Search results for: neural progentor cells

Authors: Jan Masak, Eva Kvasnickova, Vladimir Scholtz, Olga Matatkova, Marketa Valkova, Alena Cejkova

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Microbial colonization of medical instruments, catheters, implants, etc. is a serious problem in the spread of nosocomial infections. Biofilms exhibit enormous resistance to environment. The resistance of biofilm populations to antibiotic or biocides often increases by two to three orders of magnitude in comparison with suspension populations. Subjects of interests are substances or physical processes that primarily cause the destruction of biofilm, while the released cells can be killed by existing antibiotics. In addition, agents that do not have a strong lethal effect do not cause such a significant selection pressure to further enhance resistance. Non-thermal plasma (NTP) is defined as neutral, ionized gas composed of particles (photons, electrons, positive and negative ions, free radicals and excited or non-excited molecules) which are in permanent interaction. In this work, the effect of NTP generated by the cometary corona with a metallic grid on the formation and stability of biofilm and metabolic activity of cells in biofilm was studied. NTP was applied on biofilm populations of Staphylococcus epidermidis DBM 3179, Pseudomonas aeruginosa DBM 3081, DBM 3777, ATCC 15442 and ATCC 10145, Escherichia coli DBM 3125 and Candida albicans DBM 2164 grown on solid media on Petri dishes and on the titanium alloy (Ti6Al4V) surface used for the production joint replacements. Erythromycin (for S. epidermidis), polymyxin B (for E. coli and P. aeruginosa), amphotericin B (for C. albicans) and ceftazidime (for P. aeruginosa) were used to study the combined effect of NTP and antibiotics. Biofilms were quantified by crystal violet assay. Metabolic activity of the cells in biofilm was measured using MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) colorimetric test based on the reduction of MTT into formazan by the dehydrogenase system of living cells. Fluorescence microscopy was applied to visualize the biofilm on the surface of the titanium alloy; SYTO 13 was used as a fluorescence probe to stain cells in the biofilm. It has been shown that biofilm populations of all studied microorganisms are very sensitive to the type of used NTP. The inhibition zone of biofilm recorded after 60 minutes exposure to NTP exceeded 20 cm², except P. aeruginosa DBM 3777 and ATCC 10145, where it was about 9 cm². Also metabolic activity of cells in biofilm differed for individual microbial strains. High sensitivity to NTP was observed in S. epidermidis, in which the metabolic activity of biofilm decreased after 30 minutes of NTP exposure to 15% and after 60 minutes to 1%. Conversely, the metabolic activity of cells of C. albicans decreased to 53% after 30 minutes of NTP exposure. Nevertheless, this result can be considered very good. Suitable combinations of exposure time of NTP and the concentration of antibiotic achieved in most cases a remarkable synergic effect on the reduction of the metabolic activity of the cells of the biofilm. For example, in the case of P. aeruginosa DBM 3777, a combination of 30 minutes of NTP with 1 mg/l of ceftazidime resulted in a decrease metabolic activity below 4%.

Keywords: anti-biofilm activity, antibiotic, non-thermal plasma, opportunistic pathogens

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Authors: Simone F. Medeiros, Isabela F. Santos, Rodolfo M. Moraes, Jaspreet K. Kular, Marcus A. Johns, Ram Sharma, Amilton M. Santos

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Tissue engineering aims to develop alternatives to treat damaged tissues by promoting their regeneration. Its basic principle is to place cells on a scaffold capable of promoting cell functions, and for this purpose, polymeric nanoparticles have been successfully used due to the ability of some macro chains to mimic the extracellular matrix and influence cell functions. In general, nanoparticles require surface chemical modification to achieve cell adhesion, and recent advances in their synthesis include methods for modifying the ligand density and distribution onto nanoparticles surface. However, this work reports the development of biodegradable polymeric nanoparticles capable of promoting cellular adhesion without any surface chemical modification by ligands. Biocompatible and biodegradable nanoparticles based on poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBHV) were synthesized by solvent evaporation method. The produced nanoparticles were small in size (85 and 125 nm) and colloidally stable against time in aqueous solution. Morphology evaluation showed their spherical shape with small polydispersity. Human osteoblast-like cells (MG63) were cultured in the presence of PHBHV nanoparticles, and growth kinetics were compared to those grown on tissue culture polystyrene (TCPS). Cell attachment on non-tissue culture polystyrene (non-TCPS) pre-coated with nanoparticles was assessed and compared to attachment on TCPS. These findings reveal the potential of PHBHV nanoparticles for cell adhesion and growth, without requiring a matrix ligand to support cells, to be used as scaffolds, in tissue engineering applications.

Keywords: tissue engineering, PHBHV, stem cells, cellular attachment

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Authors: Shahrzad Zolfagharnassab, Abdul Rashid Mohamed Shariff, Reza Ehsani, Hawa Ze Jaffar, Ishak Aris

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Ripeness estimation of oil palm fresh fruit is important processes that affect the profitableness and salability of oil palm fruits. The adulthood or ripeness of the oil palm fruits influences the quality of oil palm. Conventional procedure includes physical grading of Fresh Fruit Bunches (FFB) maturity by calculating the number of loose fruits per bunch. This physical classification of oil palm FFB is costly, time consuming and the results may have human error. Hence, many researchers try to develop the methods for ascertaining the maturity of oil palm fruits and thereby, deviously the oil content of distinct palm fruits without the need for exhausting oil extraction and analysis. This research investigates the potential of infrared images (Thermal Images) as a predictor to classify the oil palm FFB ripeness. A total of 270 oil palm fresh fruit bunches from most common cultivar of oil palm bunches Nigresens according to three maturity categories: under ripe, ripe and over ripe were collected. Each sample was scanned by the thermal imaging cameras FLIR E60 and FLIR T440. The average temperature of each bunches were calculated by using image processing in FLIR Tools and FLIR ThermaCAM researcher pro 2.10 environment software. The results show that temperature content decreased from immature to over mature oil palm FFBs. An overall analysis-of-variance (ANOVA) test was proved that this predictor gave significant difference between underripe, ripe and overripe maturity categories. This shows that the temperature as predictors can be good indicators to classify oil palm FFB. Classification analysis was performed by using the temperature of the FFB as predictors through Linear Discriminant Analysis (LDA), Mahalanobis Discriminant Analysis (MDA), Artificial Neural Network (ANN) and K- Nearest Neighbor (KNN) methods. The highest overall classification accuracy was 88.2% by using Artificial Neural Network. This research proves that thermal imaging and neural network method can be used as predictors of oil palm maturity classification.

Keywords: artificial neural network, maturity classification, oil palm FFB, thermal imaging

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Authors: A. I. Al-Bassam, A. M. El-Nggar

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Polycrystalline Cu In I-x GaxSe2 thin films have been fabricated. Some physical properties such as lattice parameters, crystal structure and microstructure of Cu In I-x GaxSe2 were determined using X-ray diffractometry and scanning electron microscopy. X-ray diffraction analysis showed that the films with x ≥ 0.5 have a chalcopyrite structure and the films with x ≤ 0.5 have a zinc blende structure. The lattice parameters were found to vary linearly with composition over a wide range from x = 0 to x =1.0. The variation of lattice parameters with composition was found to obey Vegard's law. The variation of the c/a with composition was also linear. The quality of a wide range of Cu In I-xGaxSe2 thin film absorbers from CuInSe to CuGaSe was evaluated by Photoluminescence (PL) measurements.

Keywords: grain size, polycrystalline, solar cells, lattice parameters

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Authors: Hussain Mustatab Wahedi, Sun You Kim

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Skin acts as a barrier against the harmful environmental factors. Integrity and timely recovery of the skin from injuries and harmful effects of radiations is thus very important. This study aimed to investigate the importance of Sirt1 in the recovery of skin from UVB-induced damage and cutaneous wounds by using natural and synthetic novel Sirt1 activators. Juglone, known as a natural Pin1 inhibitor, and NED416 a novel synthetic Sirt1 activator were checked for their ability to regulate the expression and activity of Sirt1 and hence photo-damage and wound healing in cultured skin cells (NHDF and HaCaT cells) and mouse model by using Sirt1 siRNA knockdown, cell migration assay, GST-Pulldown assay, western blot analysis, tube formation assay, and immunohistochemistry. Interestingly, Sirt1 knockdown inhibited skin cell migration in vitro. Juglone up regulated the expression of Sirt1 in both the cell lines under normal and UVB irradiated conditions, enhanced Sirt1 activity and increased the cell viability by reducing reactive oxygen species synthesis and apoptosis. Juglone promoted wound healing by increasing cell migration and angiogenesis through Cdc42/Rac1/PAK, MAPKs and Smad pathways in skin cells. NED416 upregulated Sirt1 expression in HaCaT and NHDF cells as well as increased Sirt1 activity. NED416 promoted the process of wound healing in early as well as later stages by increasing macrophage recruitment, skin cell migration, and angiogenesis through Cdc42/Rac1 and MAPKs pathways. So, both these compounds activated Sirt1 and promoted the process of wound healing thus pointing towards the possible role of Sirt1 in skin regeneration and wound healing.

Keywords: skin regeneration, wound healing, Sirt1, UVB light

Procedia PDF Downloads 188

Authors: J. Barilla, M. Lokajíček, H. Pisaková, P. Simr

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The final biological effect of ionizing particles may be influenced strongly by some chemical substances present in cells mainly in the case of low-LET radiation. The influence of oxygen may be particularly important because oxygen is always present in living cells. The corresponding processes are then running mainly in the chemical stage of radio biological mechanism. The radical clusters formed by densely ionizing ends of primary or secondary charged particles are mainly responsible for final biological effect. The damage effect depends then on radical concentration at a time when the cluster meets a DNA molecule. It may be strongly influenced by oxygen present in a cell as oxygen may act in different directions: at small concentration of it the interaction with hydrogen radicals prevails while at higher concentrations additional efficient oxygen radicals may be formed. The basic radical concentration in individual clusters diminishes, which is influenced by two parallel processes: chemical reactions and diffusion of corresponding clusters. The given simultaneous evolution may be modeled and analyzed well with the help of Continuous Petri nets. The influence of other substances present in cells during irradiation may be studied, too. Some results concerning the impact of oxygen content will be presented.

Keywords: radiobiological mechanism, chemical phase, DSB formation, Petri nets

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Authors: Hawraa Zbeeb, Hala Khalifeh, Mohamad Khalil, Francesca Storace, Francesca Baldini, Giulio Lupidi, Laura Vergani

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Sarcopoterium spinosum, a widely distributed spiny shrub belonging to the Rosaceae family, is rich in essential and beneficial constituents. In fact, S. spinosum fruits and roots are traditionally used as herbal medicine in the eastern Mediterranean landscape, and this shrub is mentioned as a medicinal plant in a large number of ethnobotanical surveys. Aqueous root extracts from S. spinosum are used by traditional medicinal practitioners for weight loss treatment of diabetes and pain. Moreover, the anti-diabetic activity of S. spinosum root extract has been reported in different studies, but the beneficial effects of aerial parts, especially fruits, have not been elucidated yet. The aim of the present study was to investigate the in vitro antioxidant and lipid-lowering properties of an ethanolic extract from S. spinosum fruits using both hepatic (FaO) and endothelial (HECV) cells in an attempt to evaluate its possible employment as a nutraceutical supplement. First of all, in vitro spectrophotometric assays were employed to characterize the extract. The total phenol content (TPC) was evaluated by Folin–Ciocalteu spectrophotometric method and the radical scavenging activity was tested by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2, 2'-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) assays. After that, the beneficial effects of the extract were tested on cells. FaO cells treated for 3 hours with 0.75 mM oleate/palmitate mix (1:2 molar ratio) mimic in vitro a moderate hepato-steatosis. HECV cells exposed for 1 hour to 100 µM H₂O₂ mimic an oxidative insult leading to oxidative stress conditions. After the metabolic and oxidative insult, both cell lines were treated with increasing concentrations of the S. spinosum extract (1, 10, 25 µg/mL) for 24 hours. The results showed the S. spinosum ethanolic extract is rather rich in phenols (TPC of 18.6 mgGAE/g dry extracts). Moreover, the extract showed a good scavenging ability in vitro (IC₅₀ 15.9 µg/ml and 10.9 µg/ml measured by DPPH and ABTS assays, respectively). When the extract was tested on cells, the results showed that it could ameliorate some markers of cell dysfunction. The three concentrations of the extract led to a significant decrease in the intracellular triglyceride (TG) content in steatotic FaO cells measured by spectrophotometric assay. On the other hand, HECV cells treated with increasing concentrations of the extract did not result in a significant decrease in both lipid peroxidation measured by the Thiobarbituric Acid Reactive Substances (TBARS) assay, and in reactive oxygen species (ROS) production measured by fluorometric analysis after DCF staining. Interestingly, the ethanolic extract was able to accelerate the wound repair of confluent HECV cells with respect to H₂O₂-insulted cells as measured by T-scratch assay. Taken together, these results seem to indicate that the ethanol extract from S. spinosum fruits is rich in phenol compounds and plays considerable lipid-lowering activity in vitro on steatotic hepatocytes and accelerates wound healing repair on endothelial cells. In light of that, the ethanolic extract from S. spinosum fruits could be a potential candidate for nutraceutical applications.

Keywords: antioxidant activity, ethanolic extract, lipid-lowering activity, phenolic compounds, Sarcopoterium spinosum fruits

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Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

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Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feed-forward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on self organizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: classification, SOFM algorithm, neural network, neighborhood, RGB image

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Authors: Hamzeh Alipour, Masoumeh Bagheri, Abbasali Raz, Javad Dadgar Pakdel, Kourosh Azizi, Aboozar Soltani, Mohammad Djaefar Moemenbellah-Fard

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Background: Maggot debridement therapy is an appropriate, effective, and controlled method using sterilized larvae of Luciliasericata (L.sericata) to treat wounds. Netrin-A is an enzyme in the Laminins family which secreted from salivary gland of L.sericata with a central role in neural regeneration and angiogenesis. This study aimed to production of new recombinant Netrin-A protein of Luciliasericata larvae by baculovirus expression vector system (BEVS) in SF9. Material and methods: In the first step, gene structure was subjected to the in silico studies, which were include determination of Antibacterial activity, Prion formation risk, homology modeling, Molecular docking analysis, and Optimization of recombinant protein. In the second step, the Netrin-A gene was cloned and amplified in pTG19 vector. After digestion with BamH1 and EcoR1 restriction enzymes, it was cloned in pFastBac HTA vector. It was then transformed into DH10Bac competent cells, and the recombinant Bacmid was subsequently transfected into insect Sf9 cells. The expressed recombinant Netrin-A was thus purified in the Ni-NTA agarose. This protein evaluation was done using SDS-PAGE and western blot, respectively. Finally, its concentration was calculated with the Bradford assay method. Results: The Bacmid vector structure with Netrin-A was successfully constructed and then expressed as Netrin-A protein in the Sf9 cell lane. The molecular weight of this protein was 52 kDa with 404 amino acids. In the in silico studies, fortunately, we predicted that recombinant LSNetrin-A have Antibacterial activity and without any prion formation risk.This molecule hasa high binding affinity to the Neogenin and a lower affinity to the DCC-specific receptors. Signal peptide located between amino acids 24 and 25. The concentration of Netrin-A recombinant protein was calculated to be 48.8 μg/ml. it was confirmed that the characterized gene in our previous study codes L. sericata Netrin-A enzyme. Conclusions: Successful generation of the recombinant Netrin-A, a secreted protein in L.sericata salivary glands, and because Luciliasericata larvae are used in larval therapy. Therefore, the findings of the present study could be useful to researchers in future studies on wound healing.

Keywords: blowfly, BEVS, gene, immature insect, recombinant protein, Sf9

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Authors: G. M. Hamada, A. A. Al-Gathe, A. M. Al-Khudafi

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Determination of water saturation in sandstone is a vital question to determine the initial oil or gas in place in reservoir rocks. Water saturation determination using electrical measurements is mainly on Archie’s formula. Consequently accuracy of Archie’s formula parameters affects water saturation values rigorously. Determination of Archie’s parameters a, m, and n is proceeded by three conventional techniques, Core Archie-Parameter Estimation (CAPE) and 3-D. This work introduces the hybrid system of parallel self-organizing neural network (PSONN) targeting accepted values of Archie’s parameters and, consequently, reliable water saturation values. This work focuses on Archie’s parameters determination techniques; conventional technique, CAPE technique, and 3-D technique, and then the calculation of water saturation using current. Using the same data, a hybrid parallel self-organizing neural network (PSONN) algorithm is used to estimate Archie’s parameters and predict water saturation. Results have shown that estimated Arche’s parameters m, a, and n are highly accepted with statistical analysis, indicating that the PSONN model has a lower statistical error and higher correlation coefficient. This study was conducted using a high number of measurement points for 144 core plugs from a sandstone reservoir. PSONN algorithm can provide reliable water saturation values, and it can supplement or even replace the conventional techniques to determine Archie’s parameters and thereby calculate water saturation profiles.

Keywords: water saturation, Archie’s parameters, artificial intelligence, PSONN, sandstone reservoir

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Authors: Susmita Panda, Arnab Banerjee, Ajinkya Baxy, Bappaditya Manna

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The design of short to medium-span high-speed bridges in critical locations is an essential aspect of vehicle-bridge interaction. Due to dynamic interaction between moving load and bridge, mathematical models or finite element modeling computations become time-consuming. Thus, to reduce the computational effort, a universal approximator using an artificial neural network (ANN) has been used to evaluate the dynamic response of the bridge. The data set generation and training of surrogate models have been conducted over the results obtained from mathematical modeling. Further, the robustness of the surrogate model has been investigated, which showed an error percentage of less than 10% with conventional methods. Additionally, the dependency of the dynamic response of the bridge on various load and bridge parameters has been highlighted through a parametric study.

Keywords: artificial neural network, mode superposition method, moving load analysis, surrogate models

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Authors: Boudemagh Naime

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Automatic radar detection requires some methods of adapting to variations in the background clutter in order to control their false alarm rate. The problem becomes more complicated in non-Gaussian environment. In fact, the conventional approach in real time applications requires a complex statistical modeling and much computational operations. To overcome these constraints, we propose another approach based on artificial neural network (ANN-CMLD-CFAR) using a Back Propagation (BP) training algorithm. The considered environment follows a log-normal distribution in the presence of multiple Rayleigh-targets. To evaluate the performances of the considered detector, several situations, such as scale parameter and the number of interferes targets, have been investigated. The simulation results show that the ANN-CMLD-CFAR processor outperforms the conventional statistical one.

Keywords: radat detection, ANN-CMLD-CFAR, log-normal clutter, statistical modelling

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Authors: Olena Grygorieva

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Nowadays mechanisms of thymocytes emigration from the thymus to the periphery are investigated actively. We have proposed a hypothesis of thymocytes’ migration from the thymus through lymphatic vessels during periodical short-term local edema. By morphological, hystochemical methods we have examined quantity of lymphocytes, epitelioreticulocytes, mast cells, blood and lymphatic vessels in morpho-functional areas of rats’ thymuses during the first week after birth in 4 hours interval. In newborn and beginning from 8 hour after birth every 12 hours specific density of the thymus, absolute quantity of microcirculatory vessels, especially of lymphatic ones, lymphcyte-epithelial index, quantity of mast cells and their degranulative forms increase. Structure of extracellular matrix, intrathymical microenvironment and lymphocytes’ adhesive properties change. Absolute quantity of small lymphocytes in thymic cortex changes wavy. All these changes are straightly expressed from 0 till 2, from 12 till 16, from 108 till 120 hours of postnatal life. During this periods paravasal lymphatic vessels are stuffed with lymphocytes, i.e. discrete migration of lymphocytes from the thymus occurs. After rapid edema reduction, quantity of lymphatic vessels decrease, they become empty. Therefore, in the thymus of newborn periodical short-term local edema is observed, on its top discrete migration of lymphocytes from the thymus occurs.

Keywords: lymphocytes, lymphatic vessels, mast cells, thymus

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Authors: N. Selami, M. Kaid Harche

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A pink-pigmented, aerobic, facultatively methylotrophic bacterium, was isolated from Retama monosperma root nodules and identified as a member of the genus Methylobacterium. Inoculation of R. monosperma plants by a pure culture of isolate strain under a hydroponic condition, resulted, 10 dpi, the puffiness at lateral roots. The observation in detail the anatomy and ultra-structure of infection sites by light and electron microscopy show that the bacteria induce stimulation of the division of cortical cells and digestion of epidermis cells then, Methylobacterium was observed in the inter and intracellular spaces of the outer cortex root. These preliminary results allow us to suggest the establishment of an epi-endosymbiotic interaction between Methylobacterium sp and R. monosperma.

Keywords: endophytic colonization, Methylobacterium, microscopy, nodule, pink pigmented, Retama monosperma

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Authors: Bayan Almofty, Yuto Yamaki, Tadamasa Terai, Sadahito Uto

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Myopathy (muscles disease) treatment are expected in the field of regenerative medicine and applied research of cultured muscle to bio actuator is performed in Biomedical Engineering as applied research of cultured muscle. This study is about cultured myoblast C2C12 from mouse skeletal muscle and a mechanism of cultured muscle contraction by electric stimulation is investigated. Grayanotoxins (GTXs) belong to neurotoxins known to enhance the permeability of cell membrane for Na ions. Grayanotoxins are extracted from a famous Pieris japonica and Ericaceae as a phytotoxin. We investigated the functional role of GTXs on muscle cells (C2C12) contraction and membrane potential. A change in membrane potential is measured using a micro glass tube electrode contraction of myotubes is induced by applying an external electrical stimulation. The contraction and membrane potential change induced by injection of current using the micro glass electrode are also measured. From the result, contraction and membrane potential of muscle cells was affected by GTXs treatment, suggesting that the diverse chemical structures of GTXs are responsible for contraction and membrane potential of muscle cells.

Keywords: skeletal muscle, C2C12, myoblast, myotubes, contraction, Grayanotoxins, membrane potential, neurotoxins, phytotoxin

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Authors: Pocholo Rodriguez, Anne Bernadine Ocampo, Ian Benedict Chan, Janric Micah Gray

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The state of an electric power system may be classified as either stable or unstable. The borderline of stability is at any condition for which a slight change in an unfavourable direction of any pertinent quantity will cause instability. Voltage instability in power distribution systems could lead to voltage collapse and thus power blackouts. The researchers will present an intelligent system using back propagation algorithm that can detect voltage instability and output voltage of a power distribution and classify it as stable or unstable. The researchers’ work is the use of parameters involved in voltage instability as input parameters to the neural network for training and testing purposes that can provide faster detection and monitoring of the power distribution system.

Keywords: back-propagation algorithm, load instability, neural network, power distribution system

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Authors: Grzegorz Swiderski, Agata Jablonska-Trypuc, Natalia Popow, Renata Swislocka, Wlodzimierz Lewandowski

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Doxorubicin belongs to the group of anthracycline antitumor antibiotics. Because of the wide spectrum of actions, it is one of the most widely used anthracycline antibiotics, including the treatment of breast, ovary, bladder, lung cancers as well as neuroblastoma, lymphoma, leukemia and myeloid leukemia. Antitumor activity of doxorubicin is based on the same mechanisms as for most anthracyclines. Like the metal ions affect the nucleic acids on many biological processes, so the environment of the metal chelates of antibiotics can have a significant effect on the pharmacological properties of drugs. Complexation of anthracyclines with metal ions may contribute to the production of less toxic compounds. In the framework of this study, the composition of complexes obtained in aqueous solutions of doxorubicin with metal ions (Cu2+ and Zn2+). Complexation was analyzed by spectrophotometric titration in aqueous solution at pH 7.0. The pH was adjusted with 0.02M Tris-HCl buffer. The composition of the complexes found was Cu: doxorubicin (1: 2) and a Zn: doxorubicin (1: 1). The effect of Dox, Dox-Cu and Dox-Zn was examined in MCF-7 breast cancer cell line, which were obtained from American Type Culture Collection (ATCC). The compounds were added to the cultured cells for a final concentration in the range of 0,01µM to 0,5µM. The number of MCF-7 cells with division into living and dead, was determined by direct counts of cells with the use of trypan blue dye using LUNA Logos Biosystems cell counter. ApoTox-Glo Triplex Assay (Promega, Madison, Wisconsin, USA) was used according to the manufacturer’s instructions to measure the MCF-7 cells’ viability, cytotoxicity and apoptosis. We observed a decrease in cells proliferation in a dose-dependent manner. An increase in cytotoxicity and decrease in viability in the ApoTox Triplex assay was also showed for all tested compounds. Apoptosis, showed as caspase 3/7 activation, was observed only in Dox treatment. In Dox-Zn and Dox-Cu caspase 3/7 activation was not observed. This work was financially supported by National Science Centre, Poland, under the research project number 2014/13/B/NZ7/02 352.

Keywords: anticancer properties, anthracycline antibiotic, doxorubicine, metal complexes

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Authors: Sudeshna Mukherjee, Leena Fageria, R. Venkataramana Dilip, Rajdeep Chowdhury, Jitendra Panwar

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Metal nanoparticles in recent years have gained importance in cancer therapy due to their enhanced permeability retention effect. Among various nanomaterials, silver nanoparticles (AgNPs) have received considerable attention due to their unique properties like conductivity, chemical stability, relative lower toxicity and outstanding therapeutic potential, such as anti-inflammatory, antimicrobial and anti-cancerous activities. In this study, we took a greener approach to synthesize silver nanoparticle from fungus and analyze its effects on both epithelial and mesenchymal derived cancer cells. Much research has been done on nanoparticle-induced apoptosis, but little is known about its role in autophagy. In our study, the silver nanoparticles were seen to induce autophagy which was analyzed by studying the expression of several autophagy markers like, LC3B-II and ATG genes. Monodansylcadaverine (MDC) assay also revealed the induction of autophagy upon treatment with AgNPs. Inhibition of autophagy by chloroquine resulted in increased cell death suggesting autophagy as a survival strategy adopted by the cells. In parallel to autophagy induction, silver nanoparticles induced ROS accumulation. Interestingly, autophagy inhibition by chloroquine increased ROS level, resulting in enhanced cell death. We further analyzed MAPK signaling upon AgNP treatment. It was observed that along with autophagy, activation of JNK signaling served as pro-survival while ERK signaling served as a pro-death signal. Our results provide valuable insights into the role of autophagy upon AgNP exposure and provide cues to probabilistic strategies to effectively sensitize cancer cells.

Keywords: autophagy, JNK signalling, reactive oxygen species, silver nanoparticles

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Authors: Tanima Chatterjee, Maitree Bhattacharyya

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The global challenge of type 2 diabetes mellitus is a major health concern in this millennium, and researchers are continuously exploring new targets to develop a novel therapeutic strategy. Type 2 diabetes mellitus (T2DM) is often coupled with dyslipidemia increasing the risks for cardiovascular (CVD) complications. Enhanced oxidative and nitrosative stresses appear to be the major risk factors underlying insulin resistance, dyslipidemia, β-cell dysfunction, and T2DM pathogenesis. Autophagy emerges to be a promising defense mechanism against stress-mediated cell damage regulating tissue homeostasis, cellular quality control, and energy production, promoting cell survival. In this study, we have attempted to explore the pivotal role of autophagy in T2DM subjects with or without dyslipidemia in peripheral blood mononuclear cells and insulin-resistant HepG2 cells utilizing flow cytometric platform, confocal microscopy, and molecular biology techniques like western blotting, immunofluorescence, and real-time polymerase chain reaction. In the case of T2DM with dyslipidemia higher population of autophagy, positive cells were detected compared to patients with the only T2DM, which might have resulted due to higher stress. Autophagy was observed to be triggered both by oxidative and nitrosative stress revealing a novel finding of our research. LC3 puncta was observed in peripheral blood mononuclear cells and periphery of HepG2 cells in the case of the diabetic and diabetic-dyslipidemic conditions. Increased expression of ATG5, LC3B, and Beclin supports the autophagic pathway in both PBMC and insulin-resistant Hep G2 cells. Upon blocking autophagy by 3-methyl adenine (3MA), the apoptotic cell population increased significantly, as observed by caspase‐3 cleavage and reduced expression of Bcl2. Autophagy has also been evidenced to control oxidative stress-mediated up-regulation of inflammatory markers like IL-6 and TNF-α. To conclude, this study elucidates autophagy to play a protective role in the case of diabetes mellitus with dyslipidemia. In the present scenario, this study demands to have a significant impact on developing a new therapeutic strategy for diabetic dyslipidemic subjects by enhancing autophagic activity.

Keywords: autophagy, apoptosis, dyslipidemia, reactive oxygen species, reactive nitrogen species, Type 2 diabetes

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Authors: Abu Salim Mustafa

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Rv3873 is a relatively large size protein (371 amino acids in length) and its gene is located in the immunodominant genomic region of difference (RD)1 that is present in the genome of Mycobacterium tuberculosis but deleted from the genomes of all the vaccine strains of Bacillus Calmette Guerin (BCG) and most other mycobacteria. However, when tested for cellular immune responses using peripheral blood mononuclear cells from tuberculosis patients and BCG-vaccinated healthy subjects, this protein was found to be a major stimulator of cell mediated immune responses in both groups of subjects. In order to further identify the sequence of immunodominant epitopes and explore their Human Leukocyte Antigen (HLA)-restriction for epitope recognition, 24 peptides (25-mers overlapping with the neighboring peptides by 10 residues) covering the sequence of Rv3873 were synthesized chemically using fluorenylmethyloxycarbonyl chemistry and tested in cell mediated immune responses. The results of these experiments helped in the identification of an immunodominant peptide P9 that was recognized by people expressing varying HLA-DR types. Furthermore, it was also predicted to be a promiscuous binder with multiple epitopes for binding to HLA-DR, HLA-DP and HLA-DQ alleles of HLA-class II molecules that present antigens to T helper cells, and to HLA-class I molecules that present antigens to T cytotoxic cells. In addition, the evaluation of peptide P9 using an immunogenicity predictor server yielded a high score (0.94), which indicated a greater probability of this peptide to elicit a protective cellular immune response. In conclusion, P9, a peptide with multiple epitopes and ability to bind several HLA class I and class II molecules for presentation to cells of the cellular immune response, may be useful as a peptide-based vaccine against tuberculosis.

Keywords: mycobacterium tuberculosis, PPE68, peptides, vaccine

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Authors: Yu-Chu Yeh, WeiChin Hsu, Chih-Yen Chang

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Substitution, combination, modification, putting to other uses, elimination, and rearrangement (SCAMPER) has been regarded as an effective technique that provides a structured way to help people to produce creative ideas and solutions. Although some neuroscience studies regarding creativity training have been conducted, no study has focused on SCAMPER. This study therefore aimed at examining whether the learning of SCAMPER through video tutorials would result in alternations of neural activation. Thirty college students were randomly assigned to the experimental group or the control group. The experimental group was requested to watch SCAMPER videos, whereas the control group was asked to watch natural-scene videos which were regarded as neutral stimulating materials. Each participant was brain scanned in a Functional magnetic resonance imaging (fMRI) machine while undertaking a creativity test before and after watching the videos. Furthermore, a two-way ANOVA was used to analyze the interaction between groups (the experimental group; the control group) and tasks (C task; M task; X task). The results revealed that the left precuneus significantly activated in the interaction of groups and tasks, as well as in the main effect of group. Furthermore, compared with the control group, the experimental group had greater activation in the default mode network (left precuneus and left inferior parietal cortex) and the motor network (left postcentral gyrus and left supplementary area). The findings suggest that the SCAMPER training may facilitate creativity through the stimulation of the default mode network and the motor network.

Keywords: creativity, default mode network, neural activation, SCAMPER

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Authors: Hira Lal Gope, Hidekazu Fukai

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The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: convolutional neural networks, coffee bean, peaberry, sorting, support vector machine

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Authors: Dong-An Wang

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All kinds of microspheres have been extensively employed as carriers for drug, gene and therapeutic cell delivery. Most therapeutic cell delivery microspheres rely on a two-step methodology: fabrication of microspheres and subsequent seeding of cells onto them. In this study, we have developed a novel one-step cell encapsulation technique using a convenient and instant water-in-oil single emulsion approach to form cell-encapsulated gelatin microspheres. This technology is adopted for hyaline cartilage tissue engineering, in which autologous chondrocytes are used as therapeutic cells. Cell viability was maintained throughout and after the microsphere formation (75-100 µm diameters) process that avoids involvement of any covalent bonding reactions or exposure to any further chemicals. Further encapsulation of cell-laden microspheres in alginate gels were performed under 4°C via a prompt process. Upon the formation of alginate constructs, they were immediately relocated into CO2 incubator where the temperature was maintained at 37°C; under this temperature, the cell-laden gelatin microspheres dissolved within hours to yield similarly sized cavities and the chondrocytes were therefore suspended within the cavities inside the alginate gel bulk. Hence, the gelatin cell-laden microspheres served two roles: as cell delivery vehicles which can be removable through temperature curing, and as porogens within an alginate hydrogel construct to provide living space for cell growth and tissue development as well as better permeability for mutual diffusions. These cell-laden microspheres, namely “temperature-cured dissolvable gelatin microsphere based cell carriers” (tDGMCs), were further encapsulated in a chondrocyte-laden alginate scaffold system and analyzed by WST-1, gene expression analyses, biochemical assays, histology and immunochemistry stains. The positive results consistently demonstrated the promise of tDGMC technology in delivering these non-anchorage dependent cells (chondrocytes). It can be further conveniently translated into delivery of other non-anchorage dependent cell species, including stem cells, progenitors or iPS cells, for regeneration of tissues in internal organs, such as engineered hepatogenesis or pancreatic regeneration.

Keywords: biomaterials, tissue engineering, microsphere, hydrogel, porogen, anchorage dependence

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Authors: Mayuva Youngsabanant-Areekijseree, Chanikarn Srinark, S. Sengsai, Mayuree Pumipaiboon

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Our project was aimed at morphology of oocytes, follicle cells and follicular fluid proteins study of Large White pig (at local slaughter house in Nakhon Pathom Province). The porcine oocytes and follicular fluid of healthy small follicles (1-2 mm), medium follicles (3-6 mm in diameters) and large follicles (7-8 mm and 10 mm in diameter) were aspirated and collected from the ovary by sterile technique. Then, the oocytes and the follicle cells were separated from the fluid. The oocytes were round shape and surrounded by zona pellucida with numerous layers of cumulus cells. Based on the number of cumulus cell layers surrounding oocytes, the oocytes were classified into 5 types, which were intact-, multi-, partial-cumulus layer oocyte, completely denuded oocyte and degenerative oocyte. The collected oocytes showed high percentages of intact- and multi- cumulus cell layers in the small follicles (53.48%) medium follicles (56.94%) and large follicles (56.52%) which have high potential to develop into mature oocytes in vitro. Proteins from follicular fluid of 3 size follicles were separated by SDS-PAGE and LC/MS/MS. The molecular weight of follicular fluid proteins from the small follicles were 24, 60-65, 79, 110, 140, 160, and > 220 kDa. Meanwhile, the follicular fluid protein from medium and large follicle contained 52, 65, 79, 90, 110, 120, 160, 190 and > 220 kDa. Almost all proteins played important roles in promoting and regulating growth and development of oocytes and ovulation. This finding was an initial tool for in vitro testing and applied biotechnology research. Acknowledgements: The project was funded by a grant from Silpakorn University Research & Development Institute (SURDI) and Faculty of Science, Silpakorn University, Thailand.

Keywords: follicular fluid protein, LC/MS/MS, porcine oocyte, SDS-PAGE, reproductive biology

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Authors: Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević, Lidija R. Jevrić, Stela Jokić

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The subject of this paper is to correlate antibacterial behavior of benzimidazole derivatives with their molecular characteristics using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on the inhibitory activity of benzimidazole derivatives against Staphylococcus aureus. The data were processed by linear least squares (LLS) and artificial neural network (ANN) procedures. The LLS mathematical models have been developed as a calibration models for prediction of the inhibitory activity. The quality of the models was validated by leave one out (LOO) technique and by using external data set. High agreement between experimental and predicted inhibitory acivities indicated the good quality of the derived models. These results are part of the CMST COST Action No. CM1306 "Understanding Movement and Mechanism in Molecular Machines".

Keywords: Antibacterial, benzimidazoles, chemometric, QSAR.

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Authors: Lei Zhu, Nan Li

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Cold stamping has been widely applied in the automotive industry for the mass production of a great range of automotive panels. Predicting the springback to ensure the dimensional accuracy of the cold-stamped components is a critical step. The main approaches for the prediction and compensation of springback in cold stamping include running Finite Element (FE) simulations and conducting experiments, which require forming process expertise and can be time-consuming and expensive for the design of cold stamping tools. Machine learning technologies have been proven and successfully applied in learning complex system behaviours using presentative samples. These technologies exhibit the promising potential to be used as supporting design tools for metal forming technologies. This study, for the first time, presents a novel application of a Convolutional Neural Network (CNN) based surrogate model to predict the springback fields for variable U-shape cold bending geometries. A dataset is created based on the U-shape cold bending geometries and the corresponding FE simulations results. The dataset is then applied to train the CNN surrogate model. The result shows that the surrogate model can achieve near indistinguishable full-field predictions in real-time when compared with the FE simulation results. The application of CNN in efficient springback prediction can be adopted in industrial settings to aid both conceptual and final component designs for designers without having manufacturing knowledge.

Keywords: springback, cold stamping, convolutional neural networks, machine learning

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Authors: Shara Toibayeva, Irbulat Utepbergenov, Lyazzat Issabekova, Aidana Bodesova

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The article discusses the importance of quality assessment as a strategic tool in business and emphasizes the significance of the effectiveness of quality management systems (QMS) for enterprises. The evaluation of these systems takes into account the specificity of quality indicators, the multilevel nature of the system, and the need for optimal selection of the number of indicators and evaluation of the system state, which is critical for making rational management decisions. Methods and models of automated enterprise quality management are proposed, including an intelligent automated quality management system integrated with the Management Information and Control System. These systems make it possible to automate the implementation and support of QMS, increasing the validity, efficiency, and effectiveness of management decisions by automating the functions performed by decision makers and personnel. The paper also emphasizes the use of recurrent neural networks to improve automated quality management. Recurrent neural networks (RNNs) are used to analyze and process sequences of data, which is particularly useful in the context of document quality assessment and non-conformance detection in quality management systems. These networks are able to account for temporal dependencies and complex relationships between different data elements, which improves the accuracy and efficiency of automated decisions. The project was supported by a grant from the Ministry of Education and Science of the Republic of Kazakhstan under the Zhas Galym project No. AR 13268939, dedicated to research and development of digital technologies to ensure consistency of QMS regulatory documents.

Keywords: automated control system, quality management, document structure, formal language

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Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs, and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine-learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient but not the magnitude. A neural network with two hidden layers were then used to learn the coefficient magnitudes along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction

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Authors: T. Wresdiyati, S. Sa’diah, A. Winarto

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Diabetes mellitus (DM) is a metabolic disease that can be indicated by the high level of blood glucose. The objective of this study was to observe the antidiabetic properties of ethanolic extract of Indonesian Swietenia mahagoni Jacq. seed on the profile of pancreatic superoxide dismutase and β-cells in the alloxan- experimental diabetic rats. The Swietenia mahagoni seed was obtained from Leuwiliang-Bogor, Indonesia. Extraction of Swietenia mahagoni was done by using ethanol with maceration methods. A total of 25 male Sprague dawley rats were divided into five groups; (a) negative control group, (b) positive control group (DM), (c) DM group that was treated with Swietenia mahagoni seed extract, (d) DM group that was treated with acarbose, and (e) non-DM group that was treated with Swietenia mahagoni seed extract. The DM groups were induced by alloxan (110 mg/kgBW). The extract was orally administrated to diabetic rats 500 mg/kg/BW/day for 28 days. The extract showed hypoglycemic effect, increased body weight, increased the content of superoxide dismutase in the pancreatic tissue, and delayed the rate of β-cells damage of experimental diabetic rats. These results suggested that the ethanolic extract of Indonesian Swietenia mahagoni Jacq. seed could be proposed as a potential anti-diabetic agent.

Keywords: beta cells, diabetes, hypoglycemic, rat, Swietenia mahagoni

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Authors: Florin Leon, Silvia Curteanu

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The Bacterial Foraging Optimization (BFO) algorithm is inspired by the behavior of bacteria such as Escherichia coli or Myxococcus xanthus when searching for food, more precisely the chemotaxis behavior. Bacteria perceive chemical gradients in the environment, such as nutrients, and also other individual bacteria, and move toward or in the opposite direction to those signals. The application example considered as a case study consists in establishing the dependency between the reaction yield of hydrogels based on polyacrylamide and the working conditions such as time, temperature, monomer, initiator, crosslinking agent and inclusion polymer concentrations, as well as type of the polymer added. This process is modeled with a neural network which is included in an optimization procedure based on BFO. An experimental study of BFO parameters is performed. The results show that the algorithm is quite robust and can obtain good results for diverse combinations of parameter values.

Keywords: bacterial foraging, hydrogels, modeling and optimization, neural networks

Procedia PDF Downloads 153