Search results for: neural progentor cells
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4927

Search results for: neural progentor cells

4207 Discriminant Function Based on Circulating Tumor Cells for Accurate Diagnosis of Metastatic Breast Cancer

Authors: Hatem A. El-Mezayen, Ahmed Abdelmajeed, Fatehya Metwally, Usama Elsaly, Salwa Atef

Abstract:

Tumor metastasis involves the dissemination of malignant cells into the basement membrane and vascular system contributes to the circulating pool of these markers. In this context our aim has been focused on development of a non-invasive. Circulating tumor cells (CTCs) represent a unique liquid biopsy carrying comprehensive biological information of the primary tumor. Herein, we sought to develop a novel score based on the combination of the most significant CTCs biomarkers with and routine laboratory tests for accurate detection of metastatic breast cancer. Methods: Cytokeratin 18 (CK18), Cytokeratin 19 (CK19), and CA15.3 were assayed in metastatic breast cancer (MBC) patients (75), non-MBC patients (50) and healthy control (20). Results: Areas under receiving operating curve (AUCs) were calculated and used for construction on novel score. A novel score named MBC-CTCs = CA15.3 (U/L) × 0.08 + CK 18 % × 2.9 + CK19 × 3.1– 510. That function correctly classified 87% of metastatic breast cancer at cut-off value = 0.55. (i.e great than 0.55 indicates patients with metastatic breast cancer and less than 0.55 indicates patients with non-metastatic breast cancer). Conclusion: MBC-CTCs is a novel, non-invasive and simple can applied to discriminate patients with metastatic breast cancer.

Keywords: metastatic breast cancer, circulating tumor cells, cytokeratin, EpiCam

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4206 Study of a Cross-Flow Membrane to a Kidney Encapsulation Engineering Structures for Immunosuppression Filter

Authors: Sihyun Chae, Ryoto Arai, Waldo Concepcion, Paula Popescu

Abstract:

The kidneys perform an important role in the human hormones that regulate the blood pressure, produce an active form of vitamin D and control the production of red blood cells. Kidney disease can cause health problems, such as heart disease. Also, increase the chance of having a stroke or heart attack. There are mainly to types of treatments for kidney disease, dialysis, and kidney transplant. For a better quality of life, the kidney transplant is desirable. However, kidney transplant can cause antibody reaction and patients’ body would be attacked by immune system of their own. For solving that issue, patients with transplanted kidney always take immunosuppressive drugs which can hurt kidney as side effects. Patients willing to do a kidney transplant have a waiting time of 3.6 years in average searching to find an appropriate kidney, considering there are almost 96,380 patients waiting for kidney transplant. There is a promising method to solve these issues: bioartificial kidney. Our membrane is specially designed with unique perforations capable to filter the blood cells separating the white blood cells from red blood cells. White blood cells will not pass through the encapsulated kidney preventing the immune system to attack the new organ and eliminating the need of a matching donor. It is possible to construct life-time long encapsulation without needing pumps or a power supply on the cell’s separation method preventing futures surgeries due the Cross-Channel Flow inside the device. This technology allows the possibility to use an animal kidney, prevent cancer cells to spread through the body, arm and leg transplants in the future. This project aims to improve the quality of life of patients with kidney disease.

Keywords: kidney encapsulation, immunosuppression filter, leukocyte filter, leukocyte

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4205 Uncertainty Estimation in Neural Networks through Transfer Learning

Authors: Ashish James, Anusha James

Abstract:

The impressive predictive performance of deep learning techniques on a wide range of tasks has led to its widespread use. Estimating the confidence of these predictions is paramount for improving the safety and reliability of such systems. However, the uncertainty estimates provided by neural networks (NNs) tend to be overconfident and unreasonable. Ensemble of NNs typically produce good predictions but uncertainty estimates tend to be inconsistent. Inspired by these, this paper presents a framework that can quantitatively estimate the uncertainties by leveraging the advances in transfer learning through slight modification to the existing training pipelines. This promising algorithm is developed with an intention of deployment in real world problems which already boast a good predictive performance by reusing those pretrained models. The idea is to capture the behavior of the trained NNs for the base task by augmenting it with the uncertainty estimates from a supplementary network. A series of experiments with known and unknown distributions show that the proposed approach produces well calibrated uncertainty estimates with high quality predictions.

Keywords: uncertainty estimation, neural networks, transfer learning, regression

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4204 Co-Culture with Murine Stromal Cells Enhances the In-vitro Expansion of Hematopoietic Stem Cells in Response to Low Concentrations of Trans-Resveratrol

Authors: Mariyah Poonawala, Selvan Ravindran, Anuradha Vaidya

Abstract:

Despite much progress in understanding the regulatory factors and cytokines that support the maturation of the various cell lineages of the hematopoietic system, factors that govern the self-renewal and proliferation of hematopoietic stem cells (HSCs) is still a grey area of research. Hematopoietic stem cell transplantation (HSCT) has evolved over the years and gained tremendous importance in the treatment of both malignant and non-malignant diseases. However, factors such as graft rejection and multiple organ failure have challenged HSCT from time to time, underscoring the urgent need for development of milder processes for successful hematopoietic transplantation. An emerging concept in the field of stem cell biology states that the interactions between the bone-marrow micro-environment and the hematopoietic stem and progenitor cells is essential for regulation, maintenance, commitment and proliferation of stem cells. Understanding the role of mesenchymal stromal cells in modulating the functionality of HSCs is, therefore, an important area of research. Trans-resveratrol has been extensively studied for its various properties to combat and prevent cancer, diabetes and cardiovascular diseases etc. The aim of the present study was to understand the effect of trans-resveratrol on HSCs using single and co-culture systems. We have used KG1a cells since it is a well accepted hematopoietic stem cell model system. Our preliminary experiments showed that low concentrations of trans-resveratrol stimulated the HSCs to undergo proliferation whereas high concentrations of trans-resveratrol did not stimulate the cells to proliferate. We used a murine fibroblast cell line, M210B4, as a stromal feeder layer. On culturing the KG1a cells with M210B4 cells, we observed that the stimulatory as well as inhibitory effects of trans-resveratrol at low and high concentrations respectively, were enhanced. Our further experiments showed that low concentration of trans-resveratrol reduced the generation of reactive oxygen species (ROS) and nitric oxide (NO) whereas high concentrations increased the oxidative stress in KG1a cells. We speculated that perhaps the oxidative stress was imposing inhibitory effects at high concentration and the same was confirmed by performing an apoptotic assay. Furthermore, cell cycle analysis and growth kinetic experiments provided evidence that low concentration of trans-resveratrol reduced the doubling time of the cells. Our hypothesis is that perhaps at low concentration of trans-resveratrol the cells get pushed into the G0/G1 phase and re-enter the cell cycle resulting in their proliferation, whereas at high concentration the cells are perhaps arrested at G2/M phase or at cytokinesis and therefore undergo apoptosis. Liquid Chromatography-Quantitative-Time of Flight–Mass Spectroscopy (LC-Q-TOF MS) analyses indicated the presence of trans-resveratrol and its metabolite(s) in the supernatant of the co-cultured cells incubated with high concentration of trans-resveratrol. We conjecture that perhaps the metabolites of trans-resveratrol are responsible for the apoptosis observed at the high concentration. Our findings may shed light on the unsolved problems in the in vitro expansion of stem cells and may have implications in the ex vivo manipulation of HSCs for therapeutic purposes.

Keywords: co-culture system, hematopoietic micro-environment, KG1a cell line, M210B4 cell line, trans-resveratrol

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4203 Design of a Cooperative Neural Network, Particle Swarm Optimization (PSO) and Fuzzy Based Tracking Control for a Tilt Rotor Unmanned Aerial Vehicle

Authors: Mostafa Mjahed

Abstract:

Tilt Rotor UAVs (Unmanned Aerial Vehicles) are naturally unstable and difficult to maneuver. The purpose of this paper is to design controllers for the stabilization and trajectory tracking of this type of UAV. To this end, artificial intelligence methods have been exploited. First, the dynamics of this UAV was modeled using the Lagrange-Euler method. The conventional method based on Proportional, Integral and Derivative (PID) control was applied by decoupling the different flight modes. To improve stability and trajectory tracking of the Tilt Rotor, the fuzzy approach and the technique of multilayer neural networks (NN) has been used. Thus, Fuzzy Proportional Integral and Derivative (FPID) and Neural Network-based Proportional Integral and Derivative controllers (NNPID) have been developed. The meta-heuristic approach based on Particle Swarm Optimization (PSO) method allowed adjusting the setting parameters of NNPID controller, giving us an improved NNPID-PSO controller. Simulation results under the Matlab environment show the efficiency of the approaches adopted. Besides, the Tilt Rotor UAV has become stable and follows different types of trajectories with acceptable precision. The Fuzzy, NN and NN-PSO-based approaches demonstrated their robustness because the presence of the disturbances did not alter the stability or the trajectory tracking of the Tilt Rotor UAV.

Keywords: neural network, fuzzy logic, PSO, PID, trajectory tracking, tilt-rotor UAV

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4202 Performance of Neural Networks vs. Radial Basis Functions When Forming a Metamodel for Residential Buildings

Authors: Philip Symonds, Jon Taylor, Zaid Chalabi, Michael Davies

Abstract:

With the world climate projected to warm and major cities in developing countries becoming increasingly populated and polluted, governments are tasked with the problem of overheating and air quality in residential buildings. This paper presents the development of an adaptable model of these risks. Simulations are performed using the EnergyPlus building physics software. An accurate metamodel is formed by randomly sampling building input parameters and training on the outputs of EnergyPlus simulations. Metamodels are used to vastly reduce the amount of computation time required when performing optimisation and sensitivity analyses. Neural Networks (NNs) are compared to a Radial Basis Function (RBF) algorithm when forming a metamodel. These techniques were implemented using the PyBrain and scikit-learn python libraries, respectively. NNs are shown to perform around 15% better than RBFs when estimating overheating and air pollution metrics modelled by EnergyPlus.

Keywords: neural networks, radial basis functions, metamodelling, python machine learning libraries

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4201 Comprehending the Relationship between the Red Blood Cells of a Protein 4.1 -/- Patient and Those of Healthy Controls: A Comprehensive Analysis of Tandem Mass Spectrometry Data

Authors: Ahmed M. Hjazi, Bader M. Hjazi

Abstract:

Protein 4.1 is a crucial component of complex interactions between the cytoskeleton and other junctional complex proteins. When the gene encoding this protein is altered, resulting in reduced expression, or when the protein is absent, the red cell undergoes a significant structural change. This research aims to achieve a deeper comprehension of the biochemical effects of red cell protein deficiency. A Tandem Mass Spectrometry Analysis (TMT-MS/MS) of patient cells lacking protein 4.1 compared to three healthy controls was achieved by the Proteomics Institute of the University of Bristol. The SDS-PAGE and Western blotting were utilized on the original patient sample and controls to partially confirm TMT MS/MS data analysis of the protein-4.1-deficient cells. Compared to healthy controls, protein levels in samples lacking protein 4.1 had a significantly higher concentration of proteins that probably originated from reticulocytes. This could occur if the patient has an elevated reticulocyte count. The increase in chaperone and reticulocyte-associated proteins was most notable in this study. This may result from elevated quantities of reticulocytes in patients with hereditary elliptocytosis.

Keywords: hereditary elliptocytosis, protein 4.1, red cells, tandem mass spectrometry data.

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4200 Continuum-Based Modelling Approaches for Cell Mechanics

Authors: Yogesh D. Bansod, Jiri Bursa

Abstract:

The quantitative study of cell mechanics is of paramount interest since it regulates the behavior of the living cells in response to the myriad of extracellular and intracellular mechanical stimuli. The novel experimental techniques together with robust computational approaches have given rise to new theories and models, which describe cell mechanics as a combination of biomechanical and biochemical processes. This review paper encapsulates the existing continuum-based computational approaches that have been developed for interpreting the mechanical responses of living cells under different loading and boundary conditions. The salient features and drawbacks of each model are discussed from both structural and biological points of view. This discussion can contribute to the development of even more precise and realistic computational models of cell mechanics based on continuum approaches or on their combination with microstructural approaches, which in turn may provide a better understanding of mechanotransduction in living cells.

Keywords: cell mechanics, computational models, continuum approach, mechanical models

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4199 Optimization of Laser Doping Selective Emitter for Silicon Solar Cells

Authors: Meziani Samir, Moussi Abderrahmane, Chaouchi Sofiane, Guendouzi Awatif, Djema Oussama

Abstract:

Laser doping has a large potential for integration into silicon solar cell technologies. The ability to process local, heavily diffused regions in a self-aligned manner can greatly simplify processing sequences for the fabrication of selective emitter. The choice of laser parameters for a laser doping process with 532nm is investigated. Solid state lasers with different power and speed were used for laser doping. In this work, the aim is the formation of selective emitter solar cells with a reduced number of technological steps. In order to have a highly doped localized emitter region, we used a 532 nm laser doping. Note that this region will receive the metallization of the Ag grid by screen printing. For this, we use SOLIDWORKS software to design a single type of pattern for square silicon cells. Sheet resistances, phosphorus doping concentration and silicon bulk lifetimes of irradiated samples are presented. Additionally, secondary ion mass spectroscopy (SIMS) profiles of the laser processed samples were acquired. Scanning electron microscope and optical microscope images of laser processed surfaces at different parameters are shown and compared.

Keywords: laser doping, selective emitter, silicon, solar cells

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4198 Role of Interleukin 6 on Cell Differentiations in Stem Cells Isolated from Human Exfoliated Deciduous Teeth

Authors: Nunthawan Nowwarote, Waleerat Sukarawan, Prasit Pavasant, Thanaphum Osathanon

Abstract:

Interleukin 6 (IL-6) is a multifunctional cytokine, regulating various biological responses in several tissues. A Recent study shows that IL-6 plays a role in stemness maintenance in stem cells isolated from human exfoliated deciduous teeth (SHEDs). However, the role of IL-6 on cell differentiation in SHEDs remains unknown. The present study investigated the effect of IL-6 on SHEDs differentiation. Cells were isolated from dental pulp tissues of human deciduous teeth. Flow cytometry was used to determined mesenchymal stem cell marker expression, and the multipotential differentiation (osteogenic, adipogenic and neurogenic lineage ) was also determined. The mRNA was determined using real-time quantitative polymerase chain reaction, and the phenotypes were confirmed by chemical and immunofluorescence staining. Results demonstrated that SHEDs expressed CD44, CD73, CD90, CD105 but not CD45. Further, the up-regulation of osteogenic, adipogenic and neurogenic marker genes was observed upon maintaining cells in osteogenic, adipogenic and neurogenic induction medium, respectively. The addition of IL-6 induced osteogenic by up-regulated osteogenic marker gene also increased in vitro mineralization. Under neurogenic medium supplement with IL-6, up-regulated neurogenic marker. Whereas, an addition of IL-6 attenuated adipogenic differentiation by SHEDs. In conclusion, this evidence implies that IL-6 may participate in cells differentiation ability of SHEDs.

Keywords: SHEDs, IL-6, cell differentiations, dental pulp

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4197 Phytopathology Prediction in Dry Soil Using Artificial Neural Networks Modeling

Authors: F. Allag, S. Bouharati, M. Belmahdi, R. Zegadi

Abstract:

The rapid expansion of deserts in recent decades as a result of human actions combined with climatic changes has highlighted the necessity to understand biological processes in arid environments. Whereas physical processes and the biology of flora and fauna have been relatively well studied in marginally used arid areas, knowledge of desert soil micro-organisms remains fragmentary. The objective of this study is to conduct a diversity analysis of bacterial communities in unvegetated arid soils. Several biological phenomena in hot deserts related to microbial populations and the potential use of micro-organisms for restoring hot desert environments. Dry land ecosystems have a highly heterogeneous distribution of resources, with greater nutrient concentrations and microbial densities occurring in vegetated than in bare soils. In this work, we found it useful to use techniques of artificial intelligence in their treatment especially artificial neural networks (ANN). The use of the ANN model, demonstrate his capability for addressing the complex problems of uncertainty data.

Keywords: desert soil, climatic changes, bacteria, vegetation, artificial neural networks

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4196 Estimation of Fouling in a Cross-Flow Heat Exchanger Using Artificial Neural Network Approach

Authors: Rania Jradi, Christophe Marvillet, Mohamed Razak Jeday

Abstract:

One of the most frequently encountered problems in industrial heat exchangers is fouling, which degrades the thermal and hydraulic performances of these types of equipment, leading thus to failure if undetected. And it occurs due to the accumulation of undesired material on the heat transfer surface. So, it is necessary to know about the heat exchanger fouling dynamics to plan mitigation strategies, ensuring a sustainable and safe operation. This paper proposes an Artificial Neural Network (ANN) approach to estimate the fouling resistance in a cross-flow heat exchanger by the collection of the operating data of the phosphoric acid concentration loop. The operating data of 361 was used to validate the proposed model. The ANN attains AARD= 0.048%, MSE= 1.811x10⁻¹¹, RMSE= 4.256x 10⁻⁶ and r²=99.5 % of accuracy which confirms that it is a credible and valuable approach for industrialists and technologists who are faced with the drawbacks of fouling in heat exchangers.

Keywords: cross-flow heat exchanger, fouling, estimation, phosphoric acid concentration loop, artificial neural network approach

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4195 Neural Network Based Decision Trees Using Machine Learning for Alzheimer's Diagnosis

Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, S. Meenakshi Sundaram

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Alzheimer’s disease is one of the prevalent kind of ailment, expected for impudent reconciliation or an effectual therapy is to be accredited hitherto. Probable detonation of patients in the upcoming years, and consequently an enormous deal of apprehension in early discovery of the disorder, this will conceivably chaperon to enhanced healing outcomes. Complex impetuosity of the brain is an observant symbolic of the disease and a unique recognition of genetic sign of the disease. Machine learning alongside deep learning and decision tree reinforces the aptitude to absorb characteristics from multi-dimensional data’s and thus simplifies automatic classification of Alzheimer’s disease. Susceptible testing was prophesied and realized in training the prospect of Alzheimer’s disease classification built on machine learning advances. It was shrewd that the decision trees trained with deep neural network fashioned the excellent results parallel to related pattern classification.

Keywords: Alzheimer's diagnosis, decision trees, deep neural network, machine learning, pattern classification

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4194 Identification of Genomic Mutations in Prostate Cancer and Cancer Stem Cells By Single Cell RNAseq Analysis

Authors: Wen-Yang Hu, Ranli Lu, Mark Maienschein-Cline, Danping Hu, Larisa Nonn, Toshi Shioda, Gail S. Prins

Abstract:

Background: Genetic mutations are highly associated with increased prostate cancer risk. In addition to whole genome sequencing, somatic mutations can be identified by aligning transcriptome sequences to the human genome. Here we analyzed bulk RNAseq and single cell RNAseq data of human prostate cancer cells and their matched non-cancer cells in benign regions from 4 individual patients. Methods: Sequencing raw reads were aligned to the reference genome hg38 using STAR. Variants were annotated using Annovar with respect to overlap gene annotation information, effect on gene and protein sequence, and SIFT annotation of nonsynonymous variant effect. We determined cancer-specific novel alleles by comparing variant calls in cancer cells to matched benign cells from the same individual by selecting unique alleles that were only detected in the cancer samples. Results: In bulk RNAseq data from 3 patients, the most common variants were the noncoding mutations at UTR3/UTR5, and the major variant types were single-nucleotide polymorphisms (SNP) including frameshift mutations. C>T transversion is the most frequently presented substitution of SNP. A total of 222 genes carrying unique exonic or UTR variants were revealed in cancer cells across 3 patients but not in benign cells. Among them, transcriptome levels of 7 genes (CITED2, YOD1, MCM4, HNRNPA2B1, KIF20B, DPYSL2, NR4A1) were significantly up or down regulated in cancer stem cells. Out of the 222 commonly mutated genes in cancer, 19 have nonsynonymous variants and 11 are damaged genes with variants including SIFT, frameshifts, stop gain/loss, and insertions/deletions (indels). Two damaged genes, activating transcription factor 6 (ATF6) and histone demethylase KDM3A are of particular interest; the former is a survival factor for certain cancer cells while the later positively activates androgen receptor target genes in prostate cancer. Further, single cell RNAseq data of cancer cells and their matched non-cancer benign cells from both primary 2D and 3D tumoroid cultures were analyzed. Similar to the bulk RNAseq data, single cell RNAseq in cancer demonstrated that the exonic mutations are less common than noncoding variants, with SNPs including frameshift mutations the most frequently presented types in cancer. Compared to cancer stem cell enriched-3D tumoroids, 2D cancer cells carried 3-times higher variants, 8-times more coding mutations and 10-times more nonsynonymous SNP. Finally, in both 2D primary and 3D tumoroid cultures, cancer stem cells exhibited fewer coding mutations and noncoding SNP or insertions/deletions than non-stem cancer cells. Summary: Our study demonstrates the usefulness of bulk and single cell RNAseaq data in identifying somatic mutations in prostate cancer, providing an alternative method in screening candidate genes for prostate cancer diagnosis and potential therapeutic targets. Cancer stem cells carry fewer somatic mutations than non-stem cancer cells due to their inherited immortal stand DNA from parental stem cells that explains their long-lived characteristics.

Keywords: prostate cancer, stem cell, genomic mutation, RNAseq

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4193 The Use of Layered Neural Networks for Classifying Hierarchical Scientific Fields of Study

Authors: Colin Smith, Linsey S Passarella

Abstract:

Due to the proliferation and decentralized nature of academic publication, no widely accepted scheme exists for organizing papers by their scientific field of study (FoS) to the author’s best knowledge. While many academic journals require author provided keywords for papers, these keywords range wildly in scope and are not consistent across papers, journals, or field domains, necessitating alternative approaches to paper classification. Past attempts to perform field-of-study (FoS) classification on scientific texts have largely used a-hierarchical FoS schemas or ignored the schema’s inherently hierarchical structure, e.g. by compressing the structure into a single layer for multi-label classification. In this paper, we introduce an application of a Layered Neural Network (LNN) to the problem of performing supervised hierarchical classification of scientific fields of study (FoS) on research papers. In this approach, paper embeddings from a pretrained language model are fed into a top-down LNN. Beginning with a single neural network (NN) for the highest layer of the class hierarchy, each node uses a separate local NN to classify the subsequent subfield child node(s) for an input embedding of concatenated paper titles and abstracts. We compare our LNN-FOS method to other recent machine learning methods using the Microsoft Academic Graph (MAG) FoS hierarchy and find that the LNN-FOS offers increased classification accuracy at each FoS hierarchical level.

Keywords: hierarchical classification, layer neural network, scientific field of study, scientific taxonomy

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4192 Benign Osteoblastoma of the Mandible Resection and Replacement of the Defects with Decellularized Cattle Bone Scaffold with Mesenchymal Bone Marrow Stem Cells

Authors: K. Mardaleishvili, G. Loladze, G. Shatirishivili, D. Chakhunashvili, A. Vishnevskaya, Z. Kakabadze

Abstract:

Benign osteoblastoma is a benign tumor of the bone, usually affecting the vertebrae and long tubular bones. It is a rarely seen tumor of the facial bones. The authors present a case of a 28-year-old male patient with a tumor in mandibular body. The lesion was radically resected and histological analysis of the specimen demonstrated features typical of a benign osteoblastoma. The defect of the jaw was reconstructed with titanium implants and decellularized and lyophilized cattle bone matrix with mesenchymal bone marrow stem cells transplantation. This presentation describes the procedures for rehabilitating a patient with decellularized bone scaffold in the region of the face, recovering the facial contours and esthetics of the patient.

Keywords: facial bones, osteoblastoma, stem cells, transplantation

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4191 Using Lysosomal Immunogenic Cell Death to Target Breast Cancer via Xanthine Oxidase/Micro-Antibody Fusion Protein

Authors: Iulianna Taritsa, Kuldeep Neote, Eric Fossel

Abstract:

Lysosome-induced immunogenic cell death (LIICD) is a powerful mechanism of targeting cancer cells that kills circulating malignant cells and primes the host’s immune cells against future remission. Current immunotherapies for cancer are limited in preventing recurrence – a gap that can be bridged by training the immune system to recognize cancer neoantigens. Lysosomal leakage can be induced therapeutically to traffic antigens from dying cells to dendritic cells, which can later present those tumorigenic antigens to T cells. Previous research has shown that oxidative agents administered in the tumor microenvironment can initiate LIICD. We generated a fusion protein between an oxidative agent known as xanthine oxidase (XO) and a mini-antibody specific for EGFR/HER2-sensitive breast tumor cells. The anti-EGFR single domain antibody fragment is uniquely sourced from llama, which is functional without the presence of a light chain. These llama micro-antibodies have been shown to be better able to penetrate tissues and have improved physicochemical stability as compared to traditional monoclonal antibodies. We demonstrate that the fusion protein created is stable and can induce early markers of immunogenic cell death in an in vitro human breast cancer cell line (SkBr3). Specifically, we measured overall cell death, as well as surface-expressed calreticulin, extracellular ATP release, and HMGB1 production. These markers are consensus indicators of ICD. Flow cytometry, luminescence assays, and ELISA were used respectively to quantify biomarker levels between treated versus untreated cells. We also included a positive control group of SkBr3 cells dosed with doxorubicin (a known inducer of LIICD) and a negative control dosed with cisplatin (a known inducer of cell death, but not of the immunogenic variety). We looked at each marker at various time points after cancer cells were treated with the XO/antibody fusion protein, doxorubicin, and cisplatin. Upregulated biomarkers after treatment with the fusion protein indicate an immunogenic response. We thus show the potential for this fusion protein to induce an anticancer effect paired with an adaptive immune response against EGFR/HER2+ cells. Our research in human cell lines here provides evidence for the success of the same therapeutic method for patients and serves as the gateway to developing a new treatment approach against breast cancer.

Keywords: apoptosis, breast cancer, immunogenic cell death, lysosome

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4190 Lucilia Sericata Netrin-A: Secreted by Salivary Gland Larvae as a Potential to Neuroregeneration

Authors: Hamzeh Alipour, Masoumeh Bagheri, Tahereh Karamzadeh, Abbasali Raz, Kourosh Azizi

Abstract:

Netrin-A, a protein identified for conducting commissural axons, has a similar role in angiogenesis. In addition, studies have shown that one of the netrin-A receptors is expressed in the growing cells of small capillaries. It will be interesting to study this new group of molecules because their role in wound healing will become clearer in the future due to angiogenesis. The greenbottle blowfly Luciliasericata (L. sericata) larvae are increasingly used in maggot therapy of chronic wounds. This aim of this was the identification of moleculareatures of Netrin-A in L. sericata larvae. Larvae were reared under standard maggotarium conditions. The nucleic acid sequence of L. sericataNetrin-A (LSN-A) was then identified using Rapid Amplification of cDNA Ends (RACE) and Rapid Amplification of Genomic Ends (RAGE). Parts of the Netrin-A gene, including the middle, 3′-, and 5′-ends were identified, TA cloned in pTG19 plasmid, and transferred into DH5ɑ Escherichia coli. Each part was sequenced and assembled using SeqMan software. This gene structure was further subjected to in silico analysis. The DNA of LSN-A was identified to be 2407 bp, while its mRNA sequence was recognized as 2115 bp by Oligo0.7 software. It translated the Netrin-A protein with 704 amino acid residues. Its molecular weight is estimated to be 78.6 kDa. The 3-D structure ofNetrin-A drawn by SWISS-MODEL revealed its similarity to the Netrin-1 of humans with 66.8% identity. The LSN-A protein conduces to repair the myelin membrane in neuronal cells. Ultimately, it can be an effective candidate in neural regeneration and wound healing. Furthermore, our next attempt is to deplore recombinant proteins for use in medical sciences.

Keywords: maggot therapy, netrin-A, RACE, RAGE, lucilia sericata

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4189 Defective Autophagy Disturbs Neural Migration and Network Activity in hiPSC-Derived Cockayne Syndrome B Disease Models

Authors: Julia Kapr, Andrea Rossi, Haribaskar Ramachandran, Marius Pollet, Ilka Egger, Selina Dangeleit, Katharina Koch, Jean Krutmann, Ellen Fritsche

Abstract:

It is widely acknowledged that animal models do not always represent human disease. Especially human brain development is difficult to model in animals due to a variety of structural and functional species-specificities. This causes significant discrepancies between predicted and apparent drug efficacies in clinical trials and their subsequent failure. Emerging alternatives based on 3D in vitro approaches, such as human brain spheres or organoids, may in the future reduce and ultimately replace animal models. Here, we present a human induced pluripotent stem cell (hiPSC)-based 3D neural in a vitro disease model for the Cockayne Syndrome B (CSB). CSB is a rare hereditary disease and is accompanied by severe neurologic defects, such as microcephaly, ataxia and intellectual disability, with currently no treatment options. Therefore, the aim of this study is to investigate the molecular and cellular defects found in neural hiPSC-derived CSB models. Understanding the underlying pathology of CSB enables the development of treatment options. The two CSB models used in this study comprise a patient-derived hiPSC line and its isogenic control as well as a CSB-deficient cell line based on a healthy hiPSC line (IMR90-4) background thereby excluding genetic background-related effects. Neurally induced and differentiated brain sphere cultures were characterized via RNA Sequencing, western blot (WB), immunocytochemistry (ICC) and multielectrode arrays (MEAs). CSB-deficiency leads to an altered gene expression of markers for autophagy, focal adhesion and neural network formation. Cell migration was significantly reduced and electrical activity was significantly increased in the disease cell lines. These data hint that the cellular pathologies is possibly underlying CSB. By induction of autophagy, the migration phenotype could be partially rescued, suggesting a crucial role of disturbed autophagy in defective neural migration of the disease lines. Altered autophagy may also lead to inefficient mitophagy. Accordingly, disease cell lines were shown to have a lower mitochondrial base activity and a higher susceptibility to mitochondrial stress induced by rotenone. Since mitochondria play an important role in neurotransmitter cycling, we suggest that defective mitochondria may lead to altered electrical activity in the disease cell lines. Failure to clear the defective mitochondria by mitophagy and thus missing initiation cues for new mitochondrial production could potentiate this problem. With our data, we aim at establishing a disease adverse outcome pathway (AOP), thereby adding to the in-depth understanding of this multi-faced disorder and subsequently contributing to alternative drug development.

Keywords: autophagy, disease modeling, in vitro, pluripotent stem cells

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4188 RBF Modelling and Optimization Control for Semi-Batch Reactors

Authors: Magdi M. Nabi, Ding-Li Yu

Abstract:

This paper presents a neural network based model predictive control (MPC) strategy to control a strongly exothermic reaction with complicated nonlinear kinetics given by Chylla-Haase polymerization reactor that requires a very precise temperature control to maintain product uniformity. In the benchmark scenario, the operation of the reactor must be guaranteed under various disturbing influences, e.g., changing ambient temperatures or impurity of the monomer. Such a process usually controlled by conventional cascade control, it provides a robust operation, but often lacks accuracy concerning the required strict temperature tolerances. The predictive control strategy based on the RBF neural model is applied to solve this problem to achieve set-point tracking of the reactor temperature against disturbances. The result shows that the RBF based model predictive control gives reliable result in the presence of some disturbances and keeps the reactor temperature within a tight tolerance range around the desired reaction temperature.

Keywords: Chylla-Haase reactor, RBF neural network modelling, model predictive control, semi-batch reactors

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4187 Electrospun Nanofibrous Scaffolds Modified with Collagen-I and Fibronectin with LX-2 Cells to Study Liver Fibrosis in vitro

Authors: Prativa Das, Lay Poh Tan

Abstract:

Three-dimensional microenvironment is a need to study the event cascades of liver fibrosis in vitro. Electrospun nanofibers modified with essential extracellular matrix proteins can closely mimic the random fibrous structure of native liver extracellular matrix (ECM). In this study, we fabricate a series of 3D electrospun scaffolds by wet electrospinning process modified with different ratios of collagen-I to fibronectin to achieve optimized distribution of these two ECM proteins on the fiber surface. A ratio of 3:1 of collagen-I to fibronectin was found to be optimum for surface modification of electrospun poly(lactic-co-glycolic acid) (PLGA) fibers by chemisorption process. In 3:1 collagen-I to fibronectin modified scaffolds the total protein content increased by ~2 fold compared to collagen-I modified and ~1.5 fold compared to 1:1/9:1 collagen-I to fibronectin modified scaffolds. We have cultured LX-2 cells on this scaffold over 14 days and found that LX-2 cells acquired more quiescent phenotype throughout the culture period and shown significantly lower expression of alpha smooth muscle actin and collagen-I. Thus, this system can be used as a model to study liver fibrosis by using different fibrogenic mediators in vitro.

Keywords: electrospinning, collagen-I and fibronectin, surface modification of fiber, LX-2 cells, liver fibrosis

Procedia PDF Downloads 126
4186 Detecting and Secluding Route Modifiers by Neural Network Approach in Wireless Sensor Networks

Authors: C. N. Vanitha, M. Usha

Abstract:

In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.

Keywords: neural networks, pattern learning, security, wireless sensor networks

Procedia PDF Downloads 404
4185 Effect of Locally Injected Mesenchymal Stem Cells on Bone Regeneration of Rat Calvaria Defects

Authors: Gileade P. Freitas, Helena B. Lopes, Alann T. P. Souza, Paula G. F. P. Oliveira, Adriana L. G. Almeida, Paulo G. Coelho, Marcio M. Beloti, Adalberto L. Rosa

Abstract:

Bone tissue presents great capacity to regenerate when injured by trauma, infectious processes, or neoplasia. However, the extent of injury may exceed the inherent tissue regeneration capability demanding some kind of additional intervention. In this scenario, cell therapy has emerged as a promising alternative to treat challenging bone defects. This study aimed at evaluating the effect of local injection of bone marrow-derived mesenchymal stem cells (BM-MSCs) and adipose tissue-derived mesenchymal stem cells (AT-MSCs) on bone regeneration of rat calvaria defects. BM-MSCs and AT-MSCs were isolated and characterized by expression of surface markers; cell viability was evaluated after injection through a 21G needle. Defects of 5 mm in diameter were created in calvaria and after two weeks a single injection of BM-MSCs, AT-MSCs or vehicle-PBS without cells (Control) was carried out. Cells were tracked by bioluminescence and at 4 weeks post-injection bone formation was evaluated by micro-computed tomography (μCT) and histology, nanoindentation, and through gene expression of bone remodeling markers. The data were evaluated by one-way analysis of variance (p≤0.05). BM-MSCs and AT-MSCs presented characteristics of mesenchymal stem cells, kept viability after passing through a 21G needle and remained in the defects until day 14. In general, injection of both BM-MSCs and AT-MSCs resulted in higher bone formation compared to Control. Additionally, this bone tissue displayed elastic modulus and hardness similar to the pristine calvaria bone. The expression of all evaluated genes involved in bone formation was upregulated in bone tissue formed by BM-MSCs compared to AT-MSCs while genes involved in bone resorption were upregulated in AT-MSCs-formed bone. We show that cell therapy based on the local injection of BM-MSCs or AT-MSCs is effective in delivering viable cells that displayed local engraftment and induced a significant improvement in bone healing. Despite differences in the molecular cues observed between BM-MSCs and AT-MSCs, both cells were capable of forming bone tissue at comparable amounts and properties. These findings may drive cell therapy approaches toward the complete bone regeneration of challenging sites.

Keywords: cell therapy, mesenchymal stem cells, bone repair, cell culture

Procedia PDF Downloads 184
4184 The Role of Moringa oleifera Extract Leaves in Inducing Apoptosis in Breast Cancer Cell Line

Authors: V. Yurina, H. Sujuti, E. Rahmani, A. R. Nopitasari

Abstract:

Breast cancer has the highest prevalence cancer in women. Moringa leaves (M. oleifera) contain quercetin, kaempferol, and benzyl isothiocyanate which can enhance induction of apoptosis. This research aimed to study the role of the leaf extract of Moringa to increase apoptosis in breast cancer cell line, MCF-7 cells. This research used in vitro experimental, post-test only, control group design on breast cancer cells MCF-7 in vitro. Moringa leaves were extracted by maceration method with ethanol 70%. Cells were treated with drumstick leaves extract on 1100, 2200, and 4400 μg/ml for Hsp27 and caspase-9 expression (immunocytochemistry) and apoptosis (TUNEL assay) test. The results of this study found that the IC50 2200 µg/ml. Moringa leaves extract can significantly increase the expression of caspase-9 (p<0.05) and decreased Hsp 27 expression (p<0.05). Moreover it can increase apoptosis (p<0.05) significantly in MCF-7 cells. The conclusion of this study is Moringa leaves extract is able to increase the expression of caspase-9, decrease Hsp27 expression and increase apoptosis in breast cancer cell-line MCF-7.

Keywords: apoptosis, breast cancer, caspase-9, Hsp27, Moringa oleifera

Procedia PDF Downloads 544
4183 Developing an Advanced Algorithm Capable of Classifying News, Articles and Other Textual Documents Using Text Mining Techniques

Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

Abstract:

The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

Procedia PDF Downloads 121
4182 Investigating the Role of Circular RNA GATAD2A on H1N1 Replication

Authors: Tianqi Yu, Yingnan Ding, Yina Zhang, Yulan Liu, Yahui Li, Jing Lei, Jiyong Zhou, Suquan Song, Boli Hu

Abstract:

Circular RNAs (circRNAs) play critical roles in various diseases. However, whether and how circular RNA regulates influenza A virus (IAV) infection is unknown. Here, we studied the role of circular RNA GATA Zinc Finger Domain Containing 2A (circ-GATAD2A) in the replication of IAV H1N1 in A549 cells. Circ-GATAD2A was formed upon H1N1 infection. Knockdown of circ-GATAD2A in A549 cells enhanced autophagy and inhibited H1N1 replication. By contrast, overexpression of circ-GATAD2A impaired autophagy and promoted H1N1 replication. Similarly, knockout of vacuolar protein sorting 34 (VPS34) blocked autophagy and increased H1N1 replication. However, the expression of circ-GATAD2A could not further enhance H1N1 replication in VPS34 knockout cells. Collectively, these data indicated that circ-GATAD2A promotes the replication of H1N1 by inhibiting autophagy.

Keywords: autophagy, circ-GATAD2A, H1N1, replication

Procedia PDF Downloads 155
4181 Colonization of Embrionic Gonads of Nile Tilapia by Giant Gourami Testicular Germ Cells

Authors: Irma Andriani, Ita Djuwita, Komar Sumantadinata, Alimuddin

Abstract:

The recent study has been conducted to develop testicular germ cell transplantation as a tool for preservation and propagation of male germ-plasm from endangered fish species, as well as to produce surrogate broodstock of commercially valuable fish. Giant gourami testis had been used as a model for donor and Nile tilapia larvae as recipient. We developed testicular cell xenotransplantation by optimizing the timing of intraperitoneal cell transplantation to recipient larvae aged 1, 3, 5 and 7 days post hatching (dph). Freshly isolated testis of giant gourami weighing 600–800 g were minced in dissociation medium and then incubated for 3 hours in room temperature to collect monodisperce cell suspension. Donor cells labeled with PKH 26 were transplanted into the peritoneal cavity of Nile tilapia larvae using glass micropipettes. Parameters observed were survival rate of Nile tilapia larvae at 24 hours post transplantation (pt) and colonization efficiency of donor cells at 2 and 3 months pt. The incorporated donor cells were observed under fluorescent microscope. The result showed that the lowest survival rate at 24 hours pt was 1 dph larvae (82.74±6.76%) and the highest survival rate were 3 and 5 dph larvae (95.00±5.00% and 95.00±2.50%, respectively). The highest colonization efficiency was on 3 dph larvae (61.1±34.71%) and the lowest colonization efficiency was on 7 dph larvae (19.43±17.33%). In conclusion, 3 dph Nile tilapia larvae was the best recipient for giant gourami testicular germ cells xenotransplantation.

Keywords: xenotransplantation, testicular germ cell, giant gourami, Nile tilapia, colonization efficiency

Procedia PDF Downloads 582
4180 Experimental Study of Boost Converter Based PV Energy System

Authors: T. Abdelkrim, K. Ben Seddik, B. Bezza, K. Benamrane, Aeh. Benkhelifa

Abstract:

This paper proposes an implementation of boost converter for a resistive load using photovoltaic energy as a source. The model of photovoltaic cell and operating principle of boost converter are presented. A PIC micro controller is used in the close loop control to generate pulses for controlling the converter circuit. To performance evaluation of boost converter, a variation of output voltage of PV panel is done by shading one and two cells.

Keywords: boost converter, microcontroller, photovoltaic power generation, shading cells

Procedia PDF Downloads 878
4179 Effect of Varying Scaffold Architecture and Porosity of Calcium Alkali Orthophosphate Based-Scaffolds for Bone Tissue Engineering

Authors: D. Adel, F. Giacomini, R. Gildenhaar, G. Berger, C. Gomes, U. Linow, M. Hardt, B. Peleskae, J. Günster, A. Houshmand, M. Stiller, A. Rack, K. Ghaffar, A. Gamal, M. El Mofty, C. Knabe

Abstract:

The goal of this study was to develop 3D scaffolds from a silica containing calcium alkali orthophosphate utilizing two different fabrication processes, first a replica technique namely the Schwartzwalder Somers method (SSM), and second 3D printing, i.e. Rapid prototyping (RP). First, the mechanical and physical properties of the scaffolds (porosity, compressive strength, and solubility) was assessed and second their potential to facilitate homogenous colonization with osteogenic cells and extracellular bone matrix formation throughout the porous scaffold architecture. To this end murine and rat calavarie osteoblastic cells were dynamically seeded on both scaffold types under perfusion with concentrations of 3 million cells. The amount of cells and extracellular matrix as well as osteogenic marker expression was evaluated using hard tissue histology, immunohistochemistry, and histomorphometric analysis. Total porosities of both scaffolds were 86.9 % and 50% for SSM and RP respectively, Compressive strength values were 0.46 ± 0.2 MPa for SSM and 6.6± 0.8 MPa for RP. Regarding the cellular behavior, RP scaffolds displayed a higher cell and matrix percentage of 24.45%. Immunoscoring yielded strong osteocalcin expression of cells and matrix in RP scaffolds and a moderate expression in SSM scaffolds. 3D printed RP scaffolds displayed superior mechanical and biological properties compared to SSM. 3D printed scaffolds represent excellent candidates for bone tissue engineering.

Keywords: calcium alkali orthophosphate, extracellular matrix mineralization, osteoblast differentiation, rapid prototyping, scaffold

Procedia PDF Downloads 329
4178 Mechanical Prosthesis Controlled by Brain-Computer Interface

Authors: Tianyu Cao, KIRA (Ruizhi Zhao)

Abstract:

The purpose of our research is to study the possibility of people with physical disabilities manipulating mechanical prostheses through brain-computer interface (BCI) technology. The brain-machine interface (BCI) of the neural prosthesis records signals from neurons and uses mathematical modeling to decode them, converting desired movements into body movements. In order to improve the patient's neural control, the prosthesis is given a natural feeling. It records data from sensitive areas from the body to the prosthetic limb and encodes signals in the form of electrical stimulation to the brain. In our research, the brain-computer interface (BCI) is a bridge connecting patients’ cognition and the real world, allowing information to interact with each other. The efficient work between the two is achieved through external devices. The flow of information is controlled by BCI’s ability to record neuronal signals and decode signals, which are converted into device control. In this way, we could encode information and then send it to the brain through electrical stimulation, which has significant medical application.

Keywords: biomedical engineering, brain-computer interface, prosthesis, neural control

Procedia PDF Downloads 181