Search results for: Biomarker Discovery

Authors: Indre Brazauskaite, Vilte Auruskeviciene

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Significance of the study is outlined through current strategic management challenges faced by SMEs. First, innovation is recognized as competitive advantage in the market, having ever changing market conditions. It is of constant interest from both practitioners and academics to capture and capitalize on business opportunities or mitigate the foreseen risks. Secondly, it is recognized that integrated system is needed for proper implementation of innovation process, especially during the period of business incubation, associated with relatively high risks of new product failure. Finally, ability to successful commercialize innovations leads to tangible business results that allow to grow organizations further. This is particularly relevant to SMEs due to limited structures, resources, or capabilities. Cooperation between scientific and business institutions could be a tool of mutual interest to observe, address, and further develop innovations during the incubation period, which is the most demanding and challenging during the innovation process. Material aims to address the following problematics: i) indicate the major barriers and challenges in innovation process that SMEs are facing, ii) outline the possibilities for these barriers and challenges to be addressed by cooperation between scientific and business institutions. Basis for this research is stage-by-stage integrated innovation management process which presents existing challenges and needed aid in operational decision making. The stage-by-stage innovation management process exploration highlights relevant research opportunities that have high practical relevance in the field. It is expected to reveal the possibility for business incubation programs that could combine interest from both – practices and academia. Methodology. Scientific meta-analysis of to-date scientific literature that explores innovation process. Research model is built on the combination of stage-gate model and lean six sigma approach. It outlines the following steps: i) pre-incubation (discovery and screening), ii) incubation (scoping, planning, development, and testing), and iii) post-incubation (launch and commercialization) periods. Empirical quantitative research is conducted to address barriers and challenges related to innovation process among SMEs that limits innovations from successful launch and commercialization and allows to identify potential areas for cooperation between scientific and business institutions. Research sample, high level decision makers representing trading SMEs, are approached with structured survey based on the research model to investigate the challenges associated with each of the innovation management step. Expected findings. First, the current business challenges in the innovation process are revealed. It will outline strengths and weaknesses of innovation management practices and systems across SMEs. Secondly, it will present material for relevant business case investigation for scholars to serve as future research directions. It will contribute to a better understanding of quality innovation management systems. Third, it will contribute to the understanding the need for business incubation systems for mutual contribution from practices and academia. It can increase relevance and adaptation of business research.

Keywords: cooperation between scientific and business institutions, innovation barriers and challenges, innovation measure, innovation process, SMEs

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Authors: Narges Bahmanyar, Masoud Ghorbani

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Rabies is caused by several species of the genus Lyssavirus in the Rhabdoviridae family. The disease is deadly encephalitis transmitted from warm-blooded animals to humans, and domestic and wild carnivores play the most crucial role in its transmission. The prevalence of rabies in poor areas of developing salinities is constantly posed as a global threat to public health. According to the World Health Organization, approximately 60,000 people die yearly from rabies. Of these, 60% of deaths are related to the Middle East. Although rabies encephalitis is incurable to date, awareness of the disease and the use of vaccines is the best way to combat the disease. Although effective vaccines are available, there is a high cost involved in vaccine production and management to combat rabies. Increasing the prevalence and discovery of new strains of rabies virus requires the need for safe, effective, and as inexpensive vaccines as possible. One of the approaches considered to achieve the quality and quantity expressed through the manufacture of recombinant types of rabies vaccine. Currently, livestock rabies vaccines are used only in inactivated or live attenuated vaccines, the process of inactivation of which pays attention to considerations. The rabies virus contains a negatively polarized single-stranded RNA genome that encodes the five major structural genes (N, P, M, G, L) from '3 to '5 . Rabies virus glycoprotein G, the major antigen, can produce the virus-neutralizing antibody. N-antigen is another candidate for developing recombinant vaccines. However, because it is within the RNP complex of the virus, the possibility of genetic diversity based on different geographical locations is very high. Glycoprotein G is structurally and antigenically more protected than other genes. Protection at the level of its nucleotide sequence is about 90% and at the amino acid level is 96%. Recombinant vaccines, consisting of a pathogenic subunit, contain fragments of the protein or polysaccharide of the pathogen that have been carefully studied to determine which of these molecules elicits a stronger and more effective immune response. These vaccines minimize the risk of side effects by limiting the immune system's access to the pathogen. Such vaccines are relatively inexpensive, easy to produce, and more stable than vaccines containing viruses or whole bacteria. The problem with these vaccines is that the pathogenic subunits may elicit a weak immune response in the body or may be destroyed before they reach the immune cells, which requires nanoparticles to overcome. Suitable for use as an adjuvant. Among these, biodegradable nanoparticles with functional levels are good candidates as adjuvants for the vaccine. In this study, we intend to use beta-glucan nanoparticles as adjuvants. The surface glycoprotein of the rabies virus (G) is responsible for identifying and binding the virus to the target cell. This glycoprotein is the major protein in the structure of the virus and induces an antibody response in the host. In this study, we intend to use rabies virus surface glycoprotein conjugated with beta-glucan nanoparticles to produce vaccines.

Keywords: rabies, vaccines, beta glucan, nanoprticles, adjuvant, recombinant protein

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Authors: Binder Hans

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Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

Procedia PDF Downloads 148

Authors: Sumeet Rai, Anuj Tyagi, B. T. Naveen Kumar, Shubhkaramjeet Kaur, Niraj K. Singh

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Since their discovery, indiscriminate use of antibiotics in human, veterinary and aquaculture systems has resulted in global emergence/spread of multidrug-resistant bacterial pathogens. Thus, the need for alternative approaches to control bacterial infections has become utmost important. High selectivity/specificity of bacteriophages (phages) permits the targeting of specific bacteria without affecting the desirable flora. In this study, a lytic phage (Ahp1) specific to Aeromonas hydrophila subsp. hydrophila was isolated from finfish aquaculture pond. The host range of Ahp1 range was tested against 10 isolates of A. hydrophila, 7 isolates of A. veronii, 25 Vibrio cholerae isolates, 4 V. parahaemolyticus isolates and one isolate each of V. harveyi and Salmonella enterica collected previously. Except the host A. hydrophila subsp. hydrophila strain, no lytic activity against any other bacterial was detected. During the adsorption rate and one-step growth curve analysis, 69.7% of phage particles were able to get adsorbed on host cell followed by the release of 93 ± 6 phage progenies per host cell after a latent period of ~30 min. Phage nucleic acid was extracted by column purification methods. After determining the nature of phage nucleic acid as dsDNA, phage genome was subjected to next-generation sequencing by generating paired-end (PE, 2 x 300bp) reads on Illumina MiSeq system. De novo assembly of sequencing reads generated circular phage genome of 42,439 bp with G+C content of 58.95%. During open read frame (ORF) prediction and annotation, 22 ORFs (out of 49 total predicted ORFs) were functionally annotated and rest encoded for hypothetical proteins. Proteins involved in major functions such as phage structure formation and packaging, DNA replication and repair, DNA transcription and host cell lysis were encoded by the phage genome. The complete genome sequence of Ahp1 along with gene annotation was submitted to NCBI GenBank (accession number MF683623). Stability of Ahp1 preparations at storage temperatures of 4 °C, 30 °C, and 40 °C was studied over a period of 9 months. At 40 °C storage, phage counts declined by 4 log units within one month; with a total loss of viability after 2 months. At 30 °C temperature, phage preparation was stable for < 5 months. On the other hand, phage counts decreased by only 2 log units over a period of 9 during storage at 4 °C. As some of the phages have also been reported as glycerol sensitive, the stability of Ahp1 preparations in (0%, 15%, 30% and 45%) glycerol stocks were also studied during storage at -80 °C over a period of 9 months. The phage counts decreased only by 2 log units during storage, and no significant difference in phage counts was observed at different concentrations of glycerol. The Ahp1 phage discovered in our study had a very narrow host range and it may be useful for phage typing applications. Moreover, the endolysin and holin genes in Ahp1 genome could be ideal candidates for recombinant cloning and expression of antimicrobial proteins.

Keywords: Aeromonas hydrophila, endolysin, phage, narrow host range

Procedia PDF Downloads 162

Authors: M. Koksal, T. Ozyazici, E. Gurdal, M. Yarım, E. Demirpolat, M. B. Y. Aycan

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The discovery of new drugs in cancer chemotherapy is still a major topic because of severe side effects, selectivity problems and resistance development potential of existing drugs. In recent years, combined anticancer therapies or multi-acting drugs are clinically preferred over traditional cytotoxic treatment, with the aim of avoiding resistance and toxic side effects. Arrangement of multi-acting targets can be carried out either by combination of several drugs with different mechanisms or by usage of a single chemical compound capable of regulating several targets of a disease with multiple factors. In literature, several pyrimidine and piperazine derivatives have been involved in the structure of many compounds which have been used as chemotherapeutic agents along with wide clinical applications. The aim of this study is to combine pyrimidine and piperazine core structures to research and develop novel piperazinylpyrimidine derivatives with selective cytotoxicity over cancer cells. In this study, a group of novel 6-fluorophenyl-3-[2-(substitutedpiperazinyl)ethyl] hexahydropyrimidine-2,4-dione derivatives designed to observe the desired anticancer activity due to pyrimidine and piperazine based scaffolds. Target compounds were obtained by the reaction of appropriate piperazine derivatives and 6-(2/4-fluorophenyl)-3-(2-chloroethyl)hexahydropyrimidine-2,4-dione. The synthetic pathway of 6-(2/4-fluorophenyl)-3-(2-chloroethyl)hexahydropyrimidine-2,4-dione was started with Rodionov reaction using aldehyde, malonic acid and ammonium acetate in ethanol. Isolated β-fluorophenyl-β-amino acids were treated with 2-chloroethylisocyanate in the presence of an aqueous sodium hydroxide solution at room temperature to yield the sodium salts of the corresponding ureido acids. By addition of a mineral acid, ureido acids were precipitated. Later, these ureido acids were refluxed in thionyl chloride to give the 6-(2/4-fluorophenyl)-3-(2-chloroethyl)hexahydropyrimidine-2,4-di-one which were furthermore treated with secondary amines. Structures of purified compounds were characterized with IR, 1H-NMR, 13C-NMR, mass spectroscopies and elemental analysis. All of the compounds gave satisfactory analytical and spectroscopic data, which were in full accordance with their depicted structures. In IR spectra of the compounds, N-H group was seen at 3230-3213 cm⁻¹. C-H was seen at 3100-2820 cm⁻¹ and C=O vibrational peaks were observed approximately at 1725 and 1665 cm⁻¹ in accordance with literature. In the NMR spectra of target compounds, the methylene protons of piperazine give two separate multiplet peaks around 3.5 and 4.5 ppm representing the successful N-alkylation of the structure. The cytotoxic activity of the synthesized compounds was investigated on human bronchial epithelial (BEAS 2B), lung (A549), colon adenocarcinoma (COLO205) and breast (MCF7) cell lines, by means of sulphorhodamine B (SRB) assays in triplicate. IC₅₀ values of the screened derivatives were found in range of 11.8-78 µM. This project was supported by The Scientific and Technological Research Council of Turkey (TUBITAK, Project no: 215S157).

Keywords: cytotoxicity, hexahydropyrimidine, piperazine, sulphorhodamine B assay

Procedia PDF Downloads 152

Authors: Z. Yousefniayejahr, S. Bolognini, A. Bonini, C. Campobasso, N. Poma, F. Vivaldi, M. Di Luca, A. Tavanti, F. Di Francesco

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Pathogenic bacteria represent a threat to healthcare systems and the food industry because their rapid detection remains challenging. Electrochemical biosensors are gaining prominence as a novel technology for the detection of pathogens due to intrinsic features such as low cost, rapid response time, and portability, which make them a valuable alternative to traditional methodologies. These sensors use biorecognition elements that are crucial for the identification of specific bacteria. In this context, bacteriophages are promising tools for their inherent high selectivity towards bacterial hosts, which is of fundamental importance when detecting bacterial pathogens in complex biological samples. In this study, we present the development of a low-cost and portable sensor based on the Zeno phage for the rapid detection of Staphylococcus aureus. Screen-printed gold electrodes functionalized with the Zeno phage were used, and electrochemical impedance spectroscopy was applied to evaluate the change of the charge transfer resistance (Rct) as a result of the interaction with S. aureus MRSA ATCC 43300. The phage-based biosensor showed a linear range from 101 to 104 CFU/mL with a 20-minute response time and a limit of detection (LOD) of 1.2 CFU/mL under physiological conditions. The biosensor’s ability to recognize various strains of staphylococci was also successfully demonstrated in the presence of clinical isolates collected from different geographic areas. Assays using S. epidermidis were also carried out to verify the species-specificity of the phage sensor. We only observed a remarkable change of the Rct in the presence of the target S. aureus bacteria, while no substantial binding to S. epidermidis occurred. This confirmed that the Zeno phage sensor only targets S. aureus species within the genus Staphylococcus. In addition, the biosensor's specificity with respect to other bacterial species, including gram-positive bacteria like Enterococcus faecium and the gram-negative bacterium Pseudomonas aeruginosa, was evaluated, and a non-significant impedimetric signal was observed. Notably, the biosensor successfully identified S. aureus bacterial cells in a complex matrix such as a nasal swab, opening the possibility of its use in a real-case scenario. We diluted different concentrations of S. aureus from 108 to 100 CFU/mL with a ratio of 1:10 in the nasal swap matrices collected from healthy donors. Three different sensors were applied to measure various concentrations of bacteria. Our sensor indicated high selectivity to detect S. aureus in biological matrices compared to time-consuming traditional methods, such as enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR), and radioimmunoassay (RIA), etc. With the aim to study the possibility to use this biosensor to address the challenge associated to pathogen detection, ongoing research is focused on the assessment of the biosensor’s analytical performances in different biological samples and the discovery of new phage bioreceptors.

Keywords: electrochemical impedance spectroscopy, bacteriophage, biosensor, Staphylococcus aureus

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Authors: Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Diego Santibañez Oyarce, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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Streptococcus pyogenes is a gram-positive bacteria involved in a wide range of diseases and is a major-human-specific bacterial pathogen. In Chile, this year the 'Ministerio de Salud' declared an alert due to the increase in strains throughout the year. This increase can be attributed to the multitude of factors including antimicrobial resistance (AMR) and Virulence Factors (VF). Understanding these VF and AMR is crucial for developing effective strategies and improving public health responses. Moreover, experimental identification and characterization of these pathogenic mechanisms are labor-intensive and time-consuming. Therefore, new computational methods are required to provide robust techniques for accelerating this identification. Advances in Machine Learning (ML) algorithms represent the opportunity to refine and accelerate the discovery of VF associated with Streptococcus pyogenes. In this work, we evaluate the accuracy of various machine learning models in predicting the virulence factors and antimicrobial resistance of Streptococcus pyogenes, with the objective of providing new methods for identifying the pathogenic mechanisms of this organism.Our comprehensive approach involved the download of 32,798 genbank files of S. pyogenes from NCBI dataset, coupled with the incorporation of data from Virulence Factor Database (VFDB) and Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. These datasets provided labeled examples of both virulent and non-virulent genes, enabling a robust foundation for feature extraction and model training. We employed preprocessing, characterization and feature extraction techniques on primary nucleotide/amino acid sequences and selected the optimal more for model training. The feature set was constructed using sequence-based descriptors (e.g., k-mers and One-hot encoding), and functional annotations based on database prediction. The ML models compared are logistic regression, decision trees, support vector machines, neural networks among others. The results of this work show some differences in accuracy between the algorithms, these differences allow us to identify different aspects that represent unique opportunities for a more precise and efficient characterization and identification of VF and AMR. This comparative analysis underscores the value of integrating machine learning techniques in predicting S. pyogenes virulence and AMR, offering potential pathways for more effective diagnostic and therapeutic strategies. Future work will focus on incorporating additional omics data, such as transcriptomics, and exploring advanced deep learning models to further enhance predictive capabilities.

Keywords: antibiotic resistance, streptococcus pyogenes, virulence factors., machine learning

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Authors: Margareta Simina Stanc, Aurel Mototolea, Tiberiu Potarniche

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Sacidava archeological site is located in Dobrudja region, Romania, on a hill on the right bank of the Danube - the Musait point, located at about 5 km north-east from Dunareni village. The place-name documents the fact that, prior to the Roman conquest, in the area, there was a Getic settlement. The location of the Sacidava was made possible by corroborating the data provided by the ancient sources with the epigraphic documents (the milial pillar during the time of Emperor Decius). The tegular findings attest that an infantry unit, cohors I Cilicum milliaria equitata, as well as detachments from Legio V Macedonica and Legio XI Claudia, were confined to Sacidava. During the period of the Dominion, the garrison of the fortification is the host of a cavalry unit: cuneus equitum scutariorum. In the immediate vicinity to the Roman fortress, to the east, were identified two other fortifications: a Getic settlement (4th-1st century B.C.) and an Early Medieval settlement (9th-10th century A.C.). The archaeological material recovered during the research is represented by ceramic forms such as amphoras, jugs, pots, cups, plates, to which are added oil lamps, some of them typologically new at the time of discovery. Local ceramic shapes were also founded, worked by hand or by wheel, considered un-Romanized or in the course of Romanization. During the time of the Principality, Sacidava it represented an important military outpost serving mainly the city of Tropaeum Traiani, controlling also the supply and transport on the Danube limes in the Moesic sector. This role will determine the development of the fortress and the appearance of extramuros civil structures, thus becoming an important landmark during the 5th-6th centuries A.C., becoming a representation of power of the Roman empire in an area of continuous conflict. During recent archaeological researches, faunal remains were recovered, and their analysis allowed to estimate the animal resources and subsistence practices (animal husbandry, hunting, fishing) in the settlement. The methodology was specific to archaeozoology, mainly consisting of anatomical, taxonomical, and taphonomical identifications, recording, and quantification of the data. The remains of domestic mammals have the highest proportion indicating the importance of animal husbandry; the predominant species are Bos taurus, Ovis aries/Capra hircus, and Sus domesticus. Fishing and hunting were of secondary importance in the subsistence economy of the community. Wild boar and the red deer were the most frequently hunted species. Just a few fish bones were recovered. Thus, the ancient city of Sacidava is proving to be an important element of cultural heritage of the south-eastern part of Romania, for whose conservation and enhancement efforts must be made, especially by landscape reconstruction.

Keywords: archaeozoology, landscape reconstruction, limes, military outpost

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Authors: Richard Levy, Peter Dawson

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Ft. Conger, located in the Canadian Arctic was one of the most remote 19th-century scientific stations. Established in 1881 on Ellesmere Island, a wood framed structure established a permanent base from which to conduct scientific research. Under the charge of Lt. Greely, Ft. Conger was one of 14 expeditions conducted during the First International Polar Year (FIPY). Our research project “From Science to Survival: Using Virtual Exhibits to Communicate the Significance of Polar Heritage Sites in the Canadian Arctic” focused on the creation of a virtual museum website dedicated to one of the most important polar heritage site in the Canadian Arctic. This website was developed under a grant from Virtual Museum of Canada and enables visitors to explore the fort’s site from 1875 to the present, http://fortconger.org. Heritage sites are often viewed as static places. A goal of this project was to present the change that occurred over time as each new group of explorers adapted the site to their needs. The site was first visited by British explorer George Nares in 1875 – 76. Only later did the United States government select this site for the Lady Franklin Bay Expedition (1881-84) with research to be conducted under the FIPY (1882 – 83). Still later Robert Peary and Matthew Henson attempted to reach the North Pole from Ft. Conger in 1899, 1905 and 1908. A central focus of this research is on the virtual reconstruction of the Ft. Conger. In the summer of 2010, a Zoller+Fröhlich Imager 5006i and Minolta Vivid 910 laser scanner were used to scan terrain and artifacts. Once the scanning was completed, the point clouds were registered and edited to form the basis of a virtual reconstruction. A goal of this project has been to allow visitors to step back in time and explore the interior of these buildings with all of its artifacts. Links to text, historic documents, animations, panorama images, computer games and virtual labs provide explanations of how science was conducted during the 19th century. A major feature of this virtual world is the timeline. Visitors to the website can begin to explore the site when George Nares, in his ship the HMS Discovery, appeared in the harbor in 1875. With the emergence of Lt Greely’s expedition in 1881, we can track the progress made in establishing a scientific outpost. Still later in 1901, with Peary’s presence, the site is transformed again, with the huts having been built from materials salvaged from Greely’s main building. Still later in 2010, we can visit the site during its present state of deterioration and learn about the laser scanning technology which was used to document the site. The Science and Survival at Fort Conger project represents one of the first attempts to use virtual worlds to communicate the historical and scientific significance of polar heritage sites where opportunities for first-hand visitor experiences are not possible because of remote location.

Keywords: 3D imaging, multimedia, virtual reality, arctic

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Authors: Vikas Kumar, Kailash Chandra, Kaomud Tyagi

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The insect order Thysanoptera includes small insects commonly called thrips. As insect vectors, only thrips are capable of Tospoviruses transmission (genus Tospovirus, family Bunyaviridae) affecting various crops. Currently, fifteen species of subfamily Thripinae (Thripidae) have been reported as vectors for tospoviruses. Frankliniella schultzei, which is reported as act as a vector for at least five tospovirses, have been suspected to be a species complex with more than one species. It is one of the historical unresolved issues where, two species namely, F. schultzei Trybom and F. sulphurea Schmutz were erected from South Africa and Srilanaka respectively. These two species were considered to be valid until 1968 when sulphurea was treated as colour morph (pale form) and synonymised under schultzei (dark form) However, these two have been considered as valid species by some of the thrips workers. Parallel studies have indicated that brown form of schultzei is a vector for tospoviruses while yellow form is a non-vector. However, recent studies have shown that yellow populations have also been documented as vectors. In view of all these facts, it is highly important to have a clear understanding whether these colour forms represent true species or merely different populations with different vector carrying capacities and whether there is some hidden diversity in 'Frankliniella schultzei species complex'. In this study, we aim to study the 'Frankliniella schultzei species complex' with molecular spectacles with DNA data from India and Australia and Africa. A total of fifty-five specimens was collected from diverse locations in India and Australia. We generated molecular data using partial fragments of mitochondrial cytochrome c oxidase I gene (mtCOI) and 28S rRNA gene. For COI dataset, there were seventy-four sequences, out of which data on fifty-five was generated in the current study and others were retrieved from NCBI. All the four different tree construction methods: neighbor-joining, maximum parsimony, maximum likelihood and Bayesian analysis, yielded the same tree topology and produced five cryptic species with high genetic divergence. For, rDNA, there were forty-five sequences, out of which data on thirty-nine was generated in the current study and others were retrieved from NCBI. The four tree building methods yielded four cryptic species with high bootstrap support value/posterior probability. Here we could not retrieve one cryptic species from South Africa as we could not generate data on rDNA from South Africa and sequence for rDNA from African region were not available in the database. The results of multiple species delimitation methods (barcode index numbers, automatic barcode gap discovery, general mixed Yule-coalescent, and Poisson-tree-processes) also supported the phylogenetic data and produced 5 and 4 Molecular Operational Taxonomic Units (MOTUs) for mtCOI and 28S dataset respectively. These results of our study indicate the likelihood that F. sulphurea may be a valid species, however, more morphological and molecular data is required on specimens from type localities of these two species and comparison with type specimens.

Keywords: DNA barcoding, species complex, thrips, species delimitation

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Authors: Catarina Ferreira Rebelo, Luis Madeira de Carvalho, Fernando González González

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The order Passeridae corresponds to the richest and most abundant group of birds, with approximately 6500 species, making it possible to assert that two out of every three bird species are passerines. They are globally distributed and exhibit remarkable morphological and ecological variability. While numerous species of parasites have been identified and described in wild birds, there has been little focus on passeriformes. Seventeen passerines admitted to GREFA, a Wildlife Rehabilitation Center, throughout the months of October, November and December 2022 were analyzed. The species included Aegithalos caudatus, Anthus pratensis, Carduelis chloris, Certhia brachydactyla, Erithacus rubecula, Fringilla coelebs, Parus ater, Passer domesticus, Sturnus unicolor, Sylvia atricapilla, Turdus merula and Turdus philomelos. Data regarding past history was collected, and necropsies were conducted to identify the cause of death and body condition and determine the presence of parasites. Additionally, samples of intestinal content were collected for direct/fecal smear, flotation and sedimentation techniques. Sixteen (94.1%) passerines were considered positive for the presence of parasitic forms in at least one of the techniques used, including parasites detected in necropsy. Adult specimens of both sexes and tritonymphs of Monojoubertia microhylla and ectoparasites of the genus Ornithonyssus were identified. Macroscopic adult endoparasitic forms were also found during necropsies, including Diplotriaena sp., Serratospiculum sp. and Porrocaecum sp.. Parasitism by coccidia was observed with no sporulation. Additionally, eggs of nematodes from various genera were detected, such as Diplotriaena sp., Capillaria sp., Porrocaecum sp., Syngamus sp. and Strongyloides sp., eggs of trematodes, specifically the genus Brachylecithum and cestode oncospheres, whose genera were not identified. To our knowledge, the respiratory nematode Serratospiculum sp. found in this study is being reported for the first time in passerines in the Iberian Peninsula, along with the application of common coprological techniques for the identification of eggs in the intestinal content. The majority of parasites identified utilize intermediary hosts present in the diet of the passerines sampled. Furthermore, the discovery of certain parasites with a direct life cycle could potentially exert greater influence, particularly in specific scenarios such as within nests or during the rehabilitation process in wildlife centers. These parasites may impact intraspecific competition, increase susceptibility to predators or lead to death. However, their cost to wild birds is often not clear, as individuals can endure various parasites without significant harm. Furthermore, wild birds serve as important sources of parasites across different animal groups, including humans and other mammals. This study provides invaluable insights into the parasitic fauna of these birds, not only serving as a cornerstone for future epidemiological investigations but also enhancing our comprehension of these avian species.

Keywords: birds, parasites, passerines, wild, spain

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Authors: Oluwaseun Adeleke, Samuel Ikan, Anthony Nwala, Mopelola Raji, Fidelis Edet

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Background: The risks associated with each pregnancy is carried almost entirely by a woman; however, the decision about whether and when to get pregnant is a subject that several others contend with her to make. The self-care concept offers women of reproductive age the opportunity to take control of their health and its determinants with or without the influence of a healthcare provider, family, and friends. DMPA-SC Self-injection (SI) is becoming the cornerstone of contraceptive self-care and has the potential to expand access and create opportunities for women to take control of their reproductive health. Methodology: To obtain insight into the influences that interfere with a woman’s capacity to make contraceptive choices independently, the Delivering Innovations in Selfcare (DISC) project conducted two intensive rounds of qualitative data collection and triangulation that included provider, client, and community mobilizer interviews, facility observations, and routine program data collection. Respondents were sampled according to a convenience sampling approach and data collected analyzed using a codebook and Atlas-TI. The research team members came together for participatory analysis workshop to explore and interpret emergent themes. Findings: Insights indicate that women are increasingly finding their voice and independently seek services to prevent a deterioration of their economic situation and achieve personal ambitions. Women who hold independent decision-making power still prefer to share decision making power with their male partners. Male partners’ influence on women’s use of family planning and self-inject was most dominant. There were examples of men’s support for women’s use of contraception to prevent unintended pregnancy, as well as men withholding support. Other men outrightly deny their partners from obtaining contraceptive services and their partners cede this sexual and reproductive health right without objection. A woman’s decision to initiate family planning is affected by myths and misconceptions, many of which have cultural and religious origins. Some tribes are known for their reluctance to use contraception and often associate stigma with the pursuit of family planning (FP) services. Information given by the provider is accepted, and, in many cases, clients cede power to providers to shape their SI user journey. A provider’s influence on a client’s decision to self-inject is reinforced by their biases and concerns. Clients are inhibited by the presence of peers during group education at the health facility. Others are motivated to seek FP services by the interest expressed by peers. There is also a growing trend in the influence of social media on FP uptake, particularly Facebook fora. Conclusion: The convenience of self-administration at home is a benefit for those that contend with various forms of social influences as well as covert users. Beyond increasing choice and reducing barriers to accessing Sexual and Reproductive Health (SRH) services, it can initiate the process of self-discovery and agency in the contraceptive user journey.

Keywords: selfcare, self-empowerment, agency, DMPA-SC, contraception, family planning, influences

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Authors: Duncan Wallace, M-Tahar Kechadi

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In recent years, Machine Learning (ML) approaches have been successfully applied to an analysis of patient symptom data in the context of disease diagnosis, at least where such data is well codified. However, much of the data present in Electronic Health Records (EHR) are unlikely to prove suitable for classic ML approaches. Furthermore, as scores of data are widely spread across both hospitals and individuals, a decentralized, computationally scalable methodology is a priority. The focus of this paper is to develop a method to predict outliers in an out-of-hours healthcare provision center (OOHC). In particular, our research is based upon the early identification of patients who have underlying conditions which will cause them to repeatedly require medical attention. OOHC act as an ad-hoc delivery of triage and treatment, where interactions occur without recourse to a full medical history of the patient in question. Medical histories, relating to patients contacting an OOHC, may reside in several distinct EHR systems in multiple hospitals or surgeries, which are unavailable to the OOHC in question. As such, although a local solution is optimal for this problem, it follows that the data under investigation is incomplete, heterogeneous, and comprised mostly of noisy textual notes compiled during routine OOHC activities. Through the use of Deep Learning methodologies, the aim of this paper is to provide the means to identify patient cases, upon initial contact, which are likely to relate to such outliers. To this end, we compare the performance of Long Short-Term Memory, Gated Recurrent Units, and combinations of both with Convolutional Neural Networks. A further aim of this paper is to elucidate the discovery of such outliers by examining the exact terms which provide a strong indication of positive and negative case entries. While free-text is the principal data extracted from EHRs for classification, EHRs also contain normalized features. Although the specific demographical features treated within our corpus are relatively limited in scope, we examine whether it is beneficial to include such features among the inputs to our neural network, or whether these features are more successfully exploited in conjunction with a different form of a classifier. In this section, we compare the performance of randomly generated regression trees and support vector machines and determine the extent to which our classification program can be improved upon by using either of these machine learning approaches in conjunction with the output of our Recurrent Neural Network application. The output of our neural network is also used to help determine the most significant lexemes present within the corpus for determining high-risk patients. By combining the confidence of our classification program in relation to lexemes within true positive and true negative cases, with an inverse document frequency of the lexemes related to these cases, we can determine what features act as the primary indicators of frequent-attender and non-frequent-attender cases, providing a human interpretable appreciation of how our program classifies cases.

Keywords: artificial neural networks, data-mining, machine learning, medical informatics

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Authors: Priya Nangia, Sanchita Bansal

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As fashion cycles become more rapid, some segments of the fashion industry have adopted increasingly unsustainable production processes to keep up with demand and enhance profit margins. The growing threat to environmental and social wellbeing posed by unethical fast fashion practices and the need to integrate the targets of SDGs into this industry necessitates a shift in the fashion industry's unsustainable nature, which can only be accomplished in the long run if consumers support sustainable fashion by purchasing it. Fast fashion is defined as low-cost, trendy apparel that takes inspiration from the catwalk or celebrity culture and rapidly transforms it into garments at high-street stores to meet consumer demand. Given the importance of identity formation to many consumers, the desire to be “fashionable” often outweighs the desire to be ethical or sustainable. This paradox exemplifies the tension between the human drive to consume and the will to do so in moderation. Previous research suggests that there is an attitude-behavior gap when it comes to determining consumer purchasing behavior, but to the best of our knowledge, no study has analysed how to encourage customers to shift from fast to slow fashion. Against this backdrop, the aim of this study is twofold: first, to identify and examine the factors that impact consumers' decisions to engage in sustainable fashion, and second, the authors develop a comprehensive framework for conceptualizing and encouraging researchers and practitioners to foster sustainable consumer behavior. This study used a systematic approach to collect data and analyse literature. The approach included three key steps: review planning, review execution, and findings reporting. Authors identified the keywords “sustainable consumption” and “sustainable fashion” and retrieved studies from the Web of Science (WoS) (126 records) and Scopus database (449 records). To make the study more specific, the authors refined the subject area to management, business, and economics in the second step, retrieving 265 records. In the third step, the authors removed the duplicate records and manually reviewed the articles to examine their relevance to the research issue. The final 96 research articles were used to develop this study's systematic scheme. The findings indicate that societal norms, demographics, positive emotions, self-efficacy, and awareness all have an effect on customers' decisions to purchase sustainable apparel. The authors propose a framework, denoted by the acronym SHIFT, in which consumers are more likely to engage in sustainable behaviors when the message or context leverages the following factors: (s)social influence, (h)habit formation, (i)individual self, (f)feelings, emotions, and cognition, and (t)tangibility. Furthermore, the authors identify five broad challenges that encourage sustainable consumer behavior and use them to develop novel propositions. Finally, the authors discuss how the SHIFT framework can be used in practice to drive sustainable consumer behaviors. This research sought to define the boundaries of existing research while also providing new perspectives on future research, with the goal of being useful for the development and discovery of new fields of study, thereby expanding knowledge.

Keywords: consumer behavior, fast fashion, sustainable consumption, sustainable fashion, systematic literature review

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Authors: Mariana Durana Pinto, Thierry Aubry, Eduarda Vieira

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The Côa River is one of the tributaries of the Douro River, which in turn connects two Portuguese regions: Beira-Alta (Serra das Mesas, Sabugal) and Trás-os-Montes (Douro River, Vila Nova de Foz Côa). The river, which is approximately 140 kilometres in length, is surrounded by characteristic Northern-Estearn Portugal landscape. The dominant flora in the region includes olive and almond trees and vines, which provide habitat for a diverse range of native species. These include mammals such as the lynx and Iberian wolf, as well as birds of prey such as the Egyptian vulture and the griffon vulture. Additionally, herbivorous species such as red deer and roe deer also inhabit the region. However, the Vale Côa is inextricably linked with the rocky outcrops bearing the emblematic open-air Upper Palaeolithic rock art, indeed, it houses the world's largest collection of prehistoric open-air rock art, inscribed on the World Heritage list by UNESCO in 1998. From the initial discovery of the first engravings in 1991 to the present day, approximally 1,500 panels with rock art, mostly engravings and carving, but also some paintings, have been discovered, inventoried and recorded spanning from earlu Upper Paleolithic to the 20th century. The study and interpretation of the engravings and its geoarchaeological context, allow the construction of a chronological timeline of the human occupation and graphical production in this region. The area has been inhabited since the Early Palaeolithic, with human communities exploiting the diversity of the natural resources of the environment and adapting it to their needs. This led to the creation of an archaeological and historical cultural landscape.The region is currently inhabited by rural communities whose primary source of income is derived from agricultural activities, with a particular focus on olive oil and wine production, including the emblematic Vinho do Porto. Additionally, the region is distinguished by activities such as stone exploration and extraction (e.g. schist and granite quarries) and tourism. The latter has progressively assumed a role in the promotion and development of the region, primarily due to the engravings of the Côa Valley itself, as well as the Alto Douro Wine Region. Furthermore, this cultural landscape has been inscribed in the UNESCO World Heritage Site in 2001. The aforementioned factors give rise to a series of challenges and issues pertaining to the management and safeguarding of rock art on a daily basis. These include: I) the management of conflicts between cultural heritage and economic activity (between Rock art and vineyards, both classified as World Heritage Sites); II) the management of land-use planning in areas where the engravings are located (since the areas with engravings are larger than those identified as buffer zones by UNESCO); III) the absence of the legal figure of an 'archaeological park' and the need to solve this issue; IV) the management of tourist pressure and unauthorised visits; and V) the management of vandalism (as a consequence of misinformation and denial).

Keywords: Douro and Côa Valleys, archaeological cultural landscapes, rock art, Douro wine, conservation challenges

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Authors: B. Shaw, K. Doherty

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The Cultural Communication and Computing Research Institute (C3RI) is a diverse multidisciplinary research institute including art, design, media production, communication studies, computing and engineering. Across these disciplines it can seem like there are enormous differences of research practice and convention, including differing positions on objectivity and subjectivity, certainty and evidence, and different political and ethical parameters. These differences sit within, often unacknowledged, histories, codes, and communication styles of specific disciplines, and it is all these aspects that can make understanding of research practice across disciplines difficult. To explore this, a one day event was orchestrated, testing how a PhD community might communicate and share research in progress in a multi-disciplinary context. Instead of presenting results at a conference, research students were tasked to articulate their method of inquiry. A working party of students from across disciplines had to design a conference call, visual identity and an event framework that would work for students across all disciplines. The process of establishing the shape and identity of the conference was revealing. Even finding a linguistic frame that would meet the expectations of different disciplines for the conference call was challenging. The first abstracts submitted either resorted to reporting findings, or only described method briefly. It took several weeks of supported intervention for research students to get ‘inside’ their method and to understand their research practice as a process rich with philosophical and practical decisions and implications. In response to the abstracts the conference committee generated key methodological categories for conference sessions, including sampling, capturing ‘experience’, ‘making models’, researcher identities, and ‘constructing data’. Each session involved presentations by visual artists, communications students and computing researchers with inter-disciplinary dialogue, facilitated by alumni Chairs. The apparently simple focus on method illuminated research process as a site of creativity, innovation and discovery, and also built epistemological awareness, drawing attention to what is being researched and how it can be known. It was surprisingly difficult to limit students to discussing method, and it was apparent that the vocabulary available for method is sometimes limited. However, by focusing on method rather than results, the genuine process of research, rather than one constructed for approval, could be captured. In unlocking the twists and turns of planning and implementing research, and the impact of circumstance and contingency, students had to reflect frankly on successes and failures. This level of self – and public- critique emphasised the degree of critical thinking and rigour required in executing research and demonstrated that honest reportage of research, faults and all, is good valid research. The process also revealed the degree that disciplines can learn from each other- the computing students gained insights from the sensitive social contextualizing generated by communications and art and design students, and art and design students gained understanding from the greater ‘distance’ and emphasis on application that computing students applied to their subjects. Finding the means to develop dialogue across disciplines makes researchers better equipped to devise and tackle research problems across disciplines, potentially laying the ground for more effective collaboration.

Keywords: interdisciplinary, method, research student, training

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Authors: Nadia K. Thalji

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In the timeless tapestry of human culture, theater, mythology, and psychology intersect to weave narratives that transcend temporal and spatial boundaries. For millennia, actors have stood as guardians of intuitive wisdom, their craft serving as a conduit for the collective unconscious. This paper embarks on a journey through the realms of creative expression, melding the insights of cross-cultural psychology with the mystical allure of serendipity and synchronicity. At the nexus of these disciplines lies the enigmatic process of active imagination, a gateway to the depths of the psyche elucidated by Jung. Within the hallowed confines of the black box theater at the Department of Performing Arts, UFRGS University in Brazil, this study unfolds. Over the span of four months, a cadre of artists embarked on a voyage of exploration, harnessing the powers of imagery, movement, sound, and dreams to birth a performance that resonated with the echoes of ancient wisdom. Drawing inspiration from the fabled Oracle of Delphi and the priestesses who once dwelled within its sacred precincts, the production delves into the liminal spaces where myth and history intertwine. Through the alchemy of storytelling, participants navigate the labyrinthine corridors of cultural memory, unraveling the threads that bind the past to the present. Central to this endeavor is the phenomenon of synchronicity, wherein seemingly disparate elements coalesce in a dance of cosmic resonance. Serendipity becomes a guiding force, leading actors and audience alike along unexpected pathways of discovery. As the boundaries between performer and spectator blur, the performance becomes a crucible wherein individual narratives merge to form a collective tapestry of shared experience. Yet, beneath the surface of spectacle lies a deeper truth: the exploration of the spiritual dimensions of artistic expression. Through intuitive inquiry and embodied practice, artists tap into reservoirs of insight that transcend rational comprehension. In the communion of minds and bodies, the stage becomes a sacred space wherein the numinous unfolds in all its ineffable glory. In essence, this paper serves as a testament to the transformative power of the creative act. Across cultures and epochs, the theater has served as a crucible wherein humanity grapples with the mysteries of existence. Through the lens of cross-cultural psychology, we glimpse the universal truths that underlie the myriad manifestations of human creativity. As we navigate the turbulent currents of modernity, the wisdom of the ancients beckons us to heed the call of the collective unconscious. In the synthesis of myth and meaning, we find solace amidst the chaos, forging connections that transcend the boundaries of time and space. And in the sacred precincts of the theater, we discover the eternal truth that art is, and always shall be, the soul's journey into the unknown.

Keywords: theater, mythology, cross-cultural, synchronicity, creativity, serendipity, spiritual

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Authors: Rodrigo Arnaldo Scarpel

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Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

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Authors: E. O. Okan, A. Kepic, P. Williams

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Iron oxide copper gold (IOCG) deposits constitute important sources of copper and gold in Australia especially since the discovery of the supergiant Olympic Dam deposits in 1975. They are considered to be metasomatic expressions of large crustal-scale alteration events occasioned by intrusive actions and are associated with felsic igneous rocks in most cases, commonly potassic igneous magmatism, with the deposits ranging from ~2.2 –1.5 Ga in age. For the past two decades, geological, geochemical and potential methods have been used to identify the structures hosting these deposits follow up by drilling. Though these methods have largely been successful for shallow targets, at deeper depth due to low resolution they are limited to mapping only very large to gigantic deposits with sufficient contrast. As the search for ore-bodies under regolith cover continues due to depletion of the near surface deposits, there is a compelling need to develop new exploration technology to explore these deep seated ore-bodies within 1-4km which is the current mining depth range. Seismic reflection method represents this new technology as it offers a distinct advantage over all other geophysical techniques because of its great depth of penetration and superior spatial resolution maintained with depth. Further, in many different geological scenarios, it offers a greater ‘3D mapability’ of units within the stratigraphic boundary. Despite these superior attributes, no arguments for crustal scale seismic surveys have been proposed because there has not been a compelling argument of economic benefit to proceed with such work. For the seismic reflection method to be used at these scales (100’s to 1000’s of square km covered) the technical risks or the survey costs have to be reduced. In addition, as most IOCG deposits have large footprint due to its association with intrusions and large fault zones; we hypothesized that these deposits can be found by mainly looking for the seismic signatures of intrusions along prospective structures. In this study, we present two of such cases: - Olympic Dam and Vulcan iron-oxide copper-gold (IOCG) deposits all located in the Gawler craton, South Australia. Results from our 2D modelling experiments revealed that seismic reflection surveys using 20m geophones and 40m shot spacing as an exploration tool for locating IOCG deposit is possible even when hosted in very complex structures. The migrated sections were not only able to identify and trace various layers plus the complex structures but also show reflections around the edges of intrusive packages. The presences of such intrusions were clearly detected from 100m to 1000m depth range without losing its resolution. The modelled seismic images match the available real seismic data and have the hypothesized characteristics; thus, the seismic method seems to be a valid exploration tool to find IOCG deposits. We therefore propose that 2D seismic survey is viable for IOCG exploration as it can detect mineralised intrusive structures along known favourable corridors. This would help in reducing the exploration risk associated with locating undiscovered resources as well as conducting a life-of-mine study which will enable better development decisions at the very beginning.

Keywords: crustal scale, exploration, IOCG deposit, modelling, seismic surveys

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Authors: Bhargavi G. Iyer, Ojaswi Bhagat

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It is often noted that the value of a novel idea lies in its successful implementation. However, successful implementation requires the nurturing and encouragement of innovation. Nascent competitors are a true representation of innovation in any given industry. A nascent competitor is an entity whose prospective innovation poses a future threat to an incumbent dominant competitor. While a nascent competitor benefits in several ways, it is also exposed significantly and is at greater risk of facing the brunt of exclusionary practises and abusive conduct by dominant incumbent competitors in the industry. This research paper aims to explore the risks and threats faced by nascent competitors and analyse the benefits they accrue as well as the advantages they proffer to the economy; through an analytical, critical study. In such competitive market environments, a rise of the acquisitions of nascent competitors by the incumbent dominants is observed. Therefore, this paper will examine the dynamics of nascent acquisition. Further, this paper hopes to specifically delve into the role of antitrust bodies in regulating nascent acquisition. This paper also aspires to deal with the question how to distinguish harmful from harmless acquisitions in order to facilitate ideal enforcement practice. This paper proposes mechanisms of scrutiny in order to ensure healthy market practises and efficient merger control in the context of nascent acquisitions. Taking into account the scope and nature of the topic, as well as the resources available and accessible, a combination of the methods of doctrinal research and analytical research were employed, utilising secondary sources in order to assess and analyse the subject of research. While legally evaluating the Killer Acquisition theory and the Nascent Potential Acquisition theory, this paper seeks to critically survey the precedents and instances of nascent acquisitions. In addition to affording a compendious account of the legislative framework and regulatory mechanisms in the United States, the United Kingdom, and the European Union; it hopes to suggest an internationally practicable legal foundation for domestic legislation and enforcement to adopt. This paper hopes to appreciate the complexities and uncertainties with respect to nascent acquisitions and attempts to suggest viable and plausible policy measures in antitrust law. It additionally attempts to examine the effects of such nascent acquisitions upon the consumer and the market economy. This paper weighs the argument of shifting the evidentiary burden on to the merging parties in order to improve merger control and regulation and expounds on its discovery of the strengths and weaknesses of the approach. It is posited that an effective combination of factual, legal, and economic analysis of both the acquired and acquiring companies possesses the potential to improve ex post and ex ante merger review outcomes involving nascent companies; thus, preventing anti-competitive practises. This paper concludes with an analysis of the possibility and feasibility of industry-specific identification of anti-competitive nascent acquisitions and implementation of measures accordingly.

Keywords: acquisition, antitrust law, exclusionary practises merger control, nascent competitor

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Authors: Serhat Tüzün, Tufan Demirel

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Decision Support Systems (DSS) have been investigated by researchers and technologists for more than 35 years. This paper analyses the developments in the architecture and software of these systems, provides a systematic analysis for different Web-based DSS approaches and Intelligent Decision-making Technologies (IDT), with the suggestion for future studies. Decision Support Systems literature begins with building model-oriented DSS in the late 1960s, theory developments in the 1970s, and the implementation of financial planning systems and Group DSS in the early and mid-80s. Then it documents the origins of Executive Information Systems, online analytic processing (OLAP) and Business Intelligence. The implementation of Web-based DSS occurred in the mid-1990s. With the beginning of the new millennia, intelligence is the main focus on DSS studies. Web-based technologies are having a major impact on design, development and implementation processes for all types of DSS. Web technologies are being utilized for the development of DSS tools by leading developers of decision support technologies. Major companies are encouraging its customers to port their DSS applications, such as data mining, customer relationship management (CRM) and OLAP systems, to a web-based environment. Similarly, real-time data fed from manufacturing plants are now helping floor managers make decisions regarding production adjustment to ensure that high-quality products are produced and delivered. Web-based DSS are being employed by organizations as decision aids for employees as well as customers. A common usage of Web-based DSS has been to assist customers configure product and service according to their needs. These systems allow individual customers to design their own products by choosing from a menu of attributes, components, prices and delivery options. The Intelligent Decision-making Technologies (IDT) domain is a fast growing area of research that integrates various aspects of computer science and information systems. This includes intelligent systems, intelligent technology, intelligent agents, artificial intelligence, fuzzy logic, neural networks, machine learning, knowledge discovery, computational intelligence, data science, big data analytics, inference engines, recommender systems or engines, and a variety of related disciplines. Innovative applications that emerge using IDT often have a significant impact on decision-making processes in government, industry, business, and academia in general. This is particularly pronounced in finance, accounting, healthcare, computer networks, real-time safety monitoring and crisis response systems. Similarly, IDT is commonly used in military decision-making systems, security, marketing, stock market prediction, and robotics. Even though lots of research studies have been conducted on Decision Support Systems, a systematic analysis on the subject is still missing. Because of this necessity, this paper has been prepared to search recent articles about the DSS. The literature has been deeply reviewed and by classifying previous studies according to their preferences, taxonomy for DSS has been prepared. With the aid of the taxonomic review and the recent developments over the subject, this study aims to analyze the future trends in decision support systems.

Keywords: decision support systems, intelligent decision-making, systematic analysis, taxonomic review

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Authors: Birgit A. A. Solem, Kristin Bentsen

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Scholarly attention in entrepreneurship is currently directed towards understanding entrepreneurial venture creation as a process -the journey of new economic activities from nonexistence to existence often studied through flow- or network models. To complement existing research on entrepreneurial venture creation with more interactivity-based research of organized activities, this study examines two pop-up stores as anchor events involving on-site activities of fifteen participating entrepreneurs launching their new ventures. The pop-up stores were arranged in two middle-sized Norwegian cities and contained different brand stores that brought together actors of sub-networks and communities executing venture creation activities. The pop-up stores became on-site arenas for the entrepreneurs to create, maintain, and rejuvenate their networks, at the same time as becoming venues for temporal coordination of activities involving existing and potential customers in their venture creation. In this work, we apply a conceptual framework based on frequently addressed dilemmas within entrepreneurship theory (discovery/creation, causation/effectuation) to further shed light on the broad aspect of on-site anchor event activities and their venture creation outcomes. The dilemma-based concepts are applied as an analytic toolkit to pursue answers regarding the nature of anchor event activities typically found within entrepreneurial venture creation and how these anchor event activities affect entrepreneurial venture creation outcomes. Our study combines researcher participation with 200 hours of observation and twenty in-depth interviews. Data analysis followed established guidelines for hermeneutic analysis and was intimately intertwined with ongoing data collection. Data was coded and categorized in NVivo 12 software, and iterated several times as patterns were steadily developing. Our findings suggest that core anchor event activities typically found within entrepreneurial venture creation are; a concept- and product experimentation with visitors, arrangements to socialize (evening specials, auctions, and exhibitions), store-in-store concepts, arranged meeting places for peers and close connection with municipality and property owners. Further, this work points to four main entrepreneurial venture creation outcomes derived from the core anchor event activities; (1) venture attention, (2) venture idea-realization, (3) venture collaboration, and (4) venture extension. Our findings show that, depending on which anchor event activities are applied, the outcomes vary. Theoretically, this study offers two main implications. First, anchor event activities are both discovered and created, following the logic of causation, at the same time as being experimental, based on “learning by doing” principles of effectuation during the execution. Second, our research enriches prior studies on venture creation as a process. In this work, entrepreneurial venture creation activities and outcomes are understood through pop-up stores as on-site anchor event arenas, particularly suitable for interactivity-based research requested by the entrepreneurship field. This study also reveals important managerial implications, such as that entrepreneurs should allow themselves to find creative physical venture creation arenas (e.g., pop-up stores, showrooms), as well as collaborate with partners when discovering and creating concepts and activities based on new ideas. In this way, they allow themselves to both strategically plan for- and continually experiment with their venture.

Keywords: anchor event, interactivity-based research, pop-up store, entrepreneurial venture creation

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Authors: Xingyu Gao, Qiang Wu, Yuanyuan Liu, Yue Yang

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In the era of the knowledge economy, the relationship between scientific knowledge and patents has garnered significant attention. Understanding the intricate interplay between the foundations of science and technological innovation has emerged as a pivotal challenge for both researchers and policymakers. This study establishes a coupled network of artificial intelligence patents based on co-cited scientific papers. Leveraging centrality metrics from network analysis offers a fresh perspective on understanding the influence of information flow and knowledge sharing within the network on patent impact. The study initially obtained patent numbers for 446,890 granted US AI patents from the United States Patent and Trademark Office’s artificial intelligence patent database for the years 2002-2020. Subsequently, specific information regarding these patents was acquired using the Lens patent retrieval platform. Additionally, a search and deduplication process was performed on scientific non-patent references (SNPRs) using the Web of Science database, resulting in the selection of 184,603 patents that cited 37,467 unique SNPRs. Finally, this study constructs a coupled network comprising 59,379 artificial intelligence patents by utilizing scientific papers co-cited in patent backward citations. In this network, nodes represent patents, and if patents reference the same scientific papers, connections are established between them, serving as edges within the network. Nodes and edges collectively constitute the patent coupling network. Structural characteristics such as node degree centrality, betweenness centrality, and closeness centrality are employed to assess the scientific connections between patents, while citation count is utilized as a quantitative metric for patent influence. Finally, a negative binomial model is employed to test the nonlinear relationship between these network structural features and patent influence. The research findings indicate that network structural features such as node degree centrality, betweenness centrality, and closeness centrality exhibit inverted U-shaped relationships with patent influence. Specifically, as these centrality metrics increase, patent influence initially shows an upward trend, but once these features reach a certain threshold, patent influence starts to decline. This discovery suggests that moderate network centrality is beneficial for enhancing patent influence, while excessively high centrality may have a detrimental effect on patent influence. This finding offers crucial insights for policymakers, emphasizing the importance of encouraging moderate knowledge flow and sharing to promote innovation when formulating technology policies. It suggests that in certain situations, data sharing and integration can contribute to innovation. Consequently, policymakers can take measures to promote data-sharing policies, such as open data initiatives, to facilitate the flow of knowledge and the generation of innovation. Additionally, governments and relevant agencies can achieve broader knowledge dissemination by supporting collaborative research projects, adjusting intellectual property policies to enhance flexibility, or nurturing technology entrepreneurship ecosystems.

Keywords: centrality, patent coupling network, patent influence, social network analysis

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Authors: Sanaz Moayer, Fang Huang, Scott Gardner

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In the highly leveraged business world of today, an organisation’s success depends on how it can manage and organize its traditional and intangible assets. In the knowledge-based economy, knowledge as a valuable asset gives enduring capability to firms competing in rapidly shifting global markets. It can be argued that ability to create unique knowledge assets by configuring ICT and human capabilities, will be a defining factor for international competitive advantage in the mid-21st century. The concept of KM is recognized in the strategy literature, and increasingly by senior decision-makers (particularly in large firms which can achieve scalable benefits), as an important vehicle for stimulating innovation and organisational performance in the knowledge economy. This thinking has been evident in professional services and other knowledge intensive industries for over a decade. It highlights the importance of social capital and the value of the intellectual capital embedded in social and professional networks, complementing the traditional focus on creation of intellectual property assets. Despite the growing interest in KM within professional services there has been limited discussion in relation to multinational resource based industries such as mining and petroleum where the focus has been principally on global portfolio optimization with economies of scale, process efficiencies and cost reduction. The Australian minerals and metals mining industry, although traditionally viewed as capital intensive, employs a significant number of knowledge workers notably- engineers, geologists, highly skilled technicians, legal, finance, accounting, ICT and contracts specialists working in projects or functions, representing potential knowledge silos within the organisation. This silo effect arguably inhibits knowledge sharing and retention by disaggregating corporate memory, with increased operational and project continuity risk. It also may limit the potential for process, product, and service innovation. In this paper the strategic application of knowledge management incorporating contemporary ICT platforms and data mining practices is explored as an important enabler for knowledge discovery, reduction of risk, and retention of corporate knowledge in resource based industries. With reference to the relevant strategy, management, and information systems literature, this paper highlights possible connections (currently undergoing empirical testing), between an Strategic Knowledge Management (SKM) framework incorporating supportive Data Mining (DM) practices and competitive advantage for multinational firms operating within the Australian resource sector. We also propose based on a review of the relevant literature that more effective management of soft and hard systems knowledge is crucial for major Australian firms in all sectors seeking to improve organisational performance through the human and technological capability captured in organisational networks.

Keywords: competitive advantage, data mining, mining organisation, strategic knowledge management

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Authors: Ved Vrat Verma, Rani Gupta, Manisha Goel

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γ-glutamyltranspeptidase (GGT: EC 2.3.2.2) is an N-terminal nucleophile hydrolase conserved in all three domains of life. GGT plays a key role in glutathione metabolism where it catalyzes the breakage of the γ-glutamyl bonds and transfer of γ-glutamyl group to water (hydrolytic activity) or amino acids or short peptides (transpeptidase activity). GGTs from bacteria, archaea, and eukaryotes (human, rat and mouse) are homologous proteins sharing >50% sequence similarity and conserved four layered αββα sandwich like three dimensional structural fold. These proteins though similar in their structure to each other, are quite diverse in their enzyme activity: some GGTs are better at hydrolysis reactions but poor in transpeptidase activity, whereas many others may show opposite behaviour. GGT is known to be involved in various diseases like asthma, parkinson, arthritis, and gastric cancer. Its inhibition prior to chemotherapy treatments has been shown to sensitize tumours to the treatment. Microbial GGT is known to be a virulence factor too, important for the colonization of bacteria in host. However, all known inhibitors (mimics of its native substrate, glutamate) are highly toxic because they interfere with other enzyme pathways. However, a few successful efforts have been reported previously in designing species specific inhibitors. We aim to leverage the diversity seen in GGT family (pathogen vs. eukaryotes) for designing specific inhibitors. Thus, in the present study, we have used DIVERGE software to identify sites in GGT proteins, which are crucial for the functional and structural divergence of these proteins. Since, type II divergence sites vary in clade specific manner, so type II divergent sites were our focus of interest throughout the study. Type II divergent sites were identified for pathogen vs. eukaryotes clusters and sites were marked on clade specific representative structures HpGGT (2QM6) and HmGGT (4ZCG) of pathogen and eukaryotes clade respectively. The crucial divergent sites within 15 A radii of the binding cavity were highlighted, and in-silico mutations were performed on these sites to delineate the role of these sites on the mechanism of catalysis and protein folding. Further, the amino acid network (AAN) analysis was also performed by Cytoscape to delineate assortative mixing for cavity divergent sites which could strengthen our hypothesis. Additionally, molecular dynamics simulations were performed for wild complexes and mutant complexes close to physiological conditions (pH 7.0, 0.1 M ionic strength and 1 atm pressure) and the role of putative divergence sites and structural integrities of the homologous proteins have been analysed. The dynamics data were scrutinized in terms of RMSD, RMSF, non-native H-bonds and salt bridges. The RMSD, RMSF fluctuations of proteins complexes are compared, and the changes at protein ligand binding sites were highlighted. The outcomes of our study highlighted some crucial divergent sites which could be used for novel inhibitors designing in a species-specific manner. Since, for drug development, it is challenging to design novel drug by targeting similar protein which exists in eukaryotes, so this study could set up an initial platform to overcome this challenge and help to deduce the more effective targets for novel drug discovery.

Keywords: γ-glutamyltranspeptidase, divergence, species-specific, drug design

Procedia PDF Downloads 268

Authors: Babak Forouraghi

Abstract:

A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

Procedia PDF Downloads 59

Authors: Majed Al Otaibi, Melissa Lessard-Beaudoin, Amel Loudghi, Raphael Chouinard-Watkins, Melanie Plourde, Frederic Calon, C. Alexandre Castellano, Stephen Cunnane, Helene Payette, Pierrette Gaudreau, Denis Gris, Rona K. Graham

Abstract:

Introduction: Alzheimer disease (AD) is a chronic disorder that affects millions of individuals worldwide. Symptoms include memory dysfunction, and also alterations in attention, planning, language and overall cognitive function. Olfactory dysfunction is a common symptom of several neurological disorders including AD. Studying the mechanisms underlying the olfactory dysfunction may therefore lead to the discovery of potential biomarkers and/or treatments for neurodegenerative diseases. Objectives: To determine if olfactory dysfunction predicts future cognitive impairment in the aging population and to characterize the olfactory system in a murine model expressing a genetic factor of AD. Method: For the human study, quantitative olfactory tests (UPSIT and OMT) have been done on 93 subjects (aged 80 to 94 years) from the Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge) cohort accepting to participate in the ORCA secondary study. The telephone Modified Mini Mental State examination (t-MMSE) was used to assess cognition levels, and an olfactory self-report was also collected. In a separate cohort, olfactory cortical volume was calculated using MRI results from healthy old adults (n=25) and patients with AD (n=18) using the AAL single-subject atlas and performed with the PNEURO tool (PMOD 3.7). For the murine study, we are using Western blotting, RT-PCR and immunohistochemistry. Result: Human Study: Based on the self-report, 81% of the participants claimed to not suffer from any problem with olfaction. However, based on the UPSIT, 94% of those subjects showed a poor olfactory performance and different forms of microsmia. Moreover, the results confirm that olfactory function declines with age. We also detected a significant decrease in olfactory cortical volume in AD individuals compared to controls. Murine study: Preliminary data demonstrate there is a significant decrease in expression levels of the proform of caspase-3 and the caspase substrate STK3, in the olfactory bulb of mice expressing human APOE4 compared with controls. In addition, there is a significant decrease in the expression level of the caspase-9 proform and caspase-8 active fragment. Analysis of the mature neuron marker, NeuN, shows decreased expression levels of both isoforms. The data also suggest that Iba-1 immunostaining is increased in the olfactory bulb of APOE4 mice compared to wild type mice. Conclusions: The activation of caspase-3 may be the cause of the decreased levels of STK3 through caspase cleavage and may play role in the inflammation observed. In the clinical study, our results suggest that seniors are unaware of their olfactory function status and therefore it is not sufficient to measure olfaction using the self-report in the elderly. Studying olfactory function and cognitive performance in the aging population will help to discover biomarkers in the early stage of the AD.

Keywords: Alzheimer's disease, APOE4, cognition, caspase, brain atrophy, neurodegenerative, olfactory dysfunction

Procedia PDF Downloads 258

Authors: Bianca Peterson, Tomasz J. Sańko, Carlos C. Bezuidenhout, Johnnie Van Den Berg

Abstract:

Busseola fusca (Fuller) (Lepidoptera: Noctuidae), the maize stem borer, is a major pest in sub-Saharan Africa. It causes economic damage to maize and sorghum crops and has evolved non-recessive resistance to genetically modified (GM) maize expressing the Cry1Ab insecticidal toxin. Since B. fusca is a non-model organism, very little genomic information is publicly available, and is limited to some cytochrome c oxidase I, cytochrome b, and microsatellite data. The biology of B. fusca is well-described, but still poorly understood. This, in combination with its larval-specific behavior, may pose problems for limiting the spread of current resistant B. fusca populations or preventing resistance evolution in other susceptible populations. As part of on-going research into resistance evolution, B. fusca larvae were collected from Bt and non-Bt maize in South Africa, followed by RNA isolation (15 specimens) and sequencing on the Illumina HiSeq 2500 platform. Quality of reads was assessed with FastQC, after which Trimmomatic was used to trim adapters and remove low quality, short reads. Trinity was used for the de novo assembly, whereas TransRate was used for assembly quality assessment. Transcript identification employed BLAST (BLASTn, BLASTp, and tBLASTx comparisons), for which two libraries (nucleotide and protein) were created from 3.27 million lepidopteran sequences. Several transcripts that have previously been implicated in Cry toxin resistance was identified for B. fusca. These included aminopeptidase N, cadherin, alkaline phosphatase, ATP-binding cassette transporter proteins, and mitogen-activated protein kinase. MEGA7 was used to align these transcripts to reference sequences from Lepidoptera to detect mutations that might potentially be contributing to Cry toxin resistance in this pest. RSEM and Bioconductor were used to perform differential gene expression analysis on groups of B. fusca larvae challenged and unchallenged with the Cry1Ab toxin. Pairwise expression comparisons of transcripts that were at least 16-fold expressed at a false-discovery corrected statistical significance (p) ≤ 0.001 were extracted and visualized in a hierarchically clustered heatmap using R. A total of 329,194 transcripts with an N50 of 1,019 bp were generated from the over 167.5 million high-quality paired-end reads. Furthermore, 110 transcripts were over 10 kbp long, of which the largest one was 29,395 bp. BLAST comparisons resulted in identification of 157,099 (47.72%) transcripts, among which only 3,718 (2.37%) were identified as Cry toxin receptors from lepidopteran insects. According to transcript expression profiles, transcripts were grouped into three subclusters according to the similarity of their expression patterns. Several immune-related transcripts (pathogen recognition receptors, antimicrobial peptides, and inhibitors) were up-regulated in the larvae feeding on Bt maize, indicating an enhanced immune status in response to toxin exposure. Above all, extremely up-regulated arylphorin genes suggest that enhanced epithelial healing is one of the resistance mechanisms employed by B. fusca larvae against the Cry1Ab toxin. This study is the first to provide a resource base and some insights into a potential mechanism of Cry1Ab toxin resistance in B. fusca. Transcriptomic data generated in this study allows identification of genes that can be targeted by biotechnological improvements of GM crops.

Keywords: epithelial healing, Lepidoptera, resistance, transcriptome

Procedia PDF Downloads 201

Authors: Vincent Oghenekevbe Olughor, Olusoji Mayowa Ige

Abstract:

Except for a preexisting liver disease and malnutrition, there are no predilections for low serum albumin (SA) levels in humans. At normal reference levels (4.0-6.0g/dl) SA is a universal marker for mortality and morbidity risks assessments where depletion by 1.0g/dl increases mortality risk by 137% and morbidity by 89%.It has 40 known functions contributing significantly to the sustenance of human life. A depletion in SA to <2.2g/dl, in most clinical settings worldwide, leads to loss of oncotic pressure of blood causing clinical manifestations of bipedal Oedema, in which the patients remain conscious. SA also contributes significantly to buffering of blood to a life-sustaining pH of 7.35-7.45. A drop in blood pH to <6.9 will lead to instant coma and death, which can occur after SA continues to deplete after manifestations of bipedal Oedema. In an intervention study conducted in 2014 following the discovery that “SA is depleted during malaria fever”, a Nutraceutical formulated for use as treatment adjunct to prevent SA depletions during malaria to <2.4g/dl after Efficacy testing was found to be satisfactory. There are five known types of Malaria caused by Apicomplexan parasites, Plasmodium: the most lethal being that caused by Plasmodium falciparum causing malignant tertian malaria, in which the fever was occurring every 48 hours coincides with the dumping of malaria-toxins (Hemozoin) into blood, causing contamination: blood must remain sterile. Other Apicomplexan parasites, Toxoplasma and Cryptosporidium, are opportunistic infections of HIV. Separate studies showed SA depletions in MDRTB (multidrug resistant TB), and MDRTB-HIV patients by the same mechanism discovered with malaria and such depletions will be further complicated whenever Apicomplexan parasitic infections co-exist. Both Apicomplexan parasites and the TB parasite belong to the Obligate-group of Parasites, which are parasites that replicate only inside its host; and most of them have capacities to over-consume host nutrients during parasitaemia. In MDRTB patients the body attempts repeatedly to prevent depletions in SA to critical levels in the presence of adequate nutrients and only for a while in MDRTB-HIV patients. These groups of patients will, therefore, benefit from the already tested Nutraceutical in malaria patients. The Nutraceutical bio-Powder was formulated (to BP 1988 specification) from twelve nature-based food-grade nutrients containing all dedicated nutrients for ensuring improved synthesis of Albumin by the liver. The Nutraceutical was administered daily for 38±2days in 23 children, in a prospective phase-2 clinical trial, and its impact on body weight and core blood parameters were documented at the start and end of efficacy testing period. Sixteen children who did not experience malaria-induced depletions of SA had significant SA increase; seven children who experienced malaria-induced depletions of SA had insignificant SA decrease. The Packed Cell Volume Percentage (PCV %), a measure of the Oxygen carrying capacity of blood and the amount of nutrients the body can absorb, increased in both groups. The total serum proteins (SA+ Globulins) increased or decreased within the continuum of normal. In conclusion, MDRTB and MDRTB-HIV patients will benefit from a variant of this Nutraceutical when used as treatment adjunct.

Keywords: antitrypsin-free Nutraceutical, apicomplexan parasites, no predilections for low serum albumin, toxoplasmosis

Procedia PDF Downloads 288

Authors: Babak Forouraghi

Abstract:

A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

Procedia PDF Downloads 61