Search results for: artificial cell
Commenced in January 2007
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Edition: International
Paper Count: 5518

Search results for: artificial cell

4588 Impact of Natural and Artificial Disasters, Lackadaisical and Semantic Approach in Risk Management, and Mitigation Implication for Sustainable Goals in Nigeria, from 2009 to 2022

Authors: Wisdom Robert Duruji, Moses Kanayochukwu Ifoh, Efeoghene Edward Esiemunobo

Abstract:

This study examines the impact of natural and artificial disasters, lackadaisical and semantic approach in risk management, and mitigation implication for sustainable development goals in Nigeria, from 2009 to 2022. The study utilizes a range of research methods to achieve its objectives. These include literature review, website knowledge, Google search, news media information, academic journals, field-work and on-site observations. These diverse methods allow for a comprehensive analysis on the impact and the implications being study. The study finds that paradigm shift from remediating seismic, flooding, environmental pollution and degradation natural disasters by Nigeria Emergency Management Agency (NEMA), to political and charity organization; has plunged risk reduction strategies to embezzling opportunities. However, this lackadaisical and semantic approach in natural disaster mitigation, invariably replicates artificial disasters in Nigeria through: Boko Haram terrorist organization, Fulani herdsmen and farmers conflicts, political violence, kidnapping for ransom, ethnic conflicts, Religious dichotomy, insurgency, secession protagonists, unknown-gun-men, and banditry. This study also, finds that some Africans still engage in self-imposed slavery through human trafficking, by nefariously stow-away to Europe; through Libya, Sahara desert and Mediterranean sea; in search for job opportunities, due to ineptitude in governance by their leaders; a perilous journey that enhanced artificial disasters in Nigeria. That artificial disaster fatality in Nigeria increased from about 5,655 in 2009 to 114,318 in 2018; and to 157,643 in 2022. However, financial and material loss of about $9.29 billion was incurred in Nigeria due to natural disaster, while about $70.59 billion was accrued due to artificial disaster; from 2009 to 2018. Although disaster risk mitigation and politics can synergistically support sustainable development goals; however, they are different entities, and need for distinct separations in Nigeria, as in reality and perception. This study concluded that referendum should be conducted in Nigeria, to ascertain its current status as a nation. Therefore it is recommended that Nigerian governments should refine its naturally endowed crude oil locally; to end fuel subsidy scam, corruption and poverty in Nigeria!

Keywords: corruption, crude oil, environmental risk analysis, Nigeria, referendum, terrorism

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4587 An Automated Optimal Robotic Assembly Sequence Planning Using Artificial Bee Colony Algorithm

Authors: Balamurali Gunji, B. B. V. L. Deepak, B. B. Biswal, Amrutha Rout, Golak Bihari Mohanta

Abstract:

Robots play an important role in the operations like pick and place, assembly, spot welding and much more in manufacturing industries. Out of those, assembly is a very important process in manufacturing, where 20% of manufacturing cost is wholly occupied by the assembly process. To do the assembly task effectively, Assembly Sequences Planning (ASP) is required. ASP is one of the multi-objective non-deterministic optimization problems, achieving the optimal assembly sequence involves huge search space and highly complex in nature. Many researchers have followed different algorithms to solve ASP problem, which they have several limitations like the local optimal solution, huge search space, and execution time is more, complexity in applying the algorithm, etc. By keeping the above limitations in mind, in this paper, a new automated optimal robotic assembly sequence planning using Artificial Bee Colony (ABC) Algorithm is proposed. In this algorithm, automatic extraction of assembly predicates is done using Computer Aided Design (CAD) interface instead of extracting the assembly predicates manually. Due to this, the time of extraction of assembly predicates to obtain the feasible assembly sequence is reduced. The fitness evaluation of the obtained feasible sequence is carried out using ABC algorithm to generate the optimal assembly sequence. The proposed methodology is applied to different industrial products and compared the results with past literature.

Keywords: assembly sequence planning, CAD, artificial Bee colony algorithm, assembly predicates

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4586 Combinational Therapeutic Targeting of BRD4 and CDK7 Synergistically Induces Anticancer Effects in Hepatocellular Carcinoma

Authors: Xinxiu Li, Chuqian Zheng, Yanyan Qian, Hong Fan

Abstract:

Objectives: In hepatocellular carcinoma (HCC), oncogenes are continuously and robustly transcribed due to aberrant expression of essential components of the trans-acting super-enhancers (SE) complex. Preclinical and clinical trials are now being conducted on small-molecule inhibitors that target core-transcriptional components, including as transcriptional bromodomain protein 4 (BRD4) and cyclin-dependent kinase 7 (CDK7), in a number of malignant tumors. This study aims to explore whether co-overexpression of BRD4 and CDK7 is a potential marker of worse prognosis and a combined therapeutic target in HCC. Methods: The expression pattern of BRD4 and CDK7 and their correlation with prognosis in HCC were analyzed by RNA sequencing data and survival data of HCC patients from TCGA and GEO datasets. The protein levels of BRD4 and CDK7 were determined by immunohistochemistry (IHC), and survival data of patients were analyzed using the Kaplan-Meier method. The mRNA expression levels of genes in HCC cell lines were evaluated by quantitative PCR (q-PCR). CCK-8 and colony formation assays were conducted to assess cell proliferation of HCC upon treatment with BRD4 inhibitor JQ1 or/and CDK7 inhibitor THZ1. Results: It was shown that BRD4 and CDK7 were often overexpressed in HCCs and were associated with poor prognosis of HCC by analyzing the TCGA and GEO datasets. BRD4 or CDK7 overexpression was related to a lower survival rate. It's interesting to note that co-overexpression of CDK7 and BRD4 was a worse prognostic factor in HCC. Treatment with JQ1 or THZ1 alone had an inhibitory effect on cell proliferation; however, when JQ1 and THZ1 were combined, there was a more notable suppression of cell growth. At the same time, the combined use of JQ1 and THZ1 synergistically suppresses the expression of HCC driver genes. Conclusion: Our research revealed that BRD4 and CDK7 coupled can be a useful biomarker in HCC prognosis and the combination of JQ1 and THZ1 can be a promising therapeutic therapy against HCC.

Keywords: BRD4, CDK7, cell proliferation, combined inhibition

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4585 Artificial Intelligence in Disease Diagnosis

Authors: Shalini Tripathi, Pardeep Kumar

Abstract:

The method of translating observed symptoms into disease names is known as disease diagnosis. The ability to solve clinical problems in a complex manner is critical to a doctor's effectiveness in providing health care. The accuracy of his or her expertise is crucial to the survival and well-being of his or her patients. Artificial Intelligence (AI) has a huge economic influence depending on how well it is applied. In the medical sector, human brain-simulated intellect can help not only with classification accuracy, but also with reducing diagnostic time, cost and pain associated with pathologies tests. In light of AI's present and prospective applications in the biomedical, we will identify them in the paper based on potential benefits and risks, social and ethical consequences and issues that might be contentious but have not been thoroughly discussed in publications and literature. Current apps, personal tracking tools, genetic tests and editing programmes, customizable models, web environments, virtual reality (VR) technologies and surgical robotics will all be investigated in this study. While AI holds a lot of potential in medical diagnostics, it is still a very new method, and many clinicians are uncertain about its reliability, specificity and how it can be integrated into clinical practice without jeopardising clinical expertise. To validate their effectiveness, more systemic refinement of these implementations, as well as training of physicians and healthcare facilities on how to effectively incorporate these strategies into clinical practice, will be needed.

Keywords: Artificial Intelligence, medical diagnosis, virtual reality, healthcare ethical implications 

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4584 Roughness Discrimination Using Bioinspired Tactile Sensors

Authors: Zhengkun Yi

Abstract:

Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.

Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination

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4583 ChatGPT as a “Foreign Language Teacher”: Attitudes of Tunisian English Language Learners

Authors: Leila Najeh Bel'Kiry

Abstract:

Artificial intelligence (AI) brought about many language robots, with ChatGPT being the most sophisticated thanks to its human-like linguistic capabilities. This aspect raises the idea of using ChatGPT in learning foreign languages. Starting from the premise that positions ChatGPT as a mediator between the language and the leaner, functioning as a “ghost teacher" offering a peaceful and secure learning space, this study aims to explore the attitudes of Tunisian students of English towards ChatGPT as a “Foreign Language Teacher” . Forty-five students, in their third year of fundamental English at Tunisian universities and high institutes, completed a Likert scale questionnaire consisting of thirty-two items and covering various aspects of language (phonology, morphology, syntax, semantics, and pragmatics). A scale ranging from 'Strongly Disagree,' 'Disagree,' 'Undecided,' 'Agree,' to 'Strongly Agree.' is used to assess the attitudes of the participants towards the integration of ChaGPTin learning a foreign language. Results indicate generally positive attitudes towards the reliance on ChatGPT in learning foreign languages, particularly some compounds of language like syntax, phonology, and morphology. However, learners show insecurity towards ChatGPT when it comes to pragmatics and semantics, where the artificial model may fail when dealing with deeper contextual and nuanced language levels.

Keywords: artificial language model, attitudes, foreign language learning, ChatGPT, linguistic capabilities, Tunisian English language learners

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4582 Applying Sequential Pattern Mining to Generate Block for Scheduling Problems

Authors: Meng-Hui Chen, Chen-Yu Kao, Chia-Yu Hsu, Pei-Chann Chang

Abstract:

The main idea in this paper is using sequential pattern mining to find the information which is helpful for finding high performance solutions. By combining this information, it is defined as blocks. Using the blocks to generate artificial chromosomes (ACs) could improve the structure of solutions. Estimation of Distribution Algorithms (EDAs) is adapted to solve the combinatorial problems. Nevertheless many of these approaches are advantageous for this application, but only some of them are used to enhance the efficiency of application. Generating ACs uses patterns and EDAs could increase the diversity. According to the experimental result, the algorithm which we proposed has a better performance to solve the permutation flow-shop problems.

Keywords: combinatorial problems, sequential pattern mining, estimationof distribution algorithms, artificial chromosomes

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4581 Synthesis and Biological Activity Evaluation of U Complexes

Authors: Mohammad Kazem Mohammadi

Abstract:

The use of anticancer agents forms an important part of the treatment of cancer of various types. Uranyl Complexes with DPHMP ligand have been used for the prevention and treatment of cancers. U(IV) metal complexes prepared by reaction of uranyl salt UO2 (NO3)2.6H2O with DPHMP in dry acetonitrile. Characterization of the ligand and its complexes was made by microanalyses, FT-IR, 1H NMR, 13C NMR and UV–Visible spectroscopy. These new complex showed excellent antitumor activity against two kinds of cancer cells that that are HT29:Haman colon adenocarcinoma cell line and T47D:human breast adenocarcinoma cell line.

Keywords: uranyl complexes, DPHMP ligand, antitumor activity, HT29, T47D

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4580 Investigating Role of Novel Molecular Players in Forebrain Roof-Plate Midline Invagination

Authors: Mohd Ali Abbas Zaidi, Meenu Sachdeva, Jonaki Sen

Abstract:

In the vertebrate embryo, the forebrain anlagen develops from the anterior-most region of the neural tube which is the precursor of the central nervous system (CNS). The roof plate located at the dorsal midline region of the forebrain anlagen, acts as a source of several secreted molecules involved in patterning and morphogenesis of the forebrain. One such key morphogenetic event is the invagination of the forebrain roof plate which results in separation of the single forebrain vesicle into two cerebral hemispheres. Retinoic acid (RA) signaling plays a key role in this process. Blocking RA signaling at the dorsal forebrain midline inhibits dorsal invagination and results in the absence of certain key features of this region, such as thinning of the neuroepithelium and a lowering of cell proliferation. At present we are investigating the possibility of other signaling pathways acting in concert with RA signaling to regulate this process. We have focused on BMP signaling, which we found to be active in a mutually exclusive domain to that of RA signaling within the roof plate. We have also observed that there is a change in BMP signaling activity on modulation of RA signaling indicating an antagonistic relationship between the two. Moreover, constitutive activation of BMP signaling seems to completely inhibit thinning and partially affect invagination, leaving the lowering of cell proliferation in the midline unaffected. We are employing in-silico modeling as well as molecular manipulations to investigate the relative contribution if any, of regional differences in rates of cell proliferation and thinning of the neuroepithelium towards the process of invagination. We have found expression of certain cell adhesion molecules in forebrain roof-plate whose mRNA localization across the thickness of neuroepithelium is influenced by Bmp and RA signaling, giving regional rigidity to roof plate and assisting invagination. We also found expression of certain cytoskeleton modifiers in a localized small domains in invaginating forebrain roof plate suggesting that midline invagination is under control of many factors.

Keywords: bone morphogenetic signaling, cytoskeleton, cell adhesion molecules, forebrain roof plate, retinoic acid signaling

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4579 Investigation of Ezetimibe Administration on Cell Survival Markers in Kidney Ischemia

Authors: Zahra Heydari

Abstract:

Introduction: One of the major clinical issues is acute renal failure, which is caused by ischemia-reperfusion of the kidney and is associated with high mortality. Despite advances in this area, important issues such as tissue necrosis, cell apoptosis, and so on in damaged tissue are suggestive for more researches and study on this subject. Objective: Evaluation of the potential utility of Ezetimibe in reducing injuries and cell death induced by kidney ischemia/ reperfusion through inducing expression changes of different cellular pathways in adult Sprague-Dawley rats. Materials and methods: Forty rats weighing 180-200g were divided into 4 groups. For this purpose, the first right kidneys of the rats were removed during surgery. After 20 days, the left renal artery was closed with a soft clamp and reperfusion was performed. After 24 hours, blood samples were collected and sent to the laboratory with kidneys to measure bax and bcl-2 by Western blotting and histopathological tests. Results: Quantitative damage reviews of Kidney tissue indicates damage Acute and severe tubular lesions were observed in the ischemia group. Also, the amount of injury was significantly reduced in the treatment group. There was also a significant difference between the ischemia and sham groups. In general, the results show that a single dose of 1.2 mg/kg of ezetimibe can reduce the bax/ bcl-2 ratio compared to the ischemia group. In general, the results showed Ezetimibe is effective in reducing cell damage and death due to ischemia/ reperfusion after renal ischemia through changes in the expression of various cellular pathways in rats.

Keywords: acute renal failure, renal ischemia-reperfusion injury, ezetimibe, apoptosis

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4578 Estimation of Residual Stresses in Thick Walled Cylinder by Radial Basis Artificial Neural

Authors: Mohammad Heidari

Abstract:

In this paper a method for high strength steel is proposed of residual stresses in autofrettaged tubes by combination of artificial neural networks is presented. Many different thick walled cylinders that were subjected to different conditions were studied. At first, the residual stress is calculated by analytical solution. Then by changing of the parameters that influenced in residual stresses such as percentage of autofrettage, internal pressure, wall ratio of cylinder, material property of cylinder, bauschinger and hardening effect factor, a neural network is created. These parameters are the input of network. The output of network is residual stress. Numerical data, employed for training the network and capabilities of the model in predicting the residual stress has been verified. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 2.75% in predicting residual stress of thick wall cylinder. Further analysis of residual stress of thick wall cylinder under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach.

Keywords: thick walled cylinder, residual stress, radial basis, artificial neural network

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4577 Effects of Medium Composition on the Production of Biomass and a Carbohydrate Isomerase by a Novel Strain of Lactobacillus

Authors: M. Miriam Hernández-Arroyo, Ivonne Caro-Gonzales, Miguel Ángel Plascencia-Espinosa, Sergio R. Trejo-Estrada

Abstract:

A large biodiversity of Lactobacillus strains has been detected in traditional foods and beverages from Mexico. A selected strain of Lactobacillus sp - PODI-20, used for the obtained from an artisanal fermented beverage was cultivated in different carbon sources in a complex medium, in order to define which carbon sourced induced more effectively the isomerization of arabinose by cell fractions obtained by fermentation. Four different carbon sources were tested in a medium containing peptone and yeast extract and mineral salts. Glucose, galactose, arabinose, and lactose were tested individually at three different concentrations: 3.5, 6, and 10% w/v. The biomass yield ranged from 1.72 to 17.6 g/L. The cell pellet was processed by mechanical homogenization. Both fractions, the cellular debris, and the lysis supernatant were tested for their ability to isomerize arabinose into ribulose. The highest yield of isomer was 12 % of isomerization in the supernatant fractions; whereas up to 9.3% was obtained by the use of cell debris. The isomerization of arabinose has great significance in the production of lactic acid by fermentation of complex carbohydrate hydrolysates.

Keywords: isomerase, tagatose, aguamiel, isomerization

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4576 AI-Based Technologies for Improving Patient Safety and Quality of Care

Authors: Tewelde Gebreslassie Gebreanenia, Frie Ayalew Yimam, Seada Hussen Adem

Abstract:

Patient safety and quality of care are essential goals of health care delivery, but they are often compromised by human errors, system failures, or resource constraints. In a variety of healthcare contexts, artificial intelligence (AI), a quickly developing field, can provide fresh approaches to enhancing patient safety and treatment quality. Artificial Intelligence (AI) has the potential to decrease errors and enhance patient outcomes by carrying out tasks that would typically require human intelligence. These tasks include the detection and prevention of adverse events, monitoring and warning patients and clinicians about changes in vital signs, symptoms, or risks, offering individualized and evidence-based recommendations for diagnosis, treatment, or prevention, and assessing and enhancing the effectiveness of health care systems and services. This study examines the state-of-the-art and potential future applications of AI-based technologies for enhancing patient safety and care quality, as well as the opportunities and problems they present for patients, policymakers, researchers, and healthcare providers. In order to ensure the safe, efficient, and responsible application of AI in healthcare, the paper also addresses the ethical, legal, social, and technical challenges that must be addressed and regulated.

Keywords: artificial intelligence, health care, human intelligence, patient safty, quality of care

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4575 Effect of Copper Complexes on Human Colon Carcinoma Cell Line and Human Breast Carcinoma Cell Line

Authors: Katarína Koňariková, Georgios A. Perdikaris, Lucia Andrezálová, Zdeňka Ďuračková, Lucia Laubertová, Helena Gbelcová, Ingrid Žitňanová

Abstract:

Introduction: The continuous demand for new anti-cancer drugs has stimulated chemotherapeutic research based on the use of essential metalloelements with the aim to develop potential drugs with lower toxicity and higher antiproliferative activity against tumors. Copper(II) and its complexes play an important role as suitable species for antiproliferative tests. Objectives: The central objective of the current study was to investigate the potential in vitro anti-proliferative effects of N-salicylidene-L-glutamato copper (II) complexes and molecular mechanism of apoptosis induced by tested complexes. In our project we tested N-salicylidene-L-glutamato copper (II) complexes ZK1 - [Cu(N-salicylidene-L-glutamato)(H2O)2].H2O; MK0 - ([Cu2(N-sal-D,L-glu)2(isoquinoline)2].2H2O); MK1 - [Cu(N-salicylidene-5-methyl-L-glutamato)(H2O)].H2O; MK3 - transbis(ethanol)tetrakis(imidazol)Cu(II)(2+)bis(N-salicylidene-D,L-glutamato-N,O)-KO:KO´-(imidazol); MK5 - [Cu(N-salicylidene-D,L- glutamato)(2-methylimidazol] at concentration range 0.001-100 µmol/L against human colon carcinoma cell line HT-29 and human breast carcinoma cell line MCF-7. Methods: Viability was assessed by direct counting of 0.4% trypan blue dye-excluding cells after 24, 48 and 72 hour cultivations with or without copper complex and by MTT assay. To analyze the type of cell death and its mechanism induced by our copper complex we used different methods. To distinguish apoptosis from necrosis we used electrophoretic analysis, to study the activity of caspases 8 and 9 – luminometric analysis and caspase activity 3 colorimetric assay. Results: The observed anti-proliferative effect of the copper complexes appeared to be dose-, time- and cell line- dependent. Human colon carcinoma cells HT-29 appeared to be more sensitive to the complex MK0 ([Cu2(N-sal-D,L-glu)2(isoquinoline)2].2H2O) than to ZK1 ([Cu(N-salicylidene-L-glutamato)(H2O)2].H2O) and MK1 ([Cu(N-salicylidene-5-methyl-L-glutamato)(H2O)].H2O)). Human colon carcinoma cells HT-29 appeared to be more sensitive to the complex than human breast carcinoma cells MCF-7. IC50 decreased with time of incubation (24, 48 and 72h) for HT-29, but increased for MCF-7. By electrophoresis we found apoptotic cell death induced by our copper complexes in HT-29 at concentrations 1, 10, 50 and 100 µmol/L after 48h (ZK1) and 72h (MK0, MK1) and in MCF-7 we did not find apoptosis. We also studied molecular mechanism of apoptosis in HT-29 induced by copper complexes. We found active caspase 9 in HT-29 after ZK1 ([Cu(N-salicylidene-L-glutamato)(H2O)2].H2O) and MK1 ([Cu(N-salicylidene-5-methyl-L-glutamato)(H2O)].H2O)) influence and active caspase 8 after MK0 ([Cu2(N-sal-D,L-glu)2(isoquinoline)2].2H2O) influence. Conclusion: Our copper complexes showed cytotoxic activities against human colon carcinoma cells HT-29 and breast cancer cell line MCF-7 in vitro. Apoptosis was activated by mitochondrial pathway (intrinsic pathway) in case of ZK1 [Cu(N-salicylidene-L-glutamato)(H2O)2].H2O; MK1 [Cu(N-salicylidene-5-methyl-L-glutamato)(H2O)].H2O; MK3 - transbis(ethanol)tetrakis(imidazol)Cu(II)(2+)bis(N-salicylidene-D,L-glutamato-N,O)-KO:KO´-(imidazol) and MK5 - [Cu(N-salicylidene-D,L- glutamato)(2-methylimidazol] copper complexes and by death receptors (extrinsic pathway) in case of MK0 [Cu2(N-sal-D,L-glu)2(isoquinoline)2].2H2O copper complex in HT-29.

Keywords: apoptosis, copper complex, cancer, carcinoma cell line

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4574 Emerging Technology for Business Intelligence Applications

Authors: Hsien-Tsen Wang

Abstract:

Business Intelligence (BI) has long helped organizations make informed decisions based on data-driven insights and gain competitive advantages in the marketplace. In the past two decades, businesses witnessed not only the dramatically increasing volume and heterogeneity of business data but also the emergence of new technologies, such as Artificial Intelligence (AI), Semantic Web (SW), Cloud Computing, and Big Data. It is plausible that the convergence of these technologies would bring more value out of business data by establishing linked data frameworks and connecting in ways that enable advanced analytics and improved data utilization. In this paper, we first review and summarize current BI applications and methodology. Emerging technologies that can be integrated into BI applications are then discussed. Finally, we conclude with a proposed synergy framework that aims at achieving a more flexible, scalable, and intelligent BI solution.

Keywords: business intelligence, artificial intelligence, semantic web, big data, cloud computing

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4573 Hepatoprotective Evaluation of Potent Antioxidant Fraction from Urtica dioica L.: In vitro and In vivo Studies

Authors: Bhuwan C. Joshi, Atish Prakash, Ajudhia N. Kalia

Abstract:

Ethnopharmacological relevance: The plant Urtica dioica L. (Urticaceae) is used in various diseases including hepatic ailments. Traditionally, the leaves and roots of the plant are used in jaundice. Objective: The aim of the present work was to evaluate hepatoprotective potential of potent antioxidant from Urtica dioica L. against CCl4 induced hepatotoxicity in-vitro and in-vivo model. Materials and methods: Antioxidant activity of hydro alcoholic extract and its fractions petroleum ether fraction (PEF), ethyl acetate fraction (EAF), n-butanol fraction (NBF) and aqueous fraction (AF) were determined by DPPH radicals scavenging assay. Fractions were subjected to in-vitro cell line study. Further, the most potent fraction (EAF) was subjected to in-vivo study. The in-vivo hepatoprotective active fraction was chromatographed on silica column to isolate the bioactive constituent(s). Structure elucidation was done by using various spectrophotometric techniques like UV, IR, 1H NMR, 13C NMR and MS spectroscopy. Results and conclusion: The ethyl acetate fraction (EAF) of Urtica. dioica L. possessed the potent antioxidant activity viz. DPPH (IC50 78.99 ± 0.17 µg/ml). The in-vitro cell line study showed EAF prevented the cell damage. The EAF significantly attenuated the increased liver enzymes activities in serum and tissue. Column chromatography of most potent antioxidant fraction (EAF) leads to the isolation of 4-hydroxy-3-methoxy cinnamic acid which is responsible for its hepatoprotective potential. Hence, the present study suggests that EAF has significant antioxidant and hepatoprotective potential on CCl4 induced hepatotoxicity in-vitro and in-vivo.

Keywords: Urtica dioica L., antioxidant, HepG2 cell line, hepatoprotective

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4572 Novel Nickel Complex Compound Reactivates the Apoptotic Network, Cell Cycle Arrest and Cytoskeletal Rearrangement in Human Colon and Breast Cancer Cells

Authors: Nima Samie, Batoul Sadat Haerian, Sekaran Muniandy, M. S. Kanthimathi

Abstract:

Colon and breast cancers are categorized as the most prevalent types of cancer worldwide. Recently, the broad clinical application of metal complex compounds has led to the discovery of potential therapeutic drugs. The aim of this study was to evaluate the cytotoxic action of a selected nickel complex compound (NCC) against human colon and breast cancer cells. In this context, we determined the potency of the compound in the induction of apoptosis, cell cycle arrest, and cytoskeleton rearrangement. HT-29, WiDr, CCD-18Co, MCF-7 and Hs 190.T cell lines were used to determine the IC50 of the compound using the MTT assay. Analysis of apoptosis was carried out using immunofluorescence, acridine orange/ propidium iodide double staining, Annexin-V-FITC assay, evaluation of the translocation of NF-kB, oxygen radical antioxidant capacity, quenching of reactive oxygen species content , measurement of LDH release, caspase-3/-7, -8 and -9 assays and western blotting. The cell cycle arrest was examined using flowcytometry and gene expression was assessed using qPCR array. Results showed that our nickel complex compound displayed a potent suppressive effect on HT-29, WiDr, MCF-7 and Hs 190.T after 24 h of treatment with IC50 value of 2.02±0.54, 2.13±0.65, 3.76±015 and 3.14±0.45 µM respectively. This cytotoxic effect on normal cells was insignificant. Dipping in the mitochondrial membrane potential and increased release of cytochrome c from the mitochondria indicated induction of the intrinsic apoptosis pathway by the nickel complex compound. Activation of this pathway was further evidenced by significant activation of caspase 9 and 3/7.The nickel complex compound (NCC) was also shown activate the extrinsic pathways of apoptosis by activation of caspase-8 which is linked to the suppression of NF-kB translocation to the nucleus. Cell cycle arrest in the G1 phase and up-regulation of glutathione reductase, based on excessive ROS production were also observed. The results of this study suggest that the nickel complex compound is a potent anti-cancer agent inducing both intrinsic and extrinsic pathways as well as cell cycle arrest in colon and breast cancer cells.

Keywords: nickel complex, apoptosis, cytoskeletal rearrangement, colon cancer, breast cancer

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4571 Identification of Blood Biomarkers Unveiling Early Alzheimer's Disease Diagnosis Through Single-Cell RNA Sequencing Data and Autoencoders

Authors: Hediyeh Talebi, Shokoofeh Ghiam, Changiz Eslahchi

Abstract:

Traditionally, Alzheimer’s disease research has focused on genes with significant fold changes, potentially neglecting subtle but biologically important alterations. Our study introduces an integrative approach that highlights genes crucial to underlying biological processes, regardless of their fold change magnitude. Alzheimer's Single-cell RNA-seq data related to the peripheral blood mononuclear cells (PBMC) was extracted from the Gene Expression Omnibus (GEO). After quality control, normalization, scaling, batch effect correction, and clustering, differentially expressed genes (DEGs) were identified with adjusted p-values less than 0.05. These DEGs were categorized based on cell-type, resulting in four datasets, each corresponding to a distinct cell type. To distinguish between cells from healthy individuals and those with Alzheimer's, an adversarial autoencoder with a classifier was employed. This allowed for the separation of healthy and diseased samples. To identify the most influential genes in this classification, the weight matrices in the network, which includes the encoder and classifier components, were multiplied, and focused on the top 20 genes. The analysis revealed that while some of these genes exhibit a high fold change, others do not. These genes, which may be overlooked by previous methods due to their low fold change, were shown to be significant in our study. The findings highlight the critical role of genes with subtle alterations in diagnosing Alzheimer's disease, a facet frequently overlooked by conventional methods. These genes demonstrate remarkable discriminatory power, underscoring the need to integrate biological relevance with statistical measures in gene prioritization. This integrative approach enhances our understanding of the molecular mechanisms in Alzheimer’s disease and provides a promising direction for identifying potential therapeutic targets.

Keywords: alzheimer's disease, single-cell RNA-seq, neural networks, blood biomarkers

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4570 Developing an AI-Driven Application for Real-Time Emotion Recognition from Human Vocal Patterns

Authors: Sayor Ajfar Aaron, Mushfiqur Rahman, Sajjat Hossain Abir, Ashif Newaz

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This study delves into the development of an artificial intelligence application designed for real-time emotion recognition from human vocal patterns. Utilizing advanced machine learning algorithms, including deep learning and neural networks, the paper highlights both the technical challenges and potential opportunities in accurately interpreting emotional cues from speech. Key findings demonstrate the critical role of diverse training datasets and the impact of ambient noise on recognition accuracy, offering insights into future directions for improving robustness and applicability in real-world scenarios.

Keywords: artificial intelligence, convolutional neural network, emotion recognition, vocal patterns

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4569 Solid-State Luminescence of Fluorenone Grafted onto Cellulose Aldehyde Backbone Using Different Organic Amine Spacers

Authors: Isam M. Arafa, Mazin Y. Shatnawi, Yaser A. Yousef, Batool Zaid Al-Momani

Abstract:

The present work describes the preparation, characterization, and luminescence of a series of fluorenone (FL) based luminophores grafted onto modified cellulose microfibers. The FL is condensed onto cellulose aldehyde using three diamine spacers (H₂N-NH₂, H₂N(CH₂)₂NH₂ and H₂N(CH₂)₃NH₂) to afford Cell=Spacer=FL. The obtained products were characterized by spectroscopic (FT-IR, UV–Vis), thermal gravimetric analysis (TGA), and microscopic (Optical, SEM) techniques. The UV-Vis spectra of the FL=N(CH₂)ₓNH₂ (x = 0, 2, 3) moieties show that they are transparent in the 375- 800 nm region while they exhibit intense absorption band below 350 nm attributed to n-π* and π-π* transitions. The solid-state photoluminescence (PLs-s) of the cold-pressed pellets of the FL=N(CH₂)ₓNH₂ and Cell=Spacer=FL placed in a quartz cuvette show strong emission in the 500-550 nm region upon irradiation with Xe lamp light (λex = 320 nm). The PLs-s green emission of the grafted Cell=Spacer=FL was evaluated relative to that of the FL-based precursor. These grafted conjugated products have the potential to be used as analyte sensors for typical nitroaromatics/aromatic amines and be further extended to immunoassay studies for aromatic amino acids such as phenylalanine and histidine.

Keywords: luminescence, cellulose, fluorenone, grafting, solid state

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4568 Immobilized Iron Oxide Nanoparticles for Stem Cell Reconstruction in Magnetic Particle Imaging

Authors: Kolja Them, Johannes Salamon, Harald Ittrich, Michael Kaul, Tobias Knopp

Abstract:

Superparamagnetic iron oxide nanoparticles (SPIONs) are nanoscale magnets which can be biologically functionalized for biomedical applications. Stem cell therapies to repair damaged tissue, magnetic fluid hyperthermia for cancer therapy and targeted drug delivery based on SPIONs are prominent examples where the visualization of a preferably low concentrated SPION distribution is essential. In 2005 a new method for tomographic SPION imaging has been introduced. The method named magnetic particle imaging (MPI) takes advantage of the nanoparticles magnetization change caused by an oscillating, external magnetic field and allows to directly image the time-dependent nanoparticle distribution. The SPION magnetization can be changed by the electron spin dynamics as well as by a mechanical rotation of the nanoparticle. In this work different calibration methods in MPI are investigated for image reconstruction of magnetically labeled stem cells. It is shown that a calibration using rotationally immobilized SPIONs provides a higher quality of stem cell images with fewer artifacts than a calibration using mobile SPIONs. The enhancement of the image quality and the reduction of artifacts enables the localization and identification of a smaller number of magnetically labeled stem cells. This is important for future medical applications where low concentrations of functionalized SPIONs interacting with biological matter have to be localized.

Keywords: biomedical imaging, iron oxide nanoparticles, magnetic particle imaging, stem cell imaging

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4567 Synthesizing an Artificial Loess for Geotechnical Investigations of Collapsible Soil Behavior

Authors: Hamed Sadeghi, Pouya A. Panahi, Hamed Nasiri, Mohammad Sadeghi

Abstract:

Collapsible soils like loess comprise an important category of problematic soils for construction purposes and sustainable development. As a result, research on both geological and geotechnical aspects of this type of soil have been in progress for decades. However, considerable natural variability in physical properties of in-situ loess strata even in a single block sample challenges the fundamental laboratory investigations. The reason behind this is that it is somehow impossible to remove the effect of a specific factor like void ratio from fair comparisons to come with a reliable conclusion. In order to cope with this limitation, two types of artificially made dispersive and calcareous loess are introduced which can be easily reproduced in any soil mechanics laboratory provided that all its compositions are known and controlled. The collapse potential is explored for a variety of soil water salinity and lime content and comparisons are made against the natural soil behavior. Trends are reported for the influence of pore water salinity on collapse potential under different osmotic flow conditions. The most important advantage of artificial loess is the ease of controlling cementing agent content like calcite or dispersive potential for studying their influence on mechanical soil behavior.

Keywords: artificial loess, unsaturated soils, collapse potential, dispersive clays, laboratory tests

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4566 Dual Drug Piperine-Paclitaxel Nanoparticles Inhibit Migration and Invasion in Human Breast Cancer Cells

Authors: Monika Verma, Renuka Sharma, B. R. Gulati, Namita Singh

Abstract:

In combination therapy, two chemotherapeutic agents work together in a collaborative action. It has appeared as one of the promising approaches to improve anti-cancer treatment efficacy. In the present investigation, piperine (P-NPS), paclitaxel (PTX NPS), and a combination of both, piperine-paclitaxel nanoparticle (Pip-PTX NPS), were made by the nanoprecipitation method and later characterized by PSA, DSC, SEM, TEM, and FTIR. All nanoparticles exhibited a monodispersed size distribution with a size of below 200 nm, zeta potential ranges from (-30-40mV) and a narrow polydispersity index (>0.3) of the drugs. The average encapsulation efficiency was found to be between 80 and 90%. In vitro release of drugs for nanoparticles was done spectrophotometrically. FTIR and DSC results confirmed the presence of the drug. The Pip-PTX NPS significantly inhibit cell proliferation as compared to the native drugs nanoparticles in the breast cancer cell line MCF-7. In addition, Pip-PTX NPS suppresses cells in colony formation and soft gel agar assay. Scratch migration and Transwell chamber invasion assays revealed that combined nanoparticles reduce the migration and invasion of breast cancer cells. Morphological studies showed that Pip-PTX NPS penetrates the cells and induces apoptosis, which was further confirmed by DNA fragmentation, SEM, and western blot analysis. Taken together, Pip-PTX NPS inhibits cell proliferation, anchorage dependent and anchorage independent cell growth, reduces migration and invasion, and induces apoptosis in cells. These findings support that combination therapy using Pip-PTX NPS represents a potential approach and could be helpful in the future for breast cancer therapy.

Keywords: piperine, paclitaxel, breast cancer, apoptosis

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4565 Estimating Anthropometric Dimensions for Saudi Males Using Artificial Neural Networks

Authors: Waleed Basuliman

Abstract:

Anthropometric dimensions are considered one of the important factors when designing human-machine systems. In this study, the estimation of anthropometric dimensions has been improved by using Artificial Neural Network (ANN) model that is able to predict the anthropometric measurements of Saudi males in Riyadh City. A total of 1427 Saudi males aged 6 to 60 years participated in measuring 20 anthropometric dimensions. These anthropometric measurements are considered important for designing the work and life applications in Saudi Arabia. The data were collected during eight months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining 15 dimensions were set to be the measured variables (Model’s outcomes). The hidden layers varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was able to estimate the body dimensions of Saudi male population in Riyadh City. The network's mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found to be 0.0348 and 3.225, respectively. These results were found less, and then better, than the errors found in the literature. Finally, the accuracy of the developed neural network was evaluated by comparing the predicted outcomes with regression model. The ANN model showed higher coefficient of determination (R2) between the predicted and actual dimensions than the regression model.

Keywords: artificial neural network, anthropometric measurements, back-propagation

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4564 Experimental Assessment of Artificial Flavors Production

Authors: M. Unis, S. Turky, A. Elalem, A. Meshrghi

Abstract:

The Esterification kinetics of acetic acid with isopropnol in the presence of sulfuric acid as a homogenous catalyst was studied with isothermal batch experiments at 60,70 and 80°C and at a different molar ratio of isopropnol to acetic acid. Investigation of kinetics of the reaction indicated that the low of molar ratio is favored for esterification reaction, this is due to the reaction is catalyzed by acid. The maximum conversion, approximately 60.6% was obtained at 80°C for molar ratio of 1:3 acid : alcohol. It was found that increasing temperature of the reaction, increases the rate constant and conversion at a certain mole ratio, that is due to the esterification is exothermic. The homogenous reaction has been described with simple power-law model. The chemical equilibrium combustion calculated from the kinetic model in agreement with the measured chemical equilibrium.

Keywords: artificial flavors, esterification, chemical equilibria, isothermal

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4563 Classifying Turbomachinery Blade Mode Shapes Using Artificial Neural Networks

Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

Abstract:

Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition

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4562 AI Ethical Values as Dependent on the Role and Perspective of the Ethical AI Code Founder- A Mapping Review

Authors: Moshe Davidian, Shlomo Mark, Yotam Lurie

Abstract:

With the rapid development of technology and the concomitant growth in the capability of Artificial Intelligence (AI) systems and their power, the ethical challenges involved in these systems are also evolving and increasing. In recent years, various organizations, including governments, international institutions, professional societies, civic organizations, and commercial companies, have been choosing to address these various challenges by publishing ethical codes for AI systems. However, despite the apparent agreement that AI should be “ethical,” there is debate about the definition of “ethical artificial intelligence.” This study investigates the various AI ethical codes and their key ethical values. From the vast collection of codes that exist, it analyzes and compares 25 ethical codes that were found to be representative of different types of organizations. In addition, as part of its literature review, the study overviews data collected in three recent reviews of AI codes. The results of the analyses demonstrate a convergence around seven key ethical values. However, the key finding is that the different AI ethical codes eventually reflect the type of organization that designed the code; i.e., the organizations’ role as regulator, user, or developer affects the view of what ethical AI is. The results show a relationship between the organization’s role and the dominant values in its code. The main contribution of this study is the development of a list of the key values for all AI systems and specific values that need to impact the development and design of AI systems, but also allowing for differences according to the organization for which the system is being developed. This will allow an analysis of AI values in relation to stakeholders.

Keywords: artificial intelligence, ethical codes, principles, values

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4561 Management of Renal Malignancies with IVC Thrombus: Our Experience

Authors: Sujeet Poudyal

Abstract:

Introduction: Renal cell carcinoma is the most common malignancy associated with Inferior vena cava (IVC) thrombosis. Radical nephrectomy with tumor thrombectomy provides durable cancer-free survival. Other renal malignancies like Wilms’ tumors are also associated with IVC thrombus. We describe our experience with the management of renal malignancies associated with IVC thrombus. Methods: This prospective study included 28 patients undergoing surgery for renal malignancies associated with IVC thrombus from February 2017 to March 2023. Demographics of patients, types of renal malignancy, level of IVC thrombus, intraoperative details, need for venovenous bypass, cardiopulmonary bypass and postoperative outcomes were all documented. Results: Out of a total of 28 patients, 24 patients had clear cell Renal Cell Carcinoma,1 had renal osteosarcoma and 3 patients had Wilms tumor. The levels. of thrombus were II in eight, III in seven, and IV in six patients. The mean age of RCC was 62.81±10.2 years, renal osteosarcoma was 26 years and Wilms tumor was 23 years. There was a need for venovenous bypass in four patients and cardiopulmonary bypass in four patients, and the Postoperative period was uneventful in most cases except for two mortalities, one in Level III due to pneumonia and one in Level IV due to sepsis. All cases followed up till now have no local recurrence and metastasis except one case of RCC with Level IV IVC thrombus, which presented with paraaortic nodal recurrence and is currently managed with sunitinib. Conclusion: The complexity in the management of renal malignancy with IVC thrombus increases with the level of IVC thrombus. As radical nephrectomy with tumor thrombectomy provides durable cancer-free survival in most cases, the surgery should be undertaken in an expert and experienced setup with a strong cardiovascular backup to minimize morbidity and mortality associated with the procedure.

Keywords: renal malignancy, IVC thrombus, radical nephrectomy with tumor thrombectomy, renal cell carcinoma

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4560 Non-Steroidal Microtubule Disrupting Analogues Induce Programmed Cell Death in Breast and Lung Cancer Cell Lines

Authors: Marcel Verwey, Anna M. Joubert, Elsie M. Nolte, Wolfgang Dohle, Barry V. L. Potter, Anne E. Theron

Abstract:

A tetrahydroisoquinolinone (THIQ) core can be used to mimic the A,B-ring of colchicine site-binding microtubule disruptors such as 2-methoxyestradiol in the design of anti-cancer agents. Steroidomimeric microtubule disruptors were synthesized by introducing C'2 and C'3 of the steroidal A-ring to C'6 and C'7 of the THIQ core and by introducing a decorated hydrogen bond acceptor motif projecting from the steroidal D-ring to N'2. For this in vitro study, four non-steroidal THIQ-based analogues were investigated and comparative studies were done between the non-sulphamoylated compound STX 3450 and the sulphamoylated compounds STX 2895, STX 3329 and STX 3451. The objective of this study was to investigate the modes of cell death induced by these four THIQ-based analogues in A549 lung carcinoma epithelial cells and metastatic breast adenocarcinoma MDA-MB-231 cells. Cytotoxicity studies to determine the half maximal growth inhibitory concentrations were done using spectrophotometric quantification via crystal violet staining and lactate dehydrogenase (LDH) assays. Microtubule integrity and morphologic changes of exposed cells were investigated using polarization-optical transmitted light differential interference contrast microscopy, transmission electron microscopy and confocal microscopy. Flow cytometric quantification was used to determine apoptosis induction and the effect that THIQ-based analogues have on cell cycle progression. Signal transduction pathways were elucidated by quantification of the mitochondrial membrane integrity, cytochrome c release and caspase 3, -6 and -8 activation. Induction of autophagic cell death by the THIQ-based analogues was investigated by morphological assessment of fluorescent monodansylcadaverine (MDC) staining of acidic vacuoles and by quantifying aggresome formation via flow cytometry. Results revealed that these non-steroidal microtubule disrupting analogues inhibited 50% of cell growth at nanomolar concentrations. Immunofluorescence microscopy indicated microtubule depolarization and the resultant mitotic arrest was further confirmed through cell cycle analysis. Apoptosis induction via the intrinsic pathway was observed due to depolarization of the mitochondrial membrane, induction of cytochrome c release as well as, caspase 3 activation. Potential involvement of programmed cell death type II was observed due to the presence of acidic vacuoles and aggresome formation. Necrotic cell death did not contribute significantly, indicated by stable LDH levels. This in vitro study revealed the induction of the intrinsic apoptotic pathway as well as possible involvement of autophagy after exposure to these THIQ-based analogues in both MDA-MB-231- and A549 cells. Further investigation of this series of anticancer drugs still needs to be conducted to elucidate the temporal, mechanistic and functional crosstalk mechanisms between the two observed programmed cell deaths pathways.

Keywords: apoptosis, autophagy, cancer, microtubule disruptor

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4559 Exploring Public Opinions Toward the Use of Generative Artificial Intelligence Chatbot in Higher Education: An Insight from Topic Modelling and Sentiment Analysis

Authors: Samer Muthana Sarsam, Abdul Samad Shibghatullah, Chit Su Mon, Abd Aziz Alias, Hosam Al-Samarraie

Abstract:

Generative Artificial Intelligence chatbots (GAI chatbots) have emerged as promising tools in various domains, including higher education. However, their specific role within the educational context and the level of legal support for their implementation remain unclear. Therefore, this study aims to investigate the role of Bard, a newly developed GAI chatbot, in higher education. To achieve this objective, English tweets were collected from Twitter's free streaming Application Programming Interface (API). The Latent Dirichlet Allocation (LDA) algorithm was applied to extract latent topics from the collected tweets. User sentiments, including disgust, surprise, sadness, anger, fear, joy, anticipation, and trust, as well as positive and negative sentiments, were extracted using the NRC Affect Intensity Lexicon and SentiStrength tools. This study explored the benefits, challenges, and future implications of integrating GAI chatbots in higher education. The findings shed light on the potential power of such tools, exemplified by Bard, in enhancing the learning process and providing support to students throughout their educational journey.

Keywords: generative artificial intelligence chatbots, bard, higher education, topic modelling, sentiment analysis

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