Search results for: neural stem/precursor cells
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5688

Search results for: neural stem/precursor cells

5088 Non-linear Analysis of Spontaneous EEG After Spinal Cord Injury: An Experimental Study

Authors: Jiangbo Pu, Hanhui Xu, Yazhou Wang, Hongyan Cui, Yong Hu

Abstract:

Spinal cord injury (SCI) brings great negative influence to the patients and society. Neurological loss in human after SCI is a major challenge in clinical. Instead, neural regeneration could have been seen in animals after SCI, and such regeneration could be retarded by blocking neural plasticity pathways, showing the importance of neural plasticity in functional recovery. Here we used sample entropy as an indicator of nonlinear dynamical in the brain to quantify plasticity changes in spontaneous EEG recordings of rats before and after SCI. The results showed that the entropy values were increased after the injury during the recovery in one week. The increasing tendency of sample entropy values is consistent with that of behavioral evaluation scores. It is indicated the potential application of sample entropy analysis for the evaluation of neural plasticity in spinal cord injury rat model.

Keywords: spinal cord injury (SCI), sample entropy, nonlinear, complex system, firing pattern, EEG, spontaneous activity, Basso Beattie Bresnahan (BBB) score

Procedia PDF Downloads 465
5087 Alleviation of Endoplasmic Reticulum Stress in Mosquito Cells to Survive Dengue 2 Virus Infection

Authors: Jiun-Nan Hou, Tien-Huang Chen, Wei-June Chen

Abstract:

Dengue viruses (DENVs) are naturally transmitted between humans by mosquito vectors. Mosquito cells usually survive DENV infection, allowing infected mosquitoes to retain an active status for virus transmission. In this study, we found that DENV2 virus infection in mosquito cells causes the unfolded protein response (UPR) that activates the protein kinase RNA-like endoplasmic reticulum kinase (PERK) signal pathway, leading to shutdown of global protein translation in infected cells which was apparently regulated by the PERK signal pathway. According to observation in this study, the PERK signal pathway in DENV2-infected C6/36 cells alleviates ER stress, and reduces initiator and effector caspases, as well as the apoptosis rate via shutdown of cellular proteins. In fact, phosphorylation of eukaryotic initiation factor 2ɑ (eIF2ɑ) by the PERK signal pathway may impair recruitment of ribosomes that bind to the mRNA 5’-cap structure, resulting in an inhibitory effect on canonical cap-dependent cellular protein translation. The resultant pro-survival “byproduct” of infected mosquito cells is undoubtedly advantageous for viral replication. This finding provides insights into elucidating the PERK-mediated modulating web that is actively involved in dynamic protein synthesis, cell survival, and viral replication in mosquito cells.

Keywords: cap-dependent protein translation, dengue virus, endoplasmic reticulum stress, mosquito cells, PERK signal pathway

Procedia PDF Downloads 267
5086 Message Passing Neural Network (MPNN) Approach to Multiphase Diffusion in Reservoirs for Well Interconnection Assessments

Authors: Margarita Mayoral-Villa, J. Klapp, L. Di G. Sigalotti, J. E. V. Guzmán

Abstract:

Automated learning techniques are widely applied in the energy sector to address challenging problems from a practical point of view. To this end, we discuss the implementation of a Message Passing algorithm (MPNN)within a Graph Neural Network(GNN)to leverage the neighborhood of a set of nodes during the aggregation process. This approach enables the characterization of multiphase diffusion processes in the reservoir, such that the flow paths underlying the interconnections between multiple wells may be inferred from previously available data on flow rates and bottomhole pressures. The results thus obtained compare favorably with the predictions produced by the Reduced Order Capacitance-Resistance Models (CRM) and suggest the potential of MPNNs to enhance the robustness of the forecasts while improving the computational efficiency.

Keywords: multiphase diffusion, message passing neural network, well interconnection, interwell connectivity, graph neural network, capacitance-resistance models

Procedia PDF Downloads 149
5085 Study of Temperature Difference and Current Distribution in Parallel-Connected Cells at Low Temperature

Authors: Sara Kamalisiahroudi, Jun Huang, Zhe Li, Jianbo Zhang

Abstract:

Two types of commercial cylindrical lithium ion batteries (Panasonic 3.4 Ah NCR-18650B and Samsung 2.9 Ah INR-18650), were investigated experimentally. The capacities of these samples were individually measured using constant current-constant voltage (CC-CV) method at different ambient temperatures (-10 ℃, 0 ℃, 25 ℃). Their internal resistance was determined by electrochemical impedance spectroscopy (EIS) and pulse discharge methods. The cells with different configurations of parallel connection NCR-NCR, INR-INR and NCR-INR were charged/discharged at the aforementioned ambient temperatures. The results showed that the difference of internal resistance between cells much more evident at low temperatures. Furthermore, the parallel connection of NCR-NCR exhibits the most uniform temperature distribution in cells at -10 ℃, this feature is quite favorable for the safety of the battery pack.

Keywords: batteries in parallel connection, internal resistance, low temperature, temperature difference, current distribution

Procedia PDF Downloads 478
5084 Detection of Keypoint in Press-Fit Curve Based on Convolutional Neural Network

Authors: Shoujia Fang, Guoqing Ding, Xin Chen

Abstract:

The quality of press-fit assembly is closely related to reliability and safety of product. The paper proposed a keypoint detection method based on convolutional neural network to improve the accuracy of keypoint detection in press-fit curve. It would provide an auxiliary basis for judging quality of press-fit assembly. The press-fit curve is a curve of press-fit force and displacement. Both force data and distance data are time-series data. Therefore, one-dimensional convolutional neural network is used to process the press-fit curve. After the obtained press-fit data is filtered, the multi-layer one-dimensional convolutional neural network is used to perform the automatic learning of press-fit curve features, and then sent to the multi-layer perceptron to finally output keypoint of the curve. We used the data of press-fit assembly equipment in the actual production process to train CNN model, and we used different data from the same equipment to evaluate the performance of detection. Compared with the existing research result, the performance of detection was significantly improved. This method can provide a reliable basis for the judgment of press-fit quality.

Keywords: keypoint detection, curve feature, convolutional neural network, press-fit assembly

Procedia PDF Downloads 228
5083 Synthesis of Low-Cost Porous Silicon Carbide Foams from Renewable Sources

Authors: M. A. Bayona, E. M. Cordoba, V. R. Guiza

Abstract:

Highly porous carbon-based foams are used in a wide range of industrial applications, which include absorption, catalyst supports, thermal insulation, and biomaterials, among others. Particularly, silicon carbide (SiC) based foams have shown exceptional potential for catalyst support applications, due to their chemical inertness, large frontal area, low resistance to flow, low-pressure drop, as well as high resistance to temperature and corrosion. These properties allow the use of SiC foams in harsh environments with high durability. Commonly, SiC foams are fabricated from polysiloxane, SiC powders and phenolic resins, which can be costly or highly toxic to the environment. In this work, we propose a low-cost method for the fabrication of highly porous, three-dimensional SiC foams via template replica, using recycled polymeric sponges as sacrificial templates. A sucrose-based resin combined with a Si-containing pre-ceramic polymer was used as the precursor. Polymeric templates were impregnated with the precursor solution, followed by thermal treatment at 1500 °C under an inert atmosphere. Several synthesis parameters, such as viscosity and composition of the precursor solution (Si: Sucrose molar ratio), and the porosity of the template, were evaluated in terms of their effect on the morphology, composition and mechanical resistance of the resulting SiC foams. The synthesized composite foams exhibited a highly porous (50-90%) and interconnected structure, containing 30-90% SiC with a mechanical compressive strength between 0.01-0.1 MPa. The methodology employed here allowed the fabrication of foams with a varied concentration of SiC and with morphological and mechanical properties that contribute to the development of materials of high relevance in the industry, while using low-cost, renewable sources such as table sugar, and providing a recycling alternative for polymeric sponges.

Keywords: catalyst support, polymer replica technique, reticulated porous ceramics, silicon carbide

Procedia PDF Downloads 123
5082 Taxonomic Classification for Living Organisms Using Convolutional Neural Networks

Authors: Saed Khawaldeh, Mohamed Elsharnouby, Alaa Eddin Alchalabi, Usama Pervaiz, Tajwar Aleef, Vu Hoang Minh

Abstract:

Taxonomic classification has a wide-range of applications such as finding out more about the evolutionary history of organisms that can be done by making a comparison between species living now and species that lived in the past. This comparison can be made using different kinds of extracted species’ data which include DNA sequences. Compared to the estimated number of the organisms that nature harbours, humanity does not have a thorough comprehension of which specific species they all belong to, in spite of the significant development of science and scientific knowledge over many years. One of the methods that can be applied to extract information out of the study of organisms in this regard is to use the DNA sequence of a living organism as a marker, thus making it available to classify it into a taxonomy. The classification of living organisms can be done in many machine learning techniques including Neural Networks (NNs). In this study, DNA sequences classification is performed using Convolutional Neural Networks (CNNs) which is a special type of NNs.

Keywords: deep networks, convolutional neural networks, taxonomic classification, DNA sequences classification

Procedia PDF Downloads 442
5081 Platform Development for Vero Cell Culture on Microcarriers Using Dissociation-Reassociation Method

Authors: Thanunthon Bowornsakulwong, Charukorn Charukarn, Franck Courtes, Panit Kitsubun, Lalintip Horcharoen

Abstract:

Vero cell is a continuous cell line that is widely used for the production of viral vaccines. However, due to its adherent characteristic, scaling up strategy in large-scale production remains complicated and thus limited. Consequently, suspension-like Vero cell culture processes based on microcarriers have been introduced and employed while also providing increased surface area per volume unit. However, harvesting Vero cells from microcarriers is a huge challenge due to difficulties in cells detaching, lower recovery yield, time-consuming and dissociation agent carry-over. To overcome these problems, we developed a dissociation-association platform technology for detaching and re-attaching cells during subculturing from microcarriers to microcarriers, which will be conveniently applied to seed trains strategies in large scale bioreactors. Herein, Hillex-2 was used to culture Vero cells in serum-containing media using spinner flasks as a scale-down model. The overall confluency of cells on microcarriers was observed using inverted microscope, and the sample cells were daily detached in order to obtain the kinetics data. The metabolites consumption and by-products formation were determined by Nova Biomedical BioprofileFlex.

Keywords: dissociation-reassociation, microcarrier, scale up, Vero cell

Procedia PDF Downloads 133
5080 Age Related Changes in the Neural Substrates of Emotion Regulation: Mechanisms, Consequences, and Interventions

Authors: Yasaman Mohammadi

Abstract:

Emotion regulation is a complex process that allows individuals to manage and modulate their emotional responses in order to adaptively respond to environmental demands. As individuals age, emotion regulation abilities may decline, leading to an increased vulnerability to mood disorders and other negative health outcomes. Advances in neuroimaging techniques have greatly enhanced our understanding of the neural substrates underlying emotion regulation and age-related changes in these neural systems. Additionally, genetic research has identified several candidate genes that may influence age-related changes in emotion regulation. In this paper, we review recent findings from neuroimaging and genetic research on age-related changes in the neural substrates of emotion regulation, highlighting the mechanisms and consequences of these changes. We also discuss potential interventions, including cognitive and behavioral approaches, that may be effective in mitigating age-related declines in emotion regulation. We propose that a better understanding of the mechanisms underlying age-related changes in emotion regulation may lead to the development of more targeted interventions aimed at promoting healthy emotional functioning in older adults. Overall, this paper highlights the importance of studying age-related changes in emotion regulation and provides a roadmap for future research in this field.

Keywords: emotion regulation, aging, neural substrates, neuroimaging, emotional functioning, healthy aging

Procedia PDF Downloads 112
5079 Intelligent Prediction System for Diagnosis of Heart Attack

Authors: Oluwaponmile David Alao

Abstract:

Due to an increase in the death rate as a result of heart attack. There is need to develop a system that can be useful in the diagnosis of the disease at the medical centre. This system will help in preventing misdiagnosis that may occur from the medical practitioner or the physicians. In this research work, heart disease dataset obtained from UCI repository has been used to develop an intelligent prediction diagnosis system. The system is modeled on a feedforwad neural network and trained with back propagation neural network. A recognition rate of 86% is obtained from the testing of the network.

Keywords: heart disease, artificial neural network, diagnosis, prediction system

Procedia PDF Downloads 450
5078 Analysis of iPSC-Derived Dopaminergic Neuron Susceptibility to Influenza and Excitotoxicity in Non-Affective Psychosis

Authors: Jamileh Ahmed, Helena Hernandez, Gabriel De Erausquin

Abstract:

H1N1 virus susceptibility of iPSC-derived DA neurons from schizophrenia patients and controls will compared. C57/BL-6 fibroblasts were reprogrammed into iPSCs using a lenti-viral vector containing SOKM genes. Pluripotency verification with the AP assay and immunocytochemistry ensured iPSC presence. The experimental outcome of ISPCs from DA neuron differentiation will be discussed in the Results section. Fibroblasts from patients and controls will be reprogrammed into iPSCs using a sendai-virus vector containing SOKM. IPSCs will be characterized using the AP assay, immunocytochemistry and RT-PCR. IPSCs will then be differentiated into DA neurons. Gene methylation will be compared for both groups with custom-designed microarrays.

Keywords: schizophrenia, iPSCs, stem cells, neuroscience

Procedia PDF Downloads 429
5077 Automatic Detection of Proliferative Cells in Immunohistochemically Images of Meningioma Using Fuzzy C-Means Clustering and HSV Color Space

Authors: Vahid Anari, Mina Bakhshi

Abstract:

Visual search and identification of immunohistochemically stained tissue of meningioma was performed manually in pathologic laboratories to detect and diagnose the cancers type of meningioma. This task is very tedious and time-consuming. Moreover, because of cell's complex nature, it still remains a challenging task to segment cells from its background and analyze them automatically. In this paper, we develop and test a computerized scheme that can automatically identify cells in microscopic images of meningioma and classify them into positive (proliferative) and negative (normal) cells. Dataset including 150 images are used to test the scheme. The scheme uses Fuzzy C-means algorithm as a color clustering method based on perceptually uniform hue, saturation, value (HSV) color space. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: positive cell, color segmentation, HSV color space, immunohistochemistry, meningioma, thresholding, fuzzy c-means

Procedia PDF Downloads 210
5076 Efficient Delivery of Biomaterials into Living Organism by Using Noble Metal Nanowire Injector

Authors: Kkochorong Park, Keun Cheon Kim, Hyoban Lee, Eun Ju Lee, Bongsoo Kim

Abstract:

Introduction of biomaterials such as DNA, RNA, proteins is important for many research areas. There are many methods to introduce biomaterials into living organisms like tissue and cells. To introduce biomaterials, several indirect methods including virus‐mediated delivery, chemical reagent (i.e., lipofectamine), electrophoresis have been used. Such methods are passive delivery using an endocytosis process of cell, reducing an efficiency of delivery. Unlike the indirect delivery method, it has been reported that a direct delivery of exogenous biomolecules into nucleus have been more efficient to expression or integration of biomolecules. Nano-sized material is beneficial for detect signal from cell or deliver stimuli/materials into the cell at cellular and molecular levels, due to its similar physical scale. Especially, because 1 dimensional (1D) nanomaterials such as nanotube, nanorod and nanowire with high‐aspect ratio have nanoscale geometry and excellent mechanical, electrical, and chemical properties, they could play an important role in molecular and cellular biology. In this study, by using single crystalline 1D noble metal nanowire, we fabricated nano-sized 1D injector which can successfully interface with living cells and directly deliver biomolecules into several types of cell line (i.e., stem cell, mammalian embryo) without inducing detrimental damages on living cell. This nano-bio technology could be a promising and robust tool for introducing exogenous biomaterials into living organism.

Keywords: DNA, gene delivery, nanoinjector, nanowire

Procedia PDF Downloads 275
5075 Sirt1 Promotes C2C12 Myoblast Cell Proliferation by Myostatin Signaling Pathway

Authors: Cuili Yang, Chengcao Sun, Ruilin Xue, Yongyong Xi, Liang Wang, Dejia Li

Abstract:

Backgrounds: Previous studies showed that Sirt1 plays an important role in C2C12 myoblast cell proliferation, but the mechanism(s) involved in this process remains unclear. This work was undertaken to determine if Myostatin participates in the regulation of C2C12 proliferation by Sirt1. Methods: We administrated the Sirt1 activator resveratrol, inhibitor Nicotinamide (NAM) and Myostatin inhibitor SB431542 on C2C12 myoblast cells. Cell viability was evaluated by CCK8 assay. The expression of Sirt1 and MyoD were detected by qRT-PCR. Utilizing western blot to determinate the expression of myostatin, P107 and p-P107. Results: Our results showed that resveratrol promoted the proliferation of C2C12 myoblast cells, while NAM suppressed the proliferation of C2C12 myoblast cells; SB431542 promoted the proliferation of C2C12 myoblast cells and attenuated the inhibition effect of NAM on C2C12 myoblast cells proliferation; Resveratrol can significantly increase the expression of Sirt1 and MyoD, decrease the expression of Myostatin, while NAM can significantly down-regulate the expression of Sirt1, MyoD and the phosphorylation of P107(p-P107), but up-regulate the expression of Myostatin and the protein P107; SB431542 can significantly mitigate the effect of NAM on the expression of MyoD, P107, and p-P107. Conclusions: Taken together, these results indicate that Sirt1 promotes the proliferation of C2C12 myoblast cells via Myostatin signaling pathway.

Keywords: Sirt1, C2C12 cells, proliferation, myostatin signaling pathway

Procedia PDF Downloads 450
5074 A Three-Dimensional TLM Simulation Method for Thermal Effect in PV-Solar Cells

Authors: R. Hocine, A. Boudjemai, A. Amrani, K. Belkacemi

Abstract:

Temperature rising is a negative factor in almost all systems. It could cause by self heating or ambient temperature. In solar photovoltaic cells this temperature rising affects on the behavior of cells. The ability of a PV module to withstand the effects of periodic hot-spot heating that occurs when cells are operated under reverse biased conditions is closely related to the properties of the cell semi-conductor material. In addition, the thermal effect also influences the estimation of the maximum power point (MPP) and electrical parameters for the PV modules, such as maximum output power, maximum conversion efficiency, internal efficiency, reliability, and lifetime. The cells junction temperature is a critical parameter that significantly affects the electrical characteristics of PV modules. For practical applications of PV modules, it is very important to accurately estimate the junction temperature of PV modules and analyze the thermal characteristics of the PV modules. Once the temperature variation is taken into account, we can then acquire a more accurate MPP for the PV modules, and the maximum utilization efficiency of the PV modules can also be further achieved. In this paper, the three-Dimensional Transmission Line Matrix (3D-TLM) method was used to map the surface temperature distribution of solar cells while in the reverse bias mode. It was observed that some cells exhibited an inhomogeneity of the surface temperature resulting in localized heating (hot-spot). This hot-spot heating causes irreversible destruction of the solar cell structure. Hot spots can have a deleterious impact on the total solar modules if individual solar cells are heated. So, the results show clearly that the solar cells are capable of self-generating considerable amounts of heat that should be dissipated very quickly to increase PV module's lifetime.

Keywords: thermal effect, conduction, heat dissipation, thermal conductivity, solar cell, PV module, nodes, 3D-TLM

Procedia PDF Downloads 387
5073 Entrepreneurship in Pakistan: Opportunities and Challenges

Authors: Bushra Jamil, Nudrat Baqri, Muhammad Hassan Saeed

Abstract:

Entrepreneurship is creating or setting up a business not only for the purpose of generating profit but also for providing job opportunities. Entrepreneurs are problem solvers and product developers. They use their financial asset for hiring a professional team and combine the innovation, knowledge, and leadership leads to a successful startup or a business. To be a successful entrepreneur, one should be people-oriented and have perseverance. One must have the ability to take risk, believe in his/her potential, and have the courage to move forward in all circumstances. Most importantly, have the ability to take risk and can assess the risk. For STEM students, entrepreneurship is of specific importance and relevance as it helps them not just to be able to solve real life existing complications but to be able to recognize and identify emerging needs and glitches. It is becoming increasingly apparent that in today’s world, there is a need as well as a desire for STEM and entrepreneurship to work together. In Pakistan, entrepreneurship is slowly emerging, yet we are far behind. It is high time that we should introduce modern teaching methods and inculcate entrepreneurial initiative in students. A course on entrepreneurship can be included in the syllabus, and we must invite businessmen and policy makers to motivate young minds for entrepreneurship. This must be pitching competitions, opportunities to win seed funding, and facilities of incubation centers. In Pakistan, there are many good public sector research institutes, yet there is a void gap in the private sector. Only few research institute are meant for research and development. BJ Micro Lab is one of them. It is SECP registered company and is working in academia to promote and facilitate research in STEM. BJ Micro Lab is a women led initiative, and we are trying to promote research as a passion, not as an arduous burden. For this, we are continuously arranging training workshops and sessions. More than 100 students have been trained in ten different workshops arranged at BJ Micro Lab.

Keywords: entrepreneurship, STEM, challenges, oppurtunties

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5072 Astaxanthin Induces Cytotoxicity through Down-Regulating Rad51 Expression in Human Lung Cancer Cells

Authors: Jyh-Cheng Chen, Tai-Jing Wang, Yun-Wei Lin

Abstract:

Astaxanthin has been demonstrated to exhibit a wide range of beneficial effects including anti-inflammatory and anti-cancer properties. However, the molecular mechanism of astaxanthin-induced cytotoxicity in non-small cell lung cancer (NSCLC) cells has not been identified. Rad51 plays a central role in homologous recombination and high levels of Rad51 expression are observed in chemo- or radioresistant carcinomas. In this study, astaxanthin treatment inhibited cell viability and proliferation of two NSCLC cells, A549 and H1703. Treatment with astaxanthin decreased Rad51 expression and phospho-AKT protein level in a time and dose-dependent manner. Furthermore, expression of constitutively active AKT (AKT-CA) vector significantly rescued the decreased Rad51 protein and mRNA levels in astaxanthin-treated NSCLC cells. Combined treatment with PI3K inhibitors (LY294002 or wortmannin) and astaxanthin further decreased the Rad51 expression in NSCLC cells. Knockdown of Rad51 enhanced astaxanthin-induced cytotoxicity and growth inhibition in NSCLC cells. These findings may have implications for the rational design of future drug regimens incorporating astaxanthin for the treatment of NSCLC.

Keywords: astaxanthin, cytotoxicity, AKT, non-small cell lung cancer, PI3K

Procedia PDF Downloads 297
5071 Synthesis of Novel Organic Dyes Based on Indigo for Dye-Sensitized Solar Cells

Authors: M. Hosseinnejad, K. Gharanjig, S. Moradian

Abstract:

A novel metal free organic dyes based on indigo was prepared and used as sensitizers in dye-sensitized solar cells. The synthesized dye together with its corresponding intermediates were purified and characterized by analytical techniques. Such techniques confirmed the corresponding structures of dye and its intermediate and the yield of all the stages of dye preparation were calculated to be above 85%. Fluorometric analyses show fluorescence in the green region of the visible spectrum for dye. Oxidation potential measurements for dye ensured an energetically permissible and thermodynamically favourable charge transfer throughout the continuous cycle of photo-electric conversion. Finally, dye sensitized solar cells were fabricated in order to determine the photovoltaic behaviour and conversion efficiencies of dye. Such evaluations demonstrate rather medium conversion efficiencies of 2.33% for such simple structured synthesized dye. Such conversion efficiencies demonstrate the potentiality of future use of such dye structures in dye-sensitized solar cells with respect to low material costs, ease of molecular tailoring, high yields of reactions, high performance and ease of recyclability.

Keywords: conversion efficiency, Dye-sensitized solar cells, indigo, photonic material

Procedia PDF Downloads 368
5070 Identification of Functional T Cell Receptors Reactive to Tumor Antigens from the T Cell Repertoire of Healthy Donors

Authors: Isaac Quiros-Fernandez, Angel Cid-Arregui

Abstract:

Tumor-reactive T cell receptors (TCRs) are being subject of intense investigation since they offer great potential in adoptive cell therapies against cancer. However, the identification of tumor-specific TCRs has proven challenging, for instance, due to the limited expansion capacity of tumor-infiltrating T cells (TILs) and the extremely low frequencies of tumor-reactive T cells in the repertoire of patients and healthy donors. We have developed an approach for rapid identification and characterization of neoepitope-reactive TCRs from the T cell repertoire of healthy donors. CD8 T cells isolated from multiple donors are subjected to a first sorting step after staining with HLA multimers carrying the peptide of interest. The isolated cells are expanded for two weeks, after which a second sorting is performed using the same peptide-HLA multimers. The cells isolated in this way are then processed for single-cell sequencing of their TCR alpha and beta chains. Newly identified TCRs are cloned in appropriate expression vectors for functional analysis on Jurkat, NK92, and primary CD8 T cells and tumor cells expressing the appropriate antigen. We have identified TCRs specifically binding HLA-A2 presenting epitopes of tumor antigens, which are capable of inducing TCR-mediated cell activation and cytotoxicity in target cancer cell lines. This method allows the identification of tumor-reactive TCRs in about two to three weeks, starting from peripheral blood samples of readily available healthy donors.

Keywords: cancer, TCR, tumor antigens, immunotherapy

Procedia PDF Downloads 69
5069 Transformation of Hexagonal Cells into Auxetic in Core Honeycomb Furniture Panels

Authors: Jerzy Smardzewski

Abstract:

Structures with negative Poisson's ratios are called auxetic. They are characterized by better mechanical properties than conventional structures, especially shear strength, the ability to better absorb energy and increase strength during bending, especially in sandwich panels. Commonly used paper cores of cellular boards are made of hexagonal cells. With isotropic facings, these cells provide isotropic properties of the entire furniture board. Shelves made of such panels with a thickness similar to standard chipboards do not provide adequate stiffness and strength of the furniture. However, it is possible to transform the shape of hexagonal cells into polyhedral auxetic cells that improve the mechanical properties of the core. The work aimed to transform the hexagonal cells of the paper core into auxetic cells and determine their basic mechanical properties. Using numerical methods, it was decided to design the most favorable proportions of cells distinguished by the lowest Poisson's ratio and the highest modulus of linear elasticity. Standard cores for cellular boards commonly used to produce 34 mm thick furniture boards were used for the tests. Poisson's ratios, bending strength, and linear elasticity moduli were determined for such cores and boards. Then, the cells were transformed into auxetic structures, and analogous cellular boards were made for which mechanical properties were determined. The results of numerical simulations for which the variable parameters were the dimensions of the cell walls, wall inclination angles, and relative cell density were presented in the further part of the paper. Experimental tests and numerical simulations showed the beneficial effect of auxeticization on the mechanical quality of furniture panels. They allowed for the selection of the optimal shape of auxetic core cells.

Keywords: auxetics, honeycomb, panels, simulation, experiment

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5068 Effects of Substrate Roughness on E-Cadherin Junction of Oral Keratinocytes

Authors: Sungpyo Kim, Changseok Oh, Ga-Young Lee, Hyun-Man Kim

Abstract:

Intercellular junction of keratinocytes is crucial for epithelia to build an epithelial barrier. Junctional epithelium (JE) seals the interfaces between tooth and gingival tissue. Keratinocytes of JE attach to surfaces roughened by abrasion or erosion with aging. Thus behavior of oral keratinocytes on the rough substrates may help understand the epithelial seal of JE of which major intercellular junction is E-cadherin junction (ECJ). The present study investigated the influence of various substrate roughnesses on the development of ECJ between normal human gingival epithelial keratinocytes, HOK-16B cells. HOK-16B cells were slow in the development of ECJ on the rough substrates compared to on the smooth substrates. Furthermore, oral keratinocytes on the substrates of higher roughnesses were delayed in the development of E-cadherin junction than on the substrates of lower roughnesses. Delayed development of E-cadherin junction on the rough substrates was ascribed to the impaired spreading of cells and its higher JNK activity. Cells on the smooth substrates rapidly spread wide cytoplasmic extensions around cells. However, cells on the rough substrates slowly extended narrow cytoplasmic extensions of which number was limited due to the substrate irregularity. As these cytoplasmic extensions formed ECJ when met with the extensions of neighboring cells, thus, the present study demonstrated that a limited chance of contacts between cytoplasmic extensions due to the limited number of cytoplasmic extensions and slow development of cytoplasmic extensions brought about a delayed development of ECJ in oral keratinocytes on the rougher substrates. Sealing between cells was not complete because only part of cell membrane contributes to the formation of intercellular junction between cells on the substrates of higher roughnesses. Interestingly, inhibition of JNK activity promoted the development of ECJ on the rough substrates, of which mechanism remains to be studied further.

Keywords: substrate roughness, E-cadherin junction, oral keratinocyte, cell spreading, JNK

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5067 Effects of Reclamation on Seasonal Dynamic of Carbon, Nitrogen and Phosphorus Stoichiometry in Suaeda salsa

Authors: Yajun Qiao, Yaner Yan, Ning Li, Shuqing An

Abstract:

In order to relieve the pressure on a land resource from a huge population, reclamation has occurred in many coastal wetlands. Plants can maintain their elemental composition within normal limits despite the variations of external conditions. Reclamation may affect carbon (C), nitrogen (N) and phosphorus (P) stoichiometry in the plant to some extent by altering physical and chemical properties of soil in a coastal wetland. We reported the seasonal dynamic of C, N and P stoichiometry in root, stem and leaf of Suaeda salsa (L.) Pall. and in soil between reclamation plots and natural plots. Our results of three-way ANOVA indicated that sampling season always had significant effect on C, N, P concentrations and their ratios; organ had no significant effect on N, P concentration and N:P; plot type had no significant effect on N concentration and C:N. Sampling season explained the most variability of tissue N and P contents, C:N, C:P and N:P, while it’s organ for C using the restricted maximum likelihood (REML) method. By independent sample T-test, we found that reclamation affect more on C, N and P stoichiometry of stem than that of root or leaf on the whole. While there was no difference between reclamation plots and natural plots for soil in four seasons. For three organs, C concentration had peak values in autumn and minimum values in spring while N concentration had peak values in spring and minimum values in autumn. For P concentration, three organs all had peak values in spring; however, the root had minimum value in winter, the stem had that in autumn, and leaf had that in summer. The seasonal dynamic of C, N and P stoichiometry in a leaf of Suaeda salsa were much steadier than that in root or stem under the drive of reclamation.

Keywords: nitrogen, phosphorus, reclamation, seasonal dynamic, Suaeda salsa

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5066 Modeling of Bioelectric Activity of Nerve Cells Using Bond Graph Method

Authors: M. Ghasemi, F. Eskandari, B. Hamzehei, A. R. Arshi

Abstract:

Bioelectric activity of nervous cells might be changed causing by various factors. This alteration can lead to unforeseen circumstances in other organs of the body. Therefore, the purpose of this study was to model a single neuron and its behavior under an initial stimulation. This study was developed based on cable theory by means of the Bond Graph method. The numerical values of the parameters were derived from empirical studies of cellular electrophysiology experiments. Initial excitation was applied through square current functions, and the resulted action potential was estimated along the neuron. The results revealed that the model was developed in this research adapted with the results of experimental studies and demonstrated the electrical behavior of nervous cells properly.

Keywords: bond graph, stimulation, nervous cells, modeling

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5065 A Case Study of Deep Learning for Disease Detection in Crops

Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

Abstract:

In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

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5064 The Role of Immunologic Diamonds in Dealing with Mycobacterium Tuberculosis; Responses of Immune Cells in Affliction to the Respiratory Tuberculosis

Authors: Seyyed Mohammad Amin Mousavi Sagharchi, Elham Javanroudi

Abstract:

Introduction: Tuberculosis (TB) is a known disease with hidden features caused by Mycobacterium tuberculosis (MTB). This disease, which is one of the 10 deadliest in the world, has caused millions of deaths in recent decades. Furthermore, TB is responsible for infecting about 30% population of world. Like any infection, TB can activate the immune system by locating and colonization in the human body, especially in the alveoli. TB is granulomatosis, so MTB can absorb the host’s immune cells and other cells to form granuloma. Method: Different databases (e.g., PubMed) were recruited to prepare this paper and fulfill our goals to search and find effective papers and investigations. Results: Immune response to MTB is related to T cell killers and contains CD1, CD4, and CD8 T lymphocytes. CD1 lymphocytes can recognize glycolipids, which highly exist in the Mycobacterial fatty cell wall. CD4 lymphocytes and macrophages form granuloma, and it is the main line of immune response to Mycobacteria. On the other hand, CD8 cells have cytolytic function for directly killing MTB by secretion of granulysin. Other functions and secretion to the deal are interleukin-12 (IL-12) by induction of expression interferon-γ (INF-γ) for macrophages activation and creating a granuloma, and tumor necrosis factor (TNF) by promoting macrophage phagolysosomal fusion. Conclusion: Immune cells in battle with MTB are macrophages, dendritic cells (DCs), neutrophils, and natural killer (NK) cells. These immune cells can recognize the Mycobacterium by various receptors, including Toll-like receptors (TLRs), Nod-like receptors (NLRs), and C-type lectin receptors (CLRs) located in the cell surface. In human alveoli exist about 50 dendritic macrophages, which have close communication with other immune cells in the circulating system and epithelial cells to deal with Mycobacteria. Against immune cells, MTB handles some factors (e.g., cordfactor, O-Ag, lipoarabinomannan, sulfatides, and adenylate cyclase) and practical functions (e.g., inhibition of macrophages).

Keywords: mycobacterium tuberculosis, immune responses, immunological mechanisms, respiratory tuberculosis

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5063 Local Image Features Emerging from Brain Inspired Multi-Layer Neural Network

Authors: Hui Wei, Zheng Dong

Abstract:

Object recognition has long been a challenging task in computer vision. Yet the human brain, with the ability to rapidly and accurately recognize visual stimuli, manages this task effortlessly. In the past decades, advances in neuroscience have revealed some neural mechanisms underlying visual processing. In this paper, we present a novel model inspired by the visual pathway in primate brains. This multi-layer neural network model imitates the hierarchical convergent processing mechanism in the visual pathway. We show that local image features generated by this model exhibit robust discrimination and even better generalization ability compared with some existing image descriptors. We also demonstrate the application of this model in an object recognition task on image data sets. The result provides strong support for the potential of this model.

Keywords: biological model, feature extraction, multi-layer neural network, object recognition

Procedia PDF Downloads 542
5062 Biodegradation of Chlorpyrifos in Real Wastewater by Acromobacter xylosoxidans SRK5 Immobilized in Calcium Alginate

Authors: Saira Khalid, Imran Hashmi

Abstract:

Agrochemical industries produce huge amount of wastewater containing pesticides and other harmful residues. Environmental regulations make it compulsory to bring pesticides to a minimum level before releasing wastewater from industrial units.The present study was designed with the objective to investigate biodegradation of CP in real wastewater using bacterial cells immobilized in calcium alginate. Bacterial strain identified as Acromobacter xylosoxidans SRK5 (KT013092) using 16S rRNA nucleotide sequence analysis was used. SRK5 was immobilized in calcium alginate to make calcium alginate microspheres (CAMs). Real wastewater from industry having 50 mg L⁻¹ of CP was inoculated with free cells or CAMs and incubated for 96 h at 37˚C. CP removal efficiency with CAMs was 98% after 72 h of incubation, and no lag phase was observed. With free cells, 12h of lag phase was observed. After 96 h of incubation 87% of CP removal was observed when inoculated with free cells. No adsorption was observed on vacant CAMs. Phytotoxicity assay demonstrated considerable loss in toxicity. Almost complete COD removal was achieved at 96 h with CAMs. Study suggests the use of immobilized cells of SRK5 for bioaugmentation of industrial wastewater for CP degradation instead of free cells.

Keywords: biodegradation, chlorpyrifos, immobilization, wastewater

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5061 Cellulose Acetate Nanofiber Modification for Regulating Astrocyte Activity via Simple Heat Treatment

Authors: Sang-Myung Jung, Jeong Hyun Ju, Gwang Heum Yoon, Hwa Sung Shin

Abstract:

Central nervous system (CNS) consists of neuronal cell and supporting cells. Astrocytes are the most common supporting cells and play roles in metabolism between neurons and blood vessel. For this function, engineered astrocytes have been studied as a therapeutic source for CNS injury. In neural tissue engineering, nanofiber has been suggested as an effective scaffold for providing structure and mechanical properties influencing physiology. Cellulose acetate (CA) has been investigated for material to fabricate scaffold because of its biocompatibility, biodegradability and fine thermal stability. In this research, CA nanofiber was modified via heat treatment and its effect on astrocyte activity was evaluated. Adhesion and viability of astrocyte were increased in proportion to stiffness. Additionally, expression of GFAP, a marker of astrocyte activation, was increased via stiffness of scaffold. This research suggests a simple modification method to change stiffness of CA nanofiber and shows cellular behavior affecting stiffness of three-dimensional scaffold independently. For the results, we highlight that the stiffness is a factor to regulate astrocyte activity.

Keywords: astrocyte, cellulose acetate, cell therapy, stiffness of scaffold

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5060 Regression for Doubly Inflated Multivariate Poisson Distributions

Authors: Ishapathik Das, Sumen Sen, N. Rao Chaganty, Pooja Sengupta

Abstract:

Dependent multivariate count data occur in several research studies. These data can be modeled by a multivariate Poisson or Negative binomial distribution constructed using copulas. However, when some of the counts are inflated, that is, the number of observations in some cells are much larger than other cells, then the copula based multivariate Poisson (or Negative binomial) distribution may not fit well and it is not an appropriate statistical model for the data. There is a need to modify or adjust the multivariate distribution to account for the inflated frequencies. In this article, we consider the situation where the frequencies of two cells are higher compared to the other cells, and develop a doubly inflated multivariate Poisson distribution function using multivariate Gaussian copula. We also discuss procedures for regression on covariates for the doubly inflated multivariate count data. For illustrating the proposed methodologies, we present a real data containing bivariate count observations with inflations in two cells. Several models and linear predictors with log link functions are considered, and we discuss maximum likelihood estimation to estimate unknown parameters of the models.

Keywords: copula, Gaussian copula, multivariate distributions, inflated distributios

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5059 Isolation of Cytotoxic Compound from Tectona grandis Stem to Be Used as Thai Medicinal Preparation for Cancer Treatment

Authors: Onmanee Prajuabjinda, Pakakrong Thondeeying, Jipisute Chunthorng-Orn, Bhanuz Dechayont, Arunporn Itharat

Abstract:

A Thai medicinal preparation has been used for cancer treatment more than ten years ago in Khampramong Temple. Tectona grandis stem is one ingredient of this Thai medicinal remedy. The ethanolic extract of Tectona grandis stem showed the highest cytotoxic activities against human breast adenocarcinoma (MCF-7), but was less cytotoxic against large cell lung carcinoma (COR-L23) (IC50 = 3.92 and 7.78 µg/ml, respectively). It was isolated by bioassay-guided isolation method. Tectoquinone, a anthraquinone compound was isolated from this plant. This compound showed high specific cytotoxicity against human breast adenocarcinoma (MCF-7), but was less cytotoxic against large cell lung carcinoma (COR-L23)(IC50 =16.15 and 47.56 µg/ml or 72.67 and 214.00 µM, respectively). However, it showed less cytotoxic activity than the crude extract. In conclusion, tectoquinone as a main compound, is not the best cytotoxic compound from Tectona grandis, so there are more active cytotoxic compounds in this extract which should be isolated in the future. Moreover, tectoquinone displayed specific cytotoxicity against only human breast adenocarcinoma (MCF-7) which is a good criterion for cancer treatment.

Keywords: Tectona grandis, SRB assay, cytotoxicity, tectoquinone

Procedia PDF Downloads 432