Search results for: protein interaction networks

Authors: Redouane Tlemsani, Redouane, Belkacem Kouninef, Abdelkader Benyettou

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In this paper, our system is a Markovien system which we can see it like a Dynamic Bayesian Networks. One of the major interests of these systems resides in the complete training of the models (topology and parameters) starting from training data. The Bayesian Networks are representing models of dubious knowledge on complex phenomena. They are a union between the theory of probability and the graph theory in order to give effective tools to represent a joined probability distribution on a set of random variables. The representation of knowledge bases on description, by graphs, relations of causality existing between the variables defining the field of study. The theory of Dynamic Bayesian Networks is a generalization of the Bayesians networks to the dynamic processes. Our objective amounts finding the better structure which represents the relationships (dependencies) between the variables of a dynamic bayesian network. In applications in pattern recognition, one will carry out the fixing of the structure which obliges us to admit some strong assumptions (for example independence between some variables).

Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition, networks

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Authors: Sodamade Abiodun, Adeboye Olubunmi Omolara

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Problems associated with protein malnutrition are still prevalent in third-world countries, leading to the constant search for plants that can serve as nutrients and medicinal purposes. Huckleberry is one of the plants that has been proven useful locally in the treatment of numerous ailments and diseases. A fresh sample of Huckleberry was collected from a vegetable garden situated near the Erelu dam of the Emmanuel Alayande College of Education campus, Oyo. The sample was authenticated at the forestry research institute of Nigeria (FRIN) Ibadan. The leaves of the plant were plucked and processed for leaf protein concentrates before proximate composition; mineral analysis phytochemical and antimicrobial properties of the leaf protein concentrates were determined using a standard method of analysis. The results of proximate constituents showed; moisture content; 9.89±0.051g/100g, Ash; 3.23±0.12g/100g, crude fat; 3.96±0.11g/100g and 61.27±0.56g/100g of Nitrogen free extractive results of the mineral analysis showed that the sample contains Mg; 0.081±0.00mg/100g, Ca; 42.30±0.05mg/100g, Na; 27.57±0.09mg/100g, K; 6.81±0.01mg/100g, P; 8.90±0.03mg/100g Fe; 0.51±0.00mg/100g, Zn; 0.021±0.00mg/100g, Cd; 0.04±0.04mg/100g, Pb; 0.002±0.00mg/100g, Cr; 0.041±0.00mg/100g while cadmium was not detected in the sample. The result of phytochemical analysis of leaf protein concentrates of the Huckleberry showed the presence of Alkaloid, Saponin, Flavonoid, Tanin, Coumarin, steroid, Terpenoid, cordial glycosides, Glycosides, Quinones, Anthocyanin, phytosterols, and phenols. Ethanolic extracts of the Huckleberry leaf protein concentrates showed that it contains bioactive compounds that are capable of eradicating some tested microorganisms; Staphylococcus aureus, Streptococcus pyogenes, Streptococcus faecalis, Pseudomonas aeruginosa, Klebisidlae pneumonia and Proteus merabilis. The results of the analysis of leaf protein concentrates of Huckleberry showed that the sample contains high nutrient and mineral constituents and phytochemical compounds that could make the sample useful for medicinal activities.

Keywords: huckleberry, mentha piperita, phytochemical, leaf protein concentrates, nutritional characteristics

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Authors: Márcia Aparecida Teixeira

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Sports, in particular football, boosts considerably the financial market of a certain locality, be it city or even a country. The financial transactions involving this medium stand out from other existing businesses, such as small industries. Strategically, social networks are inserted in this sporting environment, in order to promote and attract new fans of this modality. The present study analyzes the use of social networks in Sports Marketing with a focus on football. For the object of this study, it was chosen a specific club, the Club Atlético Mineiro, a Brazilian club of great national notoriety. The social networks on focus will be: Facebook, Twitter, and Instagram. It will be analyzed the content and frequency of the posts, reception of the target public in relation to the content made available and its feedback.

Keywords: social network, sport, strategy, marketing

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Authors: Sumi Manjipparambil Surendran, Subrata Majumdar

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Aim: The aim of the study is to find out if low PAPP-A (Pregnancy-Associated Plasma Protein A) levels in the first trimester are associated with adverse obstetric outcome. Methods: A retrospective study was carried out on 114 singleton pregnancies having undergone combined test screening. Results: There is statistically significant increased incidence of low birth weight infants in the low PAPP-A group. However, significant association was not found in the incidence of pre-eclampsia, miscarriage, and placental abruption. Conclusion: Low PAPP-A in the first trimester is associated with fetal growth restriction. Recommendation: Women with low PAPP-A levels in first trimester pregnancy screening require consultant-led care and serial growth scans.

Keywords: pregnancy, pregnancy-associated plasma protein A, PAPP-A, fetal growth restriction, trimester

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Authors: Fathiah Mohamed Zuki, Robert George Edyvean

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Electrostatic interaction energy (∆EEDL) is a part of the Extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory, which, together with van der Waals (∆EVDW) and acid base (∆EAB) interaction energies, has been extensively used to investigate the initial adhesion of bacteria to surfaces. Electrostatic or electrical double layer interaction energy is considerably affected by surface potential, however it cannot be determined experimentally and is usually replaced by zeta (ζ) potential via electrophoretic mobility. This paper focuses on the effect of ionic concentration as a function of pH and the effect of mineral grain size on ζ potential. It was found that both ionic strength and mineral grain size play a major role in determining the value of ζ potential for the adhesion of P. putida to hematite and quartz surfaces. Higher ζ potential values lead to higher electrostatic interaction energies and eventually to higher total XDLVO interaction energy resulting in bacterial repulsion.

Keywords: XDLVO, electrostatic interaction energy, zeta potential, P. putida, mineral

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Authors: Ziyue Zeng

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Bacteriophages are viruses which infect bacteria specifically. Over the past decades, phage λ has been extensively studied, especially its interaction with the Escherichia coli LamB (EcLamB) protein receptor. Nonetheless, despite the enormous numbers and near-ubiquity of environmental phages, aside from phage λ, there is a paucity of information on other phages which target EcLamB as a receptor. In this study, to answer the question of whether there are other EcLamB-targeting phages in the natural environment, a simple and convenient method was developed and used for isolating environmental phages which target a particular surface structure of a particular bacterium; in this case, the EcLamB outer membrane protein. From the enrichments with the engineered bacterial hosts, a collection of EcLamB-targeting phages (ΦZZ phages) were easily isolated. Intriguingly, unlike phage λ, an obligate EcLamB-dependent phage in the Siphoviridae family, the newly isolated ΦZZ phages alternatively recognised EcLamB or E. coli OmpC (EcOmpC) as a receptor when infecting E. coli. Furthermore, ΦZZ phages were suggested to represent new species in the Tequatrovirus genus in the Myoviridae family, based on phage morphology and genomic sequences. Most phages are thought to have a narrow host range due to their exquisite specificity in receptor recognition. With the ability to optionally recognise two receptors, ΦZZ phages were considered relatively promiscuous. Via the heterologous expression of EcLamB on the bacterial cell surface, the host range of ΦZZ phages was further extended to three different enterobacterial genera. Besides, an interesting selection of evolved phage mutants with a broader host range was isolated, and the key mutations involved in their evolution to adapt to new hosts were investigated by genomic analysis. Finally, and importantly, two ΦZZ phages were found to be putative generalised transducers, which could be exploited as tools for DNA manipulations.

Keywords: environmental microbiology, phage, microbe-host interactions, microbial ecology

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Authors: Somayeh Sadat Hashemi Kamangar, Fatemeh Bakouie, Shahriar Gharibzadeh

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In this study, we target to exploit Maximum Spanning Trees (MST) of children's semantic networks to investigate their language development. To do so, we examine the graph-theoretic properties of word-embedding networks. The networks are made of words children learn prior to the age of 30 months as the nodes and the links which are built from the cosine vector similarity of words normatively acquired by children prior to two and a half years of age. These networks are weighted graphs and the strength of each link is determined by the numerical similarities of the two words (nodes) on the sides of the link. To avoid changing the weighted networks to the binaries by setting a threshold, constructing MSTs might present a solution. MST is a unique sub-graph that connects all the nodes in such a way that the sum of all the link weights is maximized without forming cycles. MSTs as the backbone of the semantic networks are suitable to examine developmental changes in semantic network topology in children. From these trees, several parameters were calculated to characterize the developmental change in network organization. We showed that MSTs provides an elegant method sensitive to capture subtle developmental changes in semantic network organization.

Keywords: maximum spanning trees, word-embedding, semantic networks, language development

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Authors: Natesan Balasubramanian, Palpandi Pounpandi, Venkatraman Thamil Priya, Vellasamy Shanmugaiah, Karubbiah Balakrishnan, Mandayam Anandam Thirunarayan

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Streptococcus agalactiae is commonly known as Group B Streptococcus (GBS) and it is the most common cause of life-threatening bacterial infection. GBS first considered as a veterinary pathogen causing mastitis in cattle later becomes a human pathogen for severe neonatal infections. In this present study, a total of 20 new clinical isolates of S. agalactiae were collected from male (6) and female patient (14) with different age group. The isolates were from Urinary tract infection (UTI), blood, pus and eye ulcer. All the 20 S. agalactiae isolates has clear hemolysis properties on blood agar medium and were identified by serogrouping and MALTI-TOF-MS analysis. Antibiotic susceptibility/resistance test was performed for 20 S. agalactiae isolates, further phenotypic resistance pattern was observed for tetracycline, vancomycin, ampicillin and penicillin. Genotypically we found two antibiotic resistance genes such as Betalactem antibiotic resistance gene (Tem) (70%) and tetracycline resistance gene Tet(O) 15% in our isolates. Six virulence factors encoding genes were performed by PCR in twenty GBS isolates, cfb gene (100%), followed by, cylE(90.47%), lmp(85.7%), bca(71.42%), rib (38%) and low frequency in bac gene (4.76%) were determined. Most of the S. agalactiae isolates produced strong biofilm in the polystyrene surface (hydrophobic), and low-level biofilm formation was found in glass tube (hydrophilic) surface. lytR is secreted protein and localized in bacterial cell wall, extra cellular membrane, and cytoplasm. In silico docking studies were performed for lytR protein with four antibiofilm compounds, including a peptide (PR39) with the docking study showed peptide has strong interaction followed by ellagic acid and interaction length is 2.95, 2.97 and 2.95 A°. In ligand EGCGO10 and O11 two atoms intract with lytR (Leu271), with binding bond affinity length is 3.24 and 3.14. The aminoacid Leu 271 is act as an impartant aminoacid, since ellagic acid and EGCG interact with same aminoacid.

Keywords: antibiotics, biofilms, clinical isolates, S. agalactiae, virulence

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Authors: Hongquan Zhang

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Inspired by endogenous protein motors, researchers have constructed various synthetic DNA motors based on the specificity and predictability of Watson-Crick base pairing. However, the application of DNA motors to signal amplification and biosensing is limited because of low mobility and difficulty in real-time monitoring of the walking process. The objective of our work was to construct a new type of DNA motor termed target-triggered DNA motors that can walk for hundreds of steps in response to a single target binding event. To improve the mobility and processivity of DNA motors, we used gold nanoparticles (AuNPs) as scaffolds to build high-density, three-dimensional tracks. Hundreds of track strands are conjugated to a single AuNP. To enable DNA motors to respond to specific protein and nucleic acid targets, we adapted the binding-induced DNA assembly into the design of the target-triggered DNA motors. In response to the binding of specific target molecules, DNA motors are activated to autonomously walk along AuNP, which is powered by a nicking endonuclease or DNAzyme-catalyzed cleavage of track strands. Each moving step restores the fluorescence of a dye molecule, enabling monitoring of the operation of DNA motors in real time. The motors can translate a single binding event into the generation of hundreds of oligonucleotides from a single nanoparticle. The motors have been applied to amplify the detection of proteins and nucleic acids in test tubes and live cells. The motors were able to detect low pM concentrations of specific protein and nucleic acid targets in homogeneous solutions without the need for separation. Target-triggered DNA motors are significant for broadening applications of DNA motors to molecular sensing, cell imagining, molecular interaction monitoring, and controlled delivery and release of therapeutics.

Keywords: biosensing, DNA motors, gold nanoparticles, signal amplification

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Authors: Sekkal Nawel

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The Web of Things (WoT), integration of smart technologies from the Internet or network to Web architecture or application, is becoming more complex, larger, and dynamic. The WoT is associated with various elements such as sensors, devices, networks, protocols, data, functionalities, and architectures to perform services for stakeholders. These services operate in the context of the interaction of stakeholders and the WoT elements. Such context is becoming a key information source from which data are of various nature and uncertain, thus leading to complex situations. In this paper, we take interest in the development of intelligent Web services. The key ingredients of this “intelligent” notion are the context diversity, the necessity of a semantic representation to manage complex situations and the capacity to reason with uncertain data. In this perspective, we introduce a multi-layered architecture based on a generic intelligent Web service model dealing with various contexts, which proactively predict future situations and reactively respond to real-time situations in order to support decision-making. For semantic context data representation, we use PR-OWL, which is a probabilistic ontology based on Multi-Entity Bayesian Networks (MEBN). PR-OWL is flexible enough to represent complex, dynamic, and uncertain contexts, the key requirements of the development for the intelligent Web services. A case study was carried out using the proposed architecture for intelligent plant watering to show the role of proactive and reactive contextual reasoning in terms of WoT.

Keywords: smart web service, the web of things, context reasoning, proactive, reactive, multi-entity bayesian networks, PR-OWL

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Authors: Vahid Bairami Rad

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Wireless communications offer organizations and users many benefits such as portability and flexibility, increased productivity, and lower installation costs. Wireless networks serve as the transport mechanism between devices and among devices and the traditional wired networks (enterprise networks and the internet). Wireless networks are many and diverse but are frequently categorized into three groups based on their coverage range: WWAN, WLAN, and WPAN. WWAN, representing wireless wide area networks, includes wide coverage area technologies such as 2G cellular, Cellular Digital Packet Data (CDPD), Global System for Mobile Communications (GSM), and Mobitex. WLAN, representing wireless local area networks, includes 802.11, Hyper lan, and several others. WPAN, represents wireless personal area network technologies such as Bluetooth and Infrared. The security services are provided largely by the WEP (Wired Equivalent Privacy) protocol to protect link-level data during wireless transmission between clients and access points. That is, WEP does not provide end-to-end security but only for the wireless portion of the connection.

Keywords: wireless lan, wired equivalent privacy, wireless network security, wlan security

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Authors: Maedeh Rahimnejad, Bahman Vahidi, Bahman Ebrahimi Hoseinzadeh, Fatemeh Yazdian, Puria Motamed Fath, Roghieh Jamjah

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Introduction: The intensive labor and high cost of developing new vehicles for controlled drug delivery highlights the need for a change in their discovery process. Computational models can be used to accelerate experimental steps and control the high cost of experiments. Methods: In this work, to better understand the interaction of anti-cancer drug and the nanocarrier with the cell membrane, we have done molecular dynamics simulation using NAMD. We have chosen paclitaxel for the drug molecule and dipalmitoylphosphatidylcholine (DPPC) as a natural phospholipid nanocarrier. Results: Next, center of mass (COM) between molecules and the van der Waals interaction energy close to the cell membrane has been analyzed. Furthermore, the simulation results of the paclitaxel interaction with the cell membrane and the interaction of DPPC as a nanocarrier loaded by the drug with the cell membrane have been compared. Discussion: Analysis by molecular dynamics (MD) showed that not only the energy between the nanocarrier and the cell membrane is low, but also the center of mass amount decreases in the nanocarrier and the cell membrane system during the interaction; therefore they show significantly better interaction in comparison to the individual drug with the cell membrane.

Keywords: anti-cancer drug, center of mass, interaction energy, molecular dynamics simulation, nanocarrier

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Authors: Gyaltsen Dakpa, K. J. Senthil Kumar, Nai-Wen Tsao, Sheng-Yang Wang

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Context: Coronavirus disease 2019 (COVID-19) is a severe respiratory illness caused by the SARS-CoV-2 virus. One of the hallmarks of COVID-19 is a change in metabolism, which can lead to increased severity and mortality. The mechanism of SARS-CoV-2-mediated perturbations of metabolic pathways has yet to be fully understood. Research Aim: This study aimed to investigate the metabolic alteration caused by SARS-CoV-2 spike protein in Phorbol 12-myristate 13-acetate (PMA)-induced human monocytes (THP-1) and to examine the regulatory effect of natural compounds like Antcins A on SARS-CoV-2 spike protein-induced metabolic alteration. Methodology: The study used a combination of proton nuclear magnetic resonance (1H-NMR) and MetaboAnalyst 5.0 software. THP-1 cells were treated with SARS-CoV-2 spike protein or control, and the metabolomic profiles of the cells were compared. Antcin A was also added to the cells to assess its regulatory effect on SARS-CoV-2 spike protein-induced metabolic alteration. Findings: The study results showed that treatment with SARS-CoV-2 spike protein significantly altered the metabolomic profiles of THP-1 cells. Eight metabolites, including glycerol-phosphocholine, glycine, canadine, sarcosine, phosphoenolpyruvic acid, glutamine, glutamate, and N, N-dimethylglycine, were significantly different between control and spike-protein treatment groups. Antcin A significantly reversed the changes in these metabolites. In addition, treatment with antacid A significantly inhibited SARS-CoV-2 spike protein-mediated up-regulation of TLR-4 and ACE2 receptors. Theoretical Importance The findings of this study suggest that SARS-CoV-2 spike protein can cause significant metabolic alterations in THP-1 cells. Antcin A, a natural compound, has the potential to reverse these metabolic alterations and may be a potential candidate for developing preventive or therapeutic agents for COVID-19. Data Collection: The data for this study was collected from THP-1 cells that were treated with SARS-CoV-2 spike protein or a control. The metabolomic profiles of the cells were then compared using 1H-NMR and MetaboAnalyst 5.0 software. Analysis Procedures: The metabolomic profiles of the THP-1 cells were analyzed using 1H-NMR and MetaboAnalyst 5.0 software. The software was used to identify and quantify the cells' metabolites and compare the control and spike-protein treatment groups. Questions Addressed: The question addressed by this study was whether SARS-CoV-2 spike protein could cause metabolic alterations in THP-1 cells and whether Antcin A can reverse these alterations. Conclusion: The findings of this study suggest that SARS-CoV-2 spike protein can cause significant metabolic alterations in THP-1 cells. Antcin A, a natural compound, has the potential to reverse these metabolic alterations and may be a potential candidate for developing preventive or therapeutic agents for COVID-19.

Keywords: SARS-CoV-2-spike, ¹H-NMR, metabolomics, antcin-A, taiwanofungus camphoratus

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Authors: Harika Atmaca, Emir Bozkurt, Latife Merve Oktay, Selim Uzunoglu, Ruchan Uslu, Burçak Karaca

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Microarrays have been developed for highly parallel enzyme-linked immunosorbent assay (ELISA) applications. The most common protein arrays are produced by using multiple monoclonal antibodies, since they are robust molecules which can be easily handled and immobilized by standard procedures without loss of activity. Protein expression profiling with protein array technology allows simultaneous analysis of the protein expression pattern of a large number of proteins. Trabectedin, a tetrahydroisoquinoline alkaloid derived from a Caribbean tunicate, Ecteinascidia turbinata, has been shown to have antitumor effects. Here, we used a novel proteomic approach to explore the mechanism of action of trabectedin in prostate cancer cell line PC-3 by apoptosis antibody microarray. XTT cell proliferation kit and Cell Death Detection Elisa Plus Kit (Roche) was used for measuring cytotoxicity and apoptosis. Human Apoptosis Protein Array (R&D Systems) which consists of 35 apoptosis related proteins was used to assess the omic protein expression pattern. Trabectedin induced cytotoxicity and apoptosis in prostate cancer cells in a time and concentration-dependent manner. The expression levels of the death receptor pathway molecules, TRAIL-R1/DR4, TRAIL R2/DR5, TNF R1/TNFRSF1A, FADD were significantly increased by 4.0-, 21.0-, 4.20- and 11.5-fold by trabectedin treatment in PC-3 cells. Moreover, mitochondrial pathway related pro-apoptotic proteins Bax, Bad, Cytochrome c, and Cleaved Caspase-3 expressions were induced by 2.68-, 2.07-, 2.8-, and 4.5-fold and the expression levels of anti-apoptotic proteins Bcl-2 and Bcl-XL were reduced by 3.5- and 5.2-fold in PC-3 cells. Proteomic (antibody microarray) analysis suggests that the mechanism of action of trabectedin may be exerted via the induction of both intrinsic and extrinsic apoptotic pathways. The antibody microarray platform can be utilised to explore the molecular mechanism of action of novel anticancer agents.

Keywords: trabectedin, prostate cancer, omic protein expression profile, apoptosis

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Authors: M. Kouyate, M. Sangare, S. Samake, S. Keita, H. G. Kim, D. H. Geschwind

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Background & Objectives: Human genetic studies can be expensive, even unaffordable, in developing countries, partly due to the sequencing costs. Our aim is to pilot the use of bioinformatics tools to guide scientifically valid, locally relevant, and economically sound autism genetic research in Mali. Methods: The following databases, NCBI, HGMD, and LSDB, were used to identify hot point mutations. Phenotype, transmission pattern, theoretical protein expression in the brain, the impact of the mutation on the 3D structure of the protein) were used to prioritize selected autism genes. We used the protein database, Modeller, and clustal W. Results: We found Mef2c (Gly27Ala/Leu38Gln), Pten (Thr131IIle), Prodh (Leu289Met), Nme1 (Ser120Gly), and Dhcr7 (Pro227Thr/Glu224Lys). These mutations were associated with endonucleases BseRI, NspI, PfrJS2IV, BspGI, BsaBI, and SpoDI, respectively. Gly27Ala/Leu38Gln mutations impacted the 3D structure of the Mef2c protein. Mef2c protein sequences across species showed a high percentage of similarity with a highly conserved MADS domain. Discussion: Mef2c, Pten, Prodh, Nme1, and Dhcr 7 gene mutation frequencies in the Malian population will be very informative. PCR coupled with restriction enzyme digestion can be used to screen the targeted gene mutations. Sanger sequencing will be used for confirmation only. This will cut down considerably the sequencing cost for gene-to-gene mutation screening. The knowledge of the 3D structure and potential impact of the mutations on Mef2c protein informed the protein family and altered function (ex. Leu38Gln). Conclusion & Future Work: Bio-informatics will positively impact autism research in Mali. Our approach can be applied to another neuropsychiatric disorder.

Keywords: bioinformatics, endonucleases, autism, Sanger sequencing, point mutations

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Authors: Pooja Kumari, Anandkumar Tengli

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Aurora kinase enzyme, a protein on overexpression, leads to metastasis and is extremely important for women’s health in terms of prevention or treatment. While creating a targeted technique, the aim of the work is to design purine molecules that inhibit in aurora kinase enzyme and helps to suppress breast cancer. Purine molecules attached to an amino acid in DNA block protein synthesis or halt the replication and metastasis caused by the aurora kinase enzyme. Various protein related to the overexpression of aurora protein was docked with purine molecule using Biovia Drug Discovery, the perpetual software. Various parameters like X-ray crystallographic structure, presence of ligand, Ramachandran plot, resolution, etc., were taken into consideration for selecting the target protein. A higher negative binding scored molecule has been taken for simulation studies. According to the available research and computational analyses, purine compounds may be powerful enough to demonstrate a greater affinity for the aurora target. Despite being clinically effective now, purines were originally meant to fight breast cancer by inhibiting the aurora kinase enzyme. In in-silico studies, it is observed that purine compounds have a moderate to high potency compared to other molecules, and our research into the literature revealed that purine molecules have a lower risk of side effects. The research involves the design, synthesis, and identification of active purine molecules against breast cancer. Purines are structurally similar to the normal metabolites of adenine and guanine; hence interfere/compete with protein synthesis and suppress the abnormal proliferation of cells/tissues. As a result, purine target metastasis cells and stop the growth of kinase; purine derivatives bind with DNA and aurora protein which may stop the growth of protein or inhibits replication and stop metastasis of overexpressed aurora kinase enzyme.

Keywords: aurora kinases, in silico studies, medicinal chemistry, combination therapies, chronic cancer, clinical translation

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Authors: Zi-Han Li, Lu Fang, Liang Wu, Dong-Yuan Chang, Manyuan Dong, Liang Ji, Qi Zhang, Ming-Hui Zhao, Sydney C.W. Tang, Lemin Zheng, Min Chen

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Uncoupling of mitochondrial respiration by chemical uncouplers has proven effective in ameliorating obesity, insulin resistance, and hyperglycemia, which were risk factors for diabetic nephropathy (DN). Recently, it was found that annexin A1(ANXA1) could improve mitochondrial function to mitigate DN progression. However, the underlying mechanism is not fully clear yet. Here, it was identified that uncoupling protein 1 (UCP1), an inner membrane protein of mitochondria, as a key to mitochondrial homeostasis improved by ANXA1. Specifically, ANXA1 attenuated mitochondrial dysfunction via appropriately upregulating UCP1 by stabilizing its transcription factor GATA binding protein 3 (GATA3) through combining with thioredoxin. Moreover, specific overexpression of UCP1 in renal cortex rescued renal injuries in diabetic Anxa1-KO mice. UCP1 deletion aggravated renal injuries in HFD/STZ-induced diabetic mice. Mechanistically, UCP1 reduced mitochondrial fission through the aristaless-related homeobox (ARX)/cardiolipin synthase 1 (CRLS1) pathway. Therapeutically, CL316243, a UCP1 agonist, could attenuate established DN in db/db mice. This work established a novel principle to harness the power of uncouplers for the treatment of DN.

Keywords: diabetic nephropathy, uncoupling protein 1, mitochondrial homeostasis, cardiolipin metabolism

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Authors: Jai Prakash Prasad, Suresh Chandra Mohan

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Modern wireless sensor networks (WSN) consist of small size, low cost devices which are networked through tight wireless communications. WSN fundamentally offers cooperation, coordination among sensor networks. Potential applications of wireless sensor networks are in healthcare, natural disaster prediction, data security, environmental monitoring, home appliances, entertainment etc. The design, development and deployment of WSN based on application requirements. The WSN design performance is optimized to improve network lifetime. The sensor node resources constrain such as energy and bandwidth imposes the limitation on efficient resource utilization and sensor node management. The proposed N-Tier GRID routing protocol focuses on the design of energy efficient large scale wireless sensor network for improved performance than the existing protocol.

Keywords: energy efficient, network lifetime, sensor networks, wireless communication

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Authors: Esmail Sadipour

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The use of social networks is increasing day by day in all societies. The purpose of this research was to know the relationship between the use of social networks (Instagram, WhatsApp, and Telegram) with executive functions and academic performance in first-year female high school students. This research was applied in terms of purpose, quantitative in terms of data type, and correlational in terms of technique. The population of this research consisted of all female high school students in the first year of district 2 of Tehran. Using Green's formula, the sample size of 150 people was determined and selected by cluster random method. In this way, from all 17 high schools in district 2 of Tehran, 5 high schools were selected by a simple random method and then one class was selected from each high school, and a total of 155 students were selected. To measure the use of social networks, a researcher-made questionnaire was used, the Barclay test (2012) was used for executive functions, and last semester's GPA was used for academic performance. Pearson's correlation coefficient and multivariate regression were used to analyze the data. The results showed that there is a negative relationship between the amount of use of social networks and self-control, self-motivation and time self-management. In other words, the more the use of social networks, the fewer executive functions of students, self-control, self-motivation, and self-management of their time. Also, with the increase in the use of social networks, the academic performance of students has decreased.

Keywords: social networks, executive function, academic performance, working memory

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Authors: Lyamine Guezouli, Kamel Barka, Zineb Seghir

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Wireless sensor and actor networks (WSANs) present a research challenge for different practice areas. Researchers are trying to optimize the use of such networks through their research work. This optimization is done on certain criteria, such as improving energy efficiency, exploiting node heterogeneity, self-adaptability and self-configuration. In this article, we present our proposal for BIFSA (Biologically-Inspired Framework for Wireless Sensor and Actor networks). Indeed, BIFSA is a middleware that addresses the key issues of wireless sensor and actor networks. BIFSA consists of two types of agents: sensor agents (SA) that operate at the sensor level to collect and transport data to actors and actor agents (AA) that operate at the actor level to transport data to base stations. Once the sensor agent arrives at the actor, it becomes an actor agent, which can exploit the resources of the actors and vice versa. BIFSA allows agents to evolve their genetic structures and adapt to the current network conditions. The simulation results show that BIFSA allows the agents to make better use of all the resources available in each type of node, which improves the performance of the network.

Keywords: wireless sensor and actor networks, self-management, genetic algorithm, agent.

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Authors: K. A. Laptinskiy, S. A. Burikov, A. M. Vervald, S. A. Dolenko, T. A. Dolenko

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The article presents the results of the application of artificial neural networks to separate the fluorescent contribution of nanodiamonds used as biomarkers, adsorbents and carriers of drugs in biomedicine, from a fluorescent background of own biological fluorophores. The principal possibility of solving this problem is shown. Use of neural network architecture let to detect fluorescence of nanodiamonds against the background autofluorescence of egg white with high accuracy - better than 3 ug/ml.

Keywords: artificial neural networks, fluorescence, data aggregation, biomarkers

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Authors: Saed Khawaldeh, Mohamed Elsharnouby, Alaa Eddin Alchalabi, Usama Pervaiz, Tajwar Aleef, Vu Hoang Minh

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Taxonomic classification has a wide-range of applications such as finding out more about the evolutionary history of organisms that can be done by making a comparison between species living now and species that lived in the past. This comparison can be made using different kinds of extracted species’ data which include DNA sequences. Compared to the estimated number of the organisms that nature harbours, humanity does not have a thorough comprehension of which specific species they all belong to, in spite of the significant development of science and scientific knowledge over many years. One of the methods that can be applied to extract information out of the study of organisms in this regard is to use the DNA sequence of a living organism as a marker, thus making it available to classify it into a taxonomy. The classification of living organisms can be done in many machine learning techniques including Neural Networks (NNs). In this study, DNA sequences classification is performed using Convolutional Neural Networks (CNNs) which is a special type of NNs.

Keywords: deep networks, convolutional neural networks, taxonomic classification, DNA sequences classification

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Authors: Ishrat Jahan Saifi, Sheelu Shafiq Siddiqi, M. R. Ajmal

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Glycation of protein is very important as well as a harmful process, which may lead to develop DM in human body. Human Serum Albumin (HSA) is the most abundant protein in blood and it is highly prone to glycation by the reducing sugars. 2-¬deoxy d-¬Ribose (dRib) is a highly reactive reducing sugar which is produced in cells as a product of the enzyme thymidine phosphorylase. It is generated during the degradation of DNA in human body. It may cause glycation in HSA rapidly and is involved in the development of DM. In present study, we did in¬vitro glycation of HSA with different concentrations of 2-¬deoxy d-¬ribose and found that dRib glycated HSA rapidly within 4h incubation at 37◦C. UV¬ Spectroscopy, Fluorescence spectroscopy, Fourier transform infrared spectroscopy (FTIR) and Circular Dichroism (CD) technique have been done to determine the structural changes in HSA upon glycation. Results of this study suggested that dRib is the potential glycating agent and it causes alteration in protein structure and biophysical properties which may lead to development and progression of Diabetes mellitus.

Keywords: 2-deoxy D-ribose, human serum albumin, glycation, diabetes mellitus

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Authors: Jafar Ahmadi, Zhohreh Asiaban, Sedigheh Fabriki Ourang

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Brassinosteroids (BRs) regulate cell elongation, vascular differentiation, senescence and stress responses. BRs signal through the BES1/BZR1 family of transcription factors, which regulate hundreds of target genes involved in this pathway. In this research a comprehensive genome-wide analysis was carried out in BES1/BZR1 gene family in Arabidopsis thaliana, Cucumis sativus, Vitis vinifera, Glycin max, and Brachypodium distachyon. Specifications of the desired sequences, dot plot and hydropathy plot were analyzed in the protein and genome sequences of five plant species. The maximum amino acid length was attributed to protein sequence Brdic3g with 374aa and the minimum amino acid length was attributed to protein sequence Gm7g with 163aa. The maximum Instability index was attributed to protein sequence AT1G19350 equal with 79.99 and the minimum Instability index was attributed to protein sequence Gm5g equal with 33.22. Aliphatic index of these protein sequences ranged from 47.82 to 78.79 in Arabidopsis thaliana, 49.91 to 57.50 in Vitis vinifera, 55.09 to 82.43 in Glycin max, 54.09 to 54.28 in Brachypodium distachyon 55.36 to 56.83 in Cucumis sativus. Overall, data obtained from our investigation contributes a better understanding of the complexity of the BES1/BZR1 gene family and provides the first step towards directing future experimental designs to perform systematic analysis of the functions of the BES1/BZR1 gene family.

Keywords: BES1/BZR1, brassinosteroids, phylogenetic analysis, transcription factor

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Authors: Samuel Nii Tackie, Oyebade K. Oyedotun, Ebenezer O. Olaniyi, Adnan Khashman

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Artificial neural networks have been used in different fields of artificial intelligence, and more specifically in machine learning. Although, other machine learning options are feasible in most situations, but the ease with which neural networks lend themselves to different problems which include pattern recognition, image compression, classification, computer vision, regression etc. has earned it a remarkable place in the machine learning field. This research exploits neural networks as a data mining tool in predicting the number of times a student repeats a course, considering some attributes relating to the course itself, the teacher, and the particular student. Neural networks were used in this work to map the relationship between some attributes related to students’ course assessment and the number of times a student will possibly repeat a course before he passes. It is the hope that the possibility to predict students’ performance from such complex relationships can help facilitate the fine-tuning of academic systems and policies implemented in learning environments. To validate the power of neural networks in data mining, Turkish students’ performance database has been used; feedforward and radial basis function networks were trained for this task; and the performances obtained from these networks evaluated in consideration of achieved recognition rates and training time.

Keywords: artificial neural network, data mining, classification, students’ evaluation

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Authors: Daidai Shen, Jean Claude Thill, Wenjia Zhang

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This study explores the dynamics of synergy and complementarity within city networks, specifically focusing on the headquarters-subsidiary relations of firms. We begin by defining these two types of networks and establishing their pivotal roles in shaping city network structures. Utilizing the mesoscale analytic approach of weighted stochastic block modeling, we discern relational patterns between city pairs and determine connection strengths through statistical inference. Furthermore, we introduce a community detection approach to uncover the underlying structure of these networks using advanced statistical methods. Our analysis, based on comprehensive network data up to 2017, reveals the coexistence of both complementarity and synergy networks within China’s technology-intensive manufacturing cities. Notably, firms in technology hardware and office & computing machinery predominantly contribute to the complementarity city networks. In contrast, a distinct synergy city network, underpinned by the cities of Suzhou and Dongguan, emerges amidst the expansive complementarity structures in technology hardware and equipment. These findings provide new insights into the relational dynamics and structural configurations of city networks in the context of technology-intensive manufacturing, highlighting the nuanced interplay between synergy and complementarity.

Keywords: city system, complementarity, synergy network, higher-order network

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Authors: Javier Perez-Vaquero, Katryn Junker, Volker Lammers, Petra Foerst

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There is increasing importance to accelerate the transition to sustainable food systems by including environmentally friendly technologies. Our work focuses on protein enrichment and fractionation of agricultural side streams by dry triboelectrostatic separation technology. Materials are fed in particulate form into a system dispersed in a highly turbulent gas stream, whereby the high collision rate of particles against surfaces and other particles greatly enhances the electrostatic charge build-up over the particle surface. A subsequent step takes the charged particles to a delimited zone in the system where there is a highly uniform, intense electric field applied. Because the charge polarity acquired by a particle is influenced by its chemical composition, morphology, and structure, the protein-rich and fiber-rich particles of the starting material get opposite charge polarities, thus following different paths as they move through the region where the electric field is present. The output is two material fractions, which differ in their respective protein content. One is a fiber-rich, low-protein fraction, while the other is a high-protein, low-fiber composition. Prior to testing, materials undergo a milling process, and some samples are stored under controlled humidity conditions. In this way, the influence of both particle size and humidity content was established. We used two oilseed meals: lupine and rapeseed. In addition to a lab-scale separator to perform the experiments, the triboelectric separation process could be successfully scaled up to a mid-scale belt separator, increasing the mass feed from g/sec to kg/hour. The triboelectrostatic separation technology opens a huge potential for the exploitation of so far underutilized alternative protein sources. Agricultural side-streams from cereal and oil production, which are generated in high volumes by the industries, can further be valorized by this process.

Keywords: bench-scale processing, dry separation, protein-enrichment, triboelectrostatic separation

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Authors: Natalia Moreno-Castellanos, Amaia Rodriguez, Gema Frühbeck

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Introduction: In adipocytes, the cytoskeleton undergoes important expression and distribution in adipocytes rearrangements during adipogenesis and in obesity. Indeed, a role for these proteins in the regulation of adipocyte differentiation and response to insulin has been demonstrated. Recently, septins have been considered as new components of the cytoskeletal network that interact with other cytoskeletal elements (actin and tubulin) profoundly modifying their dynamics. However, these proteins have not been characterized as yet in adipose tissue. In this work, were examined the cellular, molecular and functional features of a member of this family, septin 11 (SEPT11), in adipocytes and evaluated the impact of obesity on the expression of this protein in human adipose tissue. Methods: Adipose gene and protein expression levels of SEPT11 were analysed in human samples. SEPT11 distribution was evaluated by immunocytochemistry, electronic microscopy, and subcellular fractionation techniques. GST-pull down, immunoprecipitation and a Yeast-Two Hybrid (Y2H) screening were used to identify the SEPT11 interactome. Gene silencing was employed to assess the role of SEPT11 in the regulation of insulin signaling and lipid metabolism in adipocytes. Results: SEPT11 is expressed in human adipocytes, and its levels increased in both omental and subcutaneous adipose tissue in obesity, with SEPT11 mRNA content positively correlating with parameters of insulin resistance in subcutaneous fat. In non-stimulated adipocytes, SEPT11 immunoreactivity showed a ring-like distribution at the cell surface and associated to caveolae. Biochemical analyses showed that SEPT11 interacted with the main component of caveolae, caveolin-1 (CAV1) as well as with the fatty acid-binding protein, FABP5. Notably, the three proteins redistributed and co-localized at the surface of lipid droplets upon exposure of adipocytes to oleate. In this line, SEPT11 silencing in 3T3-L1 adipocytes impaired insulin signaling and decreased insulin-induced lipogenesis. Conclusions: Those findings demonstrate that SEPT11 is a novel component of the adipocyte cytoskeleton that plays an important role in the regulation of lipid traffic, metabolism and can thus represent a potential biomarker of insulin resistance in obesity in adipocytes through its interaction with both CAV1 and FABP5.

Keywords: caveolae, lipid metabolism, obesity, septins

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Authors: John N. Idenyi, Hadimundeen Abdallah, Abigeal D. Adeyemi, Jonathan C. Eya

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Gut microbiomes play a significant role in the growth, metabolism, and health of fish. However, we know very little about the interactive effects of variations in dietary composition and temperature on rainbow trout gut microbiota. Exactly 288 rainbow trout weighing 45.6g ± 0.05 (average ± SD) were fed four isocaloric, isolipidic, and isonitrogenous diets comprising 40% crude protein and 20% crude lipid and formulated as 100 % animal-based protein (AP) and a blend of 50 fish oil (FO)/50 camelina oil (CO), 100 % AP and100 % CO, 100 % plant-based protein (PP) and a blend of 50FO/50CO or 100 % PP and 100 % CO in 14 or 18°C for 150 days. Gut content was analyzed using 16S rRNA gene and shotgun sequencing. The most abundant phyla identified regardless of diet were Tenericutes, Firmicutes, Proteobacteria, Spirochaetes, Bacteroidetes, and Actinobacteria, while Aeromonadaceae and Enterobacteriaceae were dominant families in 18°C. Moreover, gut microbes were dominated by genes relating to an amino acid, carbohydrate, fat, and energy metabolisms and influenced by temperature. The shared functional profiles for all the diets suggest that plant protein sources in combination with CO could be as good as the fish meal with 50/50 FO & CO in rainbow trout farming.

Keywords: aquafeed, aquaculture, microbiome, rainbow trout

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Authors: Iuliia Zarubiieva, Joyun Tseng, Vishwesh Kulkarni

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Recent researches has focused on nucleic acids as a substrate for designing biomolecular circuits for in situ monitoring and control. A common approach is to express them by a set of idealised abstract chemical reaction networks (ACRNs). Here, we present new results on how abstract chemical reactions, viz., catalysis, annihilation and degradation, can be used to implement circuit that accurately computes logarithm function using the method of Arithmetic-Geometric Mean (AGM), which has not been previously used in conjunction with ACRNs.

Keywords: chemical reaction networks, ratio computation, stability, robustness

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