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Resveratrol treatment alters lung microbiome in the murine ovalbumin-induced asthma model by increasing mucus-degrading <i>Akkermansia muciniphila</i>.
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Abstract<p>Asthma is a chronic inflammatory disease that involves the narrowing of the lung airways and excessive mucus production. Resveratrol (RES), a polyphenolic stilbene, is known to control asthmatic attacks via different molecular mechanisms. However, no studies have examined the effect of resveratrol on the microbiome in the ovalbumin (OVA)-induced asthma mouse model. In this study, we induced asthma in BALB/c mice by injecting OVA followed by 7 days treatment with RES. Plethysmography showed that the expiratory resistance in the lung tissue was significantly reduced in the RES treated group, while mean volume, peak expiratory flow, and frequency of respiration was increased. Histopathological examination of the lungs of the RES-treated group showed significant reduction in inflammatory cell infiltration and led to restoration of normal lung tissue architecture. In addition, there were significant increases in the expression of the genes encoding tight-junction molecules (claudin-1 and cadherin-18) in the RES-treated group. We performed 16S rRNA microbial analysis of cecal flushes and pulmonary tissues, which showed that RES treatment alters the gut microbiome by significantly increasing the level of Bacteroides acidifaciens spp. compared to disease controls. In addition, there was a significant increase in Akkermansia muciniphila (AM) species within the lungs after RES treatment. AM is a gram-negative, non-spore-forming bacterium known to induce mucus degradation. Since asthma is characterized by an increase in mucus in the lungs, we concluded that RES improves asthma in OVA-induced mouse model by significantly increasing AM and preventing mucus build-up in the lungs.</p>
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Publication Date
Sat Jan 01 2022
Journal Name
1st Samarra International Conference For Pure And Applied Sciences (sicps2021): Sicps2021
The persistence and bifurcation analysis of an ecological model with fear effect involving prey refuge and harvesting
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Publication Date
Thu Aug 08 2024
Journal Name
Computation
Evaluation of the Dynamics of Psychological Panic Factor, Glucose Risk and Estrogen Effects on Breast Cancer Model
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Contracting cancer typically induces a state of terror among the individuals who are affected. Exploring how glucose excess, estrogen excess, and anxiety work together to affect the speed at which breast cancer cells multiply and the immune system’s response model is necessary to conceive of ways to stop the spread of cancer. This paper proposes a mathematical model to investigate the impact of psychological panic, glucose excess, and estrogen excess on the interaction of cancer and immunity. The proposed model is precisely described. The focus of the model’s dynamic analysis is to identify the potential equilibrium locations. According to the analysis, it is possible to establish four equilibrium positions. The stability analys

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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Study of the Electric Quadrupole Moments for some Scandium Isotopes Using Shell Model Calculations with Different Interactions
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The electric quadrupole moments for some scandium isotopes (41, 43, 44, 45, 46, 47Sc) have been calculated using the shell model in the proton-neutron formalism. Excitations out of major shell model space were taken into account through a microscopic theory which is called core polarization effectives. The set of effective charges adopted in the theoretical calculations emerging about the core polarization effect. NushellX@MSU code was used to calculate one body density matrix (OBDM). The simple harmonic oscillator potential has been used to generate the single particle matrix elements. Our theoretical calculations for the quadrupole moments used the two types of effective interactions to obtain the best interaction compared with the exp

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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
Optimization and Modeling the Performance of a Mediator-less Microbial Fuel Cell using Butler-Volmer-Monod Model
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In this study, a one-dimensional model represented by Butler-Volmer-Monod (BVM) model was proposed to compute the anode overpotential and current density in a mediator-less MFC system. The system was fueled with various organic loadings of real field petroleum refinery oily sludge to optimize the favorable organic loading for biomass to operate the suggested system. The increase in each organic loading showed higher resistance to electrons transport to the anode represented by ohmic loss. On the contrary, both activation and mass transfer losses exhibited a noticeable decrement upon the increased organic loadings. However, current density was improved throughout all increased loads achieving a maximum current density of 5.2 A/m3

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Publication Date
Thu Jun 01 2017
Journal Name
American Journal Of Pharmaceutical Education
Exploring Electronic Communication Modes Between Iraqi Faculty and Students of Pharmacy Schools Using the Technology Acceptance Model
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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Calibration and verification of the hydraulic model for Blue Nile river from Roseires dam to Khartoum city
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This research represents a practical attempt applied to calibrate and verify a hydraulic model for the Blue Nile River. The calibration procedures are performed using the observed data for a previous period and comparing them with the calibration results while verification requirements are achieved with the application of the observed data for another future period and comparing them with the verification results. The study objective covered a relationship of the river terrain with the distance between the assumed points of the dam failures along the river length. The computed model values and the observed data should conform to the theoretical analysis and the overall verification performance of the model by comparing it with anothe

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
mathematical model for segmentation of the overall planning of puplic redemption company- ministry of industry and minerals
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Abstract

The study presents a mathematical model with a disaggregating approach to the problem of production planning of a fida Company; which belongs to the ministry of Industry. The study considers disaggregating the entire production into 3 productive families of (hydraulic cylinders, Aldblatt (dampers), connections hydraulics with each holds similar characteristics in terms of the installation cost, production time and stock cost. The Consequences are an ultimate use of the available production capacity as well as meeting the requirements of these families at a minimal cost using linear programming. Moreover, the study considers developing a Master production schedule that drives detailed material and production requi

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Publication Date
Sat Jan 01 2022
Journal Name
Ssrn Electronic Journal
The Prospective of Artificial Neural Network (ANN’s) Model Application to Ameliorate Management of Post Disaster Engineering Projects
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Currently and under the COVID-19 which is considered as a kind of disaster or even any other natural or manmade disasters, this study was confirmed to be important especially when the society is proceeding to recover and reduce the risks of as possible as injuries. These disasters are leading somehow to paralyze the activities of society as what happened in the period of COVID-19, therefore, more efforts were to be focused for the management of disasters in different ways to reduce their risks such as working from distance or planning solutions digitally and send them to the source of control and hence how most countries overcame this stage of disaster (COVID-19) and collapse. Artificial intelligence should be used when there is no practica

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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Application the generalized estimating equation Method (GEE) to estimate of conditional logistic regression model for repeated measurements
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Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.

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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Electronics,computer Networking And Applied Mathematics
Comparison of Some Estimator Methods of Regression Mixed Model for the Multilinearity Problem and High – Dimensional Data
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In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

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