Search results for: multiple cells battery
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8297

Search results for: multiple cells battery

6737 Malaria Parasite Detection Using Deep Learning Methods

Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

Abstract:

Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: convolution neural network, deep learning, malaria, thin blood smears

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6736 Differential Proteomics Expression in Purple Rice Supplemented Type 2 Diabetic Rats’ Skeletal Muscle

Authors: Ei Ei Hlaing, Narissara Lailerd, Sittiruk Roytrakul, Pichapat Piamrojanaphat

Abstract:

Type 2 diabetes is one of the most common metabolic diseases all over the world. The pathogenesis of type 2 diabetes is not the only dysfunction of pancreatic beta cells but also insulin resistance in muscle, liver and adipose tissue. High levels of circulating free fatty acids, an increased lipid content of muscle cells, impaired insulin-mediated glucose uptake and diminished mitochondrial functioning are pathophysiological hallmarks of diabetic skeletal muscles. Purple rice (Oryza sativa L. indica) has been shown to have antidiabetic effects. However, the underlying mechanism(s) of antidiabetic activity of purple rice is still unraveled. In this research, to explore in-depth cellular mechanism(s), proteomic profile of purple rice supplemented type 2 diabetic rats’ skeletal muscle were analyzed contract with non-supplemented rats. Diabetic rats were induced high-fat diet combined with streptozotocin injection. By using one- dimensional gel electrophoresis (1-DE) and LC-MS/MS quantitative proteomic method, we analyzed proteomic profiles in skeletal muscle of normal rats, normal rats with purple rice supplementation, type 2 diabetic rats, and type 2 diabetic rats with purple rice supplementation. Total 2676 polypeptide expressions were identified. Among them, 24 peptides were only expressed in type 2 diabetic rats, and 24 peptides were unique peptides in type 2 diabetic rats with purple rice supplementation. Acetyl CoA carboxylase 1 (ACACA) found as unique protein in type 2 diabetic rats which is the major enzyme in lipid synthesis and metabolism. Interestingly, DNA damage response protein, heterogeneous nuclear ribonucleoprotein K [Mus musculus] (Hnrnpk), was upregulated in type 2 diabetic rats’ skeletal muscle. Meanwhile, unique proteins of type 2 diabetic rats with purple rice supplementation (bone morphogenetic 7 protein preproprotein, BMP7; and forkhead box protein NX4, Foxn4) involved with muscle cells growth through the regulation of TGF-β/Smad signaling network. Moreover, BMP7 may effect on insulin signaling through the downstream signaling of protein kinase B (Akt) which acts in protein synthesis, glucose uptake, and glycogen synthesis. In conclusion, our study supports that type 2 diabetes impairs muscular lipid metabolism. In addition, purple rice might recover the muscle cells growth and insulin signaling.

Keywords: proteomics, purple rice bran, skeletal muscle, type 2 diabetic rats

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6735 Presence, Distribution and Form of Calcium Oxalate Crystals in Relation to Age of Actinidia Deliciosa Leaves and Petioles

Authors: Muccifora S., Rinallo C., Bellani L.

Abstract:

Calcium (Ca²+) is an element essential to the plant being involved in plant growth and development. At high concentrations, it is toxic and can influence every stage, process and cellular activity of plant life. Given its toxicity, cells implement mechanisms to compartmentalize calcium in a vacuole, endoplasmic reticulum, mitochondria, plastids and cell wall. One of the most effective mechanisms to reduce the excess of calcium, thus avoiding cellular damage, is its complexation with oxalic acid to form calcium oxalate crystals that are no longer osmotically or physiologically active. However, the sequestered calcium can be mobilized when the plant needs it. Calcium crystals can be accumulated in the vacuole of specialized sink-cells called idioblasts, with different crystalline forms (druse, raphyde and styloid) of diverse physiological meanings. Actinidia deliciosa cv. Hayward presents raphydes and styloid localized in idioblasts in cells of photosynthetic and non-photosynthetic tissues. The purpose of this work was to understand if there is a relationship between the age of Actinidia leaves and the presence, distribution, dimension and shape of oxalate crystals by means of light, fluorescent, polarized and transmission electron microscopy. Three vines from female plants were chosen at the beginning of the season and used throughout the study. The leaves with petioles were collected at various stages of development from the bottom to the shoot of the plants monthly from April to July. The samples were taken in corresponding areas of the central and lateral parts of the leaves and of the basal portion of the petiole. The results showed that in the leaves, the number of raphyde idioblasts decreased with the progress of the growing season, while the styloid idioblasts increased progressively, becoming very numerous in the upper nodes of July. In June and in July samples, in the vacuoles of the highest nodes, a portion regular in shape strongly stained with rubeanic acid was present. Moreover, the chlortetracycline (CTC) staining for localization of free calcium marked the wall of the idioblasts and the wall of the cells near vascular bundles. In April petiole samples, moving towards the youngest nodes, the raphydes idioblast decreased in number and in the length of the single raphydes. Besides, crystals stained with rubeanic acid appeared in the vacuoles of some cells. In June samples, numerous raphyde idioblasts oriented parallel to vascular bundles were evident. Under the electron microscope, numerous idioblasts presented not homogeneous electrondense aggregates of material, in which a few crystals (styloids) in the form of regular holes were scattered. In July samples, an increase in the number of styloid idioblasts in the youngest nodes and little masses stained with CTC near styloids were observed. Peculiar cells stained with rubeanic acid were detected and hypothesized to be involved in the formation of the idioblasts. In conclusion, in Actinidia leaves and petioles, it seems to confirm the hypothesis that the formation of styloid idioblasts can be correlated to increasing calcium levels in growing tissues.

Keywords: calcium oxalate crystals, actinidia deliciosa, light and electron microscopy, idioblasts

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6734 Performance Evaluation of Distributed and Co-Located MIMO LTE Physical Layer Using Wireless Open-Access Research Platform

Authors: Ishak Suleiman, Ahmad Kamsani Samingan, Yeoh Chun Yeow, Abdul Aziz Bin Abdul Rahman

Abstract:

In this paper, we evaluate the benefits of distributed 4x4 MIMO LTE downlink systems compared to that of the co-located 4x4 MIMO LTE downlink system. The performance evaluation was carried out experimentally by using Wireless Open-Access Research Platform (WARP), where the comparison between the 4x4 MIMO LTE transmission downlink system in distributed and co-located techniques was examined. The measured Error Vector Magnitude (EVM) results showed that the distributed technique achieved better system performance compared to the co-located arrangement.

Keywords: multiple-input-multiple-output (MIMO), distributed MIMO, co-located MIMO, LTE

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6733 Power Management in Wireless Combustible Gas Sensors

Authors: Denis Spirjakin, Alexander Baranov, Saba Akbari, Natalia Kalenova, Vladimir Sleptsov

Abstract:

In this paper we propose the approach to power management in wireless combustible gas sensors. This approach makes possible drastically prolong sensor nodes autonomous lifetime. That is necessary to tie battery replacement to every year technical service procedures which are claimed by safety standards. Using this approach the current consumption of the wireless combustible gas sensor node was decreased from 80 mA to less than 2 mA and the power consumption from more than 220 mW to 4.6 mW. These values provide autonomous lifetime of the node more than one year.

Keywords: Gas sensors, power management, wireless sensor network

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6732 Evaluation of the Effect of Magnetic Field on Fibroblast Attachment in Contact with PHB/Iron Oxide Nanocomposite

Authors: Shokooh Moghadam, Mohammad Taghi Khorasani, Sajjad Seifi Mofarah, M. Daliri

Abstract:

Through the recent two decades, the use of magnetic-property materials with the aim of target cell’s separation and eventually cancer treatment has incredibly increased. Numerous factors can alter the efficacy of this method on curing. In this project, the effect of magnetic field on adhesion of PDL and L929 cells on nanocomposite of iron oxide/PHB with different density of iron oxides (1%, 2.5%, 5%) has been studied. The nanocamposite mentioned includes a polymeric film of poly hydroxyl butyrate and γ-Fe2O3 particles with the average size of 25 nanometer dispersed in it and during this process, poly vinyl alcohol with 98% hydrolyzed and 78000 molecular weight was used as an emulsion to achieve uniform distribution. In order to get the homogenous film, the solution of PHB and iron oxide nanoparticles were put in a dry freezer and in liquid nitrogen, which resulted in a uniform porous scaffold and for removing porosities a 100◦C press was used. After the synthesis of a desirable nanocomposite film, many different tests were performed, First, the particles size and their distribution in the film were evaluated by transmission electron microscopy (TEM) and even FTIR analysis and DMTA test were run in order to observe and accredit the chemical connections and mechanical properties of nanocomposites respectively. By comparing the graphs of case and control samples, it was established that adding nano particles caused an increase in crystallization temperature and the more density of γ-Fe2O3 lead to more Tg (glass temperature). Furthermore, its dispersion range and dumping property of samples were raised up. Moreover, the toxicity, morphologic changes and adhesion of fibroblast and cancer cells were evaluated by a variety of tests. All samples were grown in different density and in contact with cells for 24 and 48 hours within the magnetic fields of 2×10^-3 Tesla. After 48 hours, the samples were photographed with an optic and SEM and no sign of toxicity was traced. The number of cancer cells in the case of sample group was fairly more than the control group. However, there are many gaps and unclear aspects to use magnetic field and their effects in cancer and all diseases treatments yet to be discovered, not to neglect that there have been prominent step on this way in these recent years and we hope this project can be at least a minimum movement in this issue.

Keywords: nanocomposite, cell attachment, magnetic field, cytotoxicity

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6731 Can Demyelinative Lesion Cause To Behaviora Change?

Authors: Arezou Hajhashemi, Karim Asgari, Masoud Etemadifar, Maryam Keyvani, Ali Hekmatnia

Abstract:

Multiple Sclerosis (MS) is one of the most prevalent demyelinating diseases in CNS. As in other chronic cerebral diseases, impairment in cognitive functioning and in memory is popular. Because of the inflammatory and demyelinating nature of the disease, the localization of plaques in different parts of the Prefrontal and Limbic System, may lead to memorial symptoms. This investigation was intended to study relationship between frequency of plaques and memorial symptoms arising from dysfunction limbic system and prefrontal of patients with MS. The sample was selected randomly from patients with MS with memory problem, who have been referred to Isfahan Multiple Sclerosis Society. Brain System Test and Memory Test was administered to the sample, and their MRI's were analyzed by specialist in order to indentify two different parts of plaques. The data was analyzed by SPSS. The results showed that there were significant relationship between MS plaques and prefrontal's dysfunction and memorial symptom related to prefrontal area; however, there were no significant relationship between MS plaques and limbic system's dysfunction and memorial symptoms related to limbic system area. The results of this study suggest that memorial symptoms due to injury regions of the brain have the most significant relationship to prefrontal. Better judgment about these results needs more studies in future.

Keywords: multiple sclerosis, magnetic image, brain injury, behavior disorder

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6730 Mycophenolate Mofetil Increases Mucin Expression in Primary Cultures of Oral Mucosal Epithelial Cells for Application in Limbal Stem Cell Deficiency

Authors: Sandeep Kumar Agrawal, Aditi Bhattacharya, Janvie Manhas, Krushna Bhatt, Yatin Kholakiya, Nupur Khera, Ajoy Roychoudhury, Sudip Sen

Abstract:

Autologous cultured explants of human oral mucosal epithelial cells (OMEC) are a potential therapeutic modality for limbal stem cell deficiency (LSCD). Injury or inflammation of the ocular surface in the form of burns, chemicals, Stevens Johnson syndrome, ocular cicatricial pemphigoid etc. can lead to destruction and deficiency of limbal stem cells. LSCD manifests in the form of severe ocular surface diseases (OSD) characterized by persistent and recurrent epithelial defects, conjuntivalisation and neovascularisation of the corneal surface, scarring and ultimately opacity and blindness. Most of the cases of OSD are associated with severe dry eye pertaining to diminished mucin and aqueous secretion. Mycophenolate mofetil (MMF) has been shown to upregulate the mucin expression in conjunctival goblet cells in vitro. The aim of this study was to evaluate the effects of MMF on mucin expression in primary cultures of oral mucosal epithelial cells. With institutional ethics committee approval and written informed consent, thirty oral mucosal epithelial tissue samples were obtained from patients undergoing oral surgery for non-malignant conditions. OMEC were grown on human amniotic membrane (HAM, obtained from expecting mothers undergoing elective caesarean section) scaffold for 2 weeks in growth media containing DMEM & Ham’s F12 (1:1) with 10% FBS and growth factors. In vitro dosage of MMF was standardised by MTT assay. Analysis of stem cell markers was done using RT-PCR while mucin mRNA expression was quantified using RT-PCR and q-PCR before and after treating cultured OMEC with graded concentrations of MMF for 24 hours. Protein expression was validated using immunocytochemistry. Morphological studies revealed a confluent sheet of proliferating, stratified oral mucosal epithelial cells growing over the surface of HAM scaffold. The presence of progenitor stem cell markers (p63, p75, β1-Integrin and ABCG2) and cell surface associated mucins (MUC1, MUC15 and MUC16) were elucidated by RT-PCR. The mucin mRNA expression was found to be upregulated in MMF treated primary cultures of OMEC, compared to untreated controls as quantified by q-PCR with β-actin as internal reference gene. Increased MUC1 protein expression was validated by immunocytochemistry on representative samples. Our findings conclude that OMEC have the ability to form a multi-layered confluent sheet on the surface of HAM similar to a cornea, which is important for the reconstruction of the damaged ocular surface. Cultured OMEC has stem cell properties as demonstrated by stem cell markers. MMF can be a novel enhancer of mucin production in OMEC. It has the potential to improve dry eye in patients undergoing OMEC transplantation for bilateral OSD. Further clinical trials are required to establish the role of MMF in patients undergoing OMEC transplantation.

Keywords: limbal stem cell deficiency, mycophenolate mofetil, mucin, ocular surface disease

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6729 Role of Long Noncoding RNA HULC on Colorectal Carcinoma Progression through Epigenetically Repressing NKD2 Expression

Authors: Shu-Jun Li, Cheng-Cao Sun, De-Jia Li

Abstract:

Recently, long noncoding RNAs (lncRNAs) have been emerged as crucial regulators of human diseases and prognostic markers in numerous of cancers, including colorectal carcinoma (CRC). Here, we identified an oncogenetic lncRNA HULC, which may promote colorectal tumorigenesis. HULC has been found to be up-regulated and acts as oncogene in gastric cancer and hepatocellular carcinoma, but its expression pattern, biological function and underlying mechanism in CRC is still undetermined. Here, we reported that HULC expression is also over-expressed in CRC, and its increased level is associated with poor prognosis and shorter survival. Knockdown of HULC impaired CRC cells proliferation, migration and invasion, facilitated cell apoptosis in vitro, and inhibited tumorigenicity of CRC cells in vivo. Mechanistically, RNA immunoprecipitation (RIP) and RNA pull-down experiment demonstrated that HULC could simultaneously interact with EZH2 to repress underlying targets NKD2 transcription. In addition, rescue experiments determined that HULC oncogenic function is partly dependent on repressing NKD2. Taken together, our findings expound how HULC over-expression endows an oncogenic function in CRC.

Keywords: long noncoding RNA, HULC, NKD2, colorectal carcinoma, proliferation, apoptosis

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6728 Expression of Fibrogenesis Markers after Mesenchymal Stem Cells Therapy for Experimental Liver Cirrhosis

Authors: Tatsiana Ihnatovich, Darya Nizheharodava, Mikalai Halabarodzka, Tatsiana Savitskaya, Marina Zafranskaya

Abstract:

Liver fibrosis is a complex of histological changes resulting from chronic liver disease accompanied by an excessive production and deposition of extracellular matrix components in the hepatic parenchyma. Liver fibrosis is a serious medical and social problem. Hepatic stellate cells (HSCs) make a significant contribution to the extracellular matrix deposition due to liver injury. Mesenchymal stem cells (MSCs) have a pronounced anti-inflammatory, regenerative and immunomodulatory effect; they are able to differentiate into hepatocytes and induce apoptosis of activated HSCs that opens the prospect of their use for preventing the excessive fibro-formation and the development of liver cirrhosis. The aim of the study is to evaluate the effect of MSCs therapy on the expression of fibrogenesis markers genes in liver tissue and HSCs cultures of rats with experimental liver cirrhosis (ELC). Materials and methods: ELC was induced by the common bile duct ligation (CBDL) in female Wistar rats (n = 19) with an average body weight of 250 (220 ÷ 270) g. Animals from the control group (n = 10) were sham-operated. On the 56th day after the CBDL, the rats of the experimental (n = 12) and the control (n = 5) groups received intraportal MSCs in concentration of 1×106 cells/animal (previously obtained from rat’s bone marrow) or saline, respectively. The animals were taken out of the experiment on the 21st day. HSCs were isolated by sequential liver perfusion in situ with following disaggregation, enzymatic treatment and centrifugation of cell suspension on a two-stage density gradient. The expression of collagen type I (Col1a1) and type III (Col3a1), matrix metalloproteinase type 2 (MMP2) and type 9 (MMP9), tissue inhibitor of matrix metalloproteinases type 1 (TIMP1), transforming growth factor β type 1 (TGFβ1) and type 3 (TGFβ3) was determined by real-time polymerase chain reaction. Statistical analysis was performed using Statistica 10.0. Results: In ELC rats compared to sham-operated animals, a significant increase of all studied markers expression was observed. The administration of MSCs led to a significant decrease of all detectable markers in the experimental group compared to rats without cell therapy. In ELC rats, an increased MMP9/TIMP1 ratio after cell therapy was also detected. The infusion of MSCs in the sham-operated animals did not lead to any changes. In the HSCs from ELC animals, the expression of Col1a1 and Col3a1 exceeded the similar parameters of the control group (p <0.05) and statistically decreased after the MSCs administration. The correlation between Col3a1 (Rs = 0.51, p <0.05), TGFβ1 (Rs = 0.6, p <0.01), and TGFβ3 (Rs = 0.75, p <0.001) expression in HSCs cultures and liver tissue has been found. Conclusion: Intraportal administration of MSCs to rats with ELC leads to a decreased Col1a1 and Col3a1, MMP2 and MMP9, TIMP1, TGFβ1 and TGFβ3 expression. The correlation between the expression of Col3a1, TGFβ1 and TGFβ3 in liver tissue and in HSCs cultures indicates the involvement of activated HSCs in the fibrogenesis that allows considering HSCs to be the main cell therapy target in ELC.

Keywords: cell therapy, experimental liver cirrhosis, hepatic stellate cells, mesenchymal stem cells

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6727 Development of Advanced Linear Calibration Technique for Air Flow Sensing by Using CTA-Based Hot Wire Anemometry

Authors: Ming-Jong Tsai, T. M. Wu, R. C. Chu

Abstract:

The purpose of this study is to develop an Advanced linear calibration Technique for air flow sensing by using CTA-based Hot wire Anemometry. It contains a host PC with Human Machine Interface, a wind tunnel, a wind speed controller, an automatic data acquisition module, and nonlinear calibration model. To improve the fitting error by using single fitting polynomial, this study proposes a Multiple three-order Polynomial Fitting Method (MPFM) for fitting the non-linear output of a CTA-based Hot wire Anemometry. The CTA-based anemometer with built-in fitting parameters is installed in the wind tunnel, and the wind speed is controlled by the PC-based controller. The Hot-Wire anemometer's thermistor resistance change is converted into a voltage signal or temperature differences, and then sent to the PC through a DAQ card. After completion measurements of original signal, the Multiple polynomial mathematical coefficients can be automatically calculated, and then sent into the micro-processor in the Hot-Wire anemometer. Finally, the corrected Hot-Wire anemometer is verified for the linearity, the repeatability, error percentage, and the system outputs quality control reports.

Keywords: flow rate sensing, hot wire, constant temperature anemometry (CTA), linear calibration, multiple three-order polynomial fitting method (MPFM), temperature compensation

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6726 Identification of the Target Genes to Increase the Immunotherapy Response in Bladder Cancer Patients using Computational and Experimental Approach

Authors: Sahar Nasr, Lin Li, Edwin Wang

Abstract:

Bladder cancer (BLCA) is known as the 13th cause of death among cancer patients worldwide, and ~575,000 new BLCA cases are diagnosed each year. Urothelial carcinoma (UC) is the most prevalent subtype among BLCA patients, which can be categorized into muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC). Currently, various therapeutic options are available for UC patients, including (1) transurethral resection followed by intravesical instillation of chemotherapeutics or Bacillus Calmette-Guérin for NMIBC patients, (2) neoadjuvant platinum-based chemotherapy (NAC) plus radical cystectomy is the standard of care for localized MIBC patients, and (3) systematic chemotherapy for metastatic UC. However, conventional treatments may lead to several challenges for treating patients. As an illustration, some patients may suffer from recurrence of the disease after the first line of treatment. Recently, immune checkpoint therapy (ICT) has been introduced as an alternative treatment strategy for the first or second line of treatment in advanced or metastatic BLCA patients. Although ICT showed lucrative results for a fraction of BLCA patients, ~80% of patients were not responsive to it. Therefore, novel treatment methods are required to augment the ICI response rate within BLCA patients. It has been shown that the infiltration of T-cells into the tumor microenvironment (TME) is positively correlated with the response to ICT within cancerous patients. Therefore, the goal of this study is to enhance the infiltration of cytotoxic T-cells into TME through the identification of target genes within the tumor that are responsible for the non-T-cell inflamed TME and their inhibition. BLCA bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) and immune score for TCGA samples were used to determine the Pearson correlation score between the expression of different genes and immune score for each sample. The genes with strong negative correlations were selected (r < -0.2). Thereafter, the correlation between the expression of each gene and survival in BLCA patients was calculated using the TCGA data and Cox regression method. The genes that are common in both selected gene lists were chosen for further analysis. Afterward, BLCA bulk and single-cell RNA-sequencing data were ranked based on the expression of each selected gene and the top and bottom 25% samples were used for pathway enrichment analysis. If the pathways related to the T-cell infiltration (e.g., antigen presentation, interferon, or chemokine pathways) were enriched within the low-expression group, the gene was included for downstream analysis. Finally, the selected genes will be used to calculate the correlation between their expression and the infiltration rate of the activated CD+8 T-cells, natural killer cells and the activated dendric cells. A list of potential target genes has been identified and ranked based on the above-mentioned analysis and criteria. SUN-1 got the highest score within the gene list and other identified genes in the literature as benchmarks. In conclusion, inhibition of SUN1 may increase the tumor-infiltrating lymphocytes and the efficacy of ICI in BLCA patients. BLCA tumor cells with and without SUN-1 CRISPR/Cas9 knockout will be injected into the syngeneic mouse model to validate the predicted SUN-1 effect on increasing tumor-infiltrating lymphocytes.

Keywords: data analysis, gene expression analysis, gene identification, immunoinformatic, functional genomics, transcriptomics

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6725 Assessment of Biofilm Production Capacity of Industrially Important Bacteria under Electroinductive Conditions

Authors: Omolola Ojetayo, Emmanuel Garuba, Obinna Ajunwa, Abiodun A. Onilude

Abstract:

Introduction: Biofilm is a functional community of microorganisms that are associated with a surface or an interface. These adherent cells become embedded within an extracellular matrix composed of polymeric substances, i.e., biofilms refer to biological deposits consisting of both microbes and their extracellular products on biotic and abiotic surfaces. Despite their detrimental effects in medicine, biofilms as natural cell immobilization have found several applications in biotechnology, such as in the treatment of wastewater, bioremediation and biodegradation, desulfurization of gas, and conversion of agro-derived materials into alcohols and organic acids. The means of enhancing immobilized cells have been chemical-inductive, and this affects the medium composition and final product. Physical factors including electrical, magnetic, and electromagnetic flux have shown potential for enhancing biofilms depending on the bacterial species, nature, and intensity of emitted signals, the duration of exposure, and substratum used. However, the concept of cell immobilisation by electrical and magnetic induction is still underexplored. Methods: To assess the effects of physical factors on biofilm formation, six American typed culture collection (Acetobacter aceti ATCC15973, Pseudomonas aeruginosa ATCC9027, Serratia marcescens ATCC14756, Gluconobacter oxydans ATCC19357, Rhodobacter sphaeroides ATCC17023, and Bacillus subtilis ATCC6633) were used. Standard culture techniques for bacterial cells were adopted. Natural autoimmobilisation potentials of test bacteria were carried out by simple biofilms ring formation on tubes, while crystal violet binding assay techniques were adopted in the characterisation of biofilm quantity. Electroinduction of bacterial cells by direct current (DC) application in cell broth, static magnetic field exposure, and electromagnetic flux were carried out, and autoimmobilisation of cells in a biofilm pattern was determined on various substrata tested, including wood, glass, steel, polyvinylchloride (PVC) and polyethylene terephthalate. Biot Savart law was used in quantifying magnetic field intensity, and statistical analyses of data obtained were carried out using the analyses of variance (ANOVA) as well as other statistical tools. Results: Biofilm formation by the selected test bacteria was enhanced by the physical factors applied. Electromagnetic induction had the greatest effect on biofilm formation, with magnetic induction producing the least effect across all substrata used. Microbial cell-cell communication could be a possible means via which physical signals affected the cells in a polarisable manner. Conclusion: The enhancement of biofilm formation by bacteria using physical factors has shown that their inherent capability as a cell immobilization method can be further optimised for industrial applications. A possible relationship between the presence of voltage-dependent channels, mechanosensitive channels, and bacterial biofilms could shed more light on this phenomenon.

Keywords: bacteria, biofilm, cell immobilization, electromagnetic induction, substrata

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6724 A Statistical Approach to Predict and Classify the Commercial Hatchability of Chickens Using Extrinsic Parameters of Breeders and Eggs

Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

Abstract:

Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

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6723 Development of an Automatic Computational Machine Learning Pipeline to Process Confocal Fluorescence Images for Virtual Cell Generation

Authors: Miguel Contreras, David Long, Will Bachman

Abstract:

Background: Microscopy plays a central role in cell and developmental biology. In particular, fluorescence microscopy can be used to visualize specific cellular components and subsequently quantify their morphology through development of virtual-cell models for study of effects of mechanical forces on cells. However, there are challenges with these imaging experiments, which can make it difficult to quantify cell morphology: inconsistent results, time-consuming and potentially costly protocols, and limitation on number of labels due to spectral overlap. To address these challenges, the objective of this project is to develop an automatic computational machine learning pipeline to predict cellular components morphology for virtual-cell generation based on fluorescence cell membrane confocal z-stacks. Methods: Registered confocal z-stacks of nuclei and cell membrane of endothelial cells, consisting of 20 images each, were obtained from fluorescence confocal microscopy and normalized through software pipeline for each image to have a mean pixel intensity value of 0.5. An open source machine learning algorithm, originally developed to predict fluorescence labels on unlabeled transmitted light microscopy cell images, was trained using this set of normalized z-stacks on a single CPU machine. Through transfer learning, the algorithm used knowledge acquired from its previous training sessions to learn the new task. Once trained, the algorithm was used to predict morphology of nuclei using normalized cell membrane fluorescence images as input. Predictions were compared to the ground truth fluorescence nuclei images. Results: After one week of training, using one cell membrane z-stack (20 images) and corresponding nuclei label, results showed qualitatively good predictions on training set. The algorithm was able to accurately predict nuclei locations as well as shape when fed only fluorescence membrane images. Similar training sessions with improved membrane image quality, including clear lining and shape of the membrane, clearly showing the boundaries of each cell, proportionally improved nuclei predictions, reducing errors relative to ground truth. Discussion: These results show the potential of pre-trained machine learning algorithms to predict cell morphology using relatively small amounts of data and training time, eliminating the need of using multiple labels in immunofluorescence experiments. With further training, the algorithm is expected to predict different labels (e.g., focal-adhesion sites, cytoskeleton), which can be added to the automatic machine learning pipeline for direct input into Principal Component Analysis (PCA) for generation of virtual-cell mechanical models.

Keywords: cell morphology prediction, computational machine learning, fluorescence microscopy, virtual-cell models

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6722 Design of a Remote Radiation Sensing Module Based on Portable Gamma Spectrometer

Authors: Young Gil Kim, Hye Min Park, Chan Jong Park, Koan Sik Joo

Abstract:

A personal gamma spectrometer has to be sensitive, pocket-sized, and carriable on the users. To serve these requirements, we developed the SiPM-based portable radiation detectors. The prototype uses a Ce:GAGG scintillator coupled to a silicon photomultiplier and a radio frequency(RF) module to measure gamma-ray, and can be accessed wirelessly or remotely by mobile equipment. The prototype device consumes roughly 4.4W, weighs about 180g (including battery), and measures 5.0 7.0. It is able to achieve 5.8% FWHM energy resolution at 662keV.

Keywords: Ce:GAGG, gamma-ray, radio frequency, silicon photomultiplier

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6721 Feature Evaluation Based on Random Subspace and Multiple-K Ensemble

Authors: Jaehong Yu, Seoung Bum Kim

Abstract:

Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

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6720 Governance Networks of China’s Neighborhood Micro-Redevelopment: The Case of Haikou

Authors: Lin Zhang

Abstract:

Neighborhood redevelopment is vital to improve residents’ living environment, and there has been a national neighborhood micro-redevelopment initiative in China since 2020, which is largely different from the previous large-scale demolition and reconstruction projects. Yet, few studies systematically examine the new interactions of multiple actors in this initiative. China’s neighborhood (micro-) redevelopment is a kind of governance network, and the complexity perspective could reflect the dynamic nature of multiple actors and their relationships in governance networks. In order to better understand the fundamental shifts of governance networks in China’s neighborhood micro-redevelopment, this paper adopted a theoretical framework of complexity in governance networks and analyzed the new governance networks of neighborhood micro-redevelopment projects in Haikou accordingly.

Keywords: neighborhood redevelopment, governance, networks, Haikou

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6719 Characterization of a Dentigerous Cyst Cell Line and Its Secretion of Metalloproteinases

Authors: Muñiz-Lino Marcos A.

Abstract:

The ectomesenchymal tissues involved in tooth development and their remnants are the origin of different odontogenic lesions, including tumors and cysts of the jaws, with a wide range of clinical behaviors. A dentigerous cyst (DC) represents approximately 20% of all cases of odontogenic cysts, and it has been demonstrated that it can develop benign and malignant odontogenic tumors. DC is characterized by bone destruction of the area surrounding the crown of a tooth that has not erupted and contains liquid. The treatment of odontogenic tumors and cysts usually involves a partial or total removal of the jaw, causing important secondary co-morbidities. However, molecules implicated in DC pathogenesis, as well as in its development into odontogenic tumors, remain unknown. A cellular model may be useful to study these molecules, but that model has not been established yet. Here, we reported the establishment of a cell culture derived from a dentigerous cyst. This cell line was named DeCy-1. In spite of its ectomesenchymal morphology, DeCy-1 cells express epithelial markers such as cytokeratins 5, 6, and 8. Furthermore, these cells express the ODAM protein, which is present in odontogenesis and in dental follicles, indicating that DeCy-1 cells are derived from odontogenic epithelium. Analysis by electron microscopy of this cell line showed that it has a high vesicular activity, suggesting that DeCy-1 could secrete molecules that may be involved in DC pathogenesis. Thus, secreted proteins were analyzed by PAGE-SDS where we observed approximately 11 bands. In addition, the capacity of these secretions to degrade proteins was analyzed by gelatin substrate zymography. A degradation band of about 62 kDa was found in these assays. Western blot assays suggested that the matrix metalloproteinase 2 (MMP-2) is responsible for this protease activity. Thus, our results indicate that the establishment of a cell line derived from DC is a useful in vitro model to study the biology of this odontogenic lesion and its participation in the development of odontogenic tumors.

Keywords: dentigerous cyst, ameloblastoma, MMP-2, odontogenic tumors

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6718 Genomics of Adaptation in the Sea

Authors: Agostinho Antunes

Abstract:

The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of selected marine animal species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: marine genomics, evolutionary bioinformatics, human genome sequencing, genomic analyses

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6717 A Robust Stretchable Bio Micro-Electromechanical Systems Technology for High-Strain in vitro Cellular Studies

Authors: Tiffany Baetens, Sophie Halliez, Luc Buée, Emiliano Pallecchi, Vincent Thomy, Steve Arscott

Abstract:

We demonstrate here a viable stretchable bio-microelectromechanical systems (BioMEMS) technology for use with biological studies concerned with the effect of high mechanical strains on living cells. An example of this is traumatic brain injury (TBI) where neurons are damaged with physical force to the brain during, e.g., accidents and sports. Robust, miniaturized integrated systems are needed by biologists to be able to study the effect of TBI on neuron cells in vitro. The major challenges in this area are (i) to develop micro, and nanofabrication processes which are based on stretchable substrates and to (ii) create systems which are robust and performant at very high mechanical strain values—sometimes as high as 100%. At the time of writing, such processes and systems were rapidly evolving subject of research and development. The BioMEMS which we present here is composed of an elastomer substrate (low Young’s modulus ~1 MPa) onto which is patterned robust electrodes and insulators. The patterning of the thin films is achieved using standard photolithography techniques directly on the elastomer substrate—thus making the process generic and applicable to many materials’ in based systems. The chosen elastomer used is commercial ‘Sylgard 184’ polydimethylsiloxane (PDMS). It is spin-coated onto a silicon wafer. Multistep ultra-violet based photolithography involving commercial photoresists are then used to pattern robust thin film metallic electrodes (chromium/gold) and insulating layers (parylene) on the top of the PDMS substrate. The thin film metals are deposited using thermal evaporation and shaped using lift-off techniques The BioMEMS has been characterized mechanically using an in-house strain-applicator tool. The system is composed of 12 electrodes with one reference electrode transversally-orientated to the uniaxial longitudinal straining of the system. The electrical resistance of the electrodes is observed to remain very stable with applied strain—with a resistivity approaching that of evaporated gold—up to an interline strain of ~50%. The mechanical characterization revealed some interesting original properties of such stretchable BioMEMS. For example, a Poisson effect induced electrical ‘self-healing’ of cracking was identified. Biocompatibility of the commercial photoresist has been studied and is conclusive. We will present the results of the BioMEMS, which has also characterized living cells with a commercial Multi Electrode Array (MEA) characterization tool (Multi Channel Systems, USA). The BioMEMS enables the cells to be strained up to 50% and then characterized electrically and optically.

Keywords: BioMEMS, elastomer, electrical impedance measurements of living cells, high mechanical strain, microfabrication, stretchable systems, thin films, traumatic brain injury

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6716 Insect Cell-Based Models: Asutralian Sheep bBlowfly Lucilia Cuprina Embryo Primary Cell line Establishment and Transfection

Authors: Yunjia Yang, Peng Li, Gordon Xu, Timothy Mahony, Bing Zhang, Neena Mitter, Karishma Mody

Abstract:

Sheep flystrike is one of the most economically important diseases affecting the Australian sheep and wool industry (>356M/annually). Currently, control of Lucillia cuprina relies almost exclusively on chemicals controls, and the parasite has developed resistance to nearly all control chemicals used in the past. It is, therefore, critical to develop an alternative solution for the sustainable control and management of flystrike. RNA interference (RNAi) technologies have been successfully explored in multiple animal industries for developing parasites controls. This research project aims to develop a RNAi based biological control for sheep blowfly. Double-stranded RNA (dsRNA) has already proven successful against viruses, fungi, and insects. However, the environmental instability of dsRNA is a major bottleneck for successful RNAi. Bentonite polymer (BenPol) technology can overcome this problem, as it can be tuned for the controlled release of dsRNA in the gut challenging pH environment of the blowfly larvae, prolonging its exposure time to and uptake by target cells. To investigate the potential of BenPol technology for dsRNA delivery, four different BenPol carriers were tested for their dsRNA loading capabilities, and three of them were found to be capable of affording dsRNA stability under multiple temperatures (4°C, 22°C, 40°C, 55°C) in sheep serum. Based on stability results, dsRNA from potential targeted genes was loaded onto BenPol carriers and tested in larvae feeding assays, three genes resulting in knockdowns. Meanwhile, a primary blowfly embryo cell line (BFEC) derived from L. cuprina embryos was successfully established, aim for an effective insect cell model for testing RNAi efficacy for preliminary assessments and screening. The results of this study establish that the dsRNA is stable when loaded on BenPol particles, unlike naked dsRNA rapidly degraded in sheep serum. The stable nanoparticle delivery system offered by BenPol technology can protect and increase the inherent stability of dsRNA molecules at higher temperatures in a complex biological fluid like serum, providing promise for its future use in enhancing animal protection.

Keywords: lucilia cuprina, primary cell line establishment, RNA interference, insect cell transfection

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6715 An Improved Cooperative Communication Scheme for IoT System

Authors: Eui-Hak Lee, Jae-Hyun Ro, Hyoung-Kyu Song

Abstract:

In internet of things (IoT) system, the communication scheme with reliability and low power is required to connect a terminal. Cooperative communication can achieve reliability and lower power than multiple-input multiple-output (MIMO) system. Cooperative communication increases the reliability with low power, but decreases a throughput. It has a weak point that the communication throughput is decreased. In this paper, a novel scheme is proposed to increase the communication throughput. The novel scheme is a transmission structure that increases transmission rate. And a decoding scheme according to the novel transmission structure is proposed. Simulation results show that the proposed scheme increases the throughput without bit error rate (BER) performance degradation.

Keywords: cooperative communication, IoT, STBC, transmission rate

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6714 Brazilian Environmental Public Policies Analysis

Authors: Estela Macedo Alves

Abstract:

This paper is an overview on public policy analysis focused on the study of Brazilian public policy making process. The methodology is based on the review of some theories on the subject, linking them to Brazilian reality. The study presents basic policy analysis concepts, such as policy, polity and politics. It is emphasized John Kingdon's Multiple Stream Model, because of its clarifying aspects concerning public policies formulation process in democratic countries. In this path it was possible to establish interpretations on environmental public policies in Brazil and understand its methods, instead of presenting only a case study. At the end, it is possible to connect theory with Brazilian reality, identifying negative and positive points of its political processes and structure.

Keywords: Brazilian policies, environmental public policy, multiple stream model, public policy analysis

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6713 Diagnosis and Analysis of Automated Liver and Tumor Segmentation on CT

Authors: R. R. Ramsheeja, R. Sreeraj

Abstract:

For view the internal structures of the human body such as liver, brain, kidney etc have a wide range of different modalities for medical images are provided nowadays. Computer Tomography is one of the most significant medical image modalities. In this paper use CT liver images for study the use of automatic computer aided techniques to calculate the volume of the liver tumor. Segmentation method is used for the detection of tumor from the CT scan is proposed. Gaussian filter is used for denoising the liver image and Adaptive Thresholding algorithm is used for segmentation. Multiple Region Of Interest(ROI) based method that may help to characteristic the feature different. It provides a significant impact on classification performance. Due to the characteristic of liver tumor lesion, inherent difficulties appear selective. For a better performance, a novel proposed system is introduced. Multiple ROI based feature selection and classification are performed. In order to obtain of relevant features for Support Vector Machine(SVM) classifier is important for better generalization performance. The proposed system helps to improve the better classification performance, reason in which we can see a significant reduction of features is used. The diagnosis of liver cancer from the computer tomography images is very difficult in nature. Early detection of liver tumor is very helpful to save the human life.

Keywords: computed tomography (CT), multiple region of interest(ROI), feature values, segmentation, SVM classification

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6712 Anti-Neuroinflammatory and Anti-Apoptotic Efficacy of Equol, against Lipopolysaccharide Activated Microglia and Its Neurotoxicity

Authors: Lalita Subedi, Jae Kyoung Chae, Yong Un Park, Cho Kyo Hee, Lee Jae Hyuk, Kang Min Cheol, Sun Yeou Kim

Abstract:

Neuroinflammation may mediate the relationship between low levels of estrogens and neurodegenerative disease. Estrogens are neuroprotective and anti-inflammatory in neurodegenerative disease models. Due to the long term side effects of estrogens, researches have been focused on finding an effective phytoestrogens for biological activities. Daidzein present in soybeans and its active metabolite equol (7-hydroxy-3-(4'-hydroxyphenyl)-chroman) bears strong antioxidant and anticancer showed more potent anti-inflammatory and neuroprotective role in neuroinflammatory model confirmed its in vitro activity with molecular mechanism through NF-κB pathway. Three major CNS cells Microglia (BV-2), Astrocyte (C6), Neuron (N2a) were used to find the effect of equol in inducible nitric oxide synthase (iNOS), cyclooxygenase (COX-2), MAPKs signaling proteins, apoptosis related proteins by western blot analysis. Nitric oxide (NO) and prostaglandin E2 (PGE2) was measured by the Gries method and ELISA, respectively. Cytokines like tumor necrosis factor-α (TNF-α) and IL-6 were also measured in the conditioned medium of LPS activated cells with or without equol. Equol inhibited the NO production, PGE-2 production and expression of COX-2 and iNOS in LPS-stimulated microglial cells at a dose dependent without any cellular toxicity. At the same time Equol also showed promising effect in modulation of MAPK’s and nuclear factor kappa B (NF-κB) expression with significant inhibition of the production of proinflammatory cytokine like interleukin -6 (IL-6), and tumor necrosis factor -α (TNF-α). Additionally, it inhibited the LPS activated microglia-induced neuronal cell death by downregulating the apoptotic phenomenon in neuronal cells. Furthermore, equol increases the production of neurotrophins like NGF and increase the neurite outgrowth as well. In conclusion the natural daidzein metabolite equol are more active than daidzein, which showed a promising effectiveness as an anti-neuroinflammatory and neuroprotective agent via downregulating the LPS stimulated microglial activation and neuronal apoptosis. This work was supported by Brain Korea 21 Plus project and High Value-added Food Technology Development Program 114006-4, Ministry of Agriculture, Food and Rural Affairs.

Keywords: apoptosis, equol, neuroinflammation, phytoestrogen

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6711 Breast Cancer: The Potential of miRNA for Diagnosis and Treatment

Authors: Abbas Pourreza

Abstract:

MicroRNAs (miRNAs) are small single-stranded non-coding RNAs. They are almost 18-25 nucleotides long and very conservative through evolution. They are involved in adjusting the expression of numerous genes due to the existence of a complementary region, generally in the 3' untranslated regions (UTR) of target genes, against particular mRNAs in the cell. Also, miRNAs have been proven to be involved in cell development, differentiation, proliferation, and apoptosis. More than 2000 miRNAs have been recognized in human cells, and these miRNAs adjust approximately one-third of all genes in human cells. Dysregulation of miRNA originated from abnormal DNA methylation patterns of the locus, cause to down-regulated or overexpression of miRNAs, and it may affect tumor formation or development of it. Breast cancer (BC) is the most commonly identified cancer, the most prevalent cancer (23%), and the second-leading (14%) mortality in all types of cancer in females. BC can be classified based on the status (+/−) of the hormone receptors, including estrogen receptor (ER), progesterone receptor (PR), and the Receptor tyrosine-protein kinase erbB-2 (ERBB2 or HER2). Currently, there are four main molecular subtypes of BC: luminal A, approximately 50–60 % of BCs; luminal B, 10–20 %; HER2 positive, 15–20 %, and 10–20 % considered Basal (triple-negative breast cancer (TNBC)) subtype. Aberrant expression of miR-145, miR-21, miR-10b, miR-125a, and miR-206 was detected by Stem-loop real-time RT-PCR in BC cases. Breast tumor formation and development may result from down-regulation of a tumor suppressor miRNA such as miR-145, miR-125a, and miR-206 and/or overexpression of an oncogenic miRNA such as miR-21 and miR-10b. MiR-125a, miR-206, miR-145, miR-21, and miR-10b are hugely predicted to be new tumor markers for the diagnosis and prognosis of BC. MiR-21 and miR-125a could play a part in the treatment of HER-2-positive breast cancer cells, while miR-145 and miR-206 could speed up the evolution of cure techniques for TNBC. To conclude, miRNAs will be presented as hopeful molecules to be used in the primary diagnosis, prognosis, and treatment of BC and battle as opposed to its developed drug resistance.

Keywords: breast cancer, HER2 positive, miRNA, TNBC

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6710 The Impact of Tax Policies on Small Business Growth in Developing Countries: A Case Study of Montserrado Mount County, Republic of Liberia

Authors: Lemuel David

Abstract:

This study aims to investigate The Impact of Tax Policies on Small Business Growth in Developing Countries: A Case Study of Montserrado Mount County, Republic of Liberia. Businesses in Liberia are crucial for job creation and the economic empowerment of its citizens, especially in Grand Cape Mount County where they provide 95% of all jobs and support local capital formation. However, many businesses face challenges that lead to premature closure, including tax-related issues such as multiple taxations and high tax burdens. This research aims to examine the effects of various taxation on business survival in Grand Cape Mount County. The study employed a survey research design with a population of 50 and a sample size of 74. Data was collected using a self-administered questionnaire and analyzed quantitatively with simple percentages, and the research hypotheses were tested with ANOVA. The study findings revealed that multiple taxations hurts business survival, and the relationship between business size and its ability to pay taxes is significant. Therefore, the study recommends that the government of Liberia should create uniform tax policies that support business development in Grand Cape Mount County, and consider the size of businesses when formulating tax policies.

Keywords: multiple taxations, businesses, mortality, growth

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6709 Artificial Reproduction System and Imbalanced Dataset: A Mendelian Classification

Authors: Anita Kushwaha

Abstract:

We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

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6708 Finite Volume Method for Flow Prediction Using Unstructured Meshes

Authors: Juhee Lee, Yongjun Lee

Abstract:

In designing a low-energy-consuming buildings, the heat transfer through a large glass or wall becomes critical. Multiple layers of the window glasses and walls are employed for the high insulation. The gravity driven air flow between window glasses or wall layers is a natural heat convection phenomenon being a key of the heat transfer. For the first step of the natural heat transfer analysis, in this study the development and application of a finite volume method for the numerical computation of viscous incompressible flows is presented. It will become a part of the natural convection analysis with high-order scheme, multi-grid method, and dual-time step in the future. A finite volume method based on a fully-implicit second-order is used to discretize and solve the fluid flow on unstructured grids composed of arbitrary-shaped cells. The integrations of the governing equation are discretised in the finite volume manner using a collocated arrangement of variables. The convergence of the SIMPLE segregated algorithm for the solution of the coupled nonlinear algebraic equations is accelerated by using a sparse matrix solver such as BiCGSTAB. The method used in the present study is verified by applying it to some flows for which either the numerical solution is known or the solution can be obtained using another numerical technique available in the other researches. The accuracy of the method is assessed through the grid refinement.

Keywords: finite volume method, fluid flow, laminar flow, unstructured grid

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