Search results for: neural stem/precursor cells

Authors: Rahul Agarwal, Ashutosh Singh

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Cervical cancer is one of the women related cancers which starts from the pre-cancerous cells and a fraction of women with pre-cancers of the cervix will develop cervical cancer. Cervical pre-cancers if treated in pre-invasive stage can prevent almost all true cervical squamous cell carcinoma. The present study investigates the genes and pathways that are involved in the progression of cervical cancer and are responsible in transition from pre-invasive stage to other advanced invasive stages. The study used GDS3292 microarray data to identify the stage specific genes in cervical cancer and further to generate the network of the significant genes. The microarray data GDS3292 consists of the expression profiling of 10 normal cervices, 7 HSILs and 21 SCCs samples. The study identifies 70 upregulated and 37 downregulated genes in HSIL stage while 95 upregulated and 60 downregulated genes in SCC stages. Biological process including cell communication, signal transduction are highly enriched in both HSIL and SCC stages of cervical cancer. Further, the ppi interaction of genes involved in HSIL and SCC stages helps in identifying the interacting partners. This work may lead to the identification of potential diagnostic biomarker which can be utilized for early stage detection.

Keywords: cervical cancer, HSIL, microarray, SCC

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Authors: Chin-Yuan Hsu, Yu-Lung Chuang

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The expression, concentration, and activity of mitochondrial energy-utilized molecules and cellular energy-regulated molecules decreased with age in the trophocytes and oenocytes of honeybees (Apis mellifera), but those of cellular energy-metabolized molecules is unknown. In this study, the expression, concentration, and activity of cellular energy-metabolized molecules were assayed in the trophocytes and fat cells of young and old worker bees by using the techniques of cell and biochemistry. The results showed that (i) the •-hydroxylacyl-coenzyme A dehydrogenase (HOAD) activity/citrate synthase (CS) activity ratio, non-esterified fatty acids concentrations, the expression of eukaryotic initiation factor 4E, and the expression of phosphorylated eIF4E binding protein 1 decreased with age; (ii) fat and glycogen accumulation increased with age; and (iii) the pyruvate dehydrogenase (PDH) activity/citrate synthase (CS) activity ratio was not correlated with age. These finding indicated that •-oxidation (HOAD/CS) and protein synthsis decreased with age. Glycolysis (PDH/CS) was unchanged with age. The most likely reason is that sugars are the vital food of worker bees. Taken together these data reveal that young workers have higher cellular energy metabolism than old workers and that aging results in a decline in the cellular energy metabolism in worker honeybees.

Keywords: aging, energy, honeybee, metabolism

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Authors: S. Khosravi, X. Chelius, A. Unger, D. Rieger, J. Frickel, T. Sachsenheimer, C. Luechtenborg, R. Schieweck, B. Bruegger, B. Westermann, T. Klecker, W. Neupert, M. E. Harner

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The use of Saccharomyces cerevisiae as a model organism to study eukaryotic cell functions has been used successfully for decades. Like virtually all eukaryotic cells, they contain mitochondria as essential organelles performing various functions, including participation in lipid metabolism. They are separated from the cytosol by a double membrane system consisting of the mitochondrial inner membrane (MIM) and the mitochondrial outer membrane (MOM). This physical separation of the mitochondria requires an exchange of metabolites, proteins, and lipids. Proteinaceous contact sites are thought to be important for this communication. Recently, it was found that Cqd1, in cooperation with Cqd2, controls the distribution of Coenzyme Q within the cell. In this study, a contact site is described, formed by the MOM protein complex Por1-Om14 and the UbiB protein kinase-like MIM protein Cqd1. The present results suggest the additional involvement of Cqd1 in the homeostasis of phospholipids. Moreover, we show that overexpression of the UbiB family proteins also causes tethering of the mitochondria to the endoplasmatic reticulum. Due to the conservation of the subunits of this contact site to higher eukaryotes, its identification in S. cerevisiae might provide promising avenues for further research in other organisms.

Keywords: contact sites, mitochondrial architecture, mitochondrial proteins, yeast mitochondria

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Authors: Jacques M. Berner, Monja Gerber, Gillian L. Maggs-Kolling, Stuart J. Piketh

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The enigmatic melon species, Acanthosicyos horridus Welw. ex Hook. f., locally known as !nara, is endemic to the hyper-arid Namib Desert, where it thrives in sandy dune areas and dry river banks. The Namib Desert is characterized by extreme weather conditions which include high temperatures, very low rainfall, and extremely dry air. Plant and animals that have made the Namib Dessert their home are dependent on non-rainfall water inputs, like fog, dew and water vapor, for survival. Fog is believed to be the most important non-rainfall water input for most of the coastal Namib Desert and is a life line to many Namib plants and animals. It is commonly assumed that the !nara plant is adapted and dependent upon coastal fog events. The !nara plant shares many comparable adaptive features with other organisms that are known to exploit fog as a source of moisture. These include groove-like structures on the stems and the cone-like structures of thorns. These structures are believed to be the driving forces behind directional water flow that allow plants to take advantage of fog events. The !nara-fog interaction was investigated in this study to determine the dependence of !nara on these fog events, as it would illustrate strategies to benefit from non-rainfall water inputs. The direct water uptake capacity of !nara shoots was investigated through absorption tests. Furthermore, the movement and behavior of fluorescent water droplets on a !nara stem were investigated through time-lapse macrophotography. The shoot water potential was measured to investigate the effect of fog on the water status of !nara stems. These tests were used to determine whether the morphology of !nara has evolved to exploit fog as a non-rainfall water input and whether the !nara plant has adapted physiologically in response to fog. Chlorophyll a fluorescence was used to compare the photochemical efficiency of !nara plants on days with fog events to that on non-foggy days. The results indicate that !nara plants do have the ability to take advantage of fog events as commonly believed. However, the !nara plant did not exhibit visible signs of drought stress and this, together with the strong shoot water potential, indicates that these plants are reliant on permanent underground water sources. Chlorophyll a fluorescence data indicated that temperature stress and wind were some of the main abiotic factors influencing the plants’ overall vitality.

Keywords: Acanthosicyos horridus, chlorophyll a fluorescence, fog, foliar absorption, !nara

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Authors: Ilma Robo, Saimir Heta, Gerhard Nokaj

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Introduction: The method of treatment and the treatment protocols of apical periodontitis are now known, but the ongoing debate remains on whether or not prescription antibiotics should be given to patients suffering from this type of pathology. In fact, as an indication for prescribing antibiotics, this type of pathology remains between clinical indication and contraindication. Material and Methods: This article is of the short-communication type and has the sole purpose of analyzing the clinical picture of apical periodontitis and the fact that the appearance and extent of this pathology in the periapex area passes the stage when the host or the immune cells of the organism of the affected individual, react against bacterial factors. Results: Determining whether or not to prescribe systemic antibiotics according to literature sources can be avoided. In some cases, research in this field about this pathology even indicates endodontic rinsers or irrigants, such as chlorhexidine, in typical cases, mainly in persistent apical periodontitis. Conclusions: In times when bacterial resistance is a hot topic in some fields of scientific research, it is important to divide dental pathologies of bacterial origin into those when systemic antibiotic prescriptions must be given and those when every clinical issue is resolved only with endodontic root canal treatment. Even certain sources of published literature show the specifics of the most effective antibiotics against the bacterial flora causing the pathology of apical periodontitis.

Keywords: endodontic treatment, apical periodontitis, antibiotics, chlorhexidine

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Authors: Jeong Hwan Joo, Keun Pil Kim

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During meiosis, meiotic recombination is initiated by Spo11-mediated DSB formation and exonuclease-mediated DSB resection occurs to expose single stranded DNA formation. RPA is further required to inhibit secondary structure formation of ssDNA that can be formed Watson-Crick pairing. Rad51-Dmc1, RecA homologs in eukaryote and their accessory factors involve in searching homolog templates to mediate strand exchange. In this study, we investigate the recombinational roles of replication protein A (RPA), which is heterotrimeric protein that is composed of RPA1, RPA2, and RPA3. Here, we investigated meiotic recombination using DNA physical analysis at the HIS4LEU2 hot spot. In rfa1-119 (K45E, N316S) cells, crossover (CO) and non-crossover (NCO) products reduced than WT. rfa1-119 delayed in single end invasion-to-double holiday junction (SEI-to-dHJ) transition and exhibits a defect in second-end capture that is also modulated by Rad52. In the further experiment, we observed that in rfa1-119 mutant, RPA could not be released in timely manner. Furthermore, rfa1-119 exhibits failure in the second end capture, implying reduction of COs and NCOs. In this talk, we will discuss more detail how RPA involves in chromatin axis association via formation of axis-bridge and why RPA is required for Rad52-mediated second-end capture progression.

Keywords: homolog interaction, meiotic recombination, replication protein A, RPA1

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Authors: Jonas Colin

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Standing at the vanguard of AI development, Alpha represents an unprecedented synthesis of logical rigor and human abstraction, meticulously crafted to mirror the user's unique persona and personality, a feat previously unattainable in AI development. Alpha, an avant-garde artefact in the realm of artificial intelligence, epitomizes a paradigmatic shift in personalized digital interaction, amalgamating user-specific dialogic patterns with the sophisticated algorithmic prowess of OpenAI's GPT-3.5 to engender a platform for enhanced metacognitive engagement and individualized user experience. Underpinned by a sophisticated algorithmic framework, Alpha integrates vast datasets through a complex interplay of neural network models and symbolic AI, facilitating a dynamic, adaptive learning process. This integration enables the system to construct a detailed user profile, encompassing linguistic preferences, emotional tendencies, and cognitive styles, tailoring interactions to align with individual characteristics and conversational contexts. Furthermore, Alpha incorporates advanced metacognitive elements, enabling real-time reflection and adaptation in communication strategies. This self-reflective capability ensures continuous refinement of its interaction model, positioning Alpha not just as a technological marvel but as a harbinger of a new era in human-computer interaction, where machines engage with us on a deeply personal and cognitive level, transforming our interaction with the digital world.

Keywords: chatbot, GPT 3.5, metacognition, symbiose

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Authors: Chih-Chieh Yang, Chung-Neng Huang

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In power system, how to improve the fault diagnosis technology of transmission line has always been the primary goal of power grid operators. In recent years, due to the rise of green energy, the addition of all kinds of distributed power also has an impact on the stability of the power system. Because the smart meters are with the function of data recording and bidirectional transmission, the adaptive Fuzzy Neural inference system, ANFIS, as well as the artificial intelligence that has the characteristics of learning and estimation in artificial intelligence. For transmission network, in order to avoid misjudgment of the fault type and location due to the input of these unstable power sources, combined with the above advantages of smart meter and ANFIS, a method for identifying fault types and location of faults is proposed in this study. In ANFIS training, the bus voltage and current information collected by smart meters can be trained through the ANFIS tool in MATLAB to generate fault codes to identify different types of faults and the location of faults. In addition, due to the uncertainty of distributed generation, a wind power system is added to the transmission network to verify the diagnosis correctness of the study. Simulation results show that the method proposed in this study can correctly identify the fault type and location of fault with more efficiency, and can deal with the interference caused by the addition of unstable power sources.

Keywords: ANFIS, fault diagnosis, power system, smart meter

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Authors: Elena G. Salina, Vadim A. Makarov

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With the emergence of primary resistance to the current drugs and wide distribution of latent tuberculosis infection, a need for new compounds with a novel mode of action is growing steadily. Copper-mediated innate immunity and antibacterial toxicity propose novel strategies in TB drug discovery and development. Transcriptome of M. tuberculosis was obtained by RNA-seq, intracellular copper content was measured by ISP MS and complexes of 1-hydroxy-2-thiopyridines with copper were detected by HPLC.1-hydroxy-2-thiopyridine derivatives were found to be highly active in vitro against both actively growing and dormant non-culturable M. tuberculosis. Transcriptome response to 1-hydroxy-2-thiopyridines revealed signs of copper toxicity in M. tuberculosis bacilli. Indeed, Cu was found to accumulate inside cells treated with 1-hydroxy-2-thiopyridines. These compounds were found to form stable charged lipophylic complexes with Cu²⁺ ions which transport into mycobacterial cell. Subsequent metabolic destruction of the complex led to transformation of 1-hydroxy-2-thiopyridines into 2-methylmercapto-2-ethoxycarbonylpyridines, which did not possess antitubercular activity and releasing of free Cu²⁺ in the cytoplasm. 1-hydroxy-2-thiopyridines are a potent class of Cu-dependent inhibitors of M. tuberculosis which may control M. tuberculosis infection by impairment of copper homeostasis. Acknowledgment: This work was financially supported by the Ministry of Education and Science of the RussianFederation (Agreement No 14.616.21.0065; unique identifier RFMEFI61616X0065).

Keywords: copper toxicity, drug discovery, M. tuberculosis inhibitors, 2-thiopyridines

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Authors: Simone Leonardi, Luca Ardito

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Micro-influencers are effective elements in the marketing strategies of companies and institutions because of their capability to create an hyper-engaged audience around a specific topic of interest. In recent years, many scientific approaches and commercial tools have handled the task of detecting this type of social media users. These strategies adopt solutions ranging from rule based machine learning models to deep neural networks and graph analysis on text, images, and account information. This work compares the existing solutions and proposes an ensemble method to generalize them with different input data and social media platforms. The deployed solution combines deep learning models on unstructured data with statistical machine learning models on structured data. We retrieve both social media accounts information and multimedia posts on Twitter and Instagram. These data are mapped into feature vectors for an eXtreme Gradient Boosting (XGBoost) classifier. Sixty different topics have been analyzed to build a rule based gold standard dataset and to compare the performances of our approach against baseline classifiers. We prove the effectiveness of our work by comparing the accuracy, precision, recall, and f1 score of our model with different configurations and architectures. We obtained an accuracy of 0.91 with our best performing model.

Keywords: deep learning, gradient boosting, image processing, micro-influencers, NLP, social media

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Authors: Syahidah N. Zulkifli, Herlina A. Rahim, Nurul A. M. Subha

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Sustaining water quality is critical in order to avoid any harmful health consequences for end-user consumers. The detection of microbial impurities at the household level is the foundation of water security. Water quality is now monitored only at water utilities or infrastructure, such as water treatment facilities or reservoirs. This research provides a first-hand scientific understanding of microbial composition presence in Malaysia’s household point-of-use (POUs) water supply influenced by seasonal fluctuations, standstill periods, and flow dynamics by using the NIR-Raman spectroscopic technique. According to the findings, 20% of water samples were contaminated by pathogenic bacteria, which are Legionella and Salmonella cells. A comparison of the spectra reveals significant signature peaks (420 cm⁻¹ to 1800 cm⁻¹), including species-specific bands. This demonstrates the importance of regularly monitoring POUs water quality to provide a safe and clean water supply to homeowners. Conventional Raman spectroscopy, up-to-date, is no longer suited for real-time monitoring. Therefore, this study introduced an alternative micro-spectrometer to give a rapid and sustainable way of monitoring POUs water quality. Assessing microbiological threats in water supply becomes more reliable and efficient by leveraging IoT protocol.

Keywords: microbial contaminants, water quality, water monitoring, Raman spectroscopy

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Authors: Riaan Kleyn

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Mass wine production companies across the globe are provided with grapes from winegrowers that predominantly utilize mechanical harvesting machines to harvest wine grapes. Mechanical harvesting accelerates the rate at which grapes are harvested, allowing grapes to be delivered faster to meet the demands of wine cellars. The disadvantage of the mechanical harvesting method is the inclusion of material-other-than-grapes (MOG) in the harvested wine grape loads arriving at the cellar which degrades the quality of wine that can be produced. Currently, wine cellars do not have a method to determine the amount of MOG present within wine grape loads. This paper seeks to find an optimal computer vision method capable of detecting the amount of MOG within a wine grape load. A MOG detection method will encourage winegrowers to deliver MOG-free wine grape loads to avoid penalties which will indirectly enhance the quality of the wine to be produced. Traditional image segmentation methods were compared to deep learning segmentation methods based on images of wine grape loads that were captured at a wine cellar. The Mask R-CNN model with a ResNet-50 convolutional neural network backbone emerged as the optimal method for this study to determine the amount of MOG in an image of a wine grape load. Furthermore, a statistical analysis was conducted to determine how the MOG on the surface of a grape load relates to the mass of MOG within the corresponding grape load.

Keywords: computer vision, wine grapes, machine learning, machine harvested grapes

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Authors: Chandra Shekhar Majumder, Md. Shamsul Haque, Khondaker Anower Hossain, Md. Rafiqul Islam

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Introduction: Ocular helminths are parasites that infect the eye or its adnexa. They can be either motile worms or sessile worms that form cysts. These parasites require two hosts for their life cycle, a definite host (usually a human) and an intermediate host (usually an insect). While there have been reports of ocular helminths infecting various structures of the eye, including the anterior chamber and subconjunctival space, there is no previous record of such a case involving the lens. Research Aim: The aim of this case report is to present a rare case of ocular helminth infection in the lens and to contribute to the understanding of this unusual site of infection. Methodology: This study is a case report, presenting the details and findings of an 80-year-old retired policeman who presented with severe pain, redness, and vision loss in the left eye. The patient had a history of diabetes mellitus and hypertension. The examination revealed the presence of a thread-like helminth in the lens. The patient underwent treatment and follow-up, and the helminth specimen was sent for identification to the department of Parasitology. Case report: An 80-year-old retired policeman attended the OPD, Faridpur Medical College Hospital with the complaints of severe pain, redness and gross dimness of vision of the left eye for 5 days. He had a history of diabetes mellitus and hypertension for 3 years. On examination, L/E visual acuity was PL only, moderate ciliary congestion, KP 2+, cells 2+ and posterior synechia from 5 to 7 O’clock position was found. Lens was opaque. A thread like helminth was found under the anterior of the lens. The worm was moving and changing its position during examination. On examination of R/E, visual acuity was 6/36 unaided, 6/18 with pinhole. There was lental opacity. Slit-lamp and fundus examination were within normal limit. Patient was admitted in Faridpur Medical College Hospital. Diabetes mellitus was controlled with insulin. ICCE with PI was done on the same day of admission under depomedrol coverage. The helminth was recovered from the lens. It was thread like, about 5 to 6 mm in length, 1 mm in width and pinkish in colour. The patient followed up after 7 days, VA was HM, mild ciliary congestion, few KPs and cells were present. Media was hazy due to vitreous opacity. The worm was sent to the department of Parasitology, NIPSOM, Dhaka for identification. Findings: The findings of this case report highlight the presence of a helminth in the lens, which has not been previously reported. The helminth was successfully removed from the lens, but the patient experienced complications such as anterior uveitis and vitreous opacity. The exact mechanism by which the helminth enters the lens remains unclear. Theoretical Importance: This case report contributes to the existing literature on ocular helminth infections by reporting a unique case involving the lens. It highlights the need for further research to understand the pathogenesis and mechanism of entry of helminths in the lens. Data Collection and Analysis Procedures: The data for this case report were collected through clinical examination and medical records of the patient. The findings were described and presented in a descriptive manner. No statistical analysis was conducted. Question Addressed: This case report addresses the question of whether ocular helminth infections can occur in the lens, which has not been previously reported. Conclusion: To the best of our knowledge, this is the first reported case of ocular helminth infection in the lens. The presence of the helminth in the lens raises interesting questions regarding its pathogenesis and entry mechanism. Further study and research are needed to explore these aspects. Ophthalmologists and parasitologists should be aware of the possibility of ocular helminth infections in unusual sites like the lens.

Keywords: ocular, helminth, unsual site, lens

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Authors: Glauco M. M. M. Lustosa, João Paulo C. Costa, Leinig Antônio Perazolli, Maria Aparecida Zaghete

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SnO2 has electrical conductivity due to the excess of electrons and structural defects, being its electrical behavior highly dependent on sintering temperature and chemical composition. The addition of metals modifiers into the crystalline structure can improve and controlling the behavior of some semiconductor oxides that can therefore develop different applications such as varistors (ceramic with non-ohmic behavior between current and voltage, i.e. conductive during normal operation and resistive during overvoltage). The polymeric precursor method, based on the complexation reaction between metal ion and policarboxylic acid and then polymerized with ethylene glycol, was used to obtain nanopowders ceramic. The metal immobilization reduces its segregation during the decomposition of the polyester resulting in a crystalline oxide with high chemical homogeneity. The preparation of films from ceramics nanoparticles using electrophoretic deposition method (EPD) brings prospects for a new generation of smaller size devices with easy integration technology. EPD allows to control time and current and therefore it can have control of the thickness, surface roughness and the film density, quickly and with low production costs. The sintering process is key to control size and grain boundary density of the film. In this step, there is the diffusion of metals that promote densification and control of intrinsic defects or change these defects which will form and modify the potential barrier in the grain boundary. The use of microwave oven for sintering is an advantageous process due to the fast and homogeneous heating rate, promoting the diffusion and densification without irregular grain growth. This research was done a comparative study of sintering temperature by use of zinc as modifier agent to verify the influence on sintering step aiming to promote densification and grain growth, which influences the potential barrier formation and then changed the electrical behavior. SnO2-nanoparticles were obtained with 1 %mol of ZnO + 0.05 %mol of Nb2O5 (SZN), deposited as film through EPD (voltage 2 kV, time of 10 min) on Si/Pt substrate. Sintering was made in a microwave oven at 800, 900 and 1000 °C. For complete coverage of the substrate by nanoparticles with low surface roughness and uniform thickness was added 0.02 g of solid iodine in alcoholic suspension SnO2 to increase particle surface charge. They were also used magneto in EPD system that improved the deposition rate forming a compact film. Using a scanning electron microscope of high resolution (SEM_FEG) it was observed nanoparticles with average size between 10-20 nm, after sintering the average size was 150 to 200 nm and thickness of 5 µm. Also, it was verified that the temperature at 1000 °C was the most efficient in sintering. The best sintering time was also recorded and determined as 40 minutes. After sintering, the films were recovered with Cr3+ ions layer by EPD, then the films were again thermally treated. The electrical characterizations (nonlinear coefficient of 11.4, voltage rupture of ~60 V and leakage current = 4.8x10−6 A), allow considering the new methodology suitable for prepare SnO2-based varistor applied for development of electrical protection devices for low voltage.

Keywords: chemical synthesis, electrophoretic deposition, microwave sintering, tin dioxide

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Authors: Magdalena Hałupka-Bryl, Magdalena Bednarowicz, Ryszard Krzyminiewski, Yukio Nagasaki

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Due to their unique physical properties, superparamagnetic iron oxide nanoparticles are increasingly used in medical applications. They are very useful carriers for delivering antitumor drugs in targeted cancer treatment. Magnetic nanoparticles (PEG-PIONs/DOX) with chemotherapeutic were synthesized by coprecipitation method followed by coating with biocompatible polymer PEG-derivative (poly(ethylene glycol)-block-poly(4-vinylbenzylphosphonate). Complete physicochemical characterization was carried out (ESR, HRTEM, X-ray diffraction, SQUID analysis) to evaluate the magnetic properties of obtained PEG-PIONs/DOX. Nanoparticles were investigated also in terms of their stability, drug loading efficiency, drug release and antiproliferative effect on cancer cells. PEG-PIONs/DOX have been successfully used for the efficient delivery of an anticancer drug into the tumor region. Fluorescent imaging showed the internalization of PEG-PIONs/DOX in the cytoplasm. Biodistribution studies demonstrated that PEG-PIONs/DOX preferentially accumulate in tumor region via the enhanced permeability and retention effect. The present findings show that synthesized nanosystem is promising tool for potential magnetic drug delivery.

Keywords: targeted drug delivery, magnetic properties, iron oxide nanoparticles, biodistribution

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Authors: Anne Marie Morrin

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This paper will focus on the design, delivery and assessment of a transdisciplinary STEAM (Science, Technology, Engineering, Arts, and Mathematics) education initiative in a college of education in Ireland. The project explores a transdisciplinary approach to supporting STEAM education where the concepts, methodologies and assessments employed derive from visual art sessions within initial teacher education. The research will demonstrate that the STEAM Education approach is effective when visual art concepts and methods are placed at the core of the teaching and learning experience. Within this study, emphasis is placed on authentic collaboration and transdisciplinary pedagogical approaches with the STEAM subjects. The partners included a combination of teaching expertise in STEM and Visual Arts education, artists, in-service and pre-service teachers and children. The inclusion of all stakeholders mentioned moves towards a more authentic approach where transdisciplinary practice is at the core of the teaching and learning. Qualitative data was collected using a combination of questionnaires (focused and open-ended questions) and focus groups. In addition, the data was collected through video diaries where students reflected on their visual journals and transdisciplinary practice, which gave rich insight into participants' experiences and opinions on their learning. It was found that an effective program of STEAM education integration was informed by co-teaching (continuous professional development), which involved a commitment to adaptable and flexible approaches to teaching, learning, and assessment, as well as the importance of continuous reflection-in-action by all participants. The delivery of a transdisciplinary model of STEAM education was devised to reconceptualizatise how individual subject areas can develop essential skills and tackle critical issues (such as self-care and climate change) through data visualisation and technology. The success of the project can be attributed to the collaboration, which was inclusive, flexible and a willingness between various stakeholders to be involved in the design and implementation of the project from conception to completion. The case study approach taken is particularistic (focusing on the STEAM-ED project), descriptive (providing in-depth descriptions from varied and multiple perspectives), and heuristic (interpreting the participants’ experiences and what meaning they attributed to their experiences).

Keywords: collaboration, transdisciplinary, STEAM, visual arts education

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Authors: Tomas Trainys, Algimantas Venckauskas

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Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.

Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.

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Authors: Samir Dekali, David Crouzier

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Due to their new physico-chemical properties engineered nanoparticles (ENPs) are increasingly employed in numerous industrial sectors (such as electronics, textile, aerospace, cosmetics, pharmaceuticals, food industry, etc). These new physico-chemical properties can also represent a threat for the human health. Consumers can notably be exposed involuntarily by different routes such as inhalation, ingestion or through the skin. Several studies recently reported a possible biodistribution of these ENPs on the blood-brain barrier (BBB). Consequently, there is a great need for developing BBB in vitro models representative of the in vivo situation and capable of rapidly and accurately assessing ENPs toxic effects and their potential translocation through this barrier. In this study, several in vitro models established with micro-endothelial brain cell lines of different origins (bEnd.3 mouse cell line or a new human cell line) co-cultivated or not with astrocytic cells (C6 rat or C8-B4 mouse cell lines) on Transwells® were compared using different endpoints: trans-endothelial resistance, permeability of the Lucifer yellow and protein junction labeling. Impact of NIST diesel exhaust particles on BBB cell viability is also discussed.

Keywords: nanoparticles, blood-brain barrier, diesel exhaust particles, toxicology

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Authors: Maha Soltan, Amal Z. Hassan, Howaida I. Abd-Alla, Atef G. Hanna

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Two naturally known cardenolides; acovenoside A and acobioside A were isolated from the Egyptian cultivar; Acokanthera spectabilis leaves. It is an ornamental and poisonous plant that has been traditionally claimed for their medicinal properties against infectious microbes, killing worms and curing some inflammations at little amounts. We examined the growth inhibition effects of both cardenolides against four types of human cancer cell lines using Sulphorhodamine B assay. In addition, the clonogenic assay was also performed for testing the growth inhibiting power of the isolated compounds. An in vitro mechanistic investigation was further accomplished against hepatocellular carcinoma HepG2 cell line. Microscopic examination, colorimetric ELISA and flow cytometry techniques were our tools of proving at least part of the anticancer pathway of the tested compounds. Both compounds were able to inhibit the growth of 4 human cancer cell lines at less than 100 nM. In addition, they were able to activate the executioner Caspase-3 and apoptosis was then induced as a consequence of cell growth arrest at G2/M. An attention must be payed to those bioactive agents particularly when giving their activity against cancer cells at considerable small values while presenting safe therapeutic margins as indicated by literature.

Keywords: anticancer, cardenolides, Caspase-3, apoptosis

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Authors: Kishore Kumar R., Kaustav Sengupta, Shalini Sood Sehgal, Poornima Santhanam

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Fashion is a human expression that is constantly changing. One of the prime factors that consistently influences fashion is the change in colour preferences. The role of colour in our everyday lives is very significant. It subconsciously explains a lot about one’s mindset and mood. Analyzing the colours by extracting them from the outfit images is a critical study to examine the individual’s/consumer behaviour. Several research works have been carried out on extracting colours from images, but to the best of our knowledge, there were no studies that extract colours to specific apparel and identify colour patterns geographically. This paper proposes a framework for accurately extracting colours from T-shirt images and predicting dominant colours geographically. The proposed method consists of two stages: first, a U-Net deep learning model is adopted to segment the T-shirts from the images. Second, the colours are extracted only from the T-shirt segments. The proposed method employs the iMaterialist (Fashion) 2019 dataset for the semantic segmentation task. The proposed framework also includes a mechanism for gathering data and analyzing India’s general colour preferences. From this research, it was observed that black and grey are the dominant colour in different regions of India. The proposed method can be adapted to study fashion’s evolving colour preferences.

Keywords: colour analysis in t-shirts, convolutional neural network, encoder-decoder, k-means clustering, semantic segmentation, U-Net model

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Authors: RAM PAL SINGH, VIKASH CHAUDHARY, MONIKA VERMA

Abstract:

In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks.

Keywords: BER, DWT, extreme leaning machine (ELM), PSNR

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Authors: Harukuni Tokuda, Xu FengHao, Nobutaka Suzuki

Abstract:

As part of an ongoing our projects to investigate the anti-tumor promoring properties (chemopreventive potency) of Gromwell seed, dry powder materials and its active compounds were carried out through useful test systems. Gromwell seed (Coix lachryma-jobi seed) (GS) is a grass crop that has long been used and played a role in traditional medicine as a nourishing food, and for the treatment of various aliments, paticularly cancer. The application of a new screening procedure which utilizes the synergistic effect of short-chain fatty acids and phorbol esters in enable rapid and easy detection of naturally occurring substances(anti-tumor promoters chemo-preventive agents) with inhibition of Epstein-Barr virus(EBV) activation, using human lymphblastoid cells. In addition, we have now extended these investigations to a new tumorigenesis model in which we initiated the tumors with DMBA intiation and promoted with 1.7 nmol of TPA in two-stage mouse skin test and other models. these results provide a basis for further development of these botanical supplements for human cancer chemoprevention and observations seem that this materials more extensively as one of the trials for the purpose of complementary and alternative medicine.

Keywords: chemoprevention, medicinal plant, mouse, carcinogenesis systems

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

Abstract:

Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

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Authors: Hakim Chayeb

Abstract:

Macrophages (Mo) play an essential role in host defense against pathogens. These inflammatory cells contain a large group of inducible enzymes such as NO synthase (NOS). This study was conducted to characterize experimentally induced inflammation in vivo by lipopolysaccharides (LPS). LPS is an essential component of the outer membrane of Gram-negative bacteria and a potent inducer of macrophage. Except control rats, all rats received different doses of LPS intra-peritoneally. The involvement of inducible NO synthase (iNOS) and constitutive (cNOS ) in the modulation of the inflammatory response was studied by treating the rats with L-NAME (non-selective NOS inhibitor) or aminoguanidine (AG inhibitor of iNOS). Inhibitors were injected 24 hours before LPS administration. The results showed that esterase activity (a marker of macrophage infiltration) which is induced by LPS is reduced by AG, was potentiated by treatment with L-NAME in tissue homogenates of the liver, kidney and spleen. Meanwhile, the concentrations of nitric oxide (NO) induced by LPS were reduced with AG and are completely inhibited with L-NAME in the tissues studied. NO concentrations and plasma transaminase levels have undergone remarkable increases in rats treated with LPS alone. However, the AG significantly reduced these rates. Our results highlighted the role of NO synthase inhibitors in reducing of inflammatory responses that characterize many infectious diseases.

Keywords: aminoguanidine, esterase, LPS, L-NAME, macrophage, nitric oxide

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Authors: S. Pradhan, D. Pradhan, G. Tripathy, T. Dasmohapatra

Abstract:

Suppressors of cytokine signalling (SOCS3), a newly indentified anti-apoptotic molecule is a downstream effecter of the receptor tyrosine kinase-Ras signalling pathway. Current study has uncovered that SOCS3 may have wide and imperative capacities, particularly because of its close correlation with malignant tumors. To investigate the impact of SOCS3 on MDR, we analyzed the expression of P-gp and SOCS3 by immune-histochemistry and found there was positive correlation between them. At that point we effectively interfered with RNA translation by the contamination of siRNA of SOCS3 into MCF7/ADM breast cancer cell lines through a lentivirus, and the expression of the target gene was significantly inhibited. After RNAi the drug resistance was reduced altogether and the expression of MDR1 mRNA and P-gp in MCF7/ADM cell lines demonstrated a significant decrease. Likewise the expression of P53 protein increased in a statistically significant manner (p ≤ 0.01) after RNAi exposure. Moreover, flowcytometry analysis uncovers that cell cycle and anti-apoptotic enhancing capacity of cells changed after RNAi treatment. These outcomes proposed SOCS3 may take part in breast cancer MDR by managing MDR1 and P53 expression, changing cell cycle and enhancing the anti-apoptotic ability.

Keywords: SOCS3gene, breast cancer, multidrug resistance, MDR1 gene, RNA interference

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Authors: Md Rafiqul Islam, Ashir Ahmed, Anwaar Ulhaq, Abu Raihan M. Kamal, Yuan Miao, Hua Wang

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Mental health of people is equally important as of their physical health. Mental health and well-being are influenced not only by individual attributes but also by the social circumstances in which people find themselves and the environment in which they live. Like physical health, there is a number of internal and external factors such as biological, social and occupational factors that could influence the mental health of people. People living in poverty, suffering from chronic health conditions, minority groups, and those who exposed to/or displaced by war or conflict are generally more likely to develop mental health conditions. However, to authors’ best knowledge, there is dearth of knowledge on the impact of workplace (especially the highly stressed IT/Tech workplace) on the mental health of its workers. This study attempts to examine the factors influencing the mental health of tech workers. A publicly available dataset containing more than 65,000 cells and 100 attributes is examined for this purpose. Number of machine learning techniques such as ‘Decision Tree’, ‘K nearest neighbor’ ‘Support Vector Machine’ and ‘Ensemble’, are then applied to the selected dataset to draw the findings. It is anticipated that the analysis reported in this study would contribute in presenting useful insights on the attributes contributing in the mental health of tech workers using relevant machine learning techniques.

Keywords: mental disorder, diagnosis, occupational stress, IT workplace

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Authors: Shreyansh Singh, Afroz Ahmed

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Sentiment Analysis intends to naturally reveal the hidden mentality that we hold towards an entity. The total of this assumption over a populace addresses sentiment surveying and has various applications. Current text-based sentiment analysis depends on the development of word embeddings and Machine Learning models that take in conclusion from enormous text corpora. Sentiment Analysis from text is presently generally utilized for consumer loyalty appraisal and brand insight investigation. With the expansion of online media, multimodal assessment investigation is set to carry new freedoms with the appearance of integral information streams for improving and going past text-based feeling examination using the new transforms methods. Since supposition can be distinguished through compelling follows it leaves, like facial and vocal presentations, multimodal opinion investigation offers good roads for examining facial and vocal articulations notwithstanding the record or printed content. These methodologies use the Recurrent Neural Networks (RNNs) with the LSTM modes to increase their performance. In this study, we characterize feeling and the issue of multimodal assessment investigation and audit ongoing advancements in multimodal notion examination in various spaces, including spoken surveys, pictures, video websites, human-machine, and human-human connections. Difficulties and chances of this arising field are additionally examined, promoting our theory that multimodal feeling investigation holds critical undiscovered potential.

Keywords: sentiment analysis, RNN, LSTM, word embeddings

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Authors: Adel Omar Ashour, Paul S. Dyer

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Aspergillus nidulans can reproduce by asexual or sexual means, producing green conidiospores or red-purple ascospores respectively. The latter one is produced in dark-purple globose ‘cleistothecia’ which are surrounded by Hülle cells. The species has a homothallic (self fertile) sexual breeding system. Given the extra metabolic costs associated with sexual compared to asexual reproduction it would be predicted that ascospore production would confer evolutionary benefits. However, due to the homothallic breeding system there is very rarely any increased genetic variation in ascospore offspring and traditionally conidia and ascospores are considered to be equally environmental resistant. We therefore examined in detail whether conidia and ascospores might exhibit as yet undetected differences in spore viability when subjected to certain environmental stressors. Spores from two strains of A. nidulans (comprising wild-type and KU mutants) were exposed to various levels of temperature (50-70°C for 30 min) and UV (350 nm for 10-60 min) stress. Results of experiments will be presented, including comparison of ‘D’ (decimal point reduction) values of conidia versus ascospores of A. nidulans. We detected that under certain exposure levels ascospores have significantly increased resistance compared to conidia. The increased environmental resistance of ascospores might be a key factor explaining the persistence of sexuality in this homothallic species, and reasons for differential survival are suggested.

Keywords: Aspergillus nidulans, asexual reproduction, conidia, ascospores, cleistothecia, d-value

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Authors: Mehmet Savsar, Majid Aldaihani

Abstract:

Flexible Manufacturing Systems (FMS) are used to produce a variety of parts on the same equipment. Therefore, their utilization is higher than traditional machining systems. Higher utilization, on the other hand, results in more frequent equipment failures and additional need for maintenance. Therefore, it is necessary to carefully analyze operational characteristics and productivity of FMS or Flexible Manufacturing Cells (FMC), which are smaller configuration of FMS, before installation or during their operation. Appropriate models should be developed to determine production rates based on operational conditions, including equipment reliability, availability, and repair capacity. In this paper, a stochastic model is developed for an automated FMC system, which consists of two machines served by two robots and a single repairman. The model is used to determine system productivity and equipment utilization under different operational conditions, including random machine failures, random repairs, and limited repair capacity. The results are compared to previous study results for FMC system with sufficient repair capacity assigned to each machine. The results show that the model will be useful for design engineers and operational managers to analyze performance of manufacturing systems at the design or operational stages.

Keywords: flexible manufacturing, FMS, FMC, stochastic modeling, production rate, reliability, availability

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Authors: Sajeli A. Begum, Ameer Basha, Kirti Hira, Rukaiyya Khan

Abstract:

Cyclic dipeptides are simple diketopiperazine derivatives being investigated by several scientists for their biological effects which include anticancer, antimicrobial, haematological, anticonvulsant, immunomodulatory effect, etc. They are potentially active microbial metabolites having been synthesized too, for developing into drug candidates. Cultures of Pseudomonas species have earlier been reported to produce cyclic dipeptides, helping in quorum sensing signals and bacterial–host colonization phenomena during infections, causing cell anti-proliferation and immunosuppression. Fluorescing Pseudomonas species have been identified to secrete lipid derivatives, peptides, pyrroles, phenazines, indoles, aminoacids, pterines, pseudomonic acids and some antibiotics. In the present work, results of investigation on the cyclic dipeptide metabolites secreted by the culture broth of Pseudomonas species as potent pro-inflammatory cytokine inhibitors are discussed. The bacterial strain was isolated from the rhizospheric soil of groundnut crop and identified as Pseudomonas aeruginosa by 16S rDNA sequence (GenBank Accession No. KT625586). Culture broth of this strain was prepared by inoculating into King’s B broth and incubating at 30 ºC for 7 days. The ethyl acetate extract of culture broth was prepared and lyophilized to get a dry residue (EEPA). Lipopolysaccharide (LPS)-induced ELISA assay proved the inhibition of tumor necrosis factor-alpha (TNF-α) secretion in culture supernatant of RAW 264.7 cells by EEPA (IC50 38.8 μg/mL). The effect of oral administration of EEPA on plasma TNF-α level in rats was tested by ELISA kit. The LPS mediated plasma TNF-α level was reduced to 45% with 125 mg/kg dose of EEPA. Isolation of the chemical constituents of EEPA through column chromatography yielded ten cyclic dipeptides, which were characterized using nuclear magnetic resonance and mass spectroscopic techniques. These cyclic dipeptides are biosynthesized in microorganisms by multifunctional assembly of non-ribosomal peptide synthases and cyclic dipeptide synthase. Cyclo (Gly-L-Pro) was found to be more potentially (IC50 value 4.5 μg/mL) inhibiting TNF-α production followed by cyclo (trans-4-hydroxy-L-Pro-L-Phe) (IC50 value 14.2 μg/mL) and the effect was equal to that of standard immunosuppressant drug, prednisolone. Further, the effect was analyzed by determining mRNA expression of TNF-α in LPS-stimulated RAW 264.7 macrophages using quantitative real-time reverse transcription polymerase chain reaction. EEPA and isolated cyclic dipeptides demonstrated diminution of TNF-α mRNA expression levels in a dose-dependent manner under the tested conditions. Also, they were found to control the expression of other pro-inflammatory cytokines like IL-1β and IL-6, when tested through their mRNA expression levels in LPS-stimulated RAW 264.7 macrophages under LPS-stimulated conditions. In addition, significant inhibition effect was found on Nitric oxide production. Further all the compounds exhibited weak toxicity to LPS-induced RAW 264.7 cells. Thus the outcome of the study disclosed the effectiveness of EEPA and the isolated cyclic dipeptides in down-regulating key cytokines involved in pathophysiology of autoimmune diseases.In another study led by the investigators, microbial cyclic dipeptides were found to exhibit excellent antimicrobial effect against Fusarium moniliforme which is an important causative agent of Sorghum grain mold disease. Thus, cyclic dipeptides are emerging small molecular drug candidates for various autoimmune diseases.

Keywords: cyclic dipeptides, cytokines, Fusarium moniliforme, Pseudomonas, TNF-alpha

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