90 research outputs found
Electrochemical Impedance Imaging via the Distribution of Diffusion Times
We develop a mathematical framework to analyze electrochemical impedance
spectra in terms of a distribution of diffusion times (DDT) for a parallel
array of random finite-length Warburg (diffusion) or Gerischer
(reaction-diffusion) circuit elements. A robust DDT inversion method is
presented based on Complex Nonlinear Least Squares (CNLS) regression with
Tikhonov regularization and illustrated for three cases of nanostructured
electrodes for energy conversion: (i) a carbon nanotube supercapacitor, (ii) a
silicon nanowire Li-ion battery, and (iii) a porous-carbon vanadium flow
battery. The results demonstrate the feasibility of non-destructive "impedance
imaging" to infer microstructural statistics of random, heterogeneous
materials
Analysis, Design, and Generalization of Electrochemical Impedance Spectroscopy (EIS) Inversion Algorithms
We introduce a framework for analyzing and designing EIS inversion
algorithms. Our framework stems from the observation of four features common to
well-defined EIS inversion algorithms, namely (1) the representation of unknown
distributions, (2) the minimization of a metric of error to estimate parameters
arising from the chosen representation, subject to constraints on (3) the
complexity control parameters, and (4) a means for choosing optimal control
parameter values. These features must be present to overcome the ill-posed
nature of EIS inversion problems. We review three established EIS inversion
algorithms to illustrate the pervasiveness of these features, and show the
utility of the framework by resolving ambiguities concerning three more
algorithms. Our framework is then used to design the generalized EIS inversion
(gEISi) algorithm, which uses Gaussian basis function representation, modality
control parameter, and cross-validation for choosing the optimal control
parameter value. The gEISi algorithm is applicable to the generalized EIS
inversion problem, which allows for a wider range of underlying models. We also
considered the construction of credible intervals for distributions arising
from the algorithm. The algorithm is able to accurately reproduce distributions
which have been difficult to obtain using existing algorithms. It is provided
gratis on the repository https://github.com/suryaeff/gEISi.git.Comment: 46 pages, to be submitted to the Journal of the Electrochemical
Societ
The Glymphatic System in Diabetes-Induced Dementia
The glymphatic system has emerged as an important player in central nervous system (CNS) diseases, by regulating the vasculature impairment, effectively controlling the clearance of toxic peptides, modulating activity of astrocytes, and being involved in the circulation of neurotransmitters in the brain. Recently, several studies have indicated decreased activity of the glymphatic pathway under diabetes conditions such as in insulin resistance and hyperglycemia. Furthermore, diabetes leads to the disruption of the blood-brain barrier and decrease of apolipoprotein E (APOE) expression and the secretion of norepinephrine in the brain, involving the impairment of the glymphatic pathway and ultimately resulting in cognitive decline. Considering the increased prevalence of diabetes-induced dementia worldwide, the relationship between the glymphatic pathway and diabetes-induced dementia should be investigated and the mechanisms underlying their relationship should be discussed to promote the development of an effective therapeutic approach in the near future. Here, we have reviewed recent evidence for the relationship between glymphatic pathway dysfunction and diabetes. We highlight that the enhancement of the glymphatic system function during sleep may be beneficial to the attenuation of neuropathology in diabetes-induced dementia. Moreover, we suggest that improving glymphatic system activity may be a potential therapeutic strategy for the prevention of diabetes-induced dementia
Transcriptomic Analysis of High Fat Diet Fed Mouse Brain Cortex
High fat diet can lead to metabolic diseases such as obesity and diabetes known to be chronic inflammatory diseases with high prevalence worldwide. Recent studies have reported cognitive dysfunction in obese patients is caused by a high fat diet. Accordingly, such dysfunction is called “type 3 diabetes” or “diabetic dementia.” Although dysregulation of protein-coding genes has been extensively studied, profiling of non-coding RNAs including long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) has not been reported yet. Therefore, the objective of this study was to obtain profiles of diverse RNAs and determine their patterns of alteration in high fat fed brain cortex compared to normal brain cortex. To investigate regulatory roles of both coding and non-coding RNAs in high fat diet brain, we performed RNA sequencing of ribosomal RNA-depleted RNAs and identified genome-wide lncRNAs and circRNAs expression and co-expression patterns of mRNAs in high fat diet mouse brain cortex. Our results showed expression levels of mRNAs related to neurogenesis, synapse, and calcium signaling were highly changed in high fat diet fed cortex. In addition, numerous differentially expressed lncRNAs and circRNAs were identified. Our study provides valuable expression profiles and potential function of both coding and non-coding RNAs in high fat diet fed brain cortex
The role of melatonin in the onset and progression of type 3 diabetes
Abstract Alzheimer’s disease (AD) is defined by the excessive accumulation of toxic peptides, such as beta amyloid (Aβ) plaques and intracellular neurofibrillary tangles (NFT). The risk factors associated with AD include genetic mutations, aging, insulin resistance, and oxidative stress. To date, several studies that have demonstrated an association between AD and diabetes have revealed that the common risk factors include insulin resistance, sleep disturbances, blood brain barrier (BBB) disruption, and altered glucose homeostasis. Many researchers have discovered that there are mechanisms common to both diabetes and AD. AD that results from insulin resistance in the brain is termed “type 3 diabetes”. Melatonin synthesized by the pineal gland is known to contribute to circadian rhythms, insulin resistance, protection of the BBB, and cell survival mechanisms. Here, we review the relationship between melatonin and type 3 diabetes, and suggest that melatonin might regulate the risk factors for type 3 diabetes. We suggest that melatonin is crucial for attenuating the onset of type 3 diabetes by intervening in Aβ accumulation, insulin resistance, glucose metabolism, and BBB permeability
Glutathione Suppresses Cerebral Infarct Volume and Cell Death after Ischemic Injury: Involvement of FOXO3 Inactivation and Bcl2 Expression
Ischemic stroke interrupts the flow of blood to the brain and subsequently results in cerebral infarction and neuronal cell death, leading to severe pathophysiology. Glutathione (GSH) is an antioxidant with cellular protective functions, including reactive oxygen species (ROS) scavenging in the brain. In addition, GSH is involved in various cellular survival pathways in response to oxidative stress. In the present study, we examined whether GSH reduces cerebral infarct size after middle cerebral artery occlusion in vivo and the signaling mechanisms involved in the promotion of cell survival after GSH treatment under ischemia/reperfusion conditions in vitro. To determine whether GSH reduces the extent of cerebral infarction, cell death after ischemia, and reperfusion injury, we measured infarct size in ischemic brain tissue and the expression of claudin-5 associated with brain infarct formation. We also examined activation of the PI3K/Akt pathway, inactivation of FOXO3, and expression of Bcl2 to assess the role of GSH in promoting cell survival in response to ischemic injury. Based on our results, we suggest that GSH might improve the pathogenesis of ischemic stroke by attenuating cerebral infarction and cell death
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