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Chemokine network dysregulation in EGFR-mutant NSCLC: impact on tumor immunity and drug resistance
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EGFR-mutant non–small cell lung cancer (NSCLC) initially responds well to EGFR tyrosine kinase inhibitors (EGFR-TKIs), yet resistance is nearly inevitable and responses to immune checkpoint inhibitors (ICIs) remain limited. In a retrospective cohort of 57 patients with advanced EGFR-mutant NSCLC treated with nivolumab or pembrolizumab, the objective response rate was 12.3%, although responses were concentrated in a small subgroup with concurrent high PD-L1 expression and dense intratumoral CD8⁺ immune-cell infiltration. Emerging evidence links these outcomes to chemokine-network dysregulation that alters immune trafficking and spatial organization. Oncogenic EGFR signaling shifts chemokine networks away from effector T-cell recruitment and toward regulatory and myeloid-cell accumulation, thereby promoting immune exclusion and treatment adaptation. CXCL12–CXCR4 signaling, stromal barriers, and defective organization of tertiary lymphoid structures further reinforce immune exclusion and ICI resistance. Under EGFR-TKI pressure, chemokine programs evolve dynamically, permitting transient immune entry while sustaining drug tolerance, EMT-associated persistence, and myeloid-supported resistance. However, most proposed chemokine mechanisms remain supported predominantly by preclinical or clinical-correlative evidence, and their causal, temporal, and predictive relevance in patients remains unresolved. Defining these circuits may guide biomarker-driven combinations to convert immune-excluded tumors into immune-permissive states and to prolong disease control through rational TKI-, ICI-, and chemokine-targeted therapeutic strategies.

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Fri Dec 08 2023
Journal Name
Frontiers In Endocrinology
Estrobolome dysregulation is associated with altered immunometabolism in a mouse model of endometriosis
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Introduction

Endometriosis is a painful disease that affects around 5% of women of reproductive age. In endometriosis, ectopic endometrial cells or seeded endometrial debris grow in abnormal locations including the peritoneal cavity. Common manifestations of endometriosis include dyspareunia, dysmenorrhea, chronic pelvic pain and often infertility and symptomatic relief or surgical removal are mainstays of treatment. Endometriosis both promotes and responds to estrogen imbalance, leading to intestinal bacterial estrobolome dysregulation and a subsequent induction of inflammation.

Methods

In the current study, we investigated the linkage be

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Publication Date
Mon Aug 17 2026
Journal Name
Baghdad Science Journal
Molecular Characterization and Genotypic Distribution of Hepatitis B Virus Isolates in Iraq: Prevalence of Drug Resistance Mutations
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Hepatitis B virus (HBV) remains one of the most pervasive viral threats worldwide, posing a significant risk to millions. Due to the absence of proofreading activity during reverse transcription, HBV exhibits a high genetic variability. To date, ten distinct HBV genotypes have been identified globally, associated with varying disease outcomes, including progression to cirrhosis and carcinoma, as well as responses to antivirals. Consequently, genotypic analysis and molecular characterization of HBV are critical for optimizing therapeutic strategies. This study aimed to investigate the distribution of HBV genotypes among Iraqi patients and to characterize their molecular profiles. Therefore, a modified protocol was used to improve seq

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Publication Date
Fri Nov 03 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences( P-issn 1683 - 3597 E-issn 2521 - 3512)
Synergistic Effects of 2-Deoxy-D-Glucose and Cinnamic Acid with Erlotinib on NSCLC Cell Line
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Background: In spite of all efforts, Non-small cell lung cancer (NSCLC) is a fatal solid tumor with a poor prognosis as of its high metastasis and resistance to present treatments. Tyrosine kinase inhibitors (TKI) such as erlotinib are efficient in treating NSCLC but the emergence of chemoresistance and adverse effects substantially limits their single use. Objective: in this study, the combination treatments of either 2-deoxy-D-glucose (2DG) or cinnamic acid (CINN) with erlotinib (ERL) were tested for their possible synergistic effect on the proliferation and migration capacity of NSCLC cells. Methods: In this study, NSCLC model cell line A549 was used to investigate the effects of single compounds and their combination on cell gro

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Publication Date
Fri Jul 18 2025
Journal Name
Sar Journal Of Medical Biochemistry
Western Diets Implications on Health, Including Its Influence on Metabolism and the Immunity
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Processed and red The Western diet, a modern dietary pattern, typically consists of meat, sugar-filled beverages, candies, chocolates, fried foods, prefabricated meals, refined cereals, conventionally produced animal products, high-fat dairy products, and high-fructose items. The goal of this review is to outline how the Western pattern diet affects gut microbiota and mitochondrial fitness, as well as metabolism, inflammation, and antioxidant status. Cancer, mental health, and cardiovascular health; We offer a thorough analysis of how the westernized diet and related nutrients affect immune cell responses as well as the hygienic costs of the Western diet. A consensus critical evaluation utilizing primary sources, including scientifi

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Publication Date
Fri Sep 27 2019
Journal Name
Journal Of Baghdad College Of Dentistry
The Impact of Chronic Periodontitis on Mother-Infant Bonding Status in Relation to Salivary Tumor Necrosis Factor Alpha and Interleukin-6
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Background: Chronic periodontitis is a bacterial infection that result in bone destruction associated with the increasing level of salivary tumor necrosis alpha and interleukin6 that affect Mother-infant bonding status. The aim of the present study was to assess the relationship between the Mother-infant bonding status in mothers with chronic periodontitis in relation to Salivary Tumor necrosis factor alpha and Salivary Interleukin6. Materials and Methods: The selected sample consisted of mothers with chronic periodontitis compared with mothers with healthy periodontium in postpartum period, their age ranged between 30-40 years. Both groups were subjected to postpartum Bonding Questionnaire (PBQ). Periodontal health status was assessed f

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Publication Date
Sat Jan 01 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

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Publication Date
Tue Feb 01 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

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Publication Date
Tue Sep 06 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

Scopus (2)
Scopus
Publication Date
Wed May 22 2024
Journal Name
Journal Of Biotechnology Research Center
Review Article: DNA Methylation in Cancer Immunity
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Background: The transcriptional control of various cell types, especially in the development or functioning of immune system cells involved in either promoting or inhibiting the immune response against cancer, is significantly influenced by DNA or RNA methylation. Multifaceted interconnections exist between immunological or cancer cell populations in the tumor's microenvironment (TME). TME alters the fluctuating DNA (as well as RNA) methylation sequences in these immunological cells to change their development into pro- or anti-cancer cell categories (such as T cells, which are regulatory, for instance). Objective: This review highlights the impact of DNA and RNA methylation on myeloid and lymphoid cells, unraveling their intricate

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