CNS & Neurological Disorders - Drug Targets (Formerly Current Drug Targets - CNS & Neurological Disorders) - Volume 16, Issue 1, 2017

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.

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.

Obstructive sleep apnea-hypopnea syndrome (OSAHS) is normally linked to cognitive and functional dysfunctions. In this study, we explored the resting-state functional connectivity (rsFC) in the default mode network (DMN) to show the mechanism of neurophysiology in patients with OSAHS. Resting-state structural and functional Magnetic Resonance Imaging (fMRI) data were obtained from sixteen male moderate-to- severe patients with untreated OSAHS and 15 male matched healthy control subjects. The rsFC in the DMN was analyzed between OSAHS and healthy controls by the CONN software. Compared with the controls, the rsFC showed a significant decrease in the medial prefrontal cortex, anterior cingulate and posterior cingulate, and showed an increase in the left inferior parietal lobule in OSAHS patients. The results indicated that the OSAHS patients presented alternatives of rsFC in the DMN compared with the controls.

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.

Background: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) results from NOTCH3 gene mutations, which lead to the degeneration of vascular smooth muscle cells (VSMCs). The clinical presentation of CADASIL patients is dependent on the impact of other vascular risk factors and the type of NOTCH3 mutation present. Methods: Here, we report a rare pathogenic mutation on exon 14 of the NOTCH3 gene in a Chinese family affected by CADASIL with phenotypic peculiarities. We performed genetic testing, clinical and neuropsychological examination, brain magnetic resonance images (MRI), and electron microscopy (EM) in skin biopsies. Results: NOTCH3 gene analysis revealed a c.2182C>T substitution on exon 14, which is the first example of this mutation in a Chinese individual from the Han ancestry. Granular osmiophilic material (GOM) was found in the proband, and all patients had migraine, subcortical ischemic events, and mood disturbances, without progressive cognitive impairment. Cranial MRI further showed white matter hyperintensity, involving bilateral basal ganglia and multiple microbleeds (MBs), in the thalamus and brain stem. Conclusions: This study suggests that different missense mutations in NOTCH3 might contribute to atypical clinical features of CADASIL. This report also indicates that for individuals with a positive family history having clinical and neuroradiological findings suggestive of CADASIL, genetic testing and GOM detection should be performed.

Our purpose is to develop a clinical decision support system to classify the patients’ diagnostics based on features gathered from Magnetic Resonance Imaging (MRI) and Expanded Disability Status Scale (EDSS). We studied 120 patients and 19 healthy individuals (not afflicted with MS) have been studied for this study. Healthy individuals in the control group do not have any complaint or drug use history. For the kernel trick, efficient performance in non-linear classification, the Convex Combination of Infinite Kernels model was developed to measure the health status of patients based on features gathered from MRI and EDSS. Our calculations show that our proposed model classifies the multiple sclerosis (MS) diagnosis level with better accuracy than single kernel, artificial neural network and other machine learning methods, and it can also be used as a decision support system for identifying MS health status of patients.

The aim of this study is to introduce Hamiltonian path to analyze functional connectivity of brain default mode networks (DMNs). Firstly, the brain DMNs in resting state are constructed with the employment of functional Magnetic Resonance Imaging (fMRI) data. Then, the Dijkstra algorithm is used to calculate the shortest path length of the node which represents each brain region, and the Hamiltonian path of the default network is solved through the improved adaptive ant colony algorithm. Finally, complex network analysis methods are introduced to discuss the node and network properties of brain functional connectivity in both normal subjects and stroke patients. The experimental result demonstrated that there are some significant differences in the properties of the DMNs between stroke patients and normal subjects, especially the length of Hamiltonian path. It also verifies the effectiveness on studying the functional connectivity of the brain DMNs by applying the proposed method of Hamiltonian path.

Spinal cord injury (SCI) is a long-lasting damage in the spinal cord that leads to paraparesis, paraplegia, quadriplegia and other lifetime disabilities. The underlying mechanisms responsible for the failure of axonal regeneration after SCI remain only partially understood. Although a spectrum of medical treatments has been made available for this disease, the therapeutic effects remain disappointing. The emergence of antibody treatment has paved a new pathway for the management of SCI. In this current review, we summarized the application of antibodies in SCI in studies of myelin repair, neuroprotection, axon outgrowth, and anti-immune reaction. In the meantime, the combination treatment of the antibody with other reagents or stem cell transplant was also reviewed.

Background: Vortioxetine (VRX) is a multimodal antidepressant that acts as serotonin (5HT) transporter inhibitor as well as 5HT3A and 5HT7 receptors antagonist, 5HT1A and 5HT1B receptors partial agonist. It was recently approved in the US and the EU for the treatment of adult patients with Major Depressive Disorder (MDD). Objective: The present article aims at systematically reviewing findings of the published and unpublished research on the pharmacological properties, efficacy, safety and tolerability of oral VRX in the treatment of MDD. Method: A systematic review, in accordance with the Cochrane Collaboration and the PRISMA guidelines, was conducted searching the electronic databases MEDLINE, by combining the following keyterms: ((vortioxetine OR LU AA21004 OR brintellix) AND (antidepressant OR depression OR major depressive disorder), without language/time restrictions. Further studies were retrieved from reference listing of relevant articles or manual search. Preclinical and clinical studies (RCT and open label trials) were here retrieved. Results: Several placebo-controlled and active-treatment studies demonstrated the antidepressant efficacy and tolerability of VRX in adult patients affected with MDD. In addition, VRX seems to own procognitive activity. VRX seems generally well tolerated, without significant cardiovascular or weight gain effects. The most common adverse events reported included nausea, vomiting, hyperhidrosis, headache, dizziness, somnolence, diarrhoea and dry mouth. Conclusion: Overall, placebo controlled and active treatment trials support that VRX is effective and well tolerated in MDD. Its combined serotonin reuptake inhibition with agonism, partial agonism and antagonism of a number of receptors might provide a broader spectrum of antidepressant activity than currently available agents.

Introduction: Individual response to interferon beta (IFN-β) 1a treatment is heterogeneous in multiple sclerosis (MS). Our objective was to find a connection between serum levels of interleukin (IL)-10, IL-17 and transforming growth factor beta (TGF-β)1 in MS patients treated with IFN-β in order to identify the nonresponders (NR). Material and Methods: We included in the study 32 healthy subjects and 32 MS patients: 10 naive, 10 early treated and 12 late treated with INF-β1a. Serum determination of cytokines and brain MRI were performed at the beginning of the study, after 6 and 12 months. Rio score was calculated at the end of the study. Results: MS patients had initially a significant higher level of IL-17 and a lower level of TGF-β1 compared to healthy subjects. IL-17 level in early treated patients was significantly lower compared to the naive and late treated groups. INF-β1a treatment significantly increased IL-10 and decreased IL-17 levels. Initial low levels of IL-10 were associated with an increase in physical disability. IL-17 levels positively correlated with the number of relapses and MRI activity. Nine patients were NR to Avonex. Patients with a Rio score of 3 had higher initial levels of IL-17 and those with a Rio score of 0 had higher initial levels of IL-10 and TGF-β1. Conclusion: IFN-β1a decreased IL-17 and increased IL-10 seric levels; IL-17 significantly correlated with MS activity; TGF-β1 activity is titer-dependent, increased levels were associated with IL-17 inhibition; NR patients to IFN-β1a will have initial high IL-17 and low IL-10 and TGF-β seric levels.

Background: A relevant therapeutic time window (TTW) is an important criterion for considering the clinical relevance of a substance preventing newborn hypoxic-ischemic (HI) brain damage. Objective: To test the TTW of the neuroprotective effects of cannabidol (CBD), a non-psychoactive cannabinoid in a model of newborn HI brain damage. Method: 9-10 day-old C57BL6 mice underwent a HI insult (10% oxygen for 90 min after left carotid artery electrocoagulation). Then, CBD 1 mg/kg or vehicle were administered s.c. 15 min, or 1, 3, 6, 12, 18 or 24 h after the end of the HI insult. Seven days later brain damage was assessed using T2W Magnetic Resonance Imaging scan (ipsilateral hemisphere volume loss, IVHL) and histological studies: Nissl staining (neuropathological score), TUNEL staining (apoptotic damage) and immunohistochemistry with glial fibrillary acidic protein (astrocyte viability) or ionized calcium binding adaptor molecule (microglial activation). Results: CBD administered up to 18 h after HI reduced IHVL and neuropathological score by 60%, TUNEL+ count by 90% and astrocyte damage by 50%. In addition, CBD blunted the HI-induced increase in microglial population. When CBD administration was delayed 24 h, however, the neuroprotective effect was lost in terms of IHVL, apoptosis or astrogliosis reduction. Conclusion: CBD shows a TTW of 18 h when administered to HI newborn mice, which represents a broader TTW than reported for other neuroprotective treatments including hypothermia.