Search results for: cell morphology prediction

Authors: Gema M. Rodado, Jose M. Olavarrieta

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Hydrogen fuel cell technologies have experienced a great boost in the last decades, significantly increasing the production of these devices for both stationary and portable (mainly automotive) applications; these are influenced by two main factors: environmental pollution and energy shortage. A fuel cell is an electrochemical device that converts chemical energy directly into electricity by using hydrogen and oxygen gases as reactive components and obtaining water and heat as byproducts of the chemical reaction. Fuel cells, specifically those of Proton Exchange Membrane (PEM) technology, are considered an alternative to internal combustion engines, mainly because of the low emissions they produce (almost zero), high efficiency and low operating temperatures (< 373 K). The introduction and use of fuel cells in the automotive market requires the development of standardized and validated procedures to test and evaluate their performance in different environmental conditions including vibrations and freeze-thaw cycles. These situations of vibration and extremely low/high temperatures can affect the physical integrity or even the excellent operation or performance of the fuel cell stack placed in a vehicle in circulation or in different climatic conditions. The main objective of this work is the development and validation of vibration and freeze-thaw cycling test procedures for fuel cell stacks that can be used in a vehicle in order to consolidate their safety, performance, and durability. In this context, different experimental tests were carried out at the facilities of the National Hydrogen Centre (CNH2). The experimental equipment used was: A vibration platform (shaker) for vibration test analysis on fuel cells in three axes directions with different vibration profiles. A walk-in climatic chamber to test the starting, operating, and stopping behavior of fuel cells under defined extreme conditions. A test station designed and developed by the CNH2 to test and characterize PEM fuel cell stacks up to 10 kWe. A 5 kWe PEM fuel cell stack in off-operation mode was used to carry out two independent experimental procedures. On the one hand, the fuel cell was subjected to a sinusoidal vibration test on the shaker in the three axes directions. It was defined by acceleration and amplitudes in the frequency range of 7 to 200 Hz for a total of three hours in each direction. On the other hand, the climatic chamber was used to simulate freeze-thaw cycles by defining a temperature range between +313 K and -243 K with an average relative humidity of 50% and a recommended ramp up and rump down of 1 K/min. The polarization curve and gas leakage rate were determined before and after the vibration and freeze-thaw tests at the fuel cell stack test station to evaluate the robustness of the stack. The results were very similar, which indicates that the tests did not affect the fuel cell stack structure and performance. The proposed procedures were verified and can be used as an initial point to perform other tests with different fuel cells.

Keywords: climatic chamber, freeze-thaw cycles, PEM fuel cell, shaker, vibration tests

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Authors: M. Yusuf Ansari, Asad Abbas

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Proton exchange membrane (PEM) fuel cell is a very efficient and promising energy conversion device. Although Nafion® is considered as benchmark materials for membrane used in PEM fuel cell, it has limitations that restrict its uses. Alternative materials for the membrane is always a challenging field for researchers. Sulfonated poly(ether ether ketone) (SPEEK) is one of the promising material for membrane due to its chemical and mechanical stability and lower cost. In this work, SPEEK is synthesized, and property booster such as silica nanoparticles and polyvinyl alcohol (PVA) are also added to analyse changes in properties such as water uptake, IEC, and conductivity. It has been found that adding PVA support high water uptake and proton conductivity but at large amount of PVA reduces the proton conductivity due to very high water uptake. Adding silica enhances water uptake and proton conductivity.

Keywords: PEM Membrane, sulfonated poly (ether ether ketone) (SPEEK), silica fumes (SiO2), polyvinyl alcohol (PVA)

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Authors: Lin Dong-Yih, Yang S. M., Huang B. W., Lian J. A.

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Super duplex stainless steel has excellent mechanical properties and corrosion resistance. It becomes important structural material as its application has been extended to the fields such as renewable energy and the chemical industry because of its excellent properties. As examples are offshore wind power, solar cell machinery, and pipes in the chemical industry. The mechanical properties and corrosion resistance of super duplex stainless steel can be eliminated by welding due to the precipitation of the hard and brittle σ phase, which is rich of chromium, and molybdenum elements. This paper studies the influence of carbon element on the phase transformation of -ferrite and σ phase in 2507 super duplex stainless steel. The 2507 will be under argon gas protection welded with 316 and 316L extra low carbon stainless steel separately. The microstructural phases of stainless steels before and after welding, in fusion, heat affected zones, and base material will be studied via X-ray, OM, SEM, EPMA i.e. their quantity, size, distribution, and morphology. The influences of diffusion by carbon element will be compared according to the microstructures, hardness, and corrosion tests.

Keywords: complex stainless steel, welding, phase formation, carbon element, sigma phase, delta ferrite

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Authors: Mazaher Yarmohamadi-Vasel, Ali Reza Modarresi-Alama, Sahar Shabzendedara

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Purpose/Objectives: The first purpose was synthesize Poly(N-(sulfophenyl)aniline) nanoflowers (PSANFLs) and Poly(N-(sulfophenyl)aniline) nanofibers/titanium dioxide nanoparticles ((PSANFs/TiO2NPs) by a solid-state mechano-chemical reaction and template-free method and use them in hybrid solar cell. Also, our second aim was to increase the solubility and the processability of conjugated nanomaterials in water through polar functionalized materials. poly[N-(4-sulfophenyl)aniline] is easily soluble in water because of the presence of polar groups of sulfonic acid in the polymer chain. Materials/Methods: Iron (III) chloride hexahydrate (FeCl3∙6H2O) were bought from Merck Millipore Company. Titanium oxide nanoparticles (TiO2, <20 nm, anatase) and Sodium diphenylamine-4-sulfonate (99%) were bought from Sigma-Aldrich Company. Titanium dioxide nanoparticles paste (PST-20T) was prepared from Sharifsolar Co. Conductive glasses coated with indium tin oxide (ITO) were bought from Xinyan Technology Co (China). For the first time we used the solid-state mechano-chemical reaction and template-free method to synthesize Poly(N-(sulfophenyl)aniline) nanoflowers. Moreover, for the first time we used the same technique to synthesize nanocomposite of Poly(N-(sulfophenyl)aniline) nanofibers and titanium dioxide nanoparticles (PSANFs/TiO2NPs) also for the first time this nanocomposite was synthesized. Examining the results of electrochemical calculations energy gap obtained by CV curves and UV–vis spectra demonstrate that PSANFs/TiO2NPs nanocomposite is a p-n type material that can be used in photovoltaic cells. Doctor blade method was used to creat films for three kinds of hybrid solar cells in terms of different patterns like ITO│TiO2NPs│Semiconductor sample│Al. In the following, hybrid photovoltaic cells in bilayer and bulk heterojunction structures were fabricated as ITO│TiO2NPs│PSANFLs│Al and ITO│TiO2NPs│PSANFs /TiO2NPs│Al, respectively. Fourier-transform infrared spectra, field emission scanning electron microscopy (FE-SEM), ultraviolet-visible spectra, cyclic voltammetry (CV) and electrical conductivity were the analysis that used to characterize the synthesized samples. Results and Conclusions: FE-SEM images clearly demonstrate that the morphology of the synthesized samples are nanostructured (nanoflowers and nanofibers). Electrochemical calculations of band gap from CV curves demonstrated that the forbidden band gap of the PSANFLs and PSANFs/TiO2NPs nanocomposite are 2.95 and 2.23 eV, respectively. I–V characteristics of hybrid solar cells and their power conversion efficiency (PCE) under 100 mWcm−2 irradiation (AM 1.5 global conditions) were measured that The PCE of the samples were 0.30 and 0.62%, respectively. At the end, all the results of solar cell analysis were discussed. To sum up, PSANFLs and PSANFLs/TiO2NPs were successfully synthesized by an affordable and straightforward mechanochemical reaction in solid-state under the green condition. The solubility and processability of the synthesized compounds have been improved compared to the previous work. We successfully fabricated hybrid photovoltaic cells of synthesized semiconductor nanostructured polymers and TiO2NPs as different architectures. We believe that the synthesized compounds can open inventive pathways for the development of other Poly(N-(sulfophenyl)aniline based hybrid materials (nanocomposites) proper for preparing new generation solar cells.

Keywords: mechanochemical synthesis, PSANFLs, PSANFs/TiO2NPs, solar cell

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Authors: Amir Hossein Hejazi, Nima Amjady

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In recent years, due to environmental issues traditional energy sources had been replaced by renewable ones. Wind energy as the fastest growing renewable energy shares a considerable percent of energy in power electricity markets. With this fast growth of wind energy worldwide, owners and operators of wind farms, transmission system operators, and energy traders need reliable and secure forecasts of wind energy production. In this paper, a new forecasting strategy is proposed for short-term wind power prediction based on Echo State Networks (ESN). The forecast engine utilizes state-of-the-art training process including dynamical reservoir with high capability to learn complex dynamics of wind power or wind vector signals. The study becomes more interesting by incorporating prediction of wind direction into forecast strategy. The Big Bang-Big Crunch (BB-BC) evolutionary optimization algorithm is adopted for adjusting free parameters of ESN-based forecaster. The proposed method is tested by real-world hourly data to show the efficiency of the forecasting engine for prediction of both wind vector and wind power output of aggregated wind power production.

Keywords: wind power forecasting, echo state network, big bang-big crunch, evolutionary optimization algorithm

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Authors: Amiel Satvedi, Richard Pyne

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Injuries in professional sports occur on a regular basis. Some may be minor, while others can cause huge impact on a player's career and earning potential. In soccer, there is a high risk of players picking up injuries during game time. This research work seeks to help soccer players reduce the risk of getting injured by predicting the likelihood of injury while playing in the near future and then providing recommendations for intervention. The injury prediction tool will use a soccer player's number of minutes played on the field, number of appearances, distance covered and performance data for the current and previous seasons as variables to conduct statistical analysis and provide injury predictive results using a machine learning linear regression model.

Keywords: injury predictor, soccer injury prevention, machine learning in soccer, big data in soccer

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Authors: Rinat Arbel-Goren, Joel Stavans

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Cell-to-cell variations in transcript or protein abundance, called noise, may give rise to phenotypic variability between isogenic cells, enhancing the probability of survival under stress conditions. These variations may be introduced by post-transcriptional regulatory processes such as non-coding, small RNAs stoichiometric degradation of target transcripts in bacteria. We study the iron homeostasis network in Escherichia coli, in which the RyhB small RNA regulates the expression of various targets as a model system. Using fluorescence reporter genes to detect protein levels and single-molecule fluorescence in situ hybridization to monitor transcripts levels in individual cells, allows us to compare noise at both transcript and protein levels. The experimental results and computer simulations show that extrinsic noise buffers through a feed-forward loop configuration the increase in variability introduced at the transcript level by iron deprivation, illuminating the important role that extrinsic noise plays during stress. Surprisingly, extrinsic noise also decouples of fluctuations of two different targets, in spite of RyhB being a common upstream factor degrading both. Thus, phenotypic variability increases under stress conditions by the decoupling of target fluctuations in the same cell rather than by increasing the noise of each. We also present preliminary results on the adaptation of cells to prolonged iron deprivation in order to shed light on the evolutionary role of post-transcriptional downregulation by small RNAs.

Keywords: cell-to-cell variability, Escherichia coli, noise, single-molecule fluorescence in situ hybridization (smFISH), transcript

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Authors: A. W. Zularisam, Sveta Thakur, Lakhveer Singh, Mimi Sakinah Abdul Munaim

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Clostridium sp. LS2 was immobilised by entrapment in polyethylene glycol (PEG) gel beads to improve the biohydrogen production rate from palm oil mill effluent (POME). We sought to explore and optimise the hydrogen production capability of the immobilised cells by studying the conditions for cell immobilisation, including PEG concentration, cell loading and curing times, as well as the effects of temperature and K2HPO4 (500–2000 mg/L), NiCl2 (0.1–5.0 mg/L), FeCl2 (100–400 mg/L) MgSO4 (50–200 mg/L) concentrations on hydrogen production rate. The results showed that by optimising the PEG concentration (10% w/v), initial biomass (2.2 g dry weight), curing time (80 min) and temperature (37 °C), as well as the concentrations of K2HPO4 (2000 mg/L), NiCl2 (1 mg/L), FeCl2 (300 mg/L) and MgSO4 (100 mg/L), a maximum hydrogen production rate of 7.3 L/L-POME/day and a yield of 0.31 L H2/g chemical oxygen demand were obtained during continuous operation. We believe that this process may be potentially expanded for sustained and large-scale hydrogen production.

Keywords: hydrogen, polyethylene glycol, immobilised cell, fermentation, palm oil mill effluent

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Authors: Venoos Iman, Suzita Mohd Noor, Syam Mohan, Mohamad Ibrahim Noordin

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Girinimbine, a carbazole alkaloid was isolated from the stem bark and root of Murraya koenigii and its structure and purity was identified by HPLC and LC-MS. Here we report that Girinimbine strongly inhibit angiogenesis activity both in vitro and in vivo. MTT result showed that girinimbine inhibits cell proliferation of the HUVECS cell line in vitro. Result of endothelial cell invasion, migration, tube formation and wound healing assays also demonstrated significant time and does dependent inhibition by girinimbine. Moreover, girinibine mediates its anti-angiogenic activity through up- and down-regulation of angiogenic and anti-aniogenic proteins. Furthermore, anti-angiogenic potential of girinimbine was evidenced in vivo on zebrafish model. Girinimbine inhibited neo-vessels formation in zebrafish embryos during 24 hours exposure time. Together, these results demonstrated for the first time that girinimbine could effectively suppress angiogenesis and strongly suggest that it might be a novel angiogenesis inhibitor.

Keywords: anti-angiogenic, carbazole alkaloid, girinimbine, zebrafish

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Authors: Suman Chaudhary, Rupinder K. Kanwar, Jagat R. Kanwar

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Azadirachta indica, also known as Neem belonging to the mahogany family is actively gaining interest in the era of modern day medicine due to its extensive applications in homeopathic medicine such as Ayurveda and Unani. More than 140 phytochemicals have been extracted from neem leaves, seed, bark and flowers for agro-medicinal applications. Among the various components, neem leaf protein (NLP) is currently the most investigated active ingredient, due to its immunomodulatory activities against tumor growth. However, these therapeutic ingredients of neem are susceptible to degradation and cannot withstand the drastic pH changes under physiological environment, and therefore, there is an urgent need of an alternative strategy such as a nano-delivery system to exploit its medicinal benefits. This study hypothesizes that guar gum (GG) derived biodegradable nano-carrier based encapsulation of NLP will improve its stability, specificity and sensitivity, thus facilitating targeted anti-cancer therapeutics. GG is a galactomannan derived from the endosperm of the guar beans seeds. Synthesis of guar nanocapsules (NCs) was performed using nanoprecipitation technique where the GG was encapsulated with NLP. Preliminary experiments conducted to characterize the NCs confirmed spherical morphology with a narrow size distribution of 30-40 nm. Differential scanning colorimetric analysis (DSC) validated the stability of these NCs even at a temperature range of 50-60°C which was well within the physiological and storage conditions. Thermogravimetric (TGA) analysis indicated high decomposition temperature of these NCs ranging upto 350°C. Additionally, Fourier Transform Infrared spectroscopy (FTIR) and the SDS-PAGE data acquired confirmed the successful encapsulation of NLP in the NCs. The anti-cancerous therapeutic property of this NC was tested on colon cancer cells (caco-2) as they are one of the most prevalent form of cancer. These NCs (both NLP loaded and void) were also tested on human intestinal epithelial cells (FHs 74) cells to evaluate their effect on normal cells. Cytotoxicity evaluation of the NCs in the cell lines confirmed that the IC50 for NLP in FHs 74 cells was ~2 fold higher than in caco-2 cells, indicating that this nanoformulation system possessed biocompatible anti-cancerous properties Immunoconfocal microscopy analysis confirmed the time dependent internalization of the NCs within 6h. Recent findings performed using Annexin V and PI staining indicated a significant increase (p ≤ 0.001) in the early and late apoptotic cell population when treated with the NCs signifying the role of NLP in inducing apoptosis in caco-2 cells. This was further validated using Western blot, Polymerase chain reaction (PCR) and Fluorescence activated cell sorter (FACS) aided protein expressional analysis which presented a downregulation of survivin, an anti-apoptotic cell marker and upregulation of Bax/Bcl-2 ratio (pro-apoptotic indicator). Further, both the NLP NC and unencapsulated NLP treatment destabilized the mitochondrial membrane potential subsequently facilitating the release of the pro-apoptotic caspase cascade initiator, cytochrome-c. Future studies will be focused towards granting specificity to these NCs towards cancer cells, along with a comprehensive analysis of the anti-cancer potential of this naturally occurring compound in different cancer and in vivo animal models, will validate the clinical application of this unprecedented protein therapeutic.

Keywords: anti-tumor, guar gum, nanocapsules, neem leaf protein

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Authors: Li Yang, Yang Song, Martin Y. M. Chiang

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Objective: To experimentally substantiate the micromechanical compatibility between cell and scaffold, in the regenerative medicine approach for restoring bone volume, is essential for phenotypic transitions Methods: Through nanotechnology and electrospinning process, nanofibrous scaffolds were fabricated to host dental follicle stem cells (DFSCs). Blends (50:50) of polycaprolactone (PCL) and silk fibroin (SF), mixed with various content of cellulose nanocrystals (CNC, up to 5% in weight), were electrospun to prepare nanofibrous scaffolds with heterogeneous microstructure in terms of fiber size. Colloidal probe atomic force microscopy (AFM) and conventional uniaxial tensile tests measured the scaffold stiffness at the micro-and macro-scale, respectively. The cell elastic modulus and cell-scaffold adhesive interaction (i.e., a chemical function) were examined through single-cell force spectroscopy using AFM. The quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to determine if the mechanotransduction signal (i.e., Yap1, Wwr2, Rac1, MAPK8, Ptk2 and Wnt5a) is upregulated by the scaffold stiffness at the micro-scale (cellular scale). Results: The presence of CNC produces fibrous scaffolds with a bimodal distribution of fiber diameter. This structural heterogeneity, which is CNC-composition dependent, remarkably modulates the mechanical functionality of scaffolds at microscale and macroscale simultaneously, but not the chemical functionality (i.e., only a single material property is varied). In in vitro tests, the osteogenic differentiation and gene expression associated with mechano-sensitive cell markers correlate to the degree of micromechanical compatibility between DFSCs and the scaffold. Conclusion: Cells require compliant scaffolds to encourage energetically favorable interactions for mechanotransduction, which are converted into changes in cellular biochemistry to direct the phenotypic evolution. The micromechanical compatibility is indeed important to the efficacy of regenerative medicine.

Keywords: phenotype transition, scaffold stiffness, electrospinning, cellulose nanocrystals, single-cell force spectroscopy

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Authors: Muhammad Awais Afzal, Lorena Tuchscherr De Hauschopp, Christian Hübner

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Introduction: Autophagy is an evolutionarily conserved lysosome-dependent degradation pathway, which can be induced by extrinsic and intrinsic stressors in living systems to adapt to fluctuating environmental conditions. In the context of inflammatory stress, autophagy contributes to the elimination of invading pathogens, the regulation of innate and adaptive immune mechanisms, and regulation of inflammasome activity as well as tissue damage repair. Lysosomes can be recycled from autolysosomes by the process of autophagic lysosome reformation (ALR), which depends on the presence of several proteins including Spatacsin. Thus ALR contributes to the replenishment of lysosomes that are available for fusion with autophagosomes in situations of increased autophagic turnover, e.g., during bacterial infections, inflammatory stress or sepsis. Objectives: We aimed to assess whether ALR plays a role for cell survival in an in-vitro bacterial infection model. Methods: Mouse embryonic fibroblasts (MEFs) were isolated from wild-type mice and Spatacsin (Spg11-/-) knockout mice. Wild-type MEFs and Spg11-/- MEFs were infected with Staphylococcus aureus (multiplication of infection (MOI) used was 10). After 8 and 16 hours of infection, cell viability was assessed on BD flow cytometer through propidium iodide intake. Bacterial intake by cells was also calculated by plating cell lysates on blood agar plates. Results: in-vitro infection of MEFs with Staphylococcus aureus showed a marked decrease of cell viability in ALR deficient Spatacsin knockout (Spg11-/-) MEFs after 16 hours of infection as compared to wild-type MEFs (n=3 independent experiments; p < 0.0001) although no difference was observed for bacterial intake by both genotypes. Conclusion: Suggesting that ALR is important for the defense of invading pathogens e.g. S. aureus, we observed a marked increase of cell death in an in-vitro infection model in cells with compromised ALR.

Keywords: autophagy, autophagic lysosome reformation, bacterial infections, Staphylococcus aureus

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Authors: Marwa M. Abu-Serie, Marwa M. Eltarahony

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The search for reliable, effective, and safe nanoparticles (NPs) as a treatment for cancer is a pressing priority. In this study, Cu-NPs were fabricated by Streptomyces cyaneofuscatus through simultaneous bioreduction strategy of copper nitrate salt. The as-prepared Cu-NPs subjected to structural analysis; energy-dispersive X-ray spectroscopy, elemental mapping, X-ray diffraction, transmission electron microscopy, and ζ-potential. These biological synthesized Cu-NPs were mixed with disulfiram (DS), forming a nanocomplex of Cu-DS with a size of ~135 nm. The prepared nanocomplex (nanoCu-DS) exhibited higher anticancer activity than that of free complex of DS-Cu, Cu-NPs, and DS alone. This was illustrated by the lowest IC50 of nanoCu-DS (< 4 µM) against human breast and liver cancer cell lines comparing with DS-Cu, Cu-NPs, and DS (~8, 22.98-33.51 and 11.95-14.86, respectively). Moreover, flow cytometric analysis confirmed that higher apoptosis percentage range of nanoCu-DS-treated in MDA-MB 231, MCF-7, Huh-7, and HepG-2 cells (51.24-65.28%) than free complex of Cu-DS ( < 4.5%). Regarding inhibition potency of liver and breast cancer cell migration, no significant difference was recorded between free and nanocomplex. Furthermore, nanoCu-DS suppressed gene expression of β-catenine, Akt, and NF-κB and upregulated p53 expression (> 3, >15, > 5 and ≥ 3 folds, respectively) more efficiently than free complex (all ~ 1 fold) in MDA-MB 231 and Huh-7 cells. Our finding proved this prepared nano complex has a powerful anticancer activity relative to free complex, thereby offering a promising cancer treatment.

Keywords: biologically prepared Cu-NPs, breast cancer cell lines, liver cancer cell lines, nanoCu- disulfiram

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Authors: Damião Sousa, Hasan Turkez, Ozlem Tozlu, Tamires Lima

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Glioblastoma (GBM) is an aggressive cancer from the brain and with high prevalence and significant morbimortality. Therefore, it is necessary to investigate new therapeutic options against this pathology. Thus, the purpose of this study was to evaluate the antitumor activity from Mentha crispa essential oil (MCEO), its major constituent rotundifolone (ROT) and a series of six analogues on human U87MG glioblastoma cell line. The antitumor effects of the compounds on human U87MG-GBM cell line were assessed using in vitro cell viability assays. In addition, biosafety tests were performed on cultured human blood cells. The data show that MCEO, 1,2-perillaldehyde epoxide (EPER1) and perillaldehyde (PALD) were the most cytotoxic compounds against the U87MG cells, with IC50 values of 16.263, 15.087 and 14.888 μg/mL, respectively. The treatment with MCEO, EPER1 and PALD did not lead to damage in blood cells. These chemical analogues may be useful as prototypes for development of novel antitumor drugs due to their promising activities and toxicological safety.

Keywords: antitumor activity, cancer, natural products, terpenes

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Authors: Pintusorn Hansakul, Ruchilak Rattarom, Arunporn Itharat

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Background: Benjakul, a Thai traditional herbal formulation, comprises of five plants: Piper chaba, Piper sarmentosum, Piper interruptum, Plumbago indica, and Zingiber officinale. It has been widely used to treat cancer patients in the context of folk medicine in Thailand. This study aimed to investigate the cytotoxic effect of the ethanol extract of Benjakul against three non-small cell lung cancer (NSCLC) cell lines (NCI-H226, A549, COR-L23), small cell lung cancer (SCLC) cell line NCI-H1688 and normal lung fibroblast cell line MRC-5. The study further examined the molecular mechanisms underlying its cytotoxicity via induction of apoptosis in NCI-H226 cells. Methods: The cytotoxic effect of Benjakul was determined by SRB assay. The effect of Benjakul on cell cycle distribution was assessed by flow cytometric analysis. The apoptotic effects of Benjakul were determined by sub-G1 quantitation and Annexin V-FITC/PI flow cytometric analyses as well as by changes in caspase-3 activity. Results: Benjakul exerted potent cytotoxicity on NCI-H226 and A549 cells but lower cytotoxicity on COR-L23 and NCI-H1688 cells without any cytotoxic effect on normal cells. Molecular studies showed that Benjakul extract induced G2/M phase arrest in human NCI-H226 cells in a dose-dependent manner. The highest concentration of Benjakul (150 μg/ml) led to the highest increase in the G2/M population at 12 h, followed by the highest increase in the sub-G1 population (apoptotic cells) at 60 h. Benjakul extract also induced early apoptosis (AnnexinV +/PI−) in NCI-H226 cells in a dose- and time- dependent manner. Moreover, treatment with 150 μg/ml Benjakul extract for 36 h markedly increased caspase-3 activity by 3.5-fold, and pretreatment with the general caspase inhibitor z-VAD-fmk completely abolished such activity. Conclusions: This study reveals for the first time the regulation of apoptosis in human lung cancer NCI-H226 cells through caspase-dependent mechanism by Benjakul extract.

Keywords: apoptosis, Benjakul, caspase activation, cytotoxicity

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Authors: David Oluigbo, Erik Hemberg, Nathan Shwatal, Wenqi Ding, Yin Yuan, Susanna Mierau

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Introduction: Calcium imaging is an established technique in neuroscience research for detecting activity in neural networks. Bursts of action potentials in neurons lead to transient increases in intracellular calcium visualized with fluorescent indicators. Manual identification of cell bodies and their contours by experts typically takes 10-20 minutes per calcium imaging recording. Our aim, therefore, was to design an automated pipeline to facilitate and optimize calcium imaging data analysis. Our pipeline aims to accelerate cell body and contour identification and production of graphical representations reflecting changes in neuronal calcium-based fluorescence. Methods: We created a Python-based pipeline that uses OpenCV (a computer vision Python package) to accurately (1) detect neuron contours, (2) extract the mean fluorescence within the contour, and (3) identify transient changes in the fluorescence due to neuronal activity. The pipeline consisted of 3 Python scripts that could both be easily accessed through a Python Jupyter notebook. In total, we tested this pipeline on ten separate calcium imaging datasets from murine dissociate cortical cultures. We next compared our automated pipeline outputs with the outputs of manually labeled data for neuronal cell location and corresponding fluorescent times series generated by an expert neuroscientist. Results: Our results show that our automated pipeline efficiently pinpoints neuronal cell body location and neuronal contours and provides a graphical representation of neural network metrics accurately reflecting changes in neuronal calcium-based fluorescence. The pipeline detected the shape, area, and location of most neuronal cell body contours by using binary thresholding and grayscale image conversion to allow computer vision to better distinguish between cells and non-cells. Its results were also comparable to manually analyzed results but with significantly reduced result acquisition times of 2-5 minutes per recording versus 10-20 minutes per recording. Based on these findings, our next step is to precisely measure the specificity and sensitivity of the automated pipeline’s cell body and contour detection to extract more robust neural network metrics and dynamics. Conclusion: Our Python-based pipeline performed automated computer vision-based analysis of calcium image recordings from neuronal cell bodies in neuronal cell cultures. Our new goal is to improve cell body and contour detection to produce more robust, accurate neural network metrics and dynamic graphs.

Keywords: calcium imaging, computer vision, neural activity, neural networks

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

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The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: big data, machine learning, smart city, social cost, transportation network

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Authors: S. Mahdavi, S.R. Allahkaram

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Electrodeposition is a simple and economic technique for precision coating of different shaped substrates with pure metal, alloy or composite films. Dc electrodeposition was used to produce Cr, Co-Cr and Co-Cr/TiO2 nano-composite coatings from Cr(III) based electrolytes onto 316L SS substrates. The effects of TiO2 nano-particles concentration on co-deposition of these particles along with Cr content and microhardness of the coatings were investigated. Morphology of the Cr, Co-Cr and Co-Cr/TiO2 coatings besides their tribological behavior were studied. The results showed that increment of TiO2 nano-particles concentration from 0 to 30 g L-1 in the bath increased their co-deposition and Cr content of the coatings from 0 to 3.5 wt.% and from 23.7 to 31.2 wt.%, respectively. Microhardness of Cr coating was about 920 Hv which was higher than Co-Cr and even Co-Cr/TiO2 films. Microhardness of Co-Cr and Co-Cr/TiO2 coatings were improved by increasing their Cr and TiO2 content. All the coatings had nodular morphology and contained microcracks. Nodules sizes and the number of microcracks in the alloy and composite coatings were lower than the Cr film. Wear results revealed that the Co-Cr/TiO2 coating had the lowest wear loss between all the samples, while the Cr film had the worst wear resistance.

Keywords: Co-Cr alloy, electrodeposition, nano-composite, tribological behavior, trivalent chromium

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Authors: E. A. Alaswad, H. M. Choudhry, F. Z. Filimban

Abstract:

Sickle Cell Anemia (SCA) is one type of blood diseases related to autosomal disorder. The sickle shaped red blood cells are the main cause of many problems in the blood vessels and capillaries. Aerva Javanica (J) and Ficus Palmata (P) are medicinal plants that have many popular uses and have been proved their efficacy. The aim of this study was to assess the antioxidants activity and the antisickling effect of J and P extractions. The period of this study, air-dried leaves of J, and P plants were ground and the active components were extracted by maceration in water (W) and methanol (M) as solvents. The antioxidants activity of JW, PW, JM, and PM were assessed by way of the radical scavenging method using 2,2-diphenyl-1-picrylhydrazyl (DPPH). To determine the antisickling effect of J and P extracts. 20 samples were collected from sickle cell anemia patients. Different concentrations of J and P extracts (200 and 110 μg/mL) were added on the sample and incubated. A drop of each sample was examined with light microscope. Normal and sickled RBCs were calculated and expressed as the percent of sickling. The stabilization effect of the extracts was measured by the osmotic fragility test for erythrocytes. The finding suggests as estimated by DPPH method, all the extracts showed an antioxidant activity with a significant inhibition of the DPPH radicals. PM has the least IC50% with 71.49 μg/ml while JM was the most with 408.49 μg/ml. Sickle cells treated with extracts at different concentrations significantly reduced the percentage of sickling compering to control samples. However, JM 200 μg/mL give the highest anti-sickling affect with 17.4% of sickling compared to control 67.5 of sickling while PM at 200 μg/mL showed the highest membrane cell stability. In a conclusion, the results showed that J and P extracts have antisickling effects. Therefore, the Aerva javanica and Ficus palmata may have a role in SCA management and a good impact on the patient's lives.

Keywords: Aerva javanica, antioxidant, antisickling, Ficus palmata, sickle cell anemia

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Authors: A. A. Balkhi, G. M. Mir, Javid A. Sheikh

Abstract:

To cater the demands of increasing traffic with new applications the cellular mobile networks face new changes in deployment in infrastructure for making cellular networks heterogeneous. To reduce overhead processing the densely deployed cells require smart behavior with self-organizing capabilities with high adaptation to the neighborhood. We propose self-organization of unused resources usually excessive unused channels of neighbouring cells with densely populated cells to reduce handover failure rates. The neighboring cells share unused channels after fulfilling some conditional candidature criterion using threshold values so that they are not suffered themselves for starvation of channels in case of any abrupt change in traffic pattern. The cells are classified as ‘red’, ‘yellow’, or ‘green’, as per the available channels in cell which is governed by traffic pattern and thresholds. To combat the deficiency of channels in red cell, migration of unused channels from under-loaded cells, hierarchically from the qualified candidate neighboring cells is explored. The resources are returned back when the congested cell is capable of self-contained traffic management. In either of the cases conditional sharing of resources is executed for enhanced traffic management so that User Equipment (UE) is provided uninterrupted services with high Quality of Service (QoS). The fuzzy logic-based simulation results show that the proposed algorithm is efficiently in coincidence with improved successful handoffs.

Keywords: candidate cell, channel sharing, fuzzy logic, handover, small cells

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Authors: Shenghu Feng, Jun Cheng

Abstract:

The molecular mechanism underlying nonalcoholic fatty liver disease (NAFLD) progression to hepatocellular carcinoma (HCC) remains unknown. In this study, immunohistochemistry staining result showed that NS5ABP37 protein expression decreased as with increasing degree of HCC malignancy. In agreement, NS5ABP37 protein overexpression significantly suppressed cell proliferation, caused G1/S cell cycle arrest, and induced apoptosis by increasing caspase-3/7 activity and cleaved caspase-3 levels. In addition, NS5ABP37 overexpression resulted in decreased intracellular TG and TC contents, with level reduction in SREBPs and downstream effectors. Furthermore, NS5ABP37 overexpression decreased SREBP1c and SREBP2 levels by inducing their respective promoters. Finally, ROS levels and ER-stress were both induced by NS5ABP37 overexpression. These findings together demonstrate that NS5ABP37 inhibits cancer cell proliferation and promotes apoptosis, by altering SREBP-dependent lipogenesis and cholesterogenesis in HepG2 cells and inducing oxidative stress and ER stress.

Keywords: NS5ABP37, liver cancer, lipid metabolism, oxidative stress, ER stress

Procedia PDF Downloads 154

Authors: Mohab Magdy Mostafa Mohamed

Abstract:

The objective of this paper is to introduce a vertical handover (VHO) algorithm between wireless LANs (WLANs) and LTE mobile networks. The proposed algorithm is based on the fuzzy control theory and takes into consideration power level, subscriber velocity, and target cell load instead of only power level in traditional algorithms. Simulation results show that network performance in terms of number of handovers and handover occurrence distance is improved.

Keywords: vertical handover, fuzzy control theory, power level, speed, target cell load

Procedia PDF Downloads 353

Authors: Hui Zhang, Sherif Beskhyroun

Abstract:

Structural Health monitoring systems (SHM) are commonly used to identify and assess structural damage. In terms of damage detection, SHM needs to periodically collect data from sensors placed in the structure as damage-sensitive features. This includes abnormal changes caused by the strain field and abnormal symptoms of the structure, such as damage and deterioration. Currently, deploying sensors on a large scale in a building structure is a challenge. In this study, a highly stretchable strain sensors are used in this study to collect data sets of strain generated on the surface of full-size reinforced concrete (RC) frames under extreme cyclic load application. This sensing sheet can be switched freely between the test bending strain and the axial strain to achieve two different configurations. On this basis, the deep neural network prediction model of the frame beam and frame column is established. The training results show that the method can accurately predict the strain value and has good generalization ability. The two deep neural network prediction models will also be deployed in the SHM system in the future as part of the intelligent strain sensor system.

Keywords: strain sensing sheets, deep neural networks, strain measurement, SHM system, RC frames

Procedia PDF Downloads 99

Authors: Ugwuowo Leonard Chidi, Oparaji Chetachukwu Jecinta., Ogidi Chibuzor Agafenachukwu, Onuoha Rebecca Obianuju

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This experiment was conducted to investigate the growth performance, haematology and serum biochemistry indices of broiler birds fed diets containing Neem leaf meal. A total of 96 unsexed day-old broiler birds were allocated to four treatments of T1, T2, T3 and T4 and replicated three times with eight birds per replicate in a Completely Randomized Design. The treatments were diets containing 2.0, 4.0, 6.0 and 8.0% Neem leaf meal respectively. Growth performances, packed cell volume, red blood cell count, haemoglobin, white blood cell count, lymphocytes, mean corpuscular volume, mean corpuscular haemoglobin concentration, platelet count, aspartate amino transaminase, alanine amino transaminase, alkaline phosphate, cholesterol, albumin, globulin, urea, glucose, total protein and creatinine were evaluated. Results showed that there were no significant differences (P>0.05) in all the growth performance parameters among the treatments. The results of the experiment showed that there were significant differences (P<0.05) in all the heamatological and serum biochemistry parameters at finisher phases. Mean corpuscular volume, white blood cell count, lymphocytes, red blood cell count, haemoglobin, platelet count, creatinine and triglyceride increased and were highest in treatment two while treatment four had the least values in mean corpuscular volume, urea, white blood cell, haemoglobin and triglyceride. This implies that the levels of inclusion of Neem leaf meal in this experiment did not affect the growth performance of the broiler chicks but the haematological and serum biochemistry indices were affected. Treatment two with a 4% inclusion level of Neem leaf meal has shown the capacity to replace vaccines and antibiotics in broilers due to the positive effects it had on both the haematological and serum biochemistry.

Keywords: leaf meal, broiler, Aziradicta indica, serum biochemistry, haematology

Procedia PDF Downloads 76

Authors: Tafadzwa Makonese, Harold Annegarn, Patricia Forbes

Abstract:

Residential coal combustion is one of the largest sources of carbonaceous aerosols in the Highveld region of South Africa, significantly affecting the local and regional climate. In this study, we investigated single coal burning particles emitted when using different fire-ignition techniques (top-lit up-draft vs bottom-lit up-draft) and air ventilation rates (defined by the number of air holes above and below the fire grate) in selected informal braziers. Aerosol samples were collected on nucleopore filters at the SeTAR Centre Laboratory, University of Johannesburg. Individual particles (~700) were investigated using a scanning electron microscope equipped with an energy-dispersive X-ray spectroscopy (EDS). Two distinct forms of spherical organic particles (SOPs) were identified, one less oxidized than the other. The particles were further classified into "electronically" dark and bright, according to China et al. [2014]. EDS analysis showed that 70% of the dark spherical organic particles balls had higher (~60%) relative oxygen content than in the bright SOPs. We quantify the morphology of spherical organic particles and classify them into four categories: ~50% are bare single particles; ~35% particles are aggregated and form diffusion accretion chains; 10% have inclusions; and 5% are deformed due to impaction on filter material during sampling. We conclude that there are two distinct kinds of coal burning spherical organic particles and that dark SOPs are less volatile than bright SOPs. We also show that these spherical organic particles are similar in nature and characteristics to tar balls observed in biomass combustion, and that they have the potential to absorb sunlight thereby affecting the earth’s radiative budget and climate. This study provides insights on the mixing states, morphology, and possible formation mechanisms of these organic particles from residential coal combustion in informal stoves.

Keywords: spherical organic particles, residential coal combustion, fixed-bed, aerosols, morphology, stoves

Procedia PDF Downloads 466

Authors: W. Benstaali, A. Belasri

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In this work we study a planar lamp filled with neon-xenon gas. We use a one-dimensional particle in a cell with Monte Carlo simulation (PIC-MCC) to investigate the effect xenon concentration on the energy deposited on excitation, ionization and ions. A Xe-Ne discharge is studied for a gas pressure of 400 torr. The results show an efficient Xe20-Ne mixture with an applied voltage of 1.2KV; the xenon excitation energy represents 65% form total energy dissipated in the discharge. We have also studied electrical properties and the energy balance a discharge for Xe50-Ne which needs a voltage of 2kv; the xenon energy is than more important.

Keywords: dielectric barrier discharge, efficiency, excitation, lamps

Procedia PDF Downloads 167

Authors: Ibtissem El Ouar, Cornelia Braicu, Dalila Naimi, Alexendru Irimie, Ioana Berindan-Neagoe

Abstract:

Helix aspersa, 'the garden snail' is a big land snail widely found in the Mediterranean countries, it is one of the most consumed species in the west of Algeria. It is commonly used in zootherapy to purify blood and to treat cardiovascular diseases and liver problems. The aim of our study is to investigate, the antitumor activity of an aqueous extract from Helix aspersa prepared by the traditional method on Hs578T; a triple negative breast cancer cell line. Firstly, the free radical scavenging activity of H. aspersa extract was assessed by measuring its capability for scavenging the radical 2,2-diphenyl-1-picrylhydrazyl (DPPH), as well as its ability to reduce ferric ion by the FRAP assay (ferric reducing ability). The cytotoxic effect of H. aspersa extract against Hs578T cells was evaluated by the MTT test (3-(4,5- dimethylthiazl-2-yl)-2,5- diphenyltetrazolium bromide)) while the mode of cell death induced by the extract has been determined by fluorescence microscopy using acredine orange/ethidium bromide (AO/EB) probe. The level of TNFα has also measured in cell medium by ELISA method. The results suggest that H. aspersa extract has an antioxidant activity, especially at high concentrations, it can reduce DPPH radical and ferric ion. The MTT test shows that H. aspersa extract has a great cytotoxic effect against breast cancer cells, the IC50 value correspond of the dilution 1% of the crude extract. Moreover, the AO/EB staining shows that TNFα induced necrosis is the main form of cell death induced by the extract. In conclusion, the present study may open new perspectives in the search for new natural anticancer drugs.

Keywords: breast cancer, Helix aspersa, Hs578t cell line, necrosis

Procedia PDF Downloads 422

Authors: Pedro Paulo Galindo Francisco, Eli Dhadad Junior

Abstract:

This study addresses the Meese-Rogoff Puzzle by introducing the latest machine learning techniques as alternatives for predicting the exchange rates. Using RMSE as a comparison metric, Meese and Rogoff discovered that economic models are unable to outperform the random walk model as short-term exchange rate predictors. Decades after this study, no statistical prediction technique has proven effective in overcoming this obstacle; although there were positive results, they did not apply to all currencies and defined periods. Recent advancements in artificial intelligence technologies have paved the way for a new approach to exchange rate prediction. Leveraging this technology, we applied five machine learning techniques to attempt to overcome the Meese-Rogoff puzzle. We considered daily data for the real, yen, British pound, euro, and Chinese yuan against the US dollar over a time horizon from 2010 to 2023. Our results showed that none of the presented techniques were able to produce an RMSE lower than the Random Walk model. However, the performance of some models, particularly LSTM and N-BEATS were able to outperform the ARIMA model. The results also suggest that machine learning models have untapped potential and could represent an effective long-term possibility for overcoming the Meese-Rogoff puzzle.

Keywords: exchage rate, prediction, machine learning, deep learning

Procedia PDF Downloads 32

Authors: Rajalaxmi N., Padma Bhat, Pooja Garag, Pooja N. M., V. S. Hombalimath

Abstract:

Microbial fuel cell (MFC) is the advancement of science that aims at utilizing the oxidizing potential of bacteria for wastewater treatment and production of bio-hydrogen and bio-electricity. Salt-bridge is the economic alternative to highly priced proton-exchange membrane in the construction of a microbial fuel cell. This paper studies the electricity generating capacity of E.coli and Clostridium sporogenes in microbial fuel cells (MFCs). Unlike most of MFC research, this targets the long term goals of renewable energy production and wastewater treatment. In present study the feasibility and potential of bioelectricity production from different wastewater was observed. Different wastewater was primarily treated which were confirmed by the COD tests which showed reduction of COD. We observe that the electricity production of MFCs decreases almost linearly after 120 hrs. The sewage wastewater containing Clostridium sporogenes showed bioelectricity production up to 188mV with COD removal of 60.52%. Sewage wastewater efficiently produces bioelectricity and this also helpful to reduce wastewater pollution load.

Keywords: microbial fuel cell, bioelectricity, wastewater, salt bridge, COD

Procedia PDF Downloads 537

Authors: Danilo López, Johana Hernández, Edwin Rivas

Abstract:

The use of the Multilayer Perceptron Neural Networks (MLPNN) technique is presented to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data through the primary wireless network. To validate the results, sequences of occupancy data of channel were generated by simulation. The results show that the prediction percentage is greater than 60% in some of the tests carried out.

Keywords: cognitive radio, neural network, prediction, primary user

Procedia PDF Downloads 371