Search results for: annotated facial expression dataset

Authors: Azar Heidarizadi, Mahdieh Salimi, Hossein Mozdarani

Abstract:

Introduction: As a complex disease, breast cancer results from several genetic and epigenetic changes. Lactoferrin, a member of the transferrin family, is reported to have a number of biological functions, including DNA synthesis, immune responses, iron transport, etc., any of which could play a role in tumor progression. This study aimed to investigate the bioinformatics data and experimental assay to find the pattern of promoter methylation and gene expression of LTF in breast cancer to study its potential role in cancer management. Material and Methods: To evaluate the LTF promoter's methylation status, we studied the MS-PCR and Real-Time PCR on samples from patients with breast cancer and normal cases. This study includes 67 patient samples, including tumoral, plasma, and normal tissue adjacent samples, as well as 30 plasma samples from standard cases and 10 tissue samples of breast reduction cases. Subsequently, bioinformatics analyses such as cBioPortal databases, string, and geomatics were conducted to disclose the prognostic value of LTF in breast cancer progression. Results: The analysis of LTF expression showed an inverse relationship between the expression level of LTF and the stages of tissues of breast cancer patients (p<0.01). In fact, stages 1 and 2 had a high expression in LTF, while, in stages 3 and 4, a significant reduction was observable (p < 0.0001). LTF expression frequently alters with a decrease in the expression in ER+, PR+, and HER2+ patients (P < 0.01) and an increase in the expression in the TNBC, LN¯, ER¯, and PR- patients (P < 0.001). Also, LTF expression is significantly associated with metastasis and lymph node involvement factors (P < 0.0001). The sensitivity and specificity of LTF were detected, respectively. A negative correlation was detected between the results of level expression and methylation of the LTF promoter. Conclusions: The altered expression of LTF observed in breast cancer patients could be considered as a promotion in cell proliferation and metastasis even in the early stages of cancer.

Keywords: LTF, expression, methylation, breast cancer

Procedia PDF Downloads 24

Authors: Billel Kenidra, Mohamed Benmohammed

Abstract:

Data mining technique used in the field of clustering is a subject of active research and assists in biological pattern recognition and extraction of new knowledge from raw data. Clustering means the act of partitioning an unlabeled dataset into groups of similar objects. Each group, called a cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. Several clustering methods are based on partitional clustering. This category attempts to directly decompose the dataset into a set of disjoint clusters leading to an integer number of clusters that optimizes a given criterion function. The criterion function may emphasize a local or a global structure of the data, and its optimization is an iterative relocation procedure. The K-Means algorithm is one of the most widely used partitional clustering techniques. Since K-Means is extremely sensitive to the initial choice of centers and a poor choice of centers may lead to a local optimum that is quite inferior to the global optimum, we propose a strategy to initiate K-Means centers. The improved K-Means algorithm is compared with the original K-Means, and the results prove how the efficiency has been significantly improved.

Keywords: microarray data mining, biological pattern recognition, partitional clustering, k-means algorithm, centroid initialization

Procedia PDF Downloads 161

Authors: Mustafa Oz

Abstract:

This study compares how do people express their opinions on the Facebook versus on Twitter. It was sought to understand whether people were more willing to express their opinions on some social media channels than others. It was assumed that fear of isolation and affordances may influence users’ opinion expression behaviors on social media websites. Thus two most popular social media websites, Twitter and Facebook, were compared. This study aims to provide the comprehensive understanding of political expression on social media platforms. An online survey (N=535) was conducted to understand respondents’ opinion expression behaviors. Overall, the results suggested that people were more likely to express their opinion on Twitter than Facebook when they think the majority does not support their opinion. The study concluded that people operate differently on Facebook versus Twitter.

Keywords: social media, spiral of silence, affordances, political expression

Procedia PDF Downloads 110

Authors: André Augusto Ceballos Melo

Abstract:

Design to facilitate the recognition of congruent prosthetic movements, context-to-motion translations guided by image, verbal prompt, users nonverbal communication such as facial expressions, gestures, paralinguistics, scene context, and object recognition contributes to this process though it can also be applied to other tasks, such as walking, Prosthetic limbs as assistive technology through gestures, sound codes, signs, facial, body expressions, and scene context The context-to-motion model is a machine learning approach that is designed to improve the control and dexterity of prosthetic limbs. It works by using sensory input from the prosthetic limb to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. This can help to improve the performance of the prosthetic limb and make it easier for the user to perform a wide range of tasks. There are several key benefits to using the context-to-motion model for prosthetic limb control. First, it can help to improve the naturalness and smoothness of prosthetic limb movements, which can make them more comfortable and easier to use for the user. Second, it can help to improve the accuracy and precision of prosthetic limb movements, which can be particularly useful for tasks that require fine motor control. Finally, the context-to-motion model can be trained using a variety of different sensory inputs, which makes it adaptable to a wide range of prosthetic limb designs and environments. Stable diffusion is a machine learning method that can be used to improve the control and stability of movements in robotic and prosthetic systems. It works by using sensory feedback to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. One key aspect of stable diffusion is that it is designed to be robust to noise and uncertainty in the sensory feedback. This means that it can continue to produce stable, smooth movements even when the sensory data is noisy or unreliable. To implement stable diffusion in a robotic or prosthetic system, it is typically necessary to first collect a dataset of examples of the desired movements. This dataset can then be used to train a machine learning model to predict the appropriate control inputs for a given set of sensory observations. Once the model has been trained, it can be used to control the robotic or prosthetic system in real-time. The model receives sensory input from the system and uses it to generate control signals that drive the motors or actuators responsible for moving the system. Overall, the use of the context-to-motion model has the potential to significantly improve the dexterity and performance of prosthetic limbs, making them more useful and effective for a wide range of users Hand Gesture Body Language Influence Communication to social interaction, offering a possibility for users to maximize their quality of life, social interaction, and gesture communication.

Keywords: stable diffusion, neural interface, smart prosthetic, augmenting

Procedia PDF Downloads 71

Authors: Avyarthana Dey, Naren P. Rao, Arpitha Jacob, Chaitra V. Hiremath, Shivarama Varambally, Ganesan Venkatasubramanian, Rose Dawn Bharath, Bangalore N. Gangadhar

Abstract:

Objective: Impaired facial emotion recognition is widely reported in schizophrenia. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. However, its effect on facial emotion recognition deficits seen in schizophrenia is not well explored. In this study, we examined the effect of intranasal OXT on processing facial emotions and its neural correlates in patients with schizophrenia. Method: 12 male patients (age= 31.08±7.61 years, education= 14.50±2.20 years) participated in this single-blind, counterbalanced functional magnetic resonance imaging (fMRI) study. All participants underwent three fMRI scans; one at baseline, one each after single dose 24IU intranasal OXT and intranasal placebo. The order of administration of OXT and placebo were counterbalanced and subject was blind to the drug administered. Participants performed a facial emotion recognition task presented in a block design with six alternating blocks of faces and shapes. The faces depicted happy, angry or fearful emotions. The images were preprocessed and analyzed using SPM 12. First level contrasts comparing recognition of emotions and shapes were modelled at individual subject level. A group level analysis was performed using the contrasts generated at the first level to compare the effects of intranasal OXT and placebo. The results were thresholded at uncorrected p < 0.001 with a cluster size of 6 voxels. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. Results: Compared to placebo, intranasal OXT attenuated activity in inferior temporal, fusiform and parahippocampal gyri (BA 20), premotor cortex (BA 6), middle frontal gyrus (BA 10) and anterior cingulate gyrus (BA 24) and enhanced activity in the middle occipital gyrus (BA 18), inferior occipital gyrus (BA 19), and superior temporal gyrus (BA 22). There were no significant differences between the conditions on the accuracy scores of emotion recognition between baseline (77.3±18.38), oxytocin (82.63 ± 10.92) or Placebo (76.62 ± 22.67). Conclusion: Our results provide further evidence to the modulatory effect of oxytocin in patients with schizophrenia. Single dose oxytocin resulted in significant changes in activity of brain regions involved in emotion processing. Future studies need to examine the effectiveness of long-term treatment with OXT for emotion recognition deficits in patients with schizophrenia.

Keywords: recognition, functional connectivity, oxytocin, schizophrenia, social cognition

Procedia PDF Downloads 186

Authors: Bingquan Shen

Abstract:

Convolutional Neural Networks (CNN) have demonstrated their effectiveness in synthesizing 3D views of object instances at various viewpoints. Given the problem where one have limited viewpoints of a particular object for classification, we present a pose normalization architecture to transform the object to existing viewpoints in the training dataset before classification to yield better classification performance. We have demonstrated that this Pose Normalization Network (PNN) can capture the style of the target object and is able to re-render it to a desired viewpoint. Moreover, we have shown that the PNN improves the classification result for the 3D chairs dataset and ShapeNet airplanes dataset when given only images at limited viewpoint, as compared to a CNN baseline.

Keywords: convolutional neural networks, object classification, pose normalization, viewpoint invariant

Procedia PDF Downloads 307

Authors: Sanjay Adhikesaven

Abstract:

Workplace accidents are a critical problem that causes many deaths, injuries, and financial losses. Climate change has a severe impact on industrial workers, partially caused by global warming. To reduce such casualties, it is important to proactively find unsafe environments where injuries could occur by detecting the use of personal protective equipment (PPE) and identifying unsafe activities. Thus, we propose an industrial workplace alerting and monitoring platform to detect PPE use and classify unsafe activity in group settings involving multiple humans and objects over a long period of time. Our proposed method is the first to analyze prolonged actions involving multiple people or objects. It benefits from combining pose estimation with PPE detection in one platform. Additionally, we propose the first open-source annotated data set with video data from industrial workplaces annotated with the action classifications and detected PPE. The proposed system can be implemented within the surveillance cameras already present in industrial settings, making it a practical and effective solution.

Keywords: computer vision, deep learning, workplace safety, automation

Procedia PDF Downloads 77

Authors: Isa Moazen, Ali Nahvi

Abstract:

Driver drowsiness is a major cause of vehicle accidents, and facial images are highly valuable to detect drowsiness. In this paper, we perform our research via a thermal camera to record drivers' facial images on a driving simulator. A robust real-time algorithm extracts the features using horizontal and vertical integration projection, contours, contour orientations, and cropping tools. The features are included four target areas on the cheeks and forehead. Qt compiler and OpenCV are used with two cameras with different resolutions. A high-resolution thermal camera is used for fifteen subjects, and a low-resolution one is used for a person. The results are investigated by four temperature plots and evaluated by observer rating of drowsiness.

Keywords: advanced driver assistance systems, thermal imaging, driver drowsiness detection, feature extraction

Procedia PDF Downloads 101

Authors: Hsin-Yang Wang, K. M. A. Salam, Ying-Jia Lin, Daniel Tan, Tzu-Hsuan Chou, Hung-Yu Kao

Abstract:

Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo.

Keywords: OSML, BERT, text classification, one shot

Procedia PDF Downloads 79

Authors: Chang Liang, Weizhi Gong, Yan Zhang

Abstract:

Purpose: Hepatocellular carcinoma (HCC) is a malignant tumor with a high mortality rate and poor prognosis worldwide. Murine double minute 2 (MDM2) regulates the tumor suppressor p53, increasing cancer risk and accelerating tumor progression. Speckle-type POX virus and zinc finger protein (SPOP), a key of subunit of Cullin-Ring E3 ligase, inhibits tumor genesis and progression by the ubiquitination of its downstream substrates. This study aimed to clarify whether SPOP and MDM2 are mutually regulated in HCC and the correlation between SPOP and MDM2 and the prognosis of HCC patients. Methods: First, the expression of SPOP and MDM2 in HCC tissues were detected by TCGA database. Then, 53 paired samples of HCC tumor and adjacent tissues were collected to evaluate the expression of SPOP and MDM2 using immunohistochemistry. Chi-square test or Fisher’s exact test were used to analyze the relationship between clinicopathological features and the expression levels of SPOP and MDM2. In addition, Kaplan‒Meier curve analysis and log-rank test were used to investigate the effects of SPOP and MDM2 on the survival of HCC patients. Last, the Multivariate Cox proportional risk regression model analyzed whether the different expression levels of SPOP and MDM2 were independent risk factors for the prognosis of HCC patients. Results: Bioinformatics analysis revealed the low expression of SPOP and high expression of MDM2 were related to worse prognosis of HCC patients. The relationship between the expression of SPOP and MDM2 and tumor stem-like features showed an opposite trend. The immunohistochemistry showed the expression of SPOP protein was significantly downregulated while MDM2 protein significantly upregulated in HCC tissue compared to that in para-cancerous tissue. Tumors with low SPOP expression were related to worse T stage and Barcelona Clinic Liver Cancer (BCLC) stage, but tumors with high MDM2 expression were related to worse T stage, M stage, and BCLC stage. Kaplan–Meier curves showed HCC patients with high SPOP expression and low MDM2 expression had better survival than those with low SPOP expression and high MDM2 expression (P < 0.05). A multivariate Cox proportional risk regression model confirmed that a high MDM2 expression level was an independent risk factor for poor prognosis in HCC patients (P <0.05). Conclusion: The expression of SPOP protein was significantly downregulated, while the expression of MDM2 significantly upregulated in HCC. The low expression of SPOP and high expression. of MDM2 were associated with malignant progression and poor prognosis of HCC patients, indicating a potential therapeutic target for HCC patients.

Keywords: hepatocellular carcinoma, murine double minute 2, speckle-type POX virus and zinc finger protein, ubiquitination

Procedia PDF Downloads 104

Authors: Ali Dulla

Abstract:

This paper introduces a new dataset (and the methodology used to generate it) based on a wide range of historical Arabic documents containing clean data simple and homogeneous-page layouts. The experiments are implemented on printed and handwritten documents obtained respectively from some important libraries such as Qatar Digital Library, the British Library and the Library of Congress. We have gathered and commented on 150 archival document images from different locations and time periods. It is based on different documents from the 17th-19th century. The dataset comprises differing page layouts and degradations that challenge text line segmentation methods. Ground truth is produced using the Aletheia tool by PRImA and stored in an XML representation, in the PAGE (Page Analysis and Ground truth Elements) format. The dataset presented will be easily available to researchers world-wide for research into the obstacles facing various historical Arabic documents such as geometric correction of historical Arabic documents.

Keywords: dataset production, ground truth production, historical documents, arbitrary warping, geometric correction

Procedia PDF Downloads 145

Authors: Dalia M. Abouelfadl, Noha N. Yassen, Marwa E. Shabana

Abstract:

Background: The evolution of immune therapy motivated many to study the relation between immune response and progression of cancer. Little is known about expression of PD-L1 (a newly evolving immunotherapeutic drug) in papillary thyroid carcinoma (PTC) arising de-novo and PTC arising on top of autoimmune thyroiditis (Hashimoto's (HT) and lymphocytic thyroiditis (LT)). The aim of this work is to study the alteration of expression of PD-L1 in PTCs arising from de-novo or on top of HT OR LT using immunohistochemistry and image analyser system. Method: 100 paraffin blocks for PTC cases were collected retrospectively for staining using PD-L1 rabbit monoclonal antibody (BIOCARE-ACI 3171 A, C). The antibody expression is measured digitally using Image Analyzer Leica Qwin 3000, and the membranous and cytoplasmic expression of PD-L1 in tumor cells was considered positive. The results were correlated with tumor grade, size, and LN status. Results: The study samples consisted of 41 cases of PTC arising De novo, 36 cases on top of HT, and 23 on top of LT. Expression of PD-L1 was highest among the PTC-HL group (25 case-69%) followed by PTC-TL group (14 case-60.8%) then de-novo PTC (19 case-46%) with P Value < 0.05. PD-L1 expression correlated with nodal metastasis and was not relevant to tumor size or grade. Conclusion: The severity of the immune response in tumor microenvironment directly influences PTC prognosis. The anti PD-L1 Ab can be a very successful therapeutic agent for PTC arising on top of HT.

Keywords: carcinoma, Hashimoto's, lymphocytic, papillary, PD-L1, thyroiditis

Procedia PDF Downloads 151

Authors: Aleya Ferdausi, Meriel Jones, Anthony Halls

Abstract:

The Amaryllidaceae genus Narcissus contains secondary metabolites, which are important sources of bioactive compounds such as pharmaceuticals indicating that their biological activity extends from the native plant to humans. Transcriptome analysis (RNA-seq) is an effective platform for the identification and functional characterization of candidate genes as well as to identify genes encoding uncharacterized enzymes. The biotechnological production of secondary metabolites in plant cell or organ cultures has become a tempting alternative to the extraction of whole plant material. The biochemical pathways for the production of secondary metabolites require primary metabolites to undergo a series of modifications catalyzed by enzymes such as cytochrome P450s, methyltransferases, glycosyltransferases, and acyltransferases. Differential gene expression analysis of Narcissus was obtained from two conditions, i.e. field and in vitro callus. Callus was obtained from modified MS (Murashige and Skoog) media supplemented with growth regulators and twin-scale explants from Narcissus cv. Carlton bulb. A total of 2153 differentially expressed transcripts were detected in Narcissus bulb and in vitro callus, and 78.95% of those were annotated. It showed the expression of genes involved in the biosynthesis of alkaloids were present in both conditions i.e. cytochrome P450s, O-methyltransferase (OMTs), NADP/NADPH dehydrogenases or reductases, SAM-synthetases or decarboxylases, 3-ketoacyl-CoA, acyl-CoA, cinnamoyl-CoA, cinnamate 4-hydroxylase, alcohol dehydrogenase, caffeic acid, N-methyltransferase, and NADPH-cytochrome P450s. However, cytochrome P450s and OMTs involved in the later stage of Amaryllidaceae alkaloids biosynthesis were mainly up-regulated in field samples. Whereas, the enzymes involved in initial biosynthetic pathways i.e. fructose biphosphate adolase, aminotransferases, dehydrogenases, hydroxyl methyl glutarate and glutamate synthase leading to the biosynthesis of precursors; tyrosine, phenylalanine and tryptophan for secondary metabolites were up-regulated in callus. The knowledge of probable genes involved in secondary metabolism and their regulation in different tissues will provide insight into the Narcissus plant biology related to alkaloid production.

Keywords: narcissus, callus, transcriptomics, secondary metabolites

Procedia PDF Downloads 114

Authors: Ankita Shukla, Tiratha Raj Singh

Abstract:

Colorectal cancer (CRC) imposes serious mortality burden worldwide and it has been increasing for past consecutive years. Continuous efforts have been made so far to diagnose the disease condition and to identify the root cause for it. In this study, we performed the pathway level as well as the differential gene expression studies for CRC. We analyzed the gene expression profile GSE24514 from Gene Expression Omnibus (GEO) along with the gene pathways involved in the CRC. This analysis helps us to understand the behavior of the genes that have shown differential expression through their targeted pathways. Pathway analysis for the targeted genes covers the wider area which therefore decreases the possibility to miss the significant ones. This will prove to be beneficial to expose the ones that have not been given attention so far. Through this analysis, we attempt to understand the various neighboring genes that have close relationship to the targeted one and thus proved to be significantly controlling the CRC. It is anticipated that the identified hub and neighboring genes will provide new directions to look at the pathway level differently and will be crucial for the regulatory processes of the disease.

Keywords: mismatch repair, microsatellite instability, carcinogenesis, morbidity

Procedia PDF Downloads 293

Authors: Ali Asghar Saki, Sayed Ali Hosseini Siyar, Abbass Ashoori

Abstract:

This study was conducted to evaluate the effect of Echinacea purpurea on the expression of cyclooxygenase-2 (COX-2), interleukin-17F (IL-17F) in seven-day-old broiler chickens. Four groups were fed with concentration of 0 g/kg, 5 g/kg, 10 g/kg and 20 g/kg from the root of E. purpurea in the basal diet and two other groups were only fed with the basal diet for 21 days. At the 28^th day, lipopolysaccharide (LPS, 2 mg/kg diet) was injected in four groups and the basal diet group was injected by saline as control. The chickens’ spleen RNA expression was measured for the COX-2 and IL-17F genes by Real-Time PCR. The results have shown that chickens which were fed E. purpurea had a lower COX-2 and IL-17F mRNA expression. The chickens who have received LPS only, lymphocyte was lower than other treatments. Vital organ weights were not significantly different, but body weight loss was recovered by dietary herbs inclusion. The results of this study have shown the positive effect of an anti-inflammatory herb to prevent the undesirable effect of inflammation.

Keywords: broiler chickens, Echinacea purporea, gene expression, lipopolysaccharide

Procedia PDF Downloads 201

Authors: Mohamad R. Moshtagh, Ahmad Bagheri

Abstract:

Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

Procedia PDF Downloads 49

Authors: Raju Ranjha, Surbhi Aggarwal

Abstract:

Background: Inflammation plays an important role in infectious and non-infectious diseases. MiRNA is also reported to play role in inflammation and associated cancers. Chemokine CXCL12 is also known to play role in inflammation and various cancers. CXCL12/CXCR4 chemokine axis was involved in pathogenesis of IBD specially UC. Supplementation of CXCL12 induces homing of dendritic cells to spleen and enhances control of plasmodium parasite in BALB/c mice. We looked at the regulation of CXCL12β by miRNA in UC colitis. Prolonged inflammation of colon in UC patient increases the risk of developing colorectal cancer. We looked at the expression differences of CXCl12β and its targeting miRNA in cancer susceptible area of colon of UC patients. Aim: Aim of this study was to find out the expression regulation of CXCL12β by miRNA in inflammation. Materials and Methods: Biopsy samples and blood samples were collected from UC patients and non-IBD controls. mRNA expression was analyzed using microarray and real-time PCR. CXCL12β targeting miRNA were looked by using online target prediction tools. Expression of CXCL12β in blood samples and cell line supernatant was analyzed using ELISA. miRNA target was validated using dual luciferase assay. Results and conclusion: We found miR-200a regulate the expression of CXCL12β in UC. Expression of CXCL12β was increased in cancer susceptible part of colon and expression of its targeting miRNA was decreased in the same part of colon. miR-200a regulate CXCL12β expression in inflammation and may be an important therapeutic target in inflammation associated cancer.

Keywords: inflammation, miRNA, regulation, CXCL12

Procedia PDF Downloads 242

Authors: Sehmus Aslan, Sibel Karacaoglu, Cengiz Sevgin, Ummuhan Bas Aslan

Abstract:

Objective: Anger expression style is an important moderator of the effects on the person and person’s environment. Anger and anger expression have become important constructs in identifying individuals at high risk for psychological difficulties. To our knowledge, there is no information about anger and anger expression of adolescents with visual impairment. The aim of this study was to compare anger and anger expression among adolescents with and without visual impairment. Methods: Thirty-eight adolescents with visual impairment (18 female, 20 male) and 44 adolescents without visual impairment (22 female, 24 male), in totally 84 adolescents aged between 12 to 15 years, participated in the study. Anger and anger expression of the participants assessed with The State-Trait Anger Scale (STAS). STAS, a self-report questionnaire, is designed to measure the experience and expression of anger. STAS has four subtitles including continuous anger, anger in, anger out and anger control. Reliability and validity of the STAS have been well established among adolescents. Mann-Whitney U Test was used for statistical analysis. Results: No significant differences were found in the scores of continuous anger and anger out between adolescents with and without visual impairment (p < 0.05). On the other hand, there were differences in scores of anger control and anger in between adolescents with and without visual impairment (p>0.05). The score of anger control in adolescents with visual impairment were higher compared with adolescents without visual impairment. Meanwhile, the adolescents with visual impairment had lower score for anger in compared with adolescents without visual impairment. Conclusions: The results of this study suggest that there is no difference in anger level among adolescents with and without visual impairment meanwhile there is difference in anger expression.

Keywords: adolescent, anger, impaired, visual

Procedia PDF Downloads 380

Authors: Lee A. Browne, K. Rumbold

Abstract:

The first fluorinating enzyme, 5'-fluoro-5'-deoxyadenosine synthase (fluorinase) was isolated from the soil bacterium Streptomyces cattleya. Such an enzyme, with the ability to catalyze a C-F bond, presents great potential as a biocatalyst. Naturally fluorinated compounds are extremely rare in nature. As a result, the number of fluorinases identified remains relatively few. The field of fluorination is almost completely synthetic. However, with the increasing demand for fluorinated organic compounds of commercial value in the agrochemical, pharmaceutical and materials industries, it has become necessary to utilize biologically based methods such as biocatalysts. A key step in this crucial process is the large-scale production of the fluorinase enzyme in considerable quantities for industrial applications. Thus, this study aimed to optimize expression of the fluorinase enzyme in both prokaryotic and eukaryotic expression systems in order to obtain high protein yields. The fluorinase gene was cloned into the pET 41b(+) and pPinkα-HC vectors and used to transform the expression hosts, E.coli BL21(DE3) and Pichia pastoris (PichiaPink™ strains) respectively. Expression trials were conducted to select optimal conditions for expression in both expression systems. Fluorinase catalyses a reaction between S-adenosyl-L-Methionine (SAM) and fluoride ion to produce 5'-fluorodeoxyadenosine (5'FDA) and L-Methionine. The activity of the enzyme was determined using HPLC by measuring the product of the reaction 5'FDA. A gradient mobile phase of 95:5 v/v 50mM potassium phosphate buffer to a final mobile phase containing 80:20 v/v 50mM potassium phosphate buffer and acetonitrile were used. This resulted in the complete separation of SAM and 5’-FDA which eluted at 1.3 minutes and 3.4 minutes respectively. This proved that the fluorinase enzyme was active. Optimising expression of the fluorinase enzyme was successful in both E.coli and PichiaPink™ where high expression levels in both expression systems were achieved. Protein production will be scaled up in PichiaPink™ using fermentation to achieve large-scale protein production. High level expression of protein is essential in biocatalysis for the availability of enzymes for industrial applications.

Keywords: biocatalyst, expression, fluorinase, PichiaPink™

Procedia PDF Downloads 525

Authors: Samina Jam Nazeer Ahmad, Samia Yasin, Ijaz Ahmad, Muhammad Tahir, Jam Nazeer Ahmad

Abstract:

Phytoplasmas are phloem-inhibited plant pathogenic bacteria that are transferred by insect vectors. Among biotic factors, Phytoplasma infection induces abnormality influencing the physiology as well as morphology of plants. In 16Sr-IX group phytoplasma-infected brassica compestris, flower abnormalities have been associated with changes in the expression of floral development genes. To determine whether methylation was involved in down-regulation of flower development, the process of DNA methylation and Demethylation was investigated as a possible mechanism for regulation of floral gene expression in phytoplasma infected Brassica transmitted by Orosious orientalis vector by using RT-PCR, MSRE-PCR, Southern blotting, Bisulfite Sequencing, etc. Transcriptional expression of methylated genes was found to be globally down-regulated in plants infected with phytoplasma, but not severely in those infested by insect vectors and variation in expression was found in genes involved in methylation. These results also showed that genes particularly orthologous to Arabidopsis APETALA3 involved in petal formation and flower development was down-regulated severely in phytoplasma-infected brassica and with the fact that phytoplasma and insect induce variation in developmental gene expression. The DNA methylation status of flower developmental gene in phytoplasma infected plants with 5-azacytidine restored gene expression strongly suggesting that DNA methylation was involved in down-regulation of floral development genes in phytoplasma infected brassica.

Keywords: genes expression, phytoplasma, DNA methylation, flower development

Procedia PDF Downloads 340

Authors: Ozhan Simsek, Dicle Donmez, Burhanettin Imrak, Ahsen Isik Ozguven, Yildiz Aka Kacar

Abstract:

Pomegranate (Punica granatum L.) is known to be one of the oldest edible fruit tree species, with a wide geographical global distribution. Fruits from the two defined varieties (Hicaznar and 33N26) were taken at intervals after pollination and fertilization at different sizes. Seed samples were used for transcriptome sequencing. Primary sequencing was produced by Illumina Hi-Seq™ 2000. Firstly, we had raw reads, and it was subjected to quality control (QC). Raw reads were filtered into clean reads and aligned to the reference sequences. De novo analysis was performed to detect genes expressed in seeds of pomegranate varieties. We performed downstream analysis to determine differentially expressed genes. We generated about 27.09 gb bases in total after Illumina Hi-Seq sequencing. All samples were assembled together, we got 59,264 Unigenes, the total length, average length, N50, and GC content of Unigenes are 84.547.276 bp, 1.426 bp, 2,137 bp, and 46.20 %, respectively. Unigenes were annotated with 7 functional databases, finally, 42.681(NR: 72.02%), 39.660 (NT: 66.92%), 30.790 (Swissprot: 51.95%), 20.212 (COG: 34.11%), 27.689 (KEGG: 46.72%), 12.328 (GO: 20.80%), and 33,833 (Interpro: 57.09%) Unigenes were annotated. With functional annotation results, we detected 42.376 CDS, and 4.999 SSR distribute on 16.143 Unigenes.

Keywords: next generation sequencing, SSR, RNA-Seq, Illumina

Procedia PDF Downloads 211

Authors: Ishani Majumdar, Jaishree Paul

Abstract:

Introduction: Ulcerative Colitis (UC) is an inflammatory disease of the colon resulting from an autoimmune response towards individual’s own microbiota. Excessive inflammation is characterized by hyper-activation of NFkB, a transcription factor regulating expression of various pro-inflammatory genes. The ubiquitin editing complex consisting of TNFAIP3, ITCH, RNF11 and TAX1BP1 maintains homeostatic levels of active NFkB through feedback inhibition and assembles in response to various stimuli that activate NFkB. TNFAIP3 deubiquitinates key signaling molecules involved in NFkB activation pathway. ITCH, RNF11 and TAX1BP1 provide substrate specificity, acting as adaptors for TNFAIP3 function. Aim: This study aimed to find expression of members of the ubiquitin editing complex at the transcript level in inflamed colon tissues of UC patients. Materials and Methods: Colonic biopsy samples were collected from 30 UC patients recruited at Department of Gastroenterology, AIIMS (New Delhi). Control group (n= 10) consisted of individuals undergoing examination for functional disorders. Real Time PCR was used to determine relative expression with GAPDH as housekeeping gene. Results: Expression of members of the ubiquitin editing complex was significantly altered during active disease. Expression of TNFAIP3 was upregulated while concomitant decrease in expression of ITCH, RNF11, TAX1BP1 was seen in UC patients. Discussion: This study reveals that increase in expression of TNFAIP3 was unable to control inflammation during active UC. Further, insufficient upregulation of ITCH, RNF11, TAX1BP1 may limit the formation of the ubiquitin complex and contribute to pathogenesis of UC.

Keywords: altered expression, inflammation, ubiquitin editing complex, ulcerative colitis

Procedia PDF Downloads 231

Authors: Shital Patil, Surendra Bhosale

Abstract:

Cardiac diseases are the leading causes of mortality and morbidity in the world, from recent few decades accounting for a large number of deaths have emerged as the most life-threatening disorder globally. Machine learning and Artificial intelligence have been playing key role in predicting the heart diseases. A relevant set of feature can be very helpful in predicting the disease accurately. In this study, we proposed a comparative analysis of 4 different features selection methods and evaluated their performance with both raw (Unbalanced dataset) and sampled (Balanced) dataset. The publicly available Z-Alizadeh Sani dataset have been used for this study. Four feature selection methods: Data Analysis, minimum Redundancy maximum Relevance (mRMR), Recursive Feature Elimination (RFE), Chi-squared are used in this study. These methods are tested with 8 different classification models to get the best accuracy possible. Using balanced and unbalanced dataset, the study shows promising results in terms of various performance metrics in accurately predicting heart disease. Experimental results obtained by the proposed method with the raw data obtains maximum AUC of 100%, maximum F1 score of 94%, maximum Recall of 98%, maximum Precision of 93%. While with the balanced dataset obtained results are, maximum AUC of 100%, F1-score 95%, maximum Recall of 95%, maximum Precision of 97%.

Keywords: cardio vascular diseases, machine learning, feature selection, SMOTE

Procedia PDF Downloads 85

Authors: Ahmed Bahieldin, Ahmed Atef, Jamal S. M. Sabir, Nour O. Gadalla, Sherif Edris, Ahmed M. Alzohairy, Nezar A. Radhwan, Mohammed N. Baeshen, Ahmed M. Ramadan, Hala F. Eissa, Sabah M. Hassan, Nabih A. Baeshen, Osama Abuzinadah, Magdy A. Al-Kordy, Fotouh M. El-Domyati, Robert K. Jansen

Abstract:

Wild salt-tolerant barley (Hordeum spontaneum) is the ancestor of cultivated barley (Hordeum vulgare or H. vulgare). Although the cultivated barley genome is well studied, little is known about genome structure and function of its wild ancestor. In the present study, RNA-Seq analysis was performed on young leaves of wild barley treated with salt (500 mM NaCl) at four different time intervals. Transcriptome sequencing yielded 103 to 115 million reads for all replicates of each treatment, corresponding to over 10 billion nucleotides per sample. Of the total reads, between 74.8 and 80.3% could be mapped and 77.4 to 81.7% of the transcripts were found in the H. vulgare unigene database (unigene-mapped). The unmapped wild barley reads for all treatments and replicates were assembled de novo and the resulting contigs were used as a new reference genome. This resultedin94.3 to 95.3%oftheunmapped reads mapping to the new reference. The number of differentially expressed transcripts was 9277, 3861 of which were uni gene-mapped. The annotated unigene- and de novo-mapped transcripts (5100) were utilized to generate expression clusters across time of salt stress treatment. Two-dimensional hierarchical clustering classified differential expression profiles into nine expression clusters, four of which were selected for further analysis. Differentially expressed transcripts were assigned to the main functional categories. The most important groups were ‘response to external stimulus’ and ‘electron-carrier activity’. Highly expressed transcripts are involved in several biological processes, including electron transport and exchanger mechanisms, flavonoid biosynthesis, reactive oxygen species (ROS) scavenging, ethylene production, signaling network and protein refolding. The comparisons demonstrated that mRNA-Seq is an efficient method for the analysis of differentially expressed genes and biological processes under salt stress.

Keywords: electron transport, flavonoid biosynthesis, reactive oxygen species, rnaseq

Procedia PDF Downloads 361

Authors: Stefania Arguelles Reyes, Octavio José Salcedo Parra, Alberto Acosta López

Abstract:

This paper presents a web application for the improvement of images through recognition. The web application is based on the analysis of picture-based recognition methods that allow an improvement on the physical appearance of people posting in social networks. The basis relies on the study of tools that can correct or improve some features of the face, with the help of a wide collection of user images taken as reference to build a facial profile. Automatic facial profiling can be achieved with a deeper study of the Object Detection Library. It was possible to improve the initial images with the help of MATLAB and its filtering functions. The user can have a direct interaction with the program and manually adjust his preferences.

Keywords: Matlab, make up, recognition methods, web application

Procedia PDF Downloads 112

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

Abstract:

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

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

Procedia PDF Downloads 426

Authors: Roxane A. Legaie, Kjiana E. Schwab, Caroline E. Gargett

Abstract:

Studies looking at the changes in gene expression from RNAseq data often make use of linear models. It is also common practice to focus on a subset of data for a comparison of interest, leaving aside the samples not involved in this particular comparison. This work shows the importance of including all observations in the modeling process to better estimate variance parameters, even when the samples included are not directly used in the comparison under test. The human endometrium is a dynamic tissue, which undergoes cycles of growth and regression with each menstrual cycle. The mesenchymal stem cells (MSCs) present in the endometrium are likely responsible for this remarkable regenerative capacity. However recent studies suggest that MSCs also plays a role in the pathogenesis of endometriosis, one of the most common medical conditions affecting the lower abdomen in women in which the endometrial tissue grows outside the womb. In this study we compared gene expression profiles between MSCs and non-stem cell counterparts (‘non-MSC’) obtained from women with (‘E’) or without (‘noE’) endometriosis from RNAseq. Raw read counts were used for differential expression analysis using a linear model with the limma-voom R package, including either all samples in the study or only the samples belonging to the subset of interest (e.g. for the comparison ‘E vs noE in MSC cells’, including only MSC samples from E and noE patients but not the non-MSC ones). Using the full dataset we identified about 100 differentially expressed (DE) genes between E and noE samples in MSC samples (adj.p-val < 0.05 and |logFC|>1) while only 9 DE genes were identified when using only the subset of data (MSC samples only). Important genes known to be involved in endometriosis such as KLF9 and RND3 were missed in the latter case. When looking at the MSC vs non-MSC cells comparison, the linear model including all samples identified 260 genes for noE samples (including the stem cell marker SUSD2) while the subset analysis did not identify any DE genes. When looking at E samples, 12 genes were identified with the first approach and only 1 with the subset approach. Although the stem cell marker RGS5 was found in both cases, the subset test missed important genes involved in stem cell differentiation such as NOTCH3 and other potentially related genes to be used for further investigation and pathway analysis.

Keywords: differential expression, endometriosis, linear model, RNAseq

Procedia PDF Downloads 405

Authors: Salman Akrokayan

Abstract:

Synthetic cDNA (ScDNA) of granulocyte colony-stimulating factor (G-CSF) was constructed using a DNA synthesizer with the aim to increase its expression level. 5' end of the ScDNA of G-CSF coding region was modified by decreasing the GC content without altering the predicted amino acids sequence. The identity of the resulting protein from ScDNA was confirmed by the highly specific enzyme-linked immunosorbent assay. In conclusion, a synthetic G-CSF cDNA in combination with the recombinant DNA protocol offers a rapid and reliable strategy for synthesizing the target protein. However, the commercial utilization of this methodology requires rigorous validation and quality control.

Keywords: synthetic cDNA, recombinant G-CSF, cloning, gene expression

Procedia PDF Downloads 249

Authors: Sheng-Hui Lan, Shan-Ying Wu, Shu-Ching Lin, Wei-Chen Wang, Hsiao-Sheng Liu

Abstract:

Autophagy is an essential mechanism to maintain cellular homeostasis through its degradation function, and the autophagy deficiency is related various diseases including tumorigenesis in several cancers. MicroRNAs (miRNAs) are small none coding RNAs, which regulate gene expression through degradation of mRNA or inhibition of translation. However, the relationship between autophagy deficiency and dysregulated miRNAs is still unclear. We revealed a mechanism that autophagy up-regulates miR-449a expression at the transcriptional level through activation of forkhead transcription factor family member FoxO1 and then suppresses tumorigenesis in CRC. Our data showed that the autophagic activity and miR-449a expression were lower in colorectal cancer (CRC) and has a positive correlation. We further reveal that autophagy degrades p300 expression and then suppresses acetylation of FoxO1. Under autophagic induction conditions, FoxO1 is transported from the cytoplasm to the nucleus and binds to the miR-449a promoter and then promotes miR-449a expression. In addition, either miR-449a overexpression or amiodarone-induced autophagy inhibits cell cycle progression, proliferation, colony formation migration, invasion, and tumor formation of SW480 cells. Our findings indicate that autophagy inducers may have the potential to be used for prevention and treatment of CRC through upregulation of miR-449a expression.

Keywords: autophagy, MiR-449a, FoxO1, colorectal cancer

Procedia PDF Downloads 288

Authors: Fatima Akhmedova, Simon Liao

Abstract:

One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work, we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, non-redundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: face recognition, Hahn moments, recognition-by-parts, time-lapse

Procedia PDF Downloads 340