CNS & Neurological Disorders - Drug Targets (Formerly Current Drug Targets - CNS & Neurological Disorders) - Volume 16, Issue 2, 2017

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.

In this paper, we propose an automatic brain tumor segmentation method based on Deep Belief Networks (DBNs) and pathological knowledge. The proposed method is targeted against gliomas (both low and high grade) obtained in multi-sequence magnetic resonance images (MRIs). Firstly, a novel deep architecture is proposed to combine the multi-sequences intensities feature extraction with classification to get the classification probabilities of each voxel. Then, graph cut based optimization is executed on the classification probabilities to strengthen the spatial relationships of voxels. At last, pathological knowledge of gliomas is applied to remove some false positives. Our method was validated in the Brain Tumor Segmentation Challenge 2012 and 2013 databases (BRATS 2012, 2013). The performance of segmentation results demonstrates our proposal providing a competitive solution with stateof- the-art methods.

This paper presents an automatic classification system for segregating pathological brain from normal brains in magnetic resonance imaging scanning. The proposed system employs contrast limited adaptive histogram equalization scheme to enhance the diseased region in brain MR images. Two-dimensional stationary wavelet transform is harnessed to extract features from the preprocessed images. The feature vector is constructed using the energy and entropy values, computed from the level- 2 SWT coefficients. Then, the relevant and uncorrelated features are selected using symmetric uncertainty ranking filter. Subsequently, the selected features are given input to the proposed AdaBoost with support vector machine classifier, where SVM is used as the base classifier of AdaBoost algorithm. To validate the proposed system, three standard MR image datasets, Dataset-66, Dataset-160, and Dataset- 255 have been utilized. The 5 runs of k-fold stratified cross validation results indicate the suggested scheme offers better performance than other existing schemes in terms of accuracy and number of features. The proposed system earns ideal classification over Dataset-66 and Dataset-160; whereas, for Dataset- 255, an accuracy of 99.45% is achieved.

Brain lesions, especially White Matter Lesions (WMLs) that mostly found on magnetic resonance images of elderly people, are not only associated with normal aging, but also with various geriatric disorders including cardiovascular diseases, vascular disease, psychiatric disorders and dementia. Quantitative analysis of WMLs in large clinical trials is crucial in scientific investigations of such neurological diseases as well as in studying aging processes. Exploiting the different appearances of WMLs in multiple modalities, we propose a novel coarse classification to region-scalable refining method to segment WMLs in Magnetic Resonance Imaging (MRI) sequences without user intervention. Specifically, a nonlinear voxel-wise classifier is trained based on intensity features extracted from multimodality MRI sequences, and tissues’ probabilistic prior provided by partial volume estimate images in native space. By considering the prior that the WMLs almost exist in white matter, a rejection algorithm is then used to eliminate the false-positive labels from the initial coarse classification. To further segment precise lesions boundary and detect missing lesions, a region-scalable refining is finally employed to effectively segment the WMLs based on the previous initial contour. Compared with the manual segmentation results from an experienced neuroradiologist, the segmentations for real images of our proposal show desirable performances and high accuracy and provide competitive solution with stateof- the-art methods.

Differentiation of glioblastoma multiformes (GBMs) and lymphomas using multi-sequence magnetic resonance imaging (MRI) is an important task that is valuable for treatment planning. However, this task is a challenge because GBMs and lymphomas may have a similar appearance in MRI images. This similarity may lead to misclassification and could affect the treatment results. In this paper, we propose a semi-automatic method based on multi-sequence MRI to differentiate these two types of brain tumors. Our method consists of three steps: 1) the key slice is selected from 3D MRIs and region of interests (ROIs) are drawn around the tumor region; 2) different features are extracted based on prior clinical knowledge and validated using a t-test; and 3) features that are helpful for classification are used to build an original feature vector and a support vector machine is applied to perform classification. In total, 58 GBM cases and 37 lymphoma cases are used to validate our method. A leave-one-out crossvalidation strategy is adopted in our experiments. The global accuracy of our method was determined as 96.84%, which indicates that our method is effective for the differentiation of GBM and lymphoma and can be applied in clinical diagnosis.

Background: Creatine is an antioxidant agent that showed neuroprotective effects in animal models of Parkinson’s disease (PD). Creatine was selected by the National Institute of Neurological Disorders and Stroke as a possible disease modifying agent for Parkinson's disease. Therefore, many clinical trials evaluated the efficacy of creatine for patients with PD. The aim of this systematic review and meta-analysis is to synthesize evidence from published randomized controlled trials (RCTs) about the efficacy of Creatine for patients with PD. Methods: We followed PRISMA statement guidelines during the preparation of this systematic review and meta-analysis. A computer literature search for PubMed, EBSCO, web of science and Ovid Midline was carried out. We included RCTs comparing creatine with placebo in terms of motor functions and quality of life. Outcomes of total Unified Parkinson's Disease Rating Scale (UPDRS), UPDRS I, UPDRS II, and UPDRS III were pooled as mean difference (MD) between two groups from baseline to the endpoint. Statistical heterogeneity was assessed by visual inspection of the forest plot and measured by chi-square and I square tests. Results: Three RCTs (n=1935) were included in this study. The overall effect did not favor either of the two groups in terms of: UPDRS total score (MD 1.07, 95% CI [3.38 to 1.25], UPDRS III (MD 0.62, 95% CI [2.27 to 1.02]), UPDRS II (MD 0.03, 95% CI [0.81 to 0.86], or UPDRS I (MD 0.03, 95% CI [0.33 to 0.28]). Conclusion: Current evidence does not support the use of creatine for neuroprotection against PD. Future well-designed, randomized controlled trials are needed.

Exact pathophysiological mechanisms of bipolar disorder have not been sufficiently clarified. We review the evidence of mitochondrial dysfunctions on the relation between both disease and pharmacotherapy. Mitochondria produce the most of energy-rich molecules of adenosine triphosphate (ATP), apart from energy production they are involved in other functions: regulation of free radicals, antioxidant defenses, lipid peroxidation, calcium metabolism and participate in the intrinsic pathway of apoptosis. According to increasing evidence dysfunctions of mitochondria are associated with affective disorders, a hypothesis of impaired mitochondrial functions has been proposed in bipolar disorder pathogenesis. Mitochondrial DNA mutations and/or polymorphisms, impaired phospholipid metabolism and glycolytic shift, decrease in ATP production, increased oxidative stress and changes of intracellular calcium are concerned in mood disorders and effects of mood stabilizers. Recent studies have also provided data about the positive effects of chronic treatment by mood stabilizers on mitochondrial functions.

Background: Epilepsy and depression are two of the common diseases seriously threatening life and health of human. A shared neurobiological substrate led to the bidirectional relationship and high comorbid occurrence of the two disorders. Recently, an increasing number of patients with epilepsy (PWE) require some form of antidepressant medication. However, most of the available antidepressants are inadequate for PWE for some reasons. So, the search for novel and increasingly effective drugs with anticonvulsant and antidepressant activities is necessary. Methods: A series of 2-substituted-6-(4H-1,2,4-triazol-4-yl)benzo[d]oxazoles (5a-p) were designed and synthesized. Their anticonvulsant activities were evaluated using maximal electroshock shock (MES) and subcutaneous pentylenetetrazole (scPTZ) seizure models in mice. Their antidepressant activities were screened with the forced swimming test (FST). Results: All the compounds showed anti-MES activities in different degree, among which 5g and 5j were the most promising one with ED50 value of 31.7 and 12.7 mg/kg, respectively. What’s more, 5g and 5j also exhibited nice anti-scPTZ activities and low neurotoxicity. Interestingly, these compounds also showed good antidepressant activities in FST. And the efficacy of 5g were also confirmed by a tail suspension test and a open field test. The pretreatment of thiosemicarbazide (an inhibitor of γ- aminobutyric acid synthesis enzyme) significantly increased the ED50 of 5g in MES and reversed the reductions in the immobility time of 5g in FST. Conclusion: Triazole-containing benzo[d]oxazole is a good skeleton to develop compounds with both anticonvulsant and antidepressant activities. We have got the compound 5g, which display remarkable antidepressant and anticonvulsant activities, and the GABAergic system was involved in the action mechanism of 5g.

Introduction: Therapeutic strategies targeting Alzheimer’s disease-related molecule β- amyloid (Aβ), Tau protein and β-site amyloid precursor protein cleaving enzyme (BACE) have been recently explored. However, the treatment effect for single target is not ideal. Based on multiaspect roles of Rho kinase inhibitor Fasudil on neuroprotection, neurorepair and immunomodulation, we observed therapeutic potential of Fasudil and explored possible mechanisms in amyloid precursor protein/ presenilin-1 transgenic (APP/PS1 Tg) mice, an animal model of Alzheimer’s disease. Methods: APP/PS1 Tg mice were treated with Fasudil (25 mg/kg/day) for 2 months by intraperitoneal injection. Mouse behavior tests were recorded every day. The expression of Aβ deposition, Tau protein phosphorylation, BACE and postsynaptic density 95 (PSD-95) in hippocampus was assayed. The levels in the brain of Toll-like receptors (TLRs)-nuclear factor kappa B/p65#136;NF-κB/p65)- myeloid differentiation primary response gene 88 (MyD88) inflammatory cytokine axis were measured. Results: Fasudil treatment ameliorated learning and memory deficits, accompanied by reduced Aβ deposition, Tau protein phosphorylation, and BACE expression, as well as increased PSD-95 expression in hippocampus. Fasudil intervention also inhibited TLR-2/4, p-NF-κB/p65, MyD88, interleukin-1beta, interleukin-6 and tumor necrosis factor-α for TLRs-NF-κB-MyD88 inflammatory cytokine axis and the induction of interleukin-10. Conclusion: Fasudil exhibited multitarget therapeutic effect in APP/PS1 Tg mice. The study provides preclinical evidence that Fasudil treatment ameliorated memory deficits in APP/PS1 Tg mice, accompanied by the reduction of Aβ deposition and Tau protein phosphorylation, the decrease of BACE and the increase of PSD-95, as well as inhibition of TLRs-NF-κB-MyD88 inflammatory cytokine axis. However, these results still need to be repeated and confirmed before clinical application.

Background: Cell therapies have shown to be able to improve neurological functions to some extent for patients with refractory central nervous system (CNS) diseases or damages. Meanwhile, increasing attention has been drawn to the operation-related and (or) cell-related adverse events when performing cell therapy. Our study is to explore the safety issue from 720 cases of neural progenitor cell (NPC) transplantation based on clinic manifestations and examinations. Method: A retrospective analysis of all adverse events associated with 720 cases of NPC transplantation by administering the cells into the ventricles was done. Results: One hundred and sixty-six cases had postoperative crying and irritability, 69 with vomiting and 84 with fever. None of them had CNS infection, but 4 cases presented intracranial hemorrhage. One month after cell therapy, 568 cases did EEG test, in which 153 patients showed improvement, 74 had abnormal changes in and 341 cases had no changes in; two patients developed new-onset convulsions and 3 had recurrent convulsions; 6 cases had intracranial hemorrhage, but no other CNS sequelae left from the primary diseases. 180 patients were able to follow-up for their clinical evaluation and head MRI or CT examination 2 years after transplantation. All patients didn’t show signs of tumorigenesis and no serious and irreversible operation- or cell-related adverse events. In Conclusion: there are mild adverse reactions and reversible adverse events following cell transplantation, our study indicated that NPC transplantation is a safe therapy in clinical treatment. Further clinical trials are necessary to establish the safety of this therapy.