Search results for: cell morphology prediction

Authors: N. Zoghi, Laleh Maleknia , M. E. Olya

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The nano-Cu particles were produced on cotton fabric substrate by ink-jet printing technology with water-soluble ink, which was based on copper. The surface tension and viscosity of the prepared inks were evaluated. The ink-jet printing process was repeated 1, 3, and 5 times in order to evaluate variations in the optical properties by changing thickness of printed film. Following initial drying of the printed film, the samples were annealed at different temperatures (150 °C, 200 °C and 250 °C) to determine the optimum temperature for the parameters set out in this experiment. The prepared nano-Cu particles were characterized by XRD and UV spectroscopy. The appearance of printed image and the nano-Cu particles morphology were observed by SEM. The results demonstrated that the ink-jet printing technology can be used to produce nano-particles on the cotton fabrics surface.

Keywords: ink-jet printing, nano-cu, fabric ink, in situ production, cotton fabric, water-soluble ink, morphology

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Authors: M. Sunitha, B. Nithyavani, Mathew Yohannan, S. Thiruvieni Balajji, M. A. Rathi, C. Arul Raj, P. Ragavendran, V. K. Gopalkrishnan

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Establishment of an early and reliable biomarker for ovarian carcinogenesis whose expression can be monitored through noninvasive techniques will enable early diagnosis of cancer. Carbonic anhydrases (CA) isozymes IX and XII have been suggested to play a role in oncogenic processes. In von Hippel-Lindau (VHL)-defective tumors, the cell surface transmembrane carbonic anhydrase (CA) CA XI and CA XII genes are overexpressed because of the absence of pVHL. These enzymes are involved in causing a hypoxia condition, thereby providing an environment for metastasis. Aberrant expression of the facilitative glucose transporter GLUT I is found in a wide spectrum of epithelial malignancies. Studying the mRNA expression of CA IX, CA XII and Glut I isozymes in ovarian cancer cell lines (OAW-42 and PA-1) revealed the expression of these hypoxia genes. Immunohistochemical staining of carbonic anhydrases was also performed in 40 ovarian cancer tissues. CA IX and CA XII were expressed at 540 bp and 520 bp in OAW42, PA1 in ovarian cancer cell lines. GLUT-1 was expressed at 325bp in OAW 42, PA1 genes in ovarian cancer cell lines. Immunohistochemistry revealed high to moderate levels of expression of these enzymes. The immuostaining was seen predominantly on the cell surface membrane. The study concluded that these genes CA IX, CA XII and Glut I are expressed under hypoxic condition in tumor cells. From the present results expression of CA IX, XII and Glut I may represent potential targets in ovarian cancer therapy.

Keywords: ovarian cancer, carbonic anhydrase IX, XII, Glut I, tumor markers

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Authors: Yuwaratu Syafira, Wahyu K. Y. Putra, Kusharisupeni Djokosujono

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Background/Objective: Body Mass Index (BMI) serves various purposes, including measuring the prevalence of obesity in a population, and also in formulating a patient’s diet at a hospital, and can be calculated with the equation = body weight (kg)/body height (m)². However, the BMI of an individual with difficulties in carrying their weight or standing up straight can not necessarily be measured. The aim of this study was to form a prediction model for the BMI of young adult students of Public Health Faculty of University of Indonesia. Subject/Method: This study used a cross sectional design, with a total sample of 132 respondents, consisted of 58 males and 74 females aged 21- 30. The dependent variable of this study was BMI, and the independent variables consisted of sex and anthropometric measurements, which included ulna length, arm length, tibia length, knee height, mid-upper arm circumference, and calf circumference. Anthropometric information was measured and recorded in a single sitting. Simple and multiple linear regression analysis were used to create the prediction equation for BMI. Results: The male respondents had an average BMI of 24.63 kg/m² and the female respondents had an average of 22.52 kg/m². A total of 17 variables were analysed for its correlation with BMI. Bivariate analysis showed the variable with the strongest correlation with BMI was Mid-Upper Arm Circumference/√Ulna Length (MUAC/√UL) (r = 0.926 for males and r = 0.886 for females). Furthermore, MUAC alone also has a very strong correlation with BMI (r = 0,913 for males and r = 0,877 for females). Prediction models formed from either MUAC/√UL or MUAC alone both produce highly accurate predictions of BMI. However, measuring MUAC/√UL is considered inconvenient, which may cause difficulties when applied on the field. Conclusion: The prediction model considered most ideal to estimate BMI is: Male BMI (kg/m²) = 1.109(MUAC (cm)) – 9.202 and Female BMI (kg/m²) = 0.236 + 0.825(MUAC (cm)), based on its high accuracy levels and the convenience of measuring MUAC on the field.

Keywords: body mass index, mid-upper arm circumference, prediction model, ulna length

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Authors: Ejaz Ahmed, Huang Yong

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The operation of aero engines has a critical importance in the vicinity of lean blowout (LBO) limits. Lefebvre’s model of LBO based on empirical correlation has been extended to flame volume concept by the authors. The flame volume takes into account the effects of geometric configuration, the complex spatial interaction of mixing, turbulence, heat transfer and combustion processes inside the gas turbine combustion chamber. For these reasons, flame volume based LBO predictions are more accurate. Although LBO prediction accuracy has improved, it poses a challenge associated with Vf estimation in real gas turbine combustors. This work extends the approach of flame volume prediction previously based on fuel iterative approximation with cold flow simulations to reactive flow simulations. Flame volume for 11 combustor configurations has been simulated and validated against experimental data. To make prediction methodology robust as required in the preliminary design stage, reactive flow simulations were carried out with the combination of probability density function (PDF) and discrete phase model (DPM) in FLUENT 15.0. The criterion for flame identification was defined. Two important parameters i.e. critical injection diameter (Dp,crit) and critical temperature (Tcrit) were identified, and their influence on reactive flow simulation was studied for Vf estimation. Obtained results exhibit ±15% error in Vf estimation with experimental data.

Keywords: CFD, combustion, gas turbine combustor, lean blowout

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Authors: Azeez Yusuf, Alan Casey

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Silver nanoparticles (AgNP) are one of the most widely investigated metallic nanoparticles due to their promising antibacterial activities. In recent years, AgNP research has shifted beyond antimicrobial use to potential applications in the medical arena. This shift coupled with the extensive commercial applications of AgNP will further increase human exposure, and the subsequent risk of adverse effects that may result from repeated exposures and inefficient delivery meaning research into improved AgNP delivery is of paramount importance. In this study, AgNP were encapsulated in a natural bio-surfactant, dipalmitoylphosphatyidyl choline (DPPC), in an attempt to enhance the intracellular delivery and simultaneously mediate the associated cytotoxicity of the AgNP. It was noted that as a result of the encapsulation, liposomal-AgNP (Lipo-AgNP) at 0.625 μg/ml induced significant cell death in THP1 cell lines a notably lower dose than that of the uncoated AgNP induced cytotoxicity. The induced cytotoxicity was shown to result in an increased level of DNA fragmentation resulting in a cell cycle interruption at the S phase of the cell cycle. It was shown that the predominate form of cell death upon exposure to both uncoated and Lipo-AgNP was apoptosis, however, a ROS-independent activation of the executioner caspases 3/7 occurred when exposed to the Lipo-AgNP. These findings showed that encapsulation of AgNP enhances AgNP cytotoxicity and mediates an ROS-independent induction of apoptosis.

Keywords: silver nanoparticles, AgNP, cytotoxicity, encapsulation, liposome

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Authors: F. Q. Shao, W. Q. Wang, Y. Yin, T. P. Yu, D. B. Zou, J. M. Ouyang

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The Radiation Pressure Acceleration (RPA) mechanism is very promising in laser-driven ion acceleration because of high laser-ion energy conversion efficiency. Although some experiments have shown the characteristics of RPA, the energy of ions is quite limited. The ion energy obtained in experiments is only several MeV/u, which is much lower than theoretical prediction. One possible limiting factor is the transverse instability incited in the RPA process. The transverse instability is basically considered as the Rayleigh-Taylor (RT) instability, which is a kind of interfacial instability and occurs when a light fluid pushes against a heavy fluid. Multi-dimensional particle-in-cell (PIC) simulations show that the onset of transverse instability will destroy the acceleration process and broaden the energy spectrum of fast ions during the RPA dominant ion acceleration processes. The evidence of the RT instability driven by radiation pressure has been observed in a laser-foil interaction experiment in a typical RPA regime, and the dominant scale of RT instability is close to the laser wavelength. The development of transverse instability in the radiation-pressure-acceleration dominant laser-foil interaction is numerically examined by two-dimensional particle-in-cell simulations. When a laser interacts with a foil with modulated surface, the internal instability is quickly incited and it develops. The linear growth and saturation of the transverse instability are observed, and the growth rate is numerically diagnosed. In order to optimize interaction parameters, a method of information entropy is put forward to describe the chaotic degree of the transverse instability. With moderate modulation, the transverse instability shows a low chaotic degree and a quasi-monoenergetic proton beam is produced.

Keywords: information entropy, radiation pressure acceleration, Rayleigh-Taylor instability, transverse instability

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Authors: Piamsiri Sawaisorn, Tienrat Tangchaikeeree, Waraporn Chan-On, Chaniya Leepiyasakulchai, Rachanee Udomsangpetch, Suradej Hongeng, Kulachart Jangpatarapongsa

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Human Vγ9Vδ2 T lymphocytes are regarded as promising effector cells for cancer immunotherapy since they have the ability to eliminate several tumor cells through non-peptide antigen recognition and non-major histocompatibility complex (MHC) restriction. An issue of recent interest is the capability to activate γδ T cells by use of a group of drugs, such as pamidronate, that cause accumulation of phosphoantigen which is recognized by γδ T cell receptors. Moreover, their antigen presenting cell-like phenotype and function have been confirmed in many clinical trials. In this study, Vγ9Vδ2 T cells derived from normal peripheral blood mononuclear cells were activated with pamidronate and the expanded Vγ9Vδ2 T cells can recognize and kill chronic myeloid leukemia (CML) cells treated with pamidronate through their cytotoxic activity. To support the strong role played by Vγ9Vδ2 T cells against cancer, we provide the evidence that Vγ9Vδ2 T cells activated with CML cell lysate antigen can efficiently express antigen presenting cell (APC) phenotype and function. In conclusion, pamidronate can be used in intentional activation of human Vγ9Vδ2 T cells and can increase the susceptibility of CML cells to cytotoxicity of Vγ9Vδ2 T cells. The activated Vγ9Vδ2 T cells by cancer cells lysate can show their APC characteristics, and so greatly increase the interest in exploring their therapeutic potential in hematologic malignancy.

Keywords: γδ T lymphocytes, antigen-presenting cells, chronic myeloid leukemia, cancer, immunotherapy

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Authors: Tarana Siddika, Ilka U. Heinemann, Patrick O’Donoghue

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Protein kinase B (AKT1) is a serine/threonine kinase and central transducer of cell survival pathways. Typical approaches to study AKT1 biology in cells rely on growth factor or insulin stimulation that activates AKT1 via phosphorylation at two key regulatory sites (Threonine308, Serine473), yet cell stimulation also activates many other kinases and fails to differentiate the effect of the two main activating sites of AKT1 on downstream substrate phosphorylation and cell growth. While both AKT1 activating sites are associated with disease and used as clinical markers, in some cancers, high levels of Threonine308 phosphorylation are associated with poor prognosis while in others poor survival correlates with high Serine473 levels. To produce cells with specific AKT1 activity, a system was developed to deliver active AKT1 to human cells. AKT1 phospho-variants were produced from Escherichia coli with programmed phosphorylation by genetic code expansion. Tagging of AKT1 with an N-terminal cell penetrating peptide tag derived from the human immunodeficiency virus trans-activator of transcription (TAT) helped to enter AKT1 proteins in mammalian cells. The TAT-tag did not alter AKT1 kinase activity and was necessary and sufficient to rapidly deliver AKT1 protein variants that persisted in human cells for 24 h without the need to use transfection reagents. TAT-pAKT1T308, TAT-pAKT1S473 and TAT-pAKT1T308S473 proteins induced selective phosphorylation of the known AKT1 substrate GSK-3αβ, and downstream stimulation of the AKT1 pathway as evidenced by phosphorylation of ribosomal protein S6 at Serine240/244 in transfected cells. Increase in cell growth and proliferation was observed due to the transfection of different phosphorylated AKT1 protein variants compared to cells with TAT-AKT1 protein. The data demonstrate efficient delivery of AKT1 with programmed phosphorylation to human cells, thus establishing a cell-based model system to investigate signaling that is dependent on specific AKT1 activity and phosphorylation.

Keywords: cell penetrating peptide, cell signaling, protein kinase b (AKT1), phosphorylation

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Authors: Aasheesh Raturi, Vimal Kothiyal, P. D. Semalty

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We studied mechanical properties of Eucalyptus tereticornis using FT-NIR spectroscopy. Firstly, spectra were pre-processed to eliminate useless information. Then, prediction model was constructed by partial least squares regression. To study the influence of pre-processing on prediction of mechanical properties for NIR analysis of wood samples, we applied various pretreatment methods like straight line subtraction, constant offset elimination, vector-normalization, min-max normalization, multiple scattering. Correction, first derivative, second derivatives and their combination with other treatment such as First derivative + straight line subtraction, First derivative+ vector normalization and First derivative+ multiplicative scattering correction. The data processing methods in combination of preprocessing with different NIR regions, RMSECV, RMSEP and optimum factors/rank were obtained by optimization process of model development. More than 350 combinations were obtained during optimization process. More than one pre-processing method gave good calibration/cross-validation and prediction/test models, but only the best calibration/cross-validation and prediction/test models are reported here. The results show that one can safely use NIR region between 4000 to 7500 cm-1 with straight line subtraction, constant offset elimination, first derivative and second derivative preprocessing method which were found to be most appropriate for models development.

Keywords: FT-NIR, mechanical properties, pre-processing, PLS

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Authors: Jiajia Peng, Danni Cheng, Jianqing Qiu, Yufang Rao, Minzi Mao, Ke Qiu, Junhong Li, Fei Chen, Feng Liu, Jun Liu, Xiaosong Mu, Wenxin Yu, Wei Zhang, Wei Xu, Yu Zhao, Jianjun Ren

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Background: Currently, primary B-cell non-Hodgkin lymphoma (B-NHL) and T/NK-cell non-Hodgkin lymphoma (NKT-NHL) originated from the nasal cavity (NC), nasopharynx (NP) and nasal sinus (NS) distinguished unclearly in the clinic. Objective: We sought to compare the clinical and survival differences of B-NHL and NKT-NHL that occurred in NC, NP, and NS, respectively. Methods: Retrospective data of patients diagnosed with nasal cavity lymphoma (NCL), nasopharyngeal lymphoma (NPL), and nasal sinus lymphoma (NSL) between 1975 and 2017 from the Surveillance, Epidemiology, and End Results (SEER) database were collected. We identified the B/NKT-NHL patients based on the histological type and performed univariate, multivariate, and Kaplan-Meier analyses to investigate the survival rates. Results: Of the identified 3,101 B-NHL and 738 NKT-NHL patients, those with B-NHL in NP were the majority (43%) and had better cancer-specific survival than those in NC and NS from 2010 to 2017 (5-year-CSS, NC vs. NP vs. NS: 81% vs. 83% vs. 82%). In contrast, most of the NKT-NHL originated from NC (68%) and had the highest CSS rate in the recent seven years (2010-2017, 5-year-CSS: 63%). Additionally, the survival outcomes of patients with NKT-NHL-NP (HR: 1.34, 95% CI: 0.62-2.89, P=0.460) who had received surgery were much worse than those of patients with NKT-NHL-NC (HR: 1.07, 95% CI: 0.75-1.52, P=0.710) and NKT-NHL-NS (HR: 1.11, 95% CI: 0.59-2.07, P=0.740). NKT-NHL-NS patients who had radiation performed (HR: 0.38, 95% CI: 0.19-0.73, P=0.004) showed the highest survival rates, while chemotherapy performed (HR: 1.01, 95% CI: 0.43-2.37, P=0.980) presented opposite results. Conclusions: Although B-NHL and NKT-NHL originating from NC, NP and NS had similar anatomical locations, their clinical characteristics, treatment therapies, and prognoses were different in this study. Our findings may suggest that B-NHL and NKT-NHL in NC, NP, and NS should be treated as different diseases in the clinic.

Keywords: nasopharyngeal lymphoma, nasal cavity lymphoma, nasal sinus lymphoma, B-cell non-Hodgkin lymphoma, T/NK-cell non-Hodgkin lymphoma

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Authors: Tomas Vampola, Michael Valášek

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On the basis of simulation-generated failure states of structural elements of a turboprop engine suitable for the busy-jet class of aircraft, an algorithm for early prediction of damage or reduction in functionality of structural elements of the engine is designed and verified with real data obtained at dynamometric testing facilities of aircraft engines. Based on an expanding database of experimentally determined data from temperature and pressure sensors during the operation of turboprop engines, this strategy is constantly modified with the aim of using the minimum number of sensors to detect an inadmissible or deteriorated operating mode of specific structural elements of an aircraft engine. The assembled algorithm for the early prediction of reduced functionality of the aircraft engine significantly contributes to the safety of air traffic and to a large extent, contributes to the economy of operation with positive effects on the reduction of the energy demand of operation and the elimination of adverse effects on the environment.

Keywords: detectability of malfunction, dynamometric testing, prediction of damage, turboprop engine

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Authors: Benhouda Afaf, Yahia Massinissa, Paolo Grieco

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Hyoscyamus albus L. is a small genus from Solanaceae family known by its use in old traditional medicine in the east of Algeria. Aim: This study aimed to characterize bioactive molecules from H. albus, evaluate their anticancer activity in several cancer cells and investigate their possible molecular mechanism. Materials and Methods: Different compounds (Peak h of fraction F), (Peak 3 of Fraction F), (Peak 1 of fraction C) were isolated from H.albus L by using high-performance chromatography (HPLC), mass spectrometry (MS) and proton NMR (NMR H1). All isolated compounds were subjected to cytotoxicity and antiproliferative assays against a panel of the four cell lines: DU-145, U-2 OS, U-87 MG and LN-229 cell lines and were determined using MTT assay, Annexin V and propodium iodide were used to evaluate apoptosis. Results: The phytochemical study of H. albus Fractions led to the isolation of quercetin-3-O-β-dglucopyranosyl-( 1 → 6)-β-d-glucopyranosid, N-trans-feruloyltyramine, Hydrocaffeoyl-N8- caffeoylspermidine.The biological results indicated that all cell lines were consistently sensitive to P1 FC in a dose-dependent manner. This difference in cytotoxic sensitivity was more pronounced in osteosarcoma cell line, U-2 OS, when compared to prostate cancer and U-87 MG. Cell viability data also demonstrated that only U-87 MG cells were responsive to treatment with Ph FF. compounds P1 FC and Ph FF have induced necrosis and apoptosis in a large part of LN-229 cells. Conclusion: The overall results of the present study provided evidence that isolated compounds are potential therapeutic entities against cancer.

Keywords: hyoscyamus albus, cancer cells, coumpounds, HPLC

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Authors: Kefaya Qaddoum

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Most of greenhouse growers desire a determined amount of yields in order to accurately meet market requirements. The purpose of this paper is to model a simple but often satisfactory supervised classification method. The original naive Bayes have a serious weakness, which is producing redundant predictors. In this paper, utilized regularization technique was used to obtain a computationally efficient classifier based on naive Bayes. The suggested construction, utilized L1-penalty, is capable of clearing redundant predictors, where a modification of the LARS algorithm is devised to solve this problem, making this method applicable to a wide range of data. In the experimental section, a study conducted to examine the effect of redundant and irrelevant predictors, and test the method on WSG data set for tomato yields, where there are many more predictors than data, and the urge need to predict weekly yield is the goal of this approach. Finally, the modified approach is compared with several naive Bayes variants and other classification algorithms (SVM and kNN), and is shown to be fairly good.

Keywords: tomato yield prediction, naive Bayes, redundancy, WSG

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Authors: Riznaldi Akbar

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In this study, we compared the performance of the Artificial Neural Network (ANN) model with back-propagation algorithm in correctly predicting in-sample and out-of-sample external debt crisis in Indonesia. We found that exchange rate, foreign reserves, and exports are the major determinants to experiencing external debt crisis. The ANN in-sample performance provides relatively superior results. The ANN model is able to classify correctly crisis of 89.12 per cent with reasonably low false alarms of 7.01 per cent. In out-of-sample, the prediction performance fairly deteriorates compared to their in-sample performances. It could be explained as the ANN model tends to over-fit the data in the in-sample, but it could not fit the out-of-sample very well. The 10-fold cross-validation has been used to improve the out-of-sample prediction accuracy. The results also offer policy implications. The out-of-sample performance could be very sensitive to the size of the samples, as it could yield a higher total misclassification error and lower prediction accuracy. The ANN model could be used to identify past crisis episodes with some accuracy, but predicting crisis outside the estimation sample is much more challenging because of the presence of uncertainty.

Keywords: debt crisis, external debt, artificial neural network, ANN

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Authors: Phawichsak Prapassornpitaya, Wanida Jinsart

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Daily monitoring PM₁₀ and PM₂.₅ data from 2007 to 2017 were analyzed to provide baseline data for prediction of the air pollution in Bangkok in the period of 2018 -2020. Two statistical models, Autoregressive Integrated Moving Average model (ARIMA) were used to evaluate the trends of pollutions. The prediction concentrations were tested by root means square error (RMSE) and index of agreement (IOA). This evaluation of the traffic PM₂.₅ and PM₁₀ were studied in association with the regulatory control and emission standard changes. The emission factors of particulate matter from diesel vehicles were decreased when applied higher number of euro standard. The trends of ambient air pollutions were expected to decrease. However, the Bangkok smog episode in February 2018 with temperature inversion caused high concentration of PM₂.₅ in the air environment of Bangkok. The impact of traffic pollutants was depended upon the emission sources, temperature variations, and metrological conditions.

Keywords: fine particulate matter, ARIMA, RMSE, Bangkok

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Authors: Ganesh R. Bhand, N. B. Chaure

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Cadmium selenide (CdSe) quantum dots (QDs) were prepared by solvothermal route. Subsequently a inorganic QDs-organic semiconductor (copper phthalocyanine) nanocomposite (i.e CuPc:CdSe nanocomposites) were produced by different concentration of QDs varied in CuPc. The nanocomposite thin films have been prepared by means of spin coating technique. The optical, structural and morphological properties of nanocomposite films have been investigated. The transmission electron microscopy (TEM) confirmed the formation of QDs having average size of  4 nm. The X-ray diffraction pattern exhibits cubic crystal structure of CdSe with reflection to (111), (220) and (311) at 25.4ᵒ, 42.2ᵒ and 49.6ᵒ respectively. The additional peak observed at lower angle at 6.9ᵒ in nanocomposite thin films are associated to CuPc. The field emission scanning electron microscopy (FESEM) observed that surface morphology varied in increasing concentration of CdSe QDs. The obtained nanocomposite show significant improvement in the thermal stability as compared to the pure CuPc indicated by thermo-gravimetric analysis (TGA) in thermograph. The effect in the Raman spectra of composites samples gives a confirm evidence of homogenous dispersion of CdSe in the CuPc matrix and their strong interaction between them to promotes charge transfer property. The success of reaction between composite was confirmed by Fourier transform infrared spectroscopy (FTIR). The photo physical properties were studied using UV - visible spectroscopy. The enhancement of the optical absorption in visible region for nanocomposite layer was observed with increasing the concentration of CdSe in CuPc. This composite may obtain the maximized interface between QDs and polymer for efficient charge separation and enhance the charge transport. Such nanocomposite films for potential application in fabrication of hybrid solar cell with improved power conversion efficiency.

Keywords: CdSe QDs, cupper phthalocyanine, FTIR, optical absorption

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Authors: Panadda Rojpibulstit, Suthathip Kittisenachai, Songchan Puthong, Sirikul Manochantr, Pornpen Gamnarai, Sasichai Kangsadalampai, Sittiruk Roytrakul

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Hepatocellular carcinoma (HCC) is the most primary hepatic cancer worldwide. Nowadays a targeted therapy via monoclonal antibodies (mAbs) specific to tumor-associated antigen is continually developed in HCC treatment. In this regard, after establishing and consequently exploring Hep88 mAb’s tumoricidal effect on hepatocellular carcinoma cell line (HepG2 cell line), the Hep88 mAb’s specific Ag from both membrane and cytoplasmic fractions of HepG2 cell line was identified by 2-D gel electrophoresis and western blot analysis. After in-gel digestion and subsequent analysis by liquid chromatography-mass spectrometry (LC-MS), mortalin (HSPA9) and alpha-enolase were identified. The recombinant proteins specific to Hep88 mAb were cloned and expressed in E.coli BL21 (DE3). Moreover, alteration of HepG2 and Chang liver cell line after being induced by Hep88 mAb for 1-3 days was investigated using a transmission electron microscope. The result demonstrated that Hep88 mAb can bind to the recombinant mortalin (HSPA9) andalpha-enolase. In addition, gradual appearance of mitochondria vacuolization and endoplasmic reticulum dilatation were observed. Taken together, paraptosis-like programmed cell death (PCD) of HepG2 is induced by binding of mortalin (HSPA9) and alpha-enolase to Hep88 mAb. Mortalin depletion by formation of Hep88 mAb-mortalin (HSPA9) complex might initiate transcription-independent of p53-mediated apoptosis. Additionally, Hep88 mAb-alpha-enolase complex might initiate HepG2 cells energy exhaustion by glycolysis pathway obstruction. These results imply that Hep88 mAb might be a promising tool for development of an effective treatment of HCC in the next decade.

Keywords: Hepatocellular carcinoma, Monoclonal antibody, Paraptosis-like program cell death, Transmission electron microscopy, mortalin (HSPA9), alpha-enolase

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Authors: S. M. Gupta, Vanita Aggarwal, Som Nath Sachdeva

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The work reported through this paper is an experimental work conducted on High Performance Concrete (HPC) with super plasticizer with the aim to develop some models suitable for prediction of compressive strength of HPC mixes. In this study, the effect of varying proportions of fly ash (0% to 50% at 10% increment) on compressive strength of high performance concrete has been evaluated. The mix designs studied were M30, M40 and M50 to compare the effect of fly ash addition on the properties of these concrete mixes. In all eighteen concrete mixes have been designed, three as conventional concretes for three grades under discussion and fifteen as HPC with fly ash with varying percentages of fly ash. The concrete mix designing has been done in accordance with Indian standard recommended guidelines i.e. IS: 10262. All the concrete mixes have been studied in terms of compressive strength at 7 days, 28 days, 90 days and 365 days. All the materials used have been kept same throughout the study to get a perfect comparison of values of results. The models for compressive strength prediction have been developed using Linear Regression method (LR), Artificial Neural Network (ANN) and Leave One Out Validation (LOOV) methods.

Keywords: high performance concrete, fly ash, concrete mixes, compressive strength, strength prediction models, linear regression, ANN

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Authors: Ae Ra Han, Seoung Eun Huh, Ji Yeon Kim, Joanne Kwak-Kim, Sung Ki Lee

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Objective: Prevalence of osteoporosis, cardiovascular disorders, and Alzheimer's disease rapidly increase after menopause. Immune activation and inflammation are suggested as an important pathogenesis of these serious diseases. Several pro-inflammatory cytokines are increased in women with surgical or natural menopause. However, the little is known about IL-17 producing T cells and Foxp3+ regulatory T (Treg) cells in post-menopause. Methods: A total of 34 postmenopausal women, who had no active cardiovascular, endocrine and infectious disorders were recruited as study group and healthy premenopausal women participated as controls. Peripheral blood mononuclear cells were isolated. Immuno-morphologic (CD3, CD4, CD8, CD19, CD56/CD16), intracellular cytokine (TNF-alpha, IFN-gamma, IL-10, IL-17), and Treg cell (Foxp3) studies were carried out using flow cytometry. The proportion of peripheral lymphocytes, including IL-17 producing and Foxp3+ Treg cells immune cell in each group were statistically analyzed. Results: The proportion of NK cells was significantly increased in menopausal women as compared to that of controls (P=.005). The ratios of TNF-alpha/IL-10 producing CD3+CD4+ T cells were increased in postmenopausal women. CD3+IL-17+ T cell level was higher in postmenopausal women and CD4+ Foxp3+ Treg cells was lower than that of controls. The ratios of CD3+IL-17+ T cell to CD3+Foxp3+ and to CD4+Foxp3+ Treg cells were significantly increased in postmenopausal women (P=.001). Conclusions: We found enhanced innate immunity and Th1- and Th17-mediated adaptive immunity in postmenopausal women. This may explain increasing prevalence of chronic inflammatory diseases after menopause. Further studies are needed to elucidate what factors contribute to this inflammatory shift in the postmenopause.

Keywords: inflammation, immune cell, menopause, Th17, regulatory T cell

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Authors: E. Nakamachi, S. Tanaka, K. Yamamoto, Y. Morita

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In this study, we developed a three-dimensional (3D) direct current electric field (DCEF) stimulation bio-reactor for axonal outgrowth enhancement to generate the neural network of the central nervous system (CNS). By using our newly developed 3D DCEF stimulation bio-reactor, we cultured the rat pheochromocytoma cells (PC12) and investigated the effects on the axonal extension enhancement and network generation. Firstly, we designed and fabricated a 3D bio-reactor, which can load DCEF stimulation on PC12 cells embedded in the collagen gel as extracellular environment. The connection between the electrolyte and the medium using salt bridges for DCEF stimulation was introduced to avoid the cell death by the toxicity of metal ion. The distance between the salt bridges was adopted as the design variable to optimize a structure for uniform DCEF stimulation, where the finite element (FE) analyses results were used. Uniform DCEF strength and electric flux vector direction in the PC12 cells embedded in collagen gel were examined through measurements of the fabricated 3D bio-reactor chamber. Measurement results of DCEF strength in the bio-reactor showed a good agreement with FE results. In addition, the perfusion system was attached to maintain pH 7.2 ~ 7.6 of the medium because pH change was caused by DCEF stimulation loading. Secondly, we disseminated PC12 cells in collagen gel and carried out 3D culture. Finally, we measured the morphology of PC12 cell bodies and neurites by the multiphoton excitation fluorescence microscope (MPM). The effectiveness of DCEF stimulation to enhance the axonal outgrowth and the neural network generation was investigated. We confirmed that both an increase of mean axonal length and axogenesis rate of PC12, which have been exposed 5 mV/mm for 6 hours a day for 4 days in the bioreactor. We found following conclusions in our study. 1) Design and fabrication of DCEF stimulation bio-reactor capable of 3D culture nerve cell were completed. A uniform electric field strength of average value of 17 mV/mm within the 1.2% error range was confirmed by using FE analyses, after the structure determination through the optimization process. In addition, we attached a perfusion system capable of suppressing the pH change of the culture solution due to DCEF stimulation loading. 2) Evaluation of DCEF stimulation effects on PC12 cell activity was executed. The 3D culture of PC 12 was carried out adopting the embedding culture method using collagen gel as a scaffold for four days under the condition of 5.0 mV/mm and 10mV/mm. There was a significant effect on the enhancement of axonal extension, as 11.3% increase in an average length, and the increase of axogenesis rate. On the other hand, no effects on the orientation of axon against the DCEF flux direction was observed. Further, the network generation was enhanced to connect longer distance between the target neighbor cells by DCEF stimulation.

Keywords: PC12, DCEF stimulation, 3D bio-reactor, axonal extension, neural network generation

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Authors: Suzan Anwar, Utkarsh Goyal

Abstract:

Heart rate (HR) is a predictor of cardiovascular, cerebrovascular, and all-cause mortality in the general population, as well as in patients with cardio and cerebrovascular diseases. Machine learning (ML) significantly improves the accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment while avoiding unnecessary treatment of others. This research examines relationship between the individual's various heart health inputs like age, sex, cp, trestbps, thalach, oldpeaketc, and the likelihood of developing heart disease. Machine learning techniques like logistic regression and decision tree, and Python are used. The results of testing and evaluating the model using the Heart Failure Prediction Dataset show the chance of a person having a heart disease with variable accuracy. Logistic regression has yielded an accuracy of 80.48% without data handling. With data handling (normalization, standardscaler), the logistic regression resulted in improved accuracy of 87.80%, decision tree 100%, random forest 100%, and SVM 100%.

Keywords: heart rate, machine learning, SVM, decision tree, logistic regression, random forest

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence

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Authors: Jamal Al-Zain, O. El Hajjaji, T. El Bardouni

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A (Th-U) O2 fuel pin benchmark made up of 25 w/o U and 75 w/o Th was used. In order to analyze the depletion and inventory of the fuel for the pressurized water reactor pin-cell model. The new version VIII.0 of the ENDF/B nuclear data library was used to create a data set in ACE format at various temperatures and process the data using the MAKXSF6.2 and NJOY2016 programs to process the data at the various temperatures in order to conduct this study and analyze cross-section data. The infinite multiplication factor, the concentrations and activities of the main fission products, the actinide radionuclides accumulated in the pin cell, and the total radioactivity were all estimated and compared in this study using the Monte Carlo N-Particle 6 (MCNP6.2) and DRAGON5 programs. Additionally, the behavior of the Pressurized Water Reactor (PWR) thorium pin cell that is dependent on burn-up (BU) was validated and compared with the reference data obtained using the Massachusetts Institute of Technology (MIT-MOCUP), Idaho National Engineering and Environmental Laboratory (INEEL-MOCUP), and CASMO-4 codes. The results of this study indicate that all of the codes examined have good agreements.

Keywords: PWR thorium pin cell, ENDF/B-VIII.0, MAKXSF6.2, NJOY2016, MCNP6.2, DRAGON5, fuel burn-up.

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Authors: Zohra Salim

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Objective: To access the relationship of primary tumor thickness with cervical lymphadenopathy in squamous cell carcinoma of buccal mucosa. Methodology: A cross-sectional observational study was carried out on 80 Patients with biopsy-proven oral squamous cell carcinoma of buccal mucosa at Dow University of Health Sciences. All the study participants were treated with wide local excision of the primary tumor with elective neck dissection. Patients with prior head and neck malignancy or those with prior radiotherapy or chemotherapy were excluded from the study. Data was entered and analyzed on SPSS 21. Chi-squared test with 95% C.I and 80% power of the test was used to evaluate the relationship of tumor depth with cervical lymph nodes. Results: 50 participants were male, and 30 patients were female. 30 patients were in the age range of 20-40 years, 36 patients in the range of 40-60 years, while 14 patients were beyond age 60 years. Tumor size ranged from 0.3cm to 5cm with a mean of 2.03cm. Tumor depth ranged from 0.2cm to 5cm. 20% of the participants reported with tumor depth greater than 2.5cm, while 80% of patients reported with tumor depth less than 2.5cm. Out of 80 patients, 27 reported with negative lymph nodes, while 53 patients reported with positive lymph nodes. Conclusion: Our study concludes that relationship exists between the depth of primary tumor and cervical lymphadenopathy in squamous cell carcinoma of buccal mucosa.

Keywords: squamous cell carcinoma, tumor depth, cervical lymphadenopathy, buccal mucosa

Procedia PDF Downloads 237

Authors: Shimaa M. Elsaeed, Reem K. Farag, Ibrahim M. Nassar

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Hydrogel conductive polymer nanocomposite fabricated via in-situ polymerization of polyaniline (PANI) inside thermosensitive hydrogels based on hydroxy ethyl meth acrylate (HEMA) copolymer with 2-acrylamido-2-methyl propane sulfonic acid (AMPS). SEM micrographs show the nanometric size of the conductive material (polyaniline, PANI) dispersed in the hydrogel matrix. The swelling parameters of hydrogel are measured. The incorporation of PANI improves the mechanical properties and swelling up to 30,000% without breaking. X-ray diffraction shows that typical polyaniline crystallization is formed in composite, which is advantageous to increase the electrical conductivity of the composite hydrogel. Open-circuit voltage (I-V) curve fill factor of the highest photo-conversion efficiency and enhanced to use in solar cell.

Keywords: hydrogel, solar cell, conductive polymer, nanocomposite

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Authors: Mikhail Gritskevich, Sebastian Hohenstein

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The paper presents the results of a detailed assessment of several modern Reynolds Averaged Navier-Stokes (RANS) turbulence models for prediction of C3X vane film cooling at various injection regimes. Three models are considered, namely the Shear Stress Transport (SST) model, the modification of the SST model accounting for the streamlines curvature (SST-CC), and the Explicit Algebraic Reynolds Stress Model (EARSM). It is shown that all the considered models face with a problem in prediction of the adiabatic effectiveness in the vicinity of the cooling holes; however, accounting for the Reynolds stress anisotropy within the EARSM model noticeably increases the solution accuracy. On the other hand, further downstream all the models provide a reasonable agreement with the experimental data for the adiabatic effectiveness and among the considered models the most accurate results are obtained with the use EARMS.

Keywords: discrete holes film cooling, Reynolds Averaged Navier-Stokes (RANS), Reynolds stress tensor anisotropy, turbulent heat transfer

Procedia PDF Downloads 420

Authors: Mir Ahmad Lashteh Neshaei, Hamed Afsoos Biria, Ata Ghabraei, Mir Abdolhamid Mehrdad

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Awareness of effective land using issues in coastal area including protection of natural ecosystems and coastal environment due to the increasing of human life along the coast is of great importance. There are numerous valuable structures and heritages which are located in defence sites and waterfront area. Marine structures such as groins, sea walls and detached breakwaters are constructed in coast to improve the coast stability against bed erosion due to changing wave and climate pattern. Marine mechanisms and interaction with the shore protection structures need to be intensively studied. Groins are one of the most prominent structures that are used in shore protection to create a safe environment for coastal area by maintaining the land against progressive coastal erosion. The main structural function of a groin is to control the long shore current and littoral sediment transport. This structure can be submerged and provide the necessary beach protection without negative environmental impact. However, for submerged structures adopted for beach protection, the shoreline response to these structures is not well understood at present. Nowadays, modelling and computer simulation are used to assess beach morphology in the vicinity of marine structures to reduce their environmental impact. The objective of this study is to predict the beach morphology in the vicinity of submerged groins and comparison with non-submerged groins with focus on a part of the coast located in Dahane sar Sefidrood, Guilan province, Iran where serious coast erosion has occurred recently. The simulations were obtained using a one-line model which can be used as a first approximation of shoreline prediction in the vicinity of groins. The results of the proposed model are compared with field measurements to determine the shape of the coast. Finally, the results of the present study show that using submerged groins can have a good efficiency to control the beach erosion without causing severe environmental impact to the coast. The important outcome from this study can be employed in optimum designing of defence sites in the coastal cities to improve their efficiency in terms of re-using the heritage lands.

Keywords: submerged structures, groin, shore protective structures, coastal cities

Procedia PDF Downloads 316

Authors: Pooja Rani, G. S. Mahapatra, S. K. Pandey

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In this paper, we propose a novel approach of Neural Network and Particle Swarm Optimization methods for software reliability prediction. We first explain how to apply compound function in neural network so that we can derive a Flexible Logistic (S-shaped) Growth Curve (FLGC) model. This model mathematically represents software failure as a random process and can be used to evaluate software development status during testing. To avoid trapping in local minima, we have applied Particle Swarm Optimization method to train proposed model using failure test data sets. We drive our proposed model using computational based intelligence modeling. Thus, proposed model becomes Neuro-Particle Swarm Optimization (NPSO) model. We do test result with different inertia weight to update particle and update velocity. We obtain result based on best inertia weight compare along with Personal based oriented PSO (pPSO) help to choose local best in network neighborhood. The applicability of proposed model is demonstrated through real time test data failure set. The results obtained from experiments show that the proposed model has a fairly accurate prediction capability in software reliability.

Keywords: software reliability, flexible logistic growth curve model, software cumulative failure prediction, neural network, particle swarm optimization

Procedia PDF Downloads 344

Authors: Monika Malik, Pooja Arora, Ruchi Sachdeva, Vishnampettai G. Ramachandran, Rahul Pal

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Apoptotic debris is believed to be the antigenic trigger in lupus. Whether such debris and autoantibodies induced in lupus-prone mice which specifically recognize its constituents can mediate differential effects on innate and humoral responses in such mice was assessed. The influence of apoptotic blebs and apoptotic cell-reactive monoclonal antibodies on phenotypic markers expressed on bone marrow-derived dendritic cells (BMDCs) and secreted cytokines were evaluated. Sera from lupus-prone and healthy mice immunized with the antibodies were analyzed for anti-self reactivity. Apoptotic blebs, as well as somatically-mutated IgG and non-mutated IgM apoptotic-cell reactive monoclonal antibodies, induced the preferential maturation of BMDCs derived from lupus-prone mice relative to BMDCs derived from healthy mice; antibody specificity and cell genotype both influenced the secretion of inflammatory cytokines. Immunization of lupus-prone mice with IgM and IgG antibodies led to hypergammaglobulinemia; elicited antibodies were self-reactive, and exhibited enhanced recognition of lupus-associated autoantigens (dsDNA, Ro60, RNP68, and Sm) in comparison with adjuvant-induced sera. While ‘natural’ IgM antibodies are believed to contribute to immune homeostasis, this study reveals that apoptotic cell-reactive IgM antibodies can promote inflammation and drive anti-self responses in lupus. Only in lupus-prone mice did immunization with IgG auto-antibodies enhance the kinetics of humoral anti-self responses, resulting in advanced-onset glomerulosclerosis. This study reveals that preferential innate and humoral recognition of the products of cell death in an autoimmune milieu influences the indices associated with lupus pathology.

Keywords: antigen spreading, apoptotic cell-reactive pathogenic IgG, and IgM autoantibodies, glomerulosclerosis, lupus

Procedia PDF Downloads 169

Authors: A. Hakimiyan, H. Namazi

Abstract:

Human behavior is defined as a range of behaviors exhibited by humans who are influenced by different internal or external sources. Human behavior is the subject of much research in different areas of psychology and neuroscience. Despite some advances in studies related to forecasting of human behavior, there are not many researches which consider the effect of the time delay between the presence of stimulus and the related human response. Analysis of EEG signal as a fractal time series is one of the major tools for studying the human behavior. In the other words, the human brain activity is reflected in his EEG signal. Artificial Neural Network has been proved useful in forecasting of different systems’ behavior especially in engineering areas. In this research, a time delay neural network is trained and tested in order to forecast the human EEG signal and subsequently human behavior. This neural network, by introducing a time delay, takes care of the lagging time between the occurrence of the stimulus and the rise of the subsequent action potential. The results of this study are useful not only for the fundamental understanding of human behavior forecasting, but shall be very useful in different areas of brain research such as seizure prediction.

Keywords: human behavior, EEG signal, time delay neural network, prediction, lagging time

Procedia PDF Downloads 663