Search results for: artificial cell

Authors: Gehan Labib Abuelenain, Azza Fahmi, Salma Awad Mahmoud

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Toxoplasmosis is a global parasitic disease caused by the protozoan Toxoplasma gondii (T. gondii), with a high infection rate that affects one third of the human population and results in severe implications in pregnant women, neonates, and immunocompromised patients. Anti-parasitic treatments and schemes available against toxoplasmosis have barely evolved over the last two decades. The available T. gondii therapeutics cannot completely eradicate tissue cysts produced by the parasite and are not well-tolerated by immunocompromised patients. This work aims to highlight new trends in Toxoplasma gondii diagnosis by providing a comprehensive overview of the field, summarizing recent findings, and discussing the new technological advancements in toxoplasma diagnosis and treatment. Advancements in therapeutics utilizing trends in molecular biophysics, such as biosensors, epigenetics, and artificial intelligence (AI), might provide solutions for disease management and prevention. These insights will provide tools to identify research gaps and proffer planning options for disease control.

Keywords: toxoplamosis, diagnosis, therapeutics, biosensors, AI

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Authors: Noor Akhmazillah Fauzi, Mohammed Mehdi Farid, Filipa V. Silva

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The aim of this paper is to investigate if different concentration of Manuka honey (as a model food) has a major influence on the inactivation of Saccharomyces cerevisiae (as the testing microorganism) after subjecting it to HPP. Honey samples with different sugar concentrations (20, 30, 40, 50, 60 and 70 °Brix) were prepared aseptically using sterilized distilled water. No dilution of honey was made for the 80 °Brix sample. For the 0 °Brix sample (control), sterilized distilled water was used. Thermal treatment at 55 °C for 10 min (conventionally applied in honey pasteurisation in industry) was carried out for comparison purpose. S. cerevisiae cell numbers in honey samples were established before and after each HPP and thermal treatment. The number of surviving cells was determined after a proper dilution of the untreated and treated samples by the viable plate count method. S. cerevisiae cells, in different honey concentrations (0 to 80 °Brix), subjected to 600 MPa (at ambient temperature) showed an increasing resistance to inactivation with °Brix. A significant correlation (p < 0.05) between cell reduction and °Brix was found. Cell reduction in high pressure-treated samples varied linearly with °Brix (R2 > 0.9), confirming that the baroprotective effect of the food is due to sugar content. This study has practical implications in establishing efficient process design for commercial manufacturing of high sugar food products and on the potential use of HPP for such products.

Keywords: high pressure processing, honey, Saccharomyces cerevisiae, °Brix

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Authors: Marisa Rio, Sharanya Bola, Richard H. W. Funk, Gerald Gerlach

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Cell migration, wound healing and regeneration are some of the physiological phenomena in which electric fields (EFs) have proven to have an important function. Physiologically, cells experience electrical signals in the form of transmembrane potentials, ion fluxes through protein channels as well as electric fields at their surface. As soon as a wound is created, the disruption of the epithelial layers generates an electric field of ca. 40-200 mV/mm, directing cell migration towards the wound site, starting the healing process. In vitro electrotaxis, experiments have shown cells respond to DC EFs polarizing and migrating towards one of the poles (cathode or anode). A standard electrotaxis experiment consists of an electrotaxis chamber where cells are cultured, a DC power source and agar salt bridges that help delaying toxic products from the electrodes to attain the cell surface. The electric field strengths used in such an experiment are uniform and homogeneous. In contrast, the endogenous electric field strength around a wound tend to be multi-field and non-homogeneous. In this study, we present a custom device that enables electrotaxis experiments in non-homogeneous DC electric fields. Its main feature involves the replacement of conventional metallic electrodes, separated from the electrotaxis channel by agarose gel bridges, through electrolyte-filled microchannels. The connection to the DC source is made by Ag/AgCl electrodes, incased in agarose gel and placed at the end of each microfluidic channel. An SU-8 membrane closes the fluidic channels and simultaneously serves as the single connection from each of them to the central electrotaxis chamber. The electric field distribution and current density were numerically simulated with the steady-state electric conduction module from ANSYS 16.0. Simulation data confirms the application of nonhomogeneous EF of physiological strength. To validate the biocompatibility of the device cellular viability of the photoreceptor-derived 661W cell line was accessed. The cells have not shown any signs of apoptosis, damage or detachment during stimulation. Furthermore, immunofluorescence staining, namely by vinculin and actin labelling, allowed the assessment of adhesion efficiency and orientation of the cytoskeleton, respectively. Cellular motility in the presence and absence of applied DC EFs was verified. The movement of individual cells was tracked for the duration of the experiments, confirming the EF-induced, cathodal-directed motility of the studied cell line. The in vitro monolayer wound assay, or “scratch assay” is a standard protocol to quantitatively access cell migration in vitro. It encompasses the growth of a confluent cell monolayer followed by the mechanic creation of a scratch, representing a wound. Hence, wound dynamics was monitored over time and compared for control and applied the electric field to quantify cellular population motility.

Keywords: DC non-homogeneous electric fields, electrotaxis, microfluidic biochip, wound healing

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Authors: Tugba Bayoglu

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Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

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Authors: H. Solomon, A. Abdul-Latif, R. Baleh, I. Deiab, K. Khanafer

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Aluminum foams were developed and tested due to their high energy absorption abilities for multifunctional applications. The aim of this research work was to investigate experimentally the effect of quasi-static biaxial loading complexity (combined compression-torsion) on the energy absorption capacity of highly uniform architecture open-cell aluminum foam manufactured by kelvin cell model. The two generated aluminum foams have 80% and 85% porosities, spherical-shaped pores having 11mm in diameter. These foams were tested by means of several square-section specimens. A patented rig called ACTP (Absorption par Compression-Torsion Plastique), was used to investigate the foam response under quasi-static complex loading paths having different torsional components (i.e., 0°, 37° and 53°). The main mechanical responses of the aluminum foams were studied under simple, intermediate and severe loading conditions. In fact, the key responses to be examined were stress plateau and energy absorption capacity of the two foams with respect to loading complexity. It was concluded that the higher the loading complexity and the higher the relative density, the greater the energy absorption capacity of the foam. The highest energy absorption was thus recorded under the most complicated loading path (i.e., biaxial-53°) for the denser foam (i.e., 80% porosity).

Keywords: open-cell aluminum foams, biaxial loading complexity, foams porosity, energy absorption capacity, characterization

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Authors: Madiha El Awamie, Catherine Rees

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Natural preservatives have been used as alternatives to traditional chemical preservatives; however, a limited number have been commercially developed and many remain to be investigated as sources of safer and effective antimicrobials. In this study, we have been investigating the antimicrobial activity of an extract of Glycyrrhiza glabra (liquorice) that was provided as a waste material from the production of liquorice flavourings for the food industry, and to investigate if this retained the expected antimicrobial activity so it could be used as a natural preservative. Antibacterial activity of liquorice extract was screened for evidence of growth inhibition against eight species of Gram-negative and Gram-positive bacteria, including Listeria monocytogenes, Listeria innocua, Staphylococcus aureus, Enterococcus faecalis and Bacillus subtilis. The Gram-negative bacteria tested include Pseudomonas aeruginosa, Escherichia coli and Salmonella typhimurium but none of these were affected by the extract. In contrast, for all of the Gram-positive bacteria tested, growth was inhibited as monitored using optical density. However parallel studies using viable count indicated that the cells were not killed meaning that the extract was bacteriostatic rather than bacteriocidal. The Minimum Inhibitory Concentration [MIC] and Minimum Bactericidal Concentration [MBC] of the extract was also determined and a concentration of 50 µg ml^-1 was found to have a strong bacteriostatic effect on Gram-positive bacteria. Microscopic analysis indicated that there were changes in cell shape suggesting the cell wall was affected. In addition, the use of a reporter strain of Listeria transformed with the bioluminescence genes luxABCDE indicated that cell energy levels were reduced when treated with either 12.5 or 50 µg ml^-1 of the extract, with the reduction in light output being proportional to the concentration of the extract used. Together these results suggest that the extract is inhibiting the growth of Gram-positive bacteria only by damaging the cell wall and/or membrane.

Keywords: antibacterial activity, bioluminescence, Glycyrrhiza glabra, natural preservative

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Authors: Aghasadeghi MR., Bahramali G., Sadat SM., Sadeghi SA., Yousefi M., Khodaei K., Ghorbani M., Sadat Larijani M.

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Background:The emerging COVID-19 pandemic is a serious concernfor the public health worldwide. Despite the many mutations in the virus genome, it is important to find an effective vaccine against viral mutations. Therefore, in current study, we aimed at immunoinformatic evaluation of the virus proteins immunogenicity to design a preventive vaccine candidate, which could elicit humoral and cellular immune responses as well. Methods:Three antigenic regions are included;Spike, Membrane, and Nucleocapsid amino acid sequences were obtained, and possible fusion proteins were assessed andcompared by immunogenicity, structural features, and population coverage. The best fusion protein was also evaluated for MHC-I and MHC-II T-cell epitopes and the linear and conformational B-cell epitopes. Results: Among the four predicted models, the truncated Spike protein in fusion with M and N proteins is composed of 24 highly immunogenic human MHC class I and 29 MHC class II, along with 14 B-cell linear and 61 discontinues epitopes. Also, the selected protein has high antigenicity and acceptable population coverage of 82.95% in Iran and 92.51% in Europe. Conclusion: The data indicate that the truncated Spike-M-N SARS-CoV-2form which could be potential targets of neutralizing antibodies. The protein also has the ability to stimulate humoral and cellular immunity. The in silico study provided the fusion protein as a potential preventive vaccine candidate for further in vivo evaluation.

Keywords: SARS-CoV-2, immunoinformatic, protein, vaccine

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Authors: Vahid Nourani, Atefeh Ashrafi

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Prediction of treated wastewater quality is a matter of growing importance in water treatment procedure. In this way artificial neural network (ANN), as a robust data-driven approach, has been widely used for forecasting the effluent quality of wastewater treatment. However, developing ANN model based on appropriate input variables is a major concern due to the numerous parameters which are collected from treatment process and the number of them are increasing in the light of electronic sensors development. Various studies have been conducted, using different clustering methods, in order to classify most related and effective input variables. This issue has been overlooked in the selecting dominant input variables among wastewater treatment parameters which could effectively lead to more accurate prediction of water quality. In the presented study two ANN models were developed with the aim of forecasting effluent quality of Tabriz city’s wastewater treatment plant. Biochemical oxygen demand (BOD) was utilized to determine water quality as a target parameter. Model A used Principal Component Analysis (PCA) for input selection as a linear variance-based clustering method. Model B used those variables identified by the mutual information (MI) measure. Therefore, the optimal ANN structure when the result of model B compared with model A showed up to 15% percent increment in Determination Coefficient (DC). Thus, this study highlights the advantage of PCA method in selecting dominant input variables for ANN modeling of wastewater plant efficiency performance.

Keywords: Artificial Neural Networks, biochemical oxygen demand, principal component analysis, mutual information, Tabriz wastewater treatment plant, wastewater treatment plant

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Authors: Erol Kam, Z. U. Yümün

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Natural and artificial radionuclides cause radioactive contamination in environments, just as the other non-biodegradable pollutants (heavy metals, etc.) sink to the sea floor and accumulate in sediments. Especially the habitat of benthic foraminifera living on the surface of sediments or in sediments at the seafloor are affected by radioactive pollution in the marine environment. Thus, it is important for pollution analysis to determine the radionuclides. Radioactive pollution accumulates in the lowest level of the food chain and reaches humans at the highest level. The more the accumulation, the more the environment is endangered. This study used gamma spectrometry to investigate the natural and artificial radionuclide distribution of sediment samples taken from living benthic foraminifera habitats in the Western Marmara Sea. The radionuclides, K-40, Cs-137, Ra-226, Mn 54, Zr-95+ and Th-232, were identified in the sediment samples. For this purpose, 18 core samples were taken from depths of about 25-30 meters in the Marmara Sea in 2016. The locations of the core samples were specifically selected exclusively from discharge points for domestic and industrial areas, port locations, and so forth to represent pollution in the study area. Gamma spectrometric analysis was used to determine the radioactive properties of sediments. The radionuclide concentration activity values in the sediment samples obtained were Cs-137=0.9-9.4 Bq/kg, Th-232=18.9-86 Bq/kg, Ra-226=10-50 Bq/kg, K-40=24.4–670 Bq/kg, Mn 54=0.71–0.9 Bq/kg and Zr-95+=0.18–0.19 Bq/kg. These values were compared with the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) data, and an environmental analysis was carried out. The Ra-226 series, the Th-232 series, and the K-40 radionuclides accumulate naturally and are increasing every day due to anthropogenic pollution. Although the Ra-226 values obtained in the study areas remained within normal limits according to the UNSCEAR values, the K-40, and Th-232 series values were found to be high in almost all the locations.

Keywords: Ra-226, Th-232, K-40, Cs-137, Mn 54, Zr-95+, radionuclides, Western Marmara Sea

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Authors: Nataša Kalajdžija, Strahinja Kovačević, Davor Lončar, Sanja Podunavac Kuzmanović, Lidija Jevrić

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In order to investigate the relationship between retention and structure, a quantitative Structure Retention Relationships (QSRRs) study was applied for the prediction of retention times of a set of 23 secoestrane derivatives in a reversed-phase thin-layer chromatography. After the calculation of molecular descriptors, a suitable set of molecular descriptors was selected by using step-wise multiple linear regressions. Artificial Neural Network (ANN) method was employed to model the nonlinear structure-activity relationships. The ANN technique resulted in 5-6-1 ANN model with the correlation coefficient of 0.98. We found that the following descriptors: Critical pressure, total energy, protease inhibition, distribution coefficient (LogD) and parameter of lipophilicity (miLogP) have a significant effect on the retention times. The prediction results are in very good agreement with the experimental ones. This approach provided a new and effective method for predicting the chromatographic retention index for the secoestrane derivatives investigated.

Keywords: lipophilicity, QSRR, RP TLC retention, secoestranes

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Authors: Pei-Hsiu Chiang, Ling Hong Huang, Hsin-I Chang

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In this research, we used UVA irradiation, which can penetrate into dermis and fibroblasts, the most abundant cells in dermis, to investigate the effect of UV light on dermis, such as inflammation, ECM degradation and elasticity loss. Moreover, this research is focused on the influence of hyaluronic acid (HA) on UVA treated dermal fibroblasts. We aim to establish whether HA can effectively relief ECM degradation, and restore the elasticity of UVA-damaged fibroblasts. Prolonged exposure to UVA radiation can damage fibroblasts and led variation in cell morphology and reduction in cell viability. Besides, UVA radiation can induce IL-1β expression on fibroblasts and then promote MMP-1 and MMP-3 expression, which can accelerate ECM degradation. On the other hand, prolonged exposure to UVA radiation reduced collagen and elastin synthesis on fibroblasts. Due to the acceleration of ECM degradation and the reduction of ECM synthesis, Atomic force microscope (AFM) was used to analyze the elasticity reduction on UVA-damaged fibroblasts. UVA irradiation causes photoaging on fibroblasts. UVA damaged fibroblasts with HA treatment can down-regulate the gene expression of MMP-1, MMP-3, and then slow down ECM degradation. On the other hand, HA may restore elastin and collagen synthesis in UV-damaged fibroblasts. Based on the slowdown of ECM degradation, UVA-damaged fibroblast elasticity can be effectively restored by HA treatment. In summary, HA can relief the photoaging conditions on fibroblasts, but may not be able to return fibroblasts to normal, healthy state. Although HA cannot fully recover UVA-damaged fibroblasts, HA is still potential for repairing photoaging skin.

Keywords: atomic force microscope, hyaluronic acid, UVA radiation, dermal fibroblasts

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Authors: Palingba Aimé Marie Doilkom, Mahamadou Koïta, Jean-michel Vouillamoz, Angelbert Biaou

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Most African populations rely on groundwater in rural areas for their consumption. Indeed, in the face of climate change and strong demographic growth, groundwater, particularly in the basement, is increasingly in demand. The question of the sustainability of water resources in this type of environment is therefore becoming a major issue. Groundwater recharge can be natural or artificial. Unlike natural recharge, which often results from the natural infiltration of surface water (e.g. a share of rainfall), artificial recharge consists of causing water infiltration through appropriate developments to artificially replenish the water stock of an aquifer. Artificial recharge is, therefore, one of the measures that can be implemented to secure water supply, combat the effects of climate change, and, more generally, contribute to improving the quantitative status of groundwater bodies. It is in this context that the present research is conducted with the aim of developing artificial recharge in order to contribute to the sustainability of basement aquifers in a context of climatic variability and constantly increasing water needs of populations. In order to achieve the expected results, it is therefore important to determine the characteristics of the infiltration basins and to identify the areas suitable for their implementation. The geometry of the aquifer was reproduced, and the hydraulic properties of the aquifer were collected and characterized, including boundary conditions, hydraulic conductivity, effective porosity, recharge, Van Genuchten parameters, and saturation indices. The aquifer of the Sanon experimental site is made up of three layers, namely the saprolite, the fissured horizon, and the healthy basement. Indeed, the saprolite and the fissured medium were considered for the simulations. The first results with FEFLOW model show that the water table reacts continuously for the first 100 days before stabilizing. The hydraulic charge increases by an average of 1 m. The further away from the basin, the less the water table reacts. However, if a variable hydraulic head is imposed on the basins, it can be seen that the response of the water table is not uniform over time. The lower the basin hydraulic head, the less it affects the water table. These simulations must be continued by improving the characteristics of the basins in order to obtain the appropriate characteristics for a good recharge.

Keywords: basement area, FEFLOW, infiltration basin, MAR

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Authors: Messaoud Eljamai, Sami Hidouri

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Massive multiple-input multiple-output (MIMO) is an emerging technology for new cellular networks such as 5G systems. Its principle is to use many antennas per cell in order to maximize the network's spectral efficiency. Inter-cellular interference remains a fundamental problem. The use of massive MIMO will not derogate from the rule. It improves performances only when the number of antennas is significantly greater than the number of users. This, considerably, limits the networks spectral efficiency. In this paper, a coordinated detector for an uplink massive MIMO system is proposed in order to mitigate the inter-cellular interference. The proposed scheme combines the coordinated multipoint technique with an interference-cancelling algorithm. It requires the serving cell to send their received symbols, after processing, decision and error detection, to the interfered cells via a backhaul link. Each interfered cell is capable of eliminating intercellular interferences by generating and subtracting the user’s contribution from the received signal. The resulting signal is more reliable than the original received signal. This allows the uplink massive MIMO system to improve their performances dramatically. Simulation results show that the proposed detector improves system spectral efficiency compared to classical linear detectors.

Keywords: massive MIMO, COMP, interference canceling algorithm, spectral efficiency

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Authors: Aliyu Maje Bello, Yaowaluck Maprang Roshorm

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Hand, foot, and mouth disease (HFMD) is a highly contagious viral infection affecting mostly infants and children. Although the Enterovirus A71 (EV71) is usually the major causative agent of HFMD, other enteroviruses such as coxsackievirus A16, A10, and A6 are also found in some of the recent outbreaks. The commercially available vaccines have demonstrated their effectiveness against only EV71 infection but no protection against other enteroviruses. To address the limitation of the monovalent EV71 vaccine, the present study thus designed a tetravalent vaccine against the four major enteroviruses causing HFMD and primarily evaluated the designed vaccine using an immunoinformatics approach. The immunogen was designed to contain the EV71 VP1 protein and multiple reported epitopes from all four distinct enteroviruses and thus designated a tetravalent vaccine. The 3D structure of the designed tetravalent vaccine was modeled, refined, and validated. Epitope screening showed the presence of B-cell, CTL, CD4 T cell, and IFN epitopes with vast application among the Asian population. Docking analysis confirmed the stable and strong binding interactions between the immunogen and immune receptor B-cell receptor (BCR). In silico cloning and immune simulation analyses guaranteed high efficiency and sufficient expression of the vaccine candidate in humans. Overall, the promising results obtained from the in-silico studies of the proposed tetravalent vaccine make it a potential candidate worth further experimental validation.

Keywords: enteroviruses, coxsackieviruses, hand foot and mouth disease, immunoinformatics, tetravalent vaccine

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Authors: Thomas Schalow

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It is commonly recognized that our present curriculum is not preparing students to function in the 21st century. This is particularly true in regard to communication needs across cultures - both human and non-human. In this paper, a comprehensive theory of communication-based on communication with non-human cultures and intelligences is presented to meet the following three imminent contingencies: communicating with sentient biological intelligences, communicating with extraterrestrial intelligences, and communicating with artificial super-intelligences. The paper begins with the argument that we need to become much more serious about communicating with the non-human, intelligent life forms that already exists around us here on Earth. We need to broaden our definition of communication and reach out to other sentient life forms in order to provide humanity with a better perspective of its place within our ecosystem. The paper next examines the science and philosophy behind CETI (communication with extraterrestrial intelligences) and how it could prove useful even in the absence of contact with alien life. However, CETI’s assumptions and methodology need to be revised in accordance with the communication theory being proposed in this paper if we are truly serious about finding and communicating with life beyond Earth. The final theme explored in this paper is communication with non-biological super-intelligences. Humanity has never been truly compelled to converse with other species, and our failure to seriously consider such intercourse has left us largely unprepared to deal with communication in a future that will be mediated and controlled by computer algorithms. Fortunately, our experience dealing with other cultures can provide us with a framework for this communication. The basic concepts behind intercultural communication can be applied to the three types of communication envisioned in this paper if we are willing to recognize that we are in fact dealing with other cultures when we interact with other species, alien life, and artificial super-intelligence. The ideas considered in this paper will require a new mindset for humanity, but a new disposition will yield substantial gains. A curriculum that is truly ready for the 21st century needs to be aligned with this new theory of communication.

Keywords: artificial intelligence, CETI, communication, language

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Authors: Huyen T. Pham, Nhue P. Nguyen, Tien Q. Phi, Phuong T. Dang, Hy G. Le

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Since the marine environmental conditions are extremely different from the other ones, so that marine actinomycetes might produce novel bioactive compounds. Therefore, actinomycete strains were screened from marine water and sediment samples collected from the coastal areas of Northern Vietnam. Ninety-nine actinomycete strains were obtained on starch-casein agar media by dilution technique, only seven strains, named HP112, HP12, HP411, HPN11, HP 11, HPT13 and HPX12, showed significant antibacterial activity against both gram-positive and gram-negative bacteria (Bacillus subtilis ATCC 6633, Staphylococcus epidemidis ATCC 12228, Escherichia coli ATCC 11105). Further studies were carried out with the most active HP411strain against Candida albicans ATCC 10231. This strain could grow rapidly on starch casein agar and other media with high salt containing 7-10% NaCl at 28-30oC. Spore-chain of HP411 showed an elongated and circular shape with 10 to 30 spores/chain. Identification of the strain was carried out by employing the taxonomical studies including the 16S rRNA sequence. Based on phylogenetic and phenotypic evidence it is proposed that HP411 to be belongs to species Streptomyces variabilis. The potent of the crude extract of fermentation broth of HP411that are effective against wide range of pathogens: both gram-positive, gram-negative and fungi. Further studies revealed that the crude extract HP411 could obtain the anticancer activity for cancer cell lines: Hep-G2 (liver cancer cell line); RD (cardiac and skeletal muscle letters cell line); FL (membrane of the uterus cancer cell line). However, the actinomycetes from marine ecosystem will be useful for the discovery of new drugs in the furture.

Keywords: marine actinomycetes, antibacterial, anticancer, Streptomyces variabilis

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Authors: Norimichi Nagano, Yoshio Hirano, Tsutomu Yasukawa

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Mesenchymal stem cells are thought to confer neuroprotection, facilitate tissue regeneration and exert their effects on retinal degenerative diseases, however, adverse events such as proliferative vitreoretinopathy and preretinal membrane disease associated with cell suspension transplantation have also been reported. We have recently developed human (allogeneic) adipose tissue-derived mesenchymal stem cell (adMSC) sheets through our proprietary sheet transformation technique, which could potentially mitigate these adverse events. To clarify the properties of our adMSC sheets named PAL-222, we performed in vitro studies such as viability testing, cytokine secretions by ELISA, immunohistochemical study, and migration assay. The viability of the cells exceeded 70%. Vascular Endothelial Growth Factor (VEGF) and Pigment Epithelium-Derived Factor (PEDF), which are quite important cytokines for the retinal area, were observed. PAL-222 expressed type I collagen, a strength marker, type IV collagen, a marker of the basement membrane, and elastin, an elasticity marker. Finally, the migration assay was performed and showed negative, which means that PAL-222 is stably kept in the topical area and does not come to pieces. Next, to evaluate the efficacy in vivo, we transplanted PAL-222 into the subretinal space of the eye of Royal College of Surgeons rats with congenital retinal degeneration and assessed it for three weeks after transplantation. We confirmed that PAL-222 suppressed the decrease in the thickness of the outer nuclear layer, which means that the photoreceptor protective effect treated with PAL-222 was significantly higher than that in the sham group. (p < 0.01). This finding demonstrates that PAL-222 showed their retinoprotective effect in a model of congenital retinal degeneration. As the study suggested the efficacy of PAL-222 in both in vitro and in vivo studies, we are presently engaged in clinical trials of PAL-222 for myopic chorioretinal atrophy, which is one of the retinal degenerative diseases, for the purpose of regenerative medicine.

Keywords: cell sheet, clinical trial, mesenchymal stem cell, myopic chorioretinal atrophy

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Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

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Authors: Edward W. Staley, Corban G. Rivera, Ashley J. Llorens

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Advances in reinforcement learning (RL) have resulted in recent breakthroughs in the application of artificial intelligence (AI) across many different domains. An emerging landscape of development environments is making powerful RL techniques more accessible for a growing community of researchers. However, most existing frameworks do not directly address the problem of learning in complex operating environments, such as dense urban settings or defense-related scenarios, that incorporate distributed, heterogeneous teams of agents. To help enable AI research for this important class of applications, we introduce the AI Arena: a scalable framework with flexible abstractions for distributed multi-agent reinforcement learning. The AI Arena extends the OpenAI Gym interface to allow greater flexibility in learning control policies across multiple agents with heterogeneous learning strategies and localized views of the environment. To illustrate the utility of our framework, we present experimental results that demonstrate performance gains due to a distributed multi-agent learning approach over commonly-used RL techniques in several different learning environments.

Keywords: reinforcement learning, multi-agent, deep learning, artificial intelligence

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Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

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This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: neural network, self-organizing map, rule extraction, rule insertion

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Authors: V. A. Adzika, D. Ayim-Aboagye, T. Gordh

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Background and aims: Prevalence of Sickle Cell Disease (SCD) is high in Ghana but not much is known in terms of research into non-medical strategies for managing and coping with the pain associated with SCD. This study was carried out to examine effective non-medical related strategies patients use to cope and manage their SCD condition. Methods: SCD patients (387) consisting of 180 males and 204 females between 18-65 years old years participated in the study. A cross-sectional research design was used in which participants completed questionnaires on pain, non-medical coping and management strategies, anxiety, and depression. Results of multiple regression analysis showed that socio-demographic characteristics contributed to the variance in the pain associated with SCD. Results: Over 90% of participants reported that pains associated with SCD were the main reason for seeking treatment in SCD crisis. In terms of non-medical related coping strategies, attending a place of worship and praying were the main coping strategies used in SCD crises, suggesting that patients’ beliefs, particularly in a supernatural being, served as a mitigating factor in the process of coping with the pain associated with SCD crisis. Also, avoidance and withdrawal from people and social activities were reported to be strategies used to cope effectively with the pain associated with SCD crisis. Conclusion: This indicates that it is imperative to incorporate non-medical related coping and management strategies, especially religious beliefs and psychosocial factors, to coping and management of the pain associated with SCD.

Keywords: anxiety, depression, sickle cell disease, quality of life, socio-demographic characteristics, Ghana

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Authors: Khairi El Battawy, Monika Skalicki

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The present investigation has been done on pure Egyptian Arabian mares that reared in private horse studs. Fifty non-pregnant mares were selected and examined to classify them as either being reproductively healthy or subfertile mares including clinical endometritis, early embryonic death, granulosa cell tumor, repeat breeder (post-breeding endometritis), and anoestrus mares. The purpose of the study was to assess oxidative/antioxidant biochemical metabolites, lipogram, trace elements and reproductive hormones throughout reproductive conditions in mares during regular estrous, anestrum, early pregnancy, granulose cell tumor, ovulation failure, and endometritis. Results showed intensification of the free radical-dependent process in the blood of infertile mare, especially mares with endometritis. Ultrasonography as a diagnostic tool diagnosis of endometritis in mares was an important step as it revealed much information concerning infertility problem.

Keywords: endometritis, ovulation, oxidative, mare

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Authors: Vijay Pal Singh, Yogesh Chandra Kotiyal

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Structures are a combination of various load carrying members which transfer the loads to the foundation from the superstructure safely. At the design stage, the loading of the structure is defined and appropriate material choices are made based upon their properties, mainly related to strength. The strength of materials kept on reducing with time because of many factors like environmental exposure and deformation caused by unpredictable external loads. Hence, to predict the strength of materials used in structures, various techniques are used. Among these techniques, Non-Destructive Techniques (NDT) are the one that can be used to predict the strength without damaging the structure. In the present study, the compressive strength of concrete has been predicted using Artificial Neural Network (ANN). The predicted strength was compared with the experimentally obtained actual compressive strength of concrete and equations were developed for different models. A good co-relation has been obtained between the predicted strength by these models and experimental values. Further, the co-relation has been developed using two NDT techniques for prediction of strength by regression analysis. It was found that the percentage error has been reduced between the predicted strength by using combined techniques in place of single techniques.

Keywords: rebound, ultra-sonic pulse, penetration, ANN, NDT, regression

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Authors: Lian Wu, Mervyn Merrilees

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Chronic Obstructive Pulmonary Disease (COPD) is a worldwide problem, characterized by irreversible and progressive airflow obstruction. In New Zealand, it is currently the 4th commonest cause of death and exacerbations of COPD are a frequent cause of admission to hospital. Serum levels of Clara cell secretory protein-16 (CC-16) are believed to represent Clara cell toxicity. More recently, CC-16 has been found to be associated with smoker COPD. It is produced almost exclusively by non-ciliated Clara cells in the airways, and its primary function is to protect the lungs against oxidative stress and carcinogenesis. After acute exposure to cigarette smoke, serum levels of CC-16 become elevated. CC16 is a potent natural immune-suppressor and anti-inflammatory agent. In vitro, CC16 inhibits both monocyte and polymorphonuclear neutrophils chemotaxis and phagocytosis. CC16 also inhibits fibroblast chemotaxis. However, the role of CC-16 in non-smoking related COPD is still not clear. In this study, we investigated serum CC-16 levels in non-smoking related COPD. Methods: We compared non-smoker patients with COPD (FEV1<60% of predicted, FEV1/FVC <0.7, n=100) and individuals with normal lung function FEV1≥ 80% of predicted and FEV1/FVC≥ 0.7, n=80). All subjects had no smoking history. CC-16 was measured by ELISA. Results and conclusion: Serum CC-16 levels are reduced in individuals with non-smoking related COPD, and there is a weak correlation with disease severity in non-smoking related COPD group compared to non-smoker controls.

Keywords: COPD, CC-16, ELISA, non-smoking-related COPD

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Authors: Mohammadjavad Sotoudeheian, Soroush Nematollahi

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Crohn’s disease (CD) is a chronic gastrointestinal segment inflammation encompassing immune dysregulation in a genetically susceptible individual in response to the environmental triggers and interaction between the microbiome and immune system. Uncontrolled inflammation leads to long-term complications, including fibrotic strictures and enteric fistulae. Increased production of Th1 and Th17-cell cytokines and defects in T-regulatory cells have been associated with CD. Th17-cells are essential for protection against extracellular pathogens, but their atypical activity can cause autoimmunity. Intrinsic defects in the control of programmed cell death in the mucosal T-cell compartment are strongly implicated in the pathogenesis of CD. The apoptosis defect in mucosal T-cells in CD has been endorsed as an imbalance of the Bcl-2 and the Bax. The immune system encounters foreign antigens through microbial colonization of mucosal surfaces or infections. In addition, FOSL downregulated IL-26 expression, a cytokine that marks inflammatory Th17-populations in patients suffering from CD. Furthermore, the expression of IL-23 is associated with the transcription factor primary leucine zipper transcription factor ATF-like (Batf). Batf-deficiency demonstrated the crucial role of Batf in colitis development. Batf and IL-23 mediate their effects by inducing IL-6 production. Strong association of IL-23R, Stat3, and Stat4 with IBD susceptibility point to a critical involvement of T-cells. IL-23R levels in transfer fistula were dependent on the AP-1 transcription factor JunB that additionally controlled levels of RORγt by facilitating DNA binding of Batf. T lymphocytes lacking JunB failed to induce IL-23- and Th17-mediated experimental colitis highlighting the relevance of JunB for the IL-23/ Th17 pathway. The absence of T-bet causes unrestrained Th17-cell differentiation. T-cells are central parts of immune-mediated colon fistula. Especially Th17-cells were highly prevalent in inflamed IBD tissues, as RORγt is effective in preventing colitis. Intraepithelial lymphocytes (IEL) contain unique T-cell subsets, including cells expressing RORγt. Increased activated Th17 and decreased T-regulatory cells in inflamed intestinal tissues had been seen. T-cells differentiate in response to many cytokines, including IL-1β, IL-6, IL-23, and TGF-β, into Th17-cells, a process which is critically dependent on the Batf. IL-23 promotes Th17-cell in the colon. Batf manages the generation of IL-23 induced IL-23R+ Th17-cells. Batf is necessary for TGF-β/IL-6-induced Th17-polarization. Batf-expressing T-cells are the core of T-cell-mediated colitis. The human-specific parts of three AP-1 transcription factors, FOSL1, FOSL2, and BATF, are essential during the early stages of Th17 differentiation. BATF supports the Th17 lineage. FOSL1, FOSL2, and BATF make possession of regulatory loci of genes in the Th17 lineage cascade. The AP1 transcription factor Batf is identified to control intestinal inflammation and seems to regulate pathways within lymphocytes, which could theoretically control the expression of several genes. It shows central regulatory properties over Th17-cell development and is intensely upregulated within IBD-affected tissues. Here, we demonstrated that targeting Batf in IBD appears as a therapeutic approach that reduces colitogenic T-cell activities during fistula formation while aiming to affect inflammation in the gut epithelial cells.

Keywords: immune system, Crohn’s Disease, BATF, T helper cells, Bcl, interleukin, FOSL

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Authors: Hanan Khojah, RuAngelie Edrada-Ebel

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Neurodegenerative disease including Alzheimer’s disease is a major cause of long-term disability. Oxidative stress is frequently implicated as one of the key contributing factors to neurodegenerative diseases. Protection against neuronal damage remains a great challenge for researchers. Ficus carica (commonly known as fig) is a species of great antioxidant nutritional value comprising a protective mechanism against innumerable health disorders related to oxidative stress as well as Alzheimer’s disease. The purpose of this work was to characterize the non-polar active metabolites in Ficus carica endocarp, mesocarp, and exocarp. Crude extracts were prepared using several extraction solvents, which included 1:1 water: ethylacetate, acetone and methanol. The dried extracts were then solvent partitioned between equivalent amounts of water and ethylacetate. Purification and fractionation were accomplished by high-throughput chromatography. The isolated metabolites were tested on their effect on human neuroblastoma cell line by cell viability test and cell cytotoxicity assay with acrolein. Molecular weights of the active metabolites were determined via LC–HRESIMS and GC-EIMS. Metabolomic profiling was performed to identify the active metabolites by using differential expression analysis software (Mzmine) and SIMCA for multivariate analysis. Structural elucidation and identification of the interested active metabolites were studied by 1-D and 2-D NMR. Significant differences in bioactivity against a concentration-dependent assay on acrolein radicals were observed between the three fruit parts. However, metabolites obtained from mesocarp and the endocarp demonstrated bioactivity to scavenge ROS radical. NMR profiling demonstrated that aliphatic compounds such as γ-sitosterol tend to induce neuronal bioactivity and exhibited bioactivity on the cell viability assay. γ-Sitosterol was found in higher concentrations in the mesocarp and was considered as one of the major phytosterol in Ficus carica.

Keywords: alzheimer, Ficus carica, γ-Sitosterol, metabolomics

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Authors: Mehdi Salari

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This work introduces a new experimental method of martensite treatment contains accumulative roll-bonding used for producing the nano/ultrafine grained structure in low carbon steel. The ARB process up to 4 cycles was performed under unlubricated conditions, while the annealing process was carried out in the temperature range of 450–550°C for 30–100 min. The microstructures of the deformed and annealed specimens were investigated. The results showed that in the annealed specimen at 450°C for 30 or 60 min, recrystallization couldn’t be completed. Decrease in time and temperature intensified the volume fraction of the martensite cell blocks. Fully equiaxed nano/ultrafine grained ferrite was developed from the martensite cell blocks during the annealing at temperature around 500°C for 100 min.

Keywords: martensite process, accumulative roll bonding, recrystallization, nanostructure, plain carbon steel

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Authors: S. Sudhakar, Geetha Manjunath, Siva Teja Kakileti, Himanshu Madhu

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Diagnosis of breast cancer at early stages has seen better clinical and survival outcomes. Survival rates in developing countries like India are very low due to accessibility and affordability issues of screening tests such as Mammography. In addition, Mammography is not much effective in younger women with dense breasts. This leaves a gap in current screening methods. Thermalytix is a new technique for detecting breast abnormality in a non-contact, non-invasive way. It is an AI-enabled computer-aided diagnosis solution that automates interpretation of high resolution thermal images and identifies potential malignant lesions. The solution is low cost, easy to use, portable and is effective in all age groups. This paper presents the results of a retrospective comparative analysis of Thermalytix over Mammography and Clinical Breast Examination for breast cancer screening. Thermalytix was found to have better sensitivity than both the tests, with good specificity as well. In addition, Thermalytix identified all malignant patients without palpable lumps.

Keywords: breast cancer screening, radiology, thermalytix, artificial intelligence, thermography

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Authors: Małgorzata Tomczyńska, Joanna Saluk-Bijak

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Background: Graves’ disease is a frequent organ-specific autoimmune thyroid disease, which characterized by the presence of different kind autoantibodies, that, in most cases, act as agonists of the thyrotropin receptor, leading to hyperthyroidism. Role of platelets and lymphocytes can be modulated in the pathophysiology of thyroid autoimmune diseases. Interference in the physiology of platelets can lead to enhanced activity of these cells. Activated platelets can bind to circulating lymphocytes and to affect lymphocyte adhesion. Platelets and lymphocytes can regulate mutual functions. Therefore, the activation of T lymphocytes, as well as blood platelets, is associated with the development of inflammation and oxidative stress within the target tissue. The present study was performed to investigate a platelet-lymphocyte relation by assessing the degree of their mutual aggregation in whole blood of patients with Graves’ disease. Also, the purpose of this study was to examine the impact of platelet interaction on lymphocyte migration capacity. Methods: 30 patients with Graves’ disease were recruited in the study. The matched 30 healthy subjects were served as the control group. Immunophenotyping of lymphocytes was carried out by flow cytometry method. A CytoSelect™ Cell Migration Assay Kit was used to evaluate lymphocyte migration and adhesion to blood platelets. Visual assessment of lymphocyte-platelet aggregate morphology was done using confocal microscope after magnetic cell isolation by Miltenyi Biotec. Results: The migration and functional responses of lymphocytes to blood platelets were greater in the group of Graves’ disease patients compared with healthy controls. The group of Graves’ disease patients exhibited a reduced T lymphocyte and a higher B cell count compared with controls. Based on microscopic analysis, more platelet-lymphocyte aggregates were found in patients than in control. Conclusions: Studies have shown that in Graves' disease, lymphocytes show increased platelet affinity, more strongly migrating toward them, and forming mutual cellular conglomerates. This may be due to the increased activation of blood platelets in this disease.

Keywords: blood platelets, cell migration, Graves’ disease, lymphocytes, lymphocyte-platelet aggregates

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Authors: Laura Brennan, Ram Balakumar

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ChatGPT has been developed by Open AI (Nov 2022) as a powerful artificial intelligence (AI) language model which has been designed to produce human-like text from user written prompts. To gain the most from the system, user written prompts must give context specific information. This article aims to give guidance on how to optimise the ChatGPT system in the context of education for otolaryngology. Otolaryngology is a specialist field which sees little time dedicated to providing education to both medical students and doctors. Additionally, otolaryngology trainees have seen a reduction in learning opportunities since the COVID-19 pandemic. In this article we look at these various barriers to medical education in Otolaryngology training and suggest ways that ChatGPT can overcome them and assist in simulation-based training. Examples provide how this can be achieved using the Authors’ experience to further highlight the practicalities. What this article has found is that while ChatGPT cannot replace traditional mentorship and practical surgical experience, it can serve as an invaluable supplementary resource to simulation based medical education in Otolaryngology.

Keywords: artificial intelligence, otolaryngology, surgical training, medical education

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