Search results for: malaria cells images

Authors: Sangmo Jon, Ganghyok Kim, Kwanghyok Jong, Ilnam Jo, Hyangsun Kim, Kukhyon Pae, GyeChol Sin

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The back contact dye solar cells (BCDSCs), in which the transparent conductive oxide (TCO) is omitted, have the potential to use intact low-cost general substrates such as glass, metal foil, and papers. Herein, we introduce a facile manufacturing method of a Ti back contact electrode for the BCDSCs. We found that the polylinkers such as poly(butyl titanate) have a strong binding property to make Ti particles connect with one another. A porous Ti film, which consists of Ti particles of ≤10㎛ size connected by a small amount of polylinkers, has an excellent low sheet resistance of 10 ohm sq⁻¹ for an efficient electron collection for DSCs. This Ti back contact electrode can be prepared by using a facile printing method under normal ambient conditions. Conjugating the new back contact electrode technology with the traditional monolithic structure using the carbon counter electrode, we fabricated all TCO-less DSCs. These four-layer structured DSCs consist of a dye-adsorbed nanocrystalline TiO₂ film on a glass substrate, a porous Ti back contact layer, a ZrO₂ spacer layer, and a carbon counter electrode in a layered structure. Under AM 1.5G and 100mWcm⁻² simulated sunlight illumination, the four-layer structured DSCs with N719 dyes and I⁻/I₃⁻ redox electrolytes achieved PCEs up to 5.21%.

Keywords: dye solar cells, TCO-less, back contact, printing, porous Ti film

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Authors: P. Narrima, C. Y. Looi, M. A. Mohd, H. M. Ali

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Persea declinata (Bl.) Kosterm is a member of the Lauraceae family, widely distributed in Southeast Asia. It is from the same genus with avocado (Persea americana Mill), which is widely consumed as food and for medicinal purposes. In the present study, we examined the anticancer properties of Persea declinata (Bl.) Kosterm bark methanolic crude extract (PDM). PDM exhibited a potent antiproliferative effect in MCF-7 human breast cancer cells, with an IC50 value of 16.68 µg/mL after 48h of treatment. We observed that PDM caused cell cycle arrest and subsequent apoptosis in MCF-7 cells, as exhibited by increased population at G0/G1 phase, higher lactate dehydrogenase (LDH) release, and DNA fragmentation. Mechanistic studies showed that PDM caused significant elevation in ROS production, leading to perturbation of mitochondrial membrane potential, cell permeability, and activation of caspases-3/7. On the other hand, real-time PCR and Western blot analysis showed that PDM treatment increased the expression of the proapoptotic molecule, Bax, but decreased the expression of prosurvival proteins, Bcl-2 and Bcl-xL, in a dose-dependent manner. These findings imply that PDM could inhibit proliferation in MCF-7 cells via cell cycle arrest and apoptosis induction, indicating its potential as a therapeutic agent worthy of further development.

Keywords: antiproliferative, apoptosis, MCF-7 human breast cancer, Persea declinata

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Authors: Tatsuya Kato, Masanobu Nagata, Hidetoshi Nakashima, Kazunori Matsuo

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Localization of mobile robots are important tasks for developing autonomous mobile robots. This paper proposes a method to estimate positions of a mobile robot using an omnidirectional camera on the robot. Landmarks for points of references are set up on a field where the robot works. The omnidirectional camera which can obtain 360 [deg] around images takes photographs of these landmarks. The positions of the robots are estimated from directions of these landmarks that are extracted from the images by image processing. This method can obtain the robot positions without accumulative position errors. Accuracy of the estimated robot positions by the proposed method are evaluated through some experiments. The results show that it can obtain the positions with small standard deviations. Therefore the method has possibilities of more accurate localization by tuning of appropriate offset parameters.

Keywords: mobile robots, localization, omnidirectional camera, estimating positions

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Authors: Y. S. Mohamed, L. A. Ahmed, H. A. Salem, A. M. Agha

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Liver Fibrosis is one of the most serious conditions that affect the Egyptian society. In the present study, the effect of nicorandil was investigated in experimentally-induced liver fibrosis by bile duct ligation in rats. Nicorandil (3mg/kg/day) was given orally 24 h after bile duct ligation for 14 days till the end of the experiment. Nicorandil group showed a significant improvement in liver function tests (ALT and ALP) as well as a significant decrease in oxidative stress biomarkers (TBARS and GSH), area of fibrosis and activity of hepatic stellate cells as indicated by decreased expression of alpha smooth muscle actin.Moreover, nicorandil treatment decreased HSCs proliferation due to its inhibitory effects on protein kinase C(PKC) and Platelet derived growth factor (PDGF) . Oral administration of either glibenclamide (10 mg/kg/day)(a KATP channel blocker) or L-NAME (30 mg/kg/day) (an inhibitor of nitric oxide synthase) blocked the protective effects of nicorandil. However, nicorandil and L-NAME treated group showed more or less results similar to that of untreated bile duct ligated group. In conclusion, nicorandil was effective against the development of bile duct ligated-induced liver fibrosis in rats where activation of the NO pathway plays an important role in the protective effect nicorandil.

Keywords: hepatic stellate cells, nicorandil, nitric oxide donor, liver fibrosis

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Authors: Rawan Al-Nemari, Abdulrahman Al-Senaidy, Abdelhabib Semlali

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Background and objectives: The most common cause of death in women worldwide is breast cancer. Regarding all chemotherapy disadvantages and side effects, it’s becoming necessary to identify natural products that target cancer cells with lesser harmful side effects on non-targeted cells and biological environment. Different parts of A. squamosa L., commonly known as custard apple, show varied therapeutic effects. The objective of this study is to investigate in vitro and in vivo, the anti-cancer activity of A. squamosa leaves extract. Methods: The physiological responses using MTT, nucleus staining, and LDH assays were used to evaluate cell survival and proliferation in both ER+ and ER- cells when they were exposed to extract. Monolayer wound repair assay was used to investigate the effect of extracts on cell migration. Apoptotic gene’s expression was investigated by real-time polymerase chain reaction. To study the effect of the extract on the size of tumor, breast cancer induced rats were used. Results: A. squamosa leaves extract showed high anti-proliferative and cytotoxicity effects against different breast cancer cell lines with high concentration, 100 ug/ml. The extracts have reduced the cells wound closure. Polymerase chain reaction revealed downregulation of Bcl-2 and upregulation of Bax. In breast cancer model animal developed in our laboratory, after 4 weeks treatment, treated groups have shown smaller tumor size in comparison with control group (n=4). Conclusion: These results suggest that A. squamosa leaves extract has anti-cancer activity against breast cancer in both in vitro and in vivo, and it may be developed as a potential novel agent to treat breast cancer.

Keywords: apoptosis, breast cancer, migration, proliferation

Procedia PDF Downloads 147

Authors: Masaaki Ii, Takashi Saito, Yasuhiko Tabata, Shintaro Nemoto

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Background: Clinical trials of autologous adipose-derived stem cell (AdSC) therapy for ischemic heart diseases (IHD) are now on-going. We have investigated the hypothesis that combination of AdSCs and statin, an agent with pleiotropic effects, could augment the therapeutic effect on myocardial infarction (MI). Methods and Results: Human AdSC functions with different doses of simvastatin-conjugated nanoparticle (STNP) uptake were evaluated by in vitro assays. STNP promoted the migration activity without changing the proliferation activity, and also up-regulated growth factors. Next, MI was induced by LAD ligation in nude mice, and the mice were assigned in the following groups 3 days after MI: 1) PBS (control), 2) NP-AdSCs (50000 cells), 3) STNP, and 4) STNP-AdSCs (50000 cells). Cardiac functional recovery assessed by echocardiography was improved at 4 weeks after surgery in STNP-AdSC group. Masson’s trichrome-stained sections revealed that LV fibrosis length was reduced, and the number of TUNEL-positive cardiomyocytes was less in STNP-AdSC group. Surprisingly, a number of de novo endogenous Nkx-2.5/GATA4 positive immature cardiomyocytes as well as massive vascular formation were observed in outer layer of infarcted myocardium despite of a few recruited/retained transfused STNP-AdSCs 4 weeks after MI in STNP-AdSC group. Finally, massive myocardial regeneration was observed 8 weeks after MI. Conclusions: Intravenously injected small number of statin nanoparticle-loaded hAdSCs exhibited a potent therapeutic effect inducing endogenous cardiac tissue regeneration.

Keywords: statin, drug delivery system, stem cells, cardiac regeneration

Procedia PDF Downloads 187

Authors: M. Dhana Lakshmi, S. Sakthivel Murugan

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As light passes from source to observer in the water medium, it is scattered by the suspended particulate matter. This scattering effect will plague the captured images with non-uniform illumination, blurring details, halo artefacts, weak edges, etc. To overcome this, pixel normalization with an Amended Unsharp Mask (AUM) filter is proposed to enhance the degraded image. To validate the robustness of the proposed technique irrespective of atmospheric light, the considered datasets are collected on dual locations. For those images, the maxima and minima pixel intensity value is computed and normalized; then the AUM filter is applied to strengthen the blurred edges. Finally, the enhanced image is obtained with good illumination and contrast. Thus, the proposed technique removes the effect of scattering called de-hazing and restores the perceptual information with enhanced edge detail. Both qualitative and quantitative analyses are done on considering the standard non-reference metric called underwater image sharpness measure (UISM), and underwater image quality measure (UIQM) is used to measure color, sharpness, and contrast for both of the location images. It is observed that the proposed technique has shown overwhelming performance compared to other deep-based enhancement networks and traditional techniques in an adaptive manner.

Keywords: underwater drone imagery, pixel normalization, thresholding, masking, unsharp mask filter

Procedia PDF Downloads 194

Authors: A. L. R. Rangel, J. A. M. Chaves, A. P. R. Alves Claro

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Surface modification of titanium and its alloys using TiO2 nanotube growth has been widely studied for biomedical field due to excellent interaction between implant and biological environment. The success of this treatment is directly related to anatase phase formation (TiO2 phase) which affects the cells growth. The aim of this study was to evaluate the phases formed in the nanotubes growth on the Ti-15Mo surface. Nanotubes were grown by electrochemical anodization of the alloy in ammonium fluoride based glycerol electrolyte for 24 hours at 20V. Then, the samples were annealed at 200°,400°, 450°, 500°, 600°, and 800° C for 1 hour. Contact angles measurements, scanning electron microscopy images and X rays diffraction analysis (XRD) were carried out for all samples. Raman Spectroscopy was used to evaluate TiO2 phases transformation in nanotubes samples as well. The results of XRD showed anatase formation for lower temperatures, while at 800 ° C the rutile phase was observed all over the surface. Raman spectra indicate that this phase transition occurs between 500 and 600 °C. The different phases formed have influenced the nanotubes morphologies, since higher annealing temperatures induced agglutination of the TiO2 layer, disrupting the tubular structure. On the other hand, the nanotubes drastically reduced the contact angle, regardless the annealing temperature.

Keywords: nanotubes, TiO2, titanium alloys, Ti-15Mo

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Authors: Edward Holupka, John Rossman, Tye Morancy, Joseph Aronovitz, Irving Kaplan

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A common modality for the treatment of early stage prostate cancer is the implantation of radioactive seeds directly into the prostate. The radioactive seeds are positioned inside the prostate to achieve optimal radiation dose coverage to the prostate. These radioactive seeds are positioned inside the prostate using Transrectal ultrasound imaging. Once all of the planned seeds have been implanted, two dimensional transaxial transrectal ultrasound images separated by 2 mm are obtained through out the prostate, beginning at the base of the prostate up to and including the apex. A common deep neural network, called DetectNet was trained to automatically determine the position of the implanted radioactive seeds within the prostate under ultrasound imaging. The results of the training using 950 training ultrasound images and 90 validation ultrasound images. The commonly used metrics for successful training were used to evaluate the efficacy and accuracy of the trained deep neural network and resulted in an loss_bbox (train) = 0.00, loss_coverage (train) = 1.89e-8, loss_bbox (validation) = 11.84, loss_coverage (validation) = 9.70, mAP (validation) = 66.87%, precision (validation) = 81.07%, and a recall (validation) = 82.29%, where train and validation refers to the training image set and validation refers to the validation training set. On the hardware platform used, the training expended 12.8 seconds per epoch. The network was trained for over 10,000 epochs. In addition, the seed locations as determined by the Deep Neural Network were compared to the seed locations as determined by a commercial software based on a one to three months after implant CT. The Deep Learning approach was within \strikeout off\uuline off\uwave off2.29\uuline default\uwave default mm of the seed locations determined by the commercial software. The Deep Learning approach to the determination of radioactive seed locations is robust, accurate, and fast and well within spatial agreement with the gold standard of CT determined seed coordinates.

Keywords: prostate, deep neural network, seed implant, ultrasound

Procedia PDF Downloads 198

Authors: Remzi Şahin, Sadık Ata, Kevser Dincer

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In this study, performance of proton exchange membrane (PEM) fuel cell was experimentally investigated. The efficiency of energy conversion in PEM fuel cells is dependent on the catalytic activities of the catalysts used in the cathode and anode of membrane electrode assemblies. Membrane is considered the heart of PEM fuel cells without which they cannot produce electricity. PEM fuel cell performance increased with coating carbon nanotube (CNT). CNT show a unique combination of stiffness, strength, and tenacity compared to other fiber materials which usually lack one or more of these properties. Two different experiments were performed and the membrane performance has been determined by repeating the two experiments that were done before coating. The purposes of these experiments are the observation of power change due to a temperature change in the same voltage value.

Keywords: carbon nanotube (CNT), proton exchange membrane (PEM), fuel cell, spin method

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Authors: Okike Benjamin, Garba E J. D.

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Encryption is used to conceal information from prying eyes. Presently, information and data encryption are common due to the volume of data and information in transit across the globe on daily basis. Image encryption is yet to receive the attention of the researchers as deserved. In other words, video and multimedia documents are exposed to unauthorized accessors. The authors propose image encryption using matrix transpose. An algorithm that would allow image encryption is developed. In this proposed image encryption technique, the image to be encrypted is split into parts based on the image size. Each part is encrypted separately using matrix transpose. The actual encryption is on the picture elements (pixel) that make up the image. After encrypting each part of the image, the positions of the encrypted images are swapped before transmission of the image can take place. Swapping the positions of the images is carried out to make the encrypted image more robust for any cryptanalyst to decrypt.

Keywords: image encryption, matrices, pixel, matrix transpose

Procedia PDF Downloads 421

Authors: Rongbo Shen, Jianhua Yao, Kezhou Yan, Kuan Tian, Cheng Jiang, Ke Zhou

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This study proposes a generative adversarial networks (GAN) framework to perform synthetic sampling in feature space, i.e., feature augmentation, to address the class imbalance problem in medical image analysis. A feature extraction network is first trained to convert images into feature space. Then the GAN framework incorporates adversarial learning to train a feature generator for the minority class through playing a minimax game with a discriminator. The feature generator then generates features for minority class from arbitrary latent distributions to balance the data between the majority class and the minority class. Additionally, a data cleaning technique, i.e., Tomek link, is employed to clean up undesirable conflicting features introduced from the feature augmentation and thus establish well-defined class clusters for the training. The experiment section evaluates the proposed method on two medical image analysis tasks, i.e., mass classification on mammogram and cancer metastasis classification on histopathological images. Experimental results suggest that the proposed method obtains superior or comparable performance over the state-of-the-art counterparts. Compared to all counterparts, our proposed method improves more than 1.5 percentage of accuracy.

Keywords: class imbalance, synthetic sampling, feature augmentation, generative adversarial networks, data cleaning

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Authors: Rohit Semwal, Shivam Arora, Saurav, Sangita Roy

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This work proposes a supervised framework with deep convolutional neural networks (CNNs) for vision-based sign language recognition of static gestures. Our approach addresses the acquisition and segmentation of correct inputs for the CNN-based classifier. Microsoft Kinect™ sensor, despite complex environmental conditions, can track hands efficiently. Skin Colour based segmentation is applied on cropped images of hands in different poses, used to depict different sign language gestures. The segmented hand images are used as an input for our classifier. The CNN classifier proposed in the paper is able to classify the input images with a high degree of accuracy. The system was trained and tested on 39 static sign language gestures, including 26 letters of the alphabet and 13 commonly used words. This paper includes a problem definition for building the proposed system, which acts as a sign language translator between deaf/mute and the rest of the society. It is then followed by a focus on reviewing existing knowledge in the area and work done by other researchers. It also describes the working principles behind different components of CNNs in brief. The architecture and system design specifications of the proposed system are discussed in the subsequent sections of the paper to give the reader a clear picture of the system in terms of the capability required. The design then gives the top-level details of how the proposed system meets the requirements.

Keywords: sign language, CNN, HCI, segmentation

Procedia PDF Downloads 157

Authors: Wilai Masanga, Chirapha Tannanonta, Sangutid Thongsawad, Sasikarn Chamchod, Todsaporn Fuangrod

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The major factors of radiotherapy for head and neck (HN) cancers include patient’s anatomical changes and tumour shrinkage. These changes can significantly affect the planned dose distribution that causes the treatment plan deterioration. A measured transit EPID images compared to a predicted EPID images using gamma analysis has been clinically implemented to verify the dose accuracy as part of adaptive radiotherapy protocol. However, a global gamma analysis dose not sensitive to some critical organ changes as the entire treatment field is compared. The objective of this feasibility study is to evaluate the dosimetric response to patient anatomical changes during the treatment course in HN IMRT (Head and Neck Intensity-Modulated Radiation Therapy) using a novel comparison method; organ-of-interest gamma analysis. This method provides more sensitive to specific organ change detection. Random replanned 5 HN IMRT patients with causes of tumour shrinkage and patient weight loss that critically affect to the parotid size changes were selected and evaluated its transit dosimetry. A comprehensive physics-based model was used to generate a series of predicted transit EPID images for each gantry angle from original computed tomography (CT) and replan CT datasets. The patient structures; including left and right parotid, spinal cord, and planning target volume (PTV56) were projected to EPID level. The agreement between the transit images generated from original CT and replanned CT was quantified using gamma analysis with 3%, 3mm criteria. Moreover, only gamma pass-rate is calculated within each projected structure. The gamma pass-rate in right parotid and PTV56 between predicted transit of original CT and replan CT were 42.8%( ± 17.2%) and 54.7%( ± 21.5%). The gamma pass-rate for other projected organs were greater than 80%. Additionally, the results of organ-of-interest gamma analysis were compared with 3-dimensional cone-beam computed tomography (3D-CBCT) and the rational of replan by radiation oncologists. It showed that using only registration of 3D-CBCT to original CT does not provide the dosimetric impact of anatomical changes. Using transit EPID images with organ-of-interest gamma analysis can provide additional information for treatment plan suitability assessment.

Keywords: re-plan, anatomical change, transit electronic portal imaging device, EPID, head, and neck

Procedia PDF Downloads 216

Authors: A. Seddiki, M. Djebbouri, D. Guerchi

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Medical imaging produces human body pictures in digital form. Since these imaging techniques produce prohibitive amounts of data, compression is necessary for storage and communication purposes. Many current compression schemes provide a very high compression rate but with considerable loss of quality. On the other hand, in some areas in medicine, it may be sufficient to maintain high image quality only in region of interest (ROI). This paper discusses a contribution to the lossless compression in the region of interest of Scintigraphic images based on SPIHT algorithm and global transform thresholding using Huffman coding.

Keywords: global thresholding transform, huffman coding, region of interest, SPIHT coding, scintigraphic images

Procedia PDF Downloads 367

Authors: K. Drabczyk, Z. Starowicz, S. Maleczek, P. Zieba

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The army, police and fire brigade commonly use dedicated equipment based on special textile materials. The properties of these textiles should ensure human life and health protection. Equally important is the ability to use electronic equipment and this requires access to the source of electricity. Photovoltaic cells integrated with such textiles can be solution for this problem in the most of outdoor circumstances. One idea may be to laminate the cells to textile without changing their properties. The main goal of this work was analyzed lamination quality of special designed semi-flexible solar module with special textile materials as a backsheet. In the first step of investigation, the quality of lamination was determined using device equipped with dynamometer. In this work, the crystalline silicon solar cells 50 x 50 mm and thin chemical tempered glass - 62 x 62 mm and 0.8 mm thick - were used. The obtained results showed the correlation between breaking force and type of textile weave and fiber. The breaking force was in the ranges: 4.5-5.5 N, 15-20 N and 30-33 N depending on the type of wave and fiber type. To verify these observations the microscopic and FTIR analysis of fibers was performed. The studies showed the special textile can be used as a backsheet of semi-flexible solar modules. This work presents a new composition of solar module with special textile layer which, to our best knowledge, has not been published so far. Moreover, the work presents original investigations on adhesion of EVA (ethylene-vinyl acetate) polymer to textile with respect to fiber structure of laminated substrate. This work is realized for the GEKON project (No. GEKON2/O4/268473/23/2016) sponsored by The National Centre for Research and Development and The National Fund for Environmental Protection and Water Management.

Keywords: flexible solar modules, lamination process, solar cells, textile for photovoltaics

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Authors: Shaira L. Kee, Michael Aaron G. Sy, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

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Skin diseases are considered the fourth most common disease, with melanoma and non-melanoma skin cancer as the most common type of cancer in Caucasians. The alarming increase in Skin Cancer cases shows an urgent need for further research to improve diagnostic methods, as early diagnosis can significantly improve the 5-year survival rate. Machine Learning algorithms for image pattern analysis in diagnosing skin lesions can dramatically increase the accuracy rate of detection and decrease possible human errors. Several studies have shown the diagnostic performance of computer algorithms outperformed dermatologists. However, existing methods still need improvements to reduce diagnostic errors and generate efficient and accurate results. Our paper proposes an ensemble method to classify dermoscopic images into benign and malignant skin lesions. The experiments were conducted using the International Skin Imaging Collaboration (ISIC) image samples. The dataset contains 3,297 dermoscopic images with benign and malignant categories. The results show improvement in performance with an accuracy of 88% and an F1 score of 87%, outperforming other existing models such as support vector machine (SVM), Residual network (ResNet50), EfficientNetB0, EfficientNetB4, and VGG16.

Keywords: deep learning - VGG16 - efficientNet - CNN – ensemble – dermoscopic images - melanoma

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Authors: Jolene M. Helena, Annie M. Joubert, Peace Mabeta, Magdalena Coetzee, Roy Lakier, Anne E. Mercier

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Targeting the distant tumour and its microenvironment whilst preserving bone density is important in improving the outcomes of patients with bone metastases. 2-Ethyl-3-O-sulphamoyl-estra1,3,5(10)16-tetraene (ESE-16) is an in-silico-designed 2- methoxyestradiol analogue which aimed at enhancing the parent compound’s cytotoxicity and providing a more favourable pharmacokinetic profile. In this study, the potential radiosensitization effects of ESE-16 were investigated in an in vitro bone metastasis model consisting of murine pre-osteoblastic (MC3T3-E1) and pre-osteoclastic (RAW 264.7) bone cells, metastatic prostate (DU 145) and breast (MDA-MB-231) cancer cells, as well as human umbilical vein endothelial cells (HUVECs). Cytotoxicity studies were conducted on all cell lines via spectrophotometric quantification of 3-(4,5-dimethylthiazol-2-yl)-2,5- diphenyltetrazolium bromide. The experimental set-up consisted of flow cytometric analysis of cell cycle progression and apoptosis detection (Annexin V-fluorescein isothiocyanate) to determine the lowest ESE-16 and radiation doses to induce apoptosis and significantly reduce cell viability. Subsequent experiments entailed a 24-hour low-dose ESE-16-exposure followed by a single dose of radiation. Termination proceeded 2, 24 or 48 hours thereafter. The effect of the combination treatment was investigated on osteoclasts via tartrate-resistant acid phosphatase (TRAP) activity- and actin ring formation assays. Tumour cell experiments included investigation of mitotic indices via haematoxylin and eosin staining; pro-apoptotic signalling via spectrophotometric quantification of caspase 3; deoxyribonucleic acid (DNA) damage via micronuclei analysis and histone H2A.X phosphorylation (γ-H2A.X); and Western blot analyses of bone morphogenetic protein-7 and matrix metalloproteinase-9. HUVEC experiments included flow cytometric quantification of cell cycle progression and free radical production; fluorescent examination of cytoskeletal morphology; invasion and migration studies on an xCELLigence platform; and Western blot analyses of hypoxia-inducible factor 1-alpha and vascular endothelial growth factor receptor 1 and 2. Tumour cells yielded half-maximal growth inhibitory concentration (GI50) values in the nanomolar range. ESE-16 concentrations of 235 nM (DU 145) and 176 nM (MDA-MB-231) and a radiation dose of 4 Gy were found to be significant in cell cycle and apoptosis experiments. Bone and endothelial cells were exposed to the same doses as DU 145 cells. Cytotoxicity studies on bone cells reported that RAW 264.7 cells were more sensitive to the combination treatment than MC3T3-E1 cells. Mature osteoclasts were more sensitive than pre-osteoclasts with respect to TRAP activity. However, actin ring morphology was retained. The mitotic arrest was evident in tumour and endothelial cells in the mitotic index and cell cycle experiments. Increased caspase 3 activity and superoxide production indicated pro-apoptotic signalling in tumour and endothelial cells. Increased micronuclei numbers and γ-H2A.X foci indicated increased DNA damage in tumour cells. Compromised actin and tubulin morphologies and decreased invasion and migration were observed in endothelial cells. Western blot analyses revealed reduced metastatic and angiogenic signalling. ESE-16-induced radiosensitization inhibits metastatic signalling and tumour cell survival whilst preferentially preserving bone cells. This low-dose combination treatment strategy may promote the quality of life of patients with metastatic bone disease. Future studies will include 3-dimensional in-vitro and murine in-vivo models.

Keywords: angiogenesis, apoptosis, bone metastasis, cancer, cell migration, cytoskeleton, DNA damage, ESE-16, radiosensitization.

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Authors: Yu-Chieh Chen, Li-Yun Wang, Chi-Chih Chen, Huy Hùng Đào, Ya-Mei Chen, Ming-Chu Cheng, Wen-Bin Chung, Hso-Chi Chaung, Guan-Ming Ke

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Many recent researches have demonstrated that CD154, a protein primarily expressed on activated T cell molecules, has potentially acted as a molecular adjuvant to improve the immunogenicity of subunit vaccines against viral infections. Classical swine fever (CSF) affects the swine industry worldwide that is one of the most devastating and highly contagious pig diseases. It is listed by the World Organization for Animal Health (OIE) as an infectious animal disease that must be reported. Although pigs vaccinated with subunit vaccines can be differentially diagnosed from those infected animals, subunit vaccines usually need adjuvants to enhance and elicit immune responses. In this study, CD154 was linked with CSFV E2 sequences and then expressed in CHO cells to produce the fusion protein as E2-CD154. The porcine specific CpG adjuvant was also used in one of the formulations. The specific pathogen-free pigs (SPF) at the age of 4-week-old were randomly separated into four groups, vaccinated with E2-CpG, E2-CD154, E2-CD154-CpG or the commercial Bayovac® CSF-E2 vaccine and boosted two weeks after primary vaccination. The results showed that the percentages of CD4+ and CD4+IL2+ in peripheral blood mononuclear cells (PBMC) in E2-CD154 vaccinated piglets seven days after primary vaccination were gained by 1-5% relative to the control group. In addition, the percentages of CD4+IFNγ+ T cells had slightly edged up 0.1-0.3% compared with the control group. Also, increased E2-specific IFNγ levels had edged up CD4+CD8+ T cells found in E2-CD154 and E2-CD154-CpG groups, particularly in the E2-CD154-CpG group. These results implicate that CD154 may enhance cellular immunity and synergistically act with species-specific CpG adjuvant as a dual-phase adjuvant. Therefore, the CD154 may be beneficial as a promising adjuvant in subunit vaccines.

Keywords: CD154, CpG adjuvant, cellular immunity, subunit vaccine, pig

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Authors: Rafia S. Al-lamki, Jun Wang, Simon Pacey, Jordan Pober, John R. Bradley

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Tumor necrosis factor alpha (TNF), signaling through TNFR2, may act an autocrine growth factor for renal tubular epithelial cells. Clear cell renal carcinomas (ccRCC) contain cancer stem cells (CSCs) that give rise to progeny which form the bulk of the tumor. CSCs are rarely in cell cycle and, as non-proliferating cells, resist most chemotherapeutic agents. Thus, recurrence after chemotherapy may result from the survival of CSCs. Therapeutic targeting of both CSCs and the more differentiated bulk tumor populations may provide a more effective strategy for treatment of RCC. In this study, we hypothesized that TNFR2 signaling will induce CSCs in ccRCC to enter cell cycle so that treatment with ligands that engage TNFR2 will render CSCs susceptible to chemotherapy. To test this hypothesis, we have utilized wild-type TNF (wtTNF) or specific muteins selective for TNFR1 (R1TNF) or TNFR2 (R2TNF) to treat either short-term organ cultures of ccRCC and adjacent normal kidney (NK) tissue or cultures of CD133+ cells isolated from ccRCC and adjacent NK, hereafter referred to as stem cell-like cells (SCLCs). The effect of cyclophosphamide (CP), currently an effective anticancer agent, was tested on CD133+SCLCs from ccRCC and NK before and after R2TNF treatment. Responses to TNF were assessed by flow cytometry (FACS), immunofluorescence, and quantitative real-time PCR, TUNEL, and cell viability assays. Cytotoxic effect of CP was analyzed by Annexin V and propidium iodide staining with FACS. In addition, we assessed the effect of TNF on isolated SCLCs differentiation using a three-dimensional (3D) culture system. Clinical samples of ccRCC contain a greater number SCLCs compared to NK and the number of SCSC increases with higher tumor grade. Isolated SCLCs show expression of stemness markers (oct4, Nanog, Sox2, Lin28) but not differentiation markers (cytokeratin, CD31, CD45, and EpCAM). In ccRCC organ cultures, wtTNF and R2TNF increase CD133 and TNFR2 expression and promote cell cycle entry whereas wtTNF and R1TNF increase TNFR1 expression and promote cell death of SCLCs. Similar findings are observed in SCLCs isolated from NK but the effect was greater in SCLCs isolated from ccRCC. Application of CP distinctly triggered apoptotic and necrotic cell death in SLCSs pre-treatment with R2TNF as compared to CP treatment alone, with SCLCs from ccRCC more sensitive to CP compared to SLCS from NK. Furthermore, TNF promotes differentiation of SCLCs to an epithelial phenotype in 3D cultures, confirmed by cytokeratin expression and loss of stemness markers Nanog and Sox2. The differentiated cells show positive expression of TNF and TNFR2. These findings provide evidence that selective engagement of TNFR2 drive CSCs to cell proliferation/differentiation, and targeting of cycling cells with TNFR2 agonist in combination with anti-cancer agents may be a potential therapy for RCC.

Keywords: cancer stem cells, ccRCC, cell cycle, cell death, TNF, TNFR1, TNFR2, CD133

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Authors: U. Ravi Babu, Mohd Mastan

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The present paper proposes a novel approach for handwritten digit recognition system. The present paper extract digit image features based on distance measure and derives an algorithm to classify the digit images. The distance measure can be performing on the thinned image. Thinning is the one of the preprocessing technique in image processing. The present paper mainly concentrated on an extraction of features from digit image for effective recognition of the numeral. To find the effectiveness of the proposed method tested on MNIST database, CENPARMI, CEDAR, and newly collected data. The proposed method is implemented on more than one lakh digit images and it gets good comparative recognition results. The percentage of the recognition is achieved about 97.32%.

Keywords: handwritten digit recognition, distance measure, MNIST database, image features

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Authors: Ping Bo, Meng Yunshan

Abstract:

Satellite-derived sea surface temperature (SST) is a key parameter for many operational and scientific applications. However, the disadvantage of SST data is a high percentage of missing data which is mainly caused by cloud coverage. Data Interpolating Empirical Orthogonal Function (DINEOF) algorithm is an EOF-based technique for reconstructing the missing data and has been widely used in oceanographic field. The reconstruction of SST images within a long time series using DINEOF can cause large discontinuities and one solution for this problem is to filter the temporal covariance matrix to reduce the spurious variability. Based on the previous researches, an algorithm is presented in this paper to improve the temporal correlations in EOF expansion. Similar with the previous researches, a filter, such as Laplacian filter, is implemented on the temporal covariance matrix, but the temporal relationship between two consecutive images which is used in the filter is considered in the presented algorithm, for example, two images in the same season are more likely correlated than those in the different seasons, hence the latter one is less weighted in the filter. The presented approach is tested for the monthly nighttime 4-km Advanced Very High Resolution Radiometer (AVHRR) Pathfinder SST for the long-term period spanning from 1989 to 2006. The results obtained from the presented algorithm are compared to those from the original DINEOF algorithm without filtering and from the DINEOF algorithm with filtering but without taking temporal relationship into account.

Keywords: data interpolating empirical orthogonal function, image reconstruction, sea surface temperature, temporal filter

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Authors: Sedat Aktas, Egemen Ulusoy, Remzi Yildirim

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This article explains how to get a ram image from a computer with a Linux operating system and what steps should be followed while getting it. What we mean by taking a ram image is the process of dumping the physical memory instantly and writing it to a file. This process can be likened to taking a picture of everything in the computer’s memory at that moment. This process is very important for tools that analyze ram images. Volatility can be given as an example because before these tools can analyze ram, images must be taken. These tools are used extensively in the forensic world. Forensic, on the other hand, is a set of processes for digitally examining the information on any computer or server on behalf of official authorities. In this article, the protected mode architecture in the Linux operating system is examined, and the way to save the image sample of the kernel driver and system memory to disk is followed. Tables and access methods to be used in the operating system are examined based on the basic architecture of the operating system, and the most appropriate methods and application methods are transferred to the article. Since there is no article directly related to this study on Linux in the literature, it is aimed to contribute to the literature with this study on obtaining ram images. LIME can be mentioned as a similar tool, but there is no explanation about the memory dumping method of this tool. Considering the frequency of use of these tools, the contribution of the study in the field of forensic medicine has been the main motivation of the study due to the intense studies on ram image in the field of forensics.

Keywords: linux, paging, addressing, ram-image, memory dumping, kernel modules, forensic

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Authors: Y. Fekir, K. Mederbal, M. A. Hammadouche, D. Anteur

Abstract:

The cultural park of the Ahaggar, occupying a large area of Algeria, is characterized by a rich wetlands area to be preserved and managed both in time and space. The management of a large area, by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information...), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Remote sensing imaging data have been very useful in the last decade in very interesting applications. They can aid in several domains such as the detection and identification of diverse wetland surface targets, topographical details, and geological features... In this work, we try to extract automatically wetlands area using multispectral remotely sensed data on-board the Earth Observing 1 (EO-1) and Landsat satellite. Both are high-resolution multispectral imager with a 30 m resolution. The instrument images an interesting surface area. We have used images acquired over the several area of interesting in the National Park of Ahaggar in the south of Algeria. An Extraction Algorithm is applied on the several spectral index obtained from combination of different spectral bands to extract wetlands fraction occupation of land use. The obtained results show an accuracy to distinguish wetlands area from the other lad use themes using a fine exploitation on spectral index.

Keywords: multispectral data, EO1, landsat, wetlands, Ahaggar, Algeria

Procedia PDF Downloads 377

Authors: W. R. M. Shehani Shanika

Abstract:

Selling goods and services using images, names and personalities of celebrities has become a common marketing strategy identified in modern physical and online markets. Two concepts called globalization and open economy have given numerous reasons to develop businesses to earn higher profits. Therefore, global market plus domestic markets in various countries have vigorously endorsing images of famous sport stars, film stars, singing stars and cartoon characters for the purpose of increasing demand for goods and services rendered by them. It has been evident that these trade strategies have become a threat to famous personalities in financially and personally. Right to the image is a basic human right which celebrities owned to avoid themselves from various commercial exploitations. In this respect, this paper aims to assess whether the law relating to character merchandising satisfactorily protects right to image of celebrities. However, celebrities can decide how much they receive for each representation to the general public. Simply they have exclusive right to decide monetary value for their image. But most commonly every country uses law relating to unfair competition to regulate matters arise thereof. Legal norms in unfair competition are not enough to protect image of celebrities. Therefore, celebrities must be able to avoid unauthorized use of their images for commercial purposes by fraudulent traders and getting unjustly enriched, as their images have economic value. They have the right for use their image for any commercial purpose and earn profits. Therefore it is high time to recognize right to image as a new dimension to be protected in the legal framework of character merchandising. Unfortunately, to the author’s best knowledge there are no any uniform, single international standard which recognizes right to the image of celebrities in the context of character merchandising. The paper identifies it as a controversial legal barrier faced by celebrities in the rapidly evolving marketplace. Finally, this library-based research concludes with proposals to ensure the right to image more broadly in the legal context of character merchandising.

Keywords: brand endorsement, celebrity, character merchandising, intellectual property rights, right to image, unfair competition

Procedia PDF Downloads 138

Authors: Jade Edey, Andrew Bennett, Gareth Hathway

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Nuclear receptor-related 1 protein (also known as Nurr1 or NR4A2) is an orphan nuclear receptor which plays a vital role in the development, survival and maintenance of dopaminergic (DA) neurons particularly in the substantia nigra (SN). Increasing research has investigated Nurr1’s additional role within microglia and astrocytes where it has been suggested to act as a negative regulator of inflammation; potentially offering neuroprotection. Considering both DA neurodegeneration and neuroinflammation are commonly accepted constituents of Parkinson’s Disease (PD), understanding the mechanisms by which Nurr1 regulates inflammatory processes could provide an attractive therapeutic target. Nurr1 regulates inflammation via a transrepressive mechanism possibly dependent upon SUMOylation. In addition, Nurr1 can transactivate numerous genes involved in DA synthesis, such as Tyrosine Hydroxylase (TH). A C-terminal splice variant of Nurr1, Nurr-1a, has been reported in both neuronal and glial cells. However, research into its transcriptional activity is minimal. We employed in vitro methods such as SUMO-Pulldown experiments alongside Luciferase reporter assays to investigate the SUMOylation status and transactivation capabilities of Nurr1 and Nurr-1a respectively. The SUMO-Pulldown assay demonstrated Nurr-1a undergoes significantly more SUMO modification than its full-length variant. Consequently, despite having less transcriptional activation than Nurr1, Nurr1a may play a more prominent role in repression of microglial inflammation. Contrary to published literature we also identified that SUMOylation enhances transcriptional activation by Nurr1 and Nurr1a. SUMOylation-dependent increases in Nurr1 and Nurr1a transcriptional activation were only evident in neuronal SHSY5Y cells but not in HEK293 cells. This research provides novel insight into the regulation of Nurr-1a and indicates differential effects of SUMOylation dependent regulation in neuronal and inflammatory cells.

Keywords: nuclear receptors, Parkinson’s disease, inflammation, transcriptional regulation

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Authors: Ankit Kamboj, Shikha Talwar, Nilesh Powar

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To successfully deliver our products in the market, the employees need to be in a safe environment, especially in an industrial and manufacturing environment. The consequences of delinquency in wearing safety glasses while working in industrial plants could be high risk to employees, hence the need to develop a real-time automatic detection system which detects the persons (violators) not wearing safety glasses. In this study a convolutional neural network (CNN) algorithm called faster region based CNN (Faster RCNN) with rotated bounding box has been used for detecting safety glasses on persons; the algorithm has an advantage of detecting safety glasses with different orientation angles on the persons. The proposed method of rotational bounding boxes with a convolutional neural network first detects a person from the images, and then the method detects whether the person is wearing safety glasses or not. The video data is captured at the entrance of restricted zones of the industrial environment (manufacturing plant), which is further converted into images at 2 frames per second. In the first step, the CNN with pre-trained weights on COCO dataset is used for person detection where the detections are cropped as images. Then the safety goggles are labelled on the cropped images using the image labelling tool called roLabelImg, which is used to annotate the ground truth values of rotated objects more accurately, and the annotations obtained are further modified to depict four coordinates of the rectangular bounding box. Next, the faster RCNN with rotated bounding box is used to detect safety goggles, which is then compared with traditional bounding box faster RCNN in terms of detection accuracy (average precision), which shows the effectiveness of the proposed method for detection of rotatory objects. The deep learning benchmarking is done on a Dell workstation with a 16GB Nvidia GPU.

Keywords: CNN, deep learning, faster RCNN, roLabelImg rotated bounding box, safety goggle detection

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Authors: Jonathan Gong

Abstract:

Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Mojdeh Mohseni

Abstract:

In the context of tissue engineering, the effect of microtopography as afforded by scaffold morphology is an important design parameter. Since the morphology of pores can effect on cell behavior, in this study, porous Chitosan (CHIT) - Gelatin (GEL)- Alginate (ALG) scaffolds with microtubule orientation structure were manufactured by unidirectional freeze-drying method and the effect of pore morphology on differentiation of Mesenchymal Stem Cells (MSCs) was investigated. This study showed that, the provided scaffold with natural polymer had good properties for cell behavior and the pores with highest orientation rate have produced appropriate substrate for the differentiation of stem cells.

Keywords: Chitosan, gelatin, Alginate, pore morphology, stem cell differentiation

Procedia PDF Downloads 459

Authors: Lukasz Szymanski, Zbigniew Kolacinski, Grzegorz Raniszewski, Slawomir Wiak, Lukasz Pietrzak, Dariusz Koza, Karolina Przybylowska-Sygut, Ireneusz Majsterek, Zbigniew Kaminski, Justyna Fraczyk, Malgorzata Walczak, Beata Kolasinska, Adam Bednarek, Joanna Konka

Abstract:

The aim of this work is to investigate the influence of electromagnetic field from the range of radio frequencies on the desired nanoparticles for cancer therapy. In the article, the development and demonstration of the method and the model device for hyperthermic selective destruction of cancer cells are presented. This method was based on the synthesis and functionalization of carbon nanotubes serving as ferromagnetic material nanocontainers. The methodology of the production carbon - ferromagnetic nanocontainers (FNCs) includes: The synthesis of carbon nanotubes, chemical, and physical characterization, increasing the content of a ferromagnetic material and biochemical functionalization involving the attachment of the key addresses. The ferromagnetic nanocontainers were synthesised in CVD and microwave plasma system. Biochemical functionalization of ferromagnetic nanocontainers is necessary in order to increase the binding selectively with receptors presented on the surface of tumour cells. Multi-step modification procedure was finally used to attach folic acid on the surface of ferromagnetic nanocontainers. Pristine ferromagnetic carbon nanotubes are not suitable for application in medicine and biotechnology. Appropriate functionalization of ferromagnetic carbon nanotubes allows to receiving materials useful in medicine. Finally, a product contains folic acids on the surface of FNCs. The folic acid is a ligand of folate receptors – α which is overexpressed on the surface of epithelial tumours cells. It is expected that folic acids will be recognized and selectively bound by receptors presented on the surface of tumour cells. In our research, FNCs were covalently functionalized in a multi-step procedure. Ferromagnetic carbon nanotubes were oxidated using different oxidative agents. For this purpose, strong acids such as HNO3, or mixture HNO3 and H2SO4 were used. Reactive carbonyl and carboxyl groups were formed on the open sides and at the defects on the sidewalls of FNCs. These groups allow further modification of FNCs as a reaction of amidation, reaction of introduction appropriate linkers which separate solid surface of FNCs and ligand (folic acid). In our studies, amino acid and peptide have been applied as ligands. The last step of chemical modification was reaction-condensation with folic acid. In all reaction as coupling reagents were used derivatives of 1,3,5-triazine. The first trials in the device for hyperthermal RF generator have been done. The frequency of RF generator was in the ranges from 10 to 14Mhz and from 265 to 621kHz. Obtained functionalized nanoparticles enabled to reach the temperature of denaturation tumor cells in given frequencies.

Keywords: cancer colon cells, carbon nanotubes, hyperthermia, ligands

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