Search results for: neural progentor cells

Authors: Aastha Agarwal, Veena Sharma

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N-nitrosopyrollidine or NPYR is a tobacco-specific nitrosamine which upon intoxicated causes abnormal production of Reactive Oxygen Species disrupt the endogenous antioxidant system. The study was designed to evaluate the histological changes in lung tissue of Mus musculus in NPYR administered lungs and effect of isolated flavonoid 3,6-dihydroxy-(3’,4’,7’-trimethoxyphenyl)-chromen-4-one-7-glucoside (ITC) from experimental plant Indigofera tinctorial. Post treatment with isolated compound significantly restored the abnormal symptoms and changes in pulmonary tissue. Transverse section of mouse lung in control animals appeared as a thin lace. Histologically, most of the lung was arranged as alveoli which were thin walled structures made up of single layered squamous epithelial cells. In the transverse section of lung at 100 X will clearly show the component of alveoli, surround by a thin layer of connective tissue and blood vessels. Smaller bronchioles were lined by cuboidal epithelial cells while larger bronchioles were lined by ciliated columnar epithelium layer while in NPYR intoxicated lungs signs of vast pulmonary damages and carcinogenesis as alveolar damage, necrosis, DADs or defused alveolar damages hyperplasia, metaplasia, dysplasia and next stage of carcinogenesis were revealed. Treatment with ITC showed the significant positive changes in the lung tissue due to the side hydroxyl and methoxy groups in its structure which help in combating oxidative injuries and give protection from the free radicals generated during the metabolism of NPYR in body. Thus, histopathological analysis confirms the development of the cancerous conditions in the lung tissue in mice model and the protective effects of ITC.

Keywords: flavonoid, histopathology, Indigofera tinctoria, lung

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Authors: András Fülöp, Lejla Heilmann, Zsolt Szabó, Ákos Koós

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Microbial fuel cells (MFCs) present a sustainable biotechnological solution to future energy demands. The aim of this study was to construct soil based, single cell, membrane-less MFC systems, operated without treatment to continuously power on-site monitoring and control systems during the soil bioremediation processes. Our Pseudomonas aeruginosa 541 isolate is an ideal choice for MFCs, because it is able to produce pyocyanin which behaves as electron-shuttle molecule, furthermore, it also has a significant antimicrobial effect. We tested several materials and structural configurations to obtain long term high power output. Comparing different configurations, a proton exchange membrane-less, 0.6 m long with 0.05 m diameter MFC tubes offered the best long-term performances. The long-term electricity production were tested from starch, yeast extract (YE), carboxymethyl cellulose (CMC) with humic acid (HA) as a mediator. In all cases, 3 kΩ external load have been used. The two best-operated systems were the Pseudomonas aeruginosa 541 containing MFCs with 1 % carboxymethyl cellulose and the MFCs with 1% yeast extract in the anode area and 35% hydrogel in the cathode chamber. The first had 3.3 ± 0.033 mW/m2 and the second had 4.1 ± 0.065 mW/m2 power density values. These systems have operated for 230 days without any treatment. The addition of 0.2 % HA and 1 % YE referred to the volume of the anode area resulted in 1.4 ± 0.035 mW/m2 power densities. The mixture of 1% starch with 0.2 % HA gave 1.82 ± 0.031 mW/m2. Using CMC as retard carbon source takes effect in the long-term bacterial survivor, thus enable the expression of the long term power output. The application of hydrogels in the cathode chamber significantly increased the performance of the MFC units due to their good water retention capacity.

Keywords: microbial fuel cell, bioremediation, Pseudomonas aeruginosa, biotechnological solution

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: Katarzyna Bialik-Wąs, Klaudia Pluta, Dagmara Malina, Małgorzata Miastkowska

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In recent years, biocompatible hydrogels have been used more and more in medical applications, especially as modern dressings and drug delivery systems. The main goal of this research was the characteristics of bio-hybrid hydrogel materials incorporated with the nanocarrier-drug system, which enable the release in a gradual and prolonged manner, up to 7 days. Therefore, the use of such a combination will provide protection against mechanical damage and adequate hydration. The proposed bio-hybrid hydrogels are characterized by: transparency, biocompatibility, good mechanical strength, and the dual release system, which allows for gradual delivery of the active substance, even up to 7 days. Bio-hybrid hydrogels based on sodium alginate (SA), poly(vinyl alcohol) (PVA), glycerine, and Aloe vera solution (AV) were obtained through the chemical crosslinking method using poly(ethylene glycol) diacrylate as a crosslinking agent. Additionally, a nanocarrier-drug system was incorporated into SA/PVA/AV hydrogel matrix. Here, studies were focused on the release profiles of active substances from bio-hybrid hydrogels using the USP4 method (DZF II Flow-Through System, Erweka GmbH, Langen, Germany). The equipment incorporated seven in-line flow-through diffusion cells. The membrane was placed over support with an orifice of 1,5 cm in diameter (diffusional area, 1.766 cm²). All the cells were placed in a cell warmer connected with the Erweka heater DH 2000i and the Erweka piston pump HKP 720. The piston pump transports the receptor fluid via seven channels to the flow-through cells and automatically adapts the setting of the flow rate. All volumes were measured by gravimetric methods by filling the chambers with Milli-Q water and assuming a density of 1 g/ml. All the determinations were made in triplicate for each cell. The release study of the model active substance was carried out using a regenerated cellulose membrane Spectra/Por®Dialysis Membrane MWCO 6-8,000 Carl Roth® Company. These tests were conducted in buffer solutions – PBS at pH 7.4. A flow rate of receptor fluid of about 4 ml /1 min was selected. The experiments were carried out for 7 days at a temperature of 37°C. The released concentration of the model drug in the receptor solution was analyzed using UV-Vis spectroscopy (Perkin Elmer Company). Additionally, the following properties of the modified materials were studied: physicochemical, structural (FT-IR analysis), morphological (SEM analysis). Finally, the cytotoxicity tests using in vitro method were conducted. The obtained results exhibited that the dual release system allows for the gradual and prolonged delivery of the active substances, even up to 7 days.

Keywords: wound dressings, SA/PVA hydrogels, nanocarrier-drug system, USP4 method

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Authors: Ankit Shah, R. K. Shrivastava

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Flood and drought are two main features of hydrology which affect the human life. Floods are natural disasters which cause millions of rupees’ worth of damage each year in India and the whole world. Flood causes destruction in form of life and property. An accurate estimate of the flood damage potential is a key element to an effective, nationwide flood damage abatement program. Also, the increase in demand of water due to increase in population, industrial and agricultural growth, has let us know that though being a renewable resource it cannot be taken for granted. We have to optimize the use of water according to circumstances and conditions and need to harness it which can be done by construction of hydraulic structures. For their safe and proper functioning of hydraulic structures, we need to predict the flood magnitude and its impact. Hydraulic structures play a key role in harnessing and optimization of flood water which in turn results in safe and maximum use of water available. Mainly hydraulic structures are constructed on ungauged sites. There are two methods by which we can estimate flood viz. generation of Unit Hydrographs and Flood Frequency Analysis. In this study, Regional Flood Frequency Analysis has been employed. There are many methods for estimating the ‘Regional Flood Frequency Analysis’ viz. Index Flood Method. National Environmental and Research Council (NERC Methods), Multiple Regression Method, etc. However, none of the methods can be considered universal for every situation and location. The Narmada basin is located in Central India. It is drained by most of the tributaries, most of which are ungauged. Therefore it is very difficult to estimate flood on these tributaries and in the main river. As mentioned above Artificial Neural Network (ANN)s and Multiple Regression Method is used for determination of Regional flood Frequency. The annual peak flood data of 20 sites gauging sites of Narmada Basin is used in the present study to determine the Regional Flood relationships. Homogeneity of the considered sites is determined by using the Index Flood Method. Flood relationships obtained by both the methods are compared with each other, and it is found that ANN is more reliable than Multiple Regression Method for the present study area.

Keywords: artificial neural network, index flood method, multi layer perceptrons, multiple regression, Narmada basin, regional flood frequency

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Authors: Alejandra Betancur Sánchez, Carmen Elena Zapata Sánchez, Juan Bautista López Ortiz

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Adverse effects and increased air pollution has raised concerns about regulatory policies and has fostered the development of new air quality standards; this is due to the complexity of the composition and the poorly understood reactions in the atmospheric environment. Toxic compounds act as environmental agents having various effects, from irritation to death of cells and tissues. A toxic agent is defined an adverse response in a biological system. There is a particular class that produces some kind of alteration in the genetic material or associated components, so they are recognized as genotoxic agents. Within cells, they interact directly or indirectly with DNA, causing mutations or interfere with some enzymatic repair processes or in the genesis or polymerization of proteinaceous material involved in chromosome segregation. An air pollutant may cause or contribute to increased mortality or serious illness and even pose a potential danger to human health. The aim of this study was to evaluate the effect on the viability and the genotoxic potential on the cell lines CHO-K1 and Jurkat and peripheral blood of particulate matter PM T lymphocytes 2.5 obtained from filters collected three monitoring stations network air quality Aburrá Valley. Tests, reduction of MTT, trypan blue, NRU, comet assay, sister chromatid exchange (SCE) and chromosomal aberrations allowed evidence reduction in cell viability in cell lines CHO-K1 and Jurkat and damage to the DNA from cell line CHOK1, however, no significant effects were observed in the number of SCEs and chromosomal aberrations. The results suggest that PM2.5 material has genotoxic potential and can induce cancer development, as has been suggested in other studies.

Keywords: PM2.5, cell line Jurkat, cell line CHO-K1, cytotoxicity, genotoxicity

Procedia PDF Downloads 264

Authors: Naveen Kumar B. T., Anuj Tyagi, Niraj Kumar Singh, Visanu Boonyawiwat, Shanthanagouda A. H., Orawan Boodde, Shankar K. M., Prakash Patil, Shubhkaramjeet Kaur

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Since 2009, Acute Hepatopancreatic Necrosis Disease (AHPND) outbreaks have increased rapidly, and these have led to the major economic losses to the global shrimp industry. In comparison to other treatments, passive immunity and monoclonal antibody (MAb) based farmer level kit have proved their importance in controlling and treating the diseases in the shrimp industry. In the present study, MAbs were produced against the recombinant PirB protein Vibrio parahaemolyticus strain causing AHPND. Briefly, Balb/C mice were immunized with rPirB at 15 days interval, and antibody titer was determined by ELISA. Spleen cells from mice showing high antibody titer were fused with SP2O myeloma cells for hybridoma production. Among 130 hybridomas, four showed high antibody titer and positive reactivity in an immunoblot assay. In Western blot assay, three out of four MAbs (4C4, 2C2 and 4G3) showed reactivity to rPirB protein. However, in the natural host, only Mab clone 4G3 show strong reactivity (with a strain of V. parahemolyticus causing EMS/AHPND). These clones also showed reactivity with less than 20 kDa proteins in AHPND free V. parahaemolyticus (Thailand stain). Further, on from MAb 4G3 clone, four panels of single cell MAbs clones (G3F5, G3B8, G3H2, and G3D6) were produced of which three showed strong positive reactivity to rPirB protein in the Western blot. These MAbs have potential for controlling and prevention of the AHPND through passive immunity and development of filed level rapid diagnostic kits.

Keywords: shrimp, economic loss, AHPND, MAb

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Authors: Joanna Gerszon, Aleksandra Rodacka

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In the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, protein and peptide aggregation processes play a vital role in contributing to the formation of intracellular and extracellular protein deposits. One of the major components of these deposits is the oxidatively modified glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Therefore, the purpose of this research was to answer the question whether piceatannol, a stilbene derivative, counteracts and/or slows down oxidative stress-induced GAPDH aggregation. The study also aimed to determine if this natural occurring compound prevents unfavorable nuclear translocation of GAPDH in hippocampal cells. The isothermal titration calorimetry (ITC) analysis indicated that one molecule of GAPDH can bind up to 8 molecules of piceatannol (7.3 ± 0.9). As a consequence of piceatannol binding to the enzyme, the loss of activity was observed. Parallel with GAPDH inactivation the changes in zeta potential, and loss of free thiol groups were noted. Nevertheless, the ligand-protein binding does not influence the secondary structure of the GAPDH. Precise molecular docking analysis of the interactions inside the active center allowed to presume that these effects are due to piceatannol ability to assemble a covalent binding with nucleophilic cysteine residue (Cys149) which is directly involved in the catalytic reaction. Molecular docking also showed that simultaneously 11 molecules of ligand can be bound to dehydrogenase. Taking into consideration obtained data, the influence of piceatannol on level of GAPDH aggregation induced by excessive oxidative stress was examined. The applied methods (thioflavin-T binding-dependent fluorescence as well as microscopy methods - transmission electron microscopy, Congo Red staining) revealed that piceatannol significantly diminishes level of GAPDH aggregation. Finally, studies involving cellular model (Western blot analyses of nuclear and cytosolic fractions and confocal microscopy) indicated that piceatannol-GAPDH binding prevents GAPDH from nuclear translocation induced by excessive oxidative stress in hippocampal cells. In consequence, it counteracts cell apoptosis. These studies demonstrate that by binding with GAPDH, piceatannol blocks cysteine residue and counteracts its oxidative modifications, that induce oligomerization and GAPDH aggregation as well as it prevents hippocampal cells from apoptosis by retaining GAPDH in the cytoplasm. All these findings provide a new insight into the role of piceatannol interaction with GAPDH and present a potential therapeutic strategy for some neurological disorders related to GAPDH aggregation. This work was supported by the by National Science Centre, Poland (grant number 2017/25/N/NZ1/02849).

Keywords: glyceraldehyde-3-phosphate dehydrogenase, neurodegenerative disease, neuroprotection, piceatannol, protein aggregation

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Authors: Abdulmalek Ahmed

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Formation pressure is the main function that affects drilling operation economically and efficiently. Knowing the pore pressure and the parameters that affect it will help to reduce the cost of drilling process. Many empirical models reported in the literature were used to calculate the formation pressure based on different parameters. Some of these models used only drilling parameters to estimate pore pressure. Other models predicted the formation pressure based on log data. All of these models required different trends such as normal or abnormal to predict the pore pressure. Few researchers applied artificial intelligence (AI) techniques to predict the formation pressure by only one method or a maximum of two methods of AI. The objective of this research is to predict the pore pressure based on both drilling parameters and log data namely; weight on bit, rotary speed, rate of penetration, mud weight, bulk density, porosity and delta sonic time. A real field data is used to predict the formation pressure using five different artificial intelligence (AI) methods such as; artificial neural networks (ANN), radial basis function (RBF), fuzzy logic (FL), support vector machine (SVM) and functional networks (FN). All AI tools were compared with different empirical models. AI methods estimated the formation pressure by a high accuracy (high correlation coefficient and low average absolute percentage error) and outperformed all previous. The advantage of the new technique is its simplicity, which represented from its estimation of pore pressure without the need of different trends as compared to other models which require a two different trend (normal or abnormal pressure). Moreover, by comparing the AI tools with each other, the results indicate that SVM has the advantage of pore pressure prediction by its fast processing speed and high performance (a high correlation coefficient of 0.997 and a low average absolute percentage error of 0.14%). In the end, a new empirical correlation for formation pressure was developed using ANN method that can estimate pore pressure with a high precision (correlation coefficient of 0.998 and average absolute percentage error of 0.17%).

Keywords: Artificial Intelligence (AI), Formation pressure, Artificial Neural Networks (ANN), Fuzzy Logic (FL), Support Vector Machine (SVM), Functional Networks (FN), Radial Basis Function (RBF)

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Authors: Florian Billing, Soren Segan, Meike Jakobi, Elsa Arefaine, Aliki Jerch, Xin Xiong, Matthias Becker, Thomas Joos, Burkhard Schlosshauer, Ulrich Rothbauer, Nicole Schneiderhan-Marra, Hanna Hartmann, Christopher Shipp

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The immune response plays a major role in implant biocompatibility, but an understanding of how to design biomaterials for specific immune responses is yet to be achieved. We aimed to better understand how changing certain material properties can drive immune responses. To this end, we tested immune response to experimental implant coatings that vary in specific characteristics. A layer-by-layer approach was employed to vary surface charge and wettability. Human-based in vitro models (THP-1 macrophages and primary peripheral blood mononuclear cells (PBMCS)) were used to assess immune responses using multiplex cytokine analysis, flow cytometry (CD molecule expression) and microscopy (cell morphology). We observed dramatic differences in immune response due to specific alterations in coating properties. For example altering the surface charge of coating A from anionic to cationic resulted in the substantial elevation of the pro-inflammatory molecules IL-1beta, IL-6, TNF-alpha and MIP-1beta, while the pro-wound healing factor VEGF was significantly down-regulated. We also observed changes in cell surface marker expression in relation to altered coating properties, such as CD16 on NK Cells and HLA-DR on monocytes. We furthermore observed changes in the morphology of THP-1 macrophages following cultivation on different coatings. A correlation between these morphological changes and the cytokine expression profile is ongoing. Targeted changes in biomaterial properties can produce vast differences in immune response. The properties of the coatings examined here may, therefore, be a method to direct specific biological responses in order to improve implant biocompatibility.

Keywords: biomaterials, coatings, immune system, implants

Procedia PDF Downloads 189

Authors: S. AliReza Mirghasemi, Zameer Hussain, Mohammad Saleh Sadeghi, Narges Rahimi Gabaran, Mohamadreza Baghaban Eslaminejad

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Background: Despite promising results have shown by osteogenic cell-based demineralized bone matrix composites, they need to be optimized for grafts that act as structural frameworks in load-bearing defects. The purpose of this experiment is to determine the effect of bone-marrow-mesenchymal-stem-cells seeding on partially demineralized laser-perforated structural allografts that have been implanted in critical femoral defects. Materials and Methods: P3 stem cells were used for graft seeding. Laser perforation in four rows of three holes was achieved. Cell-seeded grafts were incubated for one hour until they were planted into the defect. We used four types of grafts: partially demineralized only (Donly), partially demineralized stem cell seeded (DST), partially demineralized laser-perforated (DLP), and partially demineralized laser-perforated stem cell seeded (DLPST). histologic and histomorphometric analysis were performed at 12 weeks. Results: Partially demineralized laser-perforated had the highest woven bone formation within graft limits, stem cell seeded demineralized laser-perforated remained intact, and the difference between partially demineralized only and partially demineralized stem cell seeded was insignificant. At interface, partially demineralized laser-perforated and partially demineralized only had comparable osteogenesis, but partially demineralized stem cell seeded was inferior. The interface in stem cell seeded demineralized laser-perforated was almost replaced by distinct endochondral osteogenesis with higher angiogenesis in the vicinity. Partially demineralized stem cell seeded and stem cell seeded demineralized laser-perforated graft surfaces had extra vessel-ingrowth-like porosities, a sign of delayed resorption. Conclusion: This demonstrates that simple cell-based composites are not optimal and necessitates the supplementation of synergistic stipulations and surface changes.

Keywords: structural bone allograft, partial demineralization, laser perforation, mesenchymal stem cell

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Authors: Sina Mahdavi, Mahdi Asghari Ozma

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Multiple sclerosis (MS) is the most common inflammatory autoimmune disease of the CNS that affects the myelination process in the central nervous system (CNS). Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially human Varicella-zoster virus (VZV) and MS is one potential cause that is not well understood. This study aims to summarize the available data on VZV retrovirus infection in MS disease progression. For this study, the keywords "Multiple sclerosis", " Human Varicella-zoster virus ", and "central nervous system" in the databases PubMed, Google Scholar, Sid, and MagIran between 2016 and 2022 were searched and 14 articles were chosen, studied, and analyzed. Analysis of the amino acid sequences of HNRNPA1 with VZV proteins has shown a 62% amino acid sequence similarity between VZV gE and the PrLD/M9 epitope region (TNPO1 binding domain) of mutant HNRNPA1. A heterogeneous nuclear ribonucleoprotein (hnRNP), which is produced by HNRNPA1, is involved in the processing and transfer of mRNA and pre-mRNA. Mutant HNRNPA1 mimics gE of VZV as an antigen that leads to autoantibody production. Mutant HnRNPA1 translocates to the cytoplasm, after aggregation is presented by MHC class I, followed by CD8 + cells. Of these, antibodies and immune cells against the gE epitopes of VZV remain due to the memory immune response, causing neurodegeneration and the development of MS in genetically predisposed individuals. VZV expression during the course of MS is present in genetically predisposed individuals with HNRNPA1 mutation, suggesting a link between VZV and MS, and that this virus may play a role in the development of MS by inducing an inflammatory state. Therefore, measures to modulate VZV expression may be effective in reducing inflammatory processes in demyelinated areas of MS patients in genetically predisposed individuals.

Keywords: multiple sclerosis, varicella-zoster virus, central nervous system, autoimmunity

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Authors: Skyler Kim

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An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

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Authors: S. Altmeyer, B. Hof, F. Marques, J. M. Lopez

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We present numerical simulations concerning the reversal of spiraling vortices in short highly counter-rotating cylinders. Increasing the differential cylinder rotation results in global flow-inversion is which develops various different and complex flow dynamics of several quasi-periodic solutions that differ in their number of vortex cells in the bulk. The dynamics change from being dominated of the inner cylinder boundary layer with ’passive’ only responding outer one to be dominated by the outer cylinder boundary layer with only responding inner one. Solutions exist on either two or three tori invariant manifolds whereby they appear as symmetric or asymmetric states. We find for either moderate and high inner cylinder rotation speed the quasiperiodic flow to consist of only two vortex cells but differ as the vortices has opposite spiraling direction. These both flows live on 2-tori but differ in number of symmetries. While for the quasi-periodic flow (q^a_2) at lower rotation speed a pair of symmetrically related 2-tori T2 exists the quasi-periodic flow (q^s_2) at higher rotation speeds is symmetric living on a single 2-torus T2. In addition these both flows differ due to their dominant azimuthal m modes. The first is dominated by m=1 whereas for the latter m=3 contribution is largest. The 2-tori states are separated by a further quasi-periodic flow (q^a_3) living on pair of symmetrically related 3-tori T3. This flow offers a ’periodical’ competition between a two and three vortex cell states in the bulk. This flow is also an m=1 solution as for the quasiperiodic flows living on the pair of symmetrically-related 2-tori states. Moreover we find hysteresis resulting in coexisting regions of different quasiperiodic flows q^s_2 and q^a_3 with increasing and decreasing the differential rotation.

Keywords: transition, bifurcation, torus, symmetries

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Authors: Seyedeh Mozhgan Seyed Talebi, Chih -Hao Lee

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With an abrupt rise in the power conservation efficiency (PCE) of perovskite solar cells (PSCs) within a short span of time, the toxicity of lead was raised as a major hurdle in the path toward their commercialization. In the present research, a systematic investigation of the electrical and optical characteristics of the all-inorganic CsSnI₃ perovskite absorber layer was performed with the Vienna Ab Initio Simulation Package (VASP) using the projector-augmented wave method. The presence of inorganic halide perovskite offers the advantages of enhancing the degradation resistance of the device, reducing the cost of cells, and minimizing the recombination of generated carriers. The simulated standard device using a 1D simulator like solar cell capacitance simulator (SCAPS) version 3308 involves FTO/n-TiO₂/CsSnI₃ Perovskite absorber/Spiro OmeTAD HTL/Au contact layer. The variation in the device design key parameters such as the thickness and defect density of perovskite absorber, hole transport layer and electron transport layer and interfacial defects are examined with their impact on the photovoltaic characteristic parameters. The effect of an increase in operating temperature from 300 K to 400 K on the performance of CsSnI3-based perovskite devices is also investigated. The optimized standard device at room temperature shows the highest PCE of 25.18 % with FF of 75.71 %, Voc of 0.96 V, and Jsc of 34.67 mA/cm². The outcomes and interpretation of different inorganic Cu-based HTLs presence, such as CuSCN, Cu₂O, CuO, CuI, SrCu₂O₂, and CuSbS₂, here represent a critical avenue for the possibility of fabricating high PCE perovskite devices made of stable, low-cost, efficient, safe, and eco-friendly all-inorganic materials like CsSnI₃ perovskite light absorber.

Keywords: CsSnI₃, hole transporting layer (HTL), lead-free perovskite solar cell, SCAPS-1D software

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Authors: Olfat Mohamed Hussien Yousef

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Tamoxifen (TM) is a synthetic non-steroidal antiestrogen. It is one of the most effective drugs for treatment of estrogen-dependent cancer by binding to estrogen receptors, suppressing of epithelial proliferation and as a chemotherapeutic agent. Recently, more attention has been paid to the protective effects of natural antioxidants against toxicities induced by anti-cancer drugs involving free radical-mediated oxidative stress and tissue injury. Vitamin C is a potent antioxidant that has the ability to scavenge factors causing free radical formation in animals receiving tamoxifen. The present study aims at pinpointing the TM-induced histopathological and ultrastructural changes in the kidneys and to assess the possible chemoprotective role of vitamin C against such TM-induced microscopic changes. Thirty adult male CD-1 mice, 25-30 g in weight and 3 months old, were divided into three groups. The first group served as control. The second group received the therapeutic dose of TM at daily oral dose of 40 mg/kg body weight for 28 days. The third group received the therapeutic dose of vitamin C at a daily dose of 500 mg/kg body weight simultaneously with the therapeutic dose of TM used in group two for 28 days. Animals were sacrificed and kidney samples were obtained and processed for histological and ultrastructural examination. Histological changes induced by TM included damage of the renal corpuscles including obliteration of the subcapsular space, congestion of the glomerular blood capillaries, segmental mesangial cell proliferation with matrix expansion, capsular adhesions with the glomerular tuft especially at the urinary pole of the corpuscles. Moreover, some proximal and distal tubules suffered various degrees of degeneration in some lining cells. Haemorrhage and inflammatory cell infiltration were also observed in the intertubular spaces. Ultrastructural observations revealed damage of the parietal epithelium of Bowman’s capsule, fusion and destruction of the foot processes of podocytes and great increase of mesangial cells and mesangial matrix. The cells of the proximal convoluted tubules displayed marked destruction of the microvilli constituting the brush borders and degeneration of the mitochondria; besides, abundant lysosomes, numerous vacuoles and pyknotic nuclei were observed. The distal convoluted tubules displayed marked distruction of both the basal infolding and the mitochondria in some areas. Histological and ultrastructural results revealed that treatment of male mice with TM simultaneously with vitamin C led to apparent repair of the injured renal tissue. This might suggest that vitamin C (an antioxidant agent) can minimize the toxic effects of TM (an antiestrogen).

Keywords: tamoxifen, vitamin c, mammalian kidney, histology, ultrastructure

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Authors: Karl Kingsley

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Many mechanisms are involved in the control of cellular differentiation and growth, which are often dysregulated in many cancers. Many distinct pathways are involved in these mechanisms of control, including deoxyribonuclease (DNA) methyltransferase and histone deacetylase (HDAC) activation that controls both genetic and epigenetic modifications and micro ribonucleic acid (RNA) expression. Less is known about the expression of DNA methyltransferase (DNMT) and HDAC in oral cancers and the effect on microRNA expression. The primary objective of this study was to evaluate the expression of DNMT and HDAC family members in oral cancer and the concomitant expression of cancer-associated microRNAs. Using commercially available oral cancers, including squamous cell carcinoma (SCC)-4, SCC-9, SCC-15, and SCC-25, RNA was extracted and screened for DNMT, HDAC, and microRNA expression using highly-specific primers and quantitative polymerase chain reaction (qPCR). These data revealed low or absent expression of DNMT-1, which is associated with cellular differentiation but increased expression of DNMT-3a and DNMT-3b in all SCC cell lines compared with normal non-cancerous cell controls. In addition, no expression of HDAC1 and HDAC2 expression was found among the normal, non-cancerous cells but was highly expressed in each of the SCC cell lines examined. Differential expression of oncogenic and cancer-associated microRNAs was also observed among the SCC cell lines, including miR-21, miR-133, miR-149, miR-155, miR-365, and miR-720. These findings also appeared to vary according to observed growth rates among these cells. These data may be the first to demonstrate the expression and association between HDAC and DNMT3 family members among oral cancers. In addition, the differential expression of these epigenetic modifiers may be associated with the expression of specific microRNAs in these cancers, which have not previously been observed to the best of the author's knowledge. In addition, some associations and relationships may exist between the expression of these biomarkers and the rates of growth and proliferation, which may suggest that these expression patterns might represent potentially useful biomarkers to determine tumor aggressiveness and other phenotypic behaviors among oral cancers.

Keywords: oral cancer, DNA methyltransferase, histone deacetylase, microRNA

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Authors: Alhaji Musa Abdullahi, Usman Abdullahi, Adamu Lawan, Aminu Maidala

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Abstract 16 healthy lactating cows will be randomly selected for the trial and will be randomly divided in to 4 groups with 4 cows in each. They will be kept under similar management condition (conventional management system). Animals of relatively same weight and age will be used. After 11days for adaptation, feed intake and performance of the experimental animals will be determine. Milk sample will be collected at each milking in the morning and afternoon to determine; Milk yield, Milk fat percentage, Solid not fat percentage, Total solid percentage of milk. Cows dung will be observe to determine; Score 1 very loose watery stool, Score 2 semi solid with undigested raw material, Score 3 semi solid with less undigested raw material, Score 4 solid with very less undigested raw material, Score 5 good dung no undigested raw material. At the end of the experiment, blood samples will be analyzed for full blood counts and differentials {White Blood Cells (WBC), Red Blood Cells (RBC), Hemoglobin (Hb), Packed Cell Volume (PCV), Mean Corpuscular Volume (MCV), Mean Corpuscular Hemoglobin (MCH), Mean Corpuscular Hemoglobin Concentration (MCHC), Platelets (PLT), Lymphocytes (LYM), Basophils, Eosinophils and Monocytes Proportion (MXD) and Neutrophils (NEUT)} using automated hematology analyzer. Serum samples will be analyzed for heat shock transcription factors, heat shock proteins and hormones (Serum glucocorticoid, prolactin and cortisol). Moreover, biochemical analysis will also be conducted to check for Total protein (TP), Albumen (ALB), Globulin (GBL), Total cholesterol (TCH), glucose (G), sodium (Na+), potassium (K+), chloride (Cl-) and pH. Keywords: Lactating cows, milk composition, dung score and blood parameters.

Keywords: Lactating cows , Milk yield , Dung score , Blood parameters

Procedia PDF Downloads 184

Authors: Sabina-Adriana Floria, Marius Gavrilescu, Florin Leon, Silvia Curteanu, Costel Anton

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Neuroevolution is a subfield of artificial intelligence used to solve various problems in different application areas. Specifically, neuroevolution is a technique that applies biologically inspired methods to generate neural network architectures and optimize their parameters automatically. In this paper, we use different biologically inspired optimization algorithms in an ensemble strategy with the aim of training multilayer perceptron neural networks, resulting in regression models used to simulate the industrial chemical process of obtaining bricks from silicone-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. In addition, the initial conditions that were taken into account during the design and commissioning of the installation can change over time, which leads to the need to add new mixes to adjust the operating conditions for the desired purpose, e.g., material properties and energy saving. The present approach follows the study by simulation of a process of obtaining bricks from silicone-based materials, i.e., the modeling and optimization of the process. Optimization aims to determine the working conditions that minimize the emissions represented by nitrogen monoxide. We first use a search procedure to find the best values for the parameters of various biologically inspired optimization algorithms. Then, we propose an adaptive ensemble strategy that uses only a subset of the best algorithms identified in the search stage. The adaptive ensemble strategy combines the results of selected algorithms and automatically assigns more processing capacity to the more efficient algorithms. Their efficiency may also vary at different stages of the optimization process. In a given ensemble iteration, the most efficient algorithms aim to maintain good convergence, while the less efficient algorithms can improve population diversity. The proposed adaptive ensemble strategy outperforms the individual optimizers and the non-adaptive ensemble strategy in convergence speed, and the obtained results provide lower error values.

Keywords: optimization, biologically inspired algorithm, neuroevolution, ensembles, bricks, emission minimization

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Authors: Syed Romat Ali Shah, Bilal Shoaib, Saleem Akhtar, Munib Ahmad, Shahan Sadiqui

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Classification is a data mining technique, which is recognizedon Machine Learning (ML) algorithm. It is used to classifythe individual articlein a knownofinformation into a set of predefinemodules or group. Web mining is also a portion of that sympathetic of data mining methods. The main purpose of this paper to analysis and compare the performance of Naïve Bayse Algorithm, Decision Tree, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN)and Support Vector Machine (SVM). This paper consists of different ML algorithm and their advantages and disadvantages and also define research issues.

Keywords: Data Mining, Web Mining, classification, ML Algorithms

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Authors: Sara R. Knigge, Sugat R. Tuladhar, Alexander Becker, Tobias Schilling, Birgit Glasmacher

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Commercially available mechanical or biological heart valve prostheses both tend to fail long-term due to thrombosis, calcific degeneration, infection, or immunogenic rejection. Moreover, these prostheses are non-viable and do not grow with the patients, which is a problem for young patients. As a result, patients often need to undergo redo-operations. Tissue-engineered (TE) heart valves based on degradable electrospun fiber scaffolds represent a promising approach to overcome these limitations. Such scaffolds need sufficient mechanical properties to withstand the hydrodynamic stress of intracardiac hemodynamics. Additionally, the scaffolds should be colonized by autologous or homologous cells to facilitate the in vivo remodeling of the scaffolds to a viable structure. This study investigates how process parameters of electrospinning and degradation affect the mechanical properties of electrospun scaffolds made of FDA-approved, biodegradable polymer polycaprolactone (PCL). Fiber mats were produced from a PCL/tetrafluoroethylene solution by electrospinning. The e-spinning process was varied in terms of scaffold thickness, fiber diameter, fiber orientation, and fiber interconnectivity. The morphology of the fiber mats was characterized with a scanning electron microscope (SEM). The mats were degraded in different solutions (cell culture media, SBF, PBS and 10 M NaOH-Solution). At different time points of degradation (2, 4 and 6 weeks), tensile and cyclic loading tests were performed. Fresh porcine pericardium and heart valves served as a control for the mechanical assessment. The progression of polymer degradation was quantified by SEM and differential scanning calorimetry (DSC). Primary Human aortic endothelial cells (HAECs) and Human induced pluripotent stem cell-derived endothelial cells (iPSC-ECs) were seeded on the fiber mats to investigate the cell colonization potential. The results showed that both the electrospinning parameters and the degradation significantly influenced the mechanical properties. Especially the fiber orientation has a considerable impact and leads to a pronounced anisotropic behavior of the scaffold. Preliminary results showed that the polymer became strongly more brittle over time. However, the embrittlement can initially only be detected in the mechanical test. In the SEM and DSC investigations, neither morphological nor thermodynamic changes are significantly detectable. Live/Dead staining and SEM imaging of the cell-seeded scaffolds showed that HAECs and iPSC-ECs were able to grow on the surface of the polymer. In summary, this study's results indicate a promising approach to the development of a TE aortic heart valve based on an electrospun scaffold.

Keywords: electrospun scaffolds, long-term polymer degradation, mechanical behavior of electrospun PCL, tissue engineered aortic heart valve

Procedia PDF Downloads 144

Authors: W. Baumgartner, M. Welti, N. Hild, S. C. Hess, W. J. Stark, G. Meier Bürgisser, P. Giovanoli, J. Buschmann

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Perfusion bioreactors are used to solve problems in tissue engineering in terms of sufficient nutrient and oxygen supply. Such problems especially occur in critical size grafts because vascularization is often too slow after implantation ending up in necrotic cores. Biominerizable and biocompatible nanocomposite materials are attractive and suitable scaffold materials for bone tissue engineering because they offer mineral components in organic carriers – mimicking natural bone tissue. In addition, human adipose derived stem cells (ASCs) can potentially be used to increase bone healing as they are capable of differentiating towards osteoblasts or endothelial cells among others. In the present study, electrospun nanocomposite disks of poly-lactic-co-glycolic acid and amorphous calcium phosphate nanoparticles (PLGA/a-CaP) were seeded with human ASCs and eight disks were stacked in a bioreactor running with normal culture medium (no differentiation supplements). Under continuous perfusion and uniaxial cyclic compression, load-displacement curves as a function of time were assessed. Stiffness and energy dissipation were recorded. Moreover, stem cell densities in the layers of the piled scaffold were determined as well as their morphologies and differentiation status (endothelial cell differentiation, chondrogenesis and osteogenesis). While the stiffness of the cell free constructs increased over time caused by the transformation of the a-CaP nanoparticles into flake-like apatite, ASC-seeded constructs showed a constant stiffness. Stem cell density gradients were histologically determined with a linear increase in the flow direction from the bottom to the top of the 3.5 mm high pile (r2 > 0.95). Cell morphology was influenced by the flow rate, with stem cells getting more roundish at higher flow rates. Less than 1 % osteogenesis was found upon osteopontin immunostaining at the end of the experiment (9 days), while no endothelial cell differentiation and no chondrogenesis was triggered under these conditions. All ASCs had mainly remained in their original pluripotent status within this time frame. In summary, we have fabricated a critical size bone graft based on a biominerizable bone-biomimetic nanocomposite with preserved stiffness when seeded with human ASCs. The special feature of this bone graft was that ASC densities inside the piled construct varied with a linear gradient, which is a good starting point for tissue engineering interfaces such as bone-cartilage where the bone tissue is cell rich while the cartilage exhibits low cell densities. As such, this tissue-engineered graft may act as a bone-cartilage interface after the corresponding differentiation of the ASCs.

Keywords: bioreactor, bone, cartilage, nanocomposite, stem cell gradient

Procedia PDF Downloads 308

Authors: Clotilde Guyon, Nada Jmari, Yen-Chin Li, Jean Denoyel, Noriyuki Fujikado, Christophe Blanchet, David Root, Matthieu Giraud

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Aire induces ectopic expression of a large repertoire of tissue-specific antigen (TSA) genes in thymic medullary epithelial cells (MECs), driving immunological self-tolerance in maturing T cells. Although important mechanisms of Aire-induced transcription have recently been disclosed through the identification and the study of Aire’s partners, the fine transcriptional functions underlied by a number of them and conferred to Aire are still unknown. Alternative cleavage and polyadenylation (APA) is an essential mRNA processing step regulated by the termination complex consisting of 85 proteins, 10 of them have been related to Aire. We evaluated APA in MECs in vivo by microarray analysis with mRNA-spanning probes and RNA deep sequencing. We uncovered the preference of Aire-dependent transcripts for short-3’UTR isoforms and for proximal poly(A) site selection marked by the increased binding of the cleavage factor Cstf-64. RNA interference of the 10 Aire-related proteins revealed that Clp1, a member of the core termination complex, exerts a profound effect on short 3’UTR isoform preference. Clp1 is also significantly upregulated in the MECs compared to 25 mouse tissues in which we found that TSA expression is associated with longer 3’UTR isoforms. Aire-dependent transcripts escape a global 3’UTR lengthening associated with MEC differentiation, thereby potentiating the repressive effect of microRNAs that are globally upregulated in mature MECs. Consistent with these findings, RNA deep sequencing of actinomycinD-treated MECs revealed the increased stability of short 3’UTR Aire-induced transcripts, resulting in TSA transcripts accumulation and contributing for their enrichment in the MECs.

Keywords: Aire, central tolerance, miRNAs, transcription termination

Procedia PDF Downloads 383

Authors: Narmeen Mehmood

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The current study was conducted to evaluate the pharmacognostic parameters, phytochemical analysis and antibacterial activity of the plant. Microscopic studies were carried out to determine various Pharmacognostic parameters. Section cutting of the leaf was also done. The study of the ariel parts of Beaumontia grandiflora resulted in the identification of fatty acids mixture and unsaponifiable matters. For the separation of various constituents of the plant, successive solvent extraction was carried out in a laboratory. Material and Methods: The study was carried out with all three extracts of Beaumontia grandiflora i.e. Petroleum ether, Chloroform and Methanol. For the separation of various constituents of the plant, successive solvent extraction was carried out in the laboratory. Raw data containing the measured zones of inhibition in mm was tabulated. Results: The microscopic studies showed the presence of Upper epidermis in surface view, Part of Lamina in section view, cortical parenchyma in longitudinal view, Parenchyma with collapsed tissues, Parenchyma Cells, Epidermal cells with a part of covering trichome, starch granules, reticulated thickened vessels, Transverse Section of leaf of Beaumontia grandiflora showed Upper Epidermis, Lower Epidermis, Hairs, Vascular Bundles, Parenchyma. Phytochemical analysis of leaves of Beaumontia grandiflora indicates that Alkaloids are present. There is a possibility of the presence of some bioactive components in the crude extracts due to which it shows strong activity. Petroleum ether extract shows a greater zone of inhibition at low concentrations. Conclusion: The alkaloids possess good antibacterial activity so the presence of alkaloids may be responsible for the antibacterial activity observed in the crude organic extract of Beaumontia grandiflora.

Keywords: successive solvent extraction, zone of inhibitions., microscopy, phytochemical analysis

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Authors: Zhanara Suleimenova, Raushan Blieva, Aigerim Zhakipbekova, Inkar Tapenbayeva, Zhanar Narmuratova

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Green processes are based on innovative technologies that do not negatively affect the environment. Industrial enzymes originated from biological systems can effectively contribute to sustainable development through being isolated from microorganisms which are fermented using primarily renewable resources. Many widespread microorganisms secrete a significant amount of biocatalysts into the environment, which greatly facilitates the task of their isolation and purification. The ability to control the enzyme production through the regulation of their biosynthesis and the selection of nutrient media and cultivation conditions allows not only to increase the yield of enzymes but also to obtain enzymes with certain properties. In this regard, large potentialities are embedded in immobilized cells. Enzyme production technology in a secreted active form enabling industrial application on an economically feasible scale has been developed. This method is based on the immobilization of enzyme producers on a solid career. Immobilizing has a range of advantages: decreasing the price of the final product, absence of foreign substances, controlled process of enzyme-genesis, the ability of various enzymes' simultaneous production, etc. Design of proposed equipment gives the opportunity to increase the activity of immobilized cell culture filtrate comparing to free cells, growing in periodic culture conditions. Such technology allows giving a 10-times raise in culture productivity, to prolong the process of fungi cultivation and periods of active culture liquid generation. Also, it gives the way to improve the quality of filtrates (to make them more clear) and exclude time-consuming processes of recharging fermentative vials, that require manual removing of mycelium.

Keywords: industrial enzymes, immobilization, submerged fermentation, microscopic fungi

Procedia PDF Downloads 141

Authors: Gabriele Ciasca, Tanya E. Sassun, Eleonora Minelli, Manila Antonelli, Massimiliano Papi, Antonio Santoro, Felice Giangaspero, Roberto Delfini, Marco De Spirito

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Glioblastoma multiforme (GBM) is an extremely aggressive brain tumor, characterized by a diffuse infiltration of neoplastic cells into the brain parenchyma. Although rarely considered, mechanical cues play a key role in the infiltration process that is extensively mediated by the tumor microenvironment stiffness and, more in general, by the occurrence of aberrant interactions between neoplastic cells and the extracellular matrix (ECM). Here we provide a nano-mechanical characterization of the viscoelastic response of human GBM tissues by indentation-type atomic force microscopy. High-resolution elasticity maps show a large difference between the biomechanics of GBM tissues and the healthy peritumoral regions, opening possibilities to optimize the tumor resection area. Moreover, we unveil the nanomechanical signature of necrotic regions and anomalous vasculature, that are two major hallmarks useful for glioma staging. Actually, the morphological grading of GBM relies mainly on histopathological findings that make extensive use of qualitative parameters. Our findings have the potential to positively impact on the development of novel quantitative methods to assess the tumor grade, which can be used in combination with conventional histopathological examinations. In order to provide a more in-depth description of the role of mechanical cues in tumor progression, we compared the nano-mechanical fingerprint of GBM tissues with that of grade-I (WHO) meningioma, a benign lesion characterized by a completely different growth pathway with the respect to GBM, that, in turn hints at a completely different role of the biomechanical interactions.

Keywords: AFM, nano-mechanics, nanomedicine, brain tumors, glioblastoma

Procedia PDF Downloads 341

Authors: Le Xuan Cau

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Flash flood is occurred in short time rainfall interval: from 1 hour to 12 hours in small and medium basins. Flash floods typically have two characteristics: large water flow and big flow velocity. Flash flood is occurred at hill valley site (strip of lowland of terrain) in a catchment with large enough distribution area, steep basin slope, and heavy rainfall. The risk of flash floods is determined through Gridded Basin Flash Flood Potential Index (GBFFPI). Flash Flood Potential Index (FFPI) is determined through terrain slope flash flood index, soil erosion flash flood index, land cover flash floods index, land use flash flood index, rainfall flash flood index. Determining GBFFPI, each cell in a map can be considered as outlet of a water accumulation basin. GBFFPI of the cell is determined as basin average value of FFPI of the corresponding water accumulation basin. Based on GIS, a tool is developed to compute GBFFPI using ArcObjects SDK for .NET. The maps of GBFFPI are built in two types: GBFFPI including rainfall flash flood index (real time flash flood warning) or GBFFPI excluding rainfall flash flood index. GBFFPI Tool can be used to determine a high flash flood potential site in a large region as quick as possible. The GBFFPI is improved from conventional FFPI. The advantage of GBFFPI is that GBFFPI is taking into account the basin response (interaction of cells) and determines more true flash flood site (strip of lowland of terrain) while conventional FFPI is taking into account single cell and does not consider the interaction between cells. The GBFFPI Map of QuangNam, QuangNgai, DaNang, Hue is built and exported to Google Earth. The obtained map proves scientific basis of GBFFPI.

Keywords: ArcObjects SDK for NET, basin average value of FFPI, gridded basin flash flood potential index, GBFFPI map

Procedia PDF Downloads 381

Authors: S. S. Singh, A. Bhattacharya, S. Bhattacharya

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The eukaryotic exosome complex plays a pivotal role in RNA biogenesis, maturation, surveillance and differential expression of various RNAs in response to varying environmental signals. The exosome is composed of evolutionary conserved nine core subunits and the associated exonucleases Rrp6 and Rrp44. Rrp6p is crucial for the processing of rRNAs, other non-coding RNAs, regulation of polyA tail length and termination of transcription. Rrp6p, a 3’-5’ exonuclease is required for degradation of 5’-external transcribed spacer (ETS) released from the rRNA precursors during the early steps of pre-rRNA processing. In the parasitic protist Entamoeba histolytica in response to growth stress, there occurs the accumulation of unprocessed pre-rRNA and 5’ ETS sub fragment. To understand the processes leading to this accumulation, we looked for Rrp6 and the exosome subunits in E. histolytica, by in silico approaches. Of the nine core exosomal subunits, seven had high percentage of sequence similarity with the yeast and human. The EhRrp6 homolog contained exoribonuclease and HRDC domains like yeast but its N- terminus lacked the PMC2NT domain. EhRrp6 complemented the temperature sensitive phenotype of yeast rrp6Δ cells suggesting conservation of biological activity. We showed 3’-5’ exoribonuclease activity of EhRrp6p with in vitro-synthesized appropriate RNAs substrates. Like the yeast enzyme, EhRrp6p degraded unstructured RNA, but could degrade the stem-loops slowly. Furthermore, immunolocalization revealed that EhRrp6 was nuclear-localized in normal cells but was diminished from nucleus during serum starvation, which could explain the accumulation of 5’ETS during stress. Our study shows functional conservation of EhRrp6p in E.histolytica, an early-branching eukaryote, and will help to understand the evolution of exosomal components and their regulatory function.

Keywords: entamoeba histolytica, exosome complex, rRNA processing, Rrp6

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Authors: Mengjie Qu, Yi Wang, Jiawei Ding, Siyu Chen, Yanan Di

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Marine ecosystem is facing intensified multiple stresses caused by environmental contaminants from human activities. Xenobiotics, such as benzo(α)pyrene (BaP) have been discharged into marine environment and cause hazardous impacts on both marine organisms and human beings. As a filter-feeder, marine mussels, Mytilus spp., has been extensively used to monitor the marine environment. However, their genomic alterations induced by such xenobiotics are still kept unknown. In the present study, gills, as the first defense barrier in mussels, were selected to evaluate the genetic instability alterations induced by the exposure to BaP both in vivo and in vitro. Both random amplified polymorphic DNA (RAPD) assay and comet assay were applied as the rapid tools to assess the environmental stresses due to their low money- and time-consumption. All mussels were identified to be the single species of Mytilus coruscus before used in BaP exposure at the concentration of 56 μg/l for 1 & 3 days (in vivo exposure) or 1 & 3 hours (in vitro). Both RAPD and comet assay results were showed significantly increased genomic instability with time-specific altering pattern. After the recovery period in 'in vivo' exposure, the genomic status was as same as control condition. However, the relative higher genomic instabilities were still observed in gill cells after the recovery from in vitro exposure condition. Different repair mechanisms or signaling pathway might be involved in the isolated gill cells in the comparison with intact tissues. The study provides the robust and rapid techniques to exam the genomic stability in marine organisms in response to marine environmental changes and provide basic information for further mechanism research in stress responses in marine organisms.

Keywords: genotoxic impacts, in vivo/vitro exposure, marine mussels, RAPD and comet assay

Procedia PDF Downloads 279