Volume 11, 2017
Title of the Paper: Effect of Sling Rehabilitation Exercises with Vibration Balls on the Upper Limb Muscle Activity for Disabled People
Authors: Ju-Hwan Oh, Tae-Kyu Kwon
Abstract: The purpose of the present study is to verify the effectiveness of a muscle activity by applying the complex functional exercise methods and active rehabilitation methods of sling exercises in accordance with the provision of vibration for people with myelopathy. Study subjects were 16 men in their 40s and 50s with lower limb disabilities. They were randomly divided into a sling exercise group (SG n=4), a sling with low frequency vibration group (SLVG n=4), a sling with mid-frequency vibration group (SMVG n=4), and a sling with high frequency group (SHVG n=4). The anterior deltoid (AD), the posterior deltoid (PD), the pectoralis major (PM), the upper trapezius (UT), the latissimus dorsi (LD), the triceps (TC), the biceps (BC), and the multifidus (MF) were measured to compare and analyze muscle activity. One-way ANOVA was conducted to compare the recovery effects by using SPSS 18.0 Korea. The statistical significance was accepted at p<0.05. Our results showed that the low intensity vibration (30Hz) was the effective stimuli for open kinetic chain exercises, while vibration stimuli of an mid intensity (50Hz) were the effective vibration for closed kinetic chain.
Title of the Paper: Interaction of Lysine Dendrimers with Therapeutic Peptides – Molecular Dynamics Simulation
Authors: Igor Neelov, Elena Popova, Dilorom Khamidova, Irina I. Tarasenko
Abstract: Lysine dendrimers are highly branched molecules. They are often used for drug and other molecules delivery to different target cells. In present study the properties of complexes of lysine dendrimers with two types of therapeutic peptides (Semax and Epithalon) were compared using molecular dynamics. Our simulation demonstrates that the lysine dendrimer form complexes with both types of therapeutics peptides. It was shown that combination of two types of interactions (electrostatic and hydrophobic) result in complex formation in all cases – electrostatic and hydrophobic. It was also demonstrated, that electrostatic interactions between dendrimer and peptides in all complexes are stronger than hydrophobic. Structures of the complexes were investigated and it wa shown that decrease of electrostatic interactions leads to the destruction of the complex and the release of peptides from it.
Title of the Paper: Gait Analysis for Elderly People with Visual Impairment using Plantar Pressure Measurement
Authors: Ji-Yong Jung, Chang-Min Yang, Jung-Ja Kim
Abstract: Independent walking for elderly people with visual impairment is one of the important things in their daily lives. Accordingly, the objective of this study is to understand the gait characteristic of elderly people with visual impairment using plantar pressure distribution analysis. Ten male subjects who are visually impaired were recruited from the Korea Blind Union. Experimental procedure was divided into two conditions: walking without the white cane and with the white cane. The plantar pressure distributions were assessed during walking at a comfortable speed along a 10 m walkway. All plantar pressure distributions were subdivided into six regions of masks and five phases, and these data were analyzed for the force and pressure. The results showed that the maximum force and mean pressure of the right side increased while the peak pressure of that side decreased significantly. In addition, there was association with the foot regions and stance phase during walking both without and with the white cane. This paper suggest that gait and postural balance pattern of elderly people with visual impairment could be influenced by walking assistive device. Therefore, more researches are needed based on the gait characteristic to develop new types walking assistive device and provide appropriate rehabilitation strategies for people with visual impairment.
Title of the Paper: Application of Decision Tree and Neural Network for Diagnosis and Prescription of Pediatric Foot Disorders
Authors: Jungkyu Choi, Hee-Sang Lee, Jung-Ja Kim
Abstract: Decision trees and neural networks are typical data classification methods in data mining methods. Decision trees are so fast and interpretable, but these can be misclassified. Neural networks are slow while more reliable algorithms. In this paper, we have studied an intelligent system that diagnose and prescribe patients with pediatric foot disorder using decision tree and neural network. The object of this study was to discover meaningful knowledge between the foot disorder and biomechanical parameters related to symptoms using C5.0 decision tree and neural network. The first medical record data of 174 pediatric patients were extracted for analysis, in total 279 records, and they were diagnosed with a complex foot disorder. The dependent variable consists of five complex disorder groups, and 14 independent variables related to disorder groups were selected by importance, in 34 variables. The extracted data was separated to generate an ideal prediction model. After development of the prediction model, the prediction rate was verified and neural networks were applied for analysis of predictor importance and classification prediction. Consequently, a major symptom information in 13 diagnosis patterns were confirmed.
Title of the Paper: Testing the Independence Hypothesis of Accepted Mutations for Pairs of Adjacent Amino Acids in Protein Sequences
Authors: Jyotsna Ramanan, Peter Z. Revesz
Abstract: Evolutionary studies usually assume that the genetic mutations are independent of each other. However, that does not imply that the observed mutations are independent of each other because it is possible that when a nucleotide is mutated, then it may be biologically beneficial if an adjacent nucleotide mutates too. With a number of decoded genes currently available in various genome libraries and online databases, it is now possible to have a large-scale computer-based study to test whether the independence assumption holds for pairs of adjacent amino acids. Hence the independence question also arises for pairs of adjacent amino acids within proteins. The independence question can be tested by considering the evolution of proteins within a closely related sets of proteins, which are called protein families. In this thesis, we test the independence hypothesis for three protein families from the PFAM library, which is a publicly available online database that records a growing number of protein families. For each protein family, we construct a hypothetical common ancestor, or consensus sequence. We compare the hypothetical common ancestor of a protein family with each of the descendant protein sequences in the family to test where the mutations occurred during evolution. The comparison yields actual probabilities for each pair of amino acids changing into another pair of amino acids. By comparing the actual probabilities with the theoretical probabilities under the independence assumption, we identify anomalies that indicate that the independence assumption does not hold for many pairs of amino acids.
Title of the Paper: Better Decision Tree of Accuracy for the Task of Diagnosis of Hepatitis
Authors: Hyontai Sug
Abstract: Hepatitis is a liver disease that can be self-limiting or can cause even death of the patients so that diagnosing the disease correctly is important. As a process of diagnosing the disease understandability of the diagnosed results may be important, because it is related to human life and final decision is attributed to doctors. Decision trees are one of data mining algorithms that can generate understandable knowledge structure which is in tree shape so that the algorithms have been used widely in medicine domain. But, because the algorithms give higher priority to major classes for better accuracy, this may cause poorer results in classification of minor classes. Over-sampling for a minor class has been considered a possible solution for the problem to get better results. But, even though we use the technique, there is innate property in the data and data mining algorithm themselves, which hinders data mining task. If we build a decision tree using a training data set, some data instances are classified wrongly, and these instances may cause lower accuracy. In order to avoid such instances decision tree with higher confidence is used to check each training instances in the minor class, and good ones only are adopted in the later over-sampling process. Experiments using hepatitis data set in various over-sampling rates showed very good results.
Title of the Paper: Pectin Coated Iron Oxide Nanocomposite – a Vehicle for Controlled Release of Curcumin
Authors: Mausumi Ganguly, Deepika Pramanik
Abstract: We report a nanocomposite system capable of efficient drug loading and drug release. The water-soluble iron oxide nanoparticles (IONPs) with particle sizes up to 27 nm were obtained via co-precipitation method. These nanoparticles were coated with pectin to avoid their chances of agglomeration and also to increase the biocompatibility. The nanocomposites obtained were characterized using transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), X-ray powder diffraction (XRD) and zeta-potential measurements. The nanocomposite was used to load curcumin, an anticancer compound. The drug loading efficiency of the nanocomposite preparation was evaluated. The drug release from the nanocomposite matrix was studied at four different pH values. The results indicated that the release of drug was not significant in acidic pH but occurred at a uniform and desired rate in alkaline pH. Thus the prepared nanocomposite can act as a vehicle for controlled drug delivery.
Title of the Paper: An Ontology-Driven Toolset for Fast Prototyping of Medical Data Processing Systems
Authors: Sergey Lebedev, Nataly Zhukova, Alexander Vodyaho, Dmitry Kurapeev, Mikhail Lushnov
Abstract: Nowadays data processing systems are widely used by researchers for solving different problems in diverse subject domains including medicine. Usage of these systems encounters three problems. The first problem is a necessity to rebuild the system as often as the subject domain changes. The second problem is a necessity to integrate obtained results into the information system that is used by regular specialists. The third problem is that software development engineers usually do not appear to be specialists in the subject domain. All mentioned problems are highly significant to the medical domain. In the paper, an ontology-driven toolset for fast prototyping of medical data processing system is proposed. The toolset is based on the approach that defines a transition from the domain model to the software system prototype. The proposed approach is based on ontology-driven design and development, automation, and component reuse. The toolset is evaluated on a case study from medical domain.
Title of the Paper: The Improvement Effect of Muscle Strength Imbalance According to Sound Stimulus during Gait with Analysis of Muscular Activity and Foot Pressure
Authors: Seung-Rok Kang, Chul-Un. Hong, Tae-Kyu Kwon
Abstract: This study was to develop the balance insole system for detecting and improving the muscle imbalance of left and right side in lower limbs. We were to verify the validation of balance insole system by analyzing the strategy of muscular activities and foot pressure according to sound feedback. We developed the balance insole based FSR sensor modules for estimating the muscle imbalance using detecting foot pressure. The insole system was FPCB have 8-spot FSR sensor with sensitivity range of 64-level. The participants were twenty peoples who have muscle strength differences in left and right legs over 20%. We measured the muscular activity and foot pressure of left and right side of lower limbs in various gait environment for verifying the improvement effect of muscle imbalance according to sound feedback. They performed gait in slope at 0, 5, 10, 15% and velocity at 3, 4, 5km/h. The result showed that the level of muscle imbalance reduced within 30% for sound feedback of balance insole system contrast to high level of muscle imbalance at 169.9~279.15% during normal gait for increasing slope and velocity including foot force results. This study found the validation of balance insole system with sound feedback stimulus. Also, we thought that it is necessary to research on the sensitivity of foot area, detection of muscle imbalance and processing algorithm of correction threshold spot.
Title of the Paper: Identification of a Oculo-Motor System Human Based on Volterra Kernels
Authors: Vitaliy D. Pavlenko, Dmytro V. Salata, Hryhori P. Chaikovskyi
Abstract: A new method of constructing nonparametric dynamic model of the human oculomotor system on the basis of experimental data “input-output” is developed, considering nonlinear and inertial properties of the rectus muscles of the eye. A technology for tracking eye movement is based on the videos. It is possible to determine the dynamic characteristics of the oculo-motor system system functions as a transition of the first and second order – integral transforms Volterra kernels.
Title of the Paper: Collimator Study of a Pre-Clinical Pixelated Semiconductor SPECT System Using Monte Carlo Simulation
Authors: Hyun-Woo Jeong, Jong Seok Kim, Se Young Bae, Kanghyen Seo, Seung Hun Kim, Seong Hyeon Kang, Dong Jin Shin, Kyuseok Kim, Youngjin Lee
Abstract: In single photon emission computed tomography (SPECT) with pixelated semiconductor detector (PSD), not only pinhole collimator but also parallel-hole collimator is often used in pre-clinical nuclear medicine imaging system. The purpose of this study was to evaluate and compare pinhole and parallel-hole collimators in PSD. In this study, we performed a simulation study of the PID 350 (Ajat Oy Ltd., Finland) CdTe PSD using a Geant4 Application for Tomographic Emission (GATE) simulation. For that purpose, we designed four collimators which are most frequently used in the pre-clinical nuclear medicine: (1) pinhole collimator, (2) low energy high resolution (LEHR), (3) low energy general purpose (LEGP), and (4) low energy high sensitivity (LEHS) parallel-hole collimator. The sensitivity and spatial resolution of the four collimators were evaluated using point source. Moreover, to assess the overall performance of the imaging system, a hot-rod phantom was designed using a GATE simulation. The highest sensitivity was achieved using LEHS, followed by LEGP, LEHR, and pinhole. Also, at 2 cm source-to-collimator distance, the spatial resolution was 1.63, 2.05, 2.79, and 3.45 mm using pinhole, LEHR, LEGP, and LEHS, respectively. The reconstructed hot-rod phantom images showed that the pinhole collimator and the LEHR parallel-hole collimator give a fine spatial resolution for pre-clinical SPECT with PSD. In conclusion, we successfully compared different types of collimator with pre-clinical pixelated semiconductor SPECT system.
Title of the Paper: Efficient Electrocardiogram (ECG) Lossy Compression Scheme for Real Time e-Health Monitoring
Authors: Hatim Anas, Rachid Latif, Mounir Arioua
Abstract: E-health monitoring is adopted to solve multiple problems such as: difficult access to hospitals, health monitoring of old patients … Several operations slow down the e health systems, the most important one is the signal compression / decompression step. In this paper we present a new algorithm for compression / decompression of the ECG vital signal. The complexity of the proposed algorithm is very low and uses simple mathematical operations. In a hardware point of view, this property makes it suitable for real-time e-health monitoring. The algorithm’s kernel is based on the delta coding technique. We introduced two coding categories low and high and we defined a new frame format. This allows us to minimize the total amount of bits of the compressed signal. Three variants of the algorithm are designed and tested using the MIT-BIH physionet and PTB Diagnostic data bases. We used several signals with different cardiac pathologies for test. We reach a maximum compression ratio (CR) of 47 with a PRD of 0,073%. Our algorithm outperforms the state of the art techniques.
Title of the Paper: Interaction of Lysine Dendrimers of 2nd and 3rd Generation with Stack of Amyloid Peptides. Molecular Dynamics Simulation
Authors: I. Neelov, E. Popova, D. Khamidova, F. Komilov
Abstract: In present paper, molecular dynamics simulation is used to study amyloid fibril destruction by oppositely charged dendrimers of second and third generation. Dendrimers are often used for delivery of drugs and biological molecules. They also could be used as antibacterial, antiviral and antiamyloid agents. Since lysine dendrimers are less toxic than conventional synthetic dendrimers), they were chosen for present study and systems consisting of 2nd and 3rd generation dendrimers and stack of 16 short amyloid peptides in water were studied. It was shown that lysine dendrimers of both generations destroy amyloid stack and form stable complexes with amyloid peptides. The structures of the complexes in equilibrium state were investigated. Also it was obtained that peptides in complexes stay mainly on the surface of dendrimer and do not penetrate into them. The results obtained in present paper could be useful for elaboration in future the antiamyloiud agents for treatment of Alzheimer’s disease, since it is believed that one of the reasons for its occurrence is the formation of amyloid fibrils.
Title of the Paper: Analysis of the Influence of Trauma Injury Factors on the Probability of Survival
Authors: M. Saleh, R. Saatchi, F. Lecky, D. Burke
Abstract: The probability or likelihood of survival in trauma injuries is a clinically important parameter for triage, setting treatment priorities and research and management audit. The existing methods for determining it have short comings that necessitate further development. In this study, an artificial intelligence method called fuzzy inference system (FIS) for determining the likelihood of survival in trauma injuries is being developed and evaluated. The accuracy of the FIS primarily depends on the design of its knowledge base. The required knowledge base is being designed by carrying out a detailed statistical analysis of the trauma injury profiles contained in a large data base of injury cases. As part of this analysis, the relationships between the body regions affected by trauma injuries, physiological measures (such as blood pressure, respiration rate and heart rate), age, gender , the neurological factors assessed by the Glasgow Comma Score and pre-exiting medical conditions on the probability of survival were analysed and a FIS system to indicate the likelihoods survival was proposed. The preliminary results obtained are presented.
Title of the Paper: Numerical Study of Identification of the Main Characteristics of Air Transport in the Human Nasal Cavity
Authors: Alibek Issakhov, Aizhan Abylkassymova
Abstract: In this paper was considered the use of the numerical study of identification the main characteristics of air transport in the human nasal cavity. Investigation of air flow in the human nasal cavity is of considerable interest since breathing is done mainly through the nose. In this study conducted a two-dimensional numerical simulation of air transport in the cross-sections model of the nasal cavity to normal human nose based on the Navier-Stokes equations, the temperature transport equations and relative humidity equation. For the numerical solution of this system of equations is used projection method. The numerical solution of the equation system is divided into five stages. At the first step, it is assumed that the momentum transfer by convection and diffusion. The intermediate velocity field is solved by the 5-step Runge–Kutta method. At the second stage, the pressure field is solved by the found intermediate velocity field. The Poisson equation for the pressure field is solved by the Jacobi method. The third step assumes that the transfer is carried out only by the pressure gradient. The fourth and fifth steps of the temperature and relative humidity equations are also solved as momentum equations, with the 5-step Runge–Kutta method. This numerical algorithm fully parallelized using different geometric decompositions. The obtained data transfer numerical modelling air human nasal cavity was verified with known numerical results in the form of velocity, temperature and relative humidity profiles.
Title of the Paper: Use of Statistical Approaches and Artificial Neural Networks to Identify Gait Deviations in Children with Autism Spectrum Disorder
Authors: Che Zawiyah Che Hasan, Rozita Jailani, Nooritawati Md. Tahir
Abstract: Automated differentiation of ASD gait from normal gait patterns is important for early diagnosis as well as ensuring rapid quantitative clinical decision and appropriate treatment planning. This study explores the use of statistical feature selection approaches and artificial neural networks (ANN) for automated identification of gait deviations in children with ASD, on the basis of dominant gait features derived from the three-dimensional (3D) joint kinematic data. The gait data from 30 ASD children and 30 normal healthy children were measured using a state-of-the-art 3D motion analysis system during self-selected speed barefoot walking. Kinematic gait features from the sagittal, frontal and transverse joint angles waveforms at the pelvis, hip, knee, and ankle were extracted using time-series parameterization. Two statistical feature selection techniques, namely the between-group tests (independent samples t-test and Mann-Whitney U test) and the stepwise discriminant analysis (SWDA) were adopted as feature selector to select the meaningful gait features that were then used to train the ANN. The 10-fold cross-validation test results indicate that the selected gait features using SWDA technique are more reliable for ASD gait classification with 91.7% accuracy, 93.3% sensitivity, and 90.0% specificity. The findings of the current study demonstrate that kinematic gait features with the combination of SWDA feature selector and ANN classifier would serve as a potential tool for early diagnosis of gait deviations in children with ASD as well as provide support to clinicians and therapists for making objective, accurate, and rapid clinical decisions that lead to the appropriate targeted treatments.
Title of the Paper: Lung Cancer Detection and Classification with 3D Convolutional Neural Network (3D-CNN)
Authors: Wafaa Alakwaa, Mohammad Nassef, Amr Badr
Abstract: This paper demonstrates a computer-aided diagnosis (CAD) system for lung cancer classification of CT scans with unmarked nodules, a dataset from the Kaggle Data Science Bowl 2017. Thresholding was used as an initial segmentation approach to segment out lung tissue from the rest of the CT scan. Thresholding produced the next best lung segmentation. The initial approach was to directly feed the segmented CT scans into 3D CNNs for classification, but this proved to be inadequate. Instead, a modified U-Net trained on LUNA16 data (CT scans with labeled nodules) was used to first detect nodule candidates in the Kaggle CT scans. The U-Net nodule detection produced many false positives, so regions of CTs with segmented lungs where the most likely nodule candidates were located as determined by the U-Net output were fed into 3D Convolutional Neural Networks (CNNs) to ultimately classify the CT scan as positive or negative for lung cancer. The 3D CNNs produced a test set Accuracy of 86.6%. The performance of our CAD system outperforms the current CAD systems in literature which have several training and testing phases that each requires a lot of labeled data, while our CAD system has only three major phases (segmentation, nodule candidate detection, and malignancy classification), allowing more efficient training and detection and more generalizability to other cancers.
Title of the Paper: Classification of Host Origin in Influenza a Virus by Transferring Protein Sequences into Numerical Feature Vectors
Authors: Fayroz F. Sherif, Nourhan Zayed, Mahmoud Fakhr
Abstract: Global outbreaks of human influenza occur from influenza A viruses with novel Hemagglutinin (HA) molecules to which humans have no immunity. So accurate detection of influenza viral origin is of particular importance to improve influenza surveillance and vaccine development. Here, a total of 1500 and 2349 protein sequences for Hemagglutinin (HA) and Neuraminidase (NA) respectively were selected to be involved in our study. We used two techniques to transfer the protein sequences into feature vectors firstly, the feature vector constructed from the composition of amino acids (AAC) and secondly the feature vector constructed from the Composition, Transition, Distribution (CTD). Both used separately for the training of machine learning algorithms. Host of origin classification models constructed using KNN and random forest based on AAC and CTD feature vectors. The results guarantee that the classification performance using AAC feature vector achieves slightly better performance than using CDT feature vector. Furthermore host classification using HA protein segment achieved higher accuracy results than NA. The highest host classification model was HA-human using random forest with accuracy 96.6% and 95.3% for AAC and CDT respectively.
Title of the Paper: Study of the Aromatic Profile of Traminer Rot (Gewürztraminer) by GC-MS
Authors: J. Sochor, M. Baron, L. Sochorova, M. Kumsta
Abstract: This paper is focused on the study of the aromatic profile of Traminer rot must, cultivated in the Moravian wine-growing region in the Czech Republic. In our paper, we monitored selected terpenic substances during maceration after 0, 6, 12, 18, 24, 30, and 36 hours. The aromatic profile was studied by gas chromatography with mass detection (GC-MS). Our focus was on the determination of free, bound, and total terpenic substances, in addition to the determination of specific aromatic substances: linalool, geraniol, nerol, alpha-terpineol, and hotrienol. The study confirmed that increasing the maceration time also increases the content of free and total terpenic substances.
Title of the Paper: Risk Analysis of Transesophageal Echocardiography Telemanipulator in Catheterization Laboratory
Authors: Indhika F. Warsito, Christina Pahl, Eko Supriyanto, A. Soesanto
Abstract: The use of conventional Transesophageal Echocardiography (TEE) machine in Catheterization Laboratory (Cath Lab) remain few safety issues related to radiation and ergonomics. In order to solve these, TEE telemanipulator has been proposed. This has however other risks which may arise during the use of the machine including electrical, mechanical, and electromagnetic risks. In this paper, the risk analysis of TEE Telemanipulator in Cath Lab is discussed. This includes the hazard identification and risk level estimation. Electrical, mechanical, electromagnetic, radiation and operational hazards are identified. Failure Mode and Effect Analysis (FMEA) is used to estimate the level of risk. Test result shows that the risk of TEE manipulator type II is lower compare to conventional TEE Machine and TEE manipulator type I.
Title of the Paper: B850 Ring from Light–Harvesting Complex LH2 – Fluctuations in Dipole Moment Orientations of Bacteriochlorophyll Molecules
Authors: Pavel Herman, David Zapletal
Abstract: Interactions with fluctuated environment strongly influence properties of light–harvesting (LH) pigment–protein complexes. Slow fluctuations could be modeled by static disorder. Several types of these fluctuations are connected with changes of ring geometry. Slow fluctuations of bacteriochlorophyll’s dipole moment orientations in B850 ring from LH2 complex of purple bacteria are investigated in present paper. Three modifications of such uncorrelated static disorder type (Gaussian fluctuations of dipole moment orientations in the ring plane, Gaussian fluctuations of dipole moment orientations in a plane which is perpendicular to the ring one and Gaussian fluctuations of dipole moment orientations in arbitrary direction) are taking into account. Distributions of the nearest neighbour transfer integrals are presented and the most important statistical properties are calculated, discussed and compared for different strengths of static disorder.
Title of the Paper: Computational Characterization of Aerosol Delivery for Preterm Infants
Authors: I. Aramendia, U. Fernandez-Gamiz, A. Lopez-Arraiza, M. A. Gomez-Solaetxe, J. M. Lopez-Guede, J. Sancho, F. J. Basterretxea
Abstract: The aerosolization of perfluorocarbons along with non-invasive respiratory support has showed promising results as an alternative to treat the respiratory distress syndrome (RDS) in preterm infants. The aim of this study was to evaluate the main characteristics of the aerosol generated by an intracorporeal inhalation catheter, where one central lumen deliver the liquid and six peripheral lumens deliver the compressed air. Initially, different experiments were made with sterile water at different driving pressures to analyze properties such as the aerodynamic diameter (Da), mass median aerodynamic diameter (MMAD) and geometric standard deviation (GSD). Subsequently, the perfluorocarbon FC-75 was tested to obtained experimental data to define the boundary conditions and to validate the numerical model. The experimental validation of the numerical model provided an accurate prediction of the air flow axial velocity and suggested that the collision and coalescence of the particles plays a crucial role in the particle size and mass distribution.
Title of the Paper: Physical Principles of the Vacuum Aspiration for Prostatitis Treatment
Authors: Andrei Yu. Kulinich, Irina V. Golovacheva, Mikhail Ye. Zhuravlev
Abstract: Vacuum aspiration is an effective method of prostatitis therapy. Bacterial prostatitis leads to duct obstruction. The plug consists of dense acini epithelium and secretions. Vacuum aspiration procedure results in the destruction of the plug. The fact of the destruction has been verified by the analysis of the substance obtained during the procedure. This method is used in a few medical institutions. Meanwhile, the physical principles of the procedure have never been investigated. We analyze plausible physical mechanisms of purification of prostatic acini and ducts by means of transurethral vacuum aspiration. A mechanical model is offered to describe the process of plug destruction during vacuum aspiration procedure. The majority of medical practitioners believe that the plug is extracted as a whole during such procedure. However, our theoretical research demonstrates that the sucking of a plug as a whole, previously viewed as the most likely mechanism, is not consistent with the experimental data.
Title of the Paper: Integrated Higher-Order Evidence-Based Framework for Prediction of Higher-Order Epistasis Interactions in Alzheimer’s Disease
Authors: Fayroz F. Sherif, Nourhan Zayed, Mahmoud Fakhr, Manal Abdel Wahed, Yasser M. Kadah
Abstract: Alzheimer’s disease (AD) is the most common form of dementia with strong genetic factors in which a combination of genetic variants contributes to AD risk. Discovering epistasis interactions among genetic variants is key to identifying valuable AD predictive models that allow earlier diagnosis and better prognosis for patient. Presently, AD predictive models are derived using either statistical or biological feature selection methods. Unfortunately, both approaches suffer from inherent limitations in their generalization and prediction power. This study presents a new hybrid method between these two approaches based on integrated higher-order evidence-based (IHOEB) framework. This method combines statistical and biological feature selection methods and allow computationally-efficient detection of up to 4-way epistasis models associated with AD. The new processing framework was applied to data obtained from the Alzheimer’s Disease Neuroimaging Initiative database (ADNI). The classification accuracies of IHOEB 4-way models varied between (0.7410-0.7860) whereas the accuracies of statistical and biological 2-way models varied between (0.6450-0.6760) and (0.5300-0.5750) respectively. This new IHOEB framework offers a promising alternative for epistasis interactions in genome wide association studies where it allows identification of AD models that are supported by both statistical and biological analyses efficiently and at higher accuracy.
Title of the Paper: A Discrete Time Population Genetic Model for X-Linked Recessive Diseases
Authors: Carmen Del Vecchio, Francesca Verrilli, Luigi Glielmo, Martin Corless
Abstract: The epidemiology of X-linked recessive diseases, a class of genetic disorders, is modeled with a discretetime, structured, mathematical model. The model accounts for both de novo mutations and different reproduction rates of procreating couples depending on their health conditions. Relying on Lyapunov theory, asymptotic stability properties of equilibrium points of the model are demonstrated. The model describes the spread over time in the population of any recessive genetic disorder transmitted through the Xchromosome.
Title of the Paper: Analysis of Pediatric Foot Disorders Using Decision Tree and Neural Networks
Authors: J. K. Choi, Y. G. Won, J. J. Kim
Abstract: Data mining is method to extract hidden predictive information, and it has been recognized by many studies. The object in the study was to discover meaningful knowledge between the foot disorder and biomechanical parameters related to symptom using C5.0 decision tree and neural networks. The first medical record data of 174 pediatric patients was extracted for analysis, in total 279 records, and they were diagnosed with a complex foot disorder. The dependent variable consists of five complex disorder groups, and 14 independent variables related to disorder groups were selected by importance, in 34 variables. The extracted data was separated to generate an ideal prediction model. After development of the prediction model, the prediction rate was verified and neural networks were applied for analysis of predictor importance and classification prediction. Consequently, a major symptom information in 13 diagnosis patterns was confirmed.