5^th International Conference on Brain Disorders and Therapeutics Nov 29-30, 2017 Madrid, Spain

Biography:

Eyad Faizo is a certified licensed Medical Doctor specialized in Neurosurgery and spine surgery practicing in Murnau Hospital south Germany. He presented in international seminars, media interviews and conferences in Health Care and education. Member of the Advisory boards in many German medical companies. Member of the German and European Neurosurgical Societies.

Abstract:

The sacroiliac joint, or SI Joint, is the joint next to the bottom of the spine connecting the sacrum with the pelvis. Treatments for SI joint pain are usually non-surgical, and focus on the restoration of normal motion of the joint. SI joint irritation is a common cause of low back pain

Biography:

Ana Gámez-Valero obtained her degree in Biotechnology in the University Pablo de Olavide (Seville). During the four years, he had the opportunity to study a year in France where she started research experience in the Histology Department of the medical school (Nîmes). In 2013, he obtained an MSc in Advanced Genetics from the Universidad Autónoma of Barcelona. Since 2015, she is carrying out PhD project named “Identification of specific biosignatures from plasma samples for differential diagnosis of dementia with Lewy bodies” in the IGTP Institute in Badalona, having already published four research articles.

Abstract:

Dementia with Lewy bodies (DLB) shows overlapping features with Alzheimer disease (AD) leading to its misdiagnosis and hindering its adequate treatment. It is well established that microRNAs play an important role in neurodegeneration and they can be found in brain and the central nervous system. Since 30 years, the presence of RNA (mRNA and microRNA) in platelets has attracted attention and different mRNA expression patterns have been reported to be altered in human diseases. Our main objective was to identify disease specific mRNA and miRNA biosignatures through the analysis of platelet rich plasma (PRP) obtained from DLB patients (n=31), AD patients (n=10) and age-matched control individuals (n=31). After isolation of mRNA and miRNA from PRP, we analyzed SNCA and GBA mRNA expression levels in DLB patients and controls by reverse-transcription real time PCR; next generation sequencing was applied for miRNA discovery in the same samples. 22 miRNAs were differentially expressed and selected to be validated by real time qPCR. From those, 9 were considered as potential biomarkers for DLB being evaluated in a group of AD patients and independent groups of control and DLB individuals. Interestingly, miRNAs levels seemed to correlate with clinical symptoms and to correlate inversely with SNCA-mRNA expression in DLB patients. These results, although replication and follow-up with larger, carefully characterized cohorts are needed, represent an integrated miRNA and mRNA profile in platelet rich plasma that is likely to provide non-invasive biomarkers for the differential diagnosis of DLB versus AD.

Biography:

Juan Manuel Isusi Alcazar is a specialist in radiology and image cursing in public and private hospitals. Subspecialist in neurorradiology graduated from the national institute of neurology and neurosurgery in the city of mexico. He has participated in various congresses as a speaker and with national electronic works from his country within the Mexican Society of Radiology Mexican and Mexican Society of Neurorradiology. Also has participated in international congresses within the Iberoamerican Society of Neuroradiology (SILAN), Argentine Society of Radiology, European Society of Radiology. He was head of service within public hospitals within the Mexican Institute of Social Security (IMSS), until he arrived as medical deputy director in the state of Mexico. Neurorradiology founder of the Mexican School of Molecular Radiology in the city of Mexico since 2015. Currently carries two masters one in hospital administration and health management and the other is high address. And this is improving your english in the UNAM to bring other borders with the cerebral pet ct.

Abstract:

Considering the intrinsic limits of fluorine-18-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) for diagnosing brain tumors and tumor recurrence, several radiopharmaceuticals have been developed to detect brain tumor recurrence after treatment. Among others, a promising tracer is fluorine-18- desoxyphenylalanine (DOPA), due to its very low rate of physiological distribution in normal brain structures of white and grey matter. The aim of our study was to assess the feasibility of PET/CT with 18 F-DOPA in the detection of brain tumor recurrence aftertreatment, in comparison with MRI performance and other PET radiopharmaceuticals, currently employed in this field. The 18F-DOPA PET/CT seems to be useful in the diagnosis of patients with suspected brain tumor recurrence, because of low signal ratio in normal brain white and grey matter, in particular as compared to 18 F-FDG PET/CT low performance. Related data are presented for other fluorinated amino acid tracers. Magnetic resonance imaging is the gold standard of diagnosis and 18F-DOPA PET/CT is adjuvant to diagnosis. Further studies are needed to enrich our knowledge about this promising tracer,18 F- DOPA, especially on its possible role on semi-quantitative measurements in brain tumors.

Biography:

Morteza Kolali Khormuji received his BS Degree in Computer Engineering in 2011, and started his MS Degree in Artificial Intelligence from University of Science and Research Branch of Bushehr, Iran, in 2012. He was Technology Development Engineer at Lian AvA Corp in Bushehr. His research interests include pattern recognition, machine learning, image processing and computer vision.

Abstract:

High-dimensional genomic and proteomic data play an important role in many applications in medicine such as prognosis of diseases, diagnosis, prevention and molecular biology, to name a few. Classifying such data is a challenging task due to the various issues such as curse of dimensionality, noise and redundancy. Recently, some researchers have used the sparse representation (SR) techniques to analyze high-dimensional biological data in various applications in classification of cancer patients based on gene expression datasets. A common problem with all SR-based biological data classification methods is that they cannot utilize the topological (geometrical) structure of data. More precisely, these methods transfer the data into sparse feature space without preserving the local structure of data points. In this paper, we proposed a novel SR-based cancer classification algorithm based on gene expression data that takes into account the geometrical information of all data. Precisely speaking, we incorporate the local linear embedding algorithm into the sparse coding framework, by which we can preserve the geometrical structure of all data. For performance comparison, we applied our algorithm on six tumor gene expression datasets, by which we demonstrate that the proposed method achieves higher classification accuracy than state-of-the-art SR-based tumor classification algorithms.

Biography:

Zubrickaya Ekaterina is a postgraduate student and an assistant of the Department of Nervous Diseases, and a neurologist-neuropsychologist in Siberian Scientific and Clinical Centre. E. Zubrickaya performs research work on the topic of cognitive rehabilitation of patients with posttraumatic cognitive impairment, and participates in the development of new methods of the recovery. The author has participated in international and national conferences. The postgraduate student is the winner of Young Scientists Competitions of regional, national and international levels. The author is the coauthored of several scientific articles in journals approved by HAC and has some abstracts at scientific conferences.

Abstract:

Background & Aim: Traumatic brain injury (TBI) has been one of the most topical issues in medicine around the world. Epidemiological studies demonstrate an extremely high frequency of TBI in Russia about 600,000 people annually, and up to four and more persons per 1000 persons a year. According to the rate of injuries in developed countries in terms of overall economic and socio-medical damage to the society, TBI is the first one. The average age of the injured varies from 23 to 39.6, which affects the most economically and socially active group. The prevalence of cognitive impairments depending on the severity of the injury, according to many authors, stands at 70 to 100%. In the patients with concussion it is as high as 93.75%, with mild brain injury of 90%, with moderate-to-severe injury of 98.6%. Therefore, further research into the cognitive impairment treatment after brain injury is both medically and socio-economically important and constitutes an urgent issue at the present time.

Results & Discussion: None of the electroencephalograms of the 15 examined revealed epiactivity; 12 patients (80%) underwent operative intervention; 11 patients (73.3%) were in coma for over 10 days. As for neuropsychological impairments, all patients were diagnosed with cognitive impairments of a mild (66.7%) and large (33.3%) degree. Particularly notable is the prevalence of impairments involving inhibition of the rate of mental activity, calculation, memory, and visual spatial cognition. As a result of the treatment course that involved computer-assisted training, the patients showed statistically significant improvements in relation to the neuropsychological screening tests: MMSE (p=0.07, Ме1=25, Ме2=27), FAB (p=0.01, Ме1=15, Ме2=16), Schulte tables (p=0.01, Ме1=47, Ме2=38.6), clock-drawing test (р=0.01, Ме1=8, Ме2=9), level of anxiety as per HADS (р=0.02, Ме1=3, Ме2=2) and level of depression as per HADS (р=0.04, Ме1=2, Ме2=2), Luria 10-word memory test with immediate recall (р=0.007, Ме1=6, Ме2=7), abstract reasoning test with 6 figures (р=0.005, Ме1=16, Ме2=20), verbal reasoning test with literal stimuli (р=0.007, Ме1=11, Ме2=13) and categorical reasoning test (р=0.01, Ме1=10, Ме2=12). The incomplete figure perception test did not prove to be statistically significant (р=0.17, Ме1=6, Ме2=6). As a result of the training course, there was a strong tendency towards statistical significance of improvement in relation to the 10 word memory test with delayed recall (р=0.06, Ме1=5, Ме2=6). The examined patients mentioned subjectively estimated improvement in attention and concentration (81.8%), higher daily activity, lower level of emotional and volitional disorders (72.7%).

Conclusion: Thus cognitive impairments occurring after TBI are a widely spread symptom significantly affecting the performance efficiency and welfare of patients. The first experience in application of computer-assisted training to address the cognitive impairments in patients with moderate-to-severe TBI proved to be successful. Based on the data from the conducted pilot study, this method may be recommended as a part of the comprehensive rehabilitation treatment of patients with cognitive impairments in the interim and residual periods of TBI.

Biography:

Abstract: