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Neurobiology of Cancer Pain: A Narrative Review
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Chronic cancer pain results from the complex interaction of nociceptive, neuropathic, and neuroimmune mechanisms, which vary according to tumor type, location, stage, and treatment history. Recent advances in cancer neuroscience have reframed pain as a dynamic manifestation of reciprocal tumor–nerve–immune interactions, rather than a mere consequence of tissue damage. In this model, malignant, stromal, and immune cells remodel nociceptive circuits at peripheral and central levels. This narrative review, conducted in accordance with SANRA criteria, synthesizes current mechanistic insights into the neurobiology of cancer pain. At the peripheral level, tumor-derived mediators such as prostaglandins, cytokines, chemokines, glutamate, and endothelin-1 drive nociceptor sensitization via G-protein–coupled and tyrosine kinase pathways. In bone metastases, osteoclast-mediated resorption generates an acidic microenvironment that activates acid-sensing ion channels and transient receptor potential (TRP) channels, linking skeletal destruction with movement-evoked pain. Pathological nerve remodeling and perineural invasion further contribute to neuropathic components and adverse oncological outcomes. Treatment-induced syndromes, notably chemotherapy-induced peripheral neuropathy, result from axonal injury, mitochondrial dysfunction, and neuroinflammation. At the central level, persistent afferent input induces glial activation and chemokine signaling, amplifying synaptic transmission and promoting central sensitization. Emerging evidence also highlights epigenetic regulation, noncoding RNAs, and tumor–immune–neural crosstalk as potential therapeutic targets. Collectively, these findings position cancer pain as a disorder of aberrant tumor–nerve–immune signaling. Effective management requires precision strategies integrating mechanism-guided pharmacology, neuromodulation, and supportive care. This review emphasizes the need for translational research to bridge mechanistic discoveries with personalized, multimodal interventions in oncology.

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Publication Date
Wed Oct 07 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Correlation of Toxoplasmosis Seroprevalence and Serum Level of Interleukin-10 in Iraqi Breast Cancer Women
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Toxoplasmosis is regarded as one of the most important global life-threatening diseases in immune-compromised people. The intracellular protozoon Toxoplasma gondii is the causative pathogen of toxoplasmosis. Aim of this study is to investigate the possible association between T. gondii infection and breast cancer (BC) in Iraqi women, also to assess the effect of T. gondiion interleukin 10 (IL-10) of the immune response. By ELISA method, blood samples from 81 women with breast cancer and 60 apparently healthy women have been examined for presence of anti-toxoplasmaantibodies, also the levels of serum IL-10 were estimated in these subjects. Results showed that women with BC had the highest prevalence rate of toxoplasmosis. The anti- T.gondii

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Publication Date
Sat Aug 01 2026
Journal Name
Journal Of Taibah University Medical Sciences
The key role of RANKL and OPG as molecular biomarkers in bone remodeling associated with different grafts regarding socket preservation: A systematic review
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Objectives: Bone remodeling usually depends on complex molecular signaling, where receptor activator of NF-B ligand (RANKL) and osteoprotegerin (OPG) serve as key modulators that regulate osteoclastogenesis and overall bone metabolism process. This systematic review aimed to evaluate the influence of different graft materials on RANKL and OPG expression following alveolar ridge preservation. Methods: An electronic search of the literature was performed in Embase via Ovid, Medline via Ovid, CINAHL, Scopus and Web of Science databases, in addition to a manual search regarding all related articles. PRISMA guidelines and PICO framework were followed in this systematic review. The inclusion criteria were limited to English-published studies

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Publication Date
Mon Feb 21 2022
Journal Name
Iraqi Journal For Computer Science And Mathematics
Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

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Publication Date
Wed Dec 31 2025
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Arrestin Beta-2 in Prostate Cancer and its Relationship with Trace Elements
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Background: Prostate cancer (PCa) is the most prevalent non-cutaneous malignancy and the second-leading cause of cancer-relatedmortality among males. Cancer is just one of the several disorders that may be linked to variations in trace element concentrations.Objective: To evaluate serum arrestin β-2 as a prostate cancer tumor marker and its association with trace elements.Methods: This case- control study was carried out at the Department of Biochemistry, College of Medicine, University of Baghdad and at the Urology department, Ghazi Al-Hariri Hospital for Surgical Specialities during the period from March 2022 to May 2023. In this case-control study 120 males were enrolled: Sixty men with newly diagnosed primary prostate cancer (P

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Using jack knife to estimation logistic regression model for Breast cancer disease
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It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Using jack knife to estimation logistic regression model for Breast cancer disease
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It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

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Publication Date
Tue Jan 17 2017
Journal Name
British Journal Of Cancer
Aurora B expression modulates paclitaxel response in non-small cell lung cancer
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Publication Date
Mon Mar 23 2020
Journal Name
International Journal Of Nanoscience
Gold Nanoparticles Synthesis Using Environmentally Friendly Approach for Inhibition Human Breast Cancer
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In this study, gold nanoparticles were synthesized in a single step biosynthetic method using aqueous leaves extract of thymus vulgaris L. It acts as a reducing and capping agent. The characterizations of nanoparticles were carried out using UV-Visible spectra, X-ray diffraction (XRD) and FTIR. The surface plasmon resonance of the as-prepared gold nanoparticles (GNPs) showed the surface plasmon resonance centered at 550[Formula: see text]nm. The XRD pattern showed that the strong four intense peaks indicated the crystalline nature and the face centered cubic structure of the gold nanoparticles. The average crystallite size of the AuNPs was 14.93[Formula: see text]nm. Field emission scanning electron microscope (FESEM) was used to s

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Publication Date
Thu Apr 11 2019
Journal Name
Scientific Reports
Small-Molecule Ferroptotic Agents with Potential to Selectively Target Cancer Stem Cells
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Abstract<p>Effective management of advanced cancer requires systemic treatment including small molecules that target unique features of aggressive tumor cells. At the same time, tumors are heterogeneous and current evidence suggests that a subpopulation of tumor cells, called tumor initiating or cancer stem cells, are responsible for metastatic dissemination, tumor relapse and possibly drug resistance. Classical apoptotic drugs are less effective against this critical subpopulation. In the course of generating a library of open-chain epothilones, we discovered a new class of small molecule anticancer agents that has no effect on tubulin but instead kills selected cancer cell lines by harnessing reactive oxygen </p> ... Show More
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