Search results for: cell morphology prediction

Authors: Amin Alvani

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Multiple sclerosis (MS) is a chronic, often disabling disease in which the immune system attacks the myelin sheath of neurons in the central nervous system. The present study aimed to investigate the Relationship between behavioral inhibition/approach system (BIS-BAS) and perceived stress (PS) whit control white blood cell (WBC). 60 MS patients (male=36.7, female=63.3%; age range=15-65 participated in the study and completed the demographic questionnaire, the count blood cell (CBC) test, the behavioral Activation and behavioral inhibition scale (BIS-BAS), and the perceived stress Questionnaire (PSS-14). The results revealed that Between of BAS-reward responsiveness (BAS-DR) subscale and PS, in more than MS patient (BIS), there are increase WBC.

Keywords: behavioral inhibition/approach system, perceived stress, white blood cell, multiple sclerosis

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Authors: Win Nee Phong, Tau Chuan Ling, Pau Loke Show

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From an industrial perspective, the exploitation of microalgae for protein source is of great economical and commercial interest due to numerous attractive characteristics. Nonetheless, the release of protein from microalgae is limited by the multiple layers of the rigid thick cell wall that generally contain a large proportion of cellulose. Thus an efficient cell disruption process is required to rupture the cell wall. The conventional downstream processing methods which typically involve several unit operational steps such as disruption, isolation, extraction, concentration and purification are energy-intensive and costly. To reduce the overall cost and establish a feasible technology for the success of the large-scale production, microalgal industry today demands a more cost-effective and eco-friendly technique in downstream processing. One of the main challenges to extract the proteins from microalgae is the presence of rigid cell wall. This study aims to provide some guidance on the selection of the efficient solvent to facilitate the proteins released during the cell disruption process. The effects of solvent types such as methanol, ethanol, 1-propanol and water in rupturing the microalgae cell wall were studied. It is interesting to know that water is the most effective solvent to recover proteins from microalgae and the cost is cheapest among all other solvents.

Keywords: green, microalgae, protein, solvents

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Authors: Francis Mark A. Fernandez, Chelca Ubay, Armithan Suguitan

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Regions or provinces in a definite state certainly contribute to the economy of their mainland. These regions or provinces are the ones supplying the mainland with different resources and assets. Thus, with a certain region separating from the mainland would indeed impinge the heart of an entire state to develop and expand. With these, the researchers decided to study on the effects of the separation of one’s region to its mainland and the consequences that will take place if the mainland would rule out the region to separate from them. The researchers wrote this paper to present the causes of the separation of Catalonia from Spain and the prediction regarding the pursuance of this region to revolt from its mainland, Spain. In conducting this research, the researchers utilized two analyses, namely: qualitative and quantitative. In qualitative, numerous of information regarding the existing experiences of the citizens of Catalonia were gathered by the authors to give certainty to the prediction of the researchers. Besides this undertaking, the researchers will also gather needed information and figures through books, journals and the published news and reports. In addition, to further support this prediction under qualitative analysis, the researchers intended to operate the Phenomenological research in which the examiners will exemplify the lived experiences of each citizen in Catalonia. Moreover, the researchers will utilize one of the types of Phenomenological research which is hermeneutical phenomenology by Van Manen. In quantitative analysis, the researchers utilized the regression analysis in which it will ascertain the causality in an underlying theory in understanding the relationship of the variables. The researchers assigned and identified different variables, wherein the dependent variable or the y which represents the prediction of the researchers, the independent variable however or the x represents the arising problems that grounds the partition of the region, the summation of the independent variable or the ∑x represents the sum of the problem and finally the summation of the dependent variable or the ∑y is the result of the prediction. With these variables, using the regression analysis, the researchers will be able to show the connections and how a single variable could affect the other variables. From these approaches, the prediction of the researchers will be specified. This research could help different states dealing with this kind of problem. It will further help certain states undergoing this problem by analyzing the causes of these insurgencies and the effects on it if it will obstruct its region to consign their full-pledge autonomy.

Keywords: autonomy, liberty, prediction, separation

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Authors: I. Yalcin Enis, J. Vojtech, T. Gok Sadikoglu

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In this study, polycaprolactone (PCL) was dissolved in chloroform: ethanol solvent system at a concentration of 18 w/v %. 1, 2, 4, and 6 droplets of formic acid were added to the prepared 10ml PCL-chloroform:ethanol solutions separately. Fibrous webs were produced by electrospinning technique. Morphology of the webs was investigated by using scanning electron microscopy (SEM) whereas fiber diameters were measured by Image J Software System. The effect of formic acid addition to the mostly used chloroform solvent on fiber morphology was examined.

Keywords: chloroform, electrospinning, formic acid polycaprolactone, fiber

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Authors: M. Zareh, H. Mohammadi, B. Naser

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Atherosclerotic plaque rupture is the main trigger of heart attack and brain stroke which are the leading cause of death in developed countries. Better understanding of rupture-prone plaque can help clinicians detect vulnerable plaques- rupture prone or instable plaques- and apply immediate medical treatment to prevent these life-threatening cardiovascular events. Therefore, there are plenty of studies addressing disclosure of vulnerable plaques properties. Necrotic core and fibrous tissue are two major tissues constituting atherosclerotic plaque; using histopathological and numerical approaches, many studies have demonstrated that plaque rupture is strongly associated with a large necrotic core and a thin fibrous cap, two morphological characteristic which can be acquired by two-dimensional imaging of atherosclerotic plaque present in coronary and carotid arteries. Plaque rupture is widely considered as a mechanical failure inside plaque tissue; this failure occurs when the stress within plaque excesses the strength of tissue material; hence, finite element method, a strong numerical approach, has been extensively applied to estimate stress distribution within plaques with different compositions which is then used for assessment of various vulnerability characteristics including plaque morphology, material properties and blood pressure. This study aims to evaluate significance of three-dimensional morphology on vulnerability degree of atherosclerotic plaque. To reach this end, different two-dimensional geometrical models of atherosclerotic plaques are considered based on available data and named Main 2D Models (M2M). Then, for each of these M2Ms, two three-dimensional idealistic models are created. These two 3D models represent two possible three-dimensional morphologies which might exist for a plaque with similar 2D morphology to one of M2Ms. Finite element method is employed to estimate stress, von-Mises stress, within each 3D models. Results indicate that for each M2Ms stress can significantly varies due to possible 3D morphological changes in that plaque. Also, our results show that an atherosclerotic plaque with thick cap may experience rupture if it has a critical 3D morphology. This study highlights the effect of 3D geometry of plaque on its instability degree and suggests that 3D morphology of plaque might be necessary to more effectively and accurately assess atherosclerotic plaque vulnerability.

Keywords: atherosclerotic plaque, plaque rupture, finite element method, 3D model

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Authors: Chayma Bahar, Chokri Baccouch, Hedi Sakli, Nizar Sakli

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Harvesting and transport of optical and radiofrequency signals are a topical subject with multiple challenges. In this paper, we present a Optical RECTENNA system. We propose here a hybrid system solar cell antenna for 5G mobile communications networks. Thus, we propose rectifying circuit. A parametric study is done to follow the influence of load resistance and input power on Optical RECTENNA system performance. Thus, we propose a solar cell antenna structure in the frequency band of future 5G standard in 2.45 GHz bands.

Keywords: antenna, IoT, optical rectenna, solar cell

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Authors: Mousa Meratizaman, Sina Monadizadeh, Majid Amidpour

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One of the most favorable thermal desalination methods used widely today is Multi Effect Desalination. High energy consumption in this method causes coupling it with high temperature power cycle like gas turbine. This combination leads to higher energy efficiency. One of the high temperature power systems which have cogeneration opportunities is Solid Oxide Fuel Cell / Gas Turbine. Integration of Multi Effect Desalination with Solid Oxide Fuel Cell /Gas Turbine power cycle in a range of 300-1000 kW is considered in this article. The exhausted heat of Solid Oxide Fuel Cell /Gas Turbine power cycle is used in Heat Recovery Steam Generator to produce needed motive steam for Desalination unit. Thermodynamic simulation and parametric studies of proposed system are carried out to investigate the system performance.

Keywords: solid oxide fuel cell, thermodynamic simulation, multi effect desalination, gas turbine hybrid cycle

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Authors: I. Bochev, A. Shterev, S. Kyurkchiev

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One of the factors associated with poor success rates in human in vitro fertilization (IVF) is the suboptimal culture conditions in which fertilization and early embryonic growth occur. Co-culture systems with helper cell lines appear to enhance the in vitro conditions and allow embryos to demonstrate improved in vitro development. The co-culture of human embryos with monolayers of autologous endometrial stromal cell (EnSCs) results in increased blastocyst development with a larger number of blastomeres, lower incidence of fragmentation and higher pregnancy rates in patients with recurrent implantation failure (RIF). The aim of the study was to examine the influence of autologous endometrial stromal cell (EnSC) co-culture on day 3 embryo quality by comparing the morphological status of the embryos from the same patients undergoing consecutive IVF/Intracytoplasmic sperm injection (ICSI) cycles without and with EnSC co-culture. This retrospective randomized study (2015-2017) includes 20 couples and a total of 46 IVF/ICSI cycles. Each patient couple included had at least two IVF/ICSI procedures – one with and one without autologous EnSC co-culture. Embryo quality was assessed at 68±1 hours in culture, according to Istanbul consensus criteria (2010). Day 3 embryos were classified into three groups: good – grade 1; fair – grade 2; poor – grade 3. Embryos from all cycles were divided into two groups (A – co-cultivated; B – not co-cultivated) and analyzed. Second, for each patient couple, embryos from matched IVF/ICSI cycles (with and without co-culture) were analyzed separately. When an analysis of co-cultivated day 3 embryos from all cycles was performed (n=137; group A), 43.1% of the embryos were graded as “good”, which was not significantly different from the respective embryo quality rate of 42.2% (p = NS) in group B (n=147) with non-co-cultivated embryos. The proportions of fair and poor quality embryos in group A and group B were similar as well – 11.7% vs 10.2% and 45.2% vs 47.6% (p=NS), respectively. Nevertheless, the separate embryo analysis by matched cycles for each couple revealed that in 65% of the cases the proportion of morphologically better embryos was increased in cycles with co-culture in comparison with those without co-culture. A decrease in this proportion after endometrial stromal cell co-cultivation was found in 30% of the cases, whereas no difference was observed in only one couple. The results demonstrated that there is no marked difference in the overall morphological quality between co-cultured and non-co-cultured embryos on day 3. However, in significantly greater percentage of couples the process of autologous EnSC co-culture could increase the proportion of morphologically improved day 3 embryos. By mimicking the in vivo relationship between embryo and maternal environment, co-culture in autologous EnSC system represents a perspective approach to improve the quality of embryos in cases with elevated risk for development of embryos with impaired morphology.

Keywords: autologous endometrial stromal cells, co-culture, day 3 embryo, morphological quality

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Authors: D. Mohammadzadeh S., J. Bolouri Bazaz

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This paper presents a new prediction model for compression index of fine-grained soils using multi-gene genetic programming (MGGP) technique. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. Several laboratory test results for fine-grained were used to develop the models. Various criteria were considered to check the validity of the model. The parametric and sensitivity analyses were performed and discussed. The MGGP method was found to be very effective for predicting the soil compression index. A comparative study was further performed to prove the superiority of the MGGP model to the existing soft computing and traditional empirical equations.

Keywords: new prediction model, compression index soil, multi-gene genetic programming, MGGP

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Authors: Yousif Mohamed Y. Abdallah, Mommen A. Alkhir, Amel S. Algaddal

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This was experimental study conducted to study segmentation of brain in MRI images using edge detection and morphology filters. For brain MRI images each film scanned using digitizer scanner then treated by using image processing program (MatLab), where the segmentation was studied. The scanned image was saved in a TIFF file format to preserve the quality of the image. Brain tissue can be easily detected in MRI image if the object has sufficient contrast from the background. We use edge detection and basic morphology tools to detect a brain. The segmentation of MRI images steps using detection and morphology filters were image reading, detection entire brain, dilation of the image, filling interior gaps inside the image, removal connected objects on borders and smoothen the object (brain). The results of this study were that it showed an alternate method for displaying the segmented object would be to place an outline around the segmented brain. Those filters approaches can help in removal of unwanted background information and increase diagnostic information of Brain MRI.

Keywords: improvement, brain, matlab, markers, boundaries

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Authors: P. Jost, L. Muckova, M. Matula, J. Pejchal, D. Jun, R. Stetina

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Sulfur mustard (bis(2-chlorethyl) sulfide) is highly toxic, chemical warfare agent that has been used in the past in several armed conflicts. Except for the skin, respiratory tract is one of the important routes of exposure. The elucidation and understanding of the mechanism of toxicity of SM have been effort intensive research. The multiple targets character of SM caused cellular damage resulted in activation of many different mechanisms which contribute to cellular response and participate in the final cytopathology effect. In our present work, we compared time-dependent changes in sulfur mustard exposed adult human lung fibroblasts NHLF and lung epithelial alveolar cell line A-549. Cell viability (MTT assay, Calcein-AM assay, and xCELLigence - real-time cell analysis), apoptosis (flow cytometry), mitochondrial membrane potential (Δψm, flow cytometry), reactive oxygen species induction (DC and cell cycle distribution (flow cytometry) were studied. We observed significantly decreased mitochondrial membrane potential and subsequent induction of apoptosis correlating with decreased cellular viability in the sulfur mustard exposed cells. In low concentrations, sulfur mustard-induced S-phase cell cycle arrest, on the other hand, high concentrations, cell cycle phase distribution of sulfur mustard exposed cells resembled cell cycle phase distribution of control group, which implies nonspecific cell cycle inhibition. Epithelial cells A-549 was found as more sensible to sulfur mustard toxicity. Acknowledgements: This work was supported by a long-term organization development plan Medical Aspects of Weapons of Mass Destruction of the Faculty of Military Health Sciences, University of Defence.

Keywords: apoptosis, cell cycle, cytotoxicity, sulfur mustard

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Authors: Partha Sarathi Mondal, Srabani Sanyal

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Different geomorphic agents produce a different landforms pattern. Similarly rivers also have a distinct and diverse landforms pattern. And even, within a river course different and distinct assemblage of landforms i.e. morphological variability are seen. These morphological variability are produced by different river processes. Channel and floodplain morphology helps to interpret river processes. Consequently morphological variability can be used as an important tool for assessing river processes, hydrological connectivity and river health, which will help us to draw inference about river processes and therefore, management of river health. The present study is documented on West Rapti river, a trans-boundary river flowing through Nepal and India, from its source to confluence with Ghaghra river in India. The river shows a significant morphological variability throughout its course. The present study tries to find out factors and processes responsible for the morphological variability of the river and in which way it can be applied in river management practices. For this purpose channel and floodplain morphology of West Rapti river was mapped as accurately as possible and then on the basis of process-form interactions, inferences are drawn to understand factors of morphological variability. The study shows that the valley setting of West Rapti river, in the Himalayan region, is confined and somewhere partly confined whereas, channel of the West Rapti river is single thread in most part of Himalayan region and braided in valley region. In the foothill region valley is unconfined and channel is braided, in middle part channel is meandering and valley is unconfined, whereas, channel is anthropogenically altered in the lower part of the course. Due to this the morphology of West Rapti river is highly diverse. These morphological variability are produced by different geomorphic processes. Therefore, for any river management it is essential to sustain these morphological variability so that the river could not cross the geomorphic threshold and environmental flow of the river along with the biodiversity of riparian region is maintained.

Keywords: channel morphology, environmental flow, floodplain morphology, geomorphic threshold

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Authors: Nilubon Kurubanjerdjit, Nattakarn Iam-On, Ka-Lok Ng

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MicroRNAs are small non-coding RNA found in many different species. They play crucial roles in cancer such as biological processes of apoptosis and proliferation. The identification of microRNA-target genes can be an essential first step towards to reveal the role of microRNA in various cancer types. In this paper, we predict miRNA-target genes for lung cancer by integrating prediction scores from miRanda and PITA algorithms used as a feature vector of miRNA-target interaction. Then, machine-learning algorithms were implemented for making a final prediction. The approach developed in this study should be of value for future studies into understanding the role of miRNAs in molecular mechanisms enabling lung cancer formation.

Keywords: microRNA, miRNAs, lung cancer, machine learning, Naïve Bayes, SVM

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Authors: Dong Wu, Michael Grenn

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Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

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Authors: Shiyin He, Zheng Huang

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In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

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Authors: O. P. Oladipo, O. A. Falode

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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

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Authors: Jaehyung Jung, Kiman Kim, Heesang Eum

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Solar cell is one of the main technologies to reduce greenhouse gas (GHG). Thereby, accurate estimation of greenhouse gas reduction by solar cell technology is crucial to consider strategic applications of the solar cell. The bottom-up approach using operating data such as operation time and efficiency is one of the methodologies to improve the accuracy of the estimation. In this study, alternative GHG reductions from solar cell technology were estimated by a bottom-up approach to indirect emission source (scope 2) in Korea, 2015. In addition, the scenario-based analysis was conducted to assess the effect of technological change with respect to efficiency improvement and rate of operation. In order to estimate GHG reductions from solar cell activities in operating condition levels, methodologies were derived from 2006 IPCC guidelines for national greenhouse gas inventories and guidelines for local government greenhouse inventories published in Korea, 2016. Indirect emission factors for electricity were obtained from Korea Power Exchange (KPX) in 2011. As a result, the annual alternative GHG reductions were estimated as 21,504 tonCO2eq, and the annual average value was 1,536 tonCO2eq per each solar cell technology. Those results of estimation showed to be 91% levels versus design of capacity. Estimation of individual greenhouse gases (GHGs) showed that the largest gas was carbon dioxide (CO2), of which up to 99% of the total individual greenhouse gases. The annual average GHG reductions from solar cell per year and unit installed capacity (MW) were estimated as 556 tonCO2eq/yr•MW. Scenario analysis of efficiency improvement by 5%, 10%, 15% increased as much as approximately 30, 61, 91%, respectively, and rate of operation as 100% increased 4% of the annual GHG reductions.

Keywords: bottom-up approach, greenhouse gas (GHG), reduction, scenario, solar cell

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Authors: Xiaogang Li, Jieqiong Miao

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As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines．For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

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Authors: Anna Vildová, H. Hendrychová, J. Kubeš, L. Tůmová

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The abiotic elicitation is one of the methods for increasing the secondary metabolites production in plant tissue cultures and it seems to be more effective than traditional strategies. This study verified the use of silver nitrate as elicitor to enhance flavonolignans and flavonoid taxifolin production in suspension culture of Sylibum marianum (L.) Gaertn. Silver nitrate in various concentrations (5.887.10-3 mol/L, 5.887.10-4 mol/L, 5.887.10-5 mol/L) was used as elicitor. The content of secondary metabolites in cell suspension cultures was determined by high performance liquid chromatography. The samples were taken after 6, 12, 24, 48, 72 and 168 hours of treatment. The highest content of taxifolin production (2.2 mg.g-1) in cell suspension culture of Silybum marianum (L.) Gaertn. was detected after silver nitrate (5.887.10-4 mol/L) treatment and 72 h application. Flavonolignans such as silybinA, silybin B, silydianin, silychristin, isosilybin A, isosilybin B were not produced by cell suspension culture of S. marianum after elicitor treatment. Our results show that the secondarymetabolites could be released from S. marianum cells into the nutrient medium by changed permeability of cell wall.

Keywords: Silybum marianum (L.) Gaertn., elicitation, silver nitrate, taxifolin

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Authors: Yenni Kurniawati

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Students Prediction Skill in chemistry experiments is an important skill for pre-service chemistry students to stimulate students reflective thinking at each stage of many chemistry experiments, qualitatively and quantitatively. A Virtual Chemistry Laboratory was designed to give students opportunities and times to practicing many kinds of chemistry experiments repeatedly, everywhere and anytime, before they do a real experiment. The Virtual Chemistry Laboratory content was constructed using the Model of Educational Reconstruction and developed to enhance students ability to predicted the experiment results and analyzed the cause of error, calculating the accuracy and precision with carefully in using chemicals. This research showed students changing in making a decision and extremely beware with accuracy, but still had a low concern in precision. It enhancing students level of reflective thinking skill related to their prediction skill 1 until 2 stage in average. Most of them could predict the characteristics of the product in experiment, and even the result will going to be an error. In addition, they take experiments more seriously and curiously about the experiment results. This study recommends for a different subject matter to provide more opportunities for students to learn about other kinds of chemistry experiments design.

Keywords: virtual chemistry laboratory, chemistry experiments, prediction skill, pre-lab experiences

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Authors: Sarah Iaquinta, Christophe Blanquart, Elena Ishow, Sylvain Freour, Frederic Jacquemin, Shahram Khazaie

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Nanoparticles have recently emerged as a possible cancer treatment tool. Several formulations have been used to enhance the uptake of these nanoparticles by cancer cells and avoid their immediate clearance when administrated in vivo. Most of the previous studies focus on the investigation of the influence of the mechanical properties of the cell membrane and the particle. However, these studies do not account for the variation of adhesion and tension during the wrapping of the nanoparticle by the membrane. These couplings should be considered since the cell adapts to the interaction with the nanoparticle by, e.g., increasing the number of interactions (consequently leading to an increase of the cell membrane/nanoparticle adhesion) and by reorganizing its cytoskeleton, leading to the releasing of the tension of the cell membrane. The main contribution of this work is the proposal of a novel model for representing the cellular uptake of rigid circular nanoparticles based on an energetic model tailored to take into account the adaptation of the nanoparticle/cell membrane adhesion and of the membrane stress during wrapping. Several coupling models using sigmoidal functions are considered and compared. The study calculations revealed that the results considering constant parameters underestimated the final wrapping degree of the particle by up to 50%.

Keywords: adhesion, cellular adaptation, cellular uptake, mechanical properties, tension

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Authors: Qiang Xu, Xingxin Wu, Wenjie Guo, Xingqi Wang, Yang Sun, Renxiang Tan

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The phosphatase SHP-2 is known to exert regulatory activities on cytokine receptor signaling and the dysregulation of SHP-2 has been implicated in the pathogenesis of a variety of diseases. Here we report several small molecule regulators of SHP-2 for the treatment of T cell-mediated diseases. The new cyclodepsipeptide trichomides A, isolated from the fermentation products of Trichothecium roseum, increased the phosphorylation of SHP-2 in activated T cells, and ameliorated contact dermatitis in mice. The trichomides A’s effects were significantly reversed by using the SHP-2-specific inhibitor PHPS1 or T cell-conditional SHP-2 knockout mice. Another compound is a cerebroside Fusaruside isolated from the endophytic fungus Fusarium sp. IFB-121. Fusaruside also triggered the tyrosine phosphorylation of SHP-2, which provided a possible mean of selectively targeting STAT1 for the treatment of Th1 cell-mediated inflammation and led to the discovery of the non-phosphatase-like function of SHP-2. Namely, the Fusaruside-activated pY-SHP-2 selectively sequestrated the cytosolic STAT1 to prevent its recruitment to IFN-R, which contributed to the improvement of experimental colitis in mice. Blocking the pY-SHP-2-STAT1 interaction, with SHP-2 inhibitor NSC-87877 or using T cells from conditional SHP-2 knockout mice, reversed the effects of fusaruside. Furthermore, the fusaruside’s effect is independent of the phosphatase activity of SHP-2, demonstrating a novel role for SHP-2 in regulating STAT1 signaling and Th1-type immune responses.

Keywords: SHP-2, small molecules, T cell, T cell-mediated diseases

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Authors: Eric Chabrol, Sidonia B.G. Eckle, Renate de Boer, James McCluskey, Jamie Rossjohn, Mirjam H.M. Heemskerk, Stephanie Gras

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αβ and γδ T-cells are disparate T-cell lineages that, via their use of either αβ or γδ T-cell antigen receptors (TCRs) respectively, can respond to distinct antigens. Here we characterise a new population of human T-cells, term δβ T-cells, that express TCRs comprising a TCR-δ variable gene fused to a Joining-α/Constant-α domain, paired with an array of TCR-β chains. We characterised the cellular, functional, biophysical and structural characteristic feature of this new T-cells population that reveal some new insight into TCR diversity. We provide molecular bases of how δβ T-cells can recognise viral peptide presented by Human Leukocyte Antigen (HLA) molecule. Our findings highlight how components from αβ and γδTCR gene loci can recombine to confer antigen specificity thus expanding our understanding of T-cell biology and TCR diversity.

Keywords: new delta-beta TCR, HLA, viral peptide, structural immunology

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Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

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The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

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Authors: Roshika Tyagi, Shuvomoy Banerjee

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Among various diseases, cancer has become a huge threat to human beings globally. In the context of viral infection, Epstein–Barr virus (EBV) infection is ubiquitous in nature world-wide as well as in India. Recepteur d’Origine Nantais (RON) receptor tyrosine kinase is overexpressed in Lymphoblastoid cell lines (LCLs) but undetectable in primary B-cells. Biologically, RON expression was found to be essential for EBV transformed LCLs proliferation. In our study, we investigated whether EBV latent antigen EBNA3C is playing a crucial role in regulating RON receptor tyrosine kinase function in EBV-induced malignancies. Interestingly, we observed that expression pattern of RON was modulated by EBNA3C in EBV transformed LCLs compared with EBV negative BJAB cell line by PCR and western blot analysis. Moreover, in the absence of EBNA3C, RON expression was found low in western blot and immunofluorescence analysis and cell proliferation rate was significantly reduced in LCLs by cell viability assays. Therefore, our study clearly indicating the potential role of EBNA3C expressed in EBV-infected B-cells for modulating the functions of oncogenic kinases that leads to EBV induced B-cell transformation.

Keywords: apoptosis, cell proliferation, Epstein–barr virus, receptor tyrosine kinase

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Authors: Ediati Budi Cahyono, Triana Hertiani, Nauval Arrazy Asawimanda, Wahyu Puji Pratomo

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Background: Doxorubicin is widely used as a chemotherapeutic drug despite having many side effects. It may cause macrophage dysfunction and decreasing proliferation of lymphocyte. Noni (Morinda citrifolia) fruit which has rich of polysaccharide content has potential as antitumor and immunostimulant effect. The isolation of polysaccharide from Noni fruit has been optimized according to four different methods based on macrophage and lymphocyte activities. We found the highest polysaccharide content from one of the four methods isolation. A method of polysaccharide isolation which has the highest immunostimulant effect was used for further observation as co-chemotherapy. The aim of the study: was to evaluate the isolated polysaccharide from the method of choice as co-chemotherapy of doxorubicin for the growth of Vero, He-La, and T47D cell lines in vitro. The method: in vitro growth assay of Vero, He-La, and T47D cell lines was done using MTT-reduction method, and apoptosis test was done by double staining method to evaluate the induction apoptotic effect of the combination. Every group was treated with doxorubicin and isolated polysaccharide from method of choice with 4 variances of concentrations (25 µg/ml, 50 µg/ml, 100 µg/ml and 200 µg/ml) a long with negative control (doxorubicin only) and normal control (without doxorubicin or polysaccharide administration). Results: The combination of polysaccharide fraction in the concentration of 100μg/ml with 2μmol of doxorubicin against He-La and T47D cell lines influenced the highest cytotoxic effect by suppressing cell viability comparing with doxorubicin only. The combination of polysaccharide fraction in the concentration of 100μg/ml with 2μmol of doxorubicin-induced apoptotic effect the He-La cell line comparing with doxorubicin only. The result of the study: it can be concluded that the combination of polysaccharide fraction and doxorubicin effect more selective toward He-La and T47D cell lines than to Vero cell line. It can be suggested isolated polysaccharide from the method of choice has co-chemotherapy activity against doxorubicin.

Keywords: polysaccharide, noni fruit, doxorubicin, cancer cell lines, vero cell line

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Authors: Amelia J. McFarland, Andrew K. Davey, Shailendra Anoopkumar-Dukie

Abstract:

Microglia are the resident macrophage population of the central nervous system (CNS), contributing to both innate and adaptive immune response, and brain homeostasis. Activation of microglia occurs in response to a multitude of pathogenic stimuli in their microenvironment; this induces morphological and functional changes, resulting in a state of acute neuroinflammation which facilitates injury resolution. Adequate microglial function is essential for the health of the neuroparenchyma, with microglial dysfunction implicated in numerous CNS pathologies. Given the critical role that these macrophage-derived cells play in CNS homeostasis, there is a high demand for microglial models suitable for use in neuroscience research. The isolation of primary human microglia, however, is both difficult and costly, with microglial activation an unwanted but inevitable result of the extraction process. Consequently, there is a need for the development of alternative experimental models which exhibit morphological, biochemical and functional characteristics of human microglia without the difficulties associated with primary cell lines. In this study, our aim was to evaluate whether THP-1 human peripheral blood monocytes would display microglial-like qualities following an induced differentiation, and, therefore, be suitable for use as surrogate microglia. To achieve this aim, THP-1 human peripheral blood monocytes from acute monocytic leukaemia were differentiated with a range of phorbol 12-myristate 13-acetate (PMA) concentrations (50-200 nM) using two different protocols: a 5-day continuous PMA exposure or a 3-day continuous PMA exposure followed by a 5-day rest in normal media. In each protocol and at each PMA concentration, microglial-like cell morphology was assessed through crystal violet staining and the presence of CD-14 microglial / macrophage cell surface marker. Lipopolysaccharide (LPS) from Escherichia coli (055: B5) was then added at a range of concentrations from 0-10 mcg/mL to activate the PMA-differentiated THP-1 cells. Functional microglial-like behavior was evaluated by quantifying the release of prostaglandin (PG)-E2 and pro-inflammatory cytokines interleukin (IL)-1β and tumour necrosis factor (TNF)-α using mediator-specific ELISAs. Furthermore, production of global reactive oxygen species (ROS) and nitric oxide (NO) were determined fluorometrically using dichlorodihydrofluorescein diacetate (DCFH-DA) and diaminofluorescein diacetate (DAF-2-DA) respectively. Following PMA-treatment, it was observed both differentiation protocols resulted in cells displaying distinct microglial morphology from 10 nM PMA. Activation of differentiated cells using LPS significantly augmented IL-1β, TNF-α and PGE2 release at all LPS concentrations under both differentiation protocols. Similarly, a significant increase in DCFH-DA and DAF-2-DA fluorescence was observed, indicative of increases in ROS and NO production. For all endpoints, the 5-day continuous PMA treatment protocol yielded significantly higher mediator levels than the 3-day treatment and 5-day rest protocol. Our data, therefore, suggests that the differentiation of THP-1 human monocyte cells with PMA yields a homogenous microglial-like population which, following stimulation with LPS, undergo activation to release a range of pro-inflammatory mediators associated with microglial activation. Thus, the use of PMA-differentiated THP-1 cells represents a suitable microglial model for in vitro research.

Keywords: differentiation, lipopolysaccharide, microglia, monocyte, neuroscience, THP-1

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Authors: Jia-Shiun Chen, Quoc-Viet Huynh

Abstract:

This work develops a flexible-body dynamic model of an all-terrain vehicle (ATV), capable of recovering dynamic stresses while the ATV travels on random bumpy roads. The fatigue life of components is forecasted as well. While considering the interaction between dynamic forces and structure deformation, the proposed model achieves a highly accurate structure stress prediction and fatigue life prediction. During the simulation, stress time history of the ATV structure is retrieved for life prediction. Finally, the hot sports of the ATV frame are located, and the frame life for combined road conditions is forecasted, i.e. 25833.6 hr. If the usage of vehicle is eight hours daily, the total vehicle frame life is 8.847 years. Moreover, the reaction force and deformation due to the dynamic motion can be described more accurately by using flexible body dynamics than by using rigid-body dynamics. Based on recommendations made in the product design stage before mass production, the proposed model can significantly lower development and testing costs.

Keywords: flexible-body dynamics, veicle, dynamics, fatigue, durability

Procedia PDF Downloads 394

Authors: A. O. Boyo, A. T. Akinwunmi

Abstract:

The effect of extracting solvent and adjustment of pHs on the stability of Terminalia catappa L. dye-sensitized solar cell was investigated. We introduced ZnO as an alternative to TiO2 in the dye sensitized solar cells (DSSCs) due to its band gap similar to TiO2, higher electron mobility, and flexible procedures of preparations. Dye-sensitized solar cells (DSSCs) based on Terminalia catappa L. was extracted in water (A), ethanol (B) and the mixture of ethanol and water in the ratio 1:1by volume (C). The best performance Solar cells sensitized was from extracts A and achieved up to Jsc 1.51 mAcm−2, Voc 0.75V, FF 0.88 and η 0.63%. We notice that as pHs decreases there is the increase in DSSC efficiency. There is Long period stability in efficiency of the cells prepared using A than in C and a fair stability in efficiency of B cell. The results obtained with extracts B and C confirmed that Ethanol with water could not be considered as a suitable solvent for the extraction of natural dye.

Keywords: zinc oxide, dye-sensitized solar cell, terminalia catappa L., TiO2

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Authors: M. S. Kilic, S. Korkut, B. Hazer

Abstract:

Newly synthesized Polypropylene-g-Polyethylene glycol polymer was first time used for a compartment-less enzymatic fuel cell. Working electrodes based on Polypropylene-g-Polyethylene glycol were operated as unmediated and mediated system (with ferrocene and gold/cobalt oxide nanoparticles). Glucose oxidase and bilirubin oxidase was selected as anodic and cathodic enzyme, respectively. Glucose was used as fuel in a single-compartment and membrane-less cell. Maximum power density was obtained as 0.65 nW cm-2, 65 nW cm-2, and 23500 nW cm-2 from the unmediated, ferrocene and gold/cobalt oxide modified polymeric film, respectively. Power density was calculated to be ~16000 nW cm-2 for undiluted wastewater sample with gold/cobalt oxide nanoparticles including system.

Keywords: bilirubin oxidase, enzymatic fuel cell, glucose oxidase, nanoparticles

Procedia PDF Downloads 263