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Gut dysbiosis and immunological profile in endometriosis
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Abstract<p>Ectopic growth of normal cells or debris originating from endometrium, the inner layer of female reproductive tube leads to endometriosis. The main symptoms are dyspareunia, dysmenorrhea, and sometimes chronic pelvic pain. Unfortunately, it has no cure or treatment, only symptoms relief medication or surgical removal. Endometriosis causes estrogen imbalance leading to intestinal bacterial estrobolome dysregulation and subsequent change in immune response. Our study aims to investigate the linkage between gut dysbiosis and immunological response in endometriotic mice. Balb/c mice were ovariectomized (OVX) 7 days before intraperitoneal transplantation of 2mm2 endometrial tissue from OVX donors to OVX- or intact ovary recipients. Colonic content was collected 2 weeks post transplantation for 16s rRNA pyrosequencing. Peritoneal exudate was collected and stained to determine the phenotype of infiltrating cells by flow cytometry. Results revealed a significant increase in the number of exudate cells, natural killer (NK) cells and myeloid derived suppressor cells (MDSCs) in endometriotic mice. Phylogenetic taxonomy showed an increase in the biomass of the bacteria in endometriotic OVX mice in comparison with endometriotic nonovariectomized mice. However, the abundance of Phylum Tenericutes, Order Clostridiales, Dehalobacterium sp. and Anaeroplasma sp. were decreased. Collectively, endometriosis changed estrogen metabolism and gut microbiota which resulted in the immune modulation. (Supported by NIH P01AT003961, R01AT006888, R01MH094755, P20GM103641, R01AI129788 and R01AI123947 to PN and MN, and MoHESR to AKM).</p>
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Publication Date
Thu Oct 01 2020
Journal Name
Green Engineering
Sustainability and recovery project management implementation on construction projects in Iraq
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Publication Date
Sun Oct 01 2023
Journal Name
Journal Of Applied Hematology
D-dimer and Ferritin Levels in Prediction of COVID-19 Severity
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Abstract<sec> <title>BACKGROUND:

The most common cause of upper respiratory tract infection is coronavirus, which has a crown appearance due to the existence of spikes on its envelope. D-dimer levels in the plasma have been considered a prognostic factor for COVID-19 patients.

AIM OF THE STUDY:

The aim of the study is to demonstrate the role of COVID-19 on coagulation parameters D-dimer and ferritin with their association with COVID-19 severity and disease progression in a single-center study.

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Publication Date
Thu Sep 01 2016
Journal Name
Current Pharmaceutical Design
Dry Eye Disease: Present Challenges in the Management and Future Trends
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Publication Date
Sat Dec 01 2018
Journal Name
Swarm And Evolutionary Computation
Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
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Publication Date
Wed Oct 01 2025
Journal Name
Results In Engineering
Advances in Piezoelectric Energy Harvesting: Materials, Configurations, and Power Optimisation Strategies
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Publication Date
Mon Jan 01 2024
Journal Name
Explainable Artificial Intelligence In The Digital Sustainability Administration
Artificial Intelligence and Trends Using in Sustainability Audit: A Bibliometric Analysis
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Publication Date
Sun Aug 01 2021
Journal Name
Bulletin Of Electrical Engineering And Informatics
Robust speaker verification by combining MFCC and entrocy in noisy conditions
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Automatic speaker recognition may achieve remarkable performance in matched training and test conditions. Conversely, results drop significantly in incompatible noisy conditions. Furthermore, feature extraction significantly affects performance. Mel-frequency cepstral coefficients MFCCs are most commonly used in this field of study. The literature has reported that the conditions for training and testing are highly correlated. Taken together, these facts support strong recommendations for using MFCC features in similar environmental conditions (train/test) for speaker recognition. However, with noise and reverberation present, MFCC performance is not reliable. To address this, we propose a new feature 'entrocy' for accurate and robu

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Publication Date
Fri Jan 30 2026
Journal Name
Iraqi Journal Of Science
Theoretical Study of Positive and Negative Parity Coulomb Transitions in 40,48Ca
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Hsieh-Wildenthal (HW) and G-matrix PF1, (GXPF1) interactions for 40Ca and 48Ca, respectively. The 40Ca was considered to be consisted of 32S as a core and 1d3/21f7/2 subshells as a model space. The 48Ca was considered to be consisted of 40Ca as a core and 1f7/22p3/21f5/2 2p1/2 subshells as a model space. The obtained one body-density matrix elements (OBDME) for both interactions for the studied Coulomb transitions:  For 40Ca, the three non-normal parity transitions (C3): ,  and  and one C5 transitions,  .  For 48Ca, the two C2 transitions:  and  and one C4 transitions  were used in parallel with the transformed harmonic-oscillator basis to compute charge density, elastic electron scattering differential cross-section and ela

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Study of total Immunoglobulin E and Eosinophil count in allergic disease
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The present study aimed to evaluate the levels of total immunoglobulin E and percentage count of eosinophil in some of allergic disease. Blood sample collected from 210 patients (110 female, 100 male) with allergic disease (allergic asthma, allergic rhinitis, and urticaria) their age between 10-70 years and 50 healthy control their age between 23-52 years. A highly significant (P<0.01) increase in the mean serum total IgE in patients with asthma (503.54 ± 63.49 IU/ml), Allergic rhinitis (442.77 ± 95.76 IU/ml) and urticaria (489.53 ± 69.68 IU/ml) as a compared with healthy controls (23.67 ± 5.81 IU/ml).There was a significant difference in percentage count of eosinophil in patients groups allergic asthma 4.37 ± 0.52% ,allergic rhinitis

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Concepts of statistical learning and classification in machine learning: An overview
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Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c

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