Search results for: GAF domain protein

Authors: Adeline Meriaux, Claire Gaiani, Jennifer Burgain, Frantz Fournier, Lionel Muniglia, Jérémy Petit

Abstract:

Spray-drying process is widely used for the production of dairy powders for food and pharmaceuticals industries. It involves the atomization of a liquid feed into fine droplets, which are subsequently dried through contact with a hot air flow. The resulting powders permit transportation cost reduction and shelf life increase but can also exhibit various interesting functionalities (flowability, solubility, protein modification or acid gelation), depending on operating conditions and milk composition. Indeed, particles porosity, surface composition, lactose crystallization, protein denaturation, protein association or crust formation may change. Links between spray-drying conditions and physicochemical and functional properties of powders were investigated by a design of experiment methodology and analyzed by principal component analysis. Quadratic models were developed, and multicriteria optimization was carried out by the use of genetic algorithm. At the time of abstract submission, verification spray-drying trials are ongoing. To perform experiments, milk from dairy farm was collected, skimmed, froze and spray-dried at different air pressure (between 1 and 3 bars) and outlet temperature (between 75 and 95 °C). Dry matter, minerals content and proteins content were determined by standard method. Solubility index, absorption index and hygroscopicity were determined by method found in literature. Particle size distribution were obtained by laser diffraction granulometry. Location of the powder color in the Cielab color space and water activity were characterized by a colorimeter and an aw-value meter, respectively. Flow properties were characterized with FT4 powder rheometer; in particular compressibility and shearing test were performed. Air pressure and outlet temperature are key factors that directly impact the drying kinetics and powder characteristics during spray-drying process. It was shown that the air pressure affects the particle size distribution by impacting the size of droplet exiting the nozzle. Moreover, small particles lead to more cohesive powder and less saturated color of powders. Higher outlet temperature results in lower moisture level particles which are less sticky and can explain a spray-drying yield increase and the higher cohesiveness; it also leads to particle with low water activity because of the intense evaporation rate. However, it induces a high hygroscopicity, thus, powders tend to get wet rapidly if they are not well stored. On the other hand, high temperature provokes a decrease of native serum proteins which is positively correlated to gelation properties (gel point and firmness). Partial denaturation of serum proteins can improve functional properties of powder. The control of air pressure and outlet temperature during the spray-drying process significantly affects the physicochemical and functional properties of powder. This study permitted to better understand the links between physicochemical and functional properties of powder, to identify correlations between air pressure and outlet temperature. Therefore, mathematical models have been developed and the use of genetic algorithm will allow the optimization of powder functionalities.

Keywords: dairy powders, spray-drying, powders functionalities, design of experiment

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Authors: D. van der Merwe

Abstract:

As the environment and associated media in which creativity is expressed transitions towards digital spaces, that same creativity undergoes a transition from individual to social forms of expression. This paper explores how the emerging social construction collectively called ‘The Metaverse’ will fundamentally alter creativity: by examining creativity as a social rather than individual process, as well as the mimetic logic underlying the platforms in which this creativity is expressed, a crisis in identity, commodification and social programming is revealed wherein the artist is more a commodity than their creations, resulting in prosthetic personalities pandering to an economic logic driven by biased algorithms. Consequently the very aura of the art and creative media produced within the digital domain must be re-assessed in terms of its cultural and exhibition value.

Keywords: aura, commodification, creativity, metaverse, mimesis, social programming

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Authors: Igor Belykh

Abstract:

Anti-scatter grids used in radiographic imaging for the contrast enhancement leave specific artifacts. Those artifacts may be visible or may cause Moiré effect when a digital image is resized on a diagnostic monitor. In this paper, we propose an automated grid artifacts detection and suppression algorithm which is still an actual problem. Grid artifacts detection is based on statistical approach in spatial domain. Grid artifacts suppression is based on Kaiser bandstop filter transfer function design and application avoiding ringing artifacts. Experimental results are discussed and concluded with description of advantages over existing approaches.

Keywords: grid, computed radiography, pattern recognition, image processing, filtering

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Authors: Christine Demaecker

Abstract:

Many researchers have underlined the importance of metaphors in specialised language. Their use of specific domains helps us understand the conceptualisations used to communicate new ideas or difficult topics. Within the wide area of specialised discourse, wine tasting is a very specific example because it is almost exclusively metaphoric. Wine tasting metaphors express various conceptualisations. They are not linguistic but rather conceptual, as defined by Lakoff & Johnson. They correspond to the linguistic expression of a mental projection from a well-known or more concrete source domain onto the target domain, which is the taste of wine. But unlike most specialised terminologies, the vocabulary is never clearly defined. When metaphorical terms are listed in dictionaries, their definitions remain vague, unclear, and circular. They cannot be replaced by literal linguistic expressions. This makes it impossible to transfer them into another language with the traditional linguistic translation methods. Qualitative research investigates whether wine tasting metaphors could rather be translated with the cognitive translation process, as well described by Nili Mandelblit (1995). The research is based on a corpus compiled from two high-profile wine guides; the Parker’s Wine Buyer’s Guide and its translation into French and the Guide Hachette des Vins and its translation into English. In this small corpus with a total of 68,826 words, 170 metaphoric expressions have been identified in the original English text and 180 in the original French text. They have been selected with the MIPVU Metaphor Identification Procedure developed at the Vrije Universiteit Amsterdam. The selection demonstrates that both languages use the same set of conceptualisations, which are often combined in wine tasting notes, creating conceptual integrations or blends. The comparison of expressions in the source and target texts also demonstrates the use of the cognitive translation approach. In accordance with the principle of relevance, the translation always uses target language conceptualisations, but compared to the original, the highlighting of the projection is often different. Also, when original metaphors are complex with a combination of conceptualisations, at least one element of the original metaphor underlies the target expression. This approach perfectly integrates into Lederer’s interpretative model of translation (2006). In this triangular model, the transfer of conceptualisation could be included at the level of ‘deverbalisation/reverbalisation’, the crucial stage of the model, where the extraction of meaning combines with the encyclopedic background to generate the target text.

Keywords: cognitive translation, conceptual integration, conceptual metaphor, interpretative model of translation, wine tasting metaphor

Procedia PDF Downloads 131

Authors: Viviane A. O. Silva, Angela M. Costa, Glaucia N. M. Hajj, Ana Preto, Aline Tansini, Martin Roffé, Peter Jordan, Rui M. Reis

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Autophagy is a recycling and degradative system suggested to be a major cell death pathway in cancer cells. Autophagy pathway is interconnected with the endocytosis pathways sharing the same ultimate lysosomal destination. Lysosomes are crucial regulators of cell homeostasis, responsible to downregulate receptor signalling and turnover. It seems highly likely that derailed endocytosis can make major contributions to several hallmarks of cancer. WNK2, a member of the WNK (with-no-lysine [K]) subfamily of protein kinases, had been found downregulated by its promoter hypermethylation, and has been proposed to act as a specific tumour-suppressor gene in brain tumors. Although some contradictory studies indicated WNK2 as an autophagy modulator, its role in cancer cell death is largely unknown. There is also growing evidence for additional roles of WNK kinases in vesicular traffic. Aim: To evaluate the role of WNK2 in autophagy and endocytosis on glioma context. Methods: Wild-type (wt) A172 cells (WNK2 promoter-methylated), and A172 transfected either with an empty vector (Ev) or with a WNK2 expression vector, were used to assess the cellular basal capacities to promote autophagy, through western blot and flow-cytometry analysis. Additionally, we evaluated the effect of WNK2 on general endocytosis trafficking routes by immunofluorescence. Results: The re-expression of ectopic WNK2 did not interfere with autophagy-related protein light chain 3 (LC3-II) expression levels as well as did not promote mTOR signaling pathway alteration when compared with Ev or wt A172 cells. However, the restoration of WNK2 resulted in a marked increase (8 to 92,4%) of Acidic Vesicular Organelles formation (AVOs). Moreover, our results also suggest that WNK2 cells promotes delay in uptake and internalization rate of cholera toxin B and transferrin ligands. Conclusions: The restoration of WNK2 interferes in vesicular traffic during endocytosis pathway and increase AVOs formation. This results also suggest the role of WNK2 in growth factor receptor turnover related to cell growth and homeostasis and associates one more time, WNK2 silencing contribution in genesis of gliomas.

Keywords: autophagy, endocytosis, glioma, WNK2

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Authors: Zarine Avetisyan

Abstract:

The process of speech production and transmission naturally implies the occurrence of certain defective assumptions and erroneous formulations which may be both spontaneous, caused by haste, carelessness, etc., or deliberate. Whether deliberate or not, fallacies always act by way of “faux pas”. In the latter case, we deal with fake or deceptive arguments which are the focus of the given paper. The paper departs from the assumption that fallacies are arguments that prove nothing. Additionally and more importantly, political discourse becomes the main domain for scholarly “cultivation” while pinning down fallacies. The fallacy of telling the truth but deliberately omitting important key details in order to falsify the larger picture called “the half truth” captures special attention in the given paper.

Keywords: break in the information chain, fallacy, half truth, political discourse

Procedia PDF Downloads 392

Authors: Sohail Imran, Tariq Mahmood

Abstract:

In complex healthcare diagnostic investigation process, medical practitioners have to focus on ways to standardize their processes to perform high quality care and optimize the time and costs. Process mining techniques can be applied to extract process related knowledge from data without considering causal and dynamic dependencies in business domain and processes. The application of process mining is effective in diagnostic investigation. It is very helpful where a treatment gives no dispositive evidence favoring it. In this paper, we applied process mining to discover important process flow of diagnostic investigation for hepatitis patients. This approach has some benefits which can enhance the quality and efficiency of diagnostic investigation processes.

Keywords: process mining, healthcare, diagnostic investigation process, process flow

Procedia PDF Downloads 523

Authors: Adeline Meriaux, Claire Gaiani, Jennifer Burgain, Frantz Fournier, Lionel Muniglia, Jérémy Petit

Abstract:

Spray-drying process is widely used for the production of dairy powders for food and pharmaceuticals industries. It involves the atomization of a liquid feed into fine droplets, which are subsequently dried through contact with a hot air flow. The resulting powders permit transportation cost reduction and shelf life increase but can also exhibit various interesting functionalities (flowability, solubility, protein modification or acid gelation), depending on operating conditions and milk composition. Indeed, particles porosity, surface composition, lactose crystallization, protein denaturation, protein association or crust formation may change. Links between spray-drying conditions and physicochemical and functional properties of powders were investigated by a design of experiment methodology and analyzed by principal component analysis. Quadratic models were developed, and multicriteria optimization was carried out by the use of genetic algorithm. At the time of abstract submission, verification spray-drying trials are ongoing. To perform experiments, milk from dairy farm was collected, skimmed, froze and spray-dried at different air pressure (between 1 and 3 bars) and outlet temperature (between 75 and 95 °C). Dry matter, minerals content and proteins content were determined by standard method. Solubility index, absorption index and hygroscopicity were determined by method found in literature. Particle size distribution were obtained by laser diffraction granulometry. Location of the powder color in the Cielab color space and water activity were characterized by a colorimeter and an aw-value meter, respectively. Flow properties were characterized with FT4 powder rheometer; in particular, compressibility and shearing test were performed. Air pressure and outlet temperature are key factors that directly impact the drying kinetics and powder characteristics during spray-drying process. It was shown that the air pressure affects the particle size distribution by impacting the size of droplet exiting the nozzle. Moreover, small particles lead to more cohesive powder and less saturated color of powders. Higher outlet temperature results in lower moisture level particles which are less sticky and can explain a spray-drying yield increase and the higher cohesiveness; it also leads to particle with low water activity because of the intense evaporation rate. However, it induces a high hygroscopicity, thus, powders tend to get wet rapidly if they are not well stored. On the other hand, high temperature provokes a decrease of native serum proteins, which is positively correlated to gelation properties (gel point and firmness). Partial denaturation of serum proteins can improve functional properties of powder. The control of air pressure and outlet temperature during the spray-drying process significantly affects the physicochemical and functional properties of powder. This study permitted to better understand the links between physicochemical and functional properties of powder to identify correlations between air pressure and outlet temperature. Therefore, mathematical models have been developed, and the use of genetic algorithm will allow the optimization of powder functionalities.

Keywords: dairy powders, spray-drying, powders functionalities, design of experiment

Procedia PDF Downloads 65

Authors: Leyla Sattarzadeh, Shahin Fathi Molk Kian, Maghsoud Peeri, Mohammadali Azarbaijani, Hasan Matin Homaee

Abstract:

Inflammation by various mechanisms may cause atherosclerosis. Systemic circulating inflammatory markers such as C-reactive protein (CRP), pro-inflammatory cytokines such as Interleukin-6 (IL-6), vascular inflammatory markers as adhesion molecules like Intracellular Adhesion Molecule-1 (ICAM-1) and Vascular Cell Adhesion Molecule-1 (VCAM-1) are the predictors of cardiovascular diseases. Regarding the conflicting results about the effect of different patterns of resistance exercise training on these inflammatory markers, present study aimed to examine the effect of different patterns of eight week resistance exercise training on CRP, IL-6, ICAM-1 and VCAM-1 levels in healthy untrained women. 56 healthy volunteered untrained female university students (aged: 21 ± 3 yr., Body Mass Index: 21.5 ± 3.5 kg/m²) were selected purposefully and divided into four groups. At the end of training protocol and after subject drop during the protocol, upper body exercise training (n=11), lower body (n=12) and whole body resistance exercise training group (n=11) completed the eight weeks of training period although the control group (n=7) did anything. Blood samples gathered pre and post-experimental period and CRP, IL-6, ICAM-1 and VCAM-1 levels were evaluated using special laboratory kits, then the difference of pre and post values of each indices analyzed using one-way analysis of variance (α < 0.05). The results of one way ANOVA for difference of pre and post values of CRP, ICAM-1 and VCAM-1 showed no significant changes due to the exercise training, but there were significant differences between groups about IL-6. Tukey post- hoc test indicated that there is significant difference between the differences of pre and post values of IL-6 between lower body exercise training group and control group, and eight weeks of lower body exercise training lead to significant changes in IL-6 values. There were no changes in anthropometric indices. The findings show that the different patterns of upper, lower and whole body exercise training by involving the different amounts of muscles altered the IL-6 values in lower body exercise training group probably because of engaging the bigger amount of muscles, but showed any significant changes about CRP, ICAM-1 and VCAM-1 probably due to intensity and duration of exercise or the lower levels of these markers at baseline of healthy people.

Keywords: resistance training, C-reactive protein, interleukin-6, intracellular adhesion molecule-1, vascular cell adhesion molecule-1

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Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

Abstract:

This paper introduces a methodology for advancing Italian speech vowels landmark detection within the distinctive feature-based speech recognition domain. Leveraging the legacy tool 'xkl' by integrating combined convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the study presents a comprehensive enhancement to the 'xkl' legacy software. This integration incorporates re-assigned spectrogram methodologies, enabling meticulous acoustic analysis. Simultaneously, our proposed model, integrating combined CNNs and RNNs, demonstrates unprecedented precision and robustness in landmark detection. The augmentation of re-assigned spectrogram fusion within the 'xkl' software signifies a meticulous advancement, particularly enhancing precision related to vowel formant estimation. This augmentation catalyzes unparalleled accuracy in landmark detection, resulting in a substantial performance leap compared to conventional methods. The proposed model emerges as a state-of-the-art solution in the distinctive feature-based speech recognition systems domain. In the realm of deep learning, a synergistic integration of combined CNNs and RNNs is introduced, endowed with specialized temporal embeddings, harnessing self-attention mechanisms, and positional embeddings. The proposed model allows it to excel in capturing intricate dependencies within Italian speech vowels, rendering it highly adaptable and sophisticated in the distinctive feature domain. Furthermore, our advanced temporal modeling approach employs Bayesian temporal encoding, refining the measurement of inter-landmark intervals. Comparative analysis against state-of-the-art models reveals a substantial improvement in accuracy, highlighting the robustness and efficacy of the proposed methodology. Upon rigorous testing on a database (LaMIT) speech recorded in a silent room by four Italian native speakers, the landmark detector demonstrates exceptional performance, achieving a 95% true detection rate and a 10% false detection rate. A majority of missed landmarks were observed in proximity to reduced vowels. These promising results underscore the robust identifiability of landmarks within the speech waveform, establishing the feasibility of employing a landmark detector as a front end in a speech recognition system. The synergistic integration of re-assigned spectrogram fusion, CNNs, RNNs, and Bayesian temporal encoding not only signifies a significant advancement in Italian speech vowels landmark detection but also positions the proposed model as a leader in the field. The model offers distinct advantages, including unparalleled accuracy, adaptability, and sophistication, marking a milestone in the intersection of deep learning and distinctive feature-based speech recognition. This work contributes to the broader scientific community by presenting a methodologically rigorous framework for enhancing landmark detection accuracy in Italian speech vowels. The integration of cutting-edge techniques establishes a foundation for future advancements in speech signal processing, emphasizing the potential of the proposed model in practical applications across various domains requiring robust speech recognition systems.

Keywords: landmark detection, acoustic analysis, convolutional neural network, recurrent neural network

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Authors: T. Benazzouz, K. Auhmani

Abstract:

This paper presents a Hospital 4.0 Maturity Assessment Model based on the Industry 4.0 concepts. The self-assessment model defines current and target states of digital transformation by considering multiple aspects of a hospital and a healthcare supply chain. The developed model was validated and evaluated on real-life cases. The resulting model consisted of 5 domains: Technology, Strategy 4.0, Human resources 4.0 & Culture 4.0, Supply chain 4.0 management, and Patient journeys management. Each domain is further divided into several sub-domains, totally 34 sub-domains are identified, that reflect different facets of a hospital 4.0 mature organization.

Keywords: hospital 4.0, Industry 4.0, maturity assessment model, supply chain 4.0, patient

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Authors: Shashi Kant Verma, S. L. Sinha, D. K. Chandraker

Abstract:

Numerical simulations of selected subchannel tracer (Potassium Nitrate) based experiments have been performed to study the capabilities of state-of-the-art of Computational Fluid Dynamics (CFD) codes. The Computational Fluid Dynamics (CFD) methodology can be useful for investigating the spacer effect on turbulent mixing to predict turbulent flow behavior such as Dimensionless mixing scalar distributions, radial velocity and vortices in the nuclear fuel assembly. A Gibson and Launder (GL) Reynolds stress model (RSM) has been selected as the primary turbulence model to be applied for the simulation case as it has been previously found reasonably accurate to predict flows inside rod bundles. As a comparison, the case is also simulated using a standard k-ε turbulence model that is widely used in industry. Despite being an isotropic turbulence model, it has also been used in the modeling of flow in rod bundles and to produce lateral velocities after thorough mixing of coolant fairly. Both these models have been solved numerically to find out fully developed isothermal turbulent flow in a 30º segment of a 54-rod bundle. Numerical simulation has been carried out for the study of natural mixing of a Tracer (Passive scalar) to characterize the growth of turbulent diffusion in an injected sub-channel and, afterwards on, cross-mixing between adjacent sub-channels. The mixing with water has been numerically studied by means of steady state CFD simulations with the commercial code STAR-CCM+. Flow enters into the computational domain through the mass inflow at the three subchannel faces. Turbulence intensity and hydraulic diameter of 1% and 5.9 mm respectively were used for the inlet. A passive scalar (Potassium nitrate) is injected through the mass fraction of 5.536 PPM at subchannel 2 (Upstream of the mixing section). Flow exited the domain through the pressure outlet boundary (0 Pa), and the reference pressure was 1 atm. Simulation results have been extracted at different locations of the mixing zone and downstream zone. The local mass fraction shows uniform mixing. The effect of the applied turbulence model is nearly negligible just before the outlet plane because the distributions look like almost identical and the flow is fully developed. On the other hand, quantitatively the dimensionless mixing scalar distributions change noticeably, which is visible in the different scale of the colour bars.

Keywords: single-phase flow, turbulent mixing, tracer, sub channel analysis

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Authors: Giorgio Bertolazzi, Panayiotis Benos, Michele Tumminello, Claudia Coronnello

Abstract:

MicroRNAs are small non-coding RNAs that post-transcriptionally regulate the expression levels of messenger RNAs. MicroRNA regulation activity depends on the recognition of binding sites located on mRNA molecules. ComiR (Combinatorial miRNA targeting) is a user friendly web tool realized to predict the targets of a set of microRNAs, starting from their expression profile. ComiR incorporates miRNA expression in a thermodynamic binding model, and it associates each gene with the probability of being a target of a set of miRNAs. ComiR algorithms were trained with the information regarding binding sites in the 3’UTR region, by using a reliable dataset containing the targets of endogenously expressed microRNA in D. melanogaster S2 cells. This dataset was obtained by comparing the results from two different experimental approaches, i.e., inhibition, and immunoprecipitation of the AGO1 protein; this protein is a component of the microRNA induced silencing complex. In this work, we tested whether including coding region binding sites in the ComiR algorithm improves the performance of the tool in predicting microRNA targets. We focused the analysis on the D. melanogaster species and updated the ComiR underlying database with the currently available releases of mRNA and microRNA sequences. As a result, we find that the ComiR algorithm trained with the information related to the coding regions is more efficient in predicting the microRNA targets, with respect to the algorithm trained with 3’utr information. On the other hand, we show that 3’utr based predictions can be seen as complementary to the coding region based predictions, which suggests that both predictions, from 3'UTR and coding regions, should be considered in a comprehensive analysis. Furthermore, we observed that the lists of targets obtained by analyzing data from one experimental approach only, that is, inhibition or immunoprecipitation of AGO1, are not reliable enough to test the performance of our microRNA target prediction algorithm. Further analysis will be conducted to investigate the effectiveness of the tool with data from other species, provided that validated datasets, as obtained from the comparison of RISC proteins inhibition and immunoprecipitation experiments, will be available for the same samples. Finally, we propose to upgrade the existing ComiR web-tool by including the coding region based trained model, available together with the 3’UTR based one.

Keywords: AGO1, coding region, Drosophila melanogaster, microRNA target prediction

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Authors: Qingqing Feng, S. Thomas Ng, Frank J. Xu, Jiduo Xing

Abstract:

Faced with unprecedented challenges including aging assets, lack of maintenance budget, overtaxed and inefficient usage, and outcry for better service quality from the society, today’s infrastructure systems has become the main focus of many metropolises to pursue sustainable urban development and improve resilience. Digital twin, being one of the most innovative enabling technologies nowadays, may open up new ways for tackling various infrastructure asset management (IAM) problems. Digital twin application for IAM, as its name indicated, represents an evolving digital model of intended infrastructure that possesses functions including real-time monitoring; what-if events simulation; and scheduling, maintenance, and management optimization based on technologies like IoT, big data and AI. Up to now, there are already vast quantities of global initiatives of digital twin applications like 'Virtual Singapore' and 'Digital Built Britain'. With digital twin technology permeating the IAM field progressively, it is necessary to consider the maturity of the application and how those institutional or industrial digital twin application processes will evolve in future. In order to deal with the gap of lacking such kind of benchmark, a draft maturity model is developed for digital twin application in the IAM field. Firstly, an overview of current smart cities maturity models is given, based on which the draft Maturity Model of Digital Twin Application for Infrastructure Asset Management (MM-DTIAM) is developed for multi-stakeholders to evaluate and derive informed decision. The process of development follows a systematic approach with four major procedures, namely scoping, designing, populating and testing. Through in-depth literature review, interview and focus group meeting, the key domain areas are populated, defined and iteratively tuned. Finally, the case study of several digital twin projects is conducted for self-verification. The findings of the research reveal that: (i) the developed maturity model outlines five maturing levels leading to an optimised digital twin application from the aspects of strategic intent, data, technology, governance, and stakeholders’ engagement; (ii) based on the case study, levels 1 to 3 are already partially implemented in some initiatives while level 4 is on the way; and (iii) more practices are still needed to refine the draft to be mutually exclusive and collectively exhaustive in key domain areas.

Keywords: digital twin, infrastructure asset management, maturity model, smart city

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Authors: Olga V. Chervyakova, Elmira T. Tailakova, Vitaliy M. Strochkov, Kulyaisan T. Sultankulova, Nurlan T. Sandybayev, Lev G. Nemchinov, Rosemarie W. Hammond

Abstract:

Sheep pox is a highly contagious infection that OIE regards to be one of the most dangerous animal diseases. It causes enormous economic losses because of death and slaughter of infected animals, lower productivity, cost of veterinary and sanitary as well as quarantine measures. To control spread of sheep pox infection the attenuated vaccines are widely used in the Republic of Kazakhstan and other Former Soviet Union countries. In spite of high efficiency of live vaccines, the possible presence of the residual virulence, potential genetic instability restricts their use in disease-free areas that leads to necessity to exploit new approaches in vaccine development involving recombinant DNA technology. Vaccines on the basis of recombinant proteins are the newest generation of prophylactic preparations. The main advantage of these vaccines is their low reactogenicity and this fact makes them widely used in medical and veterinary practice for vaccination of humans and farm animals. The objective of the study is to produce recombinant immunogenic proteins for development of the high-performance means for sheep pox prophylaxis. The SPV proteins were chosen for their homology with the known immunogenic vaccinia virus proteins. Assay of nucleotide and amino acid sequences of the target SPV protein genes. It has been shown that four proteins SPPV060 (ortholog L1), SPPV074 (ortholog H3), SPPV122 (ortholog A33) and SPPV141 (ortholog B5) possess transmembrane domains at N- or C-terminus while in amino acid sequences of SPPV095 (ortholog А 4) and SPPV117 (ortholog А 27) proteins these domains were absent. On the basis of these findings the primers were constructed. Target genes were amplified and subsequently cloned into the expression vector рЕТ26b(+) or рЕТ28b(+). Six constructions (pSPPV060ΔТМ, pSPPV074ΔТМ, pSPPV095, pSPPV117, pSPPV122ΔТМ and pSPPV141ΔТМ) were obtained for expression of the SPV genes under control of T7 promoter in Escherichia coli. To purify and detect recombinant proteins the amino acid sequences were modified by adding six histidine molecules at C-terminus. Induction of gene expression by IPTG was resulted in production of the proteins with molecular weights corresponding to the estimated values for SPPV060, SPPV074, SPPV095, SPPV117, SPPV122 and SPPV141, i.e. 22, 30, 20, 19, 17 and 22 kDa respectively. Optimal protocol of expression for each gene that ensures high yield of the recombinant protein was identified. Assay of cellular lysates by western blotting confirmed expression of the target proteins. Recombinant proteins bind specifically with antibodies to polyhistidine. Moreover all produced proteins are specifically recognized by the serum from experimentally SPV-infected sheep. The recombinant proteins SPPV060, SPPV074, SPPV117, SPPV122 and SPPV141 were also shown to induce formation of antibodies with virus-neutralizing activity. The results of the research will help to develop a new-generation high-performance means for specific sheep pox prophylaxis that is one of key moments in animal health protection. The research was conducted under the International project ISTC # K-1704 “Development of methods to construct recombinant prophylactic means for sheep pox with use of transgenic plants” and under the Grant Project RK MES G.2015/0115RK01983 "Recombinant vaccine for sheep pox prophylaxis".

Keywords: prophylactic preparation, recombinant protein, sheep pox virus, subunit vaccine

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Authors: Peter Edwar Mortada Nasif

Abstract:

The use of CAD (Computer Aided Design) technology is ubiquitous in the architecture, engineering and construction (AEC) industry. This has led to its inclusion in the curriculum of architecture schools in Nigeria as an important part of the training module. This article examines the ethical issues involved in implementing CAD (Computer Aided Design) content into the architectural education curriculum. Using existing literature, this study begins with the benefits of integrating CAD into architectural education and the responsibilities of different stakeholders in the implementation process. It also examines issues related to the negative use of information technology and the perceived negative impact of CAD use on design creativity. Using a survey method, data from the architecture department of Chukwuemeka Odumegwu Ojukwu Uli University was collected to serve as a case study on how the issues raised were being addressed. The article draws conclusions on what ensures successful ethical implementation. Millions of people around the world suffer from hepatitis C, one of the world's deadliest diseases. Interferon (IFN) is treatment options for patients with hepatitis C, but these treatments have their side effects. Our research focused on developing an oral small molecule drug that targets hepatitis C virus (HCV) proteins and has fewer side effects. Our current study aims to develop a drug based on a small molecule antiviral drug specific for the hepatitis C virus (HCV). Drug development using laboratory experiments is not only expensive, but also time-consuming to conduct these experiments. Instead, in this in silicon study, we used computational techniques to propose a specific antiviral drug for the protein domains of found in the hepatitis C virus. This study used homology modeling and abs initio modeling to generate the 3D structure of the proteins, then identifying pockets in the proteins. Acceptable lagans for pocket drugs have been developed using the de novo drug design method. Pocket geometry is taken into account when designing ligands. Among the various lagans generated, a new specific for each of the HCV protein domains has been proposed.

Keywords: drug design, anti-viral drug, in-silicon drug design, hepatitis C virus, computer aided design, CAD education, education improvement, small-size contractor automatic pharmacy, PLC, control system, management system, communication

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Authors: K. Boumediene, S. E. Belhenniche

Abstract:

This article presents a numerical analysis of a turbulent flow past DTMB 4119 marine propeller by the means of RANS approach; the propeller designed at David Taylor Model Basin in USA. The purpose of this study is to predict the hydrodynamic performance of the marine propeller, it aims also to compare the results obtained with the experiment carried out in open water tests; a periodical computational domain was created to reduce the unstructured mesh size generated. The standard kw turbulence model for the simulation is selected; the results were in a good agreement. Therefore, the errors were estimated respectively to 1.3% and 5.9% for KT and KQ.

Keywords: propeller flow, CFD simulation, RANS, hydrodynamic performance

Procedia PDF Downloads 499

Authors: Myung-Gon Yoon, Jung-Ho Moon, Tae Kwon Ha

Abstract:

This paper considers a robust stabilization problem of a single agent in a multi-agent consensus system composed of identical agents, when the network topology of the system is completely unknown. It is shown that the transfer function of an agent in a consensus system can be described as a multiplicative perturbation of the isolated agent transfer function in frequency domain. Applying known robust stabilization results, we present sufficient conditions for a robust stabilization of an agent against unknown network topology.

Keywords: single agent control, multi-agent system, transfer function, graph angle

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Authors: Javed Mohammed

Abstract:

Right now, bio-medical infrastructure lags well behind the curve. Our healthcare system is dispersed and disjointed; medical records are a bit of a mess; and we do not yet have the capacity to store and process the crazy amounts of data coming our way from widespread whole-genome sequencing. And then there are privacy issues. Despite these infrastructure challenges, some researchers are plunging into bio medical Big Data now, in hopes of extracting new and actionable knowledge. They are doing delving into molecular-level data to discover bio markers that help classify patients based on their response to existing treatments; and pushing their results out to physicians in novel and creative ways. Computer scientists and bio medical researchers are able to transform data into models and simulations that will enable scientists for the first time to gain a profound under-standing of the deepest biological functions. Solving biological problems may require High-Performance Computing HPC due either to the massive parallel computation required to solve a particular problem or to algorithmic complexity that may range from difficult to intractable. Many problems involve seemingly well-behaved polynomial time algorithms (such as all-to-all comparisons) but have massive computational requirements due to the large data sets that must be analyzed. High-throughput techniques for DNA sequencing and analysis of gene expression have led to exponential growth in the amount of publicly available genomic data. With the increased availability of genomic data traditional database approaches are no longer sufficient for rapidly performing life science queries involving the fusion of data types. Computing systems are now so powerful it is possible for researchers to consider modeling the folding of a protein or even the simulation of an entire human body. This research paper emphasizes the computational biology's growing need for high-performance computing and Big Data. It illustrates this article’s indispensability in meeting the scientific and engineering challenges of the twenty-first century, and how Protein Folding (the structure and function of proteins) and Phylogeny Reconstruction (evolutionary history of a group of genes) can use HPC that provides sufficient capability for evaluating or solving more limited but meaningful instances. This article also indicates solutions to optimization problems, and benefits Big Data and Computational Biology. The article illustrates the Current State-of-the-Art and Future-Generation Biology of HPC Computing with Big Data.

Keywords: high performance, big data, parallel computation, molecular data, computational biology

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Authors: Girgis Younan, Ikram Eltayeb

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Geigeria alata belongs to the family Asteraceae, is an effective plant traditionally used in Sudan as a therapy for hepatic disease and as an antiepileptic, antispasmodic and to treat cough and intestinal complaints.The liver is responsible for many critical functions within the body and any liver disease or injury will result in the loss of those functions leading to significant damage in the body. Liver diseases cause increase in liver enzymes (AST, ALP ALT) and total bilirubin and a decrease in total blood protein level. The objective of this study is to investigate the hepato-protective activity of Geigeria alata leaves ethanolic extract. The plant leaves were extracted using 96% ethanol using Soxhlet apparatus. The hepatoprotective effect was determined using 25 wistar rats, the rats was divided to 5 groups, each group contain 5 rats: [Normal control group] receiving purified water, liver damage was induced in wistar rats by administering a 1:1 (v/v) mixture of CCl4 (1.25 ml/kg) and olive oil once at day four of the experiment [negative control group]. Two doses of extract [400mg/kg and 200mg/kg] was applied daily for 7 days, and standard drug Silymarin (200 mg/kg) were administered daily for 7 days to CCl4-treated rats. The degree of hepato-protective activity was evaluated by determining the hepatic marker enzymes AST, ALP, ALT, total Bilirubin and total proteins (TP). Results have shown that, the extract of G.alata leaves reduced the level of liver enzymes ALT, AST, ALP, total bilirubin and increased the level of total proteins. Since the levels of liver enzymes; bilirubin and total protein are considered as markers of liver function, the extract has proven to reduce the detrimental effects of liver toxicity induced using CCl4. The hepato-protective effect of extract on liver was found to be dose dependent, where the 400mg/kg dose of the extract exhibited higher activity than 200mg/kg dose. In addition, the effect of the higher dose (400mg/kg) of the extract was found to be higher than Silymarin standard drug. The result concludes that, G.alata leaves extract was found to exhibit profound hepato-protective activity, which justifies the traditional use of the plant for the treatment of hepatic diseases.

Keywords: alata, extract, geigeria, hepatoprotective

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Authors: Mariamawit T. Belete

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Cereal production and marketing are the means of livelihood for millions of households in Ethiopia. However, cereal production is constrained by technical and socio-economic factors. Among the technical factors, cereal crop diseases are the major contributing factors to the low yield. The aim of this research is to develop an integration of data mining and knowledge based system for sorghum anthracnose disease diagnosis that assists agriculture experts and development agents to make timely decisions. Anthracnose diagnosing systems gather information from Melkassa agricultural research center and attempt to score anthracnose severity scale. Empirical research is designed for data exploration, modeling, and confirmatory procedures for testing hypothesis and prediction to draw a sound conclusion. WEKA (Waikato Environment for Knowledge Analysis) was employed for the modeling. Knowledge based system has come across a variety of approaches based on the knowledge representation method; case-based reasoning (CBR) is one of the popular approaches used in knowledge-based system. CBR is a problem solving strategy that uses previous cases to solve new problems. The system utilizes hidden knowledge extracted by employing clustering algorithms, specifically K-means clustering from sampled anthracnose dataset. Clustered cases with centroid value are mapped to jCOLIBRI, and then the integrator application is created using NetBeans with JDK 8.0.2. The important part of a case based reasoning model includes case retrieval; the similarity measuring stage, reuse; which allows domain expert to transfer retrieval case solution to suit for the current case, revise; to test the solution, and retain to store the confirmed solution to the case base for future use. Evaluation of the system was done for both system performance and user acceptance. For testing the prototype, seven test cases were used. Experimental result shows that the system achieves an average precision and recall values of 70% and 83%, respectively. User acceptance testing also performed by involving five domain experts, and an average of 83% acceptance is achieved. Although the result of this study is promising, however, further study should be done an investigation on hybrid approach such as rule based reasoning, and pictorial retrieval process are recommended.

Keywords: sorghum anthracnose, data mining, case based reasoning, integration

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Authors: L. Gómez-Limia, I. Franco, T. Blanco, S. Martínez

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European eels (Anguilla anguilla) belong to Anguilliformes order and Anguillidae family. They are generally classified as warm-water fish. Eels have a great commercial value in Europe and Asian countries. Eels can reach high weights, although their commercial size is relatively low in some countries. The capture of larger eels would facilitate the recovery of the species, as well as having a greater number of either glass eels or elvers for aquaculture. In the last years, the demand and the price of eels have increased significantly. However, European eel is considered critically endangered by the International Union for the Conservation of Nature (IUCN) Red List. The biochemical composition of fishes is an important aspect of quality and affects the nutritional value and consumption quality of fish. In addition, knowing this composition can help predict an individual’s condition for their recovery. Fish is known to be important source of protein rich in essential amino acids. However, there is very little information about changes in amino acids composition of European eels with increase in size. The aim of this study was to evaluate the effect of two different weight categories on the amino acids content in muscle tissue of wild European eels. European eels were caught in River Ulla (Galicia, NW Spain), during winter. The eels were slaughtered in ice water immersion. Then, they were purchased and transferred to the laboratory. The eels were subdivided into two groups, according to the weight. The samples were kept frozen (-20 °C) until their analysis. Frozen eels were defrosted and the white muscle between the head and the anal hole. was extracted, in order to obtain amino acids composition. Thirty eels for each group were used. Liquid chromatography was used for separation and quantification of amino a cids. The results conclude that the eels are rich in glutamic acid, leucine, lysine, threonine, valine, isoleucine and phenylalanine. The analysis showed that there are significant differences (p < 0.05) among the eels with different sizes. Histidine, threonine, lysine, hydroxyproline, serine, glycine, arginine, alanine and proline were higher in small eels. European eels muscle presents between 45 and 46% of essential amino acids in the total amino acids. European eels have a well-balanced and high quality protein source in the respect of E/NE ratio. However, eels with higher weight showed a better ratio of essential and non-essential amino acid.

Keywords: European eels, amino acids, HPLC, body size

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Authors: Omar Omar, Yuan Jun, Hong Jinghua, Jin Chuanhong

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In this work molybdenum dioxide (MoO2) and sulphur powders are used to grow MoS2 mono layers at elevated temperatures T≥800 °C. Centimetre scale continues thin films with grain size up to 410 µm have been grown using chemical vapour deposition. To our best knowledge, these domains are the largest that have been grown so far. Advantage of our approach is not only because of the high quality films with large domain size one can produce, but also the procedure is potentially less hazardous than other methods tried. The thin films have been characterized using transmission electron microscopy (TEM), atomic force microscopy (AFM) and Raman spectroscopy.

Keywords: molybdenum disulphide (MoS2), monolayers, chemical vapour deposition (CVD), growth and characterization

Procedia PDF Downloads 328

Authors: Atefe Malekkhani, Lee Beattie, Mohsen Mohammadzadeh

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Unprecedented growth of megacities and urban areas all around the world have resulted in numerous risks, concerns, and problems across various aspects of urban life, including environmental, social, and economic domains like climate change, spatial and social inequalities. In this situation, ever-increasing progress of technology has created a hope for urban authorities that the negative effects of various socio-economic and environmental crises can potentially be mitigated with the use of information and communication technologies. The concept of 'smart city' represents an emerging solution to urban challenges arising from increased urbanization using ICTs. However, smart cities are often perceived primarily as technological initiatives and are implemented without considering the social and cultural contexts of cities and the needs of their residents. The implementation of smart city projects and initiatives has the potential to (un)intentionally exacerbate pre-existing social, spatial, and cultural segregation. Investigating the impact of smart city on social capital of people who are users of smart city systems and with governance as policymakers is worth exploring. The importance of inhabitants to the existence and development of smart cities cannot be overlooked. This concept has gained different perspectives in the smart city studies. Reviewing the literature about social capital and smart city show that social capital play three different roles in smart city development. Some research indicates that social capital is a component of a smart city and has embedded in its dimensions, definitions, or strategies, while other ones see it as a social outcome of smart city development and point out that the move to smart cities improves social capital; however, in most cases, it remains an unproven hypothesis. Other studies show that social capital can enhance the functions of smart cities, and the consideration of social capital in planning smart cities should be promoted. Despite the existing theoretical and practical knowledge, there is a significant research gap reviewing the knowledge domain of smart city studies through the lens of social capital. To shed light on this issue, this study aims to explore the domain of existing research in the field of smart city through the lens of social capital. This research will use the 'Preferred Reporting Items for Systematic Reviews and Meta-Analyses' (PRISMA) method to review relevant literature, focusing on the key concepts of 'Smart City' and 'Social Capital'. The studies will be selected Web of Science Core Collection, using a selection process that involves identifying literature sources, screening and filtering studies based on titles, abstracts, and full-text reading.

Keywords: smart city, urban digitalisation, ICT, social capital

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Authors: Maryam Beiranvand

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Multi-drug resistance in various microorganisms has increased globally in many healthcare facilities. Less effective antimicrobial activity of drug therapies for infection control becomes trouble. Since 1980, no new type of antimicrobial drug has been identified, even though combinations of antibiotic drugs have been discovered almost every decade. Between 1981 and 2006, over 70% of novel pharmaceuticals and chemical agents came from natural sources. Microorganisms have yielded almost 22,000 natural compounds. The identification of antimicrobial components from endophytes bacteria could help overcome the threat posed by multi-drug resistant strains. The project aims to analyze and identify antimicrobial peptides isolated from entophytic bacteria and their activity against multidrug-resistant Gram-negative bacteria in South Korea. Endophytic Paenibacillus polymyxa. 4G3 isolated from the plant, Gynura procumbery exhibited considerable antimicrobial activity against Methicillin-resistant Staphylococcus aureus, and Escherichia coli. The Rapid Annotations using Subsystems Technology showed that the total size of the draft genome was 5,739,603bp, containing 5178 genes with 45.8% G+C content. Genome annotation using antiSMASH version 6.0.0 was performed, which predicted the most common types of non-ribosomal peptide synthetase (NRPS) and polyketide synthase (PKS). In this study, diethyl aminoethyl cellulose (DEAEC) resin was used as the first step in purifying for unknown peptides, and then the target protein was identified using hydrophilic and hydrophobic solutions, optimal pH, and step-by-step tests for antimicrobial activity. This crude was subjected to C18 chromatography and elution with 0, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100% methanol, respectively. Only the fraction eluted with 20% -60% methanol demonstrated good antimicrobial activity against MDR E. coli. The concentration of the active fragment was measured by the Brad-ford test, and Protein A280 - Thermo Fisher Scientific at the end by examining the SDS PAGE Resolving Gel, 10% Acrylamide and purity were confirmed. Our study showed that, based on the combined results of the analysis and purification. P polymyxa. 4G3 has a high potential exists for producing novel functions of polymyxin E and bacitracin against bacterial pathogens.

Keywords: endophytic bacteria, antimicrobial activity, antimicrobial peptide, whole genome sequencing analysis, multi -drug resistance gram negative bacteria

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Authors: Alebiosu Olugbenga Shadrak, Victor Victoria

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Honey bees exhibit preferences in their foraging behaviour on pollen and nectar for food and honey production, respectively. Melissopalynology is the study of pollen in honey and other honey products. Several work have been conducted on the palynological studies of honeys from the southern parts of Nigeria but with relatively scant records from the Northern region of the country. This present study aimed at revealing the favourably visited plants by honey bees, Apis melifera var. adansonii, at some apiaries in Northern Nigeria, as well as determining the quality of honeys produced. Honeys were harvested and collected from four apiaries of the region, namely: Sarkin Dawa missionary bee farm, Taraba State; Eleeshuwa Bee Farm, Keffi, Nassarawa State, Bulus Beekeeper Apiaries, Kagarko, Kaduna State and Mai Gwava Bee Farm, Kano State. These honeys were acetolysed for palynological microscopic analysis and subjected to standard treatment methods for the determination of their proximate composition and sugar profiling. Fresh anthers of two dominantly represented plants in the honeys were then collected for the quantification of their pollen protein contents, using the micro-kjeldhal procedure. A total of 30 pollen types were identified in the four honeys, and some of them were common to the honeys. A classification method for expressing pollen frequency class was employed: Senna cf. siamea, Terminalia cf. catappa, Mangifera indica, Parinari curatelifolia, Vitellaria paradoxa, Elaeis guineensis, Parkia biglobosa, Phyllantus muellerianus and Berlina Grandiflora, as “Frequent” (16-45%); while the others are either Rare (3-15%) or Sporadic (less than 3 %). Pollen protein levels of the two abundantly represented plants, Senna siamea (15.90mg/ml) and Terminalia catappa (17.33mg/ml) were found to be considerably lower. The biochemical analyses revealed varying amounts of proximate composition, non-reducing sugar and total sugar levels in the honeys. The results of this study indicate that pollen and nectar of the “Frequent” plants were preferentially foraged by honeybees in the apiaries. The estimated pollen protein contents of Senna same and Terminalia catappa were considerably lower and not likely to have influenced their favourable visitation by honeybees. However, a relatively higher representation of Senna cf. siamea in the pollen spectrum might have resulted from its characteristic brightly coloured and well scented flowers, aiding greater entomophily. Terminalia catappa, Mangifera indica, Elaeis guineensis, Vitellaria paradoxa, and Parkia biglobosa are typical food crops; hence they probably attracted the honeybees owing to the rich nutritional values of their fruits and seeds. Another possible reason for a greater entomophily of the favourably visited plants are certain nutritional constituents of their pollen and nectar, which were not investigated in this study. The nutritional composition of the honeys was observed to fall within the safe limits of international norms, as prescribed by Codex Alimentarius Commission, thus they are good honeys for human consumption. It is therefore imperative to adopt strategic conservation steps in ensuring that these favourably visited plants are protected from indiscriminate anthropogenic activities and also encourage apiarists in the country to establish their bee farms more proximally to the plants for optimal honey yield.

Keywords: honeybees, melissopalynology, preferentially foraged, nutritional, bee farms, proximally

Procedia PDF Downloads 278

Authors: Samantha A. Cintron, Janet Pierce, Mihaela E. Sardiu, Diane Mahoney, Jill Peltzer, Bhanu Gupta, Qiuhua Shen

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High output heart failure (HOHF) is characterized a high output state resulting from an underlying disease process and is commonly caused by obesity. As obesity levels increase, more individuals will be at risk for obesity-related HOHF. However, the underlying pathophysiologic mechanisms of obesity-related HOHF are not well understood and need further research. The aim of the study was to describe the differences in leukocyte transcriptomes of morbidly obese patients with HOHF and those with non-HOHF. In this cross-sectional study, the study team collected blood samples, demographics, and clinical data of six patients with morbid obesity and HOHF and six patients with morbid obesity and non-HOHF. The study team isolated the peripheral blood leukocyte RNA and applied stranded total RNA sequencing. Differential gene expression was calculated, and Ingenuity Pathway Analysis software was used to interpret the canonical pathways, functional changes, upstream regulators, and mechanistic and causal networks that were associated with the significantly different leukocyte transcriptomes. The study team identified 116 differentially expressed genes; 114 were upregulated, and 2 were downregulated in the HOHF group (Benjamini-Hochberg adjusted p-value ≤ 0.05 and log2(fold-change) of ±1). The differentially expressed genes were involved with cell proliferation, mitochondrial function, erythropoiesis, erythrocyte stability, and apoptosis. The top upregulated canonical pathways associated with differentially expressed genes were autophagy, adenosine monophosphate-activated protein kinase signaling, and senescence pathways. Upstream regulator GATA Binding Protein 1 (GATA1) and a network associated with nuclear factor kappa-light chain-enhancer of activated B cells (NF-kB) were also identified based on the different leukocyte transcriptomes of morbidly obese patients with HOHF and non-HOHF. To the author’s best knowledge, this is the first study that reported the differential gene expression in patients with obesity-related HOHF and demonstrated the unique pathophysiologic mechanisms underlying the disease. Further research is needed to determine the role of cellular function and maintenance, inflammation, and iron homeostasis in obesity-related HOHF.

Keywords: cardiac output, heart failure, obesity, transcriptomics

Procedia PDF Downloads 55

Authors: Shai Sarussi

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Let S be an integral domain which is not a field, let F be its field of fractions, and let A be an F-algebra. An S-subalgebra R of A is called S-nice if R ∩ F = S and F R = A. A topological space whose set of open sets is closed under arbitrary intersections is called an Alexandroff space. Inspired by the well-known Zariski-Riemann space and the Zariski topology on the set of prime ideals of a commutative ring, we define a topology on the set of all S-nice subalgebras of A. Consequently, we get an interplay between Algebra and topology, that gives us a better understanding of the S-nice subalgebras of A. It is shown that every irreducible subset of S-nice subalgebras of A has a supremum; and a characterization of the irreducible components is given, in terms of maximal S-nice subalgebras of A.

Keywords: Alexandroff topology, integral domains, Zariski-Riemann space, S-nice subalgebras

Procedia PDF Downloads 109

Authors: William Kelly, Sorelle Veigne, Xianhua Li, Zuyi Huang, Shyamsundar Subramanian, Eugene Schaefer

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The ambr15™ bioreactor is a single-use microbioreactor for cell line development and process optimization. The ambr system offers fully automatic liquid handling with the possibility of fed-batch operation and automatic control of pH and oxygen delivery. With operating conditions for large scale biopharmaceutical production properly scaled down, micro bioreactors such as the ambr15™ can potentially be used to predict the effect of process changes such as modified media or different cell lines. In this study, gassing rates and dilution rates were varied for a semi-continuous cell culture system in the ambr15™ bioreactor. The corresponding changes to metabolite production and consumption, as well as cell growth rate and therapeutic protein production were measured. Conditions were identified in the ambr15™ bioreactor that produced metabolic shifts and specific metabolic and protein production rates also seen in the corresponding larger (5 liter) scale perfusion process. A Dynamic Flux Balance model was employed to understand and predict the metabolic changes observed. The DFB model-predicted trends observed experimentally, including lower specific glucose consumption when CO₂ was maintained at higher levels (i.e. 100 mm Hg) in the broth. A Computational Fluid Dynamic (CFD) model of the ambr15™ was also developed, to understand transfer of O₂ and CO₂ to the liquid. This CFD model predicted gas-liquid flow in the bioreactor using the ANSYS software. The two-phase flow equations were solved via an Eulerian method, with population balance equations tracking the size of the gas bubbles resulting from breakage and coalescence. Reasonable results were obtained in that the Carbon Dioxide mass transfer coefficient (kLa) and the air hold up increased with higher gas flow rate. Volume-averaged kLa values at 500 RPM increased as the gas flow rate was doubled and matched experimentally determined values. These results form a solid basis for optimizing the ambr15™, using both CFD and FBA modelling approaches together, for use in microscale simulations of larger scale cell culture processes.

Keywords: cell culture, computational fluid dynamics, dynamic flux balance analysis, microbioreactor

Procedia PDF Downloads 282

Authors: S. Stankov, H. Fidan, N. Petkova, M. Stoyanova, Tz. Radoukova, A. Stoyanova

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The aim of this study was to evaluate the chemical composition of ripe Juniperus excelsa M. Bieb. galbuli (female cones) collected from "Izgoraloto Gyune" Reserve in Krichim, Bulgaria. The moisture (36.88%), abs. weight 693.96 g/1000 pcs., and the ash content (10.57%) of ripe galbuli were determined. Lipid fraction (9.12%), cellulose (13.54%), protein (13.64%), and total carbohydrates (31.20%) were evaluated in the ripe galbuli. It was found that the ripe galbuli contained glucose (4.00%) and fructose (4.25%), but disaccharide sucrose was not identified. The main macro elements presented in the sample were K (8390.00 mg/kg), Ca (4596.00 g/kg), Mg (837.72 mg/kg), followed by Na (7.69 mg/kg); while the detected microelements consisted of Zn (8.51 mg/kg), Cu (4.66 mg/kg), Mn (3.65 mg/kg), Fe (3.26 mg/kg), Cr (3.00 mg/kg), Cd (< 0.1 mg/kg), and Pb (0.01 mg/kg).

Keywords: chemical composition, Juniperus excelsa M. Bieb, minerals, ripe galbuli

Procedia PDF Downloads 149