Search results for: protein stability prediction

Authors: Safia Hocine, Zina Benouaret, Djamil A¨ıssani

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In this paper, we study the performance of the strong stability method of the univariate classical risk model. We interest to the stability bounds established using two approaches. The first based on the strong stability method developed for a general Markov chains. The second approach based on the regenerative processes theory . By adopting an algorithmic procedure, we study the performance of the stability method in the case of exponential distribution claim amounts. After presenting numerically and graphically the stability bounds, an interpretation and comparison of the results have been done.

Keywords: Marcov chain, regenerative process, risk model, ruin probability, strong stability

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Authors: Jeonghwan Jeon

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With the advent of IPTV in the fierce competition with existing broadcasting system, it is emerged as an important issue to predict how much the adoption of IPTV service will be. This paper aims to suggest a prediction model for adopting IPTV using classification and Ranking Belief Simplex (CaRBS). A simplex plot method of representing data allows a clear visual representation to the degree of interaction of the support from the variables to the prediction of the objects. CaRBS is applied to the survey data on the IPTV adoption.

Keywords: prediction, adoption, IPTV, CaRBS

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Authors: Saleh H. Salmen, Sulaiman Ali Alharbi, Hany M. Yehia, Mohammad A. Khiyami, Milton Wainwright, Naiyf S. Alharbi, Arunachalam Chinnathambi

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An antifungal protein synthesized by Bacillus cereus has been partially purified by the use of ammonium sulfate precipitation and Sephadex-G-200 column chromatography. The protein was produced from Bacillus cereus grown in potato Dextrose Broth Medium (PDB) at 30 ºC for 3 days at 100 rpm. The protein showed antagonistic effect against some fungi and yeasts. Crude extract from medium and semi-purified protein were tested in vitro against both fungi and yeasts using the disc diffusion method in order to detect the inhibitory effect of the protein. Zones of inhibition of the following diameter were found (mm) were Alternaria alternate (28), Rhodotorula glutinis (20), Fusarium sp. (16), Rhizopus sp. (15), Penicillium digitatum (13), Mucor sp. (13) and Aspergillus niger (10). The isolated protein was found to have a molecular weight of ~35kDa by sodium deodecyl sulfate-poly acrylamide gel electrophoresis. The data showed that the protein of Bacillus cereus has antifungal activity, a fact which points to the possibility of using it as a bio-control agent against some fungi, findings which emphasize the potential role of B. cereus as an important bio-control agent.

Keywords: bacillus cereus, ~35kDa protein, molds, yeasts

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Authors: Arunima Verma, Padmabati Mondal

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Serotonin-receptor binding plays a key role in several neurological and biological processes, including mood, sleep, hunger, cognition, learning, and memory. In this article, we performed molecular dynamics simulation to examine the key residues that play an essential role in the binding of serotonin to the G-protein-coupled 5-HT₁ᴮ receptor (5-HT₁ᴮ R) via electrostatic interactions. An end-point free energy calculation method (MM-PBSA) determines the stability of the 5-HT1B R due to serotonin binding. The single-point mutation of the polar or charged amino acid residues (Asp129, Thr134) on the binding sites and the calculation of binding free energy validate the importance of these residues in the stability of the serotonin-receptor complex. Principal component analysis indicates the serotonin-bound 5-HT1BR is more stabilized than the apo-receptor in terms of dynamical changes. The difference dynamic cross-correlations map shows the correlation between the transmembrane and mini-Go, which indicates signal transduction happening between mini-Go and the receptor. Allosteric communication reveals the key nodes for signal transduction in 5-HT1BR. These results provide useful insights into the signal transduction pathways and mutagenesis study to regulate the functionality of the complex. The developed protocols can be applied to study local non-covalent interactions and long-range allosteric communications in any protein-ligand system for computer-aided drug design.

Keywords: allostery, CADD, MD simulations, MM-PBSA

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Authors: Purva Mishra, Rajesh Potlia, Kuljeet Singh Sandhu

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The role of glycyl residues in the protein structure has lingered within the research community for the last several decades. Glycyl residue is the only amino acid that is achiral due to the lack of a side chain and can, therefore, exhibit Ramachandran conformations that are disallowed for L-amino acids. The structural and functional significance of glycyl residues with L-disallowed conformation, however, remains obscure. Through statistical analysis of various datasets, we found that the glycyls with L-disallowed conformations are over-represented at disease-associated sites and tend to be evolutionarily conserved. The mutations of L-disallowed glycyls tend to destabilize the native conformation, reduce protein solubility, and promote inter-molecular aggregations. We uncovered a structural motif referred to as “β-crescent” formed around the L-disallowed glycyl, which prevents β-sheet aggregation by disrupting the alternating pattern of β-pleats. The L-disallowed conformation of glycyls also holds predictive power to infer the pathogenic missense variants. Altogether, our observations highlight that the L-disallowed conformation of glycyls is selected to facilitate native folding and prevent inter-molecular aggregations. The findings may also have implications for designing more stable proteins and prioritizing the genetic lesions implicated in diseases.

Keywords: Ramachandran plot, β-sheet, protein stability, protein aggregation

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Authors: Shahram Naghizadeh Raeisi, Ali Alghooneh

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The application of whey protein in drink industry to enhance the nutritional value of the products is important. Furthermore, the gelification of protein during thermal treatment and shelf life makes some limitations in its application. So, the main goal of this research is manufacturing of high concentrate whey protein orange drink with appropriate shelf life. In this way, whey protein was 5 to 30% hydrolyzed ( in 5 percent intervals at six stages), then thermal stability of samples with 10% concentration of protein was tested in acidic condition (T= 90 °C, pH=4.2, 5 minutes ) and neutral condition (T=120° C, pH:6.7, 20 minutes.) Furthermore, to study the shelf life of heat treated samples in 4 months at 4 and 24 °C, the time sweep rheological test were done. At neutral conditions, 5 to 20% hydrolyzed sample showed gelling during thermal treatment, whereas at acidic condition, was happened only in 5 to 10 percent hydrolyzed samples. This phenomenon could be related to the difference in hydrodynamic radius and zeta potential of samples with different level of hydrolyzation at acidic and neutral conditions. To study the gelification of heat resistant protein solutions during shelf life, for 4 months with 7 days intervals, the time sweep analysis were performed. Cross over was observed for all heat resistant neutral samples at both storage temperature, while in heat resistant acidic samples with degree of hydrolysis, 25 and 30 percentage at 4 and 20 °C, it was not seen. It could be concluded that the former sample was stable during heat treatment and 4 months storage, which made them a good choice for manufacturing high protein drinks. The Scheffe polynomial model and numerical optimization were employed for modeling and high protein orange drink formula optimization. Scheffe model significantly predicted the overal acceptance index (Pvalue<0.05) of sensorial analysis. The coefficient of determination (R2) of 0.94, the adjusted coefficient of determination (R2Adj) of 0.90, insignificance of the lack-of-fit test and F value of 64.21 showed the accuracy of the model. Moreover, the coefficient of variable (C.V) was 6.8% which suggested the replicability of the experimental data. The desirability function had been achieved to be 0.89, which indicates the high accuracy of optimization. The optimum formulation was found as following: Modified whey protein solution (65.30%), natural orange juice (33.50%), stevia sweetener (0.05%), orange peel oil (0.15%) and citric acid (1 %), respectively. Its worth mentioning that this study made an appropriate model for application of whey protein in drink industry without bitter flavor and gelification during heat treatment and shelf life.

Keywords: croos over, orange beverage, protein modification, optimization

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Authors: Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi

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For machine learning based epileptic seizure prediction, it is important for the model to be implemented in small implantable or wearable devices that can be used to monitor epilepsy patients; however, current state-of-the-art methods are complex and computationally intensive. We use Shapley Additive Explanation (SHAP) to find relevant intracranial electroencephalogram (iEEG) features and improve the computational efficiency of a state-of-the-art seizure prediction method based on the extra trees classifier while maintaining prediction performance. Results for a small contest dataset and a much larger dataset with continuous recordings of up to 3 years per patient from 15 patients yield better than chance prediction performance (p < 0.004). Moreover, while the performance of the SHAP-based model is comparable to that of the benchmark, the overall training and prediction time of the model has been reduced by a factor of 1.83. It can also be noted that the feature called zero crossing value is the best EEG feature for seizure prediction. These results suggest state-of-the-art seizure prediction performance can be achieved using efficient methods based on optimal feature selection.

Keywords: machine learning, seizure prediction, extra tree classifier, SHAP, epilepsy

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Authors: A. Ojha, Y. K. Gupta

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Organophosphate (OP) pesticides are among the most widely used synthetic chemicals for controlling a wide variety of pests throughout the world. Chlorpyrifos (CPF), methyl parathion (MPT), and malathion (MLT) are among the most extensively used OP pesticides in India. DNA strand breaks and DNA-protein crosslinks (DPC) are toxic lesions associated with the mechanisms of toxicity of genotoxic compounds. In the present study, we have examined the potential of CPF, MPT, and MLT individually and in combination, to cause DNA strand breakage and DPC formation. Peripheral blood lymphocytes of rat were exposed to 1/4 and 1/10 LC50 dose of CPF, MPT, and MLT for 2, 4, 8, and 12h. The DNA strand break was measured by the comet assay and expressed as DNA damage index while DPC estimation was done by fluorescence emission. There was significantly marked increase in DNA damage and DNA-protein crosslink formation in time and dose dependent manner. It was also observed that MPT caused the highest level of DNA damage as compared to other studied OP compounds. Thus, from present study, we can conclude that studied pesticides have genotoxic potential. The pesticides mixture does not potentiate the toxicity of each other. Nonetheless, additional in vivo data are required before a definitive conclusion can be drawn regarding hazard prediction to humans.

Keywords: organophosphate, pesticides, DNA damage, DNA protein crosslink, genotoxic

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Authors: Nais Pinta Adetya, H. Hadiyanto

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Microalgae has a potential to be utilized as food and natural colorant. The microalgae components consists of three main parts, these are lipid, protein, and carbohydrate. Crucial step in producing lipid and protein from microalgae is extraction. Microalgae has high water level (70-90%), it causes drying process of biomass needs much more energy and also has potential to distract lipid and protein from microalgae. Extraction of lipid from wet biomass is able to take place efficiently with cell disruption of microalgae by osmotic shock method. In this study, osmotic shock method was going to be integrated with ultrasound to maximalize the extraction yield of lipid and protein from wet biomass Spirulina sp. with osmotic shock method assisted ultrasound. This study consisted of two steps, these were osmotic shock process toward wet biomass and ultrasound extraction assisted. NaCl solution was used as osmotic agent, with the variation of concentrations were 10%, 20%, and 30%. Extraction was conducted in 40°C for 20 minutes with frequency of ultrasound wave was 40kHz. The optimal yield of protein (2.7%) and (lipid 38%) were achieved at 20% osmotic agent concentration.

Keywords: extraction, lipid, osmotic shock, protein, ultrasound

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Authors: Jer-Yuh Liu, Je-Chiuan Ye, Jin-Ming Hwang

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Protein kinase C alpha (PKCα) is a key signaling molecule in human cancer development. As a therapeutic strategy, targeting PKCα is difficult because the molecule is ubiquitously expressed in non-malignant cells. PKCα is regulated by the cooperative interaction of the transcription factors myeloid zinc finger 1 (MZF-1) and Ets-like protein-1 (Elk-1) in human cancer cells. By conducting tissue array analysis, herein, we determined the protein expression of MZF-1/Elk-1/PKCα in various cancers. The data show that the expression of MZF-1/Elk-1 is correlated with that of PKCα in hepatocellular carcinoma (HCC), but not in bladder and lung cancers. In addition, the PKCα down-regulation by shRNA Elk-1 was only observed in the HCC SK-Hep-1 cells. Blocking the interaction between MZF-1 and Elk-1 through the transfection of their binding domain MZF-160–72 decreased PKCα expression. This step ultimately depressed the epithelial-mesenchymal transition potential of the HCC cells. These findings could be used to develop an alternative therapeutic strategy for patients with the PKCα-derived HCC.

Keywords: protein kinase C alpha, myeloid zinc finger 1, ets-like protein-1, hepatocellular carcinoma

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Authors: Nor Zila Abd Hamid, Mohd Salmi M. Noorani

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This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series.

Keywords: chaotic approach, phase space, Cao method, local linear approximation method

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Authors: Mateen A. Khan, Elizabeth J. Theil, Dixie J. Goss

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Cellular iron homeostasis is accomplished by the coordinated regulated expression of iron uptake, storage, and export. Iron regulate the translation of ferritin and mitochondrial aconitase iron responsive element (IRE)-mRNA by interaction with an iron regulatory protein (IRPs). Iron increases protein biosynthesis encoded in iron responsive element. The noncoding structure IRE-mRNA, approximately 30-nt, folds into a stem loop to control synthesis of proteins in iron trafficking, cell cycling, and nervous system function. Fluorescence anisotropy measurements showed the presence of one binding site on IRP1 for ferritin and mitochondrial aconitase IRE-mRNA. Scatchard analysis revealed the binding affinity (Kₐ) and average binding sites (n) for ferritin and mitochondrial aconitase IRE-mRNA were 68.7 x 10⁶ M⁻¹ and 9.2 x 10⁶ M⁻¹, respectively. In order to understand the relative importance of equilibrium and stability, we further report the contribution of electrostatic interactions in the overall binding of two IRE-mRNA with IRP1. The fluorescence quenching of IRP1 protein was measured at different ionic strengths. The binding affinity of IRE-mRNA to IRP1 decreases with increasing ionic strength, but the number of binding sites was independent of ionic strength. Such results indicate a differential contribution of electrostatics to the interaction of IRE-mRNA with IRP1, possibly related to helix bending or stem interactions and an overall conformational change. Selective destabilization of ferritin and mitochondrial aconitase RNA/protein complexes as reported here explain in part the quantitative differences in signal response to iron in vivo and indicate possible new regulatory interactions.

Keywords: IRE-mRNA, IRP1, binding, ionic strength

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Authors: Hatairuk Tungkasen, Somrudee Phetchrid, Suwapat Jaidee, Supinya Yoomak, Chantana Kankamol, Mayuree Pumipaiboon, Mayuva Areekijseree

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Ovaries of reproductive female pigs were obtained from local slaughterhouses in Nakorn Pathom Province, Thailand. Follicular fluid of medium follicle (5-6 diameters) and large follicles (7-8 mm and 10 mm in diameter) were aspirated and collected by sterile technique and analyzed protein pattern. The follicular fluid protein bands were found by SDS-PAGE which has no protein band in difference compared to standard protein band. So we chose protein band molecular weight 50, 62-65, 75-80, 90, 120-160, and >220 kDa were analyzed by LC/MS/MS. The result was found immunoglobulin gamma chain, keratin, transferrin, heat shock protein, and plasminogen precursor, ceruloplasmin, and hemopexin, and protease, respectively. All proteins play important roles in promotion and regulation on growth and development of reproductive cells. The result of this study found many proteins which were useful and important for in vitro oocyte maturation and embryonic development of cell technology in animals. The further study will be use porcine follicular fluid protein of medium and large follicles as feeder cells in in vitro condition to promote oocyte and embryo maturation.

Keywords: follicular fluid protein, LC/MS/MS, porcine oocyte, SDS-PAGE

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Authors: Hanan Azzam1, Nashwa Abousamra1, Amany Mansour1, Yaser Abd El-dayem2, , Solafa Elsharawy1

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Background: Inherited thrombophilias are a heterogenous group of conditions which have been implicated in a variety of pregnancy complications. More recently, deficiency of protein Z (PZ) has been liked to pregnancy complications, including preterm delivery. Aim: We designed this study to evaluate the association of inherited thrombophilias including [Protein C (PC), Protein S (PS), Anti thrombin III (ATIII) deficiency and activated protein C (APC) resistance] and protein Z deficiency with a variety of pregnancy complications. Patients and Methods: 60 women with different pregnancy complications, including 20 patients with preeclampsia, 20 patients with intrauterine growth resistance (IUGR), and 20 patients with intrauterine fetal death (IUFD), in addition to 30 healthy pregnant women were recruited for the present study. PC and free PS antigen, ATIII activity, modified functional APC-resistance, and PZ levels were determined. Results: There was no significant association between inherited thrombophilias and complicated pregnancies as regards PC deficiency (p=1.0), AT III and PS deficiency (p=0.312), and APC-resistance (P=0.083). PZ was significantly associated with complicated pregnancies (p=0.012). Patients with protein Z levels below 1.5 µg/ml were considered deficient. Accordingly, we demonstrated protein Z deficiency in 30% of complicated pregnancies (RR 6.0, 95% CI 1.29-27.90;p=0.022), 20% of preeclampsia (RR 3.5, 95% CI 0.57 – 21.28; P = 0.174), 40% of IUGR (RR 9.3 95% CI 1.72-50.61; P = 0.010) and 30% of IUFD (RR 6, 95% CI 1.07 – 33.64; P = 0.042). Conclusions: These findings indicate the absence of association of inherited thrombophilias, including PC, PS, AT III deficiency, and APC resistance with pregnancy complications. However, PZ deficiency is associated with increased risk of pregnancy complications, especially intrauterine growth restriction and intrauterine fetal death.

Keywords: protein C, protein S, thrombophelia, pregnancy, protein Z

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Authors: Hy Dang, Bo Mei

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The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: classification, machine learning, time representation, stock prediction

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Authors: Diana Karina Baigts Allende, Mariana Gonzalez Diaz, Luis Antonio Chel Guerrero, Mukthar Sandoval Peraza

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Poverty and food insecurity are still incident problems in the developing countries, where population´s diet is based on cereals which are lack in protein content. Nevertheless, during last years the use of native plants has been studied as an alternative source of protein in order to improve the nutritional intake. Chaya crop also called Spinach tree, is a prehispanic plant native from Central America and South of Mexico (Mayan culture), which has been especially valued due to its high nutritional content particularly protein and some medicinal properties. The aim of this work was to study the effect of protein isolation processing from Chaya leaf harvest in Yucatan, Mexico on its structure quality in order: i) to valorize the Chaya crop and ii) to produce low-cost and high-quality protein. Chaya leaf was extruded, clarified and recovered using: a) acid precipitation by decreasing the pH value until reach the isoelectric point (3.5) and b) thermal coagulation, by heating the protein solution at 80 °C during 30 min. Solubilized protein was re-dissolved in water and spray dried. The presence of Fraction I protein, known as RuBisCO (Rubilose-1,5-biphosfate carboxylase/oxygenase) was confirmed by gel electrophoresis (SDS-PAGE) where molecular weight bands of 55 KDa and 12 KDa were observed. The infrared spectrum showed changes in protein structure due to the isolation method. The use of high temperatures (thermal coagulation) highly decreased protein solubility in comparison to isoelectric precipitated protein, the nutritional properties according to amino acid profile was also disturbed, showing minor amounts of overall essential amino acids from 435.9 to 367.8 mg/g. Chaya protein isolate obtained by acid precipitation showed higher protein quality according to essential amino acid score compared to FAO recommendations, which could represent an important sustainable source of protein for human consumption.

Keywords: chaya leaf, nutritional properties, protein isolate, protein structure

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Authors: Supriya H. S., Chandrakala B. M.

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Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.

Keywords: MLHN, network traffic prediction

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Authors: Ayoola, Simeon Oluwatoyin, Omogoriola Hannah Omoloye

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The effects of 17α-Methyltestosterone Hormone on blood composition of the Sex Reversed Sarotherodon melanotheron were investigated. S. melanotheron fry were reared in six (6) plastic tanks for three (3) months, of which three (3) tanks served as treatment tanks while the other three (3) served as the control. The fry were fed with 17α-methyl testosterone enzyme, which functions as a sex reversal hormone. The fry were administered this hormone for 30 days, to ensure complete sex reversal. All the S. melanotheron fry were reared to table size for duration of three (3) months, after which, blood samples were taken from both the control and treatment fishes. The blood parameters showed no significant differences with the same values of White Blood Cell count (WBC) and Total plasma protein for the control and experimental fishes. A total protein value for sex reversed specimens was 3.99g/dL, while urea and creatinine values were 0.2g/dL. Alkaline Phosphatase, Aspartate transaminase and Alanine transaminase for the treatment specimen were 183nm/mg protein/min, 98nm/mg protein/min and 105nm/mg protein/min respectively. A total protein value for control specimens was 2.81g/dL, while urea and creatinine values were 0.2g/dL. Alkaline Phosphatase, Aspartate transaminase and Alanine transaminase for the control species were 174nm/mg protein/min, 93nm/mg protein/min and 106nm/mg protein/min respectively. The safety of MT on S. melanotheron is therefore proved since there is no adverse effect on the fish.

Keywords: 17α-Methyltestosterone, haematology, sex reversal, sarotherodon melanotheron

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Authors: Alise Senberga, Laila Dubova, Liene Strauta, Ina Alsina, Ieva Erdberga

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Legume symbiotic relationship with nitrogen fixating bacteria Rhizobim leguminosarum is an important factor used to improve the productivity of legumes, due to the fact that rhizobia can supply plant with the necessary amount of nitrogen. R. leguminosarum strains have shown different activity in fixing nitrogen. Depending on the chosen R. leguminosarum strain, host plant biochemical content can be altered. In this study we focused particularly on the changes in protein content in beans (using two different varieties) and peas (five different varieties) due to the use of several different R. leguminosarum strains (four strains for both beans and peas). Overall, the protein content increase was observed after seed inoculation with R. leguminosarum. Strain and plant cultivar interaction specification was observed. The effect of R. leguminosarum inoculation on the content of protein was dependent on the R. leguminosarum strain used. Plant cultivar also appeared to have a decisive role in protein content formation with the help of R. leguminosaru.

Keywords: legumes, protein content, rhizobia strains, soil

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Authors: Qiming Zhang, Youda Ye, Qinxue Jiang

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Accurate prediction of external flowfield and aero-heating at the wall of hypersonic vehicle is very crucial for the design of aircrafts. Unstructured/hybrid meshes have more powerful advantages than structured meshes in terms of pre-processing, parallel computing and mesh adaptation, so it is imperative to develop high-resolution numerical methods for the calculation of aerothermal environment on unstructured/hybrid meshes. The inviscid flux scheme is one of the most important factors affecting the accuracy of unstructured/ hybrid mesh heat flux calculation. Here, a new hybrid flux scheme is developed and the approach of interface type selection is proposed: i.e. 1) using the exact Riemann scheme solution to calculate the flux on the faces parallel to the wall; 2) employing Sterger-Warming (S-W) scheme to improve the stability of the numerical scheme in other interfaces. The results of the heat flux fit the one observed experimentally and have little dependence on grids, which show great application prospect in unstructured/ hybrid mesh.

Keywords: aero-heating prediction, computational fluid dynamics, hybrid meshes, hybrid schemes

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Authors: Prasanna Ramachandran, Kareem Graham, Helena Kiefel, Sunit Jain, Todd DeSantis

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Microbes that reside inside the mammalian GI tract, commonly referred to as the gut microbiome, have been shown to have therapeutic effects in animal models of disease. We hypothesize that specific proteins produced by these microbes are responsible for this activity and may be used directly as therapeutics. To speed up the discovery of these key proteins from the big-data metagenomics, we have applied machine learning techniques. Using amino acid sequences of known epitopes and their corresponding binding partners, protein interaction descriptors (PID) were calculated, making a positive interaction set. A negative interaction dataset was calculated using sequences of proteins known not to interact with these same binding partners. Using Random Forest and positive and negative PID, a machine learning model was trained and used to predict interacting versus non-interacting proteins. Furthermore, the continuous variable, cosine similarity in the interaction descriptors was used to rank bacterial therapeutic candidates. Laboratory binding assays were conducted to test the candidates for their potential as therapeutics. Results from binding assays reveal the accuracy of the machine learning prediction and are subsequently used to further improve the model.

Keywords: protein-interactions, machine-learning, metagenomics, microbiome

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Authors: Khaleel Saleh Al-Rababah

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Amyloid fibril forming regions, which are known as protein aggregates, in sequences of some protein families are associated with a number of diseases known as amyloidosis. Mutations play a role in forming fibrils by accelerating the fibril formation process. In this paper we want to extract diseases that caused by those mutations as a result of the impact of the mutations on structural and functional properties of the aggregated protein. We propose a text mining system, to automatically extract mutations, diseases and relations between mutations and diseases. We presented an algorithm based on finite state to cluster mutations found in the same sentence as a sentence could contain different mutation cause different diseases. Also, we presented a co reference algorithm that enables cross-link sentences.

Keywords: amyloid, amyloidosis, co reference, protein, text mining

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Authors: Sirilak Kongkaew, Pathumwadee Yodmanee, Nopporn Kaiyawet, Arthitaya Meeprasert, Thanyada Rungrotmongkol, Toshikatsu Kaburaki, Hiroshi Noguchi, Fujio Takeuch, Nawee Kungwan, Supot Hannongbua

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Behçet’s disease (BD) is a genetic autoimmune expressed by multisystemic inflammatory disorder mostly occurred at the skin, joints, gastrointestinal tract, and genitalia, including ocular, oral, genital, and central nervous systems. Most BD patients in Japan and Korea were strongly indicated by the genetic factor namely HLA-B*51 (especially, HLA-B*51:01) marker in HMC class I, while HLA-A*26:01 allele has been detected from the BD patients in Greek, Japan, and Taiwan. To understand the selective binding of the MICA-TM peptide towards the HLAs associated with BD, the molecular dynamics simulations were applied on the four HLA alleles (B*51:01, B*35:01, A*26:01, and A*11:01) in complex with such peptide. As a result, the key residues in the binding groove of HLA protein which play an important role in the MICA-TM peptide binding and stabilization were revealed. The Van der Waals force was found to be the main protein-protein interaction. Based on the binding free energy prediction by MM/PBSA method, the MICA-TM peptide interacted stronger to the HLA alleles associated to BD in the identical class by 7-12 kcal/mol. The obtained results from the present study could help to differentiate the HLA alleles and explain a source of Behçet’s disease.

Keywords: Behçet’s disease, MD simulations, HMC class I, autoimmune

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Authors: Saskya E. Carrera P., Ben Hankamer, Melanie Oey

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The green alga C. reinhardtii provides a platform for the cheap, scalable, and safe production of complex proteins. Despite gene expression in photosynthetic organisms being tightly regulated by light, most expression studies have analysed chloroplast recombinant protein production under constant light. Here the influence of illumination time and intensity on GFP and a GFP-PlyGBS (bacterial-lysin) fusion protein expression was investigated. The expression of both proteins was strongly influenced by the light regime (6-24 hr illumination per day), the light intensity (0-450 E m⁻²s⁻¹) and growth condition (photoautotrophic, mixotrophic and heterotrophic). Heterotrophic conditions resulted in relatively low recombinant protein yields per unit volume, despite high protein yields per cell, due to low growth rates. Mixotrophic conditions exhibited the highest yields at 6 hrs illumination at 200µE m⁻²s⁻¹ and under continuous low light illumination (13-16 mg L⁻¹ GFP and 1.2-1.6 mg L⁻¹ GFP-PlyGBS), as these conditions supported good cell growth and cellular protein yields. A ~23-fold increase in protein accumulation per cell and ~9-fold increase L⁻¹ culture was observed compared to standard constant 24 hr illumination for GFP-PlyGBS. The highest yields under photoautotrophic conditions were obtained under 9 hrs illumination (6 mg L⁻¹ GFP and 2.1 mg L⁻¹ GFP-PlyGBS). This represents a ~4-fold increase in cellular protein accumulation for GFP-PlyGBS. On a volumetric basis the highest yield was at 15 hrs illumination (~2-fold increase L⁻¹ over the constant light for GFP-PlyGBS). Optimising illumination conditions to balance growth and protein expression can thus significantly enhance overall recombinant protein production in C. reinhardtii cultures.

Keywords: chlamydomonas reinhardtii, light, mixotrophic, recombinant protein

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Authors: Md. Samsuddin Ansari, Ashish Arora

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Every year 10 million people fall ill with one of the oldest diseases known as tuberculosis, caused by Mycobacterium tuberculosis. The success of M. tuberculosis as a pathogen is because of its ability to persist in host tissues. Multidrug resistance (MDR) mycobacteria cases increase every day, which is associated with efflux pumps controlled at the level of transcription. The transcription regulators of MDR transporters in bacteria belong to one of the following four regulatory protein families: AraC, MarR, MerR, and TetR. Phenolic acid decarboxylase repressor (PadR), like a family of transcription regulators, is closely related to the MarR family. Phenolic acid decarboxylase repressor (PadR) was first identified as a transcription factor involved in the regulation of phenolic acid stress response in various microorganisms (including Mycobacterium tuberculosis H37Rv). Recently research has shown that the PadR family transcription factors are global, multifunction transcription regulators. Rv0047c is a PadR subfamily-1 protein. We are exploring the biophysical and structural characterization of Rv0047c. The Rv0047 gene was amplified by PCR using the primers containing EcoRI and HindIII restriction enzyme sites cloned in pET-NH6 vector and overexpressed in DH5α and BL21 (λDE3) cells of E. coli following purification with Ni2+-NTA column and size exclusion chromatography. We did DSC to know the thermal stability; the Tm (transition temperature) of protein is 55.29ºC, and ΔH (enthalpy change) of 6.92 kcal/mol. Circular dichroism to know the secondary structure and conformation and fluorescence spectroscopy for tertiary structure study of protein. To understand the effect of pH on the structure, function, and stability of Rv0047c we employed spectroscopy techniques such as circular dichroism, fluorescence, and absorbance measurements in a wide range of pH (from pH-2.0 to pH-12). At low and high pH, it shows drastic changes in the secondary and tertiary structure of the protein. EMSA studies showed the specific binding of Rv0047c with its own 30-bp promoter region. To determine the effect of complex formation on the secondary structure of Rv0047c, we examined the CD spectra of the complex of Rv0047c with promoter DNA of rv0047. The functional role of Rv0047c was characterized by over-expressing the Rv0047c gene under the control of hsp60 promoter in Mycobacterium tuberculosis H37Rv. We have predicted the three-dimensional structure of Rv0047c using the Swiss Model and Modeller, with validity checked by the Ramachandra plot. We did molecular docking of Rv0047c with dnaA, through PatchDock following refinement through FireDock. Through this, it is possible to easily identify the binding hot-stop of the receptor molecule with that of the ligand, the nature of the interface itself, and the conformational change undergone by the protein pattern. We are using X-crystallography to unravel the structure of Rv0047c. Overall the studies show that Rv0047c may have transcription regulation along with providing an insight into the activity of Rv0047c in the pH range of subcellular environment and helps to understand the protein-protein interaction, a novel target to kill dormant bacteria and potential strategy for tuberculosis control.

Keywords: mycobacterium tuberculosis, phenolic acid decarboxylase repressor, Rv0047c, Circular dichroism, fluorescence spectroscopy, docking, protein-protein interaction

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Authors: Babak Moradi, Hassan Zare-Maivan

Abstract:

A greenhouse investigation has been conducted to study the effect of crude oil on morphology and protein content of Avicennia marina plant. Avicennia marina seeds were sown in different concentrations of the crude oil mixed soil (i.e., 2.5, 5, 7.5, and 10 w/w). Controls and replicates were also set up. Morphological traits were recorded 4 months after plantation. Avicennia marina seedlings could tolerate up to 10% (w/w). Results demonstrated that there was a reduction in plant shoot and root biomass with the increase of crude oil concentration. Plant height, total leaf number and length reduced significantly with increase of crude oil contamination. Investigation revealed that there is a great impact of crude oil contamination on protein content of the roots of the experimental plant. Protein content of roots grown in different concentrations of crude oil were more than those of the control plant. Further, results also showed that protein content was increased with increased concentration of crude oil.

Keywords: Avicennia marina, morphology, oil contamination, protein content

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Authors: Asif Bilal, Fouzia Tanvir, Sibtain Ahmad

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Estrogen receptor alpha, also known as estrogen receptor-1, is highly involved in risk of mammary carcinoma. The objectives of this study were to identify non-synonymous SNPs of estrogen receptor and their association with breast cancer and to identify the chemotherapeutic responses of phytochemicals against it via in-silico study design. For this purpose, different online tools. to identify pathogenic SNPs the tools were SIFT, Polyphen, Polyphen-2, fuNTRp, SNAP2, for finding disease associated SNPs the tools SNP&GO, PhD-SNP, PredictSNP, MAPP, SNAP, MetaSNP, PANTHER, and to check protein stability Mu-Pro, I-Mutant, and CONSURF were used. Post-translational modifications (PTMs) were detected by Musitedeep, Protein secondary structure by SOPMA, protein to protein interaction by STRING, molecular docking by PyRx. Seven SNPs having rsIDs (rs760766066, rs779180038, rs956399300, rs773683317, rs397509428, rs755020320, and rs1131692059) showing mutations on I229T, R243C, Y246H, P336R, Q375H, R394S, and R394H, respectively found to be completely deleterious. The PTMs found were 96 times Glycosylation; 30 times Ubiquitination, a single time Acetylation; and no Hydroxylation and Phosphorylation were found. The protein secondary structure consisted of Alpha helix (Hh) is (28%), Extended strand (Ee) is (21%), Beta turn (Tt) is 7.89% and Random coil (Cc) is (44.11%). Protein-protein interaction analysis revealed that it has strong interaction with Myeloperoxidase, Xanthine dehydrogenase, carboxylesterase 1, Glutathione S-transferase Mu 1, and with estrogen receptors. For molecular docking we used Asiaticoside, Ilekudinuside, Robustoflavone, Irinoticane, Withanolides, and 9-amin0-5 as ligands that extract from phytochemicals and docked with this protein. We found that there was great interaction (from -8.6 to -9.7) of these ligands of phytochemicals at ESR1 wild and two mutants (I229T and R394S). It is concluded that these SNPs found in ESR1 are involved in breast cancer and given phytochemicals are highly helpful against breast cancer as chemotherapeutic agents. Further in vitro and in vivo analysis should be performed to conduct these interactions.

Keywords: breast cancer, ESR1, phytochemicals, molecular docking

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Authors: Solange Adechian, Michèle Balage, Didier Remond, Carole Migné, Annie Quignard-Boulangé, Agnès Marset-Baglieri, Sylvie Rousset, Yves Boirie, Claire Gaudichon, Dominique Dardevet, Laurent Mosoni

Abstract:

Studies have shown that timing of protein intake, leucine content, and speed of digestion significantly affect postprandial protein utilization. Our aim was to determine if one can spare lean body mass during energy restriction by varying the quality and the timing of protein intake. Obese volunteers followed a 6-wk restricted energy diet. Four groups were compared: casein pulse, casein spread, milk-soluble protein (MSP, = whey) pulse, and MSP spread (n = 10-11 per group). In casein groups, caseins were the only protein source; it was MSP in MSP groups. Proteins were distributed in four meals per day in the proportion 8:80:4:8% in the pulse groups; it was 25:25:25:25% in the spread groups. We measured weight, body composition, nitrogen balance, 3-methylhistidine excretion, perception of hunger, plasma parameters, adipose tissue metabolism, and whole body protein metabolism. Volunteers lost 7.5 ± 0.4 kg of weight, 5.1 ± 0.2 kg of fat, and 2.2 ± 0.2 kg of lean mass, with no difference between groups. In adipose tissue, cell size and mRNA expression of various genes were reduced with no difference between groups. Hunger perception was also never different between groups. In the last week, due to a higher inhibition of protein degradation and despite a lower stimulation of protein synthesis, postprandial balance between whole body protein synthesis and degradation was better with caseins than with MSP. It seems likely that the positive effect of caseins on protein balance occurred only at the end of the experiment.

Keywords: lean body mass, fat mass, casein, whey, protein metabolism

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Authors: Debesh R. Roy

Abstract:

The fundamental issue in understanding the origin and growth mechanism of nanomaterials, from a fundamental unit is a big challenging problem to the scientists. Recently, an immense attention is generated to the researchers for prediction of exceptionally stable atomic cluster units as the building units for future smart materials. The present study is a systematic investigation on the stability and electronic properties of a series of bimetallic (semiconductor-alkaline earth) clusters, viz., BxMg3 (x=1-5) is performed, in search for exceptional and/ or unusual stable motifs. A very popular hybrid exchange-correlation functional, B3LYP as proposed by A. D. Becke along with a higher basis set, viz., 6-31+G[d,p] is employed for this purpose under the density functional formalism. The magic stability among the concerned clusters is explained using the jellium model. It is evident from the present study that the magic stability of B4Mg3 cluster arises due to the jellium shell closure.

Keywords: atomic clusters, density functional theory, jellium model, magic clusters, smart nanomaterials

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Authors: Damous Mohamed, Zeroudi Nasredine

Abstract:

High-speed milling of thin-walled parts with complex curvilinear profiles often encounters machining instability, commonly referred to as chatter. This phenomenon arises due to the dynamic interaction between the cutting tool and the part, exacerbated by the part's low rigidity and varying dynamic characteristics along the tool path. This research presents a dynamic model specifically developed to predict machining stability for such curved thin-walled components. The model employs the semi-discretization method, segmenting the tool trajectory into small, straight elements to locally approximate the behavior of an inclined plane. Dynamic characteristics for each segment are extracted through experimental modal analysis and incorporated into the simulation model to generate global stability lobe diagrams. Validation of the model is conducted through cutting tests where acoustic intensity is measured to detect instabilities. The experimental data align closely with the predicted stability limits, confirming the model's accuracy and effectiveness. This work provides a comprehensive approach to enhancing machining stability predictions, thereby improving the efficiency and quality of high-speed milling operations for thin-walled parts.

Keywords: chatter, curved thin-walled part, semi-discretization method, stability lobe diagrams

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