Machine Learning Algorithms for Classification Patients with Parkinson`s Disease and Hereditary Ataxias

Neurodegenerative diseases are a group of neurological conditions characterized by the loss or destruction of neurons in the central nervous system, resulting in severe impairments and death. Researchers commonly used a two-group classification (Patients with a Neurodegenerative disease vs. healthy subjects of control). Thus, the principal purpose of this article is to distinguish between Parkinson\u27s patients and subjects with Hereditary Ataxias using machine learning techniques. We conducted experiments using a real dataset comprising Gait characteristics derived from the inertial motion sensors of a smartphone (iPhone 5S). This investigation had 67 participants, 53 of who had Parkinson\u27s disease and 14 of whom had Hereditary Ataxias. Methods of feature selection were applied to reduce dimensionality. In addition, five classification algorithms were constructed and assessed based on their accuracy, precision, sensitivity, and specificity. The Support Vector Machine algorithm achieved an accuracy of 92.7%, a precision of 91.1%, a sensitivity of 96.2%, and a specificity of 89.1%. These results show that the suggested technique might inspire new research issues and have a direct therapeutic impact

Obstructive Sleep Apnoea Syndrome, Endothelial Function and Markers of Endothelialization. Changes after CPAP

STUDY OBJECTIVES: This study tries to assess the endothelial function in vivo using flow-mediated dilatation (FMD) and several biomarkers of endothelium formation/restoration and damage in patients with obstructive sleep apnoea (OSA) syndrome at baseline and after three months with CPAP therapy. DESIGN: Observational study, before and after CPAP therapy. SETTING AND PATIENTS: We studied 30 patients with apnoea/hypopnoea index (AHI) >15/h that were compared with themselves after three months of CPAP therapy. FMD was assessed non-invasively in vivo using the Laser-Doppler flowmetry. Circulating cell-free DNA (cf-DNA) and microparticles (MPs) were measured as markers of endothelial damage and the vascular endothelial growth factor (VEGF) was determined as a marker of endothelial restoration process. MEASUREMENTS AND RESULTS: After three month with CPAP, FMD significantly increased (1072.26 ± 483.21 vs. 1604.38 ± 915.69 PU, p< 0.005) cf-DNA and MPs significantly decreased (187.93 ± 115.81 vs. 121.28 ± 78.98 pg/ml, p<0.01, and 69.60 ± 62.60 vs. 39.82 ± 22.14 U/μL, p<0.05, respectively) and VEGF levels increased (585.02 ± 246.06 vs. 641.11 ± 212.69 pg/ml, p<0.05). These changes were higher in patients with more severe disease. There was a relationship between markers of damage (r = -0.53, p<0.005) but not between markers of damage and restoration, thus suggesting that both types of markers should be measured together. CONCLUSIONS: CPAP therapy improves FMD. This improvement may be related to an increase of endothelial restoration process and a decrease of endothelial damage

Increased mRNA expression of cytochrome oxidase in dorsal raphe nucleus of depressive suicide victims

Suicidal behavior is a problem with important social repercussions. Some groups of the population show a higher risk of suicide; for example, depression, alcoholism, psychosis or drug abuse frequently precedes suicidal behavior. However, the relationship between metabolic alterations in the brain and premorbid clinical symptoms of suicide remains uncertain. The serotonergic and noradrenergic systems have frequently been, implicated in suicidal behavior and the amount of serotonin in the brain and CSF of suicide victims has been found to be low compared with normal subjects. However, there are contradictory results regarding the role of noradrenergic neurons in the mediation of suicide attempts, possibly reflecting the heterogeneity of conditions that lead to a common outcome. In the present work we focus on the subgroup of suicide victims that share a common diagnosis of major depression. Based on post-mortem studies analyzing mRNA expression by in situ hybridization, serotonergic neurons from the dorsal raphe nucleus (DRN) from depressive suicide victims are seen to over-express cytochrome oxidase mRNA. However, no corresponding changes were found in the expression of tyrosine hydroxylase (TH) mRNA in the noradrenergic neurons of the Locus Coeruleus (LC). These results suggest that, despite of the low levels of serotonin described in suicide victims, the activity of DRN neurons could increase in the suicidally depressed, probably due to the over activation of serotonin re-uptake. No alteration was found in noradrenergic neurons, suggesting that they play no crucial role in the suicidal behavior of depressive patients

Biochemical characterization of recombinant Candida albicans mannosyltransferases Mnt1, Mnt2 and Mnt5 reveals new functions in O- and N-mannan biosynthesis

Peer reviewedPublisher PD

Knowledge representation tool for cognitiveprocesses modeling

In the last decades, neuropsychological theories tend to consider cognitive functions as a result of the whole brainwork and not as individual local areas of its cortex. Studies based on neuroimaging techniques have increased in the last years, promoting an exponential growth of the body of knowledge about relations between cognitive functions and brain structures [1]. However, so fast evolution make complicated to integrate them in verifiable theories and, even more, translated in to cognitive rehabilitation. The aim of this research work is to develop a cognitive process-modeling tool. The purpose of this system is, in the first term, to represent multidimensional data, from structural and functional connectivity, neuroimaging, data from lesion studies and derived data from clinical intervention [2][3]. This will allow to identify consolidated knowledge, hypothesis, experimental designs, new data from ongoing studies and emerging results from clinical interventions. In the second term, we pursuit to use Artificial Intelligence to assist in decision making allowing to advance towards evidence based and personalized treatments in cognitive rehabilitation. This work presents the knowledge base design of the knowledge representation tool. It is compound of two different taxonomies (structure and function) and a set of tags linking both taxonomies at different levels of structural and functional organization. The remainder of the abstract is organized as follows: Section 2 presents the web application used for gathering necessary information for generating the knowledge base, Section 3 describes knowledge base structure and finally Section 4 expounds reached conclusions