Aim: It is beneficial to classify brain images as healthy or pathological automatically, because 3D brain images can generate so much information which is time consuming and tedious for manual analysis. Among various 3D brain imaging techniques, magnetic resonance (MR) imaging is the most suitable for brain, and it is now widely applied in hospitals, because it is helpful in the four ways of diagnosis, prognosis, pre-surgical, and postsurgical procedures. There are automatic detection methods; however they suffer from low accuracy. Method: Therefore, we proposed a novel approach which employed 2D discrete wavelet transform (DWT), and calculated the entropies of the subbands as features. Then, a bat algorithm optimized extreme learning machine (BA-ELM) was trained to identify pathological brains from healthy controls. A 10x10-fold cross validation was performed to evaluate the out-of-sample performance. Result: The method achieved a sensitivity of 99.04%, a specificity of 93.89%, and an overall accuracy of 98.33% over 132 MR brain images. Conclusion: The experimental results suggest that the proposed approach is accurate and robust in pathological brain detection.
In general, proteins can only execute their various biological functions when they are appropriately folded. Their amino acid sequence encodes the relevant information required for correct three-dimensional folding, with or without the assistance of chaperones. The challenge associated with understanding protein folding is currently one of the most important aspects of the biological sciences. Misfolded protein intermediates form large polymers of unwanted aggregates and are involved in the pathogenesis of many human diseases, including Alzheimer's disease (AD) and Type 2 diabetes mellitus (T2DM). AD is one of the most prevalent neurological disorders and has worldwide impact; whereas T2DM is considered a metabolic disease that detrementally influences numerous organs, afflicts some 8% of the adult population, and shares many risk factors with AD. Research data indicates that there is a widespread conformational change in the proteins involved in AD and T2DM that form β-sheet like motifs. Although conformation of these β-sheets is common to many functional proteins, the transition from α-helix to β-sheet is a typical characteristic of amyloid deposits. Any abnormality in this transition results in protein aggregation and generation of insoluble fibrils. The abnormal and toxic proteins can interact with other native proteins and consequently catalyze their transition into the toxic state. Both AD and T2DM are prevalent in the aged population. AD is characterized by the accumulation of amyloid-β (Aβ) in brain, while T2DM is characterized by the deposition of islet amyloid polypeptide (IAPP, also known as amylin) within beta-cells of the pancreas. T2DM increases pathological angiogenesis and immature vascularisation. This also leads to chronic cerebral hypoperfusion, which results in dysfunction and degeneration of neuroglial cells. With an abundance of common mechanisms underpinning both disorders, a significant question that can be posed is whether T2DM leads to AD in aged individuals and the associations between other protein misfolding diseases.
Aim: This study presents an improved method based on "Gorji et al. Neuroscience. 2015" by introducing a relatively new classifier-linear regression classification. Method: Our method selects one axial slice from 3D brain image, and employed pseudo Zernike moment with maximum order of 15 to extract 256 features from each image. Finally, linear regression classification was harnessed as the classifier. Results: The proposed approach obtains an accuracy of 97.51%, a sensitivity of 96.71%, and a specificity of 97.73%. Conclusion: Our method performs better than Gorji's approach and five other state-of-the-art approaches.
The morphology of dendritic spines is highly correlated with the neuron function. Therefore, it is of positive influence for the research of the dendritic spines. However, it is tried to manually label the spine types for statistical analysis. In this work, we proposed an approach based on the combination of wavelet contour analysis for the backbone detection, wavelet packet entropy, and fuzzy support vector machine for the spine classification. The experiments show that this approach is promising. The average detection accuracy of "MushRoom" achieves 97.3%, "Stubby" achieves 94.6%, and "Thin" achieves 97.2%.
Aim: Sensorineural hearing loss is correlated to massive neurological or psychiatric disease. Materials: T1-weighted volumetric images were acquired from fourteen subjects with right-sided hearing loss (RHL), fifteen subjects with left-sided hearing loss (LHL), and twenty healthy controls (HC). Method: We treated a three-class classification problem: HC, LHL, and RHL. Stationary wavelet entropy was employed to extract global features from magnetic resonance images of each subject. Those stationary wavelet entropy features were used as input to a single-hidden layer feedforward neuralnetwork classifier. Results: The 10 repetition results of 10-fold cross validation show that the accuracies of HC, LHL, and RHL are 96.94%, 97.14%, and 97.35%, respectively. Conclusion: Our developed system is promising and effective in detecting hearing loss.
Background & Objective: Traumatic Brain Injury (TBI) is one of the major causes of mortality and morbidity worldwide. It represents mild, moderate and severe effects of physical assault to brain which may cause sequential, primary or secondary ramifications. Primary injury can be due to the first physical hit, blow or jolt to one of the brain compartments. The primary injury is then followed by secondary injury which leads to biochemical, cellular, and physiological changes like blood brain barrier disruption, inflammation, excitotoxicity, necrosis, apoptosis, mitochondrial dysfunction and generation of oxidative stress. Apart from this, there is also an immediate increase in glutamate at the synapses following severe TBI. Excessive glutamate at synapses in turn activates corresponding NMDA and AMPA receptors that facilitate excessive calcium influx into the neuronal cells. This leads to the generation of oxidative stress which further leads to mitochondrial dysfunction, lipid peroxidation and oxidation of proteins and DNA. As a consequence, neuronal cell death takes place and ultimately people start facing some serious disabilies. Conclusion: In the present review we provide extensive overview of the role of reactive oxygen species (ROS)-induced oxidative stress and its fatal effects on brain after TBI.
The glutamate/cystine antiporter system x(c)(-) transports cystine into cells in exchange for the important neurotransmitter glutamate at a ratio of 1:1. It is composed of a specific light chain, xCT, and a heavy chain, 4F2, linked by a disulfide bridge. Both subunits are localized prominently in the mouse and human brain especially in border areas between the brain and periphery including vascular endothelial cells, ependymal cells, choroid plexus, and leptomeninges. Glutamate exported by system x(c)(-) is largely responsible for the extracellular glutamate concentration in the brain, whereas the imported cystine is required for the synthesis of the major endogenous antioxidant, glutathione. System x(c)(-) thus connects the antioxidant defense with neurotransmission and behavior. Disturbances in the function of system x(c)(-) have been implicated in nerve cell death due to increased extracellular glutamate and reduced intracellular glutathione. In vitro, inhibition of cystine import through system x(c)(-) leads to cell death by a mechanism called oxidative glutamate toxicity or oxytosis, which includes depletion of intracellular glutathione, activation of 12-lipoxygenase, accumulation of intracellular peroxides, and the activation of a cyclic guanosine monophosphate (cGMP)-dependent calcium channel towards the end of the death cascade. Cell death caused by oxytosis is distinct from classical apoptosis. In this contribution, we discuss the function of system x(c)(-) in vitro and in vivo, the role of xCT as an important but due to its dual role probably ambivalent drug target, and the relevance of oxytosis as an in vitro assay for the identification of novel neuroprotective proteins and signaling pathways.
Palmitoylethanolamide (PEA) is an endogenous cannabinoid-like compound in the central nervous system, which can modulate several functions in different pathological states, such as inflammation and pain response. We have here investigated the effect of PEA (5-10 mg/kg, intraperitoneally) on mechanical allodynia and thermal hyperalgesia 3 and 7 days following peripheral injection of formalin. Formalin induced a significant decrease of thermal and mechanical threshold in the injected and contralateral paw. PEA chronic treatment (once per day) significantly reduced mechanical allodynia and thermal hyperalgesia in a dose-dependent manner. Consistently, in vivo electrophysiological analysis revealed a significant increase of the duration and frequency, and a rapid decrease in the onset of evoked activity of the spinal nociceptive neurons 7 days after formalin. PEA normalized the electrophysiological parameters in a dosedependent manner. Moreover, we investigated PEA effect on the glial/microglial phenotypical changes associated with spinal neuronal sensitization. We found that formalin induced a significant microglia and glia activation normalized by PEA, together with increased expression of glial interleukin 10. Finally, primary microglial cell cultures, conditioned with PEA or vehicle, where transplanted in naive and formalin-treated mice, and nociceptive neurons were recorded. We observed that only PEA-conditioned cells normalized the activity of sensitized nociceptive neurons. In conclusion these data confirm the potent anti-inflammatory and anti-allodynic effect of PEA, and highlight a possible targeted microglial/glial effect of this drug in the spinal cord.
Background & Objective: Cellular physiology and energy metabolism are maintained by the constant supply of energy furnished by the powerhouses of the cell called mitochondria. Cellular homeostasis depends on the timely clearance of damaged cellular organelles and proteins via pathways including autophagy. Mitochondria and mitochondrial autophagy play a vital role in cellular health and failure of these pathways can have a devastating effect on cellular homeostasis. Amongst the various cell types, neuronal cells are more vulnerable to bioenergetic depletion since most of their functions critically depend on the availability of energy derived from mitochondrial metabolism, thus making neurodegenerative disorders an obstinate issue. Research in the past few decades has shown that these neurodegenerative disorders are associated with mitochondrial dysfunction and compromised mitophagy leading to accumulation of protein aggregates which ultimately culminate in neurodegeneration. Conclusion: Thus, targeting mitochondria and autophagy-related proteins and enzymes in neurodegenerative disorders may open the avenues for potential targets for discovering effective therapies. Here, we review the involvement of mitochondrial and autophagy dysfunction in neurodegenerative disorders specifically focusing on Alzheimer’s, Parkinson’s and Huntington’s disease.
Purslane (Portulaca oleraceae L.), a member of the Portulacaceae family, is widespread as a weed and has been ranked as the eighth most common plant in the world. In order to evaluate purslane herbal aqueous juice as a neuroprotective agent, the antioxidant activity of purslane juice was assessed in vitro and the neuroprotective effects of purslane (1.5 mL/Kg bwt) on rotenone (12 mg/Kg bwt for 12 days) induced biochemical changes and apoptosis in striatum of rats were also examined. The repeated administration of rotenone produced dramatic increases in intercellular content of calcium, dopamine metabolites and apoptosis in the striatum. In addition, rotenone administration caused significant decrease in complex I activity. These biochemical changes and apoptosis inductions were effectively counteracted by administration of purslane. Overall, the present study demonstrated the neuroprotective role of purslane in the striatum and proposes its prophylactic potential against developing brain damage and Parkinson's disease induction followed by rotenone administration, and that purslane may be considered as a potential neuroprotective agent against environmental factors affecting the function of the dopaminergic system.
Background and Objective: Stroke is a leading cause of morbidity and mortality in both developed and developing countries all over the world. The only drug for ischemic stroke approved by FDA is recombinant tissue plasminogen activator (rtPA). However, only 2-5% stroke patients receive rtPAs treatment due to its strict therapeutic time window. As ischemic stroke is a complex disease involving multiple mechanisms, medications with multi-targets may be more powerful compared with single-target drugs. Dl-3-n-Butylphthalide (NBP) is a synthetic compound based on l-3-n- Butylphthalide that is isolated from seeds of Apium graveolens. The racemic 3-n-butylphthalide (dl- NBP) was approved by Food and Drug Administration of China for the treatment of ischemic stroke in 2002. A number of clinical studies indicated that NBP not only improved the symptoms of ischemic stroke, but also contributed to the long-term recovery. The potential mechanisms of NBP for ischemic stroke treatment may target different pathophysiological processes, including anti-oxidant, antiinflammation, anti-apoptosis, anti-thrombosis, and protection of mitochondria et al. Conclusion: In this review, we have summarized the research progress of NBP for the treatment of ischemic stroke during the past two decades.
Introduction: Natalizumab (NAT) is an effective treatment for relapsing remitting multiple sclerosis (RRMS), as it makes the blood-brain-barrier impenetrable by binding to the α4integrin subunit. The objectives of our study were to find new peripheral mechanisms of action of NAT and new biomarkers of treatment response. Material and Methods: We prospectively assessed the serum levels of 15 cytokines from the Th17 Cytokine Panel using Bio-plex Pro Human in a group of 29 RRMS patients treated with NAT and 29 healthy subjects (HS) at inclusion and after 8 months of NAT treatment. For each patient, demographic data, number of relapses and Expanded Disability Status Scale (EDSS) were collected and compared with the initial and final values of each cytokine. Moreover, the Th17/Treg shift was assessed using the interleukine (IL)-17F/IL-10 ratio and the cytokine signature (the sum of all the cytokines). Advanced statistical analysis was used. Results: RRMS patients had significantly lower serum levels of IL-23, IL-17F, IL-1β and IL-31 compared to HS. Serum sCD40L, IL-17F, IL-31 and cytokine signature levels significantly decreased after 8 months of NAT treatment. Positively correlations were found between the relapse number and IL- 17F, IL-1β, IL-31 serum levels and between EDSS and tumor necrotic factor-α, IL-1β and IL-17/IL-10 serum levels. IL-10 serum levels correlated negatively with the EDSS score. Conclusion: In evaluating the mode of action of NAT, it is important to determine the value of each cytokine, the Th17/Treg shift and the cytokine signature. NAT significantly decreased peripheral serum levels of some pro-inflammatory cytokines as a novel mechanism of action. IL-17F, sCD40L and IL-31 were the best biomarkers to assess the effectiveness of NAT.
Aim: Alzheimer's disease patients are increasing rapidly every year. Scholars tend to use computer vision methods to develop automatic diagnosis system. (Background) In 2015, Gorji et al. proposed a novel method using pseudo Zernike moment. They tested four classifiers: learning vector quantization neural network, pattern recognition neural network trained by Levenberg-Marquardt, by resilient backpropagation, and by scaled conjugate gradient. Method: This study presents an improved method by introducing a relatively new classifier-linear regression classification. Our method selects one axial slice from 3D brain image, and employed pseudo Zernike moment with maximum order of 15 to extract 256 features from each image. Finally, linear regression classification was harnessed as the classifier. Results: The proposed approach obtains an accuracy of 97.51%, a sensitivity of 96.71%, and a specificity of 97.73%. Conclusion: Our method performs better than Gorji's approach and five other state-of-the-art approaches. Therefore, it can be used to detect Alzheimer's disease.
Background & Objective: Hydrogen sulfide [H2S] has been widely known as a toxic gas for more than 300 years in the scientific community. However, the understanding about this small molecule has changed after the discovery of involvement of H2S in physiological and pathological mechanisms in brain. H2S is a third gasotransmitter and neuromodulator after carbon monoxide [CO] and nitric oxide [NO]. H2S plays an important role in memory and cognition by regulating long-term potentiation [LTP] and calcium homeostasis in neuronal cells. The disturbances in endogenous H2S levels and trans-sulfuration pathway have been implicated in neurodegenerative disorders like Alzheimer’s disease, Parkinson disease, stroke and traumatic brain injury. According to the results obtained from various studies, H2S not only behaves as neuromodulator but also is a potent antioxidant, anti-inflammatory and anti-apoptotic molecule suggesting its neuroprotective potential. Conclusion: Recently, there is an increased interest in developing H2S releasing pharmaceuticals to target various neurological disorders. This review covers the information about the involvement of H2S in neurodegenerative diseases, its molecular targets and its role as potential therapeutic molecule.
BACKGROUNDIn recent years, numerous investigations focused on the pleiotropic actions of vitamin D have been carried out. These actions include the participation of this molecule in neurophysiological and neuropathological processes. As a consequence, abundant scientific literature on the role of this vitamin in neurodegenerative entities has emerged, even concerning clinical studies.OBJECTIVETo identify the level of scientific evidence concerning the relation between vitamin D and neurodegenerative diseases, from a quantitative and qualitative perspective.METHODSTo describe, by means of a bibliometric analysis, the scientific production and its evolution through time in quantitative terms, regarding the implications of vitamin D in neurodegeneration. To analyse and present the degree of evidence in the aforementioned field of study, a systematic review of the literature focused on the most prevalent neurodegenerative diseases was carried out.RESULTSWe retrieved 848 articles in the bibliometric analysis, the majority of which were dated between the years 2010-2017. The most studied metabolite was the 25(OH)D3 and the most cited disease was multiple sclerosis. In the systematic review, we found studies about Alzheimer's and Parkinson's diseases and again, about multiple sclerosis prominently (in number and quality), with 12 randomised double-blind clinical trials.CONCLUSIONThe research about vitamin D and its relations with neurodegenerative diseases shows a growing evolution over the last decade. More studies are needed to find correlations between the clinical severity of these diseases and the specific status of vitamin D and the genotypes related with them, which seems to be a future trend.