We performed subjective physiological assessment of brain activity using the visually performed n-back task and the n-back task performed by the auditory sense. The visually performed n-back task was done with two tasks that were performed while memorizing presented numbers and the result of computational problems. We characterized and compared the oxygenated hemoglobin concentration change in the brain during the working memory task using near-infrared spectroscopy measurement. Changes in activation of brain activity were observed due to differences in tasks. The difference in the presentation method resulted in a difference in activation of brain activity. Furthermore, the computational n-back task with execution function in working memory induced more brain activity than the usual n-back task. Thus, the computed n-back task is a suitable task to train workers.
{"title":"Using NIRS to Detect Brain oxyHb Changes During Short-Term Memory Tasks","authors":"Takuya Sasabe, H. Hagiwara","doi":"10.1109/BIBE.2018.00067","DOIUrl":"https://doi.org/10.1109/BIBE.2018.00067","url":null,"abstract":"We performed subjective physiological assessment of brain activity using the visually performed n-back task and the n-back task performed by the auditory sense. The visually performed n-back task was done with two tasks that were performed while memorizing presented numbers and the result of computational problems. We characterized and compared the oxygenated hemoglobin concentration change in the brain during the working memory task using near-infrared spectroscopy measurement. Changes in activation of brain activity were observed due to differences in tasks. The difference in the presentation method resulted in a difference in activation of brain activity. Furthermore, the computational n-back task with execution function in working memory induced more brain activity than the usual n-back task. Thus, the computed n-back task is a suitable task to train workers.","PeriodicalId":127507,"journal":{"name":"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117239126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ho Seon Choi, Myounghoon Shim, Chang Hee Lee, Y. Baek
CoP(Center of pressure) and GRF(ground reaction force) of insole are very important values in biomechanics area. They are using for calculating kinematics, dynamics of human or controlling of robot like exoskeletons. As an alternative to high-cost insole pressure sensors that can measure the insole pressure distribution and calculate the center of pressure, a FSR (Force Sensing Resistor) foot sensor with FSR sensors on the bottom of the insole was developed. However, the value of the CoP calculated using fixed coordinates and the values of FSR sensors were not sufficiently accurate and FSR sensors cannot cover the whole area of the insole so it can not calculate the magnitude of GRF. Hence, in this paper, a model capable of estimating of GRF and calibrating CoP measured by FSR foot sensors using neural network fitting is introduced. These processes rely on the fact that foot has protruding areas that are initially in contact with the ground while walking, with the size and magnitude of the pressure exerted by other non-protruding areas estimated using the the constant patterns of the pressure values of the protruding areas. This paper presents the division of the insole based on anatomical shape of foot, estimations of appropriate numvers and locations of the FSR sensors, creation of virtual forces and their floating coordinates, development of algorithms with neural network fitting for estimating the values, and calculation of the estimated GRF and calibrated CoP. Validation is conducted by comparing the Values with those of F-Scan System(Tekscan, Inc.)
{"title":"Estimating GRF(Ground Reaction Force) and Calibrating CoP(Center of Pressure) of an Insole Measured by an Low-Cost Sensor with Neural Network","authors":"Ho Seon Choi, Myounghoon Shim, Chang Hee Lee, Y. Baek","doi":"10.1109/BIBE.2018.00043","DOIUrl":"https://doi.org/10.1109/BIBE.2018.00043","url":null,"abstract":"CoP(Center of pressure) and GRF(ground reaction force) of insole are very important values in biomechanics area. They are using for calculating kinematics, dynamics of human or controlling of robot like exoskeletons. As an alternative to high-cost insole pressure sensors that can measure the insole pressure distribution and calculate the center of pressure, a FSR (Force Sensing Resistor) foot sensor with FSR sensors on the bottom of the insole was developed. However, the value of the CoP calculated using fixed coordinates and the values of FSR sensors were not sufficiently accurate and FSR sensors cannot cover the whole area of the insole so it can not calculate the magnitude of GRF. Hence, in this paper, a model capable of estimating of GRF and calibrating CoP measured by FSR foot sensors using neural network fitting is introduced. These processes rely on the fact that foot has protruding areas that are initially in contact with the ground while walking, with the size and magnitude of the pressure exerted by other non-protruding areas estimated using the the constant patterns of the pressure values of the protruding areas. This paper presents the division of the insole based on anatomical shape of foot, estimations of appropriate numvers and locations of the FSR sensors, creation of virtual forces and their floating coordinates, development of algorithms with neural network fitting for estimating the values, and calculation of the estimated GRF and calibrated CoP. Validation is conducted by comparing the Values with those of F-Scan System(Tekscan, Inc.)","PeriodicalId":127507,"journal":{"name":"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133124490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper aims to construct two relationship trees of all viruses using two types of genomic sequences, DNA("deoxyribonucleic acid") and CDS ("coding sequence"), respectively, via a previously developed approach BBRD (BLAST-Based Relative Distance). The BBRD approach is capable to construct the relationship trees of different genomic sequences without identifying common conserved regions among these sequences for comparison in advance. The experimental resources of viruses, with complete genome sequences, were downloaded from NCBI(National Center for Biotechnology Information) at 2018/3/1, and there are 7,535 viruses with whole DNA sequences and 7,434 viruses with at least one CDS sequences. Experimental results show that the relationship tree constructed via DNA sequences seems to be more consistent with the taxonomy of viruses in ICTV (International Committee on Taxonomy of Viruses) than that constructed via CDS sequences. Furthermore, observing the neighbors of one unknown virus within the relationship trees can provide hints to determine or guess its taxonomic information for the biologist or virologist. This study may inspect the fitness of the structures (skeletons) of one existing taxonomy, e.g. ICTV, by observing the relationship tree and providing the parts of subtree without consistence.
本文旨在利用DNA(“脱氧核糖核酸”)和CDS(“编码序列”)这两种类型的基因组序列，通过先前开发的基于blast的相对距离(BBRD)方法，分别构建所有病毒的两个关系树。BBRD方法能够构建不同基因组序列的关系树，而无需事先确定这些序列之间的共同保守区域进行比较。2018年3月1日，从NCBI(National Center for Biotechnology Information)下载病毒全基因组序列实验资源，拥有完整DNA序列的病毒有7535种，拥有至少一个CDS序列的病毒有7434种。实验结果表明，通过DNA序列构建的关系树似乎比通过CDS序列构建的关系树更符合ICTV (International Committee on taxonomy of viruses)的病毒分类。此外，观察一个未知病毒在关系树中的邻居可以为生物学家或病毒学家提供确定或猜测其分类信息的提示。本研究可能通过观察关系树和提供子树中不一致的部分来检验现有分类(如ICTV)的结构(骨架)的适应度。
{"title":"Constructing the Relationship Tree of All Viruses via Whole Genomic Sequences","authors":"Jing-doo Wang, Yi-Chun Wang","doi":"10.1109/BIBE.2018.00010","DOIUrl":"https://doi.org/10.1109/BIBE.2018.00010","url":null,"abstract":"This paper aims to construct two relationship trees of all viruses using two types of genomic sequences, DNA(\"deoxyribonucleic acid\") and CDS (\"coding sequence\"), respectively, via a previously developed approach BBRD (BLAST-Based Relative Distance). The BBRD approach is capable to construct the relationship trees of different genomic sequences without identifying common conserved regions among these sequences for comparison in advance. The experimental resources of viruses, with complete genome sequences, were downloaded from NCBI(National Center for Biotechnology Information) at 2018/3/1, and there are 7,535 viruses with whole DNA sequences and 7,434 viruses with at least one CDS sequences. Experimental results show that the relationship tree constructed via DNA sequences seems to be more consistent with the taxonomy of viruses in ICTV (International Committee on Taxonomy of Viruses) than that constructed via CDS sequences. Furthermore, observing the neighbors of one unknown virus within the relationship trees can provide hints to determine or guess its taxonomic information for the biologist or virologist. This study may inspect the fitness of the structures (skeletons) of one existing taxonomy, e.g. ICTV, by observing the relationship tree and providing the parts of subtree without consistence.","PeriodicalId":127507,"journal":{"name":"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123687935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Enkhbat Batbayar, E. Tumenjargal, Chulgyu Song, W. Ham
Photoacoustic tomography is a quickly growing imaging method that can provide images of high spatial resolution and high contrast at a limited depths. Medical photoacoustic processing characteristics two main components: A transducer is required to transmit laser pulses and acquire the reflected ultrasound signals and a back-end processing system that will generate the final reconstructed image. In this paper, we introduce an implementation of the receive part of proposed embedded system and briefly discuss reconstruction algorithms which are used in medical imaging systems. Furthermore, an intellectual property core (IP-core), which can be controlled and configured by a user application on Zynq-7000 System-On-Chip (SoC) via AXI-Lite Interface, that can receive multichannel digitized raw signals from Analog-Front-End (AFE) device via Low Voltage Differential Signal (LVDS), is proposed for photoacoustic imaging systems. Besides, block diagram of the system, the hardware design flow and the proposed IP-core are fully described in this paper. In order to effortlessly test and evaluate a wide variety of ultrasonic signal processing applications, 16 channel system is implemented and demonstrated by using TI AFE5816 Evaluation module (EVM) based on AFE5816 device and Xilinx ZC702 Evaluation Kit based on Zynq-7000 SoC. Apart from working on hardware, we review and commented on the proposed 3-Dimensional photoacoustic image reconstruction algorithm.
{"title":"[Regular Paper] Implementation of an Ultrasound Platform for Proposed Photoacoustic Image Reconstruction Algorithm","authors":"Enkhbat Batbayar, E. Tumenjargal, Chulgyu Song, W. Ham","doi":"10.1109/BIBE.2018.00064","DOIUrl":"https://doi.org/10.1109/BIBE.2018.00064","url":null,"abstract":"Photoacoustic tomography is a quickly growing imaging method that can provide images of high spatial resolution and high contrast at a limited depths. Medical photoacoustic processing characteristics two main components: A transducer is required to transmit laser pulses and acquire the reflected ultrasound signals and a back-end processing system that will generate the final reconstructed image. In this paper, we introduce an implementation of the receive part of proposed embedded system and briefly discuss reconstruction algorithms which are used in medical imaging systems. Furthermore, an intellectual property core (IP-core), which can be controlled and configured by a user application on Zynq-7000 System-On-Chip (SoC) via AXI-Lite Interface, that can receive multichannel digitized raw signals from Analog-Front-End (AFE) device via Low Voltage Differential Signal (LVDS), is proposed for photoacoustic imaging systems. Besides, block diagram of the system, the hardware design flow and the proposed IP-core are fully described in this paper. In order to effortlessly test and evaluate a wide variety of ultrasonic signal processing applications, 16 channel system is implemented and demonstrated by using TI AFE5816 Evaluation module (EVM) based on AFE5816 device and Xilinx ZC702 Evaluation Kit based on Zynq-7000 SoC. Apart from working on hardware, we review and commented on the proposed 3-Dimensional photoacoustic image reconstruction algorithm.","PeriodicalId":127507,"journal":{"name":"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116186019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Epistasis detection facilitates determining susceptibility to disease. Multifactor dimensionality reduction (MDR) and multiobjective MDR (MOMDR) were proposed for epistasis detection. However, more measures must be investigated for MOMDR. In this study, we incorporated the Youden index (YI) and correct classification rate (CCR) into MOMDR (MOMDR-YC) for epistasis detection. Simulations were conducted to compare MDR-based YI (MDR-Y), MDR-based CCR (MDR-C), and MOMDR-YC. Moreover, the detection success rates of the three approaches are presented. MOMDR-YC revealed that the YI and CCR measures can enhance the detection success rates of MDR. The simulation results revealed that epistasis could be successfully detected by incorporating YI and CCR into MOMDR.
{"title":"Improved Multifactor Dimensionality Reduction for Epistasis Detection","authors":"Li-Yeh Chuang, Cheng-Hong Yang, Yu-Da Lin","doi":"10.1109/BIBE.2018.00057","DOIUrl":"https://doi.org/10.1109/BIBE.2018.00057","url":null,"abstract":"Epistasis detection facilitates determining susceptibility to disease. Multifactor dimensionality reduction (MDR) and multiobjective MDR (MOMDR) were proposed for epistasis detection. However, more measures must be investigated for MOMDR. In this study, we incorporated the Youden index (YI) and correct classification rate (CCR) into MOMDR (MOMDR-YC) for epistasis detection. Simulations were conducted to compare MDR-based YI (MDR-Y), MDR-based CCR (MDR-C), and MOMDR-YC. Moreover, the detection success rates of the three approaches are presented. MOMDR-YC revealed that the YI and CCR measures can enhance the detection success rates of MDR. The simulation results revealed that epistasis could be successfully detected by incorporating YI and CCR into MOMDR.","PeriodicalId":127507,"journal":{"name":"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117142665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sharing principles of drug-drug interaction, herb-drug interaction (HDI) investigates the impacts of herb-based products on activities of other conventional drugs when combining them in certain medical treatments. For years, patients using herb-based medications have built a misconception about the absolute safety of products derived from natural sources. The current fact revealed that patients had intentionally combined herb-based products and prescription drugs for any certain illnesses without safety concerns to enhance the efficiencies. Incapability of non-experts in reviewing the biomedical literature of potential HDIs may be considered as one of the most reasonable explanations for this issue. In this study, text mining techniques are applied to provide users with a novel approach to save time when looking for information of HDIs. Since constructing an annotated corpus for herb-based products in traditional manner requires a high demand for human resources and financial support, an unsupervised learning model for relation extraction which eliminates to the crucial role of an annotated training set is quite suitable. The relations connecting the entity pairs were discovered and labeled by their most significant features. The obtained result proposes a promising method for the HDIs extraction challenge.
{"title":"Semantic Relation Extraction for Herb-Drug Interactions from the Biomedical Literature Using an Unsupervised Learning Approach","authors":"Khang H Trinh, Duy Pham, Ly Le","doi":"10.1109/BIBE.2018.00072","DOIUrl":"https://doi.org/10.1109/BIBE.2018.00072","url":null,"abstract":"Sharing principles of drug-drug interaction, herb-drug interaction (HDI) investigates the impacts of herb-based products on activities of other conventional drugs when combining them in certain medical treatments. For years, patients using herb-based medications have built a misconception about the absolute safety of products derived from natural sources. The current fact revealed that patients had intentionally combined herb-based products and prescription drugs for any certain illnesses without safety concerns to enhance the efficiencies. Incapability of non-experts in reviewing the biomedical literature of potential HDIs may be considered as one of the most reasonable explanations for this issue. In this study, text mining techniques are applied to provide users with a novel approach to save time when looking for information of HDIs. Since constructing an annotated corpus for herb-based products in traditional manner requires a high demand for human resources and financial support, an unsupervised learning model for relation extraction which eliminates to the crucial role of an annotated training set is quite suitable. The relations connecting the entity pairs were discovered and labeled by their most significant features. The obtained result proposes a promising method for the HDIs extraction challenge.","PeriodicalId":127507,"journal":{"name":"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127231747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emma D. Wilson, Q. Clairon, R. Henderson, C. J. Taylor
A control theory approach to the management of the blood clotting speed using the anticoagulant Warfarin is investigated. Controllers are developed and analysed using hospital data from patients with chronic conditions under Warfarin anticoagulation treatment. Proportional Integral (PI) and Model Predictive (MPC) controllers are used to estimate treatment decisions. These controllers are adapted in a novel manner, to enable their use with missing or irregularly sampled data. The performance of the controllers is evaluated both using a simulation of the system and by retrospectively comparing actual decisions in the data to those suggested by the control algorithms. It is shown that when the blood clotting speed is within a target range, the decisions suggested by the control algorithms are similar to those actually made (by medical staff), so would likely have led to similar desirable outcomes. When the blood clotting speed is outside the desirable range and too high or too low, the control algorithms on average suggest lower, or higher inputs respectively. These suggestions are likely to lead to improved outcomes.
{"title":"[Regular Paper] Model Predictive and Proportional Integral Control of Blood Clotting Speed Using Warfarin when Data are Missing","authors":"Emma D. Wilson, Q. Clairon, R. Henderson, C. J. Taylor","doi":"10.1109/BIBE.2018.00013","DOIUrl":"https://doi.org/10.1109/BIBE.2018.00013","url":null,"abstract":"A control theory approach to the management of the blood clotting speed using the anticoagulant Warfarin is investigated. Controllers are developed and analysed using hospital data from patients with chronic conditions under Warfarin anticoagulation treatment. Proportional Integral (PI) and Model Predictive (MPC) controllers are used to estimate treatment decisions. These controllers are adapted in a novel manner, to enable their use with missing or irregularly sampled data. The performance of the controllers is evaluated both using a simulation of the system and by retrospectively comparing actual decisions in the data to those suggested by the control algorithms. It is shown that when the blood clotting speed is within a target range, the decisions suggested by the control algorithms are similar to those actually made (by medical staff), so would likely have led to similar desirable outcomes. When the blood clotting speed is outside the desirable range and too high or too low, the control algorithms on average suggest lower, or higher inputs respectively. These suggestions are likely to lead to improved outcomes.","PeriodicalId":127507,"journal":{"name":"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124171015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maryam Butt, G. Naghdy, F. Naghdy, Geoffrey Murray, H. Du
Detection of motor intention from brain signals combined with robot assistive technologies has potential to be used as an effective rehabilitation process for post-stroke patients. The work conducted on the deployment of AMADEO hand rehabilitation robotic device and Electroencephalogram based Brain Computer Interference (EEG-BCI) system to explore the technical feasibility of the approach in hand motor recovery of post-stroke patients is presented. Two different protocols consisting of simple visual cues and a 2D interactive game are presented to healthy subjects when performing hand movement. The motor intent signals produced during each protocol are detected using Support Vector Machine (SVM) algorithm. Moreover, the signals produced by different single electrodes are analyzed to identify the electrode making the highest contribution to the intent signal and the performance of SVM with respect to each protocol. Overall, an average True Positive Rate (TPR) of 71.72% and True Negative Rate (TNR) of 63.33% for visual cue protocol and an average TPR of 88.56% and TNR of 70.81% for game protocol are obtained.
{"title":"Investigating Electrode Sites for Intention Detection During Robot Based Hand Movement Using EEG-BCI System","authors":"Maryam Butt, G. Naghdy, F. Naghdy, Geoffrey Murray, H. Du","doi":"10.1109/BIBE.2018.00041","DOIUrl":"https://doi.org/10.1109/BIBE.2018.00041","url":null,"abstract":"Detection of motor intention from brain signals combined with robot assistive technologies has potential to be used as an effective rehabilitation process for post-stroke patients. The work conducted on the deployment of AMADEO hand rehabilitation robotic device and Electroencephalogram based Brain Computer Interference (EEG-BCI) system to explore the technical feasibility of the approach in hand motor recovery of post-stroke patients is presented. Two different protocols consisting of simple visual cues and a 2D interactive game are presented to healthy subjects when performing hand movement. The motor intent signals produced during each protocol are detected using Support Vector Machine (SVM) algorithm. Moreover, the signals produced by different single electrodes are analyzed to identify the electrode making the highest contribution to the intent signal and the performance of SVM with respect to each protocol. Overall, an average True Positive Rate (TPR) of 71.72% and True Negative Rate (TNR) of 63.33% for visual cue protocol and an average TPR of 88.56% and TNR of 70.81% for game protocol are obtained.","PeriodicalId":127507,"journal":{"name":"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131841891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Traumatic brain injury (TBI) is one of the most life-threatening injuries and a leading cause of the majority of disability and death across the world. Majority of the damages to the tissues are initiated by tensile and shearing structural failures. We report a three-dimensional finite element model of the human head where different parts are represented by appropriate material models. Simulations are performed for the case of dynamic loading on five locations of the head namely, frontal, frontal-top, parietal, occipital, and temporal. The developed model is validated with experimental literature. The distribution of intracranial pressure and von Mises stress is studied in detail. We observe that parietal bone is the strongest, and frontal-top concussions as more likely to result in loss of consciousness. In addition, the occipital impact represents the higher probability of neurological damage.
{"title":"[Regular Paper] Computational Modeling of Traumatic Brain Injury Due to Impact on Different Sides of Human Head","authors":"Tanu Khanuja, H. N. Unni","doi":"10.1109/BIBE.2018.00079","DOIUrl":"https://doi.org/10.1109/BIBE.2018.00079","url":null,"abstract":"Traumatic brain injury (TBI) is one of the most life-threatening injuries and a leading cause of the majority of disability and death across the world. Majority of the damages to the tissues are initiated by tensile and shearing structural failures. We report a three-dimensional finite element model of the human head where different parts are represented by appropriate material models. Simulations are performed for the case of dynamic loading on five locations of the head namely, frontal, frontal-top, parietal, occipital, and temporal. The developed model is validated with experimental literature. The distribution of intracranial pressure and von Mises stress is studied in detail. We observe that parietal bone is the strongest, and frontal-top concussions as more likely to result in loss of consciousness. In addition, the occipital impact represents the higher probability of neurological damage.","PeriodicalId":127507,"journal":{"name":"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117178330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Prostate cancer (PCa) is the second-leading cause of cancer death among men in the worldwide. Most PCa is slowly growing and usually early symptomless. About 70% of PCa patients were diagnosed at later stage and metastasis has been observed. Additionally, the cure rate of PCa closely relies on the early diagnosis with biomarkers. Prostatic Specific Antigen (PSA) is currently the only clinical biomarker for PCa diagnosis. However, the PSA test has inherent limitations and has about 75% of false-positive results. The identification of a set of genes (as biomarkers) for diagnosis and prognosis is an urgent clinical issue for PCa. Here, we integrated genome-wide analysis and protein-protein interaction network to identify potential genes for early diagnostic biomarkers of PCa. First, we collected gene expression datasets of 145 PCa samples, consisting of both tumor and corresponding normal tissues, from two different sources in Gene Expression Omnibus (GEO). We found 158 and 268 significantly highly and lowly expressed genes, respectively, in tumor samples. Moreover, we proposed cluster score (CS) and predicting score (PS) to select 28 prostate cancer-related genes (called PCa28). The results indicate that PCa28 can discriminate between the normal/tumor tissues and are specific for prostate cancer. Finally, we examined 8 genes in PCa28 on four PCa cell lines by real time quantitative polymerase chain reaction (RT-qPCR). Experimental results show that up-regulated genes have higher expression level in tumor cells in comparison to normal cells, and down-regulated genes have lower expression level in tumor cells. We believe that our method is useful and PCa28 are potential biomarkers that provide the clues to develop targeting therapy for PCa.
前列腺癌(PCa)是全球男性癌症死亡的第二大原因。大多数前列腺癌生长缓慢，通常早期无症状。大约70%的前列腺癌患者在晚期才被诊断出来，并观察到转移。此外，前列腺癌的治愈率密切依赖于生物标志物的早期诊断。前列腺特异性抗原(PSA)是目前诊断前列腺癌唯一的临床生物标志物。然而，PSA检测有其固有的局限性，约有75%的假阳性结果。鉴别一组用于前列腺癌诊断和预后的基因(作为生物标志物)是一个迫切的临床问题。在这里，我们整合了全基因组分析和蛋白-蛋白相互作用网络，以确定前列腺癌早期诊断生物标志物的潜在基因。首先，我们在gene expression Omnibus (GEO)中收集了来自两个不同来源的145个PCa样本的基因表达数据集，包括肿瘤和相应的正常组织。我们在肿瘤样本中分别发现了158和268个显著高表达和低表达的基因。此外，我们提出了聚类评分(CS)和预测评分(PS)来选择28个前列腺癌相关基因(称为PCa28)。结果表明，PCa28可以区分正常组织和肿瘤组织，并且对前列腺癌具有特异性。最后，我们利用实时定量聚合酶链反应(RT-qPCR)检测了4种PCa细胞系中PCa28的8个基因。实验结果表明，与正常细胞相比，上调基因在肿瘤细胞中的表达水平较高，下调基因在肿瘤细胞中的表达水平较低。我们相信我们的方法是有用的，PCa28是潜在的生物标志物，为开发针对PCa的靶向治疗提供线索。
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