Search results for: encoding and decoding

Authors: Karin Megheșan, Alexandra Popescu, Teodora Dobre

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In the past few years, the Russian Federation has become a central point on the security agenda of the most important international actors, due to its reloaded aggressiveness of foreign policy. Vladimir Putin, the actual president of the Russian Federation, has proven that Russia can and has the willingness to become the powerful actor that used to be during the Cold War. Russia’s new behavior on the international scene showed that Russia has not only expansionist (where expansionist is not only in terms of territory but also of ideology) intentions, but also the necessary resources, to build an empire that may have the power to counterbalance the influence of the United States and stop the expansion of the North-Atlantic Treaty Organization in an equation understood of multipolar Russian view. But in order to do this, there is necessary to follow a well-established plan or policy. Thus, the aim of the paper is to discuss how has the foreign policy of the Russian Federation evolved under the influence of the military and security strategies of the Russian nation, to briefly examine some of the factors that sculpture Russian foreign policy and behavior, in order to reshape a Russian (Soviet) profile so far considered antiquated. Our approach is an argument in favor of the analyses of the recent evolutions embedded in the course of history. In this context, the paper will include analytical thoughts about the Russian foreign policy and the latest strategic documents (security strategy and military doctrine) adopted by the Putin administration, with the purpose to highlight the main direction of action followed by all these documents together. The paper concludes that the military component is to be found in all these strategic documents, as well as at the core of Russian national interest, aspect that proves that Russia is still the adept of the traditional realist paradigm, reshaped in a Russian theory of the multipolar world.

Keywords: hybrid warfare, military component, military doctrine, Russian foreign policy, security strategy

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Authors: Kiyanoush Ghalavand

Abstract:

We have a complex paradox in the agriculture and environment sectors in the age of technology. In the one side, the achievements of the science and information ages are shaping to come that is very dangerous than ever last decades. The progress of the past decades is historic, connecting people, empowering individuals, groups, and states, and lifting a thousand people out of land and poverty in the process. Floods are the most frequent natural hazards damaging and recurring of all disasters in Iran. Additionally, floods are morphing into new and even more devastating forms in recent years. Khuzestan and Lorestan Provinces experienced heavy rains that began on March 28, 2019, and led to unprecedented widespread flooding and landslides across the provinces. The study was based on both secondary and primary data. For the present study, a questionnaire-based primary survey was conducted. Data were collected by using a specially designed questionnaire and other instruments, such as focus groups, interview schedules, inception workshops, and roundtable discussions with stakeholders at different levels. Farmers in Khuzestan and Lorestan provinces were the statistical population for this study. Data were analyzed with several software such as ATLASti, NVivo SPSS Win, ،E-Views. According to a factorial analysis conducted for the present study, 10 groups of factors were categorized climatic, economic, cultural, supportive, instructive, planning, military, policymaking, geographical, and human factors. They estimated 71.6 percent of explanatory factors of flood management obstacles in the agricultural sector in Lorestan and Khuzestan provinces. Several recommendations were finally made based on the study findings.

Keywords: chaos theory, natural hazards, risks, environmental risks, paradox

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Authors: H. Sakamoto, J. Tochimoto, S. Kurosawa, M. Suzuki, S. Oguri

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Salt stress adversely affects plant growth at various stages of development including seed germination, seedling establishment, vegetative growth and finally reproduction. Because of their immobile nature, plants have evolved mechanisms to sense and respond to salt stress. Seed dormancy is an adaptive trait that enables seed germination to coincide with favorable environmental conditions. We identified a novel locus of Arabidopsis, designated SHG1 (salt hypersensitive germination 1), whose disruption leads to reduced germination rate under moderate salt stress conditions. SHG1 encodes a transmembrane protein with an ankyrin repeat motif that has been implicated in diverse cellular processes such as signal transduction. The SGH1-disrupted Arabidopsis mutant died at the cotyledon stage when sown on salt-containing medium, although wild type plants could form true leaves under the same conditions. On the other hand, this mutant showed similar phenotypes to wild type plants when sown on medium without salt and transferred to salt-containing medium at the vegetative stage. These results suggested that SHG1 played indispensable role in the seed germination and seedling establishment under moderate salt stress conditions. SHG1 may be involved in the release of seed dormancy.

Keywords: germination, ankyrin repeat, arabidopsis, salt tolerance

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Authors: X. Laurent, M. A. Estevez, P. Mari-Beffa

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A focus of recent research is to understand the role of our own response goals in the selection of information that will be encoded in episodic memory. For example, if we respond to a target in the presence of distractors, an important aspect under study is whether the distractor and the target share a common response (compatible) or not (incompatible). Some studies have found that compatible objects tend to be groups together and stored in episodic memory, whereas others found that targets in the presence of incompatible distractors are remembered better. Our current research seems to support both views. We used a Tulving-based definition of episodic memory to differentiate memory from episodic and non-episodic traces. In this task, participants first had to classify a blue object as human or animal (target) which appeared in the presence of a green one (distractor) that could belong to the same category of the target (compatible), to the opposite (incompatible) or to an irrelevant one (neutral). Later they had to report the identity (What), location (Where) and time (When) of both target objects (which had been previously responded to) and distractors (which had been ignored). Episodic memory was inferred when the three scene properties (identity, location and time) were correct. The measure of non-episodic memory consisted of those trials in which the identity was correctly remembered, but not the location or time. Our results showed that episodic memory for compatible stimuli is significantly superior to incompatible ones. In sharp contrast, non-episodic measures found superior memory for targets in the presence of incompatible distractors. Our results demonstrate that response compatibility affects the encoding of episodic and non-episodic memory traces in different ways.

Keywords: episodic memory, action systems, compatible response, what-where-when task

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Authors: Zhou Yang, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is essential in a multitude of ways in modern urban life. The researchers of earlier work in this domain carry out the investigation chiefly with two major focuses: (1) the accurate forecast of future values in multiple time series and (2) knowledge extraction from spatial-temporal correlations. However, two key considerations for traffic prediction are often missed: the completeness of raw data and the full context of the prediction timestamp. Concentrating on the two drawbacks of earlier work, we devise an approach that can address these issues in a two-phase framework. First, we utilize the raw trajectories to a greater extent through building a VLA table and data compression. We obtain the intra-trajectory features with graph-based encoding and the intertrajectory ones with a grid-based model and the technique of back projection that restore their surrounding high-resolution spatial-temporal environment. To the best of our knowledge, we are the first to study direct feature extraction from raw trajectories for traffic prediction and attempt the use of raw data with the least degree of reduction. In the prediction phase, we provide a broader context for the prediction timestamp by taking into account the information that are around it in the training dataset. Extensive experiments on several well-known datasets have verified the effectiveness of our solution that combines the strength of raw trajectory data and prediction context. In terms of performance, our approach surpasses several state-of-the-art methods for traffic prediction.

Keywords: traffic prediction, raw data utilization, context building, data reduction

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Authors: Jake Gonzalez, Tommy Dang

Abstract:

This paper proposes a temporal graph approach to visualize and analyze the evolution of gene relationships and nomenclature over time. An interactive web-based tool implements this temporal graph, enabling researchers to traverse a timeline and observe coupled dynamics in network topology and naming conventions. Analysis of a real human genomic dataset reveals the emergence of densely interconnected functional modules over time, representing groups of genes involved in key biological processes. For example, the antimicrobial peptide DEFA1A3 shows increased connections to related alpha-defensins involved in infection response. Tracking degree and betweenness centrality shifts over timeline iterations also quantitatively highlight the reprioritization of certain genes’ topological importance as knowledge advances. Examination of the CNR1 gene encoding the cannabinoid receptor CB1 demonstrates changing synonymous relationships and consolidating naming patterns over time, reflecting its unique functional role discovery. The integrated framework interconnecting these topological and nomenclature dynamics provides richer contextual insights compared to isolated analysis methods. Overall, this temporal graph approach enables a more holistic study of knowledge evolution to elucidate complex biology.

Keywords: temporal graph, gene relationships, nomenclature evolution, interactive visualization, biological insights

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Authors: Manaphol Kulpraneet, Anirut Limtrakul, Surangrat Srisurapanon, Piyatida Tangteerawatana

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Tuberculosis (TB) remains a global health care disease world-wide. Control of the global TB epidemic has been impaired by the lack of an effective vaccine, by the emergence of drug resistant forms of Mycobacterium tuberculosis and by lack of sensitive and rapid diagnostics. Cytokines play a major role in defense against M. tuberculosis infection. Polymorphisms in the genes encoding various cytokines have been associated with tuberculosis susceptibility. Polymorphisms of the regulatory cytokine gene, the interleukin (IL)-10 is associated with the risk of tuberculosis (TB) in different populations. However, IL-10 gene polymorphism and susceptibility to TB in Thai is still unknown. The purpose of this study was to evaluate whether the common IL-10 promoter gene polymorphisms are associated with TB in Thai population. Forty eight patients with newly diagnosed pulmonary tuberculosis were studied. DNA samples were extracted from leukocytes and used to investigate -1087A/G, -819C/T, -252C/A (rs1800896, rs1800871, rs1800872) in IL-10 gene using restriction fragment length polymorphism (PCR-RFLP) methods. In this study, the genotype and allele frequencies of IL-10-1087A/G, -819C/T, -252C/A polymorphism did not significantly different between TB patients and healthy controls ((genotype: p=0.38, p=0.92, p=1; allele: p=0.57, p=0.77, p=0.89, respectively). The lack of association between common IL-10 promoter polymorphisms and TB susceptibility in this study may provide clue for better understanding of IL-10-1087A/G, -819C/T, -252C/A polymorphism and TB susceptibility in Thai population, which might facilitate the rationale design of vaccines. However, further studies in large scales population are required for confirmation.

Keywords: IL-10, cytokines, single nucleotide polymorphism (SNP), tuberculosis

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Authors: Abbas Raza Ali

Abstract:

Big Data technology is gradually becoming a dire need of large enterprises. These enterprises are generating massively large amount of off-line and streaming data in both structured and unstructured formats on daily basis. It is a challenging task to effectively extract useful insights from the large scale datasets, even though sometimes it becomes a technology constraint to manage transactional data history of more than a few months. This paper presents a framework to efficiently manage massively large and complex datasets. The framework has been tested on a communication service provider producing massively large complex streaming data in binary format. The communication industry is bound by the regulators to manage history of their subscribers’ call records where every action of a subscriber generates a record. Also, managing and analyzing transactional data allows service providers to better understand their customers’ behavior, for example, deep packet inspection requires transactional internet usage data to explain internet usage behaviour of the subscribers. However, current relational database systems limit service providers to only maintain history at semantic level which is aggregated at subscriber level. The framework addresses these challenges by leveraging Big Data technology which optimally manages and allows deep analysis of complex datasets. The framework has been applied to offload existing Intelligent Network Mediation and relational Data Warehouse of the service provider on Big Data. The service provider has 50+ million subscriber-base with yearly growth of 7-10%. The end-to-end process takes not more than 10 minutes which involves binary to ASCII decoding of call detail records, stitching of all the interrogations against a call (transformations) and aggregations of all the call records of a subscriber.

Keywords: big data, communication service providers, enterprise data warehouse, stream computing, Telco IN Mediation

Procedia PDF Downloads 175

Authors: Yuxi Liu, Boris Belousov, Mehrzad Esmaeili Charkhab, Oliver Tessmann

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This paper presents a computational solution for designing reconfigurable interlocking structures that are fully assembled with SL Blocks. Formed by S-shaped and L-shaped tetracubes, SL Block is a specific type of interlocking puzzle. Analogous to molecular self-assembly, the aggregation of SL blocks will build a reversible hierarchical and discrete system where a single module can be numerously replicated to compose semi-interlocking components that further align, wrap, and braid around each other to form complex high-order aggregations. These aggregations can be disassembled and reassembled, responding dynamically to design inputs and changes with a unique capacity for reconfiguration. To use these aggregations as architectural structures, we developed computational tools that automate the configuration of SL blocks based on architectural design objectives. There are three critical phases in our work. First, we revisit the hierarchy of the SL block system and devise a top-down-type design strategy. From this, we propose two key questions: 1) How to translate 3D polyominoes into SL block assembly? 2) How to decompose the desired voxelized shapes into a set of 3D polyominoes with interlocking joints? These two questions can be considered the Hamiltonian path problem and the 3D polyomino tiling problem. Then, we derive our solution to each of them based on two methods. The first method is to construct the optimal closed path from an undirected graph built from the voxelized shape and translate the node sequence of the resulting path into the assembly sequence of SL blocks. The second approach describes interlocking relationships of 3D polyominoes as a joint connection graph. Lastly, we formulate the desired shapes and leverage our methods to achieve their reconfiguration within different levels. We show that our computational strategy will facilitate the efficient design of hierarchical interlocking structures with a self-replicating geometric module.

Keywords: computational design, SL-blocks, 3D polyomino puzzle, combinatorial problem

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Authors: Adriane Orenha-Ottaiano

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Collocations are conventionalized, recurrent and arbitrary lexical combinations. Due to the fact that they are highly specific for a particular language and may be contextually restricted, collocations pose a problem to EFL/ESL learners with regard to production or encoding. Taking that into account, the compilation of monolingual and bilingual collocations dictionaries for the referred audience is highly crucial and significant. Thus, the aim of this paper is to discuss the importance of the compilation of an Online Corpus-based Bilingual Collocations Dictionary, in the English-Portuguese and Portuguese-English directions. On a first phase, with the use of WordSmith Tools, the collocations were extracted from a Translation Learner Corpus (TLC), a parallel corpus made up of university students’ translations in the Portuguese-English direction, with approximately 100,000 words. In a second stage, based on the keywords analyzed from the TLC, more collocational patterns were extracted using the Sketch Engine. In order to include more collocations as well as to ensure dictionary users will have access to more frequent and recurrent collocations, we also use the frequency list from The Corpus of Contemporary American English, with the purpose of extracting more patterns. The dictionary focuses on all types of collocations (verbal, noun, adjectival and adverbial collocations), in order to help the referred audience use them more accurately and productively – so far the dictionary has more than 330 entries, and more than 3,500 collocations extracted. The idea of having the proposed dictionary in online format may allow to incorporate more qualitatively and quantitatively collocational information. Besides, more examples may be included, different from conventional printed collocations dictionaries. Being the first bilingual collocations dictionary in the aforementioned directions, it is hoped to achieve the challenge of meeting learners’ collocational needs as the collocations have been selected according to learners’ difficulties regarding the use of collocations.

Keywords: Corpus-Based Collocations Dictionary, Collocations , Bilingual Collocations Dictionary, Collocational Patterns

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Authors: Abdullah A. Al Qurashi, Hattan A. Hassani, Bader K. Alaslap

Abstract:

Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy (ARVD/C) is an uncommon, inheritable cardiac disorder characterized by the progressive substitution of cardiac myocytes by fibro-fatty tissues. This pathologic substitution predisposes patients to ventricular arrhythmias and right ventricular failure. The underlying genetic defect predominantly involves genes encoding for desmosome proteins, particularly plakophilin-2 (PKP2). These aberrations lead to impaired cell adhesion, heightening the susceptibility to fibrofatty scarring under conditions of mechanical stress. Primarily, ARVD/C affects the right ventricle, but it can also compromise the left ventricle, potentially leading to biventricular heart failure. Clinical presentations can vary, spanning from asymptomatic individuals to those experiencing palpitations, syncopal episodes, and, in severe instances, sudden cardiac death. The establishment of a diagnostic criterion specifically tailored for ARVD/C significantly aids in its accurate diagnosis. Nevertheless, the task of early diagnosis is complicated by the disease's frequently asymptomatic initial stages, and the overall rarity of ARVD/C cases reported globally. In some cases, as exemplified by the adult female patient in this report, the disease may advance to terminal stages, rendering therapies like Ventricular Tachycardia (VT) ablation ineffective. This case underlines the necessity for increased awareness and understanding of ARVD/C to aid in its early detection and management. Through such efforts, we aim to decrease morbidity and mortality associated with this challenging cardiac disorder.

Keywords: arrhythmogenic right ventricular dysplasia, cardiac disease, interventional cardiology, cardiac electrophysiology

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Authors: Sanam Preet Singh

Abstract:

Music in comparison to any other art form is more reactive and alive. It has the capacity to directly interact with the listener's mind and generate an emotional response. All the major research conducted in the area majorly relied on the listener’s perspective to draw an understanding of music and its effects. There is a very small number of studies which focused on the source from which music originates, the music composers. This study aims to understand the process of how music composers understand and perceive emotions and how they translate them into music, in simpler terms how music composers encode their compositions to express determining emotions. One-to-one in-depth semi structured interviews were conducted, with 8 individuals both male and female, who were professional to intermediate-level music composers and Thematic analysis was conducted to derive the themes. The analysis showed that there is no single process on which music composers rely, rather there are combinations of multiple micro processes, which constitute the understanding and translation of emotions into music. In terms of perception of emotions, the role of processes such as Rumination, mood influence and escapism was discovered in the analysis. Unique themes about the understanding of their top down and bottom up perceptions were also discovered. Further analysis also revealed the role of imagination and emotional trigger explaining how music composers make sense of emotions. The translation process of emotions revealed the role of articulation and instrumentalization, in encoding or translating emotions to a composition. Further, applications of the trial and error method, nature influences and flow in the translation process are also discussed. In the end themes such as parallels between musical patterns and emotions, comfort zones and relatability also emerged during the analysis.

Keywords: comfort zones, escapism, flow, rumination

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Authors: Parthiban Srinivasan

Abstract:

With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: Beata Zima, Octavio A. Márquez Reyes, Masoud Mohammadgholiha, Jochen Moll, Luca de Marchi

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This document presents the approach of using compressed sensing in signal encoding and information transferring within a guided wave sensor network, comprised of specially designed frequency steerable acoustic transducers (FSATs). Wave propagation in a damaged plate was simulated using commercial FEM-based software COMSOL. Guided waves were excited by means of FSATs, characterized by the special shape of its electrodes, and modeled using PIC255 piezoelectric material. The special shape of the FSAT, allows for focusing wave energy in a certain direction, accordingly to the frequency components of its actuation signal, which makes available a larger monitored area. The process begins when a FSAT detects and records reflection from damage in the structure, this signal is then encoded and prepared for transmission, using a combined approach, based on Compressed Sensing Matching Pursuit and Quadrature Amplitude Modulation (QAM). After codification of the signal is in binary chars the information is transmitted between the nodes in the network. The message reaches the last node, where it is finally decoded and processed, to be used for damage detection and localization purposes. The main aim of the investigation is to determine the location of detected damage using reconstructed signals. The study demonstrates that the special steerable capabilities of FSATs, not only facilitate the detection of damage but also permit transmitting the damage information to a chosen area in a specific direction of the investigated structure.

Keywords: data compression, ultrasonic communication, guided waves, FEM analysis

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Authors: Kyung-Tae Lee, Li Li Wang, Kwang-Woo Jung, Yong-Sun Bahn

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Microtubules are involved in mechanical support, cytoplasmic organization as well as in a number of cellular processes by interacting with diverse microtubule-associated proteins (MAPs), such as plus-end tracking proteins, motor proteins, and tubulin-folding cofactors. A common feature of these proteins is the presence of a cytoskeleton-associated protein-glycine-rich (CAP-Gly) domain, which is evolutionarily conserved and generally considered to bind to α-tubulin to regulate functions of microtubules. However, there has been a dearth of research on CAP-Gly proteins in fungal pathogens, including Cryptococcus neoformans, which causes fatal meningoencephalitis globally. In this study, we identified five CAP-Gly proteins encoding genes in C. neoformans. Among these, Cgp1, encoded by CNAG_06352, has a unique domain structure that has not been reported before in other eukaryotes. Supporting the role of Cpg1 in microtubule-related functions, we demonstrate that deletion or overexpression of CGP1 alters cellular susceptibility to thiabendazole, a microtubule destabilizer, and Cgp1 is co-localized with cytoplasmic microtubules. Related to the cellular functions of microtubules, Cgp1 also governs maintenance of membrane stability and genotoxic stress responses. Furthermore, we demonstrate that Cgp1 uniquely regulates sexual differentiation of C. neoformans with distinct roles in the early and late stage of mating. Our domain analysis reveals that the CAP-Gly domain plays major roles in all the functions of Cgp1. Finally, the cgp1Δ mutant is attenuated in virulence. In conclusion, this novel CAP-Gly protein, Cgp1, has pleotropic roles in regulating growth, stress responses, differentiation and pathogenicity of C. neoformans.

Keywords: human fungal pathogen, CAP-Glycine protein, microtubule, meningoencephalitis

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Authors: Madhuri Goswami

Abstract:

The matrix of power establishes the hegemonic dominance and supremacy of one group through exercising repression and relegation upon the other. However, the injustice done to any race, ethnicity, or caste has instigated the protest and resistance through various modes -social campaigns, political movements, literary expression and so on. Consequently, the search for identity, the means of claiming it and strive for recognition have evolved as the persistent phenomena all through the world. In the discourse of protest and minority literature, these two discourses -African American and Indian Dalit- surprisingly, share wrath and anger, hope and aspiration, and quest for identity and struggle for self-assertion. African American and Indian Dalit are two geographically and culturally apart communities that stand together on a single platform. This paper has sought to comprehend the form and investigate the formation of identity in general and in the literary work of Toni Morrison and Indian Dalit writing, particular, i.e., Black identity and Dalit identity. The study has speculated two types of identity, namely, individual or self and social or collective identity in the literary province of these marginalized literature. Morrison’s work outsources that self-identity is not merely a reflection of an inner essence; it is constructed through social circumstances and relations. Likewise, Dalit writings too have a fair record of discovery of self-hood and formation of identity, which connects to the realization of self-assertion and worthiness of their culture among Dalit writers. Bama, Pawar, Limbale, Pawde, and Kamble investigate their true self concealed amid societal alienation. The study has found that the struggle for recognition is, in fact, the striving to become the definer, instead of just being defined; and, this striving eventually, leads to the introspection among them. To conclude, Morrison as well as Indian marginalized authors, despite being set quite distant, communicate the relation between individual and community in the context of self-consciousness, self-identification and (self) introspection. This research opens a scope for further research to find out similar phenomena and trace an analogy in other world literatures.

Keywords: identity, introspection, self-access, struggle for recognition

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Authors: Fahad Almehmadi, Abdullah Alrajhi, Bader K. Alaslab, Abdullah A. Al Qurashi, Hattan A. Hassani

Abstract:

Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy (ARVD/C) is an uncommon, inheritable cardiac disorder characterized by the progressive substitution of cardiac myocytes by fibro-fatty tissues. This pathologic substitution predisposes patients to ventricular arrhythmias and right ventricular failure. The underlying genetic defect predominantly involves genes encoding for desmosome proteins, particularly plakophilin-2 (PKP2). These aberrations lead to impaired cell adhesion, heightening the susceptibility to fibrofatty scarring under conditions of mechanical stress. Primarily, ARVD/C affects the right ventricle, but it can also compromise the left ventricle, potentially leading to biventricular heart failure. Clinical presentations can vary, spanning from asymptomatic individuals to those experiencing palpitations, syncopal episodes, and, in severe instances, sudden cardiac death. The establishment of a diagnostic criterion specifically tailored for ARVD/C significantly aids in its accurate diagnosis. Nevertheless, the task of early diagnosis is complicated by the disease's frequently asymptomatic initial stages, and the overall rarity of ARVD/C cases reported globally. In some cases, as exemplified by the adult female patient in this report, the disease may advance to terminal stages, rendering therapies like Ventricular Tachycardia (VT) ablation ineffective. This case underlines the necessity for increased awareness and understanding of ARVD/C to aid in its early detection and management. Through such efforts, we aim to decrease morbidity and mortality associated with this challenging cardiac disorder.

Keywords: ARVD/C, cardiology, interventional cardiology, cardiac electrophysiology

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Authors: S. Tebibel, C. Mechati, S. Messaoudi

Abstract:

Algeria is currently experiencing the same rate of cancer progression as that registered these last years in the western countries. Colorectal cancer, constituting increasingly a major public health problem, is the most common form of cancer after breast and Neck-womb cancer at the woman and prostate cancer at the man. Our work is based on a retrospective study to determine the cases of colorectal cancer through eastern Algeria. Our goal is to carry out an epidemiological, histological and immune- histochemical study to investigate different techniques for the diagnosis of colorectal cancer and their interests and specific in detecting the disease. The study includes 110 patients (aged between 20 to 87 years) with colorectal cancer where the inclusions and exclusions criteria were established. In our study, colorectal cancer, expresses a male predominance, with a sex ratio of 1, 99 and the most affected age group is between 50 and 59 years. We noted that the colon cancer rate is higher than rectal cancer rate, whose frequencies are respectively 60,91 % and 39,09 %. In the series of colon cancer, the ADK lieberkunien is histological the most represented type, or 85,07 % of all cases. In contrast, the proportion of ADK mucinous (colloid mucous) is only 1,49% only. Well-differentiated ADKS, are very significant in our series, they represent 83,58 % of cases. Adenocarcinoma moderately and poorly differentiated, whose proportions are respectively 2,99 % and 0.05 %. For histological varieties of rectal ADK, we see in our workforce that ADK lieberkunien represent the most common histological form, or 76,74%, while the mucosal colloid is 13,95 %. Research of the mutation on the gene encoding K-ras, a major step in the targeted therapy of colorectal cancers, is underway in our study. Colorectal cancer is the subject of much promising research concern: the evaluation of new therapies (antiangiogenic monoclonal antibodies), the search for predictors of sensitivity to chemotherapy and new prognostic markers using techniques of molecular biology and proteomics.

Keywords: adenocarcinoma, age, colorectal cancer, epidemiology, histological section, sex

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Authors: Rozeena Shaikh, Syed M Shahid, Jamil Ahmad, Qaisar Mansoor, Muhammad Ismail, Abid Azhar

Abstract:

Introduction: Diabetes mellitus (DM) is a prevalent non-communicable disease worldwide. In most high-income countries as well as middle-income and low- income countries. DM is among the top causes of deaths. DM may lead to many vascular complications like hypertension, nephropathy, retinopathy, neuropathy, and foot. Diabetic nephropathy (DN) characterized by persistent albuminuria is a leading cause of end stage renal failure (ESRF). Pathogenesis of diabetic nephropathy is implicated by the polymorphisms in genes encoding the components of reninangiotensin- aldosteron system (RAAS) which include angiotensinogen (AGT), angiotensin-II receptor and particularly angiotensin converting enzyme (ACE) gene. Method: Study subjects include 110 control, 110 patients with DM without hypertension, 110 patients with DM with hypertension and 110 patients with DN. Blood samples were collected for Biochemical analysis and PCR and sequencing for the specific region of both genes. Results: The frequency of DD genotype and D allele of ACE (I/D) was significantly (p<0.05) high in DM normotensive, DM hypertensive and DN patients when compared to control. The ACE G2350A genotypes and allele frequencies were significantly different (p<0.05) in DM hypertensive patients as compared to control and DN, while no difference was observed between DM normotensive and DN when compared to control. The genotypes and alleles of AGT (M268T) polymorphism were significantly different (p<0.05) in DM normotensive, DM hypertensive and DN when compared to control. Conclusion: The DD genotype and D allele of ACE (I/D), GG genotype and G allele of ACE (G2350A) and the TT genotype and T allele of AGT (M268T) polymorphism have shown a significant difference in genotype and allele frequencies between controls and patients.

Keywords: genetic variations, ACE, AGT, diabetes mellitus, diabetic nephropathy, Pakistan

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Authors: Christina Killian, Katie Wall, Séamus Fanning, Guerrino Macori

Abstract:

Deep-level metagenomics offers a useful technical approach to explore the three dynamic One Health axes: healthcare, domiciliary and veterinary. There is currently limited understanding of the composition of complex biofilms, natural abundance of AMR genes and gene transfer occurrence in these ecological niches. By using a newly established small-scale complex biofilm model, COMBAT has the potential to provide new information on microbial diversity, antimicrobial resistance (AMR)-encoding gene abundance, and their transfer in complex biofilms of importance to these three One Health axes. Shotgun metagenomics has been used to sample the genomes of all microbes comprising the complex communities found in each biofilm source. A comparative analysis between untreated and biocide-treated biofilms is described. The basic steps include the purification of genomic DNA, followed by library preparation, sequencing, and finally, data analysis. The use of long-read sequencing facilitates the completion of metagenome-assembled genomes (MAG). Samples were sequenced using a PromethION platform, and following quality checks, binning methods, and bespoke bioinformatics pipelines, we describe the recovery of individual MAGs to identify mobile gene elements (MGE) and the corresponding AMR genotypes that map to these structures. High-throughput sequencing strategies have been deployed to characterize these communities. Accurately defining the profiles of these niches is an essential step towards elucidating the impact of the microbiota on each niche biofilm environment and their evolution.

Keywords: COMBAT, biofilm, metagenomics, high-throughput sequencing

Procedia PDF Downloads 56

Authors: Alina Goldberg Cavalleri, Sara Franco Ortega, Nawaporn Onkokesung, Richard Dale, Melissa Brazier-Hicks, Robert Edwards

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Non-target site based resistance (NTSR) to herbicides in weeds is a polygenic trait associated with the upregulation of proteins involved in xenobiotic detoxification and translocation we have termed the xenome. Among the xenome proteins, ABC transporters play a key role in enhancing herbicide metabolism by effluxing conjugated xenobiotics from the cytoplasm into the vacuole. The importance of ABC transporters is emphasized by the fact that they often contribute to multidrug resistance in human cells and antibiotic resistance in bacteria. They also play a key role in insecticide resistance in major vectors of human diseases and crop pests. By surveying available databases, transcripts encoding ABCs have been identified as being enhanced in populations exhibiting NTSR in several weed species. Based on a transcriptomics data in black grass (Alopecurus myosuroides, Am), we have identified three proteins from the ABC-C subfamily that are upregulated in NTSR populations. ABC-C transporters are poorly characterized proteins in plants, but in Arabidopsis localize to the vacuolar membrane and have functional roles in transporting glutathionylated (GSH)-xenobiotic conjugates. We found that the up-regulation of AmABCs strongly correlates with the up-regulation of a glutathione transferase termed AmGSTU2, which can conjugate GSH to herbicides. The expression profile of the ABC transcripts was profiled in populations of black grass showing different degree of resistance to herbicides. This, together with a phylogenetic analysis, revealed that AmABCs cluster in different groups which might indicate different substrate and roles in the herbicide resistance phenotype in the different populations

Keywords: black grass, herbicide, resistance, transporters

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Authors: José Eduardo García-Mendiola

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In this work, a phenomenological approach to computational modeling of analogy processing is carried out. The paper goes through the consideration of the structure of the analogy, based on the possibility of sustaining the genesis of its elements regarding Husserl's genetic theory of association. Among particular processes which take place in order to get analogical inferences, there is one which arises crucial for enabling efficient base cases retrieval through long-term memory, namely analogical transference grounded on familiarity. In general, it has been argued that analogical reasoning is a way by which a conscious agent tries to determine or define a certain scope of objects and relationships between them using previous knowledge of other familiar domain of objects and relations. However, looking for a complete description of analogy process, a deeper consideration of phenomenological nature is required in so far, its simulation by computational programs is aimed. Also, one would get an idea of how complex it would be to have a fully computational account of the analogy elements. In fact, familiarity is not a result of a mere chain of repetitions of objects or events but generated insofar as the object/attribute or event in question is integrable inside a certain context that is taking shape as functionalities and functional approaches or perspectives of the object are being defined. Its familiarity is generated not by the identification of its parts or objective determinations as if they were isolated from those functionalities and approaches. Rather, at the core of such a familiarity between entities of different kinds lays the way they are functionally encoded. So, and hoping to make deeper inroads towards these topics, this essay allows us to consider that cognitive-computational perspectives can visualize, from the phenomenological projection of the analogy process reviewing achievements already obtained as well as exploration of new theoretical-experimental configurations towards implementation of analogy models in specific as well as in general purpose machines.

Keywords: analogy, association, encoding, retrieval

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Authors: Jawaher Bakheet Almudarra

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An Educational Supervisor assists teachers to develop their competence and skills in teaching, solving educational problems, and to improve the teaching methods to suit the educational process. They evaluate their teachers and write reports based on their assessments. In 1957, the Saudi Ministry of Education instituted Educational Supervision to facilitate effective management of schools, however, there have been concerns that the Educational Supervision has not been effective in executing its mandate. Studies depicted that Educational supervision has not been effective because it has been marred by poor and autocratic leadership practices such as stringent inspection, commanding and judging. Therefore, there is need to consider some of the ways in which school outcomes can be enhanced through the improvement of Educational supervision practices. Emotional intelligence is a relatively new concept that can be integrated into the Saudi education system that is yet to be examined in-depth and embraced particularly in the realm of educational leadership. Its recognition and adoption may improve leadership practices among Educational supervisors. This study employed a qualitative interpretive approach that will focus on decoding, describing and interpreting the connection between emotional intelligence and leadership. The study also took into account the social constructions that include consciousness, language and shared meanings. The data collection took place in the Office of Educational Supervisors in Riyadh and involved 4 Educational supervisors and 20 teachers from both genders- male and female. The data collection process encompasses three methods namely; qualitative emotional intelligence self-assessment questionnaires, reflective semi-structured interviews, and open workshops. The questionnaires would explore whether the Educational supervisors understand the meaning of emotional intelligence and its significance in enhancing the quality of education system in Saudi Arabia. Subsequently, reflective semi-structured interviews were carried out with the Educational supervisors to explore the connection between their leadership styles and the way they conceptualise their emotionality. The open workshops will include discussions on emotional aspects of Educational supervisors’ practices and how Educational supervisors make use of the emotional intelligence discourse in their leadership and supervisory relationships.

Keywords: directors of educational supervision, emotional intelligence, educational leadership, education management

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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Authors: Safee Chaudhary, Mahnoor Naseer Gondal, Hira Anees Awan, Abdul Rehman, Ammar Arif, Risham Hussain, Huma Khawar, Zainab Arshad, Muhammad Faizyab Ali Chaudhary, Waleed Ahmed, Muhammad Umer Sultan, Bibi Amina, Salaar Khan, Muhammad Moaz Ahmad, Osama Shiraz Shah, Hadia Hameed, Muhammad Farooq Ahmad Butt, Muhammad Ahmad, Sameer Ahmed, Fayyaz Ahmed, Omer Ishaq, Waqar Nabi, Wim Vanderbauwhede, Bilal Wajid, Huma Shehwana, Muhammad Tariq, Amir Faisal

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Cancer is a manifestation of multifactorial deregulations in biomolecular pathways. These deregulations arise from the complex multi-scale interplay between cellular and extracellular factors. Such multifactorial aberrations at gene, protein, and extracellular scales need to be investigated systematically towards decoding the underlying mechanisms and orchestrating therapeutic interventions for patient treatment. In this work, we propose ‘TISON’, a next-generation web-based multiscale modeling platform for clinical systems oncology. TISON’s unique modeling abstraction allows a seamless coupling of information from biomolecular networks, cell decision circuits, extra-cellular environments, and tissue geometries. The platform can undertake multiscale sensitivity analysis towards in silico biomarker identification and drug evaluation on cellular phenotypes in user-defined tissue geometries. Furthermore, integration of cancer expression databases such as The Cancer Genome Atlas (TCGA) and Human Proteome Atlas (HPA) facilitates in the development of personalized therapeutics. TISON is the next-evolution of multiscale cancer modeling and simulation platforms and provides a ‘zero-code’ model development, simulation, and analysis environment for application in clinical settings.

Keywords: systems oncology, cancer systems biology, cancer therapeutics, personalized therapeutics, cancer modelling

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Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

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Authors: Sangyeop Shin, D. C. M. Kulatunga, S. H. S. Dananjaya, Chamilani Nikapitiya, Jehee Lee, Mahanama De Zoysa

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Saprolegniasis is one of the most devastating fungal diseases in freshwater fish which is caused by species in the genus Saprolegnia including Saprolegnia parasitica. In this study, we isolated the strain of S. parasitica from diseased rainbow trout in Korea. Morphological and molecular based identification confirmed that isolated fungi belong to the member of S. parasitica, supported by its typical fungal features including cotton-like whitish mycelium, zoospores (primary and secondary) and phylogenetic analysis with internal transcribed spacer (ITS) region. Pathogenicity of isolated S. parasitica was developed in embryo, larvae, juvenile and adult zebrafish as a disease model. Up regulation of host genes encoding ZfTnf-α, Zfc-Rel, ZfIl-12, ZfLyz-c, Zfβ-def, and ZfHsp-70 was identified in zebrafish larvae after experimental challenge of S. parasitica showing the host immune responses against the S. parasitica. Survival of the juveniles upon fungal infection might be due to the increased immune protection in the host. Investigation of antifungal susceptibility of S. parasitica with natural lawsone (2-hydroxy-1,4-naphthoquinone) revealed the minimum inhibitory concentration (MIC) and percentage inhibition of radial growth (PIRG %) as 200 µg/mL and 31.8%, respectively. Lawsone was able to change the membrane permeability, and cause irreversible damage and disintegration to the cellular membranes of S. parasitica which might have effect on fungi growth inhibition. Moreover, the mycelium exposed to lawsone (MIC level) changed the transcriptional responses of S. parasitica genes. Overall results indicate that lawsone could be a potential and novel anti-S. parasitica agent for controlling S. parasitica infection.

Keywords: host-pathogen interactions, lawsone, rainbow trout, Saprolegnia parasitica, Saprolegniasis, zebrafish

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Authors: Juliana Lukša, Bazilė Ravoitytė, Elena Servienė, Saulius Serva

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Totiviridae L-A virus is a persistent Saccharomyces cerevisiae dsRNA virus. It encodes the major structural capsid protein Gag and Gag-Pol fusion protein, responsible for virus replication and encapsulation. These features also enable the copying of satellite dsRNAs (called M dsRNAs) encoding a secreted toxin and immunity to it (known as killer toxin). Viral capsid pore presumably functions in nucleotide uptake and viral mRNA release. During cell division, sporogenesis, and cell fusion, the virions remain intracellular and are transferred to daughter cells. By employing high throughput RNA sequencing data analysis, we describe the influence of solely L-A virus on the expression of genes in three different S. cerevisiae hosts. We provide a new perception into Totiviridae L-A virus-related transcriptional regulation, encompassing multiple bioinformatics analyses. Transcriptional responses to L-A infection were similar to those induced upon stress or availability of nutrients. It also delves into the connection between the cell metabolism and L-A virus-conferred demands to the host transcriptome by uncovering host proteins that may be associated with intact virions. To better understand the virus-host interaction, we applied differential proteomic analysis of virus particle-enriched fractions of yeast strains that harboreither complete killer system (L-A-lus and M-2 virus), M-2 depleted orvirus-free. Our analysis resulted in the identification of host proteins, associated with structural proteins of the virus (Gag and Gag-Pol). This research was funded by the European Social Fund under the No.09.3.3-LMT-K-712-19-0157“Development of Competences of Scientists, other Researchers, and Students through Practical Research Activities” measure.

Keywords: totiviridae, killer virus, proteomics, transcriptomics

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Authors: Irene Alevizos, Jessica Lewis, Marina Harper, John Boyce

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Acinetobacter baumannii causes a range of severe nosocomial-acquired infections, and many strains are multi-drug resistant. A. baumannii possesses survival mechanisms allowing it to thrive in competitive polymicrobial environments, including a Type VI Secretion System (T6SS) that injects effector proteins into other bacteria to give a competitive advantage. The effects of T6SS firing are broad and depend entirely on the effector that is delivered. Effects can include toxicity against prokaryotic or eukaryotic cells and the acquisition of essential nutrients. The T6SS of some species can deliver ‘specialised effectors’ that are fused directly to T6SS components, such as PAAR proteins. PAAR proteins are predicted to form the piercing tip of the T6SS and are essential for T6SS function. Although no specialised effectors have been identified in A. baumannii, many strains encode multiple PAAR proteins. Analysis of PAAR proteins across the species identified 12 families of PAAR proteins with distinct C-terminal extensions. A. baumannii AB307-0294 encodes two PAAR proteins, one of which has a C-terminal extension. Mutation of one or both of the PAAR-encoding genes in this strain showed that expression of either PAAR protein was sufficient for T6SS function. We employed a heterologous expression approach and determined that PAAR proteins from different A. baumannii strains, as well as the closely related A. baylyi species, could complement the A. baumannii ∆paar mutant and restore T6SS function. Furthermore, we showed that PAAR fusions could be used to deliver artificially cloned protein fragments by generating Histidine- and Streptavidin- tagged PAAR specialised effectors, which restored T6SS activity. This provides evidence that the fusion of protein fragments onto PAAR proteins in A. baumannii is compatible with a functional T6SS. Successful delivery by this mechanism extends the scope of what the T6SS can deliver, including user designed proteins.

Keywords: A. baumannii, effectors, PAAR, T6SS

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Authors: Chutamas Thepmalee, Aussara Panya, Mutita Junking, Jatuporn Sujjitjoon, Nunghathai Sawasdee, Pa-Thai Yenchitsomanus

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Cholangiocarcinoma (CCA) is an aggressive malignancy of bile duct epithelial cells in which the standard treatments, including surgery, radiotherapy, chemotherapy, and targeted therapy are partially effective. Many solid tumors including CCA escape host immune responses by creating tumor microenvironment and generating immunosuppressive cytokines such as interleukin-10 (IL-10) and transforming growth factor-β (TGF-β). These cytokines can inhibit dendritic cell (DC) differentiation and function, leading to decreased activation and response of effector CD4+ and CD8+ T cells for cancer cell elimination. To overcome the effects of these immunosuppressive cytokines and to increase ability of DC to activate effector CD4+ and CD8+ T cells, we generated self-differentiated DCs (SD-DCs) with down-regulation of IL-10 and TGF-β receptors for activation of effector CD4+ and CD8+ T cells. Human peripheral blood monocytes were initially transduced with lentiviral particles containing the genes encoding GM-CSF and IL-4 and then secondly transduced with lentiviral particles containing short-hairpin RNAs (shRNAs) to knock-down mRNAs of IL-10 and TGF-β receptors. The generated SD-DCs showed up-regulation of MHC class II (HLA-DR) and co-stimulatory molecules (CD40 and CD86), comparable to those of DCs generated by convention method. Suppression of IL-10 and TGF-β receptors on SD-DCs by specific shRNAs significantly increased levels of IFN-γ and also increased cytolytic activity of DC-activated effector T cells against CCA cell lines (KKU-213 and KKU-100), but it had little effect to immortalized cholangiocytes (MMNK-1). Thus, SD-DCs with down-regulation of IL-10 and TGF-β receptors increased activation of effector T cells, which is a recommended method to improve DC function for the preparation of DC-activated effector T cells for adoptive T-cell therapy.

Keywords: cholangiocarcinoma, IL-10 receptor, self-differentiated dendritic cells, TGF-β receptor

Procedia PDF Downloads 141