Search results for: multi cavitation cells (MC-Cells)
5632 Identification of the Target Genes to Increase the Immunotherapy Response in Bladder Cancer Patients using Computational and Experimental Approach
Authors: Sahar Nasr, Lin Li, Edwin Wang
Abstract:
Bladder cancer (BLCA) is known as the 13th cause of death among cancer patients worldwide, and ~575,000 new BLCA cases are diagnosed each year. Urothelial carcinoma (UC) is the most prevalent subtype among BLCA patients, which can be categorized into muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC). Currently, various therapeutic options are available for UC patients, including (1) transurethral resection followed by intravesical instillation of chemotherapeutics or Bacillus Calmette-Guérin for NMIBC patients, (2) neoadjuvant platinum-based chemotherapy (NAC) plus radical cystectomy is the standard of care for localized MIBC patients, and (3) systematic chemotherapy for metastatic UC. However, conventional treatments may lead to several challenges for treating patients. As an illustration, some patients may suffer from recurrence of the disease after the first line of treatment. Recently, immune checkpoint therapy (ICT) has been introduced as an alternative treatment strategy for the first or second line of treatment in advanced or metastatic BLCA patients. Although ICT showed lucrative results for a fraction of BLCA patients, ~80% of patients were not responsive to it. Therefore, novel treatment methods are required to augment the ICI response rate within BLCA patients. It has been shown that the infiltration of T-cells into the tumor microenvironment (TME) is positively correlated with the response to ICT within cancerous patients. Therefore, the goal of this study is to enhance the infiltration of cytotoxic T-cells into TME through the identification of target genes within the tumor that are responsible for the non-T-cell inflamed TME and their inhibition. BLCA bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) and immune score for TCGA samples were used to determine the Pearson correlation score between the expression of different genes and immune score for each sample. The genes with strong negative correlations were selected (r < -0.2). Thereafter, the correlation between the expression of each gene and survival in BLCA patients was calculated using the TCGA data and Cox regression method. The genes that are common in both selected gene lists were chosen for further analysis. Afterward, BLCA bulk and single-cell RNA-sequencing data were ranked based on the expression of each selected gene and the top and bottom 25% samples were used for pathway enrichment analysis. If the pathways related to the T-cell infiltration (e.g., antigen presentation, interferon, or chemokine pathways) were enriched within the low-expression group, the gene was included for downstream analysis. Finally, the selected genes will be used to calculate the correlation between their expression and the infiltration rate of the activated CD+8 T-cells, natural killer cells and the activated dendric cells. A list of potential target genes has been identified and ranked based on the above-mentioned analysis and criteria. SUN-1 got the highest score within the gene list and other identified genes in the literature as benchmarks. In conclusion, inhibition of SUN1 may increase the tumor-infiltrating lymphocytes and the efficacy of ICI in BLCA patients. BLCA tumor cells with and without SUN-1 CRISPR/Cas9 knockout will be injected into the syngeneic mouse model to validate the predicted SUN-1 effect on increasing tumor-infiltrating lymphocytes.Keywords: data analysis, gene expression analysis, gene identification, immunoinformatic, functional genomics, transcriptomics
Procedia PDF Downloads 1595631 Parallel Pipelined Conjugate Gradient Algorithm on Heterogeneous Platforms
Authors: Sergey Kopysov, Nikita Nedozhogin, Leonid Tonkov
Abstract:
The article presents a parallel iterative solver for large sparse linear systems which can be used on a heterogeneous platform. Traditionally, the problem of solving linear systems does not scale well on multi-CPU/multi-GPUs clusters. For example, most of the attempts to implement the classical conjugate gradient method were at best counted in the same amount of time as the problem was enlarged. The paper proposes the pipelined variant of the conjugate gradient method (PCG), a formulation that is potentially better suited for hybrid CPU/GPU computing since it requires only one synchronization point per one iteration instead of two for standard CG. The standard and pipelined CG methods need the vector entries generated by the current GPU and other GPUs for matrix-vector products. So the communication between GPUs becomes a major performance bottleneck on multi GPU cluster. The article presents an approach to minimize the communications between parallel parts of algorithms. Additionally, computation and communication can be overlapped to reduce the impact of data exchange. Using the pipelined version of the CG method with one synchronization point, the possibility of asynchronous calculations and communications, load balancing between the CPU and GPU for solving the large linear systems allows for scalability. The algorithm is implemented with the combined use of technologies: MPI, OpenMP, and CUDA. We show that almost optimum speed up on 8-CPU/2GPU may be reached (relatively to a one GPU execution). The parallelized solver achieves a speedup of up to 5.49 times on 16 NVIDIA Tesla GPUs, as compared to one GPU.Keywords: conjugate gradient, GPU, parallel programming, pipelined algorithm
Procedia PDF Downloads 1675630 Assessment of Biofilm Production Capacity of Industrially Important Bacteria under Electroinductive Conditions
Authors: Omolola Ojetayo, Emmanuel Garuba, Obinna Ajunwa, Abiodun A. Onilude
Abstract:
Introduction: Biofilm is a functional community of microorganisms that are associated with a surface or an interface. These adherent cells become embedded within an extracellular matrix composed of polymeric substances, i.e., biofilms refer to biological deposits consisting of both microbes and their extracellular products on biotic and abiotic surfaces. Despite their detrimental effects in medicine, biofilms as natural cell immobilization have found several applications in biotechnology, such as in the treatment of wastewater, bioremediation and biodegradation, desulfurization of gas, and conversion of agro-derived materials into alcohols and organic acids. The means of enhancing immobilized cells have been chemical-inductive, and this affects the medium composition and final product. Physical factors including electrical, magnetic, and electromagnetic flux have shown potential for enhancing biofilms depending on the bacterial species, nature, and intensity of emitted signals, the duration of exposure, and substratum used. However, the concept of cell immobilisation by electrical and magnetic induction is still underexplored. Methods: To assess the effects of physical factors on biofilm formation, six American typed culture collection (Acetobacter aceti ATCC15973, Pseudomonas aeruginosa ATCC9027, Serratia marcescens ATCC14756, Gluconobacter oxydans ATCC19357, Rhodobacter sphaeroides ATCC17023, and Bacillus subtilis ATCC6633) were used. Standard culture techniques for bacterial cells were adopted. Natural autoimmobilisation potentials of test bacteria were carried out by simple biofilms ring formation on tubes, while crystal violet binding assay techniques were adopted in the characterisation of biofilm quantity. Electroinduction of bacterial cells by direct current (DC) application in cell broth, static magnetic field exposure, and electromagnetic flux were carried out, and autoimmobilisation of cells in a biofilm pattern was determined on various substrata tested, including wood, glass, steel, polyvinylchloride (PVC) and polyethylene terephthalate. Biot Savart law was used in quantifying magnetic field intensity, and statistical analyses of data obtained were carried out using the analyses of variance (ANOVA) as well as other statistical tools. Results: Biofilm formation by the selected test bacteria was enhanced by the physical factors applied. Electromagnetic induction had the greatest effect on biofilm formation, with magnetic induction producing the least effect across all substrata used. Microbial cell-cell communication could be a possible means via which physical signals affected the cells in a polarisable manner. Conclusion: The enhancement of biofilm formation by bacteria using physical factors has shown that their inherent capability as a cell immobilization method can be further optimised for industrial applications. A possible relationship between the presence of voltage-dependent channels, mechanosensitive channels, and bacterial biofilms could shed more light on this phenomenon.Keywords: bacteria, biofilm, cell immobilization, electromagnetic induction, substrata
Procedia PDF Downloads 1935629 Rocket Launch Simulation for a Multi-Mode Failure Prediction Analysis
Authors: Mennatallah M. Hussein, Olivier de Weck
Abstract:
The advancement of space exploration demands a robust space launch services program capable of reliably propelling payloads into orbit. Despite rigorous testing and quality assurance, launch failures still occur, leading to significant financial losses and jeopardizing mission objectives. Traditional failure prediction methods often lack the sophistication to account for multi-mode failure scenarios, as well as the predictive capability in complex dynamic systems. Traditional approaches also rely on expert judgment, leading to variability in risk prioritization and mitigation strategies. Hence, there is a pressing need for robust approaches that enhance launch vehicle reliability from lift-off until it reaches its parking orbit through comprehensive simulation techniques. In this study, the developed model proposes a multi-mode launch vehicle simulation framework for predicting failure scenarios when incorporating new technologies, such as new propulsion systems or advanced staging separation mechanisms in the launch system. To this end, the model combined a 6-DOF system dynamics with comprehensive data analysis to simulate multiple failure modes impacting launch performance. The simulator utilizes high-fidelity physics-based simulations to capture the complex interactions between different subsystems and environmental conditions.Keywords: launch vehicle, failure prediction, propulsion anomalies, rocket launch simulation, rocket dynamics
Procedia PDF Downloads 385628 Reducing Change-Related Costs in Assembly of Lithium-Ion Batteries for Electric Cars by Mechanical Decoupling
Authors: Achim Kampker, Heiner Hans Heimes, Mathias Ordung, Nemanja Sarovic
Abstract:
A key component of the drive train of electric vehicles is the lithium-ion battery system. Among various other components, such as the battery management system or the thermal management system, the battery system mostly consists of several cells which are integrated mechanically as well as electrically. Due to different vehicle concepts with regards to space, energy and power specifications, there is a variety of different battery systems. The corresponding assembly lines are specially designed for each battery concept. Minor changes to certain characteristics of the battery have a disproportionally high effect on the set-up effort in the form of high change-related costs. This paper will focus on battery systems which are made out of battery cells with a prismatic format. The product architecture and the assembly process will be analyzed in detail based on battery concepts of existing electric cars and key variety-causing drivers will be identified. On this basis, several measures will be presented and discussed on how to change the product architecture and the assembly process in order to reduce change-related costs.Keywords: assembly, automotive industry, battery system, battery concept
Procedia PDF Downloads 3085627 Multi-Objective Optimization of a Solar-Powered Triple-Effect Absorption Chiller for Air-Conditioning Applications
Authors: Ali Shirazi, Robert A. Taylor, Stephen D. White, Graham L. Morrison
Abstract:
In this paper, a detailed simulation model of a solar-powered triple-effect LiBr–H2O absorption chiller is developed to supply both cooling and heating demand of a large-scale building, aiming to reduce the fossil fuel consumption and greenhouse gas emissions in building sector. TRNSYS 17 is used to simulate the performance of the system over a typical year. A combined energetic-economic-environmental analysis is conducted to determine the system annual primary energy consumption and the total cost, which are considered as two conflicting objectives. A multi-objective optimization of the system is performed using a genetic algorithm to minimize these objectives simultaneously. The optimization results show that the final optimal design of the proposed plant has a solar fraction of 72% and leads to an annual primary energy saving of 0.69 GWh and annual CO2 emissions reduction of ~166 tonnes, as compared to a conventional HVAC system. The economics of this design, however, is not appealing without public funding, which is often the case for many renewable energy systems. The results show that a good funding policy is required in order for these technologies to achieve satisfactory payback periods within the lifetime of the plant.Keywords: economic, environmental, multi-objective optimization, solar air-conditioning, triple-effect absorption chiller
Procedia PDF Downloads 2475626 Extension of the Simplified Theory of Plastic Zones for Analyzing Elastic Shakedown in a Multi-Dimensional Load Domain
Authors: Bastian Vollrath, Hartwig Hubel
Abstract:
In case of over-elastic and cyclic loading, strain may accumulate due to a ratcheting mechanism until the state of shakedown is possibly achieved. Load history dependent numerical investigations by a step-by-step analysis are rather costly in terms of engineering time and numerical effort. In the case of multi-parameter loading, where various independent loadings affect the final state of shakedown, the computational effort becomes an additional challenge. Therefore, direct methods like the Simplified Theory of Plastic Zones (STPZ) are developed to solve the problem with a few linear elastic analyses. Post-shakedown quantities such as strain ranges and cyclic accumulated strains are calculated approximately by disregarding the load history. The STPZ is based on estimates of a transformed internal variable, which can be used to perform modified elastic analyses, where the elastic material parameters are modified, and initial strains are applied as modified loading, resulting in residual stresses and strains. The STPZ already turned out to work well with respect to cyclic loading between two states of loading. Usually, few linear elastic analyses are sufficient to obtain a good approximation to the post-shakedown quantities. In a multi-dimensional load domain, the approximation of the transformed internal variable transforms from a plane problem into a hyperspace problem, where time-consuming approximation methods need to be applied. Therefore, a solution restricted to structures with four stress components was developed to estimate the transformed internal variable by means of three-dimensional vector algebra. This paper presents the extension to cyclic multi-parameter loading so that an unlimited number of load cases can be taken into account. The theoretical basis and basic presumptions of the Simplified Theory of Plastic Zones are outlined for the case of elastic shakedown. The extension of the method to many load cases is explained, and a workflow of the procedure is illustrated. An example, adopting the FE-implementation of the method into ANSYS and considering multilinear hardening is given which highlights the advantages of the method compared to incremental, step-by-step analysis.Keywords: cyclic loading, direct method, elastic shakedown, multi-parameter loading, STPZ
Procedia PDF Downloads 1665625 Characterization of a Dentigerous Cyst Cell Line and Its Secretion of Metalloproteinases
Authors: Muñiz-Lino Marcos A.
Abstract:
The ectomesenchymal tissues involved in tooth development and their remnants are the origin of different odontogenic lesions, including tumors and cysts of the jaws, with a wide range of clinical behaviors. A dentigerous cyst (DC) represents approximately 20% of all cases of odontogenic cysts, and it has been demonstrated that it can develop benign and malignant odontogenic tumors. DC is characterized by bone destruction of the area surrounding the crown of a tooth that has not erupted and contains liquid. The treatment of odontogenic tumors and cysts usually involves a partial or total removal of the jaw, causing important secondary co-morbidities. However, molecules implicated in DC pathogenesis, as well as in its development into odontogenic tumors, remain unknown. A cellular model may be useful to study these molecules, but that model has not been established yet. Here, we reported the establishment of a cell culture derived from a dentigerous cyst. This cell line was named DeCy-1. In spite of its ectomesenchymal morphology, DeCy-1 cells express epithelial markers such as cytokeratins 5, 6, and 8. Furthermore, these cells express the ODAM protein, which is present in odontogenesis and in dental follicles, indicating that DeCy-1 cells are derived from odontogenic epithelium. Analysis by electron microscopy of this cell line showed that it has a high vesicular activity, suggesting that DeCy-1 could secrete molecules that may be involved in DC pathogenesis. Thus, secreted proteins were analyzed by PAGE-SDS where we observed approximately 11 bands. In addition, the capacity of these secretions to degrade proteins was analyzed by gelatin substrate zymography. A degradation band of about 62 kDa was found in these assays. Western blot assays suggested that the matrix metalloproteinase 2 (MMP-2) is responsible for this protease activity. Thus, our results indicate that the establishment of a cell line derived from DC is a useful in vitro model to study the biology of this odontogenic lesion and its participation in the development of odontogenic tumors.Keywords: dentigerous cyst, ameloblastoma, MMP-2, odontogenic tumors
Procedia PDF Downloads 475624 Multi-Modal Film Boiling Simulations on Adaptive Octree Grids
Authors: M. Wasy Akhtar
Abstract:
Multi-modal film boiling simulations are carried out on adaptive octree grids. The liquid-vapor interface is captured using the volume-of-fluid framework adjusted to account for exchanges of mass, momentum, and energy across the interface. Surface tension effects are included using a volumetric source term in the momentum equations. The phase change calculations are conducted based on the exact location and orientation of the interface; however, the source terms are calculated using the mixture variables to be consistent with the one field formulation used to represent the entire fluid domain. The numerical model on octree representation of the computational grid is first verified using test cases including advection tests in severely deforming velocity fields, gravity-based instabilities and bubble growth in uniformly superheated liquid under zero gravity. The model is then used to simulate both single and multi-modal film boiling simulations. The octree grid is dynamically adapted in order to maintain the highest grid resolution on the instability fronts using markers of interface location, volume fraction, and thermal gradients. The method thus provides an efficient platform to simulate fluid instabilities with or without phase change in the presence of body forces like gravity or shear layer instabilities.Keywords: boiling flows, dynamic octree grids, heat transfer, interface capturing, phase change
Procedia PDF Downloads 2505623 Cytotoxicity thiamethoxam Study on the Hepatopancreas and Its Reversibility under the Effect of Ginger in Helix aspersa
Authors: Samira Bensoltane, Smina Ait Hamlet, Samti Meriem, Semmasel Asma
Abstract:
Living organisms in the soil are subject to regular fluctuations of abiotic parameters, as well as a chemical contamination of the environment due to human activities. They are subject to multiple stressors they face. The aim of our work was to study the effects of insecticide: thiamethoxam (neonicotinoid), and the potential reversibility of the effects by an antioxidant: ginger on a bioindicator species in ecotoxicology, the land snail Helix aspersa. The effects were studied by a targeted cell approach of evaluating the effect of these molecules on tissue and cellular aspect of hepatopancreas through histological study. Treatment with thiamethoxam concentrations 10, 20, and 40 mg/l shows signs of inflammation even at low concentrations and from the 5th day of treatment. Histological examination of the hepatopancreas of snails treated with thiamethoxam showed significant changes from the lowest concentrations tested , note intertubular connective tissue enlargement, necrosis deferent types of cells (cells with calcium , digestive, excretory) , also damage acini, alteration of the apical membrane and lysis of the basement membrane in a dose- dependent manner. After 10 days of treatment and with 40 mg/l, the same changes were observed with a very advanced degeneration of the wall of the member that could be confused with the cell debris. For cons, the histological study of the hepatopancreas in Helix aspersa treated with ginger for a period of 15 days after stopping treatment with thiamethoxam has shown a partial regeneration of hepatopancreatic tissue snails treated with all concentrations of thiamethoxam and especially in the intertubular connective tissue of the wall and hepatopancreatic digestive tubules. Finally, we can conclude that monitoring the effect of the insecticide thiamethoxam showed significant alterations, however, treatment with ginger shows regeneration of damaged cells themselves much sharper at low concentration (10 mg/L).Keywords: Helix aspersa, insecticides, thiamethoxam, ginger, hepatopancreas
Procedia PDF Downloads 2185622 Anticipation of Bending Reinforcement Based on Iranian Concrete Code Using Meta-Heuristic Tools
Authors: Seyed Sadegh Naseralavi, Najmeh Bemani
Abstract:
In this paper, different concrete codes including America, New Zealand, Mexico, Italy, India, Canada, Hong Kong, Euro Code and Britain are compared with the Iranian concrete design code. First, by using Adaptive Neuro Fuzzy Inference System (ANFIS), the codes having the most correlation with the Iranian ninth issue of the national regulation are determined. Consequently, two anticipated methods are used for comparing the codes: Artificial Neural Network (ANN) and Multi-variable regression. The results show that ANN performs better. Predicting is done by using only tensile steel ratio and with ignoring the compression steel ratio.Keywords: adaptive neuro fuzzy inference system, anticipate method, artificial neural network, concrete design code, multi-variable regression
Procedia PDF Downloads 2885621 Optimum Dispatching Rule in Solar Ingot-Wafer Manufacturing System
Authors: Wheyming Song, Hung-Hsiang Lin, Scott Lian
Abstract:
In this research, we investigate the optimal dispatching rule for machines and manpower allocation in the solar ingot-wafer systems. The performance of the method is measured by the sales profit for each dollar paid to the operators in a one week at steady-state. The decision variables are identification-number of machines and operators when each job is required to be served in each process. We propose a rule which is a function of operator’s ability, corresponding salary, and standing location while in the factory. The rule is named ‘Multi-nominal distribution dispatch rule’. The proposed rule performs better than many traditional rules including generic algorithm and particle swarm optimization. Simulation results show that the proposed Multi-nominal distribution dispatch rule improvement on the sales profit dramatically.Keywords: dispatching, solar ingot, simulation, flexsim
Procedia PDF Downloads 3045620 Coastalization and Urban Sprawl in the Mediterranean: Using High-Resolution Multi-Temporal Data to Identify Typologies of Spatial Development
Authors: Apostolos Lagarias, Anastasia Stratigea
Abstract:
Coastal urbanization is heavily affecting the Mediterranean, taking the form of linear urban sprawl along the coastal zone. This process is posing extreme pressure on ecosystems, leading to an unsustainable model of growth. The aim of this research is to analyze coastal urbanization patterns in the Mediterranean using High-resolution multi-temporal data provided by the Global Human Settlement Layer (GHSL) database. Methodology involves the estimation of a set of spatial metrics characterizing the density, aggregation/clustering and dispersion of built-up areas. As case study areas, the Spanish Coast and the Adriatic Italian Coast are examined. Coastalization profiles are examined and selected sub-areas massively affected by tourism development and suburbanization trends (Costa Blanca/Murcia, Costa del Sol, Puglia, Emilia-Romagna Coast) are analyzed and compared. Results show that there are considerable differences between the Spanish and the Italian typologies of spatial development, related to the land use structure and planning policies applied in each case. Monitoring and analyzing spatial patterns could inform integrated Mediterranean strategies for coastal areas and redirect spatial/environmental policies towards a more sustainable model of growthKeywords: coastalization, Mediterranean, multi-temporal, urban sprawl, spatial metrics
Procedia PDF Downloads 1465619 Comprehensive Risk Assessment Model in Agile Construction Environment
Authors: Jolanta Tamošaitienė
Abstract:
The article focuses on a developed comprehensive model to be used in an agile environment for the risk assessment and selection based on multi-attribute methods. The model is based on a multi-attribute evaluation of risk in construction, and the determination of their optimality criterion values are calculated using complex Multiple Criteria Decision-Making methods. The model may be further applied to risk assessment in an agile construction environment. The attributes of risk in a construction project are selected by applying the risk assessment condition to the construction sector, and the construction process efficiency in the construction industry accounts for the agile environment. The paper presents the comprehensive risk assessment model in an agile construction environment. It provides a background and a description of the proposed model and the developed analysis of the comprehensive risk assessment model in an agile construction environment with the criteria.Keywords: assessment, environment, agile, model, risk
Procedia PDF Downloads 2585618 Anti-Neuroinflammatory and Anti-Apoptotic Efficacy of Equol, against Lipopolysaccharide Activated Microglia and Its Neurotoxicity
Authors: Lalita Subedi, Jae Kyoung Chae, Yong Un Park, Cho Kyo Hee, Lee Jae Hyuk, Kang Min Cheol, Sun Yeou Kim
Abstract:
Neuroinflammation may mediate the relationship between low levels of estrogens and neurodegenerative disease. Estrogens are neuroprotective and anti-inflammatory in neurodegenerative disease models. Due to the long term side effects of estrogens, researches have been focused on finding an effective phytoestrogens for biological activities. Daidzein present in soybeans and its active metabolite equol (7-hydroxy-3-(4'-hydroxyphenyl)-chroman) bears strong antioxidant and anticancer showed more potent anti-inflammatory and neuroprotective role in neuroinflammatory model confirmed its in vitro activity with molecular mechanism through NF-κB pathway. Three major CNS cells Microglia (BV-2), Astrocyte (C6), Neuron (N2a) were used to find the effect of equol in inducible nitric oxide synthase (iNOS), cyclooxygenase (COX-2), MAPKs signaling proteins, apoptosis related proteins by western blot analysis. Nitric oxide (NO) and prostaglandin E2 (PGE2) was measured by the Gries method and ELISA, respectively. Cytokines like tumor necrosis factor-α (TNF-α) and IL-6 were also measured in the conditioned medium of LPS activated cells with or without equol. Equol inhibited the NO production, PGE-2 production and expression of COX-2 and iNOS in LPS-stimulated microglial cells at a dose dependent without any cellular toxicity. At the same time Equol also showed promising effect in modulation of MAPK’s and nuclear factor kappa B (NF-κB) expression with significant inhibition of the production of proinflammatory cytokine like interleukin -6 (IL-6), and tumor necrosis factor -α (TNF-α). Additionally, it inhibited the LPS activated microglia-induced neuronal cell death by downregulating the apoptotic phenomenon in neuronal cells. Furthermore, equol increases the production of neurotrophins like NGF and increase the neurite outgrowth as well. In conclusion the natural daidzein metabolite equol are more active than daidzein, which showed a promising effectiveness as an anti-neuroinflammatory and neuroprotective agent via downregulating the LPS stimulated microglial activation and neuronal apoptosis. This work was supported by Brain Korea 21 Plus project and High Value-added Food Technology Development Program 114006-4, Ministry of Agriculture, Food and Rural Affairs.Keywords: apoptosis, equol, neuroinflammation, phytoestrogen
Procedia PDF Downloads 3635617 Breast Cancer: The Potential of miRNA for Diagnosis and Treatment
Authors: Abbas Pourreza
Abstract:
MicroRNAs (miRNAs) are small single-stranded non-coding RNAs. They are almost 18-25 nucleotides long and very conservative through evolution. They are involved in adjusting the expression of numerous genes due to the existence of a complementary region, generally in the 3' untranslated regions (UTR) of target genes, against particular mRNAs in the cell. Also, miRNAs have been proven to be involved in cell development, differentiation, proliferation, and apoptosis. More than 2000 miRNAs have been recognized in human cells, and these miRNAs adjust approximately one-third of all genes in human cells. Dysregulation of miRNA originated from abnormal DNA methylation patterns of the locus, cause to down-regulated or overexpression of miRNAs, and it may affect tumor formation or development of it. Breast cancer (BC) is the most commonly identified cancer, the most prevalent cancer (23%), and the second-leading (14%) mortality in all types of cancer in females. BC can be classified based on the status (+/−) of the hormone receptors, including estrogen receptor (ER), progesterone receptor (PR), and the Receptor tyrosine-protein kinase erbB-2 (ERBB2 or HER2). Currently, there are four main molecular subtypes of BC: luminal A, approximately 50–60 % of BCs; luminal B, 10–20 %; HER2 positive, 15–20 %, and 10–20 % considered Basal (triple-negative breast cancer (TNBC)) subtype. Aberrant expression of miR-145, miR-21, miR-10b, miR-125a, and miR-206 was detected by Stem-loop real-time RT-PCR in BC cases. Breast tumor formation and development may result from down-regulation of a tumor suppressor miRNA such as miR-145, miR-125a, and miR-206 and/or overexpression of an oncogenic miRNA such as miR-21 and miR-10b. MiR-125a, miR-206, miR-145, miR-21, and miR-10b are hugely predicted to be new tumor markers for the diagnosis and prognosis of BC. MiR-21 and miR-125a could play a part in the treatment of HER-2-positive breast cancer cells, while miR-145 and miR-206 could speed up the evolution of cure techniques for TNBC. To conclude, miRNAs will be presented as hopeful molecules to be used in the primary diagnosis, prognosis, and treatment of BC and battle as opposed to its developed drug resistance.Keywords: breast cancer, HER2 positive, miRNA, TNBC
Procedia PDF Downloads 1005616 Artificial Reproduction System and Imbalanced Dataset: A Mendelian Classification
Authors: Anita Kushwaha
Abstract:
We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining
Procedia PDF Downloads 2785615 An Approach Based on Statistics and Multi-Resolution Representation to Classify Mammograms
Authors: Nebi Gedik
Abstract:
One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).Keywords: wave atom transform, statistical features, multi-resolution representation, mammogram
Procedia PDF Downloads 2255614 Response of Buildings with Soil-Structure Interaction with Varying Soil Types
Authors: Shreya Thusoo, Karan Modi, Rajesh Kumar, Hitesh Madahar
Abstract:
Over the years, it has been extensively established that the practice of assuming a structure being fixed at base, leads to gross errors in evaluation of its overall response due to dynamic loadings and overestimations in design. The extent of these errors depends on a number of variables; soil type being one of the major factor. This paper studies the effect of Soil Structure Interaction (SSI) on multi-storey buildings with varying under-laying soil types after proper validation of the effect of SSI. Analysis for soft, stiff and very stiff base soils has been carried out, using a powerful Finite Element Method (FEM) software package ANSYS v14.5. Results lead to some very important conclusions regarding time period, deflection and acceleration responses.Keywords: dynamic response, multi-storey building, soil-structure interaction, varying soil types
Procedia PDF Downloads 4915613 Artificial Intelligent-Based Approaches for Task Offloading, Resource Allocation and Service Placement of Internet of Things Applications: State of the Art
Authors: Fatima Z. Cherhabil, Mammar Sedrati, Sonia-Sabrina Bendib
Abstract:
In order to support the continued growth, critical latency of IoT applications, and various obstacles of traditional data centers, mobile edge computing (MEC) has emerged as a promising solution that extends cloud data-processing and decision-making to edge devices. By adopting a MEC structure, IoT applications could be executed locally, on an edge server, different fog nodes, or distant cloud data centers. However, we are often faced with wanting to optimize conflicting criteria such as minimizing energy consumption of limited local capabilities (in terms of CPU, RAM, storage, bandwidth) of mobile edge devices and trying to keep high performance (reducing response time, increasing throughput and service availability) at the same time. Achieving one goal may affect the other, making task offloading (TO), resource allocation (RA), and service placement (SP) complex processes. It is a nontrivial multi-objective optimization problem to study the trade-off between conflicting criteria. The paper provides a survey on different TO, SP, and RA recent multi-objective optimization (MOO) approaches used in edge computing environments, particularly artificial intelligent (AI) ones, to satisfy various objectives, constraints, and dynamic conditions related to IoT applications.Keywords: mobile edge computing, multi-objective optimization, artificial intelligence approaches, task offloading, resource allocation, service placement
Procedia PDF Downloads 1205612 Unsteady Three-Dimensional Adaptive Spatial-Temporal Multi-Scale Direct Simulation Monte Carlo Solver to Simulate Rarefied Gas Flows in Micro/Nano Devices
Authors: Mirvat Shamseddine, Issam Lakkis
Abstract:
We present an efficient, three-dimensional parallel multi-scale Direct Simulation Monte Carlo (DSMC) algorithm for the simulation of unsteady rarefied gas flows in micro/nanosystems. The algorithm employs a novel spatiotemporal adaptivity scheme. The scheme performs a fully dynamic multi-level grid adaption based on the gradients of flow macro-parameters and an automatic temporal adaptation. The computational domain consists of a hierarchical octree-based Cartesian grid representation of the flow domain and a triangular mesh for the solid object surfaces. The hybrid mesh, combined with the spatiotemporal adaptivity scheme, allows for increased flexibility and efficient data management, rendering the framework suitable for efficient particle-tracing and dynamic grid refinement and coarsening. The parallel algorithm is optimized to run DSMC simulations of strongly unsteady, non-equilibrium flows over multiple cores. The presented method is validated by comparing with benchmark studies and then employed to improve the design of micro-scale hotwire thermal sensors in rarefied gas flows.Keywords: DSMC, oct-tree hierarchical grid, ray tracing, spatial-temporal adaptivity scheme, unsteady rarefied gas flows
Procedia PDF Downloads 3055611 MicroRNA Drivers of Resistance to Androgen Deprivation Therapy in Prostate Cancer
Authors: Philippa Saunders, Claire Fletcher
Abstract:
INTRODUCTION: Prostate cancer is the most prevalent malignancy affecting Western males. It is initially an androgen-dependent disease: androgens bind to the androgen receptor and drive the expression of genes that promote proliferation and evasion of apoptosis. Despite reduced androgen dependence in advanced prostate cancer, androgen receptor signaling remains a key driver of growth. Androgen deprivation therapy (ADT) is, therefore, a first-line treatment approach and works well initially, but resistance inevitably develops. Abiraterone and Enzalutamide are drugs widely used in ADT and are androgen synthesis and androgen receptor signaling inhibitors, respectively. The shortage of other treatment options means acquired resistance to these drugs is a major clinical problem. MicroRNAs (miRs) are important mediators of post-transcriptional gene regulation and show altered expression in cancer. Several have been linked to the development of resistance to ADT. Manipulation of such miRs may be a pathway to breakthrough treatments for advanced prostate cancer. This study aimed to validate ADT resistance-implicated miRs and their clinically relevant targets. MATERIAL AND METHOD: Small RNA-sequencing of Abiraterone- and Enzalutamide-resistant C42 prostate cancer cells identified subsets of miRs dysregulated as compared to parental cells. Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) was used to validate altered expression of candidate ADT resistance-implicated miRs 195-5p, 497-5p and 29a-5p in ADT-resistant and -responsive prostate cancer cell lines, patient-derived xenografts (PDXs) and primary prostate cancer explants. RESULTS AND DISCUSSION: This study suggests a possible role for miR-497-5p in the development of ADT resistance in prostate cancer. MiR-497-5p expression was increased in ADT-resistant versus ADT-responsive prostate cancer cells. Importantly, miR-497-5p expression was also increased in Enzalutamide-treated, castrated (ADT-mimicking) PDXs versus intact PDXs. MiR-195-5p was also elevated in ADT-resistant versus -responsive prostate cancer cells, while there was a drop in miR-29a-5p expression. Candidate clinically relevant targets of miR-497-5p in prostate cancer were identified by mining AGO-PAR-CLIP-seq data sets and may include AVL9 and FZD6. CONCLUSION: In summary, this study identified microRNAs that are implicated in prostate cancer resistance to androgen deprivation therapy and could represent novel therapeutic targets for advanced disease.Keywords: microRNA, androgen deprivation therapy, Enzalutamide, abiraterone, patient-derived xenograft
Procedia PDF Downloads 1495610 Cytotoxic Activity against Hepatocarcinoma and Cholangiocarcinoma Cells of Four Cathartic Herbal Medicines
Authors: Pranporn Kuropakornpong, Srisopa Ruangnoo, Arunporn Itharat
Abstract:
Liver cancer has the highest prevalence rate in the North and Northeast of Thailand. Four Thai medicinal plants such as resin of Ferula asafoetida Regel, latex of Aloe barbadensis Miller leaves, roots of Baliospermum manotanum, and latex of Garcinia hanburyi Hook are used in Thai traditional medicine as cathartic drug and detoxification in liver cancer patients. Thus, this research aimed to evaluate the cytotoxic activity of these plants against hepatocarcinoma (HepG2) and cholangiocarcinoma (KKU-M156) cells by SRB assay. These plants were macerated in 95% ethanol. The results showed that roots of Baliospermum manotanum and latex of Garcinia hanburyi Hook showed the strongest cytotoxicity against HepG2 (IC50 = 3.03+0.91 and 0.62+0.01µg/ml, respectively) and KKU-M156 (IC50 = 0.978+0.663 and 0.006+0.005 µg/ml, respectively). Latex of Garcinia hanburyi Hook also showed high cytotoxicity against normal cell line (IC50=8.86+0.31 µg/ml), and even though its selective values are high, dose of this herb should be limited.Keywords: cholangiocarcinoma, cytotoxic activity, Garcinia hanburyi Hook, hepatocarcinoma
Procedia PDF Downloads 4575609 Multi-Band, Polarization Insensitive, Wide Angle Receptive Metamaterial Absorber for Microwave Applications
Authors: Lincy Stephen, N. Yogesh, G. Vasantharajan, V. Subramanian
Abstract:
This paper presents the design and simulation of a five band metamaterial absorber at microwave frequencies. The absorber unit cell consists of squares and strips arranged as the top layer and a metallic ground plane as the bottom layer on a dielectric substrate. Simulation results show five near perfect absorption bands at 3.15 GHz, 7.15 GHz, 11.12 GHz, 13.87 GHz, and 16.85 GHz with absorption magnitudes 99.68%, 99.05%, 96.98%, 98.36% and 99.44% respectively. Further, the proposed absorber exhibits polarization insensitivity and wide angle receptivity. The surface current analysis is presented to explain the mechanism of absorption in the structure. With these preferable features, the proposed absorber can be excellent choice for potential applications such as electromagnetic interference (EMI) shielding, radar cross section reduction.Keywords: electromagnetic absorber, metamaterial, multi- band, polarization insensitive, wide angle receptive
Procedia PDF Downloads 3445608 Study into the Interactions of Primary Limbal Epithelial Stem Cells and HTCEPI Using Tissue Engineered Cornea
Authors: Masoud Sakhinia, Sajjad Ahmad
Abstract:
Introduction: Though knowledge of the compositional makeup and structure of the limbal niche has progressed exponentially during the past decade, much is yet to be understood. Identifying the precise profile and role of the stromal makeup which spans the ocular surface may inform researchers of the most optimum conditions needed to effectively expand LESCs in vitro, whilst preserving their differentiation status and phenotype. Limbal fibroblasts, as opposed to corneal fibroblasts are thought to form an important component of the microenvironment where LESCs reside. Methods: The corneal stroma was tissue engineered in vitro using both limbal and corneal fibroblasts embedded within a tissue engineered 3D collagen matrix. The effect of these two different fibroblasts on LESCs and hTCEpi corneal epithelial cell line were then subsequently determined using phase contrast microscopy, histolological analysis and PCR for specific stem cell markers. The study aimed to develop an in vitro model which could be used to determine whether limbal, as opposed to corneal fibroblasts, maintained the stem cell phenotype of LESCs and hTCEpi cell line. Results: Tissue culture analysis was inconclusive and required further quantitative analysis for remarks on cell proliferation within the varying stroma. Histological analysis of the tissue-engineered cornea showed a comparable structure to that of the human cornea, though with limited epithelial stratification. PCR results for epithelial cell markers of cells cultured on limbal fibroblasts showed reduced expression of CK3, a negative marker for LESC’s, whilst also exhibiting a relatively low expression level of P63, a marker for undifferentiated LESCs. Conclusion: We have shown the potential for the construction of a tissue engineered human cornea using a 3D collagen matrix and described some preliminary results in the analysis of the effects of varying stroma consisting of limbal and corneal fibroblasts, respectively, on the proliferation of stem cell phenotype of primary LESCs and hTCEpi corneal epithelial cells. Although no definitive marker exists to conclusively illustrate the presence of LESCs, the combination of positive and negative stem cell markers in our study were inconclusive. Though it is less traslational to the human corneal model, the use of conditioned medium from that of limbal and corneal fibroblasts may provide a more simple avenue. Moreover, combinations of extracellular matrices could be used as a surrogate in these culture models.Keywords: cornea, Limbal Stem Cells, tissue engineering, PCR
Procedia PDF Downloads 2845607 Delivery of Doxorubicin to Glioblastoma Multiforme Using Solid Lipid Nanoparticles with Surface Aprotinin and Melanotransferrin Antibody for Enhanced Chemotherapy
Authors: Yung-Chih Kuo, I-Hsuan Lee
Abstract:
Solid lipid nanoparticles (SLNs) conjugated with aprotinin (Apr) and melanotransferrin antibody (Anti-MTf) were used to carry doxorubicin (Dox) across the blood–brain barrier (BBB) for glioblastoma multiforme (GBM) chemotherapy. Dox-entrapped SLNs with grafted Apr and Anti-MTf (Apr-Anti-MTf-Dox-SLNs) were applied to a cultured monolayer comprising human brain-microvascular endothelial cells (HBMECs) with regulation of human astrocyte (HAs) and to a proliferated colony of U87MG cells. Based on the average particle diameter, zeta potential, entrapping efficiency of Dox, and grafting efficiency of Apr and Anti-MTf, we found that 40% (w/w) 1,2-dipalmitoyl-sn-glycero-3-phosphocholine in lipids were appropriate for fabricating Apr-Anti-MTf-Dox-SLNs. In addition, Apr-Anti-MTf-Dox-SLNs could prevent Dox from fast dissolution and did not induce a serious cytotoxicity to HBMECs and HAs when compared with free Dox. Moreover, the treatments with Apr-Anti-MTf-Dox-SLNs enhanced the ability of Dox to infuse the BBB and to inhibit the growth of GBM. The current Apr-Anti-MTf-Dox-SLNs can be a promising pharmacotherapeutic preparation to penetrate the BBB for malignant brain tumor treatment.Keywords: solid lipid nanoparticle, glioblastoma multiforme, blood–brain barrier, doxorubicin
Procedia PDF Downloads 3645606 Supplier Selection and Order Allocation Using a Stochastic Multi-Objective Programming Model and Genetic Algorithm
Authors: Rouhallah Bagheri, Morteza Mahmoudi, Hadi Moheb-Alizadeh
Abstract:
In this paper, we develop a supplier selection and order allocation multi-objective model in stochastic environment in which purchasing cost, percentage of delivered items with delay and percentage of rejected items provided by each supplier are supposed to be stochastic parameters following any arbitrary probability distribution. To do so, we use dependent chance programming (DCP) that maximizes probability of the event that total purchasing cost, total delivered items with delay and total rejected items are less than or equal to pre-determined values given by decision maker. After transforming the above mentioned stochastic multi-objective programming problem into a stochastic single objective problem using minimum deviation method, we apply a genetic algorithm to get the later single objective problem solved. The employed genetic algorithm performs a simulation process in order to calculate the stochastic objective function as its fitness function. At the end, we explore the impact of stochastic parameters on the given solution via a sensitivity analysis exploiting coefficient of variation. The results show that as stochastic parameters have greater coefficients of variation, the value of objective function in the stochastic single objective programming problem is worsened.Keywords: dependent chance programming, genetic algorithm, minimum deviation method, order allocation, supplier selection
Procedia PDF Downloads 2595605 Modeling Competition Between Subpopulations with Variable DNA Content in Resource-Limited Microenvironments
Authors: Parag Katira, Frederika Rentzeperis, Zuzanna Nowicka, Giada Fiandaca, Thomas Veith, Jack Farinhas, Noemi Andor
Abstract:
Resource limitations shape the outcome of competitions between genetically heterogeneous pre-malignant cells. One example of such heterogeneity is in the ploidy (DNA content) of pre-malignant cells. A whole-genome duplication (WGD) transforms a diploid cell into a tetraploid one and has been detected in 28-56% of human cancers. If a tetraploid subclone expands, it consistently does so early in tumor evolution, when cell density is still low, and competition for nutrients is comparatively weak – an observation confirmed for several tumor types. WGD+ cells need more resources to synthesize increasing amounts of DNA, RNA, and proteins. To quantify resource limitations and how they relate to ploidy, we performed a PAN cancer analysis of WGD, PET/CT, and MRI scans. Segmentation of >20 different organs from >900 PET/CT scans were performed with MOOSE. We observed a strong correlation between organ-wide population-average estimates of Oxygen and the average ploidy of cancers growing in the respective organ (Pearson R = 0.66; P= 0.001). In-vitro experiments using near-diploid and near-tetraploid lineages derived from a breast cancer cell line supported the hypothesis that DNA content influences Glucose- and Oxygen-dependent proliferation-, death- and migration rates. To model how subpopulations with variable DNA content compete in the resource-limited environment of the human brain, we developed a stochastic state-space model of the brain (S3MB). The model discretizes the brain into voxels, whereby the state of each voxel is defined by 8+ variables that are updated over time: stiffness, Oxygen, phosphate, glucose, vasculature, dead cells, migrating cells and proliferating cells of various DNA content, and treat conditions such as radiotherapy and chemotherapy. Well-established Fokker-Planck partial differential equations govern the distribution of resources and cells across voxels. We applied S3MB on sequencing and imaging data obtained from a primary GBM patient. We performed whole genome sequencing (WGS) of four surgical specimens collected during the 1ˢᵗ and 2ⁿᵈ surgeries of the GBM and used HATCHET to quantify its clonal composition and how it changes between the two surgeries. HATCHET identified two aneuploid subpopulations of ploidy 1.98 and 2.29, respectively. The low-ploidy clone was dominant at the time of the first surgery and became even more dominant upon recurrence. MRI images were available before and after each surgery and registered to MNI space. The S3MB domain was initiated from 4mm³ voxels of the MNI space. T1 post and T2 flair scan acquired after the 1ˢᵗ surgery informed tumor cell densities per voxel. Magnetic Resonance Elastography scans and PET/CT scans informed stiffness and Glucose access per voxel. We performed a parameter search to recapitulate the GBM’s tumor cell density and ploidy composition before the 2ⁿᵈ surgery. Results suggest that the high-ploidy subpopulation had a higher Glucose-dependent proliferation rate (0.70 vs. 0.49), but a lower Glucose-dependent death rate (0.47 vs. 1.42). These differences resulted in spatial differences in the distribution of the two subpopulations. Our results contribute to a better understanding of how genomics and microenvironments interact to shape cell fate decisions and could help pave the way to therapeutic strategies that mimic prognostically favorable environments.Keywords: tumor evolution, intra-tumor heterogeneity, whole-genome doubling, mathematical modeling
Procedia PDF Downloads 785604 Dietary Gluten and the Balance of Gut Microbiota in the Dextran Sulphate Sodium Induced Colitis Model
Authors: Austin Belfiori, Kevin Rinek, Zach Barcroft, Jennifer Berglind
Abstract:
Diet influences the composition of the gut microbiota and host's health. Disruption of the balance among the microbiota, epithelial cells, and resident immune cells in the intestine is involved in the pathogenesis of inflammatory bowel disease (IBD). To study the role of gut microbiota in intestinal inflammation, the microbiome of control mice (C57BL6) given a gluten-containing standard diet versus C57BL6 mice given the gluten-free (GF) feed (n=10 in each group) was examined. All mice received the 3% DSS for 5 days. Throughout the study, feces were collected and processed for DNA extraction and MiSeq Illumina sequencing of V4 region of bacterial 16S rRNA gene. Alpha and beta diversities and compositional differences at phylum and genus levels were determined in intestinal microbiota. The mice receiving the GF diet showed a significantly increased abundance of Firmicutes and a decrease of Bacteroides and Lactobacillus at phylum level. Therefore, the gluten free diet led to reductions in beneficial gut bacteria populations. These findings indicate a role of wheat gluten in dysbiosis of the intestinal microbiota.Keywords: gluten, colitis, microbiota, DSS, dextran sulphate sodium
Procedia PDF Downloads 2185603 Identification and Characterization of Nuclear Envelope Protein Interactions
Authors: Mohammed Hakim Jafferali, Balaje Vijayaraghavan, Ricardo A. Figueroa, Ellinor Crafoord, Veronica J. Larsson, Einar Hallberg, Santhosh Gudise
Abstract:
The nuclear envelope which surrounds the chromatin of eukaryotic cells contains more than a hundred transmembrane proteins. Mutations in some genes encoding nuclear envelope proteins give rise to human diseases including neurological disorders. The function of many nuclear envelope proteins is not well established. This is partly because nuclear envelope proteins and their interactions are difficult to study due to the inherent resistance to extraction of nuclear envelope proteins. We have developed a novel method called MCLIP, to identify interacting partners of nuclear envelope proteins in live cells. Using MCLIP, we found three new binding partners of the inner nuclear membrane protein Samp1: the intermediate filament protein Lamin B1, the LINC complex protein Sun1 and the G-protein Ran. Furthermore, using in vitro studies, we show that Samp1 binds both Emerin and Ran directly. We have also studied the interaction between Samp1 and Ran in detail. The results show that the Samp1 binds stronger to RanGTP than RanGDP. Samp1 is the first transmembrane protein known to bind Ran and it is tempting to speculate that Samp1 may provide local binding sites for RanGTP at membranes.Keywords: MCLIP, nuclear envelope, ran, Samp1
Procedia PDF Downloads 359