Search results for: expression recognition
3044 Synergistic Cytotoxicity of Cisplatin and Taxol in Overcoming Taxol Resistance through the Inhibition of LDHA in Oral Squamous Cell Carcinoma
Authors: Lin Feng, Ling-Ling E., Hong-Chen Liu
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The development of chemoresistance in patients represents a major challenge in cancer treatment. Lactate dehydrogenase‑A (LDHA) is one of the principle isoforms of LDH that is expressed in breast tissue, controlling the conversion of pyruvate to lactate and also playing a significant role in the metabolism of glucose. The aim of this study was to identify whether LDHA was involved in oral cancer cell resistance to Taxol and whether the downregulation of LDHA, as a result of cisplatin treatment, may overcome Taxol resistance in human oral squamous cells. The OECM‑1 oral epidermal carcinoma cell line was used, which has been widely used as a model of oral cancer in previous studies. The role of LDHA in Taxol and cisplatin resistance was investigated and the synergistic cytotoxicity of cisplatin and/or Taxol in oral squamous cells was analyzed. Cell viability was analyzed by MTT assay, LDHA expression was analyzed by western blot analysis and siRNA transfection was performed to knock down LDHA expression. The present study results showed that decreased levels of LDHA were responsible for the resistance of oral cancer cells to cisplatin (CDDP). CDDP treatments downregulated LDHA expression and lower levels of LDHA were detected in the CDDP‑resistant oral cancer cells compared with the CDDP‑sensitive cells. By contrast, the Taxol‑resistant cancer cells showed elevated LDHA expression levels. In addition, small interfering RNA‑knockdown of LDHA sensitized the cells to Taxol but desensitized them to CDDP treatment while exogenous expression of LDHA sensitized the cells to CDDP, but desensitized them to Taxol. The present study also revealed the synergistic cytotoxicity of CDDP and Taxol for killing oral cancer cells through the inhibition of LDHA. This study highlights LDHA as a novel therapeutic target for overcoming Taxol resistance in oral cancer patients using the combined treatments of Taxol and CDDP.Keywords: cisplatin, Taxol, carcinoma, oral squamous cells
Procedia PDF Downloads 4063043 Applying Polyphonic Dialogue as an Approach to Thematically Analyse the Development of Online Identities in Social Media
Authors: Maryam Khosronejad
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In social media, differences between individuals become salient as they become a member of different groups with particular social and cultural practices and get engaged in various conversations. The influence of the presence of social media on the promotion of self-expression and polyphonic dialogue is an understudied area and is, therefore, the focus of this paper. This exploration aims to understand the formation of online identities as an ongoing process of orchestrating polyphonic dialogue and responding to available positions. In addition, applying the thematic analysis, it gives examples of how discursive transactions facilitate this process. The implications for the use of social media in education will be discussed based on the findings.Keywords: online identity, polyphonic dialogue, self expression, social media
Procedia PDF Downloads 2213042 SLAMF5 Regulates Myeloid Cells Activation in the Eae Model
Authors: Laura Bellassen, Idit Shachar
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Multiple sclerosis (MS) is a chronic neurological disorder characterized by demyelination of the central nervous system (CNS), leading to a wide range of physical and cognitive impairments. Myeloid cells in the CNS, such microglia and border associated macrophage cells, participate in the neuroinflammation in MS. Activation of those cells in MS contributes to the inflammatory response in the CNS and recruitment of immune cells in the this compartment. SLAMF5 is a cell surface receptor that functions as a homophilic adhesion molecule, whose signaling can activate or inhibit leukocyte function. In the current study we followed the expression and function of SLAMF5 in myeloid cells in the CNS and in the periphery in the murine model for MS, the experimental autoimmune encephalomyelitis model (EAE). Our results show that SLAMF5 deficiency or blocking decreases the expression of activation molecules and costimulatory molecules such as MHCII and CD80, resulting in delayed onset and reduced progression of the disease. Moreover, blocking SLAMF5 in peripheral monocytes derived from MS patients and iPSC-derived microglia cells, controls the expression of HLA-DR and CD80. Thus, SLAMF5 is a regulator of myeloid cells function and can serve as a therapeutic target in autoimmune disorders as Multiple Sclerosis.Keywords: multiple sclerosis, EAE model, myeloid cells, new antibody, neuroimmunology
Procedia PDF Downloads 483041 Using Speech Emotion Recognition as a Longitudinal Biomarker for Alzheimer’s Diseases
Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang
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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.Keywords: Alzheimer’s disease, speech emotion recognition, longitudinal biomarker, machine learning
Procedia PDF Downloads 1053040 Analysis of Nitrogenase Fe Protein Activity in Transplastomic Tobacco
Authors: Jose A. Aznar-Moreno, Xi Jiang, Stefan Burén, Luis M. Rubio
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Integration of prokaryotic nitrogen fixation (nif) genes into the plastid genome for expression of functional nitrogenase components could render plants capable of assimilating atmospheric N2 making their crops less dependent of nitrogen fertilizers. The nitrogenase Fe protein component (NifH) has been used as proxy for expression and targeting of Nif proteins within plant and yeast cells. Here we use tobacco plants with the Azotobacter vinelandii nifH and nifM genes integrated into the plastid genome. NifH and its maturase NifM were constitutively produced in leaves, but not roots, during light and dark periods. Nif protein expression in transplastomic plants was stable throughout development. Chloroplast NifH was soluble, but it only showed in vitro activity when isolated from leaves collected at the end of the dark period. Exposing the plant extracts to elevated temperatures precipitated NifM and apo-NifH protein devoid of [Fe4S4] clusters, dramatically increasing the specific activity of remaining NifH protein. Our data indicate that the chloroplast endogenous [Fe-S] cluster biosynthesis was insufficient for complete NifH maturation, albeit a negative effect on NifH maturation due to excess NifM in the chloroplast cannot be excluded. NifH and NifM constitutive expression in transplastomic plants did not affect any of the following traits: seed size, germination time, germination ratio, seedling growth, emergence of the cotyledon and first leaves, chlorophyll content and plant height throughout development.Keywords: NifH, chloroplast, nitrogen fixation, crop improvement, transplastomic plants, fertilizer, biotechnology
Procedia PDF Downloads 1523039 Study of Age-Dependent Changes of Peripheral Blood Leukocytes Apoptotic Properties
Authors: Anahit Hakobjanyan, Zdenka Navratilova, Gabriela Strakova, Martin Petrek
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Aging has a suppressive influence on human immune cells. Apoptosis may play important role in age-dependent immunosuppression and lymphopenia. Prevention of apoptosis may be promoted by BCL2-dependent and BCL2-independent manner. BCL2 is an antiapoptotic factor that has an antioxidative role by locating the glutathione at mitochondria and repressing oxidative stress. STAT3 may suppress apoptosis in BCL2-independent manner and promote cell survival blocking cytochrome-c release and reducing ROS production. The aim of our study was to estimate the influence of aging on BCL2-dependent and BCL2-independent prevention of apoptosis via measurement of BCL2 and STAT3 mRNAs expressions. The study was done on Armenian population (2 groups: 37 healthy young (mean age±SE; min/max age, male/female: 37.6±1.1; 20/54, 15/22), 28 healthy aged (66.7±1.5; 57/85, 12/16)). mRNA expression in peripheral blood leukocytes (PBL) was determined by RT-PCR using PSMB2 as the reference gene. Statistical analysis was done with Graph-Pad Prism 5; P < 0.05 considered as significant. The expression of BCL2 mRNA was lower in aged group (0.199) compared with young ones (0.643)(p < 0.01). Decrease expression was also recorded for female and male subgroups (p < 0.01). The expression level of STAT3 mRNA was increased (young, 0.228; aged, 0.428) (p < 0.05) during aging (in the whole age group and male/female subgroups). Decreased level of BCL2 mRNA may indicate about the suppression of BCL2-dependent prevention of apoptosis during aging in peripheral blood leukocytes. At the same time increased the level of STAT3 may suggest about activation of BCL2-independent prevention of apoptosis during aging.Keywords: BCL2, STAT3, aging, apoptosis
Procedia PDF Downloads 3203038 Profile of Internet and Smartphone Overuse Based on Internet Usage Needs
Authors: Yeoju Chung
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Adolescents internet and smartphone addiction are increasing in Korea. But differences between internet addiction and smartphone addiction have been researched in these days. The main objective of this article is to explore the presence of clusters within a sample of adolescents based on dimensions associated with addiction and internet usage needs. The sample consists of 617 adolescents in the 14-19 year age group who were recruited in Korea A cluster analysis identified four groups of participants: internet overuse(IO), smartphone overuse(SO), both overuse(B) and normal(N) use group. MANOVA analysis based on internet usage showed that there are differences among four groups in internet usage needs. IO has higher cyber self-seeking needs and emotion and thought expression needs than SO. SO has higher real relationship and life needs with cyberworld than IO, B, and N. B has the highest cyber self-seeking needs and emotion and thought expression needs, however, game fun seeking needs is the highest in IO. These results support that IO seeks game fun needs, SO seeks real relationship and life needs, and B seeks cyber self and expression in cyberworld.Keywords: addiction, internet, needs, smartphone
Procedia PDF Downloads 2653037 Effects of Oxidized LDL in M2 Macrophages: Implications in Atherosclerosis
Authors: Fernanda Gonçalves, Karla Alcântara, Vanessa Moura, Patrícia Nolasco, Jorge Kalil, Maristela Hernandez
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Introduction: Atherosclerosis is a chronic disease where two striking features are observed: retention of lipids and inflammation. Understanding the interaction between immune cells and lipoproteins involved in atherogenesis are urgent challenges, since cardiovascular diseases are the leading cause of death worldwide. Macrophages are critical to the development of atherosclerotic plaques and in the perpetuation of inflammation in these lesions. These cells are also directly involved in unstable plaque rupture. Recently different populations of macrophages are being identified in atherosclerotic lesions. Although the presence of M2 macrophages (macrophages activated by the alternative pathway, eg. The IL-4) has been identified, the function of these cells in atherosclerosis is not yet defined. M2 macrophages have a high endocytic capacity, they promote remodeling of tissues and to have anti-inflammatory activity. However, in atherosclerosis, especially unstable plaques, severe inflammatory reaction, accumulation of cellular debris and intense degradation of the tissue is observed. Thus, it is possible that the M2 macrophages have altered function (phenotype) in atherosclerosis. Objective: Our aim is to evaluate if the presence of oxidized LDL alters the phenotype and function of M2 macrophages in vitro. Methods: For this, we will evaluate whether the addition of lipoprotein in M2 macrophages differentiated in vitro with IL -4 induces 1) a reduction in the secretion of anti-inflammatory cytokines (CBA and ELISA), 2) secretion of inflammatory cytokines (CBA and ELISA), 3) expression of cell activation markers (Flow cytometry), 4) alteration in gene expression of molecules adhesion and extracellular matrix (Real-Time PCR) and 5) Matrix degradation (confocal microscopy). Results: In oxLDL stimulated M2 macrophages cultures we did not find any differences in the expression of the cell surface markers tested, including: HLA-DR, CD80, CD86, CD206, CD163 and CD36. Also, cultures stimulated with oxLDL had similar phagocytic capacity when compared to unstimulated cells. However, in the supernatant of these cultures an increase in the secretion of the pro-inflammatory cytokine IL-8 was detected. No significant changes where observed in IL-6, IL-10, IL-12 and IL-1b levels. The culture supernatant also induced massive extracellular matrix (produced by mouse embryo fibroblast) filaments degradation. When evaluating the expression of 84 extracellular matrix and adhesion molecules genes, we observed that the stimulation of oxLDL in M2 macrophages decreased 47% of the genes and increased the expression of only 3% of the genes. In particular we noted that oxLDL inhibit the expression of 60% of the genes constituents of extracellular matrix and collagen expressed by these cells, including fibronectin1 and collagen VI. We also observed a decrease in the expression of matrix protease inhibitors, such as TIMP 2. On the opposite, the matricellular protein thrombospondin had a 12 fold increase in gene expression. In the presence of native LDL 90% of the genes had no altered expression. Conclusion: M2 macrophages stimulated with oxLDL secrete the pro-inflammatory cytokine IL-8, have an altered extracellular matrix constituents gene expression, and promote the degradation of extracellular matrix. M2 macrophages may contribute to the perpetuation of inflammation in atherosclerosis and to plaque rupture.Keywords: atherosclerosis, LDL, macrophages, m2
Procedia PDF Downloads 3293036 Effects of Propolis on Immunomodulatory and Antibody Production in Broilers
Authors: Yu-Hsiang Yu
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The immunomodulatory effect of propolis has been widely investigated in the past decade. However, the beneficial effects in broilers are still poorly understood. The aim of this study was to evaluate the effect of propolis added in drinking water on immunomodulatory and antibody production in broiler. Total of 48 chicks were randomly allocated into four groups with 12 broilers per group. All birds were intranasal inoculated with Newcastle Disease vaccine at 4 and 14 days old of age. Four groups, including control without any treatment, groups of A, B and F [3 days of anterior (A), 3 days of posterior (P) and 6 days of full (F)] were supplied the propolis at 300 ppm in drinking water when vaccination was performed, respectively. Our results showed that no significant difference was found in growth performance, antibody production and immune organ index among groups. However, propolis treatments in broilers significantly reduced IL-4 expression in spleen at 14 days-old of age and bursa at 28 days-old of age compared with control group. The expression of IFN-gamma in spleen (A, P and F group) and bursal (F group) were elevated compared with control group at 28 days-old of age. In conclusion, our results indicated that propolis-treated birds could bear the capability for immunomodulatory effects by change Th1 subset cytokine expression in vaccination.Keywords: propolis, broiler, immunomodulatory, vaccination
Procedia PDF Downloads 3233035 Aminopeptidase P (DAP) Expression Pattern in Drosophila Melanogaster
Authors: Suneeta Gireesh Panicker
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Aim: Aminopeptidase P (APP) is an enzyme that has specificity for proline, can specifically cleave Xaa-Proline peptides and is a metallo-aminopeptidase. The bonds nearby to the imino acid proline are tough to cleave by many peptidases, but APP can specifically break peptide bonds engaged with proline. Membrane-bound form and a cytosolic form are the two forms in which this enzyme exists. The exact physiological function of APP remains unclear and hence the present work attempts to determine it. Methods: In the present study, the expression pattern of cytosolic Aminopeptidase P (DAP) was determined in all the embryonic stages and larval stages of wild-type Drosophila by using polyclonal monospecific antibodies. To show the presence of DAP RNA in embryonic and larval stages, RNA in situ hybridization was performed. DAP promoter-LacZ fusion reporter gene vector was used to construct transgenic embryos to study the regulation pattern of DAP. To study the DAP expression profile, a transgenic fly consisting of a DAP promoter with β-gal and GFP reporter genes in front of it was constructed. Results: DAP protein expression was observed in neuroectodermal cells, posterior midgut primordium, proctodeum, ventral neuroblast and primordial stomatogastric nervous system. It was observed in the ventral cord and midgut in stage 12. The completely developed embryos showed the intense occurrence of it in the ventral cord and gut region. The eye-antennal disc, wing disc and leg disc also showed the presence of DAP protein. LacZ expression in transgenic embryos also showed the same pattern. Conclusion: Similar to various known multiple-functional proteins, DAP could be one with different functions at different stages and in different cells. Data presented here designates DAP functions in the early embryonic and imaginal dics differentiation and development, suggesting that it may be required for the metabolism of proteins like neuropeptides and tachykinins.Keywords: aminopeptidase P, in situ hybridization, transgenic fly, embryonic stages
Procedia PDF Downloads 773034 Induction of Callus and Expression of Compounds in Capsicum Frutescens Supplemented with of 2, 4-D
Authors: Jamilah Syafawati Yaacob, Muhammad Aiman Ramli
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Cili padi or Capsicum frutescens is one of capsicum species from nightshade family, Solanaceae. It is famous in Malaysia and is widely used as a food ingredient. Capsicum frutescens also possess vast medicinal properties. The objectives of this study are to determine the most optimum 2,4-D hormone concentration for callus induction from stem explants C. frutescens and the effects of different 2,4-D concentrations on expression of compounds from C. frutescens. Seeds were cultured on MS media without hormones (MS basal media) to yield aseptic seedlings of this species, which were then used to supply explant source for subsequent tissue culture experiments. Stem explants were excised from aseptic seedlings and cultured on MS media supplemented with various concentrations (0.1, 0.3 and 0.5 mg/L) of 2,4-D to induce formation of callus. Fresh weight, dry weight and callus growth percentage in all samples were recorded. The highest mean of dry weight was observed in MS media supplemented with 0.5 mg/L 2,4-D, where 0.4499 ± 0.106 g of callus was produced. The highest percentage of callus growth (16.4%) was also observed in cultures supplemented with 0.5 mg/L 2,4-D. The callus samples were also subjected to HPLC-MS to evaluate the effect of hormone concentration on expression of bio active compounds in different samples. Results showed that caffeoylferuloylquinic acids were present in all samples, but was most abundant in callus cells supplemented with 0.3 & 0.5 mg/L 2,4-D. Interestingly, there was an unknown compound observed to be highly expressed in callus cells supplemented with 0.1 mg/L 2,4-D, but its presence was less significant in callus cells supplemented with 0.3 and 0.5 mg/L 2,4-D. Furthermore, there was also a compound identified as octadecadienoic acid, which was uniquely expressed in callus supplemented with 0.5 mg/L 2,4-D, but absent in callus cells supplemented with 0.1 and 0.3 mg/L 2,4-D. The results obtained in this study indicated that plant growth regulators played a role in expression of secondary metabolites in plants. The increase or decrease of these growth regulators may have triggered a change in the secondary metabolite biosynthesis pathways, thus causing differential expression of compounds in this plant.Keywords: callus, in vitro, secondary metabolite, 2, 4-Dichlorophenoxyacetic acid
Procedia PDF Downloads 3673033 English Learning Speech Assistant Speak Application in Artificial Intelligence
Authors: Albatool Al Abdulwahid, Bayan Shakally, Mariam Mohamed, Wed Almokri
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Artificial intelligence has infiltrated every part of our life and every field we can think of. With technical developments, artificial intelligence applications are becoming more prevalent. We chose ELSA speak because it is a magnificent example of Artificial intelligent applications, ELSA speak is a smartphone application that is free to download on both IOS and Android smartphones. ELSA speak utilizes artificial intelligence to help non-native English speakers pronounce words and phrases similar to a native speaker, as well as enhance their English skills. It employs speech-recognition technology that aids the application to excel the pronunciation of its users. This remarkable feature distinguishes ELSA from other voice recognition algorithms and increase the efficiency of the application. This study focused on evaluating ELSA speak application, by testing the degree of effectiveness based on survey questions. The results of the questionnaire were variable. The generality of the participants strongly agreed that ELSA has helped them enhance their pronunciation skills. However, a few participants were unconfident about the application’s ability to assist them in their learning journey.Keywords: ELSA speak application, artificial intelligence, speech-recognition technology, language learning, english pronunciation
Procedia PDF Downloads 983032 A Neuron Model of Facial Recognition and Detection of an Authorized Entity Using Machine Learning System
Authors: J. K. Adedeji, M. O. Oyekanmi
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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.Keywords: biometric characters, facial recognition, neural network, OpenCV
Procedia PDF Downloads 2483031 Combined Treatment of PARP-1 Inhibitor and Carbon Ion or Gamma Exposure Reduces the Metastatic Potential in Cultured Human Cells
Authors: Priyanka Chowdhury, Asitikantha Sarma, Utpal Ghosh
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Hadron therapy using high Linear Energy Transfer (LET) ion beam is producing promising clinical results worldwide. The major advantages are its ability to kill radio-resistant tumor and its anti-metastatic activity. Poly(ADP-ribose) polymerase-1 (PARP-1) inhibitors have been widely used as radiosensitizer, but its role in metastasis is unknown. The purpose of our study was to investigate the effect of PARP-1 depletion in combination with either Carbon Ion Beam (CIB) or gamma irradiation on metastatic potential of cultured cancerous cells. A549 cells were irradiated with CIB (0-4Gy) or gamma (0, 2, 4, 6 and 10 Gy) with and without PARP-1 inhibition. The metastatic potential of the cells was determined by cell migratory assay, expression, and activity of MMP-2 and MMP-9, expression of Cadherin, Fibronectin, and Vimentin. CIB exposure reduced migratory property and activity of MMP-2 and MMP-9 significantly. CIB with PARP-1 inhibition reduced cell migration and Matrix Metalloproteinase (MMPs) activity in a synergistic manner. Expression of MMPs was also down-regulated in CIB and combined treatment. On the contrary, MMP- 2 and MMP-9 activity was significantly increased in gamma irradiated cells but decreased upon combined treatment of gamma and PARP-1 inhibitor. MMPs expression and migration was reduced when gamma irradiation was combined with PARP-1 inhibition. Thus, our study clearly demonstrates that PARP-1 inhibition in combination with either high or low LET can significantly suppress metastatic potential in cancer cells and thereby can be a promising tool in controlling metastatic cancers.Keywords: high LET, low LET, matrix metalloproteinase (MMP), PARP-1
Procedia PDF Downloads 2083030 Recognition and Counting Algorithm for Sub-Regional Objects in a Handwritten Image through Image Sets
Authors: Kothuri Sriraman, Mattupalli Komal Teja
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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm
Procedia PDF Downloads 3413029 Circadian Expression of MicroRNAs in Colon and Its Changes during Colorectal Tumorigenesis
Authors: Katerina Balounova, Jiri Pacha, Peter Ergang, Martin Vodicka, Pavlina Kvapilova
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MicroRNAs are small non-coding RNAs involved in a wide range of physiological processes. Post-transcriptional regulation of gene expression by microRNAs gives the organism a further level of control of the gene-expression program and the disruption of this microRNA regulatory mechanism seems to increase the risk of various pathophysiological conditions including tumorigenesis. To the present day, microRNAs were shown to participate in the mayor signalization pathways leading to tumorigenesis, including proliferation, cell cycle, apoptosis and metastasis formation. In addition, microRNAs have been found to play important roles in the generation and maintenance of circadian clock. These clocks generate circadian rhythms, which participate in a number of regulatory pathways. Disruption of the circadian signals seems to be associated with the development and the progression of tumours including colorectal cancer. We investigated therefore whether the diurnal profiles of miRNAs linked to tumorigenesis and regulation of circadian clock are changed during tumorigenesis. Based on published data we chose 10 microRNAs linked to tumorigenesis or circadian clock (let-7b-5p, miR 1 3p, miR 106b 5p, miR 141 3p, miR 191 5p, miR 20a 5p, miR 25 3p, miR 29a 3p, miR 34a 5p and miR 93 5p) and compared their 24-hr expression profiles in healthy and in chemically induces primary colorectal tumours of 52week-old mice. Using RT-qPCR we proved circadian rhythmicity in let-7b-5p, miR 106b 5p, miR 141 3p, miR 191 5p, miR 20a 5p, miR 25 3p, miR 29a 3p and miR 93 5p in healthy colon but not in tumours. The acrophases of miR 106b 5p, miR 141 3p, miR 191 5p, miR 20a 5p, miR 25 3p and miR 93 5p were reached around CT 24, the acrophases of let-7b-5p and miR-29a-3p were slightly shifted and reached around CT 21. In summary, our results show that circadian regulation of some colonic microRNAs is greatly affected by neoplastic transformation.Keywords: circadian rhythm, colon, colorectal cancer, microRNA, tumorigenesis
Procedia PDF Downloads 1633028 Toxicological Effects of Atmospheric Fine Particulate Matter on Human Bronchial Epithelial Cells: Metabolic Activation, Genotoxicity and Epigenetic Modifications
Authors: M. Borgie, Z. Dagher, F. Ledoux, A. Verdin, F. Cazier, H. Greige, P. Shirali, D. Courcot
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In October 2013, the International Agency for Research on Cancer (IARC) classified outdoor air pollution and fine particulate matter (PM2.5) as carcinogenic to humans. Despite the clearly relationship established by epidemiological studies between PM exposure and the onset of respiratory and cardiovascular diseases, uncertainties remain about the physiopathological mechanisms responsible for these diseases. The aim of this work was to evaluate the toxicological effects of two samples of atmospheric PM2.5 collected at urban and rural sites on human bronchial epithelial cells, BEAS-2B, especially to investigate the metabolic activation of organic compounds, the alteration of epigenetic mechanisms (i.e. microRNAs genes expression), the phosphorylation of H2AX and the telomerase activity. Our results showed a significant increase in CYP1A1, CYP1B1, and AhRR genes expression, miR-21 gene expression, H2AX phosphorylation and telomerase activity in BEAS-2B cells after their exposure to PM2.5, both in a dose and site-dependent manner. These results showed that PM2.5, especially urban PM, are able to induce the expression of metabolizing enzymes which can provide metabolic biotransformation of organic compounds into more toxic and carcinogenic metabolites, and to induce the expression of the oncomiR miR-21 which promotes cell growth and enhances tumor invasion and metastasis in lung cancer. In addition, our results have highlighted the role of PM2.5 in the activation of telomerase, which can maintain the telomeres length and subsequently preventing cell death, and have also demonstrated the ability of PM2.5 to induce DNA breaks and thus to increase the risk of mutations or chromosomal translocations that lead to genomic instability. All these factors may contribute to cell abnormalities, and thus the development of cancer.Keywords: BEAS-2B cells, carcinogenesis, epigenetic alterations and genotoxicity, PM2.5
Procedia PDF Downloads 3773027 Object Detection Based on Plane Segmentation and Features Matching for a Service Robot
Authors: António J. R. Neves, Rui Garcia, Paulo Dias, Alina Trifan
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With the aging of the world population and the continuous growth in technology, service robots are more and more explored nowadays as alternatives to healthcare givers or personal assistants for the elderly or disabled people. Any service robot should be capable of interacting with the human companion, receive commands, navigate through the environment, either known or unknown, and recognize objects. This paper proposes an approach for object recognition based on the use of depth information and color images for a service robot. We present a study on two of the most used methods for object detection, where 3D data is used to detect the position of objects to classify that are found on horizontal surfaces. Since most of the objects of interest accessible for service robots are on these surfaces, the proposed 3D segmentation reduces the processing time and simplifies the scene for object recognition. The first approach for object recognition is based on color histograms, while the second is based on the use of the SIFT and SURF feature descriptors. We present comparative experimental results obtained with a real service robot.Keywords: object detection, feature, descriptors, SIFT, SURF, depth images, service robots
Procedia PDF Downloads 5373026 Transcriptomic Analyses of Kappaphycus alvarezii under Different Wavelengths of Light
Authors: Vun Yee Thien, Kenneth Francis Rodrigues, Clemente Michael Vui Ling Wong, Wilson Thau Lym Yong
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Transcriptomes associated with the process of photosynthesis have offered insights into the mechanism of gene regulation in terrestrial plants; however, limited information is available as far as macroalgae are concerned. This investigation aims to decipher the underlying mechanisms associated with photosynthesis in the red alga, Kappaphycus alvarezii, by performing a differential expression analysis on a de novo assembled transcriptomes. Comparative analysis of gene expression was designed to examine the alteration of light qualities and its effect on physiological mechanisms in the red alga. High-throughput paired-end RNA-sequencing was applied to profile the transcriptome of K. alvarezii irradiated with different wavelengths of light (blue 492-455 nm, green 577-492 nm and red 780-622 nm) as compared to the full light spectrum, resulted in more than 60 million reads individually and assembled using Trinity and SOAPdenovo-Trans. The transcripts were annotated in the NCBI non-redundant (nr) protein, SwissProt, KEGG and COG databases with a cutoff E-value of 1e-5 and nearly 30% of transcripts were assigned to functional annotation by Blast searches. Differential expression analysis was performed using edgeR. The DEGs were designated to six categories: BL (blue light) regulated, GL (green light) regulated, RL (red light) regulated, BL or GL regulated, BL or RL regulated, GL or RL regulated, and either BL, GL or RL regulated. These DEGs were mapped to terms in KEGG database and compared with the whole transcriptome background to search for genes that regulated by light quality. The outcomes of this study will enhance our understanding of molecular mechanisms underlying light-induced responses in red algae.Keywords: de novo transcriptome sequencing, differential gene expression, Kappaphycus alvareziired, red alga
Procedia PDF Downloads 5043025 Text Emotion Recognition by Multi-Head Attention based Bidirectional LSTM Utilizing Multi-Level Classification
Authors: Vishwanath Pethri Kamath, Jayantha Gowda Sarapanahalli, Vishal Mishra, Siddhesh Balwant Bandgar
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Recognition of emotional information is essential in any form of communication. Growing HCI (Human-Computer Interaction) in recent times indicates the importance of understanding of emotions expressed and becomes crucial for improving the system or the interaction itself. In this research work, textual data for emotion recognition is used. The text being the least expressive amongst the multimodal resources poses various challenges such as contextual information and also sequential nature of the language construction. In this research work, the proposal is made for a neural architecture to resolve not less than 8 emotions from textual data sources derived from multiple datasets using google pre-trained word2vec word embeddings and a Multi-head attention-based bidirectional LSTM model with a one-vs-all Multi-Level Classification. The emotions targeted in this research are Anger, Disgust, Fear, Guilt, Joy, Sadness, Shame, and Surprise. Textual data from multiple datasets were used for this research work such as ISEAR, Go Emotions, Affect datasets for creating the emotions’ dataset. Data samples overlap or conflicts were considered with careful preprocessing. Our results show a significant improvement with the modeling architecture and as good as 10 points improvement in recognizing some emotions.Keywords: text emotion recognition, bidirectional LSTM, multi-head attention, multi-level classification, google word2vec word embeddings
Procedia PDF Downloads 1713024 An Accurate Computation of 2D Zernike Moments via Fast Fourier Transform
Authors: Mohammed S. Al-Rawi, J. Bastos, J. Rodriguez
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Object detection and object recognition are essential components of every computer vision system. Despite the high computational complexity and other problems related to numerical stability and accuracy, Zernike moments of 2D images (ZMs) have shown resilience when used in object recognition and have been used in various image analysis applications. In this work, we propose a novel method for computing ZMs via Fast Fourier Transform (FFT). Notably, this is the first algorithm that can generate ZMs up to extremely high orders accurately, e.g., it can be used to generate ZMs for orders up to 1000 or even higher. Furthermore, the proposed method is also simpler and faster than the other methods due to the availability of FFT software and/or hardware. The accuracies and numerical stability of ZMs computed via FFT have been confirmed using the orthogonality property. We also introduce normalizing ZMs with Neumann factor when the image is embedded in a larger grid, and color image reconstruction based on RGB normalization of the reconstructed images. Astonishingly, higher-order image reconstruction experiments show that the proposed methods are superior, both quantitatively and subjectively, compared to the q-recursive method.Keywords: Chebyshev polynomial, fourier transform, fast algorithms, image recognition, pseudo Zernike moments, Zernike moments
Procedia PDF Downloads 2573023 A Review on Artificial Neural Networks in Image Processing
Authors: B. Afsharipoor, E. Nazemi
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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN
Procedia PDF Downloads 3983022 Microarray Data Visualization and Preprocessing Using R and Bioconductor
Authors: Ruchi Yadav, Shivani Pandey, Prachi Srivastava
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Microarrays provide a rich source of data on the molecular working of cells. Each microarray reports on the abundance of tens of thousands of mRNAs. Virtually every human disease is being studied using microarrays with the hope of finding the molecular mechanisms of disease. Bioinformatics analysis plays an important part of processing the information embedded in large-scale expression profiling studies and for laying the foundation for biological interpretation. A basic, yet challenging task in the analysis of microarray gene expression data is the identification of changes in gene expression that are associated with particular biological conditions. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. One of the most popular platforms for microarray analysis is Bioconductor, an open source and open development software project based on the R programming language. This paper describes specific procedures for conducting quality assessment, visualization and preprocessing of Affymetrix Gene Chip and also details the different bioconductor packages used to analyze affymetrix microarray data and describe the analysis and outcome of each plots.Keywords: microarray analysis, R language, affymetrix visualization, bioconductor
Procedia PDF Downloads 4723021 Cloning and Expression of Azurin: A Protein Having Antitumor and Cell Penetrating Ability
Authors: Mohsina Akhter
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Cancer has become a wide spread disease around the globe and takes many lives every year. Different treatments are being practiced but all have potential side effects with somewhat less specificity towards target sites. Pseudomonas aeruginosa is known to secrete a protein azurin with special anti-cancer function. It has unique cell penetrating peptide comprising of 18 amino acids that have ability to enter cancer cells specifically. Reported function of Azurin is to stabilize p53 inside the tumor cells and induces apoptosis through Bax mediated cytochrome c release from mitochondria. At laboratory scale, we have made recombinant azurin through cloning rpTZ57R/T-azu vector into E.coli strain DH-5α and subcloning rpET28-azu vector into E.coli BL21-CodonPlus (DE3). High expression was ensured with IPTG induction at different concentrations then optimized high expression level at 1mM concentration of IPTG for 5 hours. Purification has been done by using Ni+2 affinity chromatography. We have concluded that azurin can be a remarkable improvement in cancer therapeutics if it produces on a large scale. Azurin does not enter into the normal cells so it will prove a safe and secure treatment for patients and prevent them from hazardous anomalies.Keywords: azurin, pseudomonas aeruginosa, cancer, therapeutics
Procedia PDF Downloads 3053020 Speech Detection Model Based on Deep Neural Networks Classifier for Speech Emotions Recognition
Authors: Aisultan Shoiynbek, Darkhan Kuanyshbay, Paulo Menezes, Akbayan Bekarystankyzy, Assylbek Mukhametzhanov, Temirlan Shoiynbek
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Speech emotion recognition (SER) has received increasing research interest in recent years. It is a common practice to utilize emotional speech collected under controlled conditions recorded by actors imitating and artificially producing emotions in front of a microphone. There are four issues related to that approach: emotions are not natural, meaning that machines are learning to recognize fake emotions; emotions are very limited in quantity and poor in variety of speaking; there is some language dependency in SER; consequently, each time researchers want to start work with SER, they need to find a good emotional database in their language. This paper proposes an approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describes the sequence of actions involved in the proposed approach. One of the first objectives in the sequence of actions is the speech detection issue. The paper provides a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To investigate the working capacity of the developed model, an analysis of speech detection and extraction from real tasks has been performed.Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset
Procedia PDF Downloads 113019 Correlation between Polysaccharides Molecular Weight Changes and Pectinases Gene Expression during Papaya Ripening
Authors: Samira B. R. Prado, Paulo R. Melfi, Beatriz T. Minguzzi, João P. Fabi
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Fruit softening is the main change that occurs during papaya (Carica papaya L.) ripening. It is characterized by the depolymerization of cell wall polysaccharides, especially the pectic fractions, which causes cell wall disassembling. However, it is uncertain how the modification of the two main pectin polysaccharides fractions (water-soluble – WSF, and oxalate-soluble fractions - OSF) accounts for fruit softening. The aim of this work was to correlate molecular weight changes of WSF and OSF with the gene expression of pectin-solubilizing enzymes (pectinases) during papaya ripening. Papaya fruits obtained from a producer were harvest and storage under specific conditions. The fruits were divided in five groups according to days after harvesting. Cell walls from all groups of papaya pulp were isolated and fractionated (WSF and OSF). Expression profiles of pectinase genes were achieved according to the MIQE guidelines (Minimum Information for publication of Quantitative real-time PCR Experiments). The results showed an increased yield and a decreased molecular weight throughout ripening for WSF and OSF. Gene expression data support that papaya softening is achieved by polygalacturonases (PGs) up-regulation, in which their actions might have been facilitated by the constant action of pectinesterases (PMEs). Moreover, BGAL1 gene was up-regulated during ripening with a simultaneous galactose release, suggesting that galactosidases (GALs) could also account for pulp softening. The data suggest that a solubilization of galacturonans and a depolymerization of cell wall components were caused mainly by the action of PGs and GALs.Keywords: carica papaya, fruit ripening, galactosidases, plant cell wall, polygalacturonases
Procedia PDF Downloads 4163018 Chaotic Sequence Noise Reduction and Chaotic Recognition Rate Improvement Based on Improved Local Geometric Projection
Authors: Rubin Dan, Xingcai Wang, Ziyang Chen
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A chaotic time series noise reduction method based on the fusion of the local projection method, wavelet transform, and particle swarm algorithm (referred to as the LW-PSO method) is proposed to address the problem of false recognition due to noise in the recognition process of chaotic time series containing noise. The method first uses phase space reconstruction to recover the original dynamical system characteristics and removes the noise subspace by selecting the neighborhood radius; then it uses wavelet transform to remove D1-D3 high-frequency components to maximize the retention of signal information while least-squares optimization is performed by the particle swarm algorithm. The Lorenz system containing 30% Gaussian white noise is simulated and verified, and the phase space, SNR value, RMSE value, and K value of the 0-1 test method before and after noise reduction of the Schreiber method, local projection method, wavelet transform method, and LW-PSO method are compared and analyzed, which proves that the LW-PSO method has a better noise reduction effect compared with the other three common methods. The method is also applied to the classical system to evaluate the noise reduction effect of the four methods and the original system identification effect, which further verifies the superiority of the LW-PSO method. Finally, it is applied to the Chengdu rainfall chaotic sequence for research, and the results prove that the LW-PSO method can effectively reduce the noise and improve the chaos recognition rate.Keywords: Schreiber noise reduction, wavelet transform, particle swarm optimization, 0-1 test method, chaotic sequence denoising
Procedia PDF Downloads 1893017 Long Short-Term Memory Based Model for Modeling Nicotine Consumption Using an Electronic Cigarette and Internet of Things Devices
Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi
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In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users.Keywords: Iot, activity recognition, automatic classification, unconstrained environment
Procedia PDF Downloads 2173016 A New Scheme for Chain Code Normalization in Arabic and Farsi Scripts
Authors: Reza Shakoori
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This paper presents a structural correction of Arabic and Persian strokes using manipulation of their chain codes in order to improve the rate and performance of Persian and Arabic handwritten word recognition systems. It collects pure and effective features to represent a character with one consolidated feature vector and reduces variations in order to decrease the number of training samples and increase the chance of successful classification. Our results also show that how the proposed approaches can simplify classification and consequently recognition by reducing variations and possible noises on the chain code by keeping orientation of characters and their backbone structures.Keywords: Arabic, chain code normalization, OCR systems, image processing
Procedia PDF Downloads 3963015 Modified Form of Margin Based Angular Softmax Loss for Speaker Verification
Authors: Jamshaid ul Rahman, Akhter Ali, Adnan Manzoor
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Learning-based systems have received increasing interest in recent years; recognition structures, including end-to-end speak recognition, are one of the hot topics in this area. A famous work on end-to-end speaker verification by using Angular Softmax Loss gained significant importance and is considered useful to directly trains a discriminative model instead of the traditional adopted i-vector approach. The margin-based strategy in angular softmax is beneficial to learn discriminative speaker embeddings where the random selection of margin values is a big issue in additive angular margin and multiplicative angular margin. As a better solution in this matter, we present an alternative approach by introducing a bit similar form of an additive parameter that was originally introduced for face recognition, and it has a capacity to adjust automatically with the corresponding margin values and is applicable to learn more discriminative features than the Softmax. Experiments are conducted on the part of Fisher dataset, where it observed that the additive parameter with angular softmax to train the front-end and probabilistic linear discriminant analysis (PLDA) in the back-end boosts the performance of the structure.Keywords: additive parameter, angular softmax, speaker verification, PLDA
Procedia PDF Downloads 93