Search results for: malaria cells images

Authors: M. Rajasekar, K. Suresh

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Diosmin is a flavonoid, most abundantly found in many citrus fruits. As a flavonoid, it possesses a multitude of biological activities including anti-hyperglycemic, anti-lipid peroxidative, anti-inflammatory, antioxidant, and anti-mutagenic properties. At this point, we established the anti-proliferative and apoptosis-inducing activities of diosmin in Hep-2 and KB cells. Diosmin has cytotoxic effects through inhibiting cellular proliferation of Hep-2 and KB cells, which leads to the induction of apoptosis, as apparent by an increase in the fraction of cells in the sub-G1phase of the cell cycle. Results exposed that inhibition of cell proliferation is associated with regulation of the Interleukins/STAT pathway. In addition, Diosmin treatment with Hep-2 and KB cells actively stimulated reactive oxygen species (ROS) and mitochondrial membrane depolarization. And also an imbalance in the Bax/Bcl-2 ratio triggered the caspase cascade and shifting the balance in favor of apoptosis. These observations conclude that Diosmin induce apoptosis via Interleukins /STAT-mediated pathway.

Keywords: diosmin, apoptosis, antioxidant, STAT pathway

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Authors: Mamadou I. Wade, Henry C. Ogworonjo, Madiha Gul, Mandoye Ndoye, Mohamed Chouikha, Wayne Patterson

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In this paper, we present a novel application of the Paillier cryptographic system to the encryption of RGB (Red Green Blue) images. In this method, an RGB image is first separated into its constituent channel images, and the Paillier encryption function is applied to each of the channels pixel intensity values. Next, the encrypted image is combined and compressed if necessary before being transmitted through an unsecured communication channel. The transmitted image is subsequently recovered by a decryption process. We performed a series of security and performance analyses to the recovered images in order to verify their robustness to security attack. The results show that the proposed image encryption scheme produces highly secured encrypted images.

Keywords: image encryption, Paillier cryptographic system, RBG image encryption, Paillier

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Authors: Sharon Yunger, Liat Altman, Yuval Garini, Yaron Shav-Tal

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Understanding the dynamics of transcription in living cells has improved since the development of quantitative fluorescence-based imaging techniques. We established a method for following transcription from a single copy gene in living cells. A gene tagged with MS2 repeats, used for mRNA tagging, in its 3' UTR was integrated into a single genomic locus. The actively transcribing gene was detected and analyzed by fluorescence in situ hybridization (FISH) and live-cell imaging. Several cell clones were created that differed in the promoter regulating the gene. Thus, comparative analysis could be obtained without the risk of different position effects at each integration site. Cells in S/G2 phases could be detected exhibiting two adjacent transcription sites on sister chromatids. A sharp reduction in the transcription levels was observed as cells progressed along the cell cycle. We hypothesized that a change in chromatin structure acts as a general mechanism during the cell cycle leading to down-regulation in the activity of some genes. We addressed this question by treating the cells with chromatin decondensing agents. Quantifying and imaging the treated cells suggests that chromatin structure plays a role both in regulating transcriptional levels along the cell cycle, as well as in limiting an active gene from reaching its maximum transcription potential at any given time. These results contribute to understanding the role of chromatin as a regulator of gene expression.

Keywords: cell cycle, living cells, nucleus, transcription

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Authors: Dong-Gyu Leem, Ji-Sun Shin, Sang Yoon Choi, Kyung-Tae Lee

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In this study, we focused on the anti-proliferative effects of panaxydol, a C17 polyacetylenic compound derived from Panax ginseng roots, against various human cancer cells. We treated with panaxydol to various cancer cells and panaxydol treatment was found to significantly inhibit the proliferation of human lung cancer cells (A549) and human pancreatic cancer cells (AsPC-1 and MIA PaCa-2), of which AsPC-1 cells were most sensitive to its treatment. DNA flow cytometric analysis indicated that panaxydol blocked cell cycle progression at the G1 phase in A549 cells, which accompanied by a parallel reduction of protein expression of cyclin-dependent kinase (CDK) 2, CDK4, CDK6, cyclin D1 and cyclin E. CDK inhibitors (CDKIs), such as p21CIP1/WAF1 and p27KIP1, were gradually upregulated after panaxydol treatment at the protein levels. Furthermore, panaxydol induced the activation of p53 in A549 cells. In addition, panaxydol also induced apoptosis of AsPC-1 and MIA PaCa-2 cells, as shown by accumulation of subG1 and apoptotic cell populations. Panaxydol triggered the activation of caspase-3, -8, -9 and the cleavage of poly (ADP-ribose) polymerase (PARP). Reduction of mitochondrial transmembrane potential by panaxydol was determined by staining with dihexyloxacarbocyanine iodide. Furthermore, panaxydol suppressed the levels of anti-apoptotic proteins, XIAP and Bcl-2, and increased the levels of proapoptotic proteins, Bax and Bad. In addition, panaxydol inhibited the activation of Akt and extracellular signal-regulated kinase (ERK) and activated the p38 mitogen-activated protein kinase kinase (MAPK). Our results suggest that panaxydol is an anti-tumor compound that causes p53-mediated cell cycle arrest and apoptosis via mitochondrial apoptotic pathway in various cancer cells.

Keywords: apoptosis, cancer, G1 arrest, panaxydol

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Authors: Rui Sang, Fei Deng, Alexander Engel, Ewa M. Goldys, Wei Deng

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In this study, we brought together X-ray induced photodynamic therapy (X-PDT) and chemo-drug (5-FU) for the treatment on colorectal cancer cells. This was achieved by developing a lipid-polymer hybrid nanoparticle delivery system (FA-LPNPs-VP-5-FU). It was prepared by incorporating a photosensitizer (verteporfin), chemotherapy drug (5-FU), and a targeting moiety (folic acid) into one platform. The average size of these nanoparticles was around 100 nm with low polydispersity. When exposed to clinical doses of 4 Gy X-ray radiation, FA-LPNPs-VP-5-FU generated sufficient amounts of reactive oxygen species, triggering the apoptosis and necrosis pathway of cancer cells. Our combined X-PDT and chemo-drug strategy was effective in inhibiting cancer cells’ growth and proliferation. Cell cycle analyses revealed that our treatment induced G2/M and S phase arrest in HCT116 cells. Our results indicate that this combined treatment provides better antitumour effect in colorectal cancer cells than each of these modalities alone. This may offer a novel approach for effective colorectal cancer treatment with reduced off-target effect and drug toxicity.

Keywords: pdt, targeted lipid-polymer nanoparticles, verteporfin, colorectal cancer

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Authors: Leila Rashki Ghaleno, Mohamad Amin Hajari, Leila Montazeri, Abdolhossein Shahverdi, Mojtaba Rezazadeh Valojerdi

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Background: Spermatogonia stem cells (SSCs) exhibit pluripotency, enabling them to undergo differentiation into many cell lineages, including neurons, glia, endothelial cells, and hepatocytes when cultured in vitro. Although the specific mechanisms are not yet fully understood, it has been observed that biopolymer agents, such as hyaluronic acid (HA) and alginate (Alg), have the potential to induce transdifferentiation of SSCs. The current work aimed to examine the process of in vitro spermatogenesis and the conversion of mouse testicular cells into hepatocytes and erythrocyte-like cells utilizing the HA-Alg hydrogel. Method: After being extracted from the testes of a 5-day postpartum mouse (5 DPP), the testicular cells were separated into two enzymatic stages and then put into a composite hydrogel containing 0.5% HA and 1% alginate. On days 14 and 28 of culture, the colonies' growth, the cells' viability, and their histology were assessed. Result: Despite observing significant cell proliferation on day 14 and the development of circular-shaped organoids on day 28, it was noted that the organoids generated in the HA-Alg medium tended to maintain their circular morphology on day 28. Notably, the testicular cells underwent transdifferentiation into cell types resembling erythrocytes and hepatocytes. The hepatocyte-like cells exhibited the presence of glycogen and lipid deposits, indicating their hepatocyte-like characteristics. Interestingly, immunostaining analysis revealed the secretion of albumin and the presence of VEGFR on day 14. However, on day 28, albumin expression was not detected, while the expression of Sox9 (a marker for hepatocytes), Vegf, CD34, and C-kit (markers for erythrocytes) showed increased levels in the gene expression evaluation. Conclusion: The present findings indicated that HA-Alg could be a potent and effective agent for the transdifferentiation of testis cells into erythrocyte and hepatocyte-like cells, as recent studies have confirmed the transformation of SSCs into hepatocyte cells during in vitro culture.

Keywords: 3D culture, mouse testicular cell, hyaluronic acid, liver organoids

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Authors: Yehjune Heo

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Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Keywords: anti-spoofing, CNN, fingerprint recognition, GAN

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Authors: Farhad Aalizadeh, Ali Moosavi

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When a blood vessel is injured, the cells of your blood bond together to form a blood clot. The blood clot helps you stop bleeding. Blood clots are made of a combination of blood cells, platelets(small sticky cells that speed up the clot-making process), and fibrin (protein that forms a thread-like mesh to trap cells). Doctors call this kind of blood clot a “thrombus.”We study the effects of different parameters on the deposition of Nanoparticles on the surface of a bump in the blood vessels by the magnetic field. The Maxwell and the flow equations are solved for this purpose. It is assumed that the blood is non-Newtonian and the number of particles has been considered enough to rely on the results statistically. Using MHD and its property it is possible to control the flow velocity, remove the fouling on the walls and return the system to its original form.

Keywords: MHD, fouling, in-vivo, blood clots, simulation

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Authors: Rominkumar Busa, Shahira K. C., Lijiya A.

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Text recognition is an important area in computer vision which deals with detecting and recognising text from an image. The Optical Character Recognition (OCR) is a saturated area these days and with very good text recognition accuracy. However the same OCR methods when applied on text with small font sizes like the text data of chart images, the recognition rate is less than 30%. In this work, aims to extract small text in images using the deep learning model, CRNN with CTC loss. The text recognition accuracy is found to improve by applying image enhancement by super resolution prior to CRNN model. We also observe the text recognition rate further increases by 18% by applying the proposed method, which involves super resolution and character segmentation followed by CRNN with CTC loss. The efficiency of the proposed method shows that further pre-processing on chart image text and other small text images will improve the accuracy further, thereby helping text extraction from chart images.

Keywords: small text extraction, OCR, scene text recognition, CRNN

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Authors: Constanza A. Barriga, Rafael Bernardi, Amokrane Berdja, Christian D. Guzman

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Most image restoration methods in astronomy rely upon probabilistic tools that infer the best solution for a deconvolution problem. They achieve good performances when the point spread function (PSF) is spatially invariable in the image plane. However, this latter condition is not always satisfied with real optical systems. PSF angular variations cannot be evaluated directly from the observations, neither be corrected at a pixel resolution. We have developed a method for the restoration of images affected by static and anisotropic aberrations using deep neural networks that can be directly applied to sky images. The network is trained using simulated sky images corresponding to the T-80 telescope optical system, an 80 cm survey imager at Cerro Tololo (Chile), which are synthesized using a Zernike polynomial representation of the optical system. Once trained, the network can be used directly on sky images, outputting a corrected version of the image, which has a constant and known PSF across its field-of-view. The method was tested with the T-80 telescope, achieving better results than with PSF deconvolution techniques. We present the method and results on this telescope.

Keywords: aberrations, deep neural networks, image restoration, variable point spread function, wide field images

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Authors: Teja Sai Puligadda

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Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

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Authors: T. Mahesh, M. K. Samanta

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Antibody dug conjugate (ADC’s) concept is a less explored and more trustable for the treatment of Type 1 diabetes (T1D). T1D is thought to arise from selective immunologically mediated destruction of the insulin- producing β-cells in the pancreatic islets of Langerhans with consequent insulin deficiency. It is evident that type 1 diabetes can be conquered, by 1) to stop immune destruction of βcells, 2) to replace or regenerate β-cells, and 3) to preserve β-cell function and mass. Many studies found that the regulatory T cells (Tregs) are crucial for the maintenance of immunological tolerance. Immune tolerance is liable for the activation of the Th1 response. The important role of Th1 response in pathology of T1D entails the depletion of CD4+ T cells, which initiated the use of anti-CD4 monoclonal antibodies (mAbs) against CD4+ T cells to interfere with induction of T1D.Insulin is regulated by Glucagon-Like Peptide-1 hormone (GLP-1) which also stimulates β-cells proliferation as the half-life of GLP-1 harmone is less due to rapid degradation by DPP-IV enzyme an alternative DPP-IV-inhibitors can increase the half-life of GLP-1 through which it conquers the replacement and reserve β-cells mass. Thus in the present study Anti-CD4 mAb was conjugated with Sitagliptin which is a DPP-IV inhibitor Drug loaded in Nanoparticles through Sulfo-MBS cross-linkers. The above study can be an effective approach for treatment to overcome the Passive subcutaneous insulin therapy.

Keywords: antibody drug conjugates, anti-CD4 Mab, DPP IV inhibitors, GLP-1

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Authors: Faith-Michael E. Uzoka, Boluwaji A. Akinnuwesi, Taiwo Amoo, Flora Aladi, Stephen Fashoto, Moses Olaniyan, Joseph Osuji

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The overarching aim of this study is to develop a soft-computing system for the differential diagnosis of tropical diseases. These conditions are of concern to health bodies, physicians, and the community at large because of their mortality rates, and difficulties in early diagnosis due to the fact that they present with symptoms that overlap, and thus become ‘confusable’. We report on the first phase of our study, which focuses on the development of a fuzzy cognitive map model for early differential diagnosis of tropical diseases. We used malaria as a case disease to show the effectiveness of the FCM technology as an aid to the medical practitioner in the diagnosis of tropical diseases. Our model takes cognizance of manifested symptoms and other non-clinical factors that could contribute to symptoms manifestations. Our model showed 85% accuracy in diagnosis, as against the physicians’ initial hypothesis, which stood at 55% accuracy. It is expected that the next stage of our study will provide a multi-disease, multi-symptom model that also improves efficiency by utilizing a decision support filter that works on an algorithm, which mimics the physician’s diagnosis process.

Keywords: medical diagnosis, tropical diseases, fuzzy cognitive map, decision support filters, malaria differential diagnosis

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Authors: Leo Nnamdi Ozurumba-Dwight

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Single-cell genomic analytical systems have proved to be a platform to isolate bulk cells into selected single cells for genomic, proteomic, and related metabolomic studies. This is enabling systematic investigations of the level of heterogeneity in a diverse and wide pool of cell populations. Single cell technologies, embracing techniques such as high parameter flow cytometry, single-cell sequencing, and high-resolution images are playing vital roles in these investigations on messenger ribonucleic acid (mRNA) molecules and related gene expressions in tracking the nature and course of disease conditions. This entails targeted molecular investigations on unit cells that help us understand cell behavoiur and expressions, which can be examined for their health implications on the health state of patients. One of the vital good sides of single-cell RNA sequencing (scRNA seq) is its probing capacity to detect deranged or abnormal cell populations present within homogenously perceived pooled cells, which would have evaded cursory screening on the pooled cell populations of biological samples obtained as part of diagnostic procedures. Despite conduction of just single-cell transcriptome analysis, scRNAseq now permits comparison of the transcriptome of the individual cells, which can be evaluated for gene expressional patterns that depict areas of heterogeneity with pharmaceutical drug discovery and clinical treatment applications. It is vital to strictly work through the tools of investigations from wet lab to bioinformatics and computational tooled analyses. In the precise steps for scRNAseq, it is critical to do thorough and effective isolation of viable single cells from the tissues of interest using dependable techniques (such as FACS) before proceeding to lysis, as this enhances the appropriate picking of quality mRNA molecules for subsequent sequencing (such as by the use of Polymerase Chain Reaction machine). Interestingly, scRNAseq can be deployed to analyze various types of biological samples such as embryos, nervous systems, tumour cells, stem cells, lymphocytes, and haematopoietic cells. In haematopoietic cells, it can be used to stratify acute myeloid leukemia patterns in patients, sorting them out into cohorts that enable re-modeling of treatment regimens based on stratified presentations. In immunotherapy, it can furnish specialist clinician-immunologist with tools to re-model treatment for each patient, an attribute of precision medicine. Finally, the good predictive attribute of scRNAseq can help reduce the cost of treatment for patients, thus attracting more patients who would have otherwise been discouraged from seeking quality clinical consultation help due to perceived high cost. This is a positive paradigm shift for patients’ attitudes primed towards seeking treatment.

Keywords: immunotherapy, transcriptome, re-modeling, mRNA, scRNA-seq

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Authors: Seyed Hassan Moosa-kazemi, Hassan Vatandoost

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Malaria, Dirofilaria immitis (dog heart worm), and D. repens (dirofilariasis), which are transmitted by mosquitoes, have been reported in Iran. The Iranian mosquito fauna includes seven genera, 65 species, and three subspecies. Aedes albopictus has been reported since. West Nile, Sindbis, Dengue, Japanese encephalitis viruses, and the nematode Setaria (setariasis) has been reported in the country but there are no information about their vectors in Iran. Iran is malaria elimination phase. Insecticides residual spraying (IRS), distributed of insecticides long lasting treated nets (ITNs), fogging, release of larvivours fishes and Bacillus thuringiensis, chemical larviciding, as well as case finding and manipulation and modification of breeding places carried out thought the IVM program in the country. Prolonged exposure to insecticides over several generations of the vectors, develop resistance, a capacity to survive contact with insecticides. However, use of insecticides in agriculture has often been implicated as contributing to resistance in mosquito’s vectors. Resistance of mosquitoes to some insecticides has been documented just within a few years after the insecticides were introduced. Some enzymes such as monooxygenases, esterases and glutathione S-transferases have been considered as a reason for resistance to pyrethroid insecticides. In conclusion, regarding to documented resistance and tolerance of mosquitoes vectors to some insecticides, resistance management is suggested by using new insecticide with novel mode of action.

Keywords: control, Iran, resistance, vector

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Authors: Risti Suryantari, Flaviana

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The aim of this research is to design calibration method of Thermochromic Liquid Crystal for temperature distribution measurement based on mathematical morphology of hue image A glass of water is placed on the surface of sample TLC R25C5W at certain temperature. We use scanner for image acquisition. The true images in RGB format is converted to HSV (hue, saturation, value) by taking of hue without saturation and value. Then the hue images is processed based on mathematical morphology using Matlab2013a software to get better images. There are differences on the final images after processing at each temperature variation based on visualization observation and the statistic value. The value of maximum and mean increase with rising temperature. It could be parameter to identify the temperature of the human body surface like hand or foot surface.

Keywords: thermochromic liquid crystal, TLC, mathematical morphology, hue image

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Authors: Mohammad Y. Alfaifi

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Methidathion (MTD) (Trade name Supracide®) is a non-systemic organophosphorus insecticide used intensively worldwide including Saudi Arabia. However, there is a lack in published studies about it's genotoxicity. In this study we evaluated MTD toxicity in rat bone marrow cells (in vivo) and in lymphocytes (in vitro) using different doses based on LD50. MNNCE (Micronucleated normocromatic erythrocytes) and MNPCE (Micronucleated polychromatic erythrocytes), NDI (Nuclear division index) and NDCI (nuclear division cytotoxicity index), necrotic and apoptotic cells were recorded in rat's bone marrow samples. CA, MI (number of cells undergoing mitosis) necrotic, and apoptotic cells recorded in lymphocytes. Results showed that there was a slight increase in the frequency of micronucleated bone marrow cells. However, no structural chromosomal aberrations were detected in vivo or in vitro. On the other hand, the results showed significant increase in necrotic and apoptotic cells following MTD administration in a dose-dependent manner comparing to positive and negative control groups. In light of these results, MTD can be considered highly cytotoxic and moderate genotoxic, and precaution should be taken when using MTD.

Keywords: methidathion, micronucleus, NDI, NDCI, toxicity, chromosomal aberrations

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Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

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Authors: Deepa Gandhi, Pravin K. Naoghare, Amit Bafana, Krishnamurthi Kannan, Saravanadevi Sivanesana

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Oxidative stress is known to depreciate normal functioning of osteoblast cells. Present study reports oxidative/inflammatory signatures in fluoride exposed human osteosarcoma (HOS) cells and its possible association with the genes involved in bone developmental pathway. Microarray analysis was performed to understand the possible molecular mechanisms of stress-mediated bone lose in HOS cells. Cells were chronically exposed with sub-lethal concentration of fluoride. Global gene expression is profiling revealed 34 up regulated and 2598 down-regulated genes, which were associated with several biological processes including bone development, osteoblast differentiation, stress response, inflammatory response, apoptosis, regulation of cell proliferation. Microarray data were further validated through qRT-PCR and western blot analyses using key representative genes. Based on these findings, it can be proposed that chronic exposure of fluoride may impair bone development via oxidative and inflammatory stress. The present finding also provides important biological clues, which will be helpful for the development of therapeutic targets against diseases related bone.

Keywords: bone, HOS cells, microarray, stress

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Authors: Amir Moslemi, Amir movafeghi, Shahab Moradi

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One of the most important challenging factors in medical images is nominated as noise.Image denoising refers to the improvement of a digital medical image that has been infected by Additive White Gaussian Noise (AWGN). The digital medical image or video can be affected by different types of noises. They are impulse noise, Poisson noise and AWGN. Computed tomography (CT) images are subjected to low quality due to the noise. The quality of CT images is dependent on the absorbed dose to patients directly in such a way that increase in absorbed radiation, consequently absorbed dose to patients (ADP), enhances the CT images quality. In this manner, noise reduction techniques on the purpose of images quality enhancement exposing no excess radiation to patients is one the challenging problems for CT images processing. In this work, noise reduction in CT images was performed using two different directional 2 dimensional (2D) transformations; i.e., Curvelet and Contourlet and Discrete wavelet transform(DWT) thresholding methods of BayesShrink and AdaptShrink, compared to each other and we proposed a new threshold in wavelet domain for not only noise reduction but also edge retaining, consequently the proposed method retains the modified coefficients significantly that result in good visual quality. Data evaluations were accomplished by using two criterions; namely, peak signal to noise ratio (PSNR) and Structure similarity (Ssim).

Keywords: computed tomography (CT), noise reduction, curve-let, contour-let, signal to noise peak-peak ratio (PSNR), structure similarity (Ssim), absorbed dose to patient (ADP)

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Authors: Latef M. Ali, Farah A. Abed

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In this paper, the effect of the Barium fluoride (BaF2) layer on the absorption efficiency of GaAs/InAs nanowire solar cells was investigated using the finite difference time domain (FDTD) method. By inserting the BaF2 as antireflection with the dominant size of 10 nm to fill the space between the shells of wires on the Si (111) substrate. The absorption is significantly improved due to the strong reabsorption of light reflected at the shells and compared with the reference cells. The present simulation leads to a higher absorption efficiency (Qabs) and reaches a value of 97%, and the external quantum efficiencies (EQEs) above 92% are observed. The current density (Jsc) increases by 0.22 mA/cm2 and the open-circuit voltage (Voc) is enhanced by 0.11 mV.

Keywords: nanowire solar cells, absorption efficiency, photovoltaic, band structures, fdtd simulation

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Authors: An Chengrui, Yin Zi, Wu Bingbing, Ma Yuanzhu, Jin Kaixiu, Chen Xiao, Ouyang Hongwei

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Single cell RNA sequence (scRNA-seq) is one of the effective tools to study transcriptomics of biological processes. Recently, similarity measurement of cells is Euclidian distance or its derivatives. However, the process of scRNA-seq is a multi-variate Bernoulli event model, thus we hypothesize that it would be more efficient when the divergence between cells is valued with relative entropy than Euclidian distance. In this study, we compared the performances of Euclidian distance, Spearman correlation distance and Relative Entropy using scRNA-seq data of the early, medial and late stage of limb development generated in our lab. Relative Entropy is better than other methods according to cluster potential test. Furthermore, we developed KL-SNE, an algorithm modifying t-SNE whose definition of divergence between cells Euclidian distance to Kullback–Leibler divergence. Results showed that KL-SNE was more effective to dissect cell heterogeneity than t-SNE, indicating the better performance of relative entropy than Euclidian distance. Specifically, the chondrocyte expressing Comp was clustered together with KL-SNE but not with t-SNE. Surprisingly, cells in early stage were surrounded by cells in medial stage in the processing of KL-SNE while medial cells neighbored to late stage with the process of t-SNE. This results parallel to Heatmap which showed cells in medial stage were more heterogenic than cells in other stages. In addition, we also found that results of KL-SNE tend to follow Gaussian distribution compared with those of the t-SNE, which could also be verified with the analysis of scRNA-seq data from another study on human embryo development. Therefore, it is also an effective way to convert non-Gaussian distribution to Gaussian distribution and facilitate the subsequent statistic possesses. Thus, relative entropy is potentially a better way to determine the divergence of cells in scRNA-seq data analysis.

Keywords: Single cell RNA sequence, Similarity measurement, Relative Entropy, KL-SNE, t-SNE

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Authors: Belaynesh Chekol, Numan Çelebi

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The main purpose of this work is to recognize individual characters extracted from natural scene images using scale invariant feature transform (SIFT) features as an input to K-nearest neighbor (KNN); a classification learner algorithm. For this task, 1,068 and 78 images of English alphabet characters taken from Chars74k data set is used to train and test the classifier respectively. For each character image, We have generated describing features by using SIFT algorithm. This set of features is fed to the learner so that it can recognize and label new images of English characters. Two types of KNN (fine KNN and weighted KNN) were trained and the resulted classification accuracy is 56.9% and 56.5% respectively. The training time taken was the same for both fine and weighted KNN.

Keywords: character recognition, KNN, natural scene image, SIFT

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Authors: Tania Tzong, Chao-Yi Teng, Tzong-Yuan Wu

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Currently, Chikungunya virus (CHIKV) transmitted to humans by Aedes mosquitoes has distributed from Africa to Southeast Asia, South America, and South Europe. However, little is known about the antigenic targets for immunity, and there are no licensed vaccines or specific antiviral treatments for the disease caused by CHIKV. Baculovirus has been recognized as a novel vaccine vector with attractive characteristic features of an optional vaccine delivery vehicle. This approach provides the safety and efficacy of CHIKV vaccine. In this study, bi-cistronic recombinant baculoviruses vAc-CMV-CHIKV26S-Rhir-EGFP and vAc-CMV-pH-CHIKV26S-Lir-EGFP were produced. Both recombinant baculovirus can express EGFP reporter gene in insect cells to facilitate the recombinant virus isolation and purification. Examination of vAc-CMV-CHIKV26S-Rhir-EGFP and vAc-CMV-pH-CHIKV26S-Lir-EGFP showed that this recombinant baculovirus could induce syncytium formation in insect cells. Unexpectedly, the immunofluorescence assay revealed the expression of E1 and E2 of CHIKV structural proteins in insect cells infected by vAc-CMV-CHIKV26S-Rhir-EGFP. This result may imply that the CMV promoter can induce the transcription of CHIKV26S in insect cells. There are also E1 and E2 expression in mammalian cells transduced by vAc-CMV-CHIKV26S-Rhir-EGFP and vAc-CMV-pH-CHIKV26S-Lir-EGFP. The expression of E1 and E2 proteins of insect and mammalian cells was validated again by Western blot analysis. The vector construction with dual tandem promoters, which is polyhedrin and CMV promoter, has higher expression of the E1 and E2 of CHIKV structural proteins than the vector construction with CMV promoter only. Most of the E1 and E2 proteins expressed in mammalian cells were glycosylated. In the future, the expression of structural proteins of CHIKV in mammalian cells is expected can form virus-like particle, so it could be used as a vaccine for chikungunya virus.

Keywords: chikungunya virus, virus-like particle, vaccines, baculovirus expression vector system

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Authors: Jer Ping Ooi, Shah Rizal Bin Kasim, Nor Aini Saidin

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The objective of this study was to synthesize nano-sized β-tricalcium phosphate (β-TCP) powder and assess its cytotoxic effects on human osteoblast (hFOB1.19) by using four cytotoxicity assays, namely, lactose dehydrogenase (LDHe), tetrazolium hydroxide (XTT), neutral red (NR), and sulforhodamine B (SRB) assays. β-tricalcium phosphate (β-TCP) is a calcium phosphate compound commonly used as an implant material. To date, bulk-sized β-TCP is reported to be readily tolerated by the osteogenic cells and body based on in vitro, in vivo experiments and clinical studies. However, to what extent of nano-sized β-TCP will react in models as compared to bulk β-TCP is yet to be investigated. Thus, in this project, the cells were treated with nano β-TCP powder within a range of concentrations from 0 to 1000 μg/mL for 24, 48, and 72 h. The cytotoxicity tests showed that loss of cell viability ( > 50%) was high for hFOB1.19 cells in all assays. Cell cycle and apoptosis analysis of hFOB1.19 cells revealed that 50 μg/mL of the compound led to 30.5% of cells being apoptotic after 72 h of incubation, and the percentage was increased to 58.6% when the concentration was increased to 200 μg/mL. When the incubation time was increased from 24 to 72 h, the percentage of apoptotic cells increased from 17.3% to 58.6% when the hFOB1.19 were exposed with 200 μg/mL of nano β-TCP powder. Thus, both concentration and exposure duration affected the cytotoxicity effects of the nano β-TCP powder on hFOB1.19. We hypothesize that these cytotoxic effects on hFOB1.19 are related to the nano-scale size of the β-TCP.

Keywords: β-tricalcium phosphate, hFOB1.19, adipose-derived mesenchymal stem cells, cytotoxicity

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Authors: Heeba A. Gurku

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Introduction: Cone Beam CT(CBCT) images play an integral part in proper patient positioning in cancer patients undergoing radiation therapy treatment. But these images are low in quality. The purpose of this study is to generate high-quality synthetic CT images from CBCT using generative models. Material and Methods: This study utilized two datasets from The Cancer Imaging Archive (TCIA) 1) Lung cancer dataset of 20 patients (with full view CBCT images) and 2) Pancreatic cancer dataset of 40 patients (only 27 patients having limited view images were included in the study). Cycle Generative Adversarial Networks (GAN) and its variant Attention Guided Generative Adversarial Networks (AGGAN) models were used to generate the synthetic CTs. Models were evaluated by visual evaluation and on four metrics, Structural Similarity Index Measure (SSIM), Peak Signal Noise Ratio (PSNR) Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), to compare the synthetic CT and original CT images. Results: For pancreatic dataset with limited view CBCT images, our study showed that in Cycle GAN model, MAE, RMSE, PSNR improved from 12.57to 8.49, 20.94 to 15.29 and 21.85 to 24.63, respectively but structural similarity only marginally increased from 0.78 to 0.79. Similar, results were achieved with AGGAN with no improvement over Cycle GAN. However, for lung dataset with full view CBCT images Cycle GAN was able to reduce MAE significantly from 89.44 to 15.11 and AGGAN was able to reduce it to 19.77. Similarly, RMSE was also decreased from 92.68 to 23.50 in Cycle GAN and to 29.02 in AGGAN. SSIM and PSNR also improved significantly from 0.17 to 0.59 and from 8.81 to 21.06 in Cycle GAN respectively while in AGGAN SSIM increased to 0.52 and PSNR increased to 19.31. In both datasets, GAN models were able to reduce artifacts, reduce noise, have better resolution, and better contrast enhancement. Conclusion and Recommendation: Both Cycle GAN and AGGAN were significantly able to reduce MAE, RMSE and PSNR in both datasets. However, full view lung dataset showed more improvement in SSIM and image quality than limited view pancreatic dataset.

Keywords: CT images, CBCT images, cycle GAN, AGGAN

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Authors: Megha Rao, Søren H. Jensen, Xiufu Sun, Anke Hagen, Mogens B. Mogensen

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Solid oxide electrolysis cells have an immense potential in converting CO₂ and H₂O into syngas during co-electrolysis operation. The produced syngas can be further converted into hydrocarbons. This kind of technology is called power-to-gas or power-to-liquid. To produce hydrocarbons via this route, durability of the cells is still a challenge, which needs to be further investigated in order to improve the cells. In this work, various nickel-yttria stabilized zirconia (Ni-YSZ) fuel electrode supported or YSZ electrolyte supported cells, cerium gadolinium oxide (CGO) barrier layer, and an oxygen electrode are investigated for durability under co-electrolysis conditions in both galvanostatic and potentiostatic conditions. While changing the gas on the oxygen electrode, keeping the fuel electrode gas composition constant, a change in the gas concentration arc was observed by impedance spectroscopy. Measurements of open circuit potential revealed the presence of leaks in the setup. It is speculated that the change in concentration impedance may be related to the leaks. Furthermore, the cells were also tested under pressurized conditions to find an inter-play between the leak rate and the pressure. A mathematical modeling together with electrochemical and microscopy analysis is presented.

Keywords: co-electrolysis, durability, leaks, gas concentration arc

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Authors: Dandan Shen, Hui-zhu Wang, Xi Yu, LiLi Gui, Xiao Wei, Xiao-yan Jiang, Da-wei Wang, Min Hong

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Yu-ping-feng-san (YPFS) is a clinical medicine for asthma and other allergic diseases, but the mechanism of YPFS on relapse of allergy is unclear. Currently, people come to realize the epithelial cells(EC) play a key role in stimulating and regulating local immune response. The study of thymic stromal lymphopoietin（TSLP derived from EC provides an important evidence that the EC can regulate immune response to stimulate allergic response. In this study, we observed the effect of YPFS on TSLP in vivo and in vitro. We established a method by using bronchial epithelial cells (16HBE) for screening potential bioactive components by HPLC-MS in YPFS and then analyzed the components in serum containing YPFS by UPLC-MS. The results showed that YPFS could decrease TSLP protein level in OVA-sensitized mice and 16HBE cells. Five components combing with the 16HBE cells were both detected in the serum.

Keywords: TSLP, bronchial epithelial cells, cell-binding, drug-containing serum

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Authors: Moein Izadi, Ali Mohammadzadeh

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Detection of damaged parts of roads after earthquake is essential for coordinating rescuers. In this study, an approach is presented for the semi-automatic detection of damaged roads in a city using pre-event vector maps and both pre- and post-earthquake QuickBird satellite images. Damage is defined in this study as the debris of damaged buildings adjacent to the roads. Some spectral and texture features are considered for SVM classification step to detect damages. Finally, the proposed method is tested on QuickBird pan-sharpened images from the Bam City earthquake and the results show that an overall accuracy of 81% and a kappa coefficient of 0.71 are achieved for the damage detection. The obtained results indicate the efficiency and accuracy of the proposed approach.

Keywords: SVM classifier, disaster management, road damage detection, quickBird images

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Authors: Marija Lončar, Zorana Šuljug Vučica, Magdalena Nigoević

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Diverse social, cultural and economic trends and changes in contemporary societies influence the ways masculinity is represented in a variety of media. Masculinity is constructed within media images as a dynamic process that changes slowly over time and is shaped by various social factors. In many societies, dominant masculinity is still associated with authority, heterosexuality, marriage, professional and financial success, ethnic dominance and physical strength. But contemporary media depict men in ways that suggest a change in the approach to media images. The number of media images of men, which promote men’s identity through their body, have increased. With the male body more scrutinized and commodified, it is necessary to highlight how the body is represented and which visual elements are crucial since the body has an important role in the construction of masculinities. The study includes content analysis of male body images in the advertisements of different men’s and women’s lifestyle magazines available in Croatia. The main aim was to explore how masculinities are currently being portrayed through body regarding age, physical appearance, fashion, touch and gaze. The findings are also discussed in relation to female images since women are central in many of the processes constructing masculinities and according to the recent conceptualization of masculinity. Although the construction of male images varies through body features, almost all of them convey the message that men’s identity could be managed through manipulation and by enhancing the appearance. Furthermore, they suggest that men should engage in “bodywork” through advertised products, activities and/or practices, in order to achieve their preferred social image.

Keywords: body images, content analysis, lifestyle magazines, masculinity

Procedia PDF Downloads 222