Visualization of back pain data-A 3-D solution

Traditional approaches to gathering and visualizing pain data rely on two-dimensional (2-D) human body models, where different types of sensation are recorded with various monochrome symbols. We proposean alternative that uses a three-dimensional (3-D) representation of the human body, which can be marked in color to visualize and record pain data

Structural Prediction of Protein–Protein Interactions by Docking: Application to Biomedical Problems

A huge amount of genetic information is available thanks to the recent advances in sequencing technologies and the larger computational capabilities, but the interpretation of such genetic data at phenotypic level remains elusive. One of the reasons is that proteins are not acting alone, but are specifically interacting with other proteins and biomolecules, forming intricate interaction networks that are essential for the majority of cell processes and pathological conditions. Thus, characterizing such interaction networks is an important step in understanding how information flows from gene to phenotype. Indeed, structural characterization of protein–protein interactions at atomic resolution has many applications in biomedicine, from diagnosis and vaccine design, to drug discovery. However, despite the advances of experimental structural determination, the number of interactions for which there is available structural data is still very small. In this context, a complementary approach is computational modeling of protein interactions by docking, which is usually composed of two major phases: (i) sampling of the possible binding modes between the interacting molecules and (ii) scoring for the identification of the correct orientations. In addition, prediction of interface and hot-spot residues is very useful in order to guide and interpret mutagenesis experiments, as well as to understand functional and mechanistic aspects of the interaction. Computational docking is already being applied to specific biomedical problems within the context of personalized medicine, for instance, helping to interpret pathological mutations involved in protein–protein interactions, or providing modeled structural data for drug discovery targeting protein–protein interactions.Spanish Ministry of Economy grant number BIO2016-79960-R; D.B.B. is supported by a predoctoral fellowship from CONACyT; M.R. is supported by an FPI fellowship from the Severo Ochoa program. We are grateful to the Joint BSC-CRG-IRB Programme in Computational Biology.Peer ReviewedPostprint (author's final draft

ITS Teaching ASP Dot Net

Abstract: ASP dot net is one of the most widely used languages in web developing of its many advantages, so there are many lessons that explain its basics, so it should be an intelligent tutoring system that offers lessons and exercises for this language.why tutoring system? Simply because it is one-one teacher, adapts with all the individual differences of students, begins gradually with students from easier to harder level, save time for teacher and student, the student is not ashamed to make mistakes, and more. Therefore, in this paper, we describe the design of an Intelligent Tutoring System for teaching ASP dot net to help students learn ASP dot net easily and smoothly. Tutor provides beginner level in ASP dot net. Finally, we evaluated our tutor and the results were excellent by students and teacher

Simultaneous Robotic Manipulation and Functional Magnetic Resonance Imaging: Feasibility in Children with Autism Spectrum Disorders

An unanswered question concerning the neural basis of autism spectrum disorders (ASD) is how sensorimotor deficits in individuals with ASD are related to abnormalities of brain function. We previously described a robotic joystick and video game system that allows us to record functional magnetic resonance images (FMRI) while adult humans make goal- directed wrist motions. We anticipated several challenges in extending this approach to studying goal-directed behaviors in children with ASD and in typically developing (TYP) children. In particular we were concerned that children with autism may express increased levels of anxiety as compared to typically developing children due to the loud sounds and small enclosed space of the MRI scanner. We also were concerned that both groups of children might become restless during testing, leading to an unacceptable amount of head movement. Here we performed a pilot study evaluating the extent to which autistic and typically developing children exhibit anxiety during our experimental protocol as well as their ability to comply with task instructions. Our experimental controls were successful in minimizing group differences in drop-out due to anxiety. Kinematic performance and head motion also were similar across groups. Both groups of children engaged cortical regions (frontal, parietal, temporal, occipital) while making goal- directed movements. In addition, the ASD group exhibited task- related correlations in subcortical regions (cerebellum, thalamus), whereas correlations in the TYP group did not reach statistical significance in subcortical regions. Four distinct regions in frontal cortex showed a significant group difference such that TYP children exhibited positive correlations between the hemodynamic response and movement, whereas children with ASD exhibited negative correlations. These findings demonstrate feasibility of simultaneous application of robotic manipulation and functional imaging to study goal-directed motor behaviors in autistic and typically developing children. The findings also suggest the presence of marked changes in neural activation during a sensorimotor task requiring goal- directed movement

ITS for Teaching French

Abstract: The paper depicts the blueprint of an electronic wise indicating system for demonstrating learning French to understudies to overcome the inconveniences they go up against. The fundamental idea of this structure is a proficient introduction into learning French. The system shows the purpose of learning French and coordinates thusly made issues for the understudies to clarify. The system is logically balanced at run time to the understudy’s individual progress. The system gives unequivocal help to adaptable presentation to learners

3-D pain drawings-mobile data collection using a PDA

A large number of the adult population suffers from some kind of back pain during their lifetime. Part of the process of diagnosing and treating such back pain is for a clinician to collect information as to the type and location of the pain that is being suffered.Traditional approaches to gathering and visualizing this pain data have relied on simple 2-D representations of the human body, where different types of sensation are recorded with various monochrome symbols. Although patients have been shown to prefer such drawings to traditional questionnaires, these pain drawings can be limited in their ability to accurately record pain. The work described in this paper proposes an alternative that uses a 3-D representation of the human body, which can be marked in color to visualize and record the pain data. This study has shown that the new approach is a promising development in this area of medical practice and has been positively received by patients and clinicians alike

EEG-Biofeedback and epilepsy: concept, methodology and tools for (neuro)therapy planning and objective evaluation

EEG-Biofeedback and Epilepsy: Concept, Methodology and Tools for (Neuro)therapy Planning and Objective Evaluation ABSTRACT Objective diagnosis and therapy evaluation are still challenging tasks for many neurological disorders. This is highly related to the diversity of cases and the variety of treatment modalities available. Especially in the case of epilepsy, which is a complex disorder not well-explained at the biochemical and physiological levels, there is the need for investigations for novel features, which can be extracted and quantified from electrophysiological signals in clinical practice. Neurotherapy is a complementary treatment applied in various disorders of the central nervous system, including epilepsy. The method is subsumed under behavioral medicine and is considered an operant conditioning in psychological terms. Although the application areas of this promising unconventional approach are rapidly increasing, the method is strongly debated, since the neurophysiological underpinnings of the process are not yet well understood. Therefore, verification of the efficacy of the treatment is one of the core issues in this field of research. Considering the diversity in epilepsy and its various treatment modalities, a concept and a methodology were developed in this work for increasing objectivity in diagnosis and therapy evaluation. The approach can also fulfill the requirement of patient-specific neurotherapy planning. Neuroprofile is introduced as a tool for defining a structured set of quantifiable measures which can be extracted from electrophysiological signals. A set of novel quantitative features (i.e., percentage epileptic pattern occurrence, contingent negative variation level difference measure, direct current recovery index, heart rate recovery ratio, and hyperventilation heart rate index) were defined, and the methods were introduced for extracting them. A software concept and the corresponding tools (i.e., the neuroprofile extraction module and a database) were developed as a basis for automation to support the methodology. The features introduced were investigated through real data, which were acquired both in laboratory studies with voluntary control subjects and in clinical applications with epilepsy patients. The results indicate the usefulness of the introduced measures and possible benefits of integrating the indices obtained from electroencephalogram (EEG) and electrocardiogram for diagnosis and therapy evaluation. The applicability of the methodology was demonstrated on sample cases for therapy evaluation. Based on the insights gained through the work, synergetics was proposed as a theoretical framework for comprehending neurotherapy as a complex process of learning. Furthermore, direct current (DC)-level in EEG was hypothesized to be an order parameter of the brain complex open system. For future research in this field, investigation of the interactions between higher cognitive functions and the autonomous nervous system was proposed. Keywords: EEG-biofeedback, epilepsy, neurotherapy, slow cortical potentials, objective diagnosis, therapy evaluation, epileptic pattern quantification, fractal dimension, contingent negative variation, hyperventilation, DC-shifts, instantaneous heart rate, neuroprofile, database system, synergetics.Die Epilepsie ist eine komplexe neurologische Erkrankung, die auf biochemischer und physiologischer Ebene nicht ausreichend geklärt ist. Die Vielfalt der epileptischen Krankheitsbilder und der Behandlungsmodalitäten verursacht ein Defizit an quantitativen Kenngrößen auf elektrophysiologischer Basis, die die Objektivität und die Effizienz der Diagnose und der Therapieevaluierung signifikant erhöhen können. Die Neurotherapie (bzw. EEG-Biofeedback) ist eine komplementäre Behandlung, die bei Erkrankungen, welche in Zusammenhang mit Regulationsproblemen des Zentralnervensystems stehen, angewandt wird. Obwohl sich die Applikationen dieser unkonventionellen Methode erweitern, wird sie nach wie vor stark diskutiert, da deren neuro- und psychophysiologischen Mechanismen wenig erforscht sind. Aus diesem Grund ist die Ermittlung von Kenngrößen als elektrophysiologische Korrelaten der ablaufenden Prozesse zur objektiven Einstellung und Therapievalidierung eines der Kernprobleme des Forschungsgebietes und auch der vorliegenden Arbeit. Unter Berücksichtigung der aktuellen neurologischen Erkenntnisse und der durch Untersuchungen an Probanden, sowie an Epilepsie-Patienten gewonnenen Ergebnisse, wurden ein Konzept und eine Methodologie entwickelt, um die Objektivität in der Diagnose und Therapieevaluierung zu erhöhen. Die Methodologie basiert auf einem Neuroprofil, welches als ein signalanalytisches mehrdimensionales Modell eingeführt wurde. Es beschreibt einen strukturierten Satz quantifizierbarer Kenngrößen, die aus dem Elektroenzephalogramm (EEG), den ereignisbezogenen Potentialen und dem Elektrokardiogramm extrahiert werden können. Als Komponenten des Neuroprofils wurden neuartige quantitative Kenngrößen (percentage epileptic pattern occurrence, contingent negative variation level difference measure, direct current recovery index, heart rate recovery ratio, hyperventilation heart rate index) definiert und die Methoden zu deren Berechnung algorithmisiert. Die Anwendbarkeit der Methodologie wurde beispielhaft für die Evaluierung von Neurotherapien an Epilepsie-Patienten demonstriert. Als Basis für eine zukünftige Automatisierung wurden ein Softwarekonzept und entsprechende Tools (neuroprofile extraction module und die Datenbank ?NeuroBase?) entwickelt. Der Ansatz erfüllt auch die Anforderungen der patientenspezifischen Therapieplanung und kann auf andere Krankheitsbilder übertragen werden. Durch die neu gewonnenen Erkenntnisse wurde die Synergetik als ein theoretischer Rahmen für die Analyse der Neurotherapie als komplexer Lernprozess vorgeschlagen. Es wurde die Hypothese aufgestellt, dass das Gleichspannungsniveau im EEG ein Ordnungsparameter des Gehirn ist, wobei das Gehirn als ein komplexes offenes System betrachtet wird. Für zukünftige Forschungen auf dem Gebiet wird empfohlen, die Wechselwirkungen zwischen den höheren kognitiven Funktionen und dem autonomen Nervensystem in diesem Kontext zu untersuchen

miRNAs link metabolic reprogramming to oncogenesis

The most profound biochemical phenotype of cancer cells is their ability to metabolize glucose to lactate, even under aerobic conditions. This alternative metabolic circuitry is sufficient to support the biosynthetic and energy requirements for cancer cell proliferation and metastasis. Alterations in oncogenes and tumor suppressor genes are involved in the metabolic switch of cancer cells to aerobic glycolysis, increased glutaminolysis and fatty acid biosynthesis. MiRNAs mediate fine-tuning of genes involved directly or indirectly in cancer metabolism. In this review, we discuss the regulatory role of miRNAs on enzymes, signaling pathways and transcription factors involved in glucose and lipid metabolism. We further consider the therapeutic potential of metabolism-related miRNAs in cancer