Hasan Khan
Alzheimer’s is a late onset neurodegenerative disease and has spread to about 5.3 million people in United States.[143] Immunostaining techniques have revealed the presence of extracellular fibrillar aggregates (plaques) of amyloid β and intracellular neurofibrillary tangles of cytoskeleton-associated tau protein.[144] The most affected regions of the brain are the basal forebrain and hippocampus.[145] Familial AD occurs due to mutations in presinilins (presinilin1 and presinilin 2) and amyloid precursor protein. Presinilins are involved in proteolytic cleavage of amyloid precursor protein to form amyloid β (40 and 42).[146]
A novel solution of an elastic net regularisation for dementia knowledge discovery using deep learning
Published in Journal of Experimental & Theoretical Artificial Intelligence, 2023
Kshitiz Shrestha, Omar Hisham Alsadoon, Abeer Alsadoon, Tarik A. Rashid, Rasha S. Ali, P.W.C. Prasad, Oday D. Jerew
(W. Huang et al., 2018) enhanced a system to detect dementia disease using low-resource pairwise learning. The authors use a deep learning algorithm on Arterial Spin Labelling (ASL) magnetic resonance images. As future work, the model needs to work more on medical imaging problems using sophisticated deep learning techniques. (J. E. Lee et al., 2016) examines Nucleus basalis magno-cellularis stimulation to study the changes in spatial memory and neurotransmitter systems. The authors use 192 IgG-saporin for basal forebrain cholinergic neuron degeneration associated with memory and learning. The proposed system provides a piece of new information that consolidation and retrieves the visuospatial memory which is enhanced by Nucleus basalis magnocellularis stimulation. However, it is not clear how much the electrical stimulation effects and make changes in the neurotransmitter system, and they are related to visuospatial memory. The study of the electrical stimulation mechanism and the neurotransmitter systems will be considered as the future work of this paper. (H. Akinori et al., 2018) constructed a Multiple Layer Perceptron as a predictive model that predicts the outcome of the Morris Water Maze. The authors use the output data of the Morris Water Maze operation and fed it to the Artificial Neural Networks as an input. The output results of the Artificial Neural Network model and Morris Water Maze operation were compared. The prediction accuracy between the human tester and the Artificial Neural Network model is similar. Apart from that, the accuracy of the predictive model is affected when the explanatory and the objective variables are on the same data representation.