Search results for: malaria cells images
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5634

Search results for: malaria cells images

4374 Seashore Debris Detection System Using Deep Learning and Histogram of Gradients-Extractor Based Instance Segmentation Model

Authors: Anshika Kankane, Dongshik Kang

Abstract:

Marine debris has a significant influence on coastal environments, damaging biodiversity, and causing loss and damage to marine and ocean sector. A functional cost-effective and automatic approach has been used to look up at this problem. Computer vision combined with a deep learning-based model is being proposed to identify and categorize marine debris of seven kinds on different beach locations of Japan. This research compares state-of-the-art deep learning models with a suggested model architecture that is utilized as a feature extractor for debris categorization. The model is being proposed to detect seven categories of litter using a manually constructed debris dataset, with the help of Mask R-CNN for instance segmentation and a shape matching network called HOGShape, which can then be cleaned on time by clean-up organizations using warning notifications of the system. The manually constructed dataset for this system is created by annotating the images taken by fixed KaKaXi camera using CVAT annotation tool with seven kinds of category labels. A pre-trained HOG feature extractor on LIBSVM is being used along with multiple templates matching on HOG maps of images and HOG maps of templates to improve the predicted masked images obtained via Mask R-CNN training. This system intends to timely alert the cleanup organizations with the warning notifications using live recorded beach debris data. The suggested network results in the improvement of misclassified debris masks of debris objects with different illuminations, shapes, viewpoints and litter with occlusions which have vague visibility.

Keywords: computer vision, debris, deep learning, fixed live camera images, histogram of gradients feature extractor, instance segmentation, manually annotated dataset, multiple template matching

Procedia PDF Downloads 106
4373 Modified 'Perturb and Observe' with 'Incremental Conductance' Algorithm for Maximum Power Point Tracking

Authors: H. Fuad Usman, M. Rafay Khan Sial, Shahzaib Hamid

Abstract:

The trend of renewable energy resources has been amplified due to global warming and other environmental related complications in the 21st century. Recent research has very much emphasized on the generation of electrical power through renewable resources like solar, wind, hydro, geothermal, etc. The use of the photovoltaic cell has become very public as it is very useful for the domestic and commercial purpose overall the world. Although a single cell gives the low voltage output but connecting a number of cells in a series formed a complete module of the photovoltaic cells, it is becoming a financial investment as the use of it fetching popular. This also reduced the prices of the photovoltaic cell which gives the customers a confident of using this source for their electrical use. Photovoltaic cell gives the MPPT at single specific point of operation at a given temperature and level of solar intensity received at a given surface whereas the focal point changes over a large range depending upon the manufacturing factor, temperature conditions, intensity for insolation, instantaneous conditions for shading and aging factor for the photovoltaic cells. Two improved algorithms have been proposed in this article for the MPPT. The widely used algorithms are the ‘Incremental Conductance’ and ‘Perturb and Observe’ algorithms. To extract the maximum power from the source to the load, the duty cycle of the convertor will be effectively controlled. After assessing the previous techniques, this paper presents the improved and reformed idea of harvesting maximum power point from the photovoltaic cells. A thoroughly go through of the previous ideas has been observed before constructing the improvement in the traditional technique of MPP. Each technique has its own importance and boundaries at various weather conditions. An improved technique of implementing the use of both ‘Perturb and Observe’ and ‘Incremental Conductance’ is introduced.

Keywords: duty cycle, MPPT (Maximum Power Point Tracking), perturb and observe (P&O), photovoltaic module

Procedia PDF Downloads 176
4372 Understanding the Role of Nitric Oxide Synthase 1 in Low-Density Lipoprotein Uptake by Macrophages and Implication in Atherosclerosis Progression

Authors: Anjali Roy, Mirza S. Baig

Abstract:

Atherosclerosis is a chronic inflammatory disease characterized by the formation of lipid rich plaque enriched with necrotic core, modified lipid accumulation, smooth muscle cells, endothelial cells, leucocytes and macrophages. Macrophage foam cells play a critical role in the occurrence and development of inflammatory atherosclerotic plaque. Foam cells are the fat-laden macrophages in the initial stage atherosclerotic lesion formation. Foam cells are an indication of plaque build-up, or atherosclerosis, which is commonly associated with increased risk of heart attack and stroke as a result of arterial narrowing and hardening. The mechanisms that drive atherosclerotic plaque progression remain largely unknown. Dissecting the molecular mechanism involved in process of macrophage foam cell formation will help to develop therapeutic interventions for atherosclerosis. To investigate the mechanism, we studied the role of nitric oxide synthase 1(NOS1)-mediated nitric oxide (NO) on low-density lipoprotein (LDL) uptake by bone marrow derived macrophages (BMDM). Using confocal microscopy, we found that incubation of macrophages with NOS1 inhibitor, TRIM (1-(2-Trifluoromethylphenyl) imidazole) or L-NAME (N omega-nitro-L-arginine methyl ester) prior to LDL treatment significantly reduces the LDL uptake by BMDM. Further, addition of NO donor (DEA NONOate) in NOS1 inhibitor treated macrophages recovers the LDL uptake. Our data strongly suggest that NOS1 derived NO regulates LDL uptake by macrophages and foam cell formation. Moreover, we also checked proinflammatory cytokine mRNA expression through real time PCR in BMDM treated with LDL and copper oxidized LDL (OxLDL) in presences and absences of inhibitor. Normal LDL does not evoke cytokine expression whereas OxLDL induced proinflammatory cytokine expression which significantly reduced in presences of NOS1 inhibitor. Rapid NOS-1-derived NO and its stable derivative formation act as signaling agents for inducible NOS-2 expression in endothelial cells, leading to endothelial vascular wall lining disruption and dysfunctioning. This study highlights the role of NOS1 as critical players of foam cell formation and would reveal much about the key molecular proteins involved in atherosclerosis. Thus, targeting NOS1 would be a useful strategy in reducing LDL uptake by macrophages at early stage of disease and hence dampening the atherosclerosis progression.

Keywords: atherosclerosis, NOS1, inflammation, oxidized LDL

Procedia PDF Downloads 127
4371 Multi-Scaled Non-Local Means Filter for Medical Images Denoising: Empirical Mode Decomposition vs. Wavelet Transform

Authors: Hana Rabbouch

Abstract:

In recent years, there has been considerable growth of denoising techniques mainly devoted to medical imaging. This important evolution is not only due to the progress of computing techniques, but also to the emergence of multi-resolution analysis (MRA) on both mathematical and algorithmic bases. In this paper, a comparative study is conducted between the two best-known MRA-based decomposition techniques: the Empirical Mode Decomposition (EMD) and the Discrete Wavelet Transform (DWT). The comparison is carried out in a framework of multi-scale denoising, where a Non-Local Means (NLM) filter is performed scale-by-scale to a sample of benchmark medical images. The results prove the effectiveness of the multiscaled denoising, especially when the NLM filtering is coupled with the EMD.

Keywords: medical imaging, non local means, denoising, multiscaled analysis, empirical mode decomposition, wavelets

Procedia PDF Downloads 141
4370 Review on Quaternion Gradient Operator with Marginal and Vector Approaches for Colour Edge Detection

Authors: Nadia Ben Youssef, Aicha Bouzid

Abstract:

Gradient estimation is one of the most fundamental tasks in the field of image processing in general, and more particularly for color images since that the research in color image gradient remains limited. The widely used gradient method is Di Zenzo’s gradient operator, which is based on the measure of squared local contrast of color images. The proposed gradient mechanism, presented in this paper, is based on the principle of the Di Zenzo’s approach using quaternion representation. This edge detector is compared to a marginal approach based on multiscale product of wavelet transform and another vector approach based on quaternion convolution and vector gradient approach. The experimental results indicate that the proposed color gradient operator outperforms marginal approach, however, it is less efficient then the second vector approach.

Keywords: gradient, edge detection, color image, quaternion

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4369 Successes on in vitro Isolated Microspores Embryogenesis

Authors: Zelikha Labbani

Abstract:

The In Vitro isolated micro spore culture is the most powerful androgenic pathway to produce doubled haploid plants in the short time. To deviate a micro spore toward embryogenesis, a number of factors, different for each species, must concur at the same time and place. Once induced, the micro spore undergoes numerous changes at different levels, from overall morphology to gene expression. Induction of micro spore embryogenesis not only implies the expression of an embryogenic program, but also a stress-related cellular response and a repression of the gametophytic program to revert the microspore to a totipotent status. As haploid single cells, micro spore became a strategy to achieve various objectives particularly in genetic engineering. In this study we would show the most recent advances in the producing haploid embryos via In Vitro isolated micro spore culture.

Keywords: haploid cells, In Vitro isolated microspore culture, success

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4368 Pt Decorated Functionalized Acetylene Black as Efficient Cathode Material for Li Air Battery and Fuel Cell Applications

Authors: Rajashekar Badam, Vedarajan Raman, Noriyoshi Matsumi

Abstract:

Efficiency of energy converting and storage systems like fuel cells and Li-Air battery principally depended on oxygen reduction reaction (ORR) which occurs at cathode. As the kinetics of the ORR is very slow, it becomes the rate determining step. Exploring carbon substrates for enhancing the dispersion and activity of the metal catalyst and commercially viable simple preparation method is a very crucial area of research in the field of energy materials. Hence, many researchers made large number of carbon-based ORR materials today. But, there are hardly few studies on the effect of interaction between Pt-carbon and carbon-electrolyte on activity. In this work, we have prepared functionalized carbon-based Pt catalyst (Pt-FAB) with enhanced interfacial properties that lead to efficient ORR catalysis. The present work deals with a single-pot method to exfoliate and functionalized acetylene black with enhanced interaction with Pt as well as electrolyte. Acetylene black was functionalized and exfoliated using a facile single pot acid treatment method. The resulted FAB was further decorated with Pt-nano particles (Pt-np). The TEM images of Pt-FAB with uniformly decorated Pt-np of ~3 nm. Further, XPS studies of Pt 4f peak revealed that Pt0 peak was shifted by 0.4 eV in Pt-FAB compared to binding energy of typical Pt⁰ found in Pt/C. The shift can be ascribed to the modulation of electronic state and strong electronic interaction of Pt with carbon. Modulated electronic structure of Pt and strong electronic interaction of Pt with FAB enhances the catalytic activity and durability respectively. To understand the electrode electrolyte interface, electrochemical impedance spectroscopy was carried out. These measurements revealed that the charge transfer resistance of electrode to electrolyte for Pt-FAB is 10 times smaller than that of conventional Pt/C. The interaction with electrolyte helps reduce the interface boundaries, which in turn affects the overall catalytic performance of the electrode. Cyclic voltammetric measurements in 0.1M HClO₄ aq. at a potential scan rate of 50 mVs-1 was employed to evaluate electrochemical surface area (ECSA) of Pt. ECSA of Pt-FAB was found to be as high as 67.2 m²g⁻¹. The three-electrode system showed very high ORR catalytic activity. Mass activity at 0.9 V vs. RHE showed 460 A/g which is much higher than the DOE target values for the year 2020. Further, it showed enhanced performance by showing 723 mW/cm² of highest power density and 1006 mA/cm² of current density at 0.6 V in fuel cell single cell type configuration and 1030 mAhg⁻¹ of rechargeable capacity in Li air battery application. The higher catalytic activity can be ascribed to the improved interaction of FAB with Pt and electrolyte. The aforementioned results evince that Pt-FAB will be a promising cathode material for efficient ORR with significant cyclability for its application in fuel cells and Li-Air batteries. In conclusion, a disordered material was prepared from AB and was systematically characterized. The extremely high ORR activity and ease of preparation make it competent for replacing commercially available ORR materials.

Keywords: functionalized acetylene black, oxygen reduction reaction, fuel cells, Functionalized battery

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4367 Deep Learning-Based Object Detection on Low Quality Images: A Case Study of Real-Time Traffic Monitoring

Authors: Jean-Francois Rajotte, Martin Sotir, Frank Gouineau

Abstract:

The installation and management of traffic monitoring devices can be costly from both a financial and resource point of view. It is therefore important to take advantage of in-place infrastructures to extract the most information. Here we show how low-quality urban road traffic images from cameras already available in many cities (such as Montreal, Vancouver, and Toronto) can be used to estimate traffic flow. To this end, we use a pre-trained neural network, developed for object detection, to count vehicles within images. We then compare the results with human annotations gathered through crowdsourcing campaigns. We use this comparison to assess performance and calibrate the neural network annotations. As a use case, we consider six months of continuous monitoring over hundreds of cameras installed in the city of Montreal. We compare the results with city-provided manual traffic counting performed in similar conditions at the same location. The good performance of our system allows us to consider applications which can monitor the traffic conditions in near real-time, making the counting usable for traffic-related services. Furthermore, the resulting annotations pave the way for building a historical vehicle counting dataset to be used for analysing the impact of road traffic on many city-related issues, such as urban planning, security, and pollution.

Keywords: traffic monitoring, deep learning, image annotation, vehicles, roads, artificial intelligence, real-time systems

Procedia PDF Downloads 200
4366 Sub-Pixel Mapping Based on New Mixed Interpolation

Authors: Zeyu Zhou, Xiaojun Bi

Abstract:

Due to the limited environmental parameters and the limited resolution of the sensor, the universal existence of the mixed pixels in the process of remote sensing images restricts the spatial resolution of the remote sensing images. Sub-pixel mapping technology can effectively improve the spatial resolution. As the bilinear interpolation algorithm inevitably produces the edge blur effect, which leads to the inaccurate sub-pixel mapping results. In order to avoid the edge blur effect that affects the sub-pixel mapping results in the interpolation process, this paper presents a new edge-directed interpolation algorithm which uses the covariance adaptive interpolation algorithm on the edge of the low-resolution image and uses bilinear interpolation algorithm in the low-resolution image smooth area. By using the edge-directed interpolation algorithm, the super-resolution of the image with low resolution is obtained, and we get the percentage of each sub-pixel under a certain type of high-resolution image. Then we rely on the probability value as a soft attribute estimate and carry out sub-pixel scale under the ‘hard classification’. Finally, we get the result of sub-pixel mapping. Through the experiment, we compare the algorithm and the bilinear algorithm given in this paper to the results of the sub-pixel mapping method. It is found that the sub-pixel mapping method based on the edge-directed interpolation algorithm has better edge effect and higher mapping accuracy. The results of the paper meet our original intention of the question. At the same time, the method does not require iterative computation and training of samples, making it easier to implement.

Keywords: remote sensing images, sub-pixel mapping, bilinear interpolation, edge-directed interpolation

Procedia PDF Downloads 229
4365 The UAV Feasibility Trajectory Prediction Using Convolution Neural Networks

Authors: Adrien Marque, Daniel Delahaye, Pierre Maréchal, Isabelle Berry

Abstract:

Wind direction and uncertainty are crucial in aircraft or unmanned aerial vehicle trajectories. By computing wind covariance matrices on each spatial grid point, these spatial grids can be defined as images with symmetric positive definite matrix elements. A data pre-processing step, a specific convolution, a specific max-pooling, and a specific flatten layers are implemented to process such images. Then, the neural network is applied to spatial grids, whose elements are wind covariance matrices, to solve classification problems related to the feasibility of unmanned aerial vehicles based on wind direction and wind uncertainty.

Keywords: wind direction, uncertainty level, unmanned aerial vehicle, convolution neural network, SPD matrices

Procedia PDF Downloads 49
4364 Nano Gold and Silver for Control of Mosquitoes Manipulating Nanogeometries

Authors: Soam Prakash, Namita Soni

Abstract:

The synthesis of metallic nanoparticles is an active area of academic and more significantly, applied research in nanotechnology. Currently, nanoparticle research is an area of intense scientific interest. Silver (Ag) and Gold (Au) nanoparticles (NPs) have been the focus of fungi and plant based syntheses. Silver and gold nanoparticles are nanoparticles of silver and gold. These particles are of between 1 nm and 100 nm in size. Silver and gold have been use in the wide variety of potential applications in biomedical, optical, electronic field, treatment of burns, wounds, and several bacterial infections. There is a crucial need to produce new insecticides due to resistance and high-cost of organic insecticides which are more environmentally-friendly, safe, and target-specific. Synthesizing nanoparticles using plants and microorganisms can eliminate this problem by making the nanoparticles more biocompatible. Here we reviewed the mosquitocidal and antimicrobials activity of silver and gold nanoparticles using fungi, plants as well as bacteria.

Keywords: nano gold, nano silver, Malaria, Chikengunia, dengue control

Procedia PDF Downloads 436
4363 Metal Nanoparticles Caused Death of Metastatic MDA-MB-231 Cells

Authors: O. S. Adeyemi, C. G. Whiteley

Abstract:

The present study determined the toxic potential of metal nanoparticles in cell culture system. Silver and gold nanoparticles were synthesized and characterized following established "green" protocols. The synthesized nanoparticles, in varying concentrations ranging from 0.1–100 µM were evaluated for toxicity in metastatic MDA-MB-231 cells. The nanoparticles promoted a generation of reactive oxygen species and reduced cell viability to less than 50% in the demonstration of cellular toxicity. The nanoparticles; gold and the silver-gold mixture had IC50 values of 56.65 and 18.44 µM respectively. The IC50 concentration for silver nanoparticles could not be determined. Furthermore, the probe of the cell death using flow cytometry and confocal microscopy revealed the partial involvement of apoptosis as well as necrosis. Our results revealed cellular toxicity caused by the nanoparticles but the mechanism remains yet undefined.

Keywords: cell death, nanomedicine, nanotoxicology, toxicity

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4362 Synthesis and Application of an Organic Dye in Nanostructure Solar Cells Device

Authors: M. Hoseinnezhad, K. Gharanjig

Abstract:

Two organic dyes comprising carbazole as the electron donors and cyanoacetic acid moieties as the electron acceptors were synthesized. The organic dye was prepared by standard reaction from carbazole as the starting material. To this end, carbazole was reacted with bromobenzene and further oxidation and reacted with cyanoacetic acid. The obtained organic dye was purified and characterized using differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FT-IR), proton nuclear magnetic resonance (1HNMR), carbon nuclear magnetic resonance (13CNMR) and elemental analysis. The influence of heteroatom on carbazole donors and cyno substitution on the acid acceptor is evidenced by spectral and electrochemical photovoltaic experiments. Finally, light fastness properties for organic dye were investigated.

Keywords: dye-sensitized solar cells, indoline dye, nanostructure, oxidation potential, solar energy

Procedia PDF Downloads 193
4361 Multicellular Cancer Spheroids as an in Vitro Model for Localized Hyperthermia Study

Authors: Kamila Dus-Szachniewicz, Artur Bednarkiewicz, Katarzyna Gdesz-Birula, Slawomir Drobczynski

Abstract:

In modern oncology hyperthermia (HT) is defined as a controlled tumor heating. HT treatment temperatures range between 40–48 °C and can selectively damage heat-sensitive cancer cells or limit their further growth, usually with minimal injury to healthy tissues. Despite many advantages, conventional whole-body and regional hyperthermia have clinically relevant side effects, including cardiac and vascular disorders. Additionally, the lack of accessibility of deep-seated tumor sites and impaired targeting micrometastases renders HT less effective. It is believed that above disadvantages can significantly overcome by the application of biofunctionalized microparticles, which can specifically target tumor sites and become activated by an external stimulus to provide a sufficient cellular response. In our research, the unique optical tweezers system have enabled capturing the silica microparticles, primary cells and tumor spheroids in highly controllable and reproducible environment to study the impact of localized heat stimulation on normal and pathological cell and within multicellular tumor spheroid. High throughput spheroid model was introduced to better mimic the response to HT treatment on tumors in vivo. Additionally, application of local heating of tumor spheroids was performed in strictly controlled conditions resembling tumor microenvironment (temperature, pH, hypoxia, etc.), in response to localized and nonhomogeneous hyperthermia in the extracellular matrix, which promotes tumor progression and metastatic spread. The lack of precise control over these well- defined parameters in basic research leads to discrepancies in the response of tumor cells to the new treatment strategy in preclinical animal testing. The developed approach enables also sorting out subclasses of cells, which exhibit partial or total resistance to therapy, in order to understand fundamental aspects of the resistance shown by given tumor cells in response to given therapy mode and conditions. This work was funded by the National Science Centre (NCN, Poland) under grant no. UMO-2017/27/B/ST7/01255.

Keywords: cancer spheroids, hyperthermia, microparticles, optical tweezers

Procedia PDF Downloads 133
4360 Visualizing Matrix Metalloproteinase-2 Activity Using Extracellular Matrix-Immobilized Fluorescence Resonance Energy Transfer Bioprobe in Cancer Cells

Authors: Hawon Lee, Young-Pil Kim

Abstract:

Visualizing matrix metalloproteinases (MMPs) activity is necessary for understanding cancer metastasis because they are implicated in cell migration and invasion by degrading the extracellular matrix (ECM). While much effort has been made to sense the MMP activity, but extracellularly long-term monitoring of MMP activity still remains challenging. Here, we report a collagen-bound fluorescent bioprobe for the detection of MMP-2 activity in the extracellular environment. This bioprobe consists of ECM-immobilized part (including collagen-bound protein) and MMP-sensing part (including peptide substrate linked with fluorescence resonance energy transfer (FRET) coupler between donor green fluorescent protein (GFP) and acceptor TAMRA dye), which was constructed through intein-mediated self-splicing conjugation. Upon being immobilized on the collagen-coated surface, this bioprobe enabled efficient long-lasting observation of MMP-2 activity in the cultured cells without affecting cell growth and viability. As a result, the FRET ratio (acceptor/donor) decreased as the MMP2 activity increased in cultured cancer cells. Furthermore, unlike wild-type MMP-2, mutated MMP-2 expression (Y580A in the hemopexin region) gave rise to lowering the secretion of MMP-2 in HeLa. Conclusively, our method is anticipated to find applications for tracing and visualizing enzyme activity.

Keywords: collagen, ECM, FRET, MMP

Procedia PDF Downloads 202
4359 Ultrastructural Characterization of Lipid Droplets of Rat Hepatocytes after Whole Body 60-Cobalt Gamma Radiation

Authors: Ivna Mororó, Lise P. Labéjof, Stephanie Ribeiro, Kely Almeida

Abstract:

Lipid droplets (LDs) are normally presented in greater or lesser number in the cytoplasm of almost all eukaryotic and some prokaryotic cells. They are independent organelles composed of a lipid ester core and a surface phospholipid monolayer. As a lipid storage form, they provide an available source of energy for the cell. Recently it was demonstrated that they play an important role in other many cellular processes. Among the many unresolved questions about them, it is not even known how LDs is formed, how lipids are recruited to LDs and how they interact with the other organelles. Excess fat in the organism is pathological and often associated with the development of some genetic, hormonal or behavioral diseases. The formation and accumulation of lipid droplets in the cytoplasm can be increased by exogenous physical or chemical agents. It is well known that ionizing radiation affects lipid metabolism resulting in increased lipogenesis in cells, but the details of this process are unknown. To better understand the mode of formation of LDs in liver cells, we investigate their ultrastructural morphology after irradiation. For that, Wistar rats were exposed to whole body gamma radiation from 60-cobalt at various single doses. Samples of the livers were processed for analysis under a conventional transmission electron microscope. We found that when compared to controls, morphological changes in liver cells were evident at the higher doses of radiation used. It was detected a great number of lipid droplets of different sizes and homogeneous content and some of them merged each other. In some cells, it was observed diffused LDs, not limited by a monolayer of phospholipids. This finding suggests that the phospholipid monolayer of the LDs was disrupted by ionizing radiation exposure that promotes lipid peroxydation of endo membranes. Thus the absence of the phospholipid monolayer may prevent the realization of some cellular activities as follow: - lipid exocytosis which requires the merging of LDs membrane with the plasma membrane; - the interaction of LDs with other membrane-bound organelles such as the endoplasmic reticulum (ER), the golgi and mitochondria and; - lipolysis of lipid esters contained in the LDs which requires the presence of enzymes located in membrane-bound organelles as ER. All these impediments can contribute to lipid accumulation in the cytoplasm and the development of diseases such as liver steatosis, cirrhosis and cancer.

Keywords: radiobiology, hepatocytes, lipid metabolism, transmission electron microscopy

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4358 Prevalence of Anemia and Iron Deficiency in Women of Childbearing Age in the North-West of Libya

Authors: Mustafa Ali Abugila, Basma Nuri Kajruba, Hanan Elhadi, Rehab Ramadan Wali

Abstract:

Iron deficiency anemia is characterized by a decrease of Hb (hemoglobin), serum iron, ferritin, and RBC (red blood cells) (shape and size). Also, it is characterized by an increase in total iron binding capacity (TIBC). Red blood cells become microctytic and hypochromic due to a decrease in iron content. This study was conducted in the north west of Libya and included 210 women in childbearing age (18-45 years) who were visiting women clinic. After filling the questionnaire, blood samples were taken and analyzed for hematological and biochemical profiles. Biochemical tests included measurement of serum iron, ferritin, and total iron binding capacity (TIBC). Among the total sample (210 women), there were 87 (41.42%) pregnant and 123 (58.57%) non-pregnant women (includes married and single). Pregnant women (87) were classified according to the gestational age into first, second, and third trimesters. The means of biochemical and hematological parameters in the studied samples were: Hb = 10.37± 2.02 g/dl, RBC = 3.78± 1.037 m/m3, serum iron 61.86± 40.28 µg/dl, and TIBC = 386.01 ± 94.91 µg/dl. In this study, we considered that any women have hemoglobin below 11.5 g/dl is anemic. 89.1%, 69.5%, and 47.8% of pregnant women who belong to third trimester had low (below normal value) Hb, serum iron, and ferritin, i.e. iron deficiency anemia was more common in third trimester among the first and the second trimesters. Third trimester pregnant women also had high TIBC more than first and second trimesters.

Keywords: red blood cells, hemoglobin, total iron binding capacity, ferritin

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4357 Sesamol Decreases Melanin Biosynthesis via Melanogenesis-Related Gene Expressions in Melan-a Cells

Authors: Seung-Hwa Baek, In-Jung Nam, Sang-Han Lee

Abstract:

The development of anti-melanogenic agents is important for the prevention of serious esthetic problem like a melasma, freckle, age spots, and chloasma. The aim of this study was to investigate the anti-melanogenic effect of sesamol, an active lignan isolated from sesame seed, by mushroom and cellular tyrosinase assay, melanin content and the analysis of melanogensis-related mRNA expressions in melana cells. Sesamol showed strong inhibitory activity against the mushroom tyrosinase in a dose-dependent manner. Intracellular tyrosinase inhibition activity was also confirmed by zymography. At a concentration of 50 μM, sesamol inhibited melanin production in melan-a cells with no cytoxicity while those of phenylthiourea (PTU) as a positive control were the same condition. Sesamol significantly inhibited the expression of melanogensis-related genes, such as tyrosinase, tyrosinase-related protein-1 (TRP-1), dopachrome tautomerase (Dct), microphthalmia-associated transcription factor (MITF) and melanocortin 1 receptor (MC1R). These findings indicate that sesamol could reduce melanin biosynthesis via the downregulation of tyrosinase activity and melanin production via subsequent gene expression of melanogenesis-related proteins. Together, these results suggest that the sesamol have strong potential in inhibiting melanin biosynthesis, in that the substance may be used as a new skin-whitening agent of cosmetic materials.

Keywords: sesamol, sesame seed, melanin biosynthesis, melanogenesis-related gene, skin-whitening agent

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4356 Investigation of Cytotoxic Compounds in Ethyl Acetate and Chloroform Extracts of Nigella sativa Seeds by Sulforhodamine-B Assay-Guided Fractionation

Authors: Harshani Uggallage, Kapila D. Dissanayaka

Abstract:

A Sulforhodamine-B assay-guided fractionation on Nigella sativa seeds was conducted to determine the presence of cytotoxic compounds against human hepatoma (HepG2) cells. Initially, a freeze-dried sample of Nigella sativa seeds was sequentially extracted into solvents of increasing polarities. Crude extracts from the sequential extraction of Nigella sativa seeds in chloroform and ethyl acetate showed the highest cytotoxicity. The combined mixture of these two extracts was subjected to bioassay guided fractionation using a modified Kupchan method of partitioning, followed by Sephadex® LH-20 chromatography. This chromatographic separation process resulted in a column fraction with a convincing IC50 (half-maximal inhibitory concentration) value of 13.07µg/ml, which is considerable for developing therapeutic drug leads against human hepatoma. Reversed phase High-Performance Liquid Chromatography (HPLC) was finally conducted for the same column fraction, and the result indicates the presence of one or several main cytotoxic compounds against human HepG2 cells.

Keywords: cytotoxic compounds, half-maximal inhibitory concentration, high-performance liquid chromatography, human HepG2 cells, nigella sativa seeds, Sulforhodamine-B assay

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4355 Endocardial Ultrasound Segmentation using Level Set method

Authors: Daoudi Abdelaziz, Mahmoudi Saïd, Chikh Mohamed Amine

Abstract:

This paper presents a fully automatic segmentation method of the left ventricle at End Systolic (ES) and End Diastolic (ED) in the ultrasound images by means of an implicit deformable model (level set) based on Geodesic Active Contour model. A pre-processing Gaussian smoothing stage is applied to the image, which is essential for a good segmentation. Before the segmentation phase, we locate automatically the area of the left ventricle by using a detection approach based on the Hough Transform method. Consequently, the result obtained is used to automate the initialization of the level set model. This initial curve (zero level set) deforms to search the Endocardial border in the image. On the other hand, quantitative evaluation was performed on a data set composed of 15 subjects with a comparison to ground truth (manual segmentation).

Keywords: level set method, transform Hough, Gaussian smoothing, left ventricle, ultrasound images.

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4354 ORR Electrocatalyst for Batteries and Fuel Cells Development with SIO₂/Carbon Black Based Composite Nanomaterials

Authors: Maryam Kiani

Abstract:

This study focuses on the development of composite nanomaterials based on SiO₂ and carbon black for oxygen reduction reaction (ORR) electrocatalysts in batteries and fuel cells. The aim was to explore the potential of these composite materials as efficient catalysts for ORR, which is a critical process in energy conversion devices. The SiO₂/carbon black composite nanomaterials were synthesized using a facile and scalable method. The morphology, structure, and electrochemical properties of the materials were characterized using various techniques including scanning electron microscopy (SEM), X-ray diffraction (XRD), and electrochemical measurements. The results demonstrated that the incorporation of SiO₂ into the carbon black matrix enhanced the ORR performance of the composite material. The composite nanomaterials exhibited improved electrocatalytic activity, enhanced stability, and increased durability compared to pure carbon black. The presence of SiO₂ facilitated the formation of active sites, improved electron transfer, and increased the surface area available for ORR. This study contributes to the advancement of battery and fuel cell technology by offering a promising approach for the development of high-performance ORR electrocatalysts. The SiO₂/carbon black composite nanomaterials show great potential for improving the efficiency and durability of energy conversion devices, leading to more sustainable and efficient energy solutions.

Keywords: ORR, fuel cells, batteries, electrocatalyst

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4353 Cationic Solid Lipid Nanoparticles Conjugated with Anti-Melantransferrin and Apolipoprotein E for Delivering Doxorubicin to U87MG Cells

Authors: Yung-Chih Kuo, Yung-I Lou

Abstract:

Cationic solid lipid nanoparticles (CSLNs) with anti-melanotransferrin (AMT) and apolipoprotein E (ApoE) were used to carry antimitotic doxorubicin (Dox) across the blood–brain barrier (BBB) for glioblastoma multiforme (GBM) treatment. Dox-loaded CSLNs were prepared in microemulsion, grafted covalently with AMT and ApoE, and applied to human brain microvascular endothelial cells (HBMECs), human astrocytes, and U87MG cells. Experimental results revealed that an increase in the weight percentage of stearyl amine (SA) from 0% to 20% increased the size of AMT-ApoE-Dox-CSLNs. In addition, an increase in the stirring rate from 150 rpm to 450 rpm decreased the size of AMT-ApoE-Dox-CSLNs. An increase in the weight percentage of SA from 0% to 20% enhanced the zeta potential of AMT-ApoE-Dox-CSLNs. Moreover, an increase in the stirring rate from 150 rpm to 450 rpm reduced the zeta potential of AMT-ApoE-Dox-CSLNs. AMT-ApoE-Dox-CSLNs exhibited a spheroid-like geometry, a minor irregular boundary deviating from spheroid, and a somewhat distorted surface with a few zigzags and sharp angles. The encapsulation efficiency of Dox in CSLNs decreased with increasing weight percentage of Dox and the order in the encapsulation efficiency of Dox was 10% SA > 20% SA > 0% SA. However, the reverse order was true for the release rate of Dox, suggesting that AMT-ApoE-Dox-CSLNs containing 10% SA had better-sustained release characteristics. An increase in the concentration of AMT from 2.5 to 7.5 μg/mL slightly decreased the grafting efficiency of AMT and an increase in that from 7.5 to 10 μg/mL significantly decreased the grafting efficiency. Furthermore, an increase in the concentration of ApoE from 2.5 to 5 μg/mL slightly reduced the grafting efficiency of ApoE and an increase in that from 5 to 10 μg/mL significantly reduced the grafting efficiency. Also, AMT-ApoE-Dox-CSLNs at 10 μg/mL of ApoE could slightly reduce the transendothelial electrical resistance (TEER) and increase the permeability of propidium iodide (PI). An incorporation of 10 μg/mL of ApoE could reduce the TEER and increase the permeability of PI. AMT-ApoE-Dox-CSLNs at 10 μg/mL of AMT and 5-10 μg/mL of ApoE could significantly enhance the permeability of Dox across the BBB. AMT-ApoE-Dox-CSLNs did not induce serious cytotoxicity to HBMECs. The viability of HBMECs was in the following order: AMT-ApoE-Dox-CSLNs = AMT-Dox-CSLNs = Dox-CSLNs > Dox. The order in the efficacy of inhibiting U87MG cells was AMT-ApoE-Dox-CSLNs > AMT-Dox-CSLNs > Dox-CSLNs > Dox. A surface modification of AMT and ApoE could promote the delivery of AMT-ApoE-Dox-CSLNs to cross the BBB via melanotransferrin and low density lipoprotein receptor. Thus, AMT-ApoE-Dox-CSLNs have appropriate physicochemical properties and can be a potential colloidal delivery system for brain tumor chemotherapy.

Keywords: anti-melanotransferrin, apolipoprotein E, cationic catanionic solid lipid nanoparticle, doxorubicin, U87MG cells

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4352 Study on Surface Morphology and Reflectance of Solar Cells Applied in Pyramid Structures

Authors: Zong-Sheng Chen

Abstract:

With the advancement of technology, human activities have increased greenhouse gas emissions and fossil fuel energy production, leading to increasingly severe global warming. To mitigate global warming, energy conservation and carbon reduction have become global goals. Solar energy, a renewable energy source, not only helps achieve energy conservation and carbon reduction but also serves as an efficient energy generation method. Solar energy, derived from sunlight, is an endless and promising energy source capable of meeting high energy demands sustainably. In recent years, many countries around the world have been developing the solar energy industry, and Taiwan is no exception. Positioned in the subtropical region, Taiwan possesses geographical advantages conducive to solar energy utilization. Furthermore, Taiwan's well-developed semiconductor technology and sophisticated equipment make it highly suitable for the development of high-efficiency solar cells. This study focuses on investigating the anti-reflection properties of solar cells. Through metal-assisted chemical etching, pyramid structures are etched to allow sunlight to pass through, achieving secondary or higher-order reflections on the surface of these structures. This trapping of light within the substrate reduces reflection rates and increases conversion efficiency.

Keywords: solar cell, reflectance, pyramidal structure, potassium hydroxide

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4351 Training a Neural Network to Segment, Detect and Recognize Numbers

Authors: Abhisek Dash

Abstract:

This study had three neural networks, one for number segmentation, one for number detection and one for number recognition all of which are coupled to one another. All networks were trained on the MNIST dataset and were convolutional. It was assumed that the images had lighter background and darker foreground. The segmentation network took 28x28 images as input and had sixteen outputs. Segmentation training starts when a dark pixel is encountered. Taking a window(7x7) over that pixel as focus, the eight neighborhood of the focus was checked for further dark pixels. The segmentation network was then trained to move in those directions which had dark pixels. To this end the segmentation network had 16 outputs. They were arranged as “go east”, ”don’t go east ”, “go south east”, “don’t go south east”, “go south”, “don’t go south” and so on w.r.t focus window. The focus window was resized into a 28x28 image and the network was trained to consider those neighborhoods which had dark pixels. The neighborhoods which had dark pixels were pushed into a queue in a particular order. The neighborhoods were then popped one at a time stitched to the existing partial image of the number one at a time and trained on which neighborhoods to consider when the new partial image was presented. The above process was repeated until the image was fully covered by the 7x7 neighborhoods and there were no more uncovered black pixels. During testing the network scans and looks for the first dark pixel. From here on the network predicts which neighborhoods to consider and segments the image. After this step the group of neighborhoods are passed into the detection network. The detection network took 28x28 images as input and had two outputs denoting whether a number was detected or not. Since the ground truth of the bounds of a number was known during training the detection network outputted in favor of number not found until the bounds were not met and vice versa. The recognition network was a standard CNN that also took 28x28 images and had 10 outputs for recognition of numbers from 0 to 9. This network was activated only when the detection network votes in favor of number detected. The above methodology could segment connected and overlapping numbers. Additionally the recognition unit was only invoked when a number was detected which minimized false positives. It also eliminated the need for rules of thumb as segmentation is learned. The strategy can also be extended to other characters as well.

Keywords: convolutional neural networks, OCR, text detection, text segmentation

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4350 Color Image Enhancement Using Multiscale Retinex and Image Fusion Techniques

Authors: Chang-Hsing Lee, Cheng-Chang Lien, Chin-Chuan Han

Abstract:

In this paper, an edge-strength guided multiscale retinex (EGMSR) approach will be proposed for color image contrast enhancement. In EGMSR, the pixel-dependent weight associated with each pixel in the single scale retinex output image is computed according to the edge strength around this pixel in order to prevent from over-enhancing the noises contained in the smooth dark/bright regions. Further, by fusing together the enhanced results of EGMSR and adaptive multiscale retinex (AMSR), we can get a natural fused image having high contrast and proper tonal rendition. Experimental results on several low-contrast images have shown that our proposed approach can produce natural and appealing enhanced images.

Keywords: image enhancement, multiscale retinex, image fusion, EGMSR

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4349 Identification of Individuals in Forensic Situations after Allo-Hematopoietic Stem Cell Transplantation

Authors: Anupuma Raina, Ajay Parkash

Abstract:

In forensic investigation, DNA analysis helps in the identification of a particular individual under investigation. A set of Short Tandem Repeats loci are widely used for individualization at a molecular level in forensic testing. STRs with tetrameric repeats of DNA are highly polymorphic and widely used for forensic DNA analysis. Identification of an individual became challenging for forensic examiners after Hematopoietic Stem Cell Transplantation. HSCT is a well-accepted and life-saving treatment to treat malignant and nonmalignant diseases. It involves the administration of healthy donor stem cells to replace the patient’s own unhealthy stem cells. A successful HSCT results in complete donor-derived cells in a patient’s hematopoiesis and hence have the capability to change the genetic makeup of the patient. Although an individual who has undergone HSCT and then committed a crime is a very rare situation, but not impossible. Keeping such a situation in mind, various biological samples like blood, buccal swab, and hair follicle were collected and studied after a certain interval of time after HSCT. Blood was collected from both the patient and the donor before the transplant. The DNA profile of both was analyzed using a short tandem repeat kit for autosomal chromosomes. Among all exhibits studied, only hair follicles were found to be the most suitable biological exhibit, as no donor DNA profile was observed for up to 90 days of study.

Keywords: chimerism, HSCT, STRs analysis, forensic identification

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4348 Development and Evaluation of a Gut-Brain Axis Chip Based on 3D Printing Interconnecting Microchannel Scaffolds

Authors: Zhuohan Li, Jing Yang, Yaoyuan Cui

Abstract:

The gut-brain axis (GBA), a communication network between gut microbiota and the brain, benefits for investigation of brain diseases. Currently, organ chips are considered one of the potential tools for GBA research. However, most of the available GBA chips have limitations in replicating the three-dimensional (3D) growth environment of cells and lack the required cell types for barrier function. In the present study, a microfluidic chip was developed for GBA interaction. Blood-brain barrier (BBB) module was prepared with HBMEC, HBVP, U87 cells and decellularized matrix (dECM). Intestinal epithelial barrier (IEB) was prepared with Caco-2 and vascular endothelial cells and dECM. GBA microfluidic device was integrated with IEB and BBB modules using 3D printing interconnecting microchannel scaffolds. BBB and IEB interaction on this GBA chip were evaluated with lipopolysaccharide (LPS) exposure. The present GBA chip achieved multicellular three-dimensional cultivation. Compared with the co-culture cell model in the transwell, fluorescein was absorbed more slowly by 5.16-fold (IEB module) and 4.69-fold (BBB module) on the GBA chip. Accumulation of Rhodamine 123 and Hoechst33342 was dramatically decreased. The efflux function of transporters on IEB and BBB was significantly increased on the GBA chip. After lipopolysaccharide (LPS) disrupted the IEB, and then BBB dysfunction was further observed, which confirmed the interaction between IEB and BBB modules. These results demonstrated that this GBA chip may offer a promising tool for gut-brain interaction study.

Keywords: decellularized matrix, gut-brain axis, organ-on-chip, three-dimensional printing.

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4347 Toward Understanding the Glucocorticoid Receptor Network in Cancer

Authors: Swati Srivastava, Mattia Lauriola, Yuval Gilad, Adi Kimchi, Yosef Yarden

Abstract:

The glucocorticoid receptor (GR) has been proposed to play important, but incompletely understood roles in cancer. Glucocorticoids (GCs) are widely used as co-medication of various carcinomas, due to their ability to reduce the toxicity of chemotherapy. Furthermore, GR antagonism has proven to be a strategy to treat triple negative breast cancer and castration-resistant prostate cancer. These observations suggest differential GR involvement in cancer subtypes. The goal of our study has been to elaborate the current understanding of GR signaling in tumor progression and metastasis. Our study involves two cellular models, non-tumorigenic breast epithelial cells (MCF10A) and Ewing sarcoma cells (CHLA9). In our breast cell model, the results indicated that the GR agonist dexamethasone inhibits EGF-induced mammary cell migration, and this effect was blocked when cells were stimulated with a GR antagonist, namely RU486. Microarray analysis for gene expression revealed that the mechanism underlying inhibition involves dexamenthasone-mediated repression of well-known activators of EGFR signaling, alongside with enhancement of several EGFR’s negative feedback loops. Because GR mainly acts primarily through composite response elements (GREs), or via a tethering mechanism, our next aim has been to find the transcription factors (TFs) which can interact with GR in MCF10A cells.The TF-binding motif overrepresented at the promoter of dexamethasone-regulated genes was predicted by using bioinformatics. To validate the prediction, we performed high-throughput Protein Complementation Assays (PCA). For this, we utilized the Gaussia Luciferase PCA strategy, which enabled analysis of protein-protein interactions between GR and predicted TFs of mammary cells. A library comprising both nuclear receptors (estrogen receptor, mineralocorticoid receptor, GR) and TFs was fused to fragments of GLuc, namely GLuc(1)-X, X-GLuc(1), and X-GLuc(2), where GLuc(1) and GLuc(2) correspond to the N-terminal and C-terminal fragments of the luciferase gene.The resulting library was screened, in human embryonic kidney 293T (HEK293T) cells, for all possible interactions between nuclear receptors and TFs. By screening all of the combinations between TFs and nuclear receptors, we identified several positive interactions, which were strengthened in response to dexamethasone and abolished in response to RU486. Furthermore, the interactions between GR and the candidate TFs were validated by co-immunoprecipitation in MCF10A and in CHLA9 cells. Currently, the roles played by the uncovered interactions are being evaluated in various cellular processes, such as cellular proliferation, migration, and invasion. In conclusion, our assay provides an unbiased network analysis between nuclear receptors and other TFs, which can lead to important insights into transcriptional regulation by nuclear receptors in various diseases, in this case of cancer.

Keywords: epidermal growth factor, glucocorticoid receptor, protein complementation assay, transcription factor

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4346 Scattering Operator and Spectral Clustering for Ultrasound Images: Application on Deep Venous Thrombi

Authors: Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier, Léo Fréchier, Barthélémy Hermenault

Abstract:

Deep Venous Thrombosis (DVT) occurs when a thrombus is formed within a deep vein (most often in the legs). This disease can be deadly if a part or the whole thrombus reaches the lung and causes a Pulmonary Embolism (PE). This disorder, often asymptomatic, has multifactorial causes: immobilization, surgery, pregnancy, age, cancers, and genetic variations. Our project aims to relate the thrombus epidemiology (origins, patient predispositions, PE) to its structure using ultrasound images. Ultrasonography and elastography were collected using Toshiba Aplio 500 at Brest Hospital. This manuscript compares two classification approaches: spectral clustering and scattering operator. The former is based on the graph and matrix theories while the latter cascades wavelet convolutions with nonlinear modulus and averaging operators.

Keywords: deep venous thrombosis, ultrasonography, elastography, scattering operator, wavelet, spectral clustering

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4345 A Convolutional Neural Network-Based Model for Lassa fever Virus Prediction Using Patient Blood Smear Image

Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

Abstract:

A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

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