Search results for: annotated facial expression dataset
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3306

Search results for: annotated facial expression dataset

3186 Using Gene Expression Programming in Learning Process of Rough Neural Networks

Authors: Sanaa Rashed Abdallah, Yasser F. Hassan

Abstract:

The paper will introduce an approach where a rough sets, gene expression programming and rough neural networks are used cooperatively for learning and classification support. The Objective of gene expression programming rough neural networks (GEP-RNN) approach is to obtain new classified data with minimum error in training and testing process. Starting point of gene expression programming rough neural networks (GEP-RNN) approach is an information system and the output from this approach is a structure of rough neural networks which is including the weights and thresholds with minimum classification error.

Keywords: rough sets, gene expression programming, rough neural networks, classification

Procedia PDF Downloads 348
3185 A Novel PfkB Gene Cloning and Characterization for Expression in Potato Plants

Authors: Arfan Ali, Idrees Ahmad Nasir

Abstract:

Potato (Solanum tuberosum) is an important cash crop and popular vegetable in Pakistan and throughout the world. Cold storage of potatoes accelerates the conversion of starch into reduced sugars (glucose and fructose). This process causes dry mass and bitter taste in the potatoes that are not acceptable to end consumers. In the current study, the phosphofructokinase B gene was cloned into the pET-30 vector for protein expression and the pCambia-1301 vector for plant expression. Amplification of a 930bp product from an E. coli strain determined the successful isolation of the phosphofructokinase B gene. Restriction digestion using NcoI and BglII along with the amplification of the 930bp product using gene specific primers confirmed the successful cloning of the PfkB gene in both vectors. The protein was expressed as a His-PfkB fusion protein. Western blot analysis confirmed the presence of the 35 Kda PfkB protein when hybridized with anti-His antibodies. The construct Fani-01 was evaluated transiently using a histochemical gus assay. The appearance of blue color in the agroinfiltrated area of potato leaves confirmed the successful expression of construct Fani-01. Further, the area displaying gus expression was evaluated for PfkB expression using ELISA. Moreover, PfkB gene expression evaluated through transient expression determined successful gene expression and highlighted its potential utilization for stable expression in potato to reduce sweetening due to long-term storage.

Keywords: potato, Solanum tuberosum, transformation, PfkB, anti-sweetening

Procedia PDF Downloads 437
3184 Grammatically Coded Corpus of Spoken Lithuanian: Methodology and Development

Authors: L. Kamandulytė-Merfeldienė

Abstract:

The paper deals with the main issues of methodology of the Corpus of Spoken Lithuanian which was started to be developed in 2006. At present, the corpus consists of 300,000 grammatically annotated word forms. The creation of the corpus consists of three main stages: collecting the data, the transcription of the recorded data, and the grammatical annotation. Collecting the data was based on the principles of balance and naturality. The recorded speech was transcribed according to the CHAT requirements of CHILDES. The transcripts were double-checked and annotated grammatically using CHILDES. The development of the Corpus of Spoken Lithuanian has led to the constant increase in studies on spontaneous communication, and various papers have dealt with a distribution of parts of speech, use of different grammatical forms, variation of inflectional paradigms, distribution of fillers, syntactic functions of adjectives, the mean length of utterances.

Keywords: CHILDES, corpus of spoken Lithuanian, grammatical annotation, grammatical disambiguation, lexicon, Lithuanian

Procedia PDF Downloads 208
3183 Automatic Checkpoint System Using Face and Card Information

Authors: Kriddikorn Kaewwongsri, Nikom Suvonvorn

Abstract:

In the deep south of Thailand, checkpoints for people verification are necessary for the security management of risk zones, such as official buildings in the conflict area. In this paper, we propose an automatic checkpoint system that verifies persons using information from ID cards and facial features. The methods for a person’s information abstraction and verification are introduced based on useful information such as ID number and name, extracted from official cards, and facial images from videos. The proposed system shows promising results and has a real impact on the local society.

Keywords: face comparison, card recognition, OCR, checkpoint system, authentication

Procedia PDF Downloads 299
3182 Semi-Automated Tracking of Vibrissal Movements in Free-Moving Rodents Captured by High-Speed Videos

Authors: Hyun June Kim, Tailong Shi, Seden Akdagli, Sam Most, Yuling Yan

Abstract:

Quantitative analysis of mouse whisker movement can be used to study functional recovery and regeneration of facial nerve after an injury. However, it is challenging to accurately track mouse whisker movements, and most whisker tracking methods require manual intervention, e.g. fixing the head of the mouse during a study. Here we describe a semi-automated image processing method that is applied to high-speed video recordings of free-moving mice to track whisker movements. We first track the head movement of a mouse by delineating the lower head contour frame-by-frame to locate and determine the orientation of its head. Then, a region of interest is identified for each frame, with subsequent application of the Hough transform to track individual whisker movements on each side of the head. Our approach is used to examine the functional recovery of damaged facial nerves in mice over a course of 21 days.

Keywords: mystacial macrovibrissae, whisker tracking, head tracking, facial nerve recovery

Procedia PDF Downloads 560
3181 Difference in the Expression of CIRBP, RBM3 and HSP70 in the Myocardium and Cerebellum after Death by Hypothermi a and Carbon Monoxide Poisoning

Authors: Satoshi Furukawa, Satomu Morita, Lisa Wingenfeld, Katsuji Nishi, Masahito Hitosugi

Abstract:

We studied the expression of hypoxia-related antigens (e.g., cold-inducible antigens and apoptotic antigens) in the myocardium and the cerebellumthat were obtained from individuals after death by carbon monoxide or hypothermia. The immunohistochemistry results revealed that expression of cold-inducible RNA binding protein (CIRBP) and RNA-binding protein 3 (RBM3) may be associated with hpyothermic and the hypoxic conditions. The expression of CIRBP and RBM3 in the myocardium was different from their expression in the cerebellum, especially in the Purkinje cells. The results indicate that agonal duration influences antigen expression. In the hypothermic condition, the myocardium uses more ATP since the force of the excitation-contraction coupling of the myocardium increases by more than 400% when the experimental temperature is reduced from 35°C to 25°C. The results obtained in this study indicate that physicians should pay attention to the myocardium when cooling the patient’s body to protect the brain.

Keywords: carbon monoxide death, cerebellum, CIRBP, hypothermic death, myocardium, RBM3

Procedia PDF Downloads 334
3180 Optimizing the Capacity of a Convolutional Neural Network for Image Segmentation and Pattern Recognition

Authors: Yalong Jiang, Zheru Chi

Abstract:

In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

Procedia PDF Downloads 122
3179 Energy Complementary in Colombia: Imputation of Dataset

Authors: Felipe Villegas-Velasquez, Harold Pantoja-Villota, Sergio Holguin-Cardona, Alejandro Osorio-Botero, Brayan Candamil-Arango

Abstract:

Colombian electricity comes mainly from hydric resources, affected by environmental variations such as the El Niño phenomenon. That is why incorporating other types of resources is necessary to provide electricity constantly. This research seeks to fill the wind speed and global solar irradiance dataset for two years with the highest amount of information. A further result is the characterization of the data by region that led to infer which errors occurred and offered the incomplete dataset.

Keywords: energy, wind speed, global solar irradiance, Colombia, imputation

Procedia PDF Downloads 113
3178 New Techniques to Decrease the Interfacial Stress in Steel Beams Strengthened With FRP Laminates

Authors: A. S. Bouchikhi, A. Megueni, S. Habibi

Abstract:

One major problem when using bonded Fiber Reinforced Polymer is the presence of high inter facial stresses near the end of the composite laminate which might govern the failure of the strengthening schedule. It is known that the decrease of FRP plate thickness and the fitness of adhesive reduce the stress concentration at plate ends. Another way is to use a plate with a non uniform section or tapered ends and softer adhesive at the edges. In this paper, a comprehensive finite element (FE) study has been conducted to investigate the effect of mixed adhesive joints (MAJ) and tapering plate on the inter facial stress distribution in the adhesive layer, this paper presents the results of a study of application of two adhesives with different stiffnesses (bi-adhesive) along the joint strength length between the CFRP-strengthened steel beam for tapered and untapered plate on the distribution of inter facial stresses. A stiff adhesive was applied in the middle portion of the joint strength, while a low modulus adhesive was applied towards the edges prone to stress concentrations.

Keywords: FRP, mixed adhesive joints, stresses, tapered plate, retrofitted beams bonded

Procedia PDF Downloads 466
3177 Dominant Ideology among Filipino Women as Dictated by Cosmopolitan Magazine

Authors: Yvonne Christelle M. de Guzman, Charity Faye T. Cabie

Abstract:

This study analyzed the contents of ten issues of Cosmopolitan Magazine from 2011 to 2015. The researcher found out the hegemony among Filipino women as dictated by Cosmopolitan magazine through the use of Semiotic Analysis, Laura Mulvey’s Male Gaze and Gramsci’s concept of hegemony. The researcher also looked at the themes of cover stories, words used to describe women, meanings behind the color of magazine’s front cover, clothing, physique and pose such as gesture and facial expression used by the cover girl. However, the entire content of the magazine was not taken into account.

Keywords: dominant ideology, male gaze, semiotics, women

Procedia PDF Downloads 360
3176 Innate Immune Expression in Heterophils in Response to LPS

Authors: Rohita Gupta, G. S. Brah, R. Verma, C. S. Mukhopadhayay

Abstract:

Although chicken strains show differences in susceptibility to a number of diseases, the underlying immunological basis is yet to be elucidated. In the present study, heterophils were subjected to LPS stimulation and total RNA extraction, further differential gene expression was studied in broiler, layer and indigenous Aseel strain by Real Time RT-PCR at different time periods before and after induction. The expression of the 14 AvBDs and chTLR 1, 2, 3, 4, 5, 7, 15 and 21 was detectable in heterophils. The expression level of most of the AvBDs significantly increased (P<0.05) 3 hours post in vitro lipopolysaccharide challenge. Higher expression level and stronger activation of most AvBDs, NFkB-1 and IRF-3 in heterophils was observed with the stimulation of LPS in layer compared to broiler, and in Aseel compared to both layer and broiler. This investigation will allow more refined interpretation of immuno-genetic basis of the variable disease resistance/susceptibility in divergent stock of chicken including indigenous breed. Moreover, this study will be helpful in formulation of strategy for isolation of antimicrobial peptides from heterophils.

Keywords: differential expression, heterophils, cytokines, defensin, TLR

Procedia PDF Downloads 468
3175 High-Resolution Facial Electromyography in Freely Behaving Humans

Authors: Lilah Inzelberg, David Rand, Stanislav Steinberg, Moshe David Pur, Yael Hanein

Abstract:

Human facial expressions carry important psychological and neurological information. Facial expressions involve the co-activation of diverse muscles. They depend strongly on personal affective interpretation and on social context and vary between spontaneous and voluntary activations. Smiling, as a special case, is among the most complex facial emotional expressions, involving no fewer than 7 different unilateral muscles. Despite their ubiquitous nature, smiles remain an elusive and debated topic. Smiles are associated with happiness and greeting on one hand and anger or disgust-masking on the other. Accordingly, while high-resolution recording of muscle activation patterns, in a non-interfering setting, offers exciting opportunities, it remains an unmet challenge, as contemporary surface facial electromyography (EMG) methodologies are cumbersome, restricted to the laboratory settings, and are limited in time and resolution. Here we present a wearable and non-invasive method for objective mapping of facial muscle activation and demonstrate its application in a natural setting. The technology is based on a recently developed dry and soft electrode array, specially designed for surface facial EMG technique. Eighteen healthy volunteers (31.58 ± 3.41 years, 13 females), participated in the study. Surface EMG arrays were adhered to participant left and right cheeks. Participants were instructed to imitate three facial expressions: closing the eyes, wrinkling the nose and smiling voluntary and to watch a funny video while their EMG signal is recorded. We focused on muscles associated with 'enjoyment', 'social' and 'masked' smiles; three categories with distinct social meanings. We developed a customized independent component analysis algorithm to construct the desired facial musculature mapping. First, identification of the Orbicularis oculi and the Levator labii superioris muscles was demonstrated from voluntary expressions. Second, recordings of voluntary and spontaneous smiles were used to locate the Zygomaticus major muscle activated in Duchenne and non-Duchenne smiles. Finally, recording with a wireless device in an unmodified natural work setting revealed expressions of neutral, positive and negative emotions in face-to-face interaction. The algorithm outlined here identifies the activation sources in a subject-specific manner, insensitive to electrode placement and anatomical diversity. Our high-resolution and cross-talk free mapping performances, along with excellent user convenience, open new opportunities for affective processing and objective evaluation of facial expressivity, objective psychological and neurological assessment as well as gaming, virtual reality, bio-feedback and brain-machine interface applications.

Keywords: affective expressions, affective processing, facial EMG, high-resolution electromyography, independent component analysis, wireless electrodes

Procedia PDF Downloads 220
3174 Incorporating Spatial Transcriptome Data into Ligand-Receptor Analyses to Discover Regional Activation in Cells

Authors: Eric Bang

Abstract:

Interactions between receptors and ligands are crucial for many essential biological processes, including neurotransmission and metabolism. Ligand-receptor analyses that examine cell behavior and interactions often utilize cell type-specific RNA expressions from single-cell RNA sequencing (scRNA-seq) data. Using CellPhoneDB, a public repository consisting of ligands, receptors, and ligand-receptor interactions, the cell-cell interactions were explored in a specific scRNA-seq dataset from kidney tissue and portrayed the results with dot plots and heat maps. Depending on the type of cell, each ligand-receptor pair was aligned with the interacting cell type and calculated the positori probabilities of these associations, with corresponding P values reflecting average expression values between the triads and their significance. Using single-cell data (sample kidney cell references), genes in the dataset were cross-referenced with ones in the existing CellPhoneDB dataset. For example, a gene such as Pleiotrophin (PTN) present in the single-cell data also needed to be present in the CellPhoneDB dataset. Using the single-cell transcriptomics data via slide-seq and reference data, the CellPhoneDB program defines cell types and plots them in different formats, with the two main ones being dot plots and heat map plots. The dot plot displays derived measures of the cell to cell interaction scores and p values. For the dot plot, each row shows a ligand-receptor pair, and each column shows the two interacting cell types. CellPhoneDB defines interactions and interaction levels from the gene expression level, so since the p-value is on a -log10 scale, the larger dots represent more significant interactions. By performing an interaction analysis, a significant interaction was discovered for myeloid and T-cell ligand-receptor pairs, including those between Secreted Phosphoprotein 1 (SPP1) and Fibronectin 1 (FN1), which is consistent with previous findings. It was proposed that an effective protocol would involve a filtration step where cell types would be filtered out, depending on which ligand-receptor pair is activated in that part of the tissue, as well as the incorporation of the CellPhoneDB data in a streamlined workflow pipeline. The filtration step would be in the form of a Python script that expedites the manual process necessary for dataset filtration. Being in Python allows it to be integrated with the CellPhoneDB dataset for future workflow analysis. The manual process involves filtering cell types based on what ligand/receptor pair is activated in kidney cells. One limitation of this would be the fact that some pairings are activated in multiple cells at a time, so the manual manipulation of the data is reflected prior to analysis. Using the filtration script, accurate sorting is incorporated into the CellPhoneDB database rather than waiting until the output is produced and then subsequently applying spatial data. It was envisioned that this would reveal wherein the cell various ligands and receptors are interacting with different cell types, allowing for easier identification of which cells are being impacted and why, for the purpose of disease treatment. The hope is this new computational method utilizing spatially explicit ligand-receptor association data can be used to uncover previously unknown specific interactions within kidney tissue.

Keywords: bioinformatics, Ligands, kidney tissue, receptors, spatial transcriptome

Procedia PDF Downloads 117
3173 Design of an Air and Land Multi-Element Expression Pattern of Navigation Electronic Map for Ground Vehicles under United Navigation Mechanism

Authors: Rui Liu, Pengyu Cui, Nan Jiang

Abstract:

At present, there is much research on the application of centralized management and cross-integration application of basic geographic information. However, the idea of information integration and sharing between land, sea, and air navigation targets is not deeply applied into the research of navigation information service, especially in the information expression. Targeting at this problem, the paper carries out works about the expression pattern of navigation electronic map for ground vehicles under air and land united navigation mechanism. At first, with the support from multi-source information fusion of GIS vector data, RS data, GPS data, etc., an air and land united information expression pattern is designed aiming at specific navigation task of emergency rescue in the earthquake. And then, the characteristics and specifications of the united expression of air and land navigation information under the constraints of map load are summarized and transferred into expression rules in the rule bank. At last, the related navigation experiment is implemented to evaluate the effect of the expression pattern. The experiment selects evaluation factors of the navigation task accomplishment time and the navigation error rate as the main index, and make comparisons with the traditional single information expression pattern. To sum up, the research improved the theory of navigation electronic map and laid a certain foundation for the design and realization of united navigation system in the aspect of real-time navigation information delivery.

Keywords: navigation electronic map, united navigation, multi-element expression pattern, multi-source information fusion

Procedia PDF Downloads 166
3172 The Role of Family’s Emotional Climate and Emotional Expression Style in Academic Well-Being of Students with Military Parent

Authors: Ala Rakhshandeh, Zahra Ashkar, Solmaz Dehghani Dolatabadi, Hossein Bayat

Abstract:

The present study has been conducted to investigate the role of family emotional climate and emotional expression style in the academic well-being of students with military parents. Children, including 280 female students of Shahriar police officers, were selected by random sampling method, and they have been investigated through Alfred B. Hillburn's family emotional climate questionnaire (1964), King and Ammon's emotional expression questionnaire (1990), and Pitrinen, Sweeney, and Falto's academic well-being questionnaire (2014). The data were analyzed using statistical methods of correlation coefficient and stepwise multiple regression under the SPSS23 program. The results reveal that the variables of family emotional climate and emotional expression can explain 36.4% of the variance in academic well-being. This finding reveals that with an increase of standard deviation on the scores of family emotional climate and emotional expression, 0.513 and 0.155 standard deviations are added to the scores of academic well-being, respectively. The emotional climate of the family has a superior distinctive role in predicting the educational well-being of female students. Thus, the emotional climate of the family and the style of emotional expression play a meaningful role in the academic well-being of students with the military parent.

Keywords: emotional climate, family, emotional expression style, academic well-being

Procedia PDF Downloads 73
3171 Keypoint Detection Method Based on Multi-Scale Feature Fusion of Attention Mechanism

Authors: Xiaoxiao Li, Shuangcheng Jia, Qian Li

Abstract:

Keypoint detection has always been a challenge in the field of image recognition. This paper proposes a novelty keypoint detection method which is called Multi-Scale Feature Fusion Convolutional Network with Attention (MFFCNA). We verified that the multi-scale features with the attention mechanism module have better feature expression capability. The feature fusion between different scales makes the information that the network model can express more abundant, and the network is easier to converge. On our self-made street sign corner dataset, we validate the MFFCNA model with an accuracy of 97.8% and a recall of 81%, which are 5 and 8 percentage points higher than the HRNet network, respectively. On the COCO dataset, the AP is 71.9%, and the AR is 75.3%, which are 3 points and 2 points higher than HRNet, respectively. Extensive experiments show that our method has a remarkable improvement in the keypoint recognition tasks, and the recognition effect is better than the existing methods. Moreover, our method can be applied not only to keypoint detection but also to image classification and semantic segmentation with good generality.

Keywords: keypoint detection, feature fusion, attention, semantic segmentation

Procedia PDF Downloads 93
3170 Speech Detection Model Based on Deep Neural Networks Classifier for Speech Emotions Recognition

Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

Abstract:

Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

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 71
3169 Lipopolysaccharide Induced Avian Innate Immune Expression in Heterophils

Authors: Rohita Gupta, G. S. Brah, R. Verma, C. S. Mukhopadhayay

Abstract:

Although chicken strains show differences in susceptibility to a number of diseases, the underlying immunological basis is yet to be elucidated. In the present study, heterophils were subjected to LPS stimulation and total RNA extraction, further differential gene expression was studied in broiler, layer and indigenous Aseel strain by Real Time RT-PCR at different time periods before and after induction. The expression of the 14 AvBDs and chTLR 1, 2, 3, 4, 5, 7, 15 and 21 was detectable in heterophils. The expression level of most of the AvBDs significantly increased (P<0.05) 3 hours post in vitro lipopolysaccharide challenge. Higher expression level and stronger activation of most AvBDs, NFkB-1 and IRF-3 in heterophils was observed, with the stimulation of LPS in layer compared to broiler, and in Aseel compared to both layer and broiler. This investigation will allow more refined interpretation of immuno-genetic basis of the variable disease resistance/susceptibility in divergent stock of chicken including indigenous breed. Moreover this study will be helpful in formulation of strategy for isolation of antimicrobial peptides from heterophils.

Keywords: differential expression, heterophils, cytokines, defensin, TLR

Procedia PDF Downloads 584
3168 Effect of TPA and HTLV-1 Tax on BRCA-1 and ERE Controlled Genes Expression

Authors: Azhar Jabareen, Mahmoud Huleihel

Abstract:

BRCA-1 is a multifunctional tumor suppressor, whose expression is activated by the estrogen (E2)-liganded ERα receptor. The activated ERα is a transcriptional factor which activates various genes either by direct binding to the DNA at E2-responsive elements (EREs) and indirectly associated with a range of alternative non-ERE elements. Interference with BRCA-1 expression and/or functions leads to high risk of breast or/and ovarian cancer. Our lab investigated the involvement of Human T-cell leukemia Virus Type 1 (HTLV-1) in breast cancer, since HTLV-1 Tax was found to strongly inhibit BRCA-1 expression. In addition, long exposure of 12-O-tetradecanoylphorbol-13-acetate (TPA), which is one of the stress-inducing agents activated the HTLV-1 promoter. So here the involvement of TPA in breast cancer had been examined by testing the effect of TPA on BRCA-1 and ERE expression. The results showed that TPA activated both BRCA-1 and ERE expression. In the 12 hours TPA activated the tow promoters more than others time, and after 24 hours the level of the tow promoters was decreased. Tax inhibited BRCA-1 expression but did not succeed to inhibit the effect of TPA. Then the activation of the two promoters was not through ERα pathway because TPA had no effect on ERα binding to the two promoters of the BRCA-1 and ERE. Also, the activation was not via nuclear factor kappa B (NF-κB) pathway because when the inhibitory of NF-κB had been added to the TPA, it still activated the tow promoters. However, it seems that 53BP1 may be involved in TPA activation of these promoters because ectopic high expression of 53BP1 significantly reduced the TPA activity. In addition, in the presence of Bisindolylmaleimide-I (BI)- the inhibitor of Protein Kinase C (PKC)- there was no activation for the two promoters, so the PKC is agonized BRCA-1 and ERE activation.

Keywords: BRCA-1, ERE, HTLV-1, TPA

Procedia PDF Downloads 215
3167 Investigation of FoxM1 Gene Expression in Breast Cancer and Its Relationship with miR-216b-5p Expression Level

Authors: Neda Menbari, Ramin Mehdiabadi

Abstract:

Background: breast cancer remains a critical global health issue, constituting a leading cause of cancer-related mortality in women. MicroRNAs (miRs) are natural RNA molecules that play an important role in cellular processes and regulate post-transcriptional gene expression. MiR-216b-5p is a miR that acts as a tumor suppressor. The expression levels of FoxM1 and miR-216b-5p in malignant and control cells have been evaluated by quantitative polymerase chain reaction (qPCR) technique and flow cytometry. Results: the results of this study revealed a significant downregulation of miR-216b-5p in cancerous cells compared to the control MCF-10A cells (P=0.0004). Interestingly, the expression of miR-216b-5p exhibited an inverse relationship with key clinical indicators such as tumor size, grade, and lymph node invasion. Conclusion: The study's findings showed the prognostic value of miR-216b-5p levels in breast cancer, and its reduced expression correlates with unfavorable tumor characteristics. This research recommends performing more studies on the role of FoxM1 and miR-216b-5p in breast cancer pathology which potentially paving the way for targeted therapeutic interventions.

Keywords: breast cancer, gene expression, FOXM1, microRNA

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3166 The Clustering of Multiple Sclerosis Subgroups through L2 Norm Multifractal Denoising Technique

Authors: Yeliz Karaca, Rana Karabudak

Abstract:

Multifractal Denoising techniques are used in the identification of significant attributes by removing the noise of the dataset. Magnetic resonance (MR) image technique is the most sensitive method so as to identify chronic disorders of the nervous system such as Multiple Sclerosis. MRI and Expanded Disability Status Scale (EDSS) data belonging to 120 individuals who have one of the subgroups of MS (Relapsing Remitting MS (RRMS), Secondary Progressive MS (SPMS), Primary Progressive MS (PPMS)) as well as 19 healthy individuals in the control group have been used in this study. The study is comprised of the following stages: (i) L2 Norm Multifractal Denoising technique, one of the multifractal technique, has been used with the application on the MS data (MRI and EDSS). In this way, the new dataset has been obtained. (ii) The new MS dataset obtained from the MS dataset and L2 Multifractal Denoising technique has been applied to the K-Means and Fuzzy C Means clustering algorithms which are among the unsupervised methods. Thus, the clustering performances have been compared. (iii) In the identification of significant attributes in the MS dataset through the Multifractal denoising (L2 Norm) technique using K-Means and FCM algorithms on the MS subgroups and control group of healthy individuals, excellent performance outcome has been yielded. According to the clustering results based on the MS subgroups obtained in the study, successful clustering results have been obtained in the K-Means and FCM algorithms by applying the L2 norm of multifractal denoising technique for the MS dataset. Clustering performance has been more successful with the MS Dataset (L2_Norm MS Data Set) K-Means and FCM in which significant attributes are obtained by applying L2 Norm Denoising technique.

Keywords: clinical decision support, clustering algorithms, multiple sclerosis, multifractal techniques

Procedia PDF Downloads 134
3165 Analysis of Expression Data Using Unsupervised Techniques

Authors: M. A. I Perera, C. R. Wijesinghe, A. R. Weerasinghe

Abstract:

his study was conducted to review and identify the unsupervised techniques that can be employed to analyze gene expression data in order to identify better subtypes of tumors. Identifying subtypes of cancer help in improving the efficacy and reducing the toxicity of the treatments by identifying clues to find target therapeutics. Process of gene expression data analysis described under three steps as preprocessing, clustering, and cluster validation. Feature selection is important since the genomic data are high dimensional with a large number of features compared to samples. Hierarchical clustering and K Means are often used in the analysis of gene expression data. There are several cluster validation techniques used in validating the clusters. Heatmaps are an effective external validation method that allows comparing the identified classes with clinical variables and visual analysis of the classes.

Keywords: cancer subtypes, gene expression data analysis, clustering, cluster validation

Procedia PDF Downloads 114
3164 An Improvement of ComiR Algorithm for MicroRNA Target Prediction by Exploiting Coding Region Sequences of mRNAs

Authors: Giorgio Bertolazzi, Panayiotis Benos, Michele Tumminello, Claudia Coronnello

Abstract:

MicroRNAs are small non-coding RNAs that post-transcriptionally regulate the expression levels of messenger RNAs. MicroRNA regulation activity depends on the recognition of binding sites located on mRNA molecules. ComiR (Combinatorial miRNA targeting) is a user friendly web tool realized to predict the targets of a set of microRNAs, starting from their expression profile. ComiR incorporates miRNA expression in a thermodynamic binding model, and it associates each gene with the probability of being a target of a set of miRNAs. ComiR algorithms were trained with the information regarding binding sites in the 3’UTR region, by using a reliable dataset containing the targets of endogenously expressed microRNA in D. melanogaster S2 cells. This dataset was obtained by comparing the results from two different experimental approaches, i.e., inhibition, and immunoprecipitation of the AGO1 protein; this protein is a component of the microRNA induced silencing complex. In this work, we tested whether including coding region binding sites in the ComiR algorithm improves the performance of the tool in predicting microRNA targets. We focused the analysis on the D. melanogaster species and updated the ComiR underlying database with the currently available releases of mRNA and microRNA sequences. As a result, we find that the ComiR algorithm trained with the information related to the coding regions is more efficient in predicting the microRNA targets, with respect to the algorithm trained with 3’utr information. On the other hand, we show that 3’utr based predictions can be seen as complementary to the coding region based predictions, which suggests that both predictions, from 3'UTR and coding regions, should be considered in a comprehensive analysis. Furthermore, we observed that the lists of targets obtained by analyzing data from one experimental approach only, that is, inhibition or immunoprecipitation of AGO1, are not reliable enough to test the performance of our microRNA target prediction algorithm. Further analysis will be conducted to investigate the effectiveness of the tool with data from other species, provided that validated datasets, as obtained from the comparison of RISC proteins inhibition and immunoprecipitation experiments, will be available for the same samples. Finally, we propose to upgrade the existing ComiR web-tool by including the coding region based trained model, available together with the 3’UTR based one.

Keywords: AGO1, coding region, Drosophila melanogaster, microRNA target prediction

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3163 Correlation of P53 Gene Expression With Serum Alanine Transaminase Levels and Hepatitis B Viral Load in Cirrhosis and Hepatocellular Carcinoma Patients

Authors: Umme Shahera, Saifullah Munshi, Munira Jahan, Afzalun Nessa, Shahinul Alam, Shahina Tabassum

Abstract:

The development of HCC is a multi-stage process. Several extrinsic factors, such as aflatoxin, HBV, nutrition, alcohol, and trace elements are thought to initiate or/and promote the hepatocarcinogenesis. Alteration of p53 status is an important intrinsic factor in this process as p53 is essential for preventing inappropriate cell proliferation and maintaining genome integrity following genotoxic stress. This study was designed to assess the correlation of p53 gene expression with HBV-DNA and serum Alanine transaminase (ALT) in patients with cirrhosis and HCC. The study was conducted among 60 patients. The study population were divided into four groups (15 in each groups)-HBV positive cirrhosis, HBV negative cirrhosis, HBV positive HCC and HBV negative HCC. Expression of p53 gene was observed using real time PCR. P53 gene expressions in the above mentioned groups were correlated with serum ALT level and HBV viral load. p53 gene was significantly higher in HBV-positive patients with HCC than HBV-positive cirrhosis. Similarly, the expression of p53 was significantly higher in HBV-positive HCC than HBV-negative HCC patients. However, the expression of p53 was reduced in HBV-positive cirrhosis in comparison with HBV-negative cirrhosis. P53 gene expression in liver was not correlated with the serum levels of ALT in any of the study groups. HBV- DNA load also did not correlated with p53 gene expression in HBV positive HCC and HBV positive cirrhosis patients. This study shows that there was no significant change with the expression of p53 gene in any of the study groups with ALT level or viral load, though differential expression of p53 gene were observed in cirrhosis and HCC patients.

Keywords: P53, ALT, HBV-DNA, liver cirrhosis, hepatocellular carcinoma

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3162 Expression Regulation of Membrane Protein by Codon Variation of Amino Acid at N-Terminal Region

Authors: Ahreum Choi, Otgontuya Tsogbadrakh, Kwang-Hwan Jung

Abstract:

Microbial rhodopsins are well-known seven-transmembrane proteins that have been extensively studied. These retinal-binding proteins have divided into two types. The type I is microbial rhodopsin, and type II (visual pigment) is expressed mostly in mammalian eyes. For type I rhodopsin, there are two main functions that are ion pumping activity and sensory transduction. Anabaena sensory rhodopsin (ASR) is one of the microbial rhodopsin with main function as photo-sensory transduction. Although ASR is expressed fairly well in Escherichia coli, the expression level is relatively less compare to Proteorhodopsin. In this study, full length of ASR was used to test for the expression influence by codon usage in E. coli. Eight amino acids of codon at N-terminal part of ASR were changed randomly with designed primers, which allow 8,192 nucleotide different cases. The codon changes were screened for the preferable codons of each residue, which have given higher expression yield. Among those 57 selected mutations, there are 24 color-enhanced E. coli colonies that contain ASR proteins, and it showed better expression level than the wild type ASR codon usage. This strongly suggests that high codon usage of only partial N-terminal of protein can increase the expression level of whole protein.

Keywords: 7-transmembrane, all-trans retinal, rhodopsin, codon-usage, protein expression

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3161 Attenuation of Homocysteine-Induced Cyclooxygenase-2 Expression in Human Monocytes by Fulvic Acid

Authors: Shao-Ju Chien, Yi-Chien Wu, Ting-Ying Huang, Li-Tsen Li, You-Jin Chen, Cheng-Nan Chen

Abstract:

Homocysteine and pro-inflammatory mediators such as cyclooxygenase-2 (COX-2) have been linked to vascular dysfunction and risks of cardiovascular diseases. Fulvic acid (FA) is class of compounds of humic substances and possesses various pharmacological properties. However, the effect of FA on inflammatory responses of the monocytes remains unclear. We investigated the regulatory effect of FA on homocysteine-induced COX-2 expression in human monocytes. Peripheral blood monocytes and U937 cells were kept as controls or pre-treated with FA, and then stimulated with homocysteine. The results show that pretreating monocytes with FA inhibited the homocysteine-induced COX-2 expression in a dose-dependent manner. The inhibitor for nuclear factor-kB (NF-kB) attenuated homocysteine-induced COX-2 expression. Our findings provide a molecular mechanism by which FA inhibit homocysteine-induced COX-2 expression in monocytes, and a basis for using FA in pharmaceutical therapy against inflammation.

Keywords: homocysteine, monocytes, cyclooxygenase-2, fulvic acid, anti-inflammation

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3160 Evaluate the Changes in Stress Level Using Facial Thermal Imaging

Authors: Amin Derakhshan, Mohammad Mikaili, Mohammad Ali Khalilzadeh, Amin Mohammadian

Abstract:

This paper proposes a stress recognition system from multi-modal bio-potential signals. For stress recognition, Support Vector Machines (SVM) and LDA are applied to design the stress classifiers and its characteristics are investigated. Using gathered data under psychological polygraph experiments, the classifiers are trained and tested. The pattern recognition method classifies stressful from non-stressful subjects based on labels which come from polygraph data. The successful classification rate is 96% for 12 subjects. It means that facial thermal imaging due to its non-contact advantage could be a remarkable alternative for psycho-physiological methods.

Keywords: stress, thermal imaging, face, SVM, polygraph

Procedia PDF Downloads 455
3159 ALDH1A1 as a Cancer Stem Cell Marker: Value of Immunohistochemical Expression in Benign Prostatic Hyperplasia, Prostatic Intraepithelial Neoplasia, and Prostatic Adenocarcinoma

Authors: H. M. Abdelmoneim, N. A. Babtain, A. S. Barhamain, A. Z. Kufiah, A. S. Malibari, S. F. Munassar, R. S. Rawa

Abstract:

Introduction: Prostate cancer is one of the most common causes of morbidity and mortality in men in developed countries. Cancer Stem Cells (CSCs) could be responsible for the progression and relapse of cancer. Therefore, CSCs markers could provide a prognostic strategy for human malignancies. Aldehyde dehydrogenase 1A1 (ALDH1A1) activity has been shown to be associated with tumorigenesis and proposed to represent a functional marker for tumor initiating cells in various tumor types including prostate cancer. Material & Methods: We analyzed the immunohistochemical expression of ALDH1A1 in benign prostatic hyperplasia (BPH), prostatic intraepithelial neoplasia (PIN) and prostatic adenocarcinoma and assessed their significant correlations in 50 TURP sections. They were microscopically interpreted and the results were correlated with histopathological types and tumor grade. Results: In different prostatic histopathological lesions we found that ALDH1A1 expression was low in BPH (13.3%) and PIN (6.7%) and then its expression increased with prostatic adenocarcinoma (40%), and this was statistically highly significant (P value = 0.02). However, in different grades of prostatic adenocarcinoma we found that the higher the Gleason grade the higher the expression for ALDH1A1 and this was statistically significant (P value = 0.02). We compared the expression of ALDH1A1 in PIN and prostatic adenocarcinoma. ALDH1A1 expression was decreased in PIN and highly expressed in prostatic adenocarcinoma and this was statistically significant (P value = 0.04). Conclusion: Increasing ALDH1A1 expression is correlated with aggressive behavior of the tumor. Immunohistochemical expression of ALDH1A1 might provide a potential approach to study tumorigenesis and progression of primary prostate carcinoma.

Keywords: ALDH1A1, BPH, PIN, prostatic adenocarcinoma

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3158 Data Augmentation for Automatic Graphical User Interface Generation Based on Generative Adversarial Network

Authors: Xulu Yao, Moi Hoon Yap, Yanlong Zhang

Abstract:

As a branch of artificial neural network, deep learning is widely used in the field of image recognition, but the lack of its dataset leads to imperfect model learning. By analysing the data scale requirements of deep learning and aiming at the application in GUI generation, it is found that the collection of GUI dataset is a time-consuming and labor-consuming project, which is difficult to meet the needs of current deep learning network. To solve this problem, this paper proposes a semi-supervised deep learning model that relies on the original small-scale datasets to produce a large number of reliable data sets. By combining the cyclic neural network with the generated countermeasure network, the cyclic neural network can learn the sequence relationship and characteristics of data, make the generated countermeasure network generate reasonable data, and then expand the Rico dataset. Relying on the network structure, the characteristics of collected data can be well analysed, and a large number of reasonable data can be generated according to these characteristics. After data processing, a reliable dataset for model training can be formed, which alleviates the problem of dataset shortage in deep learning.

Keywords: GUI, deep learning, GAN, data augmentation

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3157 Comparison between Effects of Free Curcumin and Curcumin Loaded NIPAAm-MAA Nanoparticles on Telomerase and Pinx1 Gene Expression in Lung Cancer Cells

Authors: Y. Pilehvar-Soltanahmadi, F. Badrzadeh, N. Zarghami, S. Jalilzadeh-Tabrizi, R. Zamani

Abstract:

Herbal compounds such as curcumin which decrease telomerase and gene expression have been considered as beneficial tools for lung cancer treatment. In this article, we compared the effects of pure curcumin and curcumin-loaded NIPAAm-MAA nanoparticles on telomerase and PinX1 gene expression in a lung cancer cell line. A tetrazolium-based assay was used for determination of cytotoxic effects of curcumin on the Calu-6 lung cancer cell line and telomerase and pinX1 gene expression was measured with real-time PCR. MTT assay showed that Curcumin-loaded NIPAAm-MAA inhibited the growth of the Calu-6 lung cancer cell line in a time and dose-dependent manner. Our q-PCR results showed that the expression of telomerase gene was effectively reduced as the concentration of curcumin-loaded NIPAAm-MAA increased while expression of the PinX1 gene became elevated. The results showed that curcumin loaded NIPAAm-MAA exerted cytotoxic effects on the Calu-6 cell line through down-regulation of telomerase and stimulation of pinX1 gene expression. NIPPAm-MAA could be the good carrier for such kinds of hydrophobic agent.

Keywords: curcumin, NIPAAm-MAA, PinX1, telomerase, lung cancer cells

Procedia PDF Downloads 275