Search results for: discovery

Authors: Yulan Wu

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With the rapid development of social media, the issue of fake news has gained considerable prominence, drawing the attention of both the public and governments. The widespread dissemination of false information poses a tangible threat across multiple domains of society, including politics, economy, and health. However, much research has concentrated on supervised training models within specific domains, their effectiveness diminishes when applied to identify fake news across multiple domains. To solve this problem, some approaches based on domain labels have been proposed. By segmenting news to their specific area in advance, judges in the corresponding field may be more accurate on fake news. However, these approaches disregard the fact that news records can pertain to multiple domains, resulting in a significant loss of valuable information. In addition, the datasets used for training must all be domain-labeled, which creates unnecessary complexity. To solve these problems, an unsupervised domain knowledge discovery framework for fake news detection is proposed. Firstly, to effectively retain the multidomain knowledge of the text, a low-dimensional vector for each news text to capture domain embeddings is generated. Subsequently, a feature extraction module utilizing the unsupervisedly discovered domain embeddings is used to extract the comprehensive features of news. Finally, a classifier is employed to determine the authenticity of the news. To verify the proposed framework, a test is conducted on the existing widely used datasets, and the experimental results demonstrate that this method is able to improve the detection performance for fake news across multiple domains. Moreover, even in datasets that lack domain labels, this method can still effectively transfer domain knowledge, which can educe the time consumed by tagging without sacrificing the detection accuracy.

Keywords: fake news, deep learning, natural language processing, multiple domains

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Authors: Amna J. Ghith, Khaled Abu Zid, Khairia Youssef, Nasser Saad

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Backgrounds: The multikinase and vascular endothelial growth factor (VEGF) receptor inhibitors interrupt the pathway by which angiogenesis becomes established and promulgated, resulting in the inadequate nourishment of metastatic disease. VEGFR-2 has been the principal target of anti-angiogenic therapies. We disclose the new thieno pyrimidines as inhibitors of VEGFR-2 designed by a molecular modeling approach with increased synergistic activity and decreased side effects. Purpose: 2-substituted thieno pyrimidines are designed and synthesized with anticipated anticancer activity based on its in silico molecular docking study that supports the initial pharmacophoric hypothesis with a same binding mode of interaction at the ATP-binding site of VEGFR-2 (PDB 2QU5) with high docking score. Methods: A series of compounds were designed using discovery studio 4.1/CDOCKER with a rational that mimic the pharmacophoric features present in the reported active compounds that targeted VEGFR-2. An in silico ADMET study was also performed to validate the bioavailability of the newly designed compounds. Results: The Compounds to be synthesized showed interaction energy comparable to or within the range of the benzimidazole inhibitor ligand when docked with VEGFR-2. ADMET study showed comparable results most of the compounds showed absorption within (95-99) zone varying according to different substitutions attached to thieno pyrimidine ring system. Conclusions: A series of 2-subsituted thienopyrimidines are to be synthesized with anticipated anticancer activity and according to docking study structure requirement for the design of VEGFR-2 inhibitors which can act as powerful anticancer agents.

Keywords: docking, discovery studio 4.1/CDOCKER, heterocycles based anticancer agents, 2-subsituted thienopyrimidines

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Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

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Authors: S. Ahmed John

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Marine forms-bacteria, actinobacteria, cynobacteria, fungi, microalgae, seaweeds mangroves and other halophytes an extremely important oceanic resources and constituting over 90% of the oceanic biomass. The marine natural products have lead to the discovery of many compounds considered worthy for clinical applications. The marine sources have the highest probability of yielding natural products. Natural derivatives play an important role to prevent the cancer incidences as synthetic drug transformation in mangrove. 28.12% of anticancer compound extracted from the mangroves. Exchocaria agollocha has the anti cancer compounds. The present investigation reveals the potential of the Exchocaria agollocha with biotechnological applications for anti cancer, antimicrobial drug discovery, environmental remediation, and developing new resources for the industrial process. The anti-cancer activity of Exchocaria agollocha was screened from 3.906 to 1000 µg/ml of concentration with the dilution leads to 1:1 to 1:128 following methanol and chloroform extracts. The cell viability in the Exchocaria agollocha was maximum at the lower concentration where as low at the higher concentration of methanol and chloroform extracts when compare to control. At 3.906 concentration, 85.32 and 81.96 of cell viability was found at 1:128 dilution of methanol and chloroform extracts respectively. At the concentration of 31.25 following 1:16 dilution, the cell viability was 65.55 in methanol and 45.55 in chloroform extracts. However, at the higher concentration, the cell viability 22.35 and 8.12 was recorded in the extracts of methanol and chloroform. The cell viability was more in methanol when compare to chloroform extracts at lower concentration. The present findings gives current trends in screening and the activity analysis of metabolites from mangrove resources and to expose the models to bring a new sustain for tackling cancer. Bioactive compounds of Exchocaria agollocha have extensive use in treatment of many diseases and serve as a compound and templates for synthetic modification.

Keywords: bio-active product, compounds, natural products and microalgae

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Authors: Dmitry K. Shaytan, Georgy D. Laptev

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In our research we aimed to test a managerial approach for the fuzzy front end (FFE) of innovation by creating controlled experiment/ business case in a breakthrough innovation development. The experiment was in the sport industry and covered all aspects of the customer discovery stage from ideation to prototyping followed by patent application. In the paper we describe and analyze mile stones, tasks, management challenges, decisions made to create the break through innovation, evaluate overall managerial efficiency that was at the considered FFE stage. We set managerial outcome of the FFE stage as a valid product concept in hand. In our paper we introduce hypothetical construct “Q-factor” that helps us in the experiment to distinguish quality of FFE outcomes. The experiment simulated for entrepreneur the FFE of innovation and put on his shoulders responsibility for the outcome of valid product concept. While developing managerial approach to reach the outcome there was a decision to look on product concept from the cognitive psychology and cognitive science point of view. This view helped us to develop the profile of a person whose projection (mental representation) of a new product could optimize for a manager or entrepreneur FFE activities. In the experiment this profile was tested to develop breakthrough innovation for swimmers. Following the managerial approach the product concept was created to help swimmers to feel/sense water. The working prototype was developed to estimate the product concept validity and value added effect for customers. Based on feedback from coachers and swimmers there were strong positive effect that gave high value for customers, and for the experiment – the valid product concept being developed by proposed managerial approach for the FFE. In conclusions there is a suggestion of managerial approach that was derived from experiment.

Keywords: concept development, concept testing, customer discovery, entrepreneurship, entrepreneurial management, idea generation, idea screening, startup management

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Authors: Aliasghar Mehdizadeh Dastjerdi, Francisco Camara Pereira

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The increasing complexity and demand of transport services strains transportation systems especially in urban areas with limited possibilities for building new infrastructure. The solution to this challenge requires changes of travel behavior. One of the proposed means to induce such change is multimodal travel apps. This paper describes a study of the intention to use a real-time multi-modal travel app aimed at motivating travel behavior change in the Greater Copenhagen Region (Denmark) toward promoting sustainable transport options. The proposed app is a multi-faceted smartphone app including both travel information and persuasive strategies such as health and environmental feedback, tailoring travel options, self-monitoring, tunneling users toward green behavior, social networking, nudging and gamification elements. The prospective for mobility management travel apps to stimulate sustainable mobility rests not only on the original and proper employment of the behavior change strategies, but also on explicitly anchoring it on established theoretical constructs from behavioral theories. The theoretical foundation is important because it positively and significantly influences the effectiveness of the system. However, there is a gap in current knowledge regarding the study of mobility-management travel app with support in behavioral theories, which should be explored further. This study addresses this gap by a social cognitive theory‐based examination. However, compare to conventional method in technology adoption research, this study adopts a reverse approach in which the associations between theoretical constructs are explored by Max-Min Hill-Climbing (MMHC) algorithm as a hybrid causal discovery method. A technology-use preference survey was designed to collect data. The survey elicited different groups of variables including (1) three groups of user’s motives for using the app including gain motives (e.g., saving travel time and cost), hedonic motives (e.g., enjoyment) and normative motives (e.g., less travel-related CO2 production), (2) technology-related self-concepts (i.e. technophile attitude) and (3) use Intention of the travel app. The questionnaire items led to the formulation of causal relationships discovery to learn the causal structure of the data. Causal relationships discovery from observational data is a critical challenge and it has applications in different research fields. The estimated causal structure shows that the two constructs of gain motives and technophilia have a causal effect on adoption intention. Likewise, there is a causal relationship from technophilia to both gain and hedonic motives. In line with the findings of the prior studies, it highlights the importance of functional value of the travel app as well as technology self-concept as two important variables for adoption intention. Furthermore, the results indicate the effect of technophile attitude on developing gain and hedonic motives. The causal structure shows hierarchical associations between the three groups of user’s motive. They can be explained by “frustration-regression” principle according to Alderfer's ERG (Existence, Relatedness and Growth) theory of needs meaning that a higher level need remains unfulfilled, a person may regress to lower level needs that appear easier to satisfy. To conclude, this study shows the capability of causal discovery methods to learn the causal structure of theoretical model, and accordingly interpret established associations.

Keywords: travel app, behavior change, persuasive technology, travel information, causality

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Authors: Quyen Vu Dang Ha, Oanh Truong Thi, Thuoc Tran Linh, Kent Carpenter, Thinh Doan Vu, Binh Dang Thuy

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Enzyme restriction site associated DNA (EzRAD) has recently emerged as a promising genomic approach for exploring fish genetic diversity on a genome-wide scale. This is a simplified method for genomic genotyping in non-model organisms and applied for SNPs discovery in the population genetics of freshwater and marine fish in the South of Vietnam. The observations of regional-scale differentiation of commercial freshwater fish (smallscale croakers Boesemania microlepis) and marine fish (emperor Lethrinus lentjan) are clarified. Samples were collected along Hau River and coastal area in the south and center Vietnam. 52 DNA samples from Tra Vinh, An Giang Province for Boesemania microlepis and 34 DNA samples of Lethrinus lentjan from Phu Quoc, Nha Trang, Da Nang Province were used to prepare EzRAD libraries from genomic DNA digested with MboI and Sau3AI. A pooled sample of regional EzRAD libraries was sequenced using the HiSeq 2500 Illumina platform. For Boesemania microlepis, the small scale population different from upstream to downstream of Hau river were detected, An Giang population exhibited less genetic diversity (SNPs per individual from 14 to 926), in comparison to Tra Vinh population (from 11 to 2172). For Lethrinus lentjan, the result showed the minor difference between populations in the Northern and the Southern Mekong River. The numbers of contigs and SNPs vary from 1315 to 2455 and from 7122 to 8594, respectively (P ≤ 0.01). The current preliminary study reveals regional scale population disconnection probably reflecting environmental changing. Additional sampling and EzRad libraries need to be implemented for resource management in the Mekong Delta.

Keywords: Boesemania microlepis, EzRAD, Lethrinus lentjan, SNPs

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Authors: Basiru Amuneni

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Astronomy is one domain with a rise in data. Traditional tools for data management have been employed in the quest for knowledge discovery. However, these traditional tools become limited in the face of big. One means of maximizing knowledge discovery for big data is the use of scientific visualisation. The aim of the work is to explore the possibilities offered by emerging creative technologies of Virtual Reality (VR) systems and game engines to visualize multiwavelength datasets. Game Engines are primarily used for developing video games, however their advanced graphics could be exploited for scientific visualization which provides a means to graphically illustrate scientific data to ease human comprehension. Modern astronomy is now in the era of multiwavelength data where a single galaxy for example, is captured by the telescope several times and at different electromagnetic wavelength to have a more comprehensive picture of the physical characteristics of the galaxy. Visualising this in an immersive environment would be more intuitive and natural for an observer. This work presents a standalone VR application that accesses galaxy FITS files. The application was built using the Unity Game Engine for the graphics underpinning and the OpenXR API for the VR infrastructure. The work used a methodology known as Design Science Research (DSR) which entails the act of ‘using design as a research method or technique’. The key stages of the galaxy modelling pipeline are FITS data preparation, Galaxy Modelling, Unity 3D Visualisation and VR Display. The FITS data format cannot be read by the Unity Game Engine directly. A DLL (CSHARPFITS) which provides a native support for reading and writing FITS files was used. The Galaxy modeller uses an approach that integrates cleaned FITS image pixels into the graphics pipeline of the Unity3d game Engine. The cleaned FITS images are then input to the galaxy modeller pipeline phase, which has a pre-processing script that extracts, pixel, galaxy world position, and colour maps the FITS image pixels. The user can visualise image galaxies in different light bands, control the blend of the image with similar images from different sources or fuse images for a holistic view. The framework will allow users to build tools to realise complex workflows for public outreach and possibly scientific work with increased scalability, near real time interactivity with ease of access. The application is presented in an immersive environment and can use all commercially available headset built on the OpenXR API. The user can select galaxies in the scene, teleport to the galaxy, pan, zoom in/out, and change colour gradients of the galaxy. The findings and design lessons learnt in the implementation of different use cases will contribute to the development and design of game-based visualisation tools in immersive environment by enabling informed decisions to be made.

Keywords: astronomy, visualisation, multiwavelenght dataset, virtual reality

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Authors: Leticia Leandro Rade, Amanda Silva de Sousa, Suman Das, Wesley Generoso, Mayara Chagas Ávila, Plinio Salmazo Vieira, Antonio Bonomi, Gabriela Persinoti, Mario Tyago Murakami, Thomas Michael Makris, Leticia Maria Zanphorlin

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Alkenes have an economic appeal, especially in the biofuels field, since they are precursors for drop-in biofuels production, which have similar chemical and physical properties to the conventional fossil fuels, with no oxygen in their composition. After the discovery of the first P450 CYP152 OleTJE in 2011, reported with its unique property of decarboxylating fatty acids (FA), by using hydrogen peroxide as a cofactor and producing 1-alkenes as the main product, the scientific and technological interest in this family of enzymes vastly increased. In this context, the present work presents a new decarboxylase (OleTRN) with low similarity with OleTJE (32%), its biochemical characterization, and structure elucidation. As main results, OleTRN presented a high yield of expression and purity, optimum reaction conditions at 35 °C and pH from 6.5 to 8.0, and higher specificity for oleic acid. Besides that, structure-guided mutations were performed and according to the functional characterizations, it was observed that some mutations presented different specificity and chemoselectivity by varying the chain-length of FA substrates from 12 to 20 carbons. These results are extremely interesting from a biotechnological perspective as those characteristics could diversify the applications and contribute to designing better cytochrome P450 decarboxylases. Considering that peroxygenases have the potential activity of decarboxylating and hydroxylating fatty acids and that the elucidation of the intriguing mechanistic involved in the decarboxylation preferential from OleTJE is still a challenge, the elucidation of OleTRN structure and the functional characterizations of OleTRN and its mutants contribute to new information about CYP152. Besides that, the work also contributed to the discovery of a new decarboxylase with a different selectivity profile from OleTJE, which allows a wide range of applications.

Keywords: P450, decarboxylases, alkenes, biofuels

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Authors: Sutapa Som Chaudhury, Chitrangada Das Mukhopadhyay

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Alzheimer’s disease is a well-known form of dementia since its discovery in 1906. Current Food and Drug Administration approved medications e.g. cholinesterase inhibitors, memantine offer modest symptomatic relief but do not play any role in disease modification or recovery. In last three decades many small molecules, chaperons, synthetic peptides, partial β-secretase enzyme blocker have been tested for the development of a drug against Alzheimer though did not pass the 3rd clinical phase trials. Here in this study, we designed a PEGylated, aminogenic, tripeptidic polymer with two different molecular weights based on the aggregation prone amino acid sequence 17-20 in amyloid beta (Aβ) 1-42. Being conjugated with poly-ethylene glycol (PEG) which self-assembles into hydrophilic nanoparticles, these PEGylated tripeptides constitute a very good drug delivery system crossing the blood brain barrier while the peptide remains protected from proteolytic degradation and non-specific protein interactions. Moreover, being completely aminogenic they would not raise any side effects. These peptide inhibitors were evaluated for their effectiveness against Aβ42 fibrillation at an early stage of oligomer to fibril formation as well as preformed fibril clearance via Thioflavin T (ThT) assay, dynamic light scattering analyses, atomic force microscopy and scanning electron microscopy. The inhibitors were proved to be safe at a higher concentration of 20µM by the reduction assay of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) dye. Moreover, SHSY5Y neuroblastoma cells have shown a greater survivability when treated with the inhibitors following Aβ42 fibril and oligomer treatment as compared with the control Aβ42 fibril and/or oligomer treated neuroblastoma cells. These make the peptidic inhibitors a promising compound in the aspect of the discovery of alternative medication for Alzheimer’s disease.

Keywords: Alzheimer’s disease, alternative medication, amyloid beta, PEGylated peptide

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Authors: Neelma Ashraf

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Actinomycetes, particularly genus Streptomyces is of great importance due to their role in the discovery of new natural products, particularly antimicrobial secondary metabolites in the medicinal science and biotechnology industry. Different Streptomyces strains were isolated from Helianthus annuus plants and tested for antibacterial and antifungal activities. The most promising five strains were chosen for further investigation, and growth conditions for antibiotic synthesis were optimised. The supernatants were extracted in different solvents, and the extracted products were analyzed using liquid chromatography-mass spectrometry (LC-MS) and biological testing. From one of the potent strains Streptomyces globusus sp. BR123, a compound lavendamycin was identified using these analytical techniques. In addition, this potent strain also produces a strong antifungal polyene compound with a quasimolecular ion of 2072. Streptomyces sp. BR123 was genome sequenced because of its promising antimicrobial potential in order to identify the gene cluster responsible for analyzed compound “lavendamycin”. The genome analysis yielded candidate genes responsible for the production of this potent compound. The genome sequence of 8.15 Mb of Streptomyces sp. isolate BR123 with a GC content of 72.63% and 8103 protein coding genes was attained. Many antimicrobial, antiparasitic, and anticancerous compounds were detected through multiple biosynthetic gene clusters predicted by in-Silico analysis. Though, the novelty of metabolites was determined through the insignificant resemblance with known biosynthetic gene clusters. The current study gives insight into the bioactive potential of Streptomyces sp. isolate BR123 with respect to the synthesis of bioactive secondary metabolites through genomic and spectrometric analysis. Moreover, the comparative genome study revealed the connection of isolate BR123 with other Streptomyces strains, which could expand the knowledge of this genus and the mechanism involved in the discovery of new antimicrobial metabolites.

Keywords: streptomyces, secondary metabolites, genome, biosynthetic gene clusters, high performance liquid chromatography, mass spectrometry

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Authors: Rama Devi Kyatham, D. Ashok, K. S. K. Rao Patnaik, Raju Bathula

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We have shown the importance of pyrazoles as anti-microbial chemical entities. These compounds have generally been considered significant due to their wide range of pharmacological acivities and their discovery motivates new avenues of research.The proposed pyrazoles were synthesized and evaluated for their anti-microbial activities. The Synthesized compounds were analyzed by different spectroscopic methods.

Keywords: pyrazoles, validation, resistant microbial strains, anti-microbial activities

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Authors: S. Reshma Reghu, Shiburaj Sugathan, T. G. Nandu, K. B. Ramesh Kumar, Mathew Dan

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Bacterial diseases are considered to be one of the most prevalent health hazards in the developing world and many bacteria are becoming resistant to existing antibiotics making the treatment ineffective. Thus, it is necessary to find novel targets and develop new antibacterial drugs with a novel mechanism of action. The process of bacterial cell division is a novel and attractive target for new antibacterial drug discovery. FtsZ, a homolog of eukaryotic tubulin, is the major protein of the bacterial cell division machinery and is considered as an important antibacterial drug target. Zingiberaceae, the Ginger family consists of aromatic herbs with creeping rhizomes. Many of these plants have antimicrobial properties.This study aimed to determine the anti-bacterial activity of selected Zingiberaceous plants by targeting bacterial cell division protein, FtsZ. Essential oils and methanol extracts of Amomum ghaticum, Alpinia galanga, Kaempferia galanga, K. rotunda, and Zingiber officinale were tested to find its antibacterial efficiency using disc diffusion method against authentic bacterial strains obtained from MTCC (India). Essential oil isolated from A.galanga and Z.officinale were further assayed for FtsZ inhibition assay following non-radioactive malachite green-phosphomolybdate assay using E. coli FtsZ protein obtained from Cytoskelton Inc., USA. Z.officinale essential oil possess FtsZ inhibitory property. A molecular docking study was conducted with the known bioactive compounds of Z. officinale as ligands with the E. coli FtsZ protein homology model. Some of the major constituents of this plant like catechin, epicatechin, and gingerol possess agreeable docking scores. The results of this study revealed that several chemical constituents in Ginger plants can be utilised as potential source of antibacterial activity and it can warrant further investigation through drug discovery studies.

Keywords: antibacterial, FtsZ, zingiberaceae, docking

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Authors: Rima A. Ajlouni

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The discovery of quasi-periodic structures in material science is revealing an exciting new class of symmetries, which has never been explored before. Due to their unique structural and visual properties, these symmetries are drawing interest from many scientific and design disciplines. Especially, in art and architecture, these symmetries can provide a rich source of geometry for exploring new patterns, forms, systems, and structures. However, the structural systems of these complicated symmetries are still posing a perplexing challenge. While much of their local order has been explored, the global governing system is still unresolved. Understanding their unique global long-range order is essential to their generation and application. The recent discovery of dodecagonal quasi-periodic patterns in historical Islamic architecture is generating a renewed interest into understanding the mathematical principles of traditional Islamic geometry. Astonishingly, many centuries before its description in the modern science, ancient artists, by using the most primitive tools (a compass and a straight edge), were able to construct patterns with quasi-periodic formations. These ancient patterns can be found all over the ancient Islamic world, many of which exhibit formations with 5, 8, 10 and 12 quasi-periodic symmetries. Based on the examination of these historical patterns and derived from the generating principles of Islamic geometry, a global multi-level structural model is presented that is able to describe the global long-range order of dodecagonal quasi-periodic formations in Islamic Architecture. Furthermore, this method is used to construct new quasi-periodic tiling systems as well as generating their deflation and inflation rules. This method can be used as a general guiding principle for constructing infinite patches of dodecagon-based quasi-periodic formations, without the need for local strategies (tiling, matching, grid, substitution, etc.) or complicated mathematics; providing an easy tool for scientists, mathematicians, teachers, designers and artists, to generate and study a wide range of dodecagonal quasi-periodic formations.

Keywords: dodecagonal, Islamic architecture, long-range order, quasi-periodi

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Authors: Salome Labeh

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Diverse Languages that exist in Nigeria, gave rise to the need to choose among these languages, which one or ones to be used as the National Language(s) in Nigeria. The Multilingual Nature of Nigeria has been examined, in relation to the provisional result of 1991 census conducted in Nigeria and the status of language policy in the country, which eventually led to the discovery of the fact that Hausa, Igbo, Yoruba languages have the highest speaker in terms of population, and are already made co-official languages in Nigeria, alongside with English language. Then, these languages should be considered as the National Languages, if eventually a language policy emerges in Nigeria.

Keywords: multilingual, languages, culture, Nigeria

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Authors: Saurabh B. Ganorkar, Atul A. Shirkhedkar

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The need for investigations protecting against toxic impurities though seems to be a primary requirement; the impurities which may prove non - toxic can be explored for their therapeutic potential if any to assist advanced drug discovery. The essential role of pharmaceutical analysis can thus be extended effectively to achieve it. The present study successfully achieved these objectives with characterization of major degradation products as impurities for Zileuton which has been used for to treat asthma since years. The forced degradation studies were performed to identify the potential degradation products using Ultra-fine Liquid-chromatography. Liquid-chromatography-Mass spectrometry (Time of Flight) and Proton Nuclear Magnetic Resonance Studies were utilized effectively to characterize the drug along with five major oxidative and hydrolytic degradation products (DP’s). The mass fragments were identified for Zileuton and path for the degradation was investigated. The characterized DP’s were subjected to In-Silico studies as XP Molecular Docking to compare the gain or loss in binding affinity with 5-Lipooxygenase enzyme. One of the impurity of was found to have the binding affinity more than the drug itself indicating for its potential to be more bioactive as better Antiasthmatic. The close structural resemblance has the ability to potentiate or reduce bioactivity and or toxicity. The chances of being active biologically at other sites cannot be denied and the same is achieved to some extent by predictions for probability of being active with Prediction of Activity Spectrum for Substances (PASS) The impurities found to be bio-active as Antineoplastic, Antiallergic, and inhibitors of Complement Factor D. The toxicological abilities as Ames-Mutagenicity, Carcinogenicity, Developmental Toxicity and Skin Irritancy were evaluated using Toxicity Prediction by Komputer Assisted Technology (TOPKAT). Two of the impurities were found to be non-toxic as compared to original drug Zileuton. As the drugs are purposed and repurposed effectively the impurities can also be; as they can have more binding affinity; less toxicity and better ability to be bio-active at other biological targets.

Keywords: UFLC, LC-MS-TOF, NMR, Zileuton, impurities, toxicity, bio-activity

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Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

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Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

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This article offers a approach to the automatic discovery of semantic concepts and links in the domain of Oil Exploration and Production (E&P). Machine learning methods combined with textual pre-processing techniques were used to detect local patterns in texts and, thus, generate new concepts and new semantic links. Even using more specific vocabularies within the oil domain, our approach has achieved satisfactory results, suggesting that the proposal can be applied in other domains and languages, requiring only minor adjustments.

Keywords: semantic links, data mining, linked data, SKOS

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Authors: Fadia Gafri, Kathryn Mckintosh, Louise Young, Alan Harvey, Simon Mackay, Andrew Paul, Robin Plevin

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Nuclear factor-kappa B (NF-κB) is a ubiquitous transcription factor found originally to play a key role in regulating inflammation. However considerable evidence links this pathway to the suppression of apoptosis, cellular transformation, proliferation and invasion (Aggarwal et al., 2006). Moreover, recent studies have also linked inflammation to cancer progression making NF-κB overall a promising therapeutic target for drug discovery (Dobrovolskaia & Kozlov, 2005). In this study we examined the effect of the natural product canthin-6-one (SU182) as part of a CRUK small molecule drug discovery programme for effects upon the NF-κB pathway. Initial studies demonstrated that SU182 was found to have good potency against the inhibitory kappa B kinases (IKKs) at 30M in vitro. However, at concentrations up to 30M, SU182 had no effect upon TNFα stimulated loss in cellular IκBα or p65 phosphorylation in the keratinocyte cell line NCTC2544. Nevertheless, 30M SU182 reduced TNF-α / PMA-induced NF-κB-linked luciferase reporter activity to (22.9 ± 5%) and (34.6± 3 %, P<0.001) respectively, suggesting an action downstream of IKK signalling. Indeed, SU182 neither decreased NF-κB-DNA binding as assayed by EMSA nor prevented the translocation of p65 (NF-κB) to the nucleus assessed by immunofluorescence and subcellular fractionation. In addition to the inhibition of transcriptional activity of TNFα-induced NF-κB reporter activity SU182 significantly reduced PMA-induced AP-1-linked luciferase reporter activity to about (48± 9% at 30M, P<0.001) . This mode of inhibition was not sufficient to prevent the activation of NF-κB dependent induction of other proteins such as COX-2 and iNOS, or activated MAP kinases (p38, JNK and ERK1/2) in LPS stimulated RAW 264.7 macrophages. Taken together these data indicate the potential for SU182 to interfere with the transcription factors NF-κB and AP-1 at transcriptional level. However, no potential anti-inflammatory effect was indicated, further investigation for other NF-κB dependent proteins linked to survival are also required to identify the exact mechanism of action.

Keywords: Canthin-6-one, NF-κB, AP-1, phosphorylation, Nuclear translocation, DNA-binding activity, inflammatory proteins.

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Authors: Sheraz Gul

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The requirements for progressing a compound to clinical trials is well established and relies on the results from in-vitro and in-vivo animal tests to indicate that it is likely to be safe and efficacious when testing in humans. The typical data package required will include demonstrating compound safety, toxicity, bioavailability, pharmacodynamics (potential effects of the compound on body systems) and pharmacokinetics (how the compound is potentially absorbed, distributed, metabolised and eliminated after dosing in humans). If the desired criteria are met and the compound meets the clinical Candidate criteria and is deemed worthy of further development, a submission to regulatory bodies such as the US Food & Drug Administration for an exploratory Investigational New Drug Study can be made. The purpose of this study is to collect data to establish that the compound will not expose humans to unreasonable risks when used in limited, early-stage clinical studies in patients or normal volunteer subjects (Phase I). These studies are also designed to determine the metabolism and pharmacologic actions of the drug in humans, the side effects associated with increasing doses, and, if possible, to gain early evidence on their effectiveness. In order to reach the above goals, we have developed a pre-clinical high throughput Absorption, Distribution, Metabolism and Excretion–Toxicity (ADME–Toxicity) panel of assays to identify compounds that are likely to meet the Lead and Candidate compound acceptance criteria. This panel includes solubility studies in a range of biological fluids, cell viability studies in cancer and primary cell-lines, mitochondrial toxicity, off-target effects (across the kinase, protease, histone deacetylase, phosphodiesterase and GPCR protein families), CYP450 inhibition (5 different CYP450 enzymes), CYP450 induction, cardio-toxicity (hERG) and gene-toxicity. This panel of assays has been applied to multiple compound series developed in a number of projects delivering Lead and clinical Candidates and examples from these will be presented.

Keywords: absorption, distribution, metabolism and excretion–toxicity , drug discovery, food and drug administration , pharmacodynamics

Procedia PDF Downloads 147

Authors: Alaa Eddien Abdallah, Bajes Yousef Alskarnah

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Ant colony based routing algorithms are known to grantee the packet delivery, but they suffer from the huge overhead of control messages which are needed to discover the route. In this paper we utilize the network nodes positions to group the nodes in connected clusters. We use clusters-heads only on forwarding the route discovery control messages. Our simulations proved that the new algorithm has decreased the overhead dramatically without affecting the delivery rate.

Keywords: ad-hoc network, MANET, ant colony routing, position based routing

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Authors: Yang Yang, Lu Xin

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The study of extant musical sites can provide a side-by-side picture of historical ethnomusicological information. In their data collection on Chinese opera houses, researchers found that one Ming Dynasty opera house reached a width of nearly 18 meters, while all opera houses of the same period and after it was far from such a width, being significantly smaller than 18 meters. The historical transient fluctuations in the data dimension of width that caused Chinese theatres to fluctuate in the absence of construction scale constraints have piqued the interest of researchers as to why there is data variation in width. What factors have contributed to the lack of further expansion in the width of theatres? To address this question, this study used a comparative approach to conduct a venue experiment between this theater stage and another theater stage for non-heritage opera performances, collecting the subjective perceptions of performers and audiences at different theater stages, as well as combining BK Connect platform software to measure data such as echo and delay. From the subjective and objective results, it is inferred that the Chinese ancients discovered and understood the acoustical phenomenon of the Haas effect by exploring the effect of stage width on musical performance and appreciation of listening states during the Ming Dynasty and utilized this discovery to serve music in subsequent stage construction. This discovery marked a node of evolution in Chinese architectural acoustics technology driven by musical demands. It is also instructive to note that, in contrast to many of the world's "unsuccessful civilizations," China can use a combination of heritage and intangible cultural research to chart a clear, demand-driven course for the evolution of human music technology, and that the findings of such research will complete the course of human exploration of music acoustics. The findings of such research will complete the journey of human exploration of music acoustics, and this practical experience can be applied to the exploration and understanding of other musical heritage base data.

Keywords: Haas effect, musical acoustics, history of acoustical technology, Chinese opera stage, structure

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Authors: Fatima Al-Aswadi, Chan Yong

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With the large volume of unstructured data that increases day by day on the web, the motivation of representing the knowledge in this data in the machine processable form is increased. Ontology is one of the major cornerstones of representing the information in a more meaningful way on the semantic Web. The goal of Ontology learning from text is to elicit and represent domain knowledge in the machine readable form. This paper aims to give a follow-up review on the ontology learning systems from text and some of their defects. Furthermore, it discusses how far the ontology learning process will enhance in the future.

Keywords: concept discovery, deep learning, ontology learning, semantic relation, semantic web

Procedia PDF Downloads 478

Authors: Esna B. Buğday, Niray Tunçel

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Spirituality has a motivational influence on consumers' psychological states, lifestyles, and behavioral intentions. Spirituality refers to the feeling that there is a divine power greater than ourselves and a connection among oneself, others, nature, and the sacred. In addition, spirituality concerns the human soul and spirit against the material and physical world and consists of three dimensions: self-discovery, relationships, and belief in a higher power. Of them, self-discovery is to explore the meaning and the purpose of life. Relationships refer to the awareness of the connection between human beings and nature as well as respect for them. In addition, higher power represents the transcendent aspect of spirituality, which means to believe in a holy power that creates all the systems in the universe. Furthermore, a voluntary simplicity lifestyle is (1) to adopt a simple lifestyle by minimizing the attachment to and the consumption of material things and possessions, (2) to have an ecological awareness respecting all living creatures, and (3) to express the desire for exploring and developing the inner life. Voluntary simplicity is a multi-dimensional construct that consists of a desire for a voluntarily simple life (e.g., avoiding excessive consumption), cautious attitudes in shopping (e.g., not buying unnecessary products), acceptance of self-sufficiency (e.g., being self-sufficient individual), and rejection of highly developed functions of products (e.g., preference for simple functioned products). One of the main reasons for living simply is to sustain a spiritual life, as voluntary simplicity provides the space for achieving psychological and spiritual growth, cultivating self-reliance since voluntary simplifier frees themselves from the overwhelming externals and takes control of their daily lives. From this point of view, it is expected that people with a strong sense of spirituality will be likely to adopt a simple lifestyle. In this respect, the study aims to examine the impact of spirituality on consumers' voluntary simple lifestyle tendencies. As consumers' consumption attitudes and behaviors depend on their lifestyles, exploring the factors that lead them to embrace voluntary simplicity significantly predicts their purchase behavior. In this respect, this study presents empirical research based on a data set collected from 478 Turkish consumers through an online survey. First, exploratory factor analysis is applied to the data to reveal the dimensions of spirituality and voluntary simplicity scales. Second, confirmatory factor analysis is conducted to assess the measurement model. Last, the hypotheses are analyzed using partial least square structural equation modeling (PLS-SEM). The results confirm that spirituality's self-discovery and relationships dimensions positively impact both cautious attitudes in shopping and acceptance of self-sufficiency dimensions of voluntary simplicity. In contrast, belief in a higher power does not significantly influence consumers' voluntary simplicity tendencies. Even though there has been theoretical support drawing a positive relationship between spirituality and voluntary simplicity, to the best of the authors' knowledge, this has not been empirically tested in the literature before. Hence, this study contributes to the current knowledge by analyzing the direct influence of spirituality on consumers' voluntary simplicity tendencies. Additionally, analyzing this impact on the consumers of an emerging market is another contribution to the literature.

Keywords: spirituality, voluntary simplicity, self-sufficiency, conscious shopping, Turkish consumers

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Authors: Helena Maragou

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Introducing Toni Morrison’s fiction to a classroom overseas entails a significant pedagogical investment, from monitoring students’ uncertain journey through Morrison’s shifty semantics to filling in the gaps of cultural knowledge and understanding for the students to be able to relate text to context. A rewarding process, as Morrison’s works present a tremendous opportunity for transnational dialogue, an opportunity that hinges upon Toni Morrison’s bringing to the fore the untold and unspeakable lives of racial ‘Others’, but also, crucially, upon her broader critique of Western ideological hegemony. This critique is a fundamental aspect of Toni Morrison’s politics and one that appeals to young readers of Toni Morrison in Greece at a time when the questioning of institutions and ideological traditions is precipitated by regional and global change. It is more or less self-evident that to help a class of international students get aboard a Morrison novel, an instructor should begin by providing them with cultural context. These days, students’ exposure to Hollywood representations of the African American past and present, as well as the use of documentaries, photography, music videos, etc., as supplementary class material, provide a starting point, a workable historical and cultural framework for textual comprehension. The true challenge, however, lies ahead: it is one thing for students to intellectually grasp the historical hardships and traumas of Morrison’s characters and to even engage in aesthetic appreciation of Morrison’s writing; quite another to relate to her works as articulations of experiences akin to their own. The great challenge, then, is in facilitating students’ discovery of the universal Morrison, the author who speaks across cultures while voicing the untold tales of her own people; this process of discovery entails, on a pedagogical level, that students be guided through the works’ historical context, to plunge into the intricacies of Morrison’s discourse, itself an elaborate linguistic booby trap, so as to be finally brought to reconsider their own historical experiences using the lens of Morrison’s fiction. The paper will be based on experience of teaching a Toni Morrison seminar to a class of Greek students at the American College of Greece and will draw from students’ exposure and responses to Toni Morrison’s “Nobel Prize Lecture,” as well as her novels Song of Solomon and Home.

Keywords: toni morrison, international classroom, pedagogy, African American literature

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Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservice architectures are increasingly in distributed cloud applications due to the advantages on the software composition, development speed, release cycle frequency and the business logic time to market. On the other hand, these architectures also introduce some challenges on the testing and release phases of applications. Container technology solves some of these issues by providing reproducible environments, easy of software distribution and isolation of processes. However, there are other issues that remain unsolved in current container technology when dealing with multiple machines, such as networking for multi-host communication, service discovery, load balancing or data persistency (even though some of these challenges are already solved by traditional cloud vendors in a very mature and widespread manner). Container cluster management tools, such as Kubernetes, Mesos or Docker Swarm, attempt to solve these problems by introducing a new control layer where the unit of deployment is the container (or the pod — a set of strongly related containers that must be deployed on the same machine). These tools are complex to configure and manage and they do not follow a pure immutable infrastructure approach since servers are reused between deployments. Indeed, these tools introduce dependencies at execution time for solving networking or service discovery problems. If an error on the control layer occurs, which would affect running applications, specific expertise is required to perform ad-hoc troubleshooting. As a consequence, it is not surprising that container cluster support is becoming a source of revenue for consulting services. This paper presents i2kit, a deployment tool based on the immutable infrastructure pattern, where the virtual machine is the unit of deployment. The input for i2kit is a declarative definition of a set of microservices, where each microservice is defined as a pod of containers. Microservices are built into machine images using linuxkit —- a tool for creating minimal linux distributions specialized in running containers. These machine images are then deployed to one or more virtual machines, which are exposed through a cloud vendor load balancer. Finally, the load balancer endpoint is set into other microservices using an environment variable, providing service discovery. The toolkit i2kit reuses the best ideas from container technology to solve problems like reproducible environments, process isolation, and software distribution, and at the same time relies on mature, proven cloud vendor technology for networking, load balancing and persistency. The result is a more robust system with no learning curve for troubleshooting running applications. We have implemented an open source prototype that transforms i2kit definitions into AWS cloud formation templates, where each microservice AMI (Amazon Machine Image) is created on the fly using linuxkit. Even though container cluster management tools have more flexibility for resource allocation optimization, we defend that adding a new control layer implies more important disadvantages. Resource allocation is greatly improved by using linuxkit, which introduces a very small footprint (around 35MB). Also, the system is more secure since linuxkit installs the minimum set of dependencies to run containers. The toolkit i2kit is currently under development at the IMDEA Software Institute.

Keywords: container, deployment, immutable infrastructure, microservice

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Authors: Sundaram Arulmozhiraja, Kanade Shimizu, Yuta Yamamoto, Satoshi Ichikawa, Maenaka Katsumi, Hiroaki Tokiwa

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Drug discovery is shifting from small molecule based drugs targeting local active site to middle molecules (MM) targeting large, flat, and groove-shaped binding sites, for example, protein-protein interface because at least half of all targets assumed to be involved in human disease have been classified as “difficult to drug” with traditional small molecules. Hence, MMs such as peptides, natural products, glycans, nucleic acids with various high potent bioactivities become important targets for drug discovery programs in the recent years as they could be used for ‘undruggable” intracellular targets. Cell membrane permeability is one of the key properties of pharmacodynamically active MM drug compounds and so evaluating this property for the potential MMs is crucial. Computational prediction for cell membrane permeability of molecules is very challenging; however, recent advancement in the molecular dynamics simulations help to solve this issue partially. It is expected that MMs with high membrane permeability will enable drug discovery research to expand its borders towards intracellular targets. Further to understand the chemistry behind the permeability of MMs, it is necessary to investigate their conformational changes during the permeation through membrane and for that their interactions with the membrane field should be studied reliably because these interactions involve various non-bonding interactions such as hydrogen bonding, -stacking, charge-transfer, polarization dispersion, and non-classical weak hydrogen bonding. Therefore, parameters-based classical mechanics calculations are hardly sufficient to investigate these interactions rather, quantum mechanical (QM) calculations are essential. Fragment molecular orbital (FMO) method could be used for such purpose as it performs ab initio QM calculations by dividing the system into fragments. The present work is aimed to study the cell permeability of middle molecules using molecular dynamics simulations and FMO-QM calculations. For this purpose, a natural compound syringolin and its analogues were considered in this study. Molecular simulations were performed using NAMD and Gromacs programs with CHARMM force field. FMO calculations were performed using the PAICS program at the correlated Resolution-of-Identity second-order Moller Plesset (RI-MP2) level with the cc-pVDZ basis set. The simulations clearly show that while syringolin could not permeate the membrane, its selected analogues go through the medium in nano second scale. These correlates well with the existing experimental evidences that these syringolin analogues are membrane-permeable compounds. Further analyses indicate that intramolecular -stacking interactions in the syringolin analogues influenced their permeability positively. These intramolecular interactions reduce the polarity of these analogues so that they could permeate the lipophilic cell membrane. Conclusively, the cell membrane permeability of various middle molecules with potent bioactivities is efficiently studied using molecular dynamics simulations. Insight of this behavior is thoroughly investigated using FMO-QM calculations. Results obtained in the present study indicate that non-bonding intramolecular interactions such as hydrogen-bonding and -stacking along with the conformational flexibility of MMs are essential for amicable membrane permeation. These results are interesting and are nice example for this theoretical calculation approach that could be used to study the permeability of other middle molecules. This work was supported by Japan Agency for Medical Research and Development (AMED) under Grant Number 18ae0101047.

Keywords: fragment molecular orbital theory, membrane permeability, middle molecules, molecular dynamics simulation

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Authors: Ugo Rovigatti

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Neuroblastoma (NBL) has epitomized for at least 40 years our understanding of cancer cellular and molecular biology and its potential applications to novel therapeutic strategies. This includes the discovery of the very first oncogene aberrations and tumorigenesis suppression by differentiation in the 80s; the potential role of suppressor genes in the 90s; the relevance of immunotherapy in the millennium first, and the discovery of additional mutations by NGS technology in the millennium second decade. Similar discoveries were achieved in the majority of human cancers, and similar therapeutic interventions were obtained subsequently to NBL discoveries. Unfortunately, targeted therapies suggested by specific mutations (such as MYCN amplification –MNA- present in ¼ or 1/5 of cases) have not elicited therapeutic successes in aggressive NBL, where the prognosis is still dismal. The reasons appear to be linked to Tumor Heterogeneity, which is particularly evident in NBL but also a clear hallmark of aggressive human cancers generally. The new avenue of cancer immunotherapy (CIT) provided new hopes for cancer patients, but we still ignore the cellular or molecular targets. CIT is emblematic of high-risk disease (HR-NBL) since the mentioned GD2 passive immunotherapy is still providing better survival. We recently critically reviewed and evaluated the literature depicting the genomic landscapes of HR-NBL, coming to the qualified conclusion that among hundreds of affected genes, potential targets, or chromosomal sites, none correlated with anti-GD2 sensitivity. A better explanation is provided by the Micro-Foci inducing Virus (MFV) model, which predicts that neuroblasts infection with the MFV, an RNA virus isolated from a cancer-cluster (space-time association) of HR-NBL cases, elicits the appearance of MNA and additional genomic aberrations with mechanisms resembling chromothripsis. Neuroblasts infected with low titers of MFV amplified MYCN up to 100 folds and became highly transformed and malignant, thus causing neuroblastoma in young rat pups of strains SD and Fisher-344 and larger tumor masses in nu/nu mice. An association was discovered with GD2 since this glycosphingolipid is also the receptor for the family of MFV virus (dsRNA viruses). It is concluded that a dsRNA virus, MFV, appears to provide better explicatory mechanisms for the genesis of i) specific genomic aberrations such as MNA; ii) extensive tumor heterogeneity and chromothripsis; iii) the effects of passive immunotherapy with anti-GD2 monoclonals and that this and similar models should be further investigated in both pediatric and adult cancers.

Keywords: neuroblastoma, MYCN, amplification, viruses, GD2

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Authors: Marina Passero, Tianhua Zhai, Zuyi (Jacky) Huang

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Alzheimer’s disease has become a major public health issue, as indicated by the increasing populations of Americans living with Alzheimer’s disease. After decades of extensive research in Alzheimer’s disease, only seven drugs have been approved by Food and Drug Administration (FDA) to treat Alzheimer’s disease. Five of these drugs were designed to treat the dementia symptoms, and only two drugs (i.e., Aducanumab and Lecanemab) target the progression of Alzheimer’s disease, especially the accumulation of amyloid-b plaques. However, controversial comments were raised for the accelerated approvals of either Aducanumab or Lecanemab, especially with concerns on safety and side effects of these two drugs. There is still an urgent need for further drug discovery to target the biological processes involved in the progression of Alzheimer’s disease. Excessive cholesterol has been found to accumulate in the brain of those with Alzheimer’s disease. Cholesterol can be synthesized in both the blood and the brain, but the majority of biosynthesis in the adult brain takes place in astrocytes and is then transported to the neurons via ApoE. The blood brain barrier separates cholesterol metabolism in the brain from the rest of the body. Various proteins contribute to the metabolism of cholesterol in the brain, which offer potential targets for Alzheimer’s treatment. In the astrocytes, SREBP cleavage-activating protein (SCAP) binds to Sterol Regulatory Element-binding Protein 2 (SREBP2) in order to transport the complex from the endoplasmic reticulum to the Golgi apparatus. Cholesterol is secreted out of the astrocytes by ATP-Binding Cassette A1 (ABCA1) transporter. Lipoprotein receptors such as triggering receptor expressed on myeloid cells 2 (TREM2) internalize cholesterol into the microglia, while lipoprotein receptors such as Low-density lipoprotein receptor-related protein 1 (LRP1) internalize cholesterol into the neuron. Cytochrome P450 Family 46 Subfamily A Member 1 (CYP46A1) converts excess cholesterol to 24S-hydroxycholesterol (24S-OHC). Cholesterol has been approved for its direct effect on the production of amyloid-beta and tau proteins. The addition of cholesterol to the brain promotes the activity of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1), secretase, and amyloid precursor protein (APP), which all aid in amyloid-beta production. The reduction of cholesterol esters in the brain have been found to reduce phosphorylated tau levels in mice. In this work, a computational pipeline was developed to identify the protein targets involved in cholesterol regulation in brain and further to identify chemical compounds as the inhibitors of a selected protein target. Since extensive evidence shows the strong correlation between brain cholesterol regulation and Alzheimer’s disease, a detailed literature review on genes or pathways related to the brain cholesterol synthesis and regulation was first conducted in this work. An interaction network was then built for those genes so that the top gene targets were identified. The involvement of these genes in Alzheimer’s disease progression was discussed, which was followed by the investigation of existing clinical trials for those targets. A ligand-protein docking program was finally developed to screen 1.5 million chemical compounds for the selected protein target. A machine learning program was developed to evaluate and predict the binding interaction between chemical compounds and the protein target. The results from this work pave the way for further drug discovery to regulate brain cholesterol to combat Alzheimer’s disease.

Keywords: Alzheimer’s disease, drug discovery, ligand-protein docking, gene-network analysis, cholesterol regulation

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Authors: Peter Pfeifer, Julian Pfeifer, Niko Pfeifer

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Information processing is the focus of brain and cognition research. This work has a different perspective; it starts with behaviors. The detailed analysis of behaviors leads to the discovery that a significant proportion of them are based on only five basic drives. These basic drives are combinable, and the combinations result in the diversity of human behavior and thinking. The key elements are drive memories. They collect memories of drive-related situations and feelings. They contain variations of basic drives in numerous areas of life and build combinations with different meanings depending on the area. Human thinking could be explained with variations on these nested combinations of basic drives.

Keywords: cognition, psycholinguistics, psychology, psychophysiology of cognition

Procedia PDF Downloads 134