Background: The study's objective was to estimate the effects of radiation on testosterone-related hormones and blood components in prostate cancer patients. N Materials and Method: This study aims to investigate the effects of radiation on 20 male prostate cancer patients at the Middle Euphrates Oncology Centre. Blood samples were collected before and after radiation treatment, with a total dose of 60- 70 Gy, The blood parameters were analyzed. The hospital laboratory conducted the blood analysis using an analyzer (Diagon D-cell5D) to test blood components before and after radiation. Hormonal examinations included testosterone levels, using the VIDASR 30 for Multiparametric immunoassay system Results: The study assessed the socio-demography of prostate cancer male patients, revealing that the majority were aged 69.55 t 10.76 years, with a weight of 75.3 t 10.84 Kg and height of 170.50 t 8.70 cm. The stage of cancer was assessed, with 25% of patients being IV and IIV, followed by II, IB, and V. Only one patient was at stage III. The Gleason Score (GS) was used to classify patients, with 40% being given a score of 7, followed by 6, 8, and 9 equally (20%). Total Prostate-specific Antigen (PSA) had a mean value of 12.87 t 2.78. Hematological analysis showed a significant decrease in random blood sugar levels, white blood cells, lymphocytes platelets, and hemoglobin levels after radiotherapy. Testosterone levels also declined after radiotherapy fractions. However, kidney functions like urea and creatinine levels increased after pelvic irradiation Conclusion: The study found that radiation treatment for prostate cancer significantly impacted blood components and hormones associated with testosterone. It led to reduced levels of random blood sugar, white blood cells, lymphocytes, platelets, haemoglobin, and testosterone. Additionally, high-energy therapeutic x-rays increased_ levels of urea and creatinine, indicating the need for strict monitoring and management of adverse effects.
The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone
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Breast cancer (BC) is the most commonly diagnosed cancer in women. The metabolism of iron is closely regulated by hepcidin which exerts its action by interacting with a ferroportin.
The aim of the present study was to assess the alterations in the levels of some serum biomarkers that have a role in iron homeostasis (hepcidin and ferroportin) in addition to hematological parameters (hemoglobin, leukocyte and platelets count) in different stages of BC.
This study included 66 women with BC. The patients were categorized as follows : group 1 includes :22 patients with stage I disease ,group 2 includes: 22 patients with stage II disease ,and group 3 include: 22 patients with stage III disease .Group 4 includes :22 appare
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Background: Breast cancer is the most common
malignancy affecting females worldwide. The association
of Epstein-Barr virus (EBV) with this cancer is a longstanding
interest to this field.
Aim: to investigate the presence of EBV in breast tumor
tissue in relation to age.
Patients and Methods: Paraffin-embedded tissue blocks
from 45 female patients with breast tumors (ranged in age
from 28 to 85 years) were retrieved. The cases were
grouped into two categories: group (A): included 30 cases
with breast carcinoma and group (B): included 15 cases
with benign breast diseases as a control group .The
expression of EBV protein was examined
immunohistochemically.
Results: Twelve (40%) of the 30 breast canc
Human cytomegalovirus (HCMV) has a worldwide distribution and common infections. The presence of HCMV genome and antigens has been detected in many kinds of human cancers. The proto-oncogene Her2/neu is overexpressed in 25% to 30% of human breast cancers and frequently associated with tumor aggressiveness and worse prognosis. Examination was applied to detect different HCMV antigens and to demonstrate their correlation with Her2/neu overexpression in breast cancer. The present study includes samples from 70 women of 60 breast cancer patients and 10 normal breast tissues. Formalin-fixed paraffin embedded tissue blocks were obtained from each woman according to ethical approval. Human cytomegalovirus early antigen expression was detected in 5
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Background: Breast cancer is the most common
malignancy affecting females worldwide. The association
of Epstein-Barr virus (EBV) with this cancer is a longstanding
interest to this field.
Aim: to investigate the presence of EBV in breast tumor
tissue in relation to age.
Patients and Methods: Paraffin-embedded tissue blocks
from 45 female patients with breast tumors (ranged in age
from 28 to 85 years) were retrieved. The cases were
grouped into two categories: group (A): included 30 cases
with breast carcinoma and group (B): included 15 cases
with benign breast diseases as a control group .The
expression of EBV protein was examined
immunohistochemically.
Results: Twelve (40%) of the 30 breast canc
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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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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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
... Show More
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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Considering the expanding frequency of breast cancer and high incidence of vitamin D3 [25(OH)D3] insufficiently, this investigate pointed to explain a relation between serum [25(OH)D3] (the sunshine vitamin) level and breast cancer hazard. The current study aimed to see how serum levels of each [25(OH)D3], HbA1c%, total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), and triglyceride (TG) were affected a woman’s risk of getting breast cancer. In 40 healthy volunteers and 69 untreated breast cancer patients with clinical and histological evidence which include outpatients and hospitalized admissions patients at the Oncology Center, Medical City / Baghdad - Iraq. Venous blood samp
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