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Proteomic Analysis of Stromal and Epithelial Cell Communications in Human Endometrial Cancer Using a Unique 3D Co‐Culture Model
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Abstract<p>Epithelial and stromal communications are essential for normal uterine functions and their dysregulation contributes to the pathogenesis of many diseases including infertility, endometriosis, and cancer. Although many studies have highlighted the advantages of culturing cells in 3D compared to the conventional 2D culture system, one of the major limitations of these systems is the lack of incorporation of cells from non‐epithelial lineages. In an effort to develop a culture system incorporating both stromal and epithelial cells, 3D endometrial cancer spheroids are developed by co‐culturing endometrial stromal cells with cancerous epithelial cells. The spheroids developed by this method are phenotypically comparable to in vivo endometrial cancer tissue. Proteomic analysis of the co‐culture spheroids comparable to human endometrial tissue revealed 591 common proteins and canonical pathways that are closely related to endometrium biology. To determine the feasibility of using this model for drug screening, the efficacy of tamoxifen and everolimus is tested. In summary, a unique 3D model system of human endometrial cancer is developed that will serve as the foundation for the further development of 3D culture systems incorporating different cell types of the human uterus for deciphering the contributions of non‐epithelial cells present in cancer microenvironment.</p>
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Publication Date
Tue Jan 31 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on intrusion detection system based on analysis concept drift: Status and future directions
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Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Measuring the impact of internal control on tax performance using balanced score card indicators: An applied research in a sample of the branches of the General Tax Authority in Iraq
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This research dealt with the impact of internal control on tax performance using balanced scorecard indicators because of its special importance in improving tax performance and reform. The internal control system is a safety valve for senior management in all organizations, it plays an important role in the regularity and development of work and the fight against corruption To provide reliable and accurate data and information, follow up on compliance with laws, regulations and instructions. The aim of this research is to demonstrate how control affects tax performance and how to adapt internal control components to improve tax performance. In the General Authority for taxes and its branches,. The research resulted in a number of conclu

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Publication Date
Fri Jun 27 2025
Journal Name
Journal Of Physical Education
Special Exercises Using A Proposed Training Apprentice And Its Effect On Some Biomechanical Indicators and Achieving 110m Hurdles For players Under 20 years old
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Publication Date
Mon Jan 02 2017
Journal Name
Al-academy
Structural elements of composition design for fabrics image Image footage model
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End of the twentieth century witnessed by the technological evolution Convergences between the visual arts aesthetic value and objective representation of the image in the composition of the design of the fabric of new insights and unconventional potential in atypical employment. It is through access to the designs of modern fabrics that address the employment picture footage included several scenes footage from the film, which focuses on research and analytical as a study to demonstrate the elements of the picture and the organization of its rules and how to functioning in the design of fabrics, Thus, it has identified the problem by asking the following: What are the elements of the picture footage and how the functioning of the struct

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Water Resource And Hydraulic Engineering (jwrhe)
Large Scale Field Physical Model Simulation of Roseires Dam-Break, Sudan
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Physically based modeling approach has been widely developed in recent years for the simulation of dam failure process due to the lack of field data. This paper provides and describes a physically-based model depending on dimensional analysis and hydraulic simulation methods for estimating the maximum water level and the wave propagation time from breaching of field test dams. The field physical model has been constructed in Dabbah city to represent the collapse of the Roseires dam in Sudan. Five cases of a dam failure were studied to simulate water flood conditions by changing initial water height in the reservoir (0.8, 1.0, 1.2, 1.4 and 1.5 m respectively).The physical model working under five cases, case 5 had the greatest influence of t

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Publication Date
Mon Dec 02 2024
Journal Name
Engineering, Technology &amp; Applied Science Research
An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

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Publication Date
Mon Sep 30 2019
Journal Name
Environmental Engineering Research
Development of Bi-Langmuir model on the sorption of cadmium onto waste foundry sand: Effects of initial pH and temperature
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The present study develops the sorption model for simulating the effects of pH and temperature on the uptake of cadmium from contaminated water using waste foundry sand (WFS) by allowing the variation of the maximum adsorption capacity and affinity constant. The presence of two acidic functional groups with the same or different affinity is the basis in the derivation of the two models; Model 1 and Model 2 respectively. The developed Bi-Langmuir model with different affinity (Model 2) has a remarkable ability in the description of process under consideration with coefficient of determination > 0.9838 and sum of squared error < 0.08514. This result is proved by FTIR test where the weak acids responsible of cadmium ions removal

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Publication Date
Sat Jan 01 2022
Journal Name
Communications In Mathematical Biology And Neuroscience
The dynamics of the SEIR epidemic model under the influence of delay
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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating the Scheff'e Model of the Mixture
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Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.

    To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a

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Publication Date
Sun May 18 2025
Journal Name
Discover Food
Analysis of the effectiveness of natural treatments for preserving apricots and the YOLOv7 application for early damage detection
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Maintaining the quality of apricot fruits during storage is not an easy task due to the changes in their physical and chemical properties, so it is necessary to use less expensive, easy to apply, environmentally friendly, and safer preservatives to maintain the nutritional value of apricot. The damage to some fruits during storage can be a source of infection, which leads to the damage of healthy fruits more quickly, which requires building an intelligent model to detect damaged fruits. The aim of the research is to study the effect of immersing apricots in lemon juice once and sugar-water solution again on the quality properties of apricots, including sweetness, color, hardness, and water content. On the other hand, the YOLOv7 algorithm wa

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