Search results for: segmentation genes
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1357

Search results for: segmentation genes

577 A General Framework for Knowledge Discovery Using High Performance Machine Learning Algorithms

Authors: S. Nandagopalan, N. Pradeep

Abstract:

The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: active contour, bayesian, echocardiographic image, feature vector

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576 On the Implementation of The Pulse Coupled Neural Network (PCNN) in the Vision of Cognitive Systems

Authors: Hala Zaghloul, Taymoor Nazmy

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One of the great challenges of the 21st century is to build a robot that can perceive and act within its environment and communicate with people, while also exhibiting the cognitive capabilities that lead to performance like that of people. The Pulse Coupled Neural Network, PCNN, is a relative new ANN model that derived from a neural mammal model with a great potential in the area of image processing as well as target recognition, feature extraction, speech recognition, combinatorial optimization, compressed encoding. PCNN has unique feature among other types of neural network, which make it a candid to be an important approach for perceiving in cognitive systems. This work show and emphasis on the potentials of PCNN to perform different tasks related to image processing. The main drawback or the obstacle that prevent the direct implementation of such technique, is the need to find away to control the PCNN parameters toward perform a specific task. This paper will evaluate the performance of PCNN standard model for processing images with different properties, and select the important parameters that give a significant result, also, the approaches towards find a way for the adaptation of the PCNN parameters to perform a specific task.

Keywords: cognitive system, image processing, segmentation, PCNN kernels

Procedia PDF Downloads 280
575 Automatic Music Score Recognition System Using Digital Image Processing

Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

Abstract:

Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: connected component labeling, image processing, morphological processing, optical musical recognition

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574 Anti-Melanogenic Effect of Fisetin through Activating Connective Tissue Growth Factor in vivo Mice Model

Authors: Ryeong-Hyeon Kim, Ah-Reum Lee, Seong-Soo Roh, Gyo-Nam Kim

Abstract:

Appropriate regulation of melanogenesis is important for the management of skin pigmentation-related disease. Although several beneficial effects of fisetin (3,7,3’,4’-tetrahydroxyflavone) have been reported, the precise role and molecular mechanisms of fisetin in skin health both remain unclear. Here, we induced melanogenesis of HRM2 mice (n=7/group) by UVB irradiation for 20 days. UVB-induced HRM2 mice showed that the significantly increased melanin accumulation, however, fisetin treatment (25mg and 50mg/kg of body weight) dose-dependently and significantly inhibits UVB-induced melanogenesis. In line with this, fisetin treatment effectively down-regulated m RNA and expression levels of tyrosinase, TRP2, and MITF. In addition, our inhibitor assay revealed the down-regulated melanogenic marker genes by fisetin treatment were mediated with connective tissue growth factor (CCN2)/TGF-β signaling pathway. Useful information is provided for development of functional foods using fisetin for skin health.

Keywords: connective tissue growth factor, fisetin, melanogenesis, skin, TGF-beta

Procedia PDF Downloads 236
573 Awning: An Unsung Trait in Rice (Oryza Sativa L.)

Authors: Chamin Chimyang

Abstract:

The fast-changing global trend and declining forest region have impacted agricultural lands; animals, especially birds, might become one of the major pests in the near future and go neglected or unreported in many kinds of literature and events, which is mainly because of bird infestation being a pocket-zone problem. This bird infestation can be attributed to the balding of the forest region and the decline in their foraging hotspot due to anthropogenic activity. There are many ways to keep away the birds from agricultural fields, both conventional and non-conventional. But the question here is whether the traditional approach of bird scarring methods such as scare-crows are effective enough. There are many traits in rice that are supposed to keep the birds away from foraging in paddy fields, and the selection of such traits might be rewarding, such as the angle of the flag leaf from the stem, grain size, novelty of any trait in that particular region and also an awning. Awning, as such, is a very particular trait on which negative selection was imposed to such an extent that there has been a decline in the nucleotide responsible for the said trait. Thus, in this particular session, histology, genetics, genes behind the trait and how awns might be one of the solutions to the problem stated above will be discussed in detail.

Keywords: bird infestation, awning, negative selection, domestication

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572 Study of Aerosol Deposition and Shielding Effects on Fluorescent Imaging Quantitative Evaluation in Protective Equipment Validation

Authors: Shinhao Yang, Hsiao-Chien Huang, Chin-Hsiang Luo

Abstract:

The leakage of protective clothing is an important issue in the occupational health field. There is no quantitative method for measuring the leakage of personal protective equipment. This work aims to measure the quantitative leakage of the personal protective equipment by using the fluorochrome aerosol tracer. The fluorescent aerosols were employed as airborne particulates in a controlled chamber with ultraviolet (UV) light-detectable stickers. After an exposure-and-leakage test, the protective equipment was removed and photographed with UV-scanning to evaluate areas, color depth ratio, and aerosol deposition and shielding effects of the areas where fluorescent aerosols had adhered to the body through the protective equipment. Thus, this work built a calculation software for quantitative leakage ratio of protective clothing based on fluorescent illumination depth/aerosol concentration ratio, illumination/Fa ratio, aerosol deposition and shielding effects, and the leakage area ratio on the segmentation. The results indicated that the two-repetition total leakage rate of the X, Y, and Z type protective clothing for subject T were about 3.05, 4.21, and 3.52 (mg/m2). For five-repetition, the leakage rate of T were about 4.12, 4.52, and 5.11 (mg/m2).

Keywords: fluorochrome, deposition, shielding effects, digital image processing, leakage ratio, personal protective equipment

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571 Neural Machine Translation for Low-Resource African Languages: Benchmarking State-of-the-Art Transformer for Wolof

Authors: Cheikh Bamba Dione, Alla Lo, Elhadji Mamadou Nguer, Siley O. Ba

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In this paper, we propose two neural machine translation (NMT) systems (French-to-Wolof and Wolof-to-French) based on sequence-to-sequence with attention and transformer architectures. We trained our models on a parallel French-Wolof corpus of about 83k sentence pairs. Because of the low-resource setting, we experimented with advanced methods for handling data sparsity, including subword segmentation, back translation, and the copied corpus method. We evaluate the models using the BLEU score and find that transformer outperforms the classic seq2seq model in all settings, in addition to being less sensitive to noise. In general, the best scores are achieved when training the models on word-level-based units. For subword-level models, using back translation proves to be slightly beneficial in low-resource (WO) to high-resource (FR) language translation for the transformer (but not for the seq2seq) models. A slight improvement can also be observed when injecting copied monolingual text in the target language. Moreover, combining the copied method data with back translation leads to a substantial improvement of the translation quality.

Keywords: backtranslation, low-resource language, neural machine translation, sequence-to-sequence, transformer, Wolof

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570 Deep Supervision Based-Unet to Detect Buildings Changes from VHR Aerial Imagery

Authors: Shimaa Holail, Tamer Saleh, Xiongwu Xiao

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Building change detection (BCD) from satellite imagery is an essential topic in urbanization monitoring, agricultural land management, and updating geospatial databases. Recently, methods for detecting changes based on deep learning have made significant progress and impressive results. However, it has the problem of being insensitive to changes in buildings with complex spectral differences, and the features being extracted are not discriminatory enough, resulting in incomplete buildings and irregular boundaries. To overcome these problems, we propose a dual Siamese network based on the Unet model with the addition of a deep supervision strategy (DS) in this paper. This network consists of a backbone (encoder) based on ImageNet pre-training, a fusion block, and feature pyramid networks (FPN) to enhance the step-by-step information of the changing regions and obtain a more accurate BCD map. To train the proposed method, we created a new dataset (EGY-BCD) of high-resolution and multi-temporal aerial images captured over New Cairo in Egypt to detect building changes for this purpose. The experimental results showed that the proposed method is effective and performs well with the EGY-BCD dataset regarding the overall accuracy, F1-score, and mIoU, which were 91.6 %, 80.1 %, and 73.5 %, respectively.

Keywords: building change detection, deep supervision, semantic segmentation, EGY-BCD dataset

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569 Genetic Diversity and Discovery of Unique SNPs in Five Country Cultivars of Sesamum indicum by Next-Generation Sequencing

Authors: Nam-Kuk Kim, Jin Kim, Soomin Park, Changhee Lee, Mijin Chu, Seong-Hun Lee

Abstract:

In this study, we conducted whole genome re-sequencing of 10 cultivars originated from five countries including Korea, China, India, Pakistan and Ethiopia with Sesamum indicum (Zhongzho No. 13) genome as a reference. Almost 80% of the whole genome sequences of the reference genome could be covered by sequenced reads. Numerous SNP and InDel were detected by bioinformatic analysis. Among these variants, 266,051 SNPs were identified as unique to countries. Pakistan and Ethiopia had high densities of SNPs compared to other countries. Three main clusters (cluster 1: Korea, cluster 2: Pakistan and India, cluster 3: Ethiopia and China) were recovered by neighbor-joining analysis using all variants. Interestingly, some variants were detected in DGAT1 (diacylglycerol O-acyltransferase 1) and FADS (fatty acid desaturase) genes, which are known to be related with fatty acid synthesis and metabolism. These results can provide useful information to understand the regional characteristics and develop DNA markers for origin discrimination of sesame.

Keywords: Sesamum indicum, NGS, SNP, DNA marker

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568 Microarray Gene Expression Data Dimensionality Reduction Using PCA

Authors: Fuad M. Alkoot

Abstract:

Different experimental technologies such as microarray sequencing have been proposed to generate high-resolution genetic data, in order to understand the complex dynamic interactions between complex diseases and the biological system components of genes and gene products. However, the generated samples have a very large dimension reaching thousands. Therefore, hindering all attempts to design a classifier system that can identify diseases based on such data. Additionally, the high overlap in the class distributions makes the task more difficult. The data we experiment with is generated for the identification of autism. It includes 142 samples, which is small compared to the large dimension of the data. The classifier systems trained on this data yield very low classification rates that are almost equivalent to a guess. We aim at reducing the data dimension and improve it for classification. Here, we experiment with applying a multistage PCA on the genetic data to reduce its dimensionality. Results show a significant improvement in the classification rates which increases the possibility of building an automated system for autism detection.

Keywords: PCA, gene expression, dimensionality reduction, classification, autism

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567 Alternative Splicing of an Arabidopsis Gene, At2g24600, Encoding Ankyrin-Repeat Protein

Authors: H. Sakamoto, S. Kurosawa, M. Suzuki, S. Oguri

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In Arabidopsis, several genes encoding proteins with ankyrin repeats and trans-membrane domains (AtANKTM) have been identified as mediators of biotic and abiotic stress responses. It has been known that the expression of an AtANKTM gene, At2g24600, is induced in response to abiotic stress and that there are four splicing variants derived from this locus. In this study, by RT-PCR and sequencing analysis, an unknown splicing variant of the At2g24600 transcript was identified. Based on differences in the predicted amino acid sequences, the five splicing variants are divided into three groups. The three predicted proteins are highly homologous, yet have different numbers of ankyrin repeats and trans-membrane domains. It is generally considered that ankyrin repeats mediate protein-protein interaction and that the number of trans-membrane domains affects membrane topology of proteins. The protein variants derived from the At2g24600 locus may have different molecular functions each other.

Keywords: alternative splicing, ankyrin repeats, trans-membrane domains, arabidopsis

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566 Molecular Basis of Anti-Biofilm and Anti-Adherence Activity of Syzygium aromaticum on Streptococcus mutans: In Vitro and in Vivo Study

Authors: Mohd Adil, Rosina Khan, Asad U. Khan, Vasantha Rupasinghe HP

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The study examined the effects of Syzygium aromaticum extracts on the virulence properties of Streptococcus mutans. The activity of glucosyltransferases in the presence of crude and diethylether fraction was reduced to 80% at concentration 78.12μg/ml and 39.06μg/ml respectively. The glycolytic pH drop by S. mutans cells was also disrupted by these extracts without affecting the bacterial viability. Microscopic analysis revealed morphological changes of the S. mutans biofilms, indicating that these plant extracts at sub-MICs could significantly affect the ability of S. mutans to form biofilm with distorted extracellular matrix. Furthermore, with the help of quantitative RT-PCR, the expression of different genes involved in adherence, quorum sensing, in the presence of these extracts were down regulated. The crude and active fractions were found effective in preventing caries development in rats. The data showed that S. aromaticum holds promise as a naturally occurring source of compounds that may prevent biofilm-related oral diseases.

Keywords: biofilm, quorum sensing, Streptococcus mutans, Syzygium aromaticum extract

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565 Bioinformatics and Molecular Biological Characterization of a Hypothetical Protein SAV1226 as a Potential Drug Target for Methicillin/Vancomycin-Staphylococcus aureus Infections

Authors: Nichole Haag, Kimberly Velk, Tyler McCune, Chun Wu

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Methicillin/multiple-resistant Staphylococcus aureus (MRSA) are infectious bacteria that are resistant to common antibiotics. A previous in silico study in our group has identified a hypothetical protein SAV1226 as one of the potential drug targets. In this study, we reported the bioinformatics characterization, as well as cloning, expression, purification and kinetic assays of hypothetical protein SAV1226 from methicillin/vancomycin-resistant Staphylococcus aureus Mu50 strain. MALDI-TOF/MS analysis revealed a low degree of structural similarity with known proteins. Kinetic assays demonstrated that hypothetical protein SAV1226 is neither a domain of an ATP dependent dihydroxyacetone kinase nor of a phosphotransferase system (PTS) dihydroxyacetone kinase, suggesting that the function of hypothetical protein SAV1226 might be misannotated on public databases such as UniProt and InterProScan 5.

Keywords: Methicillin-resistant Staphylococcus aureus, dihydroxyacetone kinase, essential genes, drug target, phosphoryl group donor

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564 The Trajectory of the Ball in Football Game

Authors: Mahdi Motahari, Mojtaba Farzaneh, Ebrahim Sepidbar

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Tracking of moving and flying targets is one of the most important issues in image processing topic. Estimating of trajectory of desired object in short-term and long-term scale is more important than tracking of moving and flying targets. In this paper, a new way of identifying and estimating of future trajectory of a moving ball in long-term scale is estimated by using synthesis and interaction of image processing algorithms including noise removal and image segmentation, Kalman filter algorithm in order to estimating of trajectory of ball in football game in short-term scale and intelligent adaptive neuro-fuzzy algorithm based on time series of traverse distance. The proposed system attain more than 96% identify accuracy by using aforesaid methods and relaying on aforesaid algorithms and data base video in format of synthesis and interaction. Although the present method has high precision, it is time consuming. By comparing this method with other methods we realize the accuracy and efficiency of that.

Keywords: tracking, signal processing, moving targets and flying, artificial intelligent systems, estimating of trajectory, Kalman filter

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563 The Effects of Androgen Receptor Mutation on Cryptorchid Testes in 46, XY Female

Authors: Ihtisham Bukhari

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In the current study, we enrolled a 46, XY phenotypically female patient bearing testes in her inguinal canal. DNA sequencing of the AR gene detected a missense mutation C.1715A > G (p. Y572C) in exon 2 which is already known to cause Complete androgen insensitivity syndrome (CAIS). We further studied the effects of this mutation on the testicular histopathology of the patient. No spermatocytes were seen in the surface spreading of testicular tissues while H&E staining showed that seminiferous tubules predominantly have only Sertoli cells. To confirm this meiotic failure is likely due to the current AR mutation we performed mRNA expression of genes associated with AR pathway, expression and location of the associated proteins in testicular tissues. Western blot and real-time PCR data showed that the patient had high levels of expression of AMH, SOX9, and INNB in testis. Tubules were stained with SOX9 and AMH which revealed Sertoli cell maturation arrest. Therefore, we suggest that AR mutation enhances AMH expression which ultimately leads to failure in the maturation of Sertoli cells and failure in spermatogenesis.

Keywords: androgen receptor, spermatogenesis, infertility, Sertoli cell only syndrome

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562 Phylogenetic Diversity and Antibiotic Resistance in Sediments of Aegean Sea

Authors: Ilknur Tuncer, Nihayet Bizsel

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The studies in bacterial diversity and antimicrobial resistance in coastal areas are important to understand the variability in the community structures and metabolic activities. In the present study, antimicrobial susceptibility and phylogenetic analysis of bacteria isolated from stations with different depths and influenced by terrestrial and marine fluxes in eastern Aegean Sea were illustrated. 51% of the isolates were found as resistant and 14% showed high MAR index indicating the high-risk sources of contamination in the environment. The resistance and the intermediate levels and high MAR index of the study area were 38–60%, 11–38% and 0–40%, respectively. According to 16S rRNA gene analysis, it was found that the isolates belonged to two phyla Firmicutes and Gammaproteobacteria with the genera Bacillus, Halomonas, Oceanobacillus, Photobacterium, Pseudoalteromonas, Psychrobacter, and Vibrio. 47% of Bacillus strains which were dominant among all isolates were resistant. In addition to phylogenetically diverse bacteria, the variability in resistance, intermediate and high MAR index levels of the study area indicated the effect of geographical differences.

Keywords: bacterial diversity, multiple antibiotic resistance, 16S rRNA genes, Aegean Sea

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561 Molecular Characterization of Echinococcus granulosus through Amplification of 12S rRNA Gene and Cox1 Gene Fragments from Cattle in Chittagong, Bangladesh

Authors: M. Omer Faruk, A. M. A. M. Zonaed Siddiki, M. Fazal Karim, Md. Masuduzzaman, S. Chowdhury, Md. Shafiqul Islam, M. Alamgir Hossain

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The dog tapeworms Echinococcus granulosus develop hydatid cysts in various organs in human and domestic animals worldwide including Bangladesh. The aim of this study was to identify and characterize the genotype of E. granulosus isolated from cattle using 12S rRNA and Cytochrome oxidase 1 (COX 1) genes. A total of 43 hydatid cyst samples were collected from 390 examined cattle samples derived from slaughterhouses. Among them, three cysts were fertile. Genomic DNA was extracted from germinal membrane and/or protoscoleces followed by PCR amplification of mitochondrial 12S rRNA and Cytochrome oxidase 1 gene fragments. The sequence data revealed existence of G1 (64.28%) and possible G3 (21.43%) genotypes for the first time in Bangladesh. The study indicates that common sheep strain G1 is the dominant subtype of E. granulosus in Chittagong region of Bangladesh. This will increase our understanding of the epidemiology of hydatidosis in the southern part of the country and will be useful to plan suitable control measures in the long run.

Keywords: Echinococcus granulosus, Cox1, 12S rRNA, molecular characterization, Bangladesh

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560 Improved Predictive Models for the IRMA Network Using Nonlinear Optimisation

Authors: Vishwesh Kulkarni, Nikhil Bellarykar

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Cellular complexity stems from the interactions among thousands of different molecular species. Thanks to the emerging fields of systems and synthetic biology, scientists are beginning to unravel these regulatory, signaling, and metabolic interactions and to understand their coordinated action. Reverse engineering of biological networks has has several benefits but a poor quality of data combined with the difficulty in reproducing it limits the applicability of these methods. A few years back, many of the commonly used predictive algorithms were tested on a network constructed in the yeast Saccharomyces cerevisiae (S. cerevisiae) to resolve this issue. The network was a synthetic network of five genes regulating each other for the so-called in vivo reverse-engineering and modeling assessment (IRMA). The network was constructed in S. cereviase since it is a simple and well characterized organism. The synthetic network included a variety of regulatory interactions, thus capturing the behaviour of larger eukaryotic gene networks on a smaller scale. We derive a new set of algorithms by solving a nonlinear optimization problem and show how these algorithms outperform other algorithms on these datasets.

Keywords: synthetic gene network, network identification, optimization, nonlinear modeling

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559 Human Intelligence: A Corollary of Genotype and Habitat

Authors: Tripureshwari Paul

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We are born with nature molded by nurture. Studies have confirmed the productive role of genes and environment on an individual. This study examines the relationship of parental genotype values on the intellectual ability of their children. Keeping in mind that academic achievement-learning capacity of student through normative education, a function of exposure to family environment and pathology with intellectual quotient of the individual. Purposive sampling was used and children between ages 11 and 12 years and their respective parents were involved. Raven’s Standard Progressive Matrices (RSPM), Family Pathology Scale (FPS) and Family Environment Scale (FES) were administered. The results found significant relationship of Offspring IQ to Parental IQ, maternal IQ demonstrating higher values of correlation. Female IQ was significant to maternal IQ and male IQ was significant to paternal IQ. With Academic Achievement not significantly correlated to IQ, it was determined that Competitive framework, freedom to expression and Recreational Orientation in family affect a child’s intellectual performance.

Keywords: academic achievement, environment, family environment, family pathology, genotype, intelligence quotient, maternal IQ, paternal IQ

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558 Video Text Information Detection and Localization in Lecture Videos Using Moments

Authors: Belkacem Soundes, Guezouli Larbi

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This paper presents a robust and accurate method for text detection and localization over lecture videos. Frame regions are classified into text or background based on visual feature analysis. However, lecture video shows significant degradation mainly related to acquisition conditions, camera motion and environmental changes resulting in low quality videos. Hence, affecting feature extraction and description efficiency. Moreover, traditional text detection methods cannot be directly applied to lecture videos. Therefore, robust feature extraction methods dedicated to this specific video genre are required for robust and accurate text detection and extraction. Method consists of a three-step process: Slide region detection and segmentation; Feature extraction and non-text filtering. For robust and effective features extraction moment functions are used. Two distinct types of moments are used: orthogonal and non-orthogonal. For orthogonal Zernike Moments, both Pseudo Zernike moments are used, whereas for non-orthogonal ones Hu moments are used. Expressivity and description efficiency are given and discussed. Proposed approach shows that in general, orthogonal moments show high accuracy in comparison to the non-orthogonal one. Pseudo Zernike moments are more effective than Zernike with better computation time.

Keywords: text detection, text localization, lecture videos, pseudo zernike moments

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557 Decision Making Approach through Generalized Fuzzy Entropy Measure

Authors: H. D. Arora, Anjali Dhiman

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Uncertainty is found everywhere and its understanding is central to decision making. Uncertainty emerges as one has less information than the total information required describing a system and its environment. Uncertainty and information are so closely associated that the information provided by an experiment for example, is equal to the amount of uncertainty removed. It may be pertinent to point out that uncertainty manifests itself in several forms and various kinds of uncertainties may arise from random fluctuations, incomplete information, imprecise perception, vagueness etc. For instance, one encounters uncertainty due to vagueness in communication through natural language. Uncertainty in this sense is represented by fuzziness resulting from imprecision of meaning of a concept expressed by linguistic terms. Fuzzy set concept provides an appropriate mathematical framework for dealing with the vagueness. Both information theory, proposed by Shannon (1948) and fuzzy set theory given by Zadeh (1965) plays an important role in human intelligence and various practical problems such as image segmentation, medical diagnosis etc. Numerous approaches and theories dealing with inaccuracy and uncertainty have been proposed by different researcher. In the present communication, we generalize fuzzy entropy proposed by De Luca and Termini (1972) corresponding to Shannon entropy(1948). Further, some of the basic properties of the proposed measure were examined. We also applied the proposed measure to the real life decision making problem.

Keywords: entropy, fuzzy sets, fuzzy entropy, generalized fuzzy entropy, decision making

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556 Brain Tumor Detection and Classification Using Pre-Trained Deep Learning Models

Authors: Aditya Karade, Sharada Falane, Dhananjay Deshmukh, Vijaykumar Mantri

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Brain tumors pose a significant challenge in healthcare due to their complex nature and impact on patient outcomes. The application of deep learning (DL) algorithms in medical imaging have shown promise in accurate and efficient brain tumour detection. This paper explores the performance of various pre-trained DL models ResNet50, Xception, InceptionV3, EfficientNetB0, DenseNet121, NASNetMobile, VGG19, VGG16, and MobileNet on a brain tumour dataset sourced from Figshare. The dataset consists of MRI scans categorizing different types of brain tumours, including meningioma, pituitary, glioma, and no tumour. The study involves a comprehensive evaluation of these models’ accuracy and effectiveness in classifying brain tumour images. Data preprocessing, augmentation, and finetuning techniques are employed to optimize model performance. Among the evaluated deep learning models for brain tumour detection, ResNet50 emerges as the top performer with an accuracy of 98.86%. Following closely is Xception, exhibiting a strong accuracy of 97.33%. These models showcase robust capabilities in accurately classifying brain tumour images. On the other end of the spectrum, VGG16 trails with the lowest accuracy at 89.02%.

Keywords: brain tumour, MRI image, detecting and classifying tumour, pre-trained models, transfer learning, image segmentation, data augmentation

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555 Plant Regeneration via Somatic Embryogenesis and Agrobacterium-Mediated Transformation in Alfalfa (Medicago sativa L.)

Authors: Sarwan Dhir, Suma Basak, Dipika Parajulee

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Alfalfa is renowned for its nutritional and biopharmaceutical value as a perennial forage legume. However, establishing a rapid plant regeneration protocol using somatic embryogenesis and efficient transformation frequency are the crucial prerequisites for gene editing in alfalfa. This study was undertaken to establish and improve the protocol for somatic embryogenesis and subsequent plant regeneration. The experiments were conducted in response to natural sensitivity using various antibiotics such as cefotaxime, carbenicillin, gentamycin, hygromycin, and kanamycin. Using 3-week-old leaf tissue, somatic embryogenesis was initiated on Gamborg’s B5 basal (B5H) medium supplemented with 3% maltose, 0.9µM Kinetin, and 4.5µM 2,4-D. Embryogenic callus (EC) obtained from the B5H medium exhibited a high rate of somatic embryo formation (97.9%) after 3 weeks when the cultures were placed in the dark. Different developmental stages of somatic embryos and cotyledonary stages were then transferred to Murashige and Skoog’s (MS) basal medium under light, resulting in a 94% regeneration rate of plantlets. Our results indicate that leaf segments can grow (tolerate) up to 450 mg/L of cefotaxime and 400 mg/L of carbenicillin in the culture medium. However, the survival threshold for hygromycin at 12.5 mg/L, kanamycin at 250 mg/L, gentamycin at 50 mg/L, and timentin (300 mg/L). The experiment to improve the protocol for achieving efficient transient gene expression in alfalfa through genetic transformation with the Agrobacterium tumefaciens pCAMBIA1304 vector was also conducted. The vector contains two reporter genes such as β-glucuronidase (GUS) and green fluorescent protein (GFP), along with a selectable hygromycin B phosphotransferase gene (HPT), all driven under the CaMV 35s promoter. Various transformation parameters were optimized using 3-week-old in vitro-grown plantlets. The different parameters such as types of explant, leaf ages, preculture days, segment sizes, wounding types, bacterial concentrations, infection periods, co-cultivation periods, different concentrations of acetosyringone, silver nitrate, and calcium chloride were optimized for transient gene expression. The transient gene expression was confirmed via histochemical GUS and GFP visualization under fluorescent microscopy. The data were analyzed based on the semi-quantitative observation of the percentage and number of blue GUS spots on different days of agro-infection. The highest percentage of GUS positivity (76.2%) was observed in 3-week-old leaf segments wounded using a scalpel blade of 11 size- after 3 days of post-incubation at a bacterial concentration of 0.6, with 2 days of preculture, 30 min of bacterial-leaf segment co-cultivation, with the addition of 150 µM acetosyringone, 4 mM calcium chloride, and 75 µM silver nitrate. Our results suggest that various factors influence T-DNA delivery in the Agrobacterium-mediated transformation of alfalfa. The stable gene expression in the putative transgenic tissue was confirmed using PCR amplification of both marker genes, indicating that gene expression in explants was not solely due to Agrobacterium, but also from transformed cells. The improved protocol could be used for generating transgenic alfalfa plants using genome editing techniques such as CRISPR/Cas9.

Keywords: Medicago sativa l. (Alfalfa), agrobacterium tumefaciens, β-glucuronidase, green fluorescent protein, transient gene

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554 Differential Expression Analysis of Busseola fusca Larval Transcriptome in Response to Cry1Ab Toxin Challenge

Authors: Bianca Peterson, Tomasz J. Sańko, Carlos C. Bezuidenhout, Johnnie Van Den Berg

Abstract:

Busseola fusca (Fuller) (Lepidoptera: Noctuidae), the maize stem borer, is a major pest in sub-Saharan Africa. It causes economic damage to maize and sorghum crops and has evolved non-recessive resistance to genetically modified (GM) maize expressing the Cry1Ab insecticidal toxin. Since B. fusca is a non-model organism, very little genomic information is publicly available, and is limited to some cytochrome c oxidase I, cytochrome b, and microsatellite data. The biology of B. fusca is well-described, but still poorly understood. This, in combination with its larval-specific behavior, may pose problems for limiting the spread of current resistant B. fusca populations or preventing resistance evolution in other susceptible populations. As part of on-going research into resistance evolution, B. fusca larvae were collected from Bt and non-Bt maize in South Africa, followed by RNA isolation (15 specimens) and sequencing on the Illumina HiSeq 2500 platform. Quality of reads was assessed with FastQC, after which Trimmomatic was used to trim adapters and remove low quality, short reads. Trinity was used for the de novo assembly, whereas TransRate was used for assembly quality assessment. Transcript identification employed BLAST (BLASTn, BLASTp, and tBLASTx comparisons), for which two libraries (nucleotide and protein) were created from 3.27 million lepidopteran sequences. Several transcripts that have previously been implicated in Cry toxin resistance was identified for B. fusca. These included aminopeptidase N, cadherin, alkaline phosphatase, ATP-binding cassette transporter proteins, and mitogen-activated protein kinase. MEGA7 was used to align these transcripts to reference sequences from Lepidoptera to detect mutations that might potentially be contributing to Cry toxin resistance in this pest. RSEM and Bioconductor were used to perform differential gene expression analysis on groups of B. fusca larvae challenged and unchallenged with the Cry1Ab toxin. Pairwise expression comparisons of transcripts that were at least 16-fold expressed at a false-discovery corrected statistical significance (p) ≤ 0.001 were extracted and visualized in a hierarchically clustered heatmap using R. A total of 329,194 transcripts with an N50 of 1,019 bp were generated from the over 167.5 million high-quality paired-end reads. Furthermore, 110 transcripts were over 10 kbp long, of which the largest one was 29,395 bp. BLAST comparisons resulted in identification of 157,099 (47.72%) transcripts, among which only 3,718 (2.37%) were identified as Cry toxin receptors from lepidopteran insects. According to transcript expression profiles, transcripts were grouped into three subclusters according to the similarity of their expression patterns. Several immune-related transcripts (pathogen recognition receptors, antimicrobial peptides, and inhibitors) were up-regulated in the larvae feeding on Bt maize, indicating an enhanced immune status in response to toxin exposure. Above all, extremely up-regulated arylphorin genes suggest that enhanced epithelial healing is one of the resistance mechanisms employed by B. fusca larvae against the Cry1Ab toxin. This study is the first to provide a resource base and some insights into a potential mechanism of Cry1Ab toxin resistance in B. fusca. Transcriptomic data generated in this study allows identification of genes that can be targeted by biotechnological improvements of GM crops.

Keywords: epithelial healing, Lepidoptera, resistance, transcriptome

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553 A Single Cell Omics Experiments as Tool for Benchmarking Bioinformatics Oncology Data Analysis Tools

Authors: Maddalena Arigoni, Maria Luisa Ratto, Raffaele A. Calogero, Luca Alessandri

Abstract:

The presence of tumor heterogeneity, where distinct cancer cells exhibit diverse morphological and phenotypic profiles, including gene expression, metabolism, and proliferation, poses challenges for molecular prognostic markers and patient classification for targeted therapies. Understanding the causes and progression of cancer requires research efforts aimed at characterizing heterogeneity, which can be facilitated by evolving single-cell sequencing technologies. However, analyzing single-cell data necessitates computational methods that often lack objective validation. Therefore, the establishment of benchmarking datasets is necessary to provide a controlled environment for validating bioinformatics tools in the field of single-cell oncology. Benchmarking bioinformatics tools for single-cell experiments can be costly due to the high expense involved. Therefore, datasets used for benchmarking are typically sourced from publicly available experiments, which often lack a comprehensive cell annotation. This limitation can affect the accuracy and effectiveness of such experiments as benchmarking tools. To address this issue, we introduce omics benchmark experiments designed to evaluate bioinformatics tools to depict the heterogeneity in single-cell tumor experiments. We conducted single-cell RNA sequencing on six lung cancer tumor cell lines that display resistant clones upon treatment of EGFR mutated tumors and are characterized by driver genes, namely ROS1, ALK, HER2, MET, KRAS, and BRAF. These driver genes are associated with downstream networks controlled by EGFR mutations, such as JAK-STAT, PI3K-AKT-mTOR, and MEK-ERK. The experiment also featured an EGFR-mutated cell line. Using 10XGenomics platform with cellplex technology, we analyzed the seven cell lines together with a pseudo-immunological microenvironment consisting of PBMC cells labeled with the Biolegend TotalSeq™-B Human Universal Cocktail (CITEseq). This technology allowed for independent labeling of each cell line and single-cell analysis of the pooled seven cell lines and the pseudo-microenvironment. The data generated from the aforementioned experiments are available as part of an online tool, which allows users to define cell heterogeneity and generates count tables as an output. The tool provides the cell line derivation for each cell and cell annotations for the pseudo-microenvironment based on CITEseq data by an experienced immunologist. Additionally, we created a range of pseudo-tumor tissues using different ratios of the aforementioned cells embedded in matrigel. These tissues were analyzed using 10XGenomics (FFPE samples) and Curio Bioscience (fresh frozen samples) platforms for spatial transcriptomics, further expanding the scope of our benchmark experiments. The benchmark experiments we conducted provide a unique opportunity to evaluate the performance of bioinformatics tools for detecting and characterizing tumor heterogeneity at the single-cell level. Overall, our experiments provide a controlled and standardized environment for assessing the accuracy and robustness of bioinformatics tools for studying tumor heterogeneity at the single-cell level, which can ultimately lead to more precise and effective cancer diagnosis and treatment.

Keywords: single cell omics, benchmark, spatial transcriptomics, CITEseq

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552 The Effects of Circadian Rhythms Change in High Latitudes

Authors: Ekaterina Zvorykina

Abstract:

Nowadays, Arctic and Antarctic regions are distinguished to be one of the most important strategic resources for global development. Nonetheless, living conditions in Arctic regions still demand certain improvements. As soon as the region is rarely populated, one of the main points of interest is health accommodation of the people, who migrate to Arctic region for permanent and shift work. At Arctic and Antarctic latitudes, personnel face polar day and polar night conditions during the time of the year. It means that they are deprived of natural sunlight in winter season and have continuous daylight in summer. Firstly, the change in light intensity during 24-hours period due to migration affects circadian rhythms. Moreover, the controlled artificial light in winter is also an issue. The results of the recent studies on night shift medical professionals, who were exposed to permanent artificial light, have already demonstrated higher risks in cancer, depression, Alzheimer disease. Moreover, people exposed to frequent time zones change are also subjected to higher risks of heart attack and cancer. Thus, our main goals are to understand how high latitude work and living conditions can affect human health and how it can be prevented. In our study, we analyze molecular and cellular factors, which play important role in circadian rhythm change and distinguish main risk groups in people, migrating to high latitudes. The main well-studied index of circadian timing is melatonin or its metabolite 6-sulfatoxymelatonin. In low light intensity melatonin synthesis is disturbed and as a result human organism requires more time for sleep, which is still disregarded when it comes to working time organization. Lack of melatonin also causes shortage in serotonin production, which leads to higher depression risk. Melatonin is also known to inhibit oncogenes and increase apoptosis level in cells, the main factors for tumor growth, as well as circadian clock genes (for example Per2). Thus, people who work in high latitudes can be distinguished as a risk group for cancer diseases and demand more attention. Clock/Clock genes, known to be one of the main circadian clock regulators, decrease sensitivity of hypothalamus to estrogen and decrease glucose sensibility, which leads to premature aging and oestrous cycle disruption. Permanent light exposure also leads to accumulation superoxide dismutase and oxidative stress, which is one of the main factors for early dementia and Alzheimer disease. We propose a new screening system adjusted for people, migrating from middle to high latitudes and accommodation therapy. Screening is focused on melatonin and estrogen levels, sleep deprivation and neural disorders, depression level, cancer risks and heart and vascular disorders. Accommodation therapy includes different types artificial light exposure, additional melatonin and neuroprotectors. Preventive procedures can lead to increase of migration intensity to high latitudes and, as a result, the prosperity of Arctic region.

Keywords: circadian rhythm, high latitudes, melatonin, neuroprotectors

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551 Genome-Wide Insights into Whole Gut Microbiota of Rainbow Trout, Oncorhynchus Mykiss Associated with Changes in Dietary Composition and Temperature Regimens

Authors: John N. Idenyi, Hadimundeen Abdallah, Abigeal D. Adeyemi, Jonathan C. Eya

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Gut microbiomes play a significant role in the growth, metabolism, and health of fish. However, we know very little about the interactive effects of variations in dietary composition and temperature on rainbow trout gut microbiota. Exactly 288 rainbow trout weighing 45.6g ± 0.05 (average ± SD) were fed four isocaloric, isolipidic, and isonitrogenous diets comprising 40% crude protein and 20% crude lipid and formulated as 100 % animal-based protein (AP) and a blend of 50 fish oil (FO)/50 camelina oil (CO), 100 % AP and100 % CO, 100 % plant-based protein (PP) and a blend of 50FO/50CO or 100 % PP and 100 % CO in 14 or 18°C for 150 days. Gut content was analyzed using 16S rRNA gene and shotgun sequencing. The most abundant phyla identified regardless of diet were Tenericutes, Firmicutes, Proteobacteria, Spirochaetes, Bacteroidetes, and Actinobacteria, while Aeromonadaceae and Enterobacteriaceae were dominant families in 18°C. Moreover, gut microbes were dominated by genes relating to an amino acid, carbohydrate, fat, and energy metabolisms and influenced by temperature. The shared functional profiles for all the diets suggest that plant protein sources in combination with CO could be as good as the fish meal with 50/50 FO & CO in rainbow trout farming.

Keywords: aquafeed, aquaculture, microbiome, rainbow trout

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550 EnumTree: An Enumerative Biclustering Algorithm for DNA Microarray Data

Authors: Haifa Ben Saber, Mourad Elloumi

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In a number of domains, like in DNA microarray data analysis, we need to cluster simultaneously rows (genes) and columns (conditions) of a data matrix to identify groups of constant rows with a group of columns. This kind of clustering is called biclustering. Biclustering algorithms are extensively used in DNA microarray data analysis. More effective biclustering algorithms are highly desirable and needed. We introduce a new algorithm called, Enumerative tree (EnumTree) for biclustering of binary microarray data. is an algorithm adopting the approach of enumerating biclusters. This algorithm extracts all biclusters consistent good quality. The main idea of ​​EnumLat is the construction of a new tree structure to represent adequately different biclusters discovered during the process of enumeration. This algorithm adopts the strategy of all biclusters at a time. The performance of the proposed algorithm is assessed using both synthetic and real DNA micryarray data, our algorithm outperforms other biclustering algorithms for binary microarray data. Biclusters with different numbers of rows. Moreover, we test the biological significance using a gene annotation web tool to show that our proposed method is able to produce biologically relevent biclusters.

Keywords: DNA microarray, biclustering, gene expression data, tree, datamining.

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549 Polymorphism in Myostatin Gene and Its Association with Growth Traits in Kurdi Sheep of Northern Khorasan

Authors: Masoud Alipanah, Sekineh Akbari, Gholamreza Dashab

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Myostatin genes or factor 8 affecting on growth and making differentiation works (GDF8) as a moderator in the development of skeletal muscle inhibitor. If mutations occurs in the coding region of myostatin, alter its inhibitory role and the muscle growth is increased. In this study, blood samples were collected randomly from 60 Kurdish sheep in northern Khorasan and DNA extraction was performed using a modified salt. A fragment 337 bp from exon 3 myostatin gene and-specific primers by using a polymerase chain reaction (PCR) were amplified. In order to detect different forms of an allele at this locus HaeΙΙΙ restriction enzymes and PCR-RFLP analysis were used. Band patterns clarification was performed using agarose gel electrophoresis. The frequency of genotypes mm, Mm, and MM, were respectively detected, 0, 0.15 and 0.85. The allele frequency for alleles m and M, were respectively, 0.07 and 0.93. The statistical analyses indicated that m allele was significantly associated with body weight. The results of this study suggest that the Myostatin gene possibly is a candidate gene that affects growth traits in Kurdish sheep.

Keywords: GDF8 gene, Kurdi Sheep of Northern Khorasan, polymorphism, weight traits

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548 Autonomous Vehicle Detection and Classification in High Resolution Satellite Imagery

Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

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High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

Procedia PDF Downloads 231