Search results for: ovarian epithelial cancer

Authors: Nadia H. Mohammed, Anmar Al-Taie, Fadia H. Al-Sultany

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Although breast cancer prevalence continues to increase, mortality has been decreasing as a result of early detection and improvement in adjuvant systemic therapy. Nevertheless, this disease required further efforts to understand and identify the associated potential risk factors that could play a role in the prevalence of this malignancy among Iraqi women. The objective of this study was to assess the perception of certain predictive risk factors on the prevalence of breast cancer types among a sample of Iraqi women diagnosed with breast cancer. This was a retrospective observational study carried out at National Cancer Research Center in College of Medicine, Baghdad University from November 2017 to January 2018. Data of 100 patients with breast cancer whose biopsies examined in the National Cancer Research Center were included in this study. Data were collected to structure a detailed assessment regarding the patients’ demographic, medical and cancer records. The majority of study participants (94%) suffered from ductal breast cancer with mean age 49.57 years. Among those women, 48.9% were obese with body mass index (BMI) 35 kg/m². 68.1% of them had positive family history of breast cancer and 66% had low parity. 40.4% had stage II ductal breast cancer followed by 25.5% with stage III. It was found that 59.6% and 68.1% had positive oestrogen receptor sensitivity and positive human epidermal growth factor (HER2/neu) receptor sensitivity respectively. In regard to the impact of prediction of certain variables on the incidence of ductal breast cancer, positive family history of breast cancer (P < 0.0001), low parity (P< 0.0001), stage I and II breast cancer (P = 0.02) and positive HER2/neu status (P < 0.0001) were significant predictive factors among the study participants. The results from this study provide relevant evidence for a significant positive and potential association between certain risk factors and the prevalence of breast cancer among Iraqi women.

Keywords: Ductal breast cancer, hormone sensitivity, Iraq, risk factors.

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Authors: E. B. Jo, J. H. Lee, J. Y. Park, S. M. Kim

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In this study, we present an advanced detection technique for mass type breast cancer based on texture information of organs. The proposed method detects the cancer areas in three stages. In the first stage, the midpoints of mass area are determined based on AHE (Adaptive Histogram Equalization). In the second stage, we set the threshold coefficient of homogeneity by using MLE (Maximum Likelihood Estimation) to compute the uniformity of texture. Finally, mass type cancer tissues are extracted from the original image. As a result, it was observed that the proposed method shows an improved detection performance on dense breast tissues of Korean women compared with the existing methods. It is expected that the proposed method may provide additional diagnostic information for detection of mass-type breast cancer.

Keywords: Mass Type Breast Cancer, Mammography, Maximum Likelihood Estimation (MLE), Ranklets, SVM

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Authors: Souâd Demigha

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Early detection of breast cancer is considered as a major public health issue. Breast cancer screening is not generalized to the entire population due to a lack of resources, staff and appropriate tools. Systematic screening can result in a volume of data which can not be managed by present computer architecture, either in terms of storage capabilities or in terms of exploitation tools. We propose in this paper to design and develop a data warehouse system in radiology-senology (DWRS). The aim of such a system is on one hand, to support this important volume of information providing from multiple sources of data and images and for the other hand, to help assist breast cancer screening in diagnosis, education and research.

Keywords: Breast cancer screening, data warehouse, diagnosis, education, research.

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Authors: W. Kaowumpai, D. Koolpiruck, K. Viravaidya

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Female breast cancer is the second in frequency after cervical cancer. Surgery is the most common treatment for breast cancer, followed by chemotherapy as a treatment of choice. Although effective, it causes serious side effects. Controlled-release drug delivery is an alternative method to improve the efficacy and safety of the treatment. It can release the dosage of drug between the minimum effect concentration (MEC) and minimum toxic concentration (MTC) within tumor tissue and reduce the damage of normal tissue and the side effect. Because an in vivo experiment of this system can be time-consuming and labor-intensive, a mathematical model is desired to study the effects of important parameters before the experiments are performed. Here, we describe a 3D mathematical model to predict the release of doxorubicin from pluronic gel to treat human breast cancer. This model can, ultimately, be used to effectively design the in vivo experiments.

Keywords: Breast Cancer, Doxorubicin, Controlled ReleaseSystem, Diffusion and Convection Equation.

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Authors: Mohammad Darzi, Ali AsgharLiaei, Mahdi Hosseini, HabibollahAsghari

Abstract:

This article addresses feature selection for breast cancer diagnosis. The present process contains a wrapper approach based on Genetic Algorithm (GA) and case-based reasoning (CBR). GA is used for searching the problem space to find all of the possible subsets of features and CBR is employed to estimate the evaluation result of each subset. The results of experiment show that the proposed model is comparable to the other models on Wisconsin breast cancer (WDBC) dataset.

Keywords: Case-based reasoning; Breast cancer diagnosis; Genetic algorithm; Wrapper feature selection

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Authors: Alshalaa A. Shleeg, Issmail M. Ellabib

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Breast cancer is a major health burden worldwide being a major cause of death amongst women. In this paper, Fuzzy Inference Systems (FIS) are developed for the evaluation of breast cancer risk using Mamdani-type and Sugeno-type models. The paper outlines the basic difference between Mamdani-type FIS and Sugeno-type FIS. The results demonstrated the performance comparison of the two systems and the advantages of using Sugeno- type over Mamdani-type.

Keywords: Breast cancer diagnosis, Fuzzy Inference System (FIS), Fuzzy Logic, fuzzy intelligent technique.

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Authors: Kefaya Qaddoum

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The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises a machine learning system called conformal prediction (CP), in order to assign consistent confidence measures to predictions, which are combined with GRNN. We apply the resulting algorithm to the problem of breast cancer diagnosis. The results show that the prediction constructed by this method is reasonable and could be useful in practice.

Keywords: Neural network, conformal prediction, cancer classification, regression.

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Authors: Sharareh Sharifi, Pargol Ghavam Mostafavi, Ali Mashinchian Moradi, Mohammad Hadi Givianrad, Hassan Niknejad

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Marine organisms such as soft coral, sponge, ascidians, and tunicate containing rich source of natural compound have been studied in last decades because of their special chemical compounds with anticancer properties. The aim of this study was to investigate anti-cancer property of ethyl acetate extracted from marine sea pen Virgularia gustaviana found from Persian Gulf coastal (Bandar Abbas). The extraction processes were carried out with ethyl acetate for five days. Thin layer chromatography (TLC) and high-performance liquid chromatography (HPLC) were used for qualitative identification of crude extract. The viability of HeLa and MDA-Mb-231 cancer cells was investigated using MTT assay at the concentration of 25, 50, and a 100 µl/ml of ethyl acetate is extracted. The crude extract of Virgularia gustaviana demonstrated ten fractions with different Retention factor (Rf) by TLC and Retention time (Rt) evaluated by HPLC. The crude extract dose-dependently decreased cancer cell viability compared to control group. According to the results, the ethyl acetate extracted from Virgularia gustaviana inhibits the growth of cancer cells, an effect which needs to be further investigated in the future studies.

Keywords: Virgularia gustaviana, Cembrane Diterpene, anti-cancer, HeLa cancer Cell, MDA-Md-231 Cancer cell.

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: Artificial neural networks, breast cancer, cancer dataset, classifiers, cervical cancer, F-score, logistic regression, machine learning, precision, recall, support vector machine.

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Authors: Chi-Shan Chen, Mao-Chou Hsu, Feng-Chuan Pan

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The incidence of oral cancer in Taiwan increased year by year. It replaced the nasopharyngeal as the top incurrence among head and neck cancers since 1994. Early examination and earlier identification for earlier treatment is the most effective medical treatment for these cancers. Although the government fully subsidized the expenses with tremendous promotion program for oral cancer screening, the citizen-s participation remained low. Purpose of this study is to understand the factors affecting the citizens- behavior intensions of taking an oral cancer screening. Based on the Theory of Planned Behavior, this study adopted four distinctive variables in explaining the captioned behavior intentions.700 questionnaires were dispatched with 500 valid responses or 71.4% returned by the citizens with an age 30 or above from the eastern counties of Taiwan. Test results has shown that attitude toward, subjective norms of, and perceived behavioral control over the oral cancer screening varied from some demographic factors to another. The study proofed that attitude toward, subjective norms of, and perceived behavioral control over the oral cancer screening had positive impacts on the corresponding behavior intention. The test concluded that the theory of planned behavior was appropriate as a theoretical framework in explaining the influencing factors of intentions of taking oral cancer screening. This study suggested the healthcare professional should provide high accessibility of screening services other than just delivering knowledge on oral cancer to promote the citizens- intentions of taking the captioned screening. This research also provided a practical implication to the healthcare professionals when formulating and implementing promotion instruments for lifting the screening rate of oral cancer.

Keywords: Theory of planned behavior, oral cancer, cancer screening

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Authors: Fatahian Dehkordi RF., Parchami A.

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Design of experiments made for correlated the hormonal activity of steroids and their effect on the vaginal structure properties. Vaginal wall consists of distinct layers of cells which strongly differ regarding growth in answer to steroid hormones. The presence study carried out for functional evaluation and sustained replacement effect of the reproductive hormones on the vaginal morphometry in the rabbit. Rabbits were maintained control (Co) or ovariectomized (Ovz) and continuously treated with estradiol (Ovz E) and estradiol mixture with testosterone (Ovz ET). Relative to control rabbits with the distinct tissue distribution pattern, ovariectomized animals displayed declined epithelial thickness and atrophy of the muscularis layer that cause the vaginal wall thinning. Estradiol treatment of Orz rabbits inverted these changes to status of the preovariectomy. Histometric measurements in Ovz ET group completely including of thickness of the epithelial and muscular layers was greater in comparison to that of control animals.

Keywords: Vagina, Ovariectomy, Rabbit, Morphometry

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Authors: Marwa I. Shabayek, Ola A. Said, Hanan A. Attaia, Heba A. Awida

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Bladder carcinoma is an important worldwide health problem. Both cystoscopy and urine cytology used in detecting bladder cancer suffer from drawbacks where cystoscopy is an invasive method and urine cytology shows low sensitivity in low grade tumors. This study validates easier and less time-consuming techniques to evaluate the value of combined use of angiogenin and clusterin in comparison and combination with voided urine cytology in the detection of bladder cancer patients. This study includes malignant (bladder cancer patients, n= 50), benign (n=20) and healthy (n=20) groups. The studied groups were subjected to cystoscopic examination, detection of bilharzial antibodies, urine cytology, and estimation of urinary angiogenin and clusterin by ELISA. The overall sensitivity and specificity were 66% and 75% for angiogenin, 70% and 82.5% for clusterin and 46% and 80% for voided urine cytology. Combined sensitivity of angiogenin and clusterin with urine cytology increased from 82 to 88%. 

Keywords: Angiogenin, Bladder Cancer, Clusterin, Cytology.

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Authors: F. Arıkan, Z. Karakus

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Cancer is a widespread disease in the world and is the third reason of deaths among the chronic diseases. Educating patients and caregivers has a vital role for empowering them in managing disease and treatment's symptoms. Informing of the patients about their disease and treatment process decreases patient's distress and decisional conflicts, improves wellbeing of them, increase success of the treatment and survival. In this era, technological education methods are used for patients that have different chronic disease. Many studies indicated that especially web based patient education such as chronic obstructive lung disease; heart failure is more effective than printed materials. Web based education provide easiness to patients while they are reaching health services. It also has more advantages because of it decreases health cost and requirement of staff. It is thought that web based education may be beneficial method for cancer patient's empowerment in coping with the disease's symptoms. The aim of the study is evaluate the effectiveness of web based education for cancer patients' clinical outcomes.

Keywords: Cancer Patients, E-Learning, Nursing, Web Based Education.

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Authors: Ç. Erdoğan, T. Turan

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Pediatric cancer patients experience multiple distressing, challenges, physical symptom such as fatigue, pain, sleep disturbance, and balance impairment that continue years after treatment completion. In recent years, yoga is often used in children with cancer to cope with these symptoms. Yoga practice is defined as a unique physical activity that combines physical practice, breath work and mindfulness/meditation. Yoga is an increasingly popular mind-body practice also characterized as a mindfulness mode of exercise. This study aimed to evaluate the impact of yoga intervention of children with cancer. This article planned searching the literature in this field. It has been determined that individualized yoga is feasible and provides benefits for inpatient children, improves health-related quality of life, physical activity levels, physical fitness. After yoga program, children anxiety score decreases significantly. Additionally, individualized yoga is feasible for inpatient children receiving intensive chemotherapy. As a result, yoga is an alternative and complementary medicine that can be safely used in children with cancer.

Keywords: Cancer treatment, children, nursing, yoga.

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Authors: Heba F. Hozyen, Hodallah H. Ahmed, S. I. A. Shalaby, G. E. S. Essawy

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Biochemical and hormonal changes that occur in both follicular fluid and blood are involved in the control of ovarian physiology. The present study was conducted on follicular fluid and serum samples obtained from 708 buffaloes. Samples were examined for estradiol, progesterone, and cholesterol concentrations in relation to seasonal changes, ovarian follicular size, and stage of estrous cycle. The obtained results revealed that follicular fluid and serum levels of estradiol, progesterone, and cholesterol were significantly lower during summer and autumn when compared to winter and spring seasons. With the increase in follicular size, the follicular fluid levels of progesterone and cholesterol were significantly decreased, while estradiol levels were significantly increased. Estradiol and progesterone levels were significantly higher in follicular fluid than blood, while cholesterol was significantly lower in follicular fluid than serum. In conclusion, the current study threw a light on the hormonal changes in the follicular fluid and blood under the effect of heat stress which could be related to the low fertility of buffalo in the summer.

Keywords: Buffalo, follicular fluid, follicular development, seasonal changes, steroids.

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Authors: Laila Seada, Hanan Oreiby, Fawaz Al Rashid, Ashraf Negm

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Background and Objective: In most areas of the world, the incidence of thyroid cancer has been increasing over the last decade, mostly due to a combination of early detection of the neoplasm resulting from sensitive procedures and increased population exposure to radiation and unrecognized carcinogens. Methods: Cases of thyroid cancer have been retrieved from the cancer registry at King Khalid Hospital during the period from August 2012 to April 2016. Age, gender and histopathologic types have been recorded. Results: Thyroid carcinoma ranked as the second most common malignancy in females (25%) after breast cancer (31%). It constituted 20.8% of all newly diagnosed cancer cases. As for males, it ranked the 4^th type of malignancy after gastrointestinal cancer, lymphomas and soft tissue sarcomas. Mean age for females and males was 38.7 +/- 13.2 and 60.25 +/- 11.5 years, respectively, and the difference between the two groups was statistically significant (p value = 0.0001). Fifty-five (82%) were papillary carcinomas including 10 follicular variant of papillary (FVPC), and eight papillary micro carcinomas (PMC) and two tall cell/oncocytic variants. Follicular carcinomas constituted two (3.1%), while two (3.1%) were anaplastic, and two (3.1%) were medullary. Conclusion: Thyroid cancer incidence in Hail is ranking as the 2^nd most common female malignancy similar to other regions in the Kingdom. However, this high incidence contrasts with much lower rates worldwide.

Keywords: Thyroid, Hail, papillary, micro carcinoma.

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Authors: Firas Gerges, Frank Y. Shih

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Malignant Melanoma, known simply as Melanoma, is a type of skin cancer that appears as a mole on the skin. It is critical to detect this cancer at an early stage because it can spread across the body and may lead to the patient death. When detected early, Melanoma is curable. In this paper we propose a deep learning model (Convolutional Neural Networks) in order to automatically classify skin lesion images as Malignant or Benign. Images underwent certain pre-processing steps to diminish the effect of the normal skin region on the model. The result of the proposed model showed a significant improvement over previous work, achieving an accuracy of 97%.

Keywords: Deep learning, skin cancer, image processing, melanoma.

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Authors: Carlos Huertas, Reyes Juarez-Ramirez

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Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: Feature selection, mass spectrometry, biomarker discovery, cancer.

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Authors: Congo Tak Shing Ching, Hong-Sheng Chen, Tai-Ping Sun, Hsiu-Li Shieh

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Nuclear matrix protein 22 (NMP22) is a FDA approved biomarker for bladder cancer. The objective of this study is to develop a simple NMP22 immumosensor (NMP22-IMS) for accurate measurement of NMP22. The NMP22-IMS was constructed with NMP22 antibody immobilized on screen-printed carbon electrodes. The construction procedures and antibody immobilization are simple. Results showed that the NMP22-IMS has an excellent (r2³0.95) response range (20 – 100 ng/mL). In conclusion, a simple and reliable NMP22-IMS was developed, capable of precisely determining urine NMP22 level.

Keywords: Bladder Cancer, Immunosensor, Impedance, NMP22

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Authors: Liping Jing, Michael K. Ng, Tieyong Zeng

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Microarray data profiles gene expression on a whole genome scale, therefore, it provides a good way to study associations between gene expression and occurrence or progression of cancer. More and more researchers realized that microarray data is helpful to predict cancer sample. However, the high dimension of gene expressions is much larger than the sample size, which makes this task very difficult. Therefore, how to identify the significant genes causing cancer becomes emergency and also a hot and hard research topic. Many feature selection algorithms have been proposed in the past focusing on improving cancer predictive accuracy at the expense of ignoring the correlations between the features. In this work, a novel framework (named by SGS) is presented for stable gene selection and efficient cancer prediction . The proposed framework first performs clustering algorithm to find the gene groups where genes in each group have higher correlation coefficient, and then selects the significant genes in each group with Bayesian Lasso and important gene groups with group Lasso, and finally builds prediction model based on the shrinkage gene space with efficient classification algorithm (such as, SVM, 1NN, Regression and etc.). Experiment results on real world data show that the proposed framework often outperforms the existing feature selection and prediction methods, say SAM, IG and Lasso-type prediction model.

Keywords: Gene Selection, Cancer Prediction, Lasso, Clustering, Classification.

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Authors: A. Doosti, P. Ghasemi Dehkordi, M. Zamani, S. Taheri, M. Banitalebi, M. Mahmoudzadeh

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The p53 tumor suppressor gene plays two important roles in genomic stability: blocking cell proliferation after DNA damage until it has been repaired, and starting apoptosis if the damage is too critical. Codon 72 exon4 polymorphism (Arg72Pro) of the P53 gene has been implicated in cancer risk. Various studies have been done to investigate the status of p53 at codon 72 for arginine (Arg) and proline (Pro) alleles in different populations and also the association of this codon 72 polymorphism with various tumors. Our objective was to investigate the possible association between P53 Arg72Pro polymorphism and susceptibility to colorectal cancer among Isfahan and Chaharmahal Va Bakhtiari (a part of south west of Iran) population. We investigated the status of p53 at codon 72 for Arg/Arg, Arg/Pro and Pro/Pro allele polymorphisms in blood samples from 145 colorectal cancer patients and 140 controls by Nested-PCR of p53 exon 4 and digestion with BstUI restriction enzyme and the DNA fragments were then resolved by electrophoresis in 2% agarose gel. The Pro allele was 279 bp, while the Arg allele was restricted into two fragments of 160 and 119 bp. Among the 145 colorectal cancer cases 49 cases (33.79%) were homozygous for the Arg72 allele (Arg/Arg), 18 cases (12.41%) were homozygous for the Pro72 allele (Pro/Pro) and 78 cases (53.8%) found in heterozygous (Arg/Pro). In conclusion, it can be said that p53Arg/Arg genotype may be correlated with possible increased risk of this kind of cancers in south west of Iran.

Keywords: TP53, Polymorphism, Colorectal Cancer, Iran

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Authors: Rozhgar A. Khailany, Mehri Igci, Emine Bayraktar, Sakip Erturhan, Metin Karakok, Ahmet Arslan

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Kidney cancer is the most lethal urological cancer accounting for 3% of adult malignancies. VHL, a tumor-suppressor gene, is best known to be associated with renal cell carcinoma (RCC). The VHL functions as negative regulator of hypoxia inducible factors. Recent sequencing efforts have identified several novel frequent mutations of histone modifying and chromatin remodeling genes in ccRCC (clear cell RCC) including PBRM1 and SETD2. The PBRM1 gene encodes the BAF180 protein, which involved in transcriptional activation and repression of selected genes. SETD2 encodes a histone methyltransferase, which may play a role in suppressing tumor development. In this study, RNAs of 30 paired tumor and normal samples that were grouped according to the types of kidney cancer and clinical characteristics of patients, including gender and average age were examined by RT-PCR, SSCP and sequencing techniques. VHL, PBRM1 and SETD2 expressions were relatively down-regulated. However, statistically no significance was found (Wilcoxon signed rank test, p>0.05). Interestingly, no mutation was observed on the contrary of previous studies. Understanding the molecular mechanisms involved in the pathogenesis of RCC has aided the development of molecular-targeted drugs for kidney cancer. Further analysis is required to identify the responsible genes rather than VHL, PBRM1 and SETD2 in kidney cancer.

Keywords: Kidney cancer, molecular biomarker, expression analysis, mutation screening.

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Authors: Siddhant Rao

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Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.

Keywords: Object detection, histopathology, breast cancer, mitotic count, deep learning, computer vision.

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Authors: B. Thanasansomboon, S. Choemprayong, N. Parinyanitikul, U. Tanlamai

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Being diagnosed with metastatic breast cancer, the patients as well as their caretakers are affected physically and mentally. Although the medical systems in Thailand have been attempting to improve the quality and effectiveness of the treatment of the disease in terms of physical illness, the success of the treatment also depends on the quality of mental health. Metastatic breast cancer patients have found that social support is a key factor that helps them through this difficult time. It is recognized that social support in different dimensions, including emotional support, social network support, informational support, instrumental support and appraisal support, are contributing factors that positively affect the quality of life of patients in general, and it is undeniable that social support in various forms is important in promoting the quality of life of metastatic breast patients. However, previous studies have not been dedicated to investigating their quality of life concerning affective, cognitive, and behavioral outcomes. Therefore, this study aims to develop integrated social support through social networks to improve the quality of life of metastatic breast cancer patients in Thailand.

Keywords: Social support, metastatic breast cancer, quality of life, social network.

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Authors: M. Sadeghi, H. Pezeshk, R. Tusserkani, A. Sharifi Zarchi, A. Malekpour, M. Foroughmand, S. Goliaei, M. Totonchi, N. Ansari–Pour

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The role and relative importance of intrinsic and extrinsic factors in the development of complex diseases such as cancer still remains a controversial issue. Determining the amount of variation explained by these factors needs experimental data and statistical models. These models are nevertheless based on the occurrence and accumulation of random mutational events during stem cell division, thus rendering cancer development a stochastic outcome. We demonstrate that not only individual genome sequencing is uninformative in determining cancer risk, but also assigning a unique genome sequence to any given individual (healthy or affected) is not meaningful. Current whole-genome sequencing approaches are therefore unlikely to realize the promise of personalized medicine. In conclusion, since genome sequence differs from cell to cell and changes over time, it seems that determining the risk factor of complex diseases based on genome sequence is somewhat unrealistic, and therefore, the resulting data are likely to be inherently uninformative.

Keywords: Cancer risk, extrinsic factors, genome sequencing, intrinsic factors.

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Authors: Arundhati Devi Maibam, K. Ingocha Singh

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Cervical cancer is preventable if detected early. Determination of risk factors is essential to plan screening programmes to prevent the disease. To study the demographic risk factors of cervical cancer among Manipuri women, information on age, marital status, educational level, monthly family income and socioeconomic status were collected through a pre-tested interview schedule. In this study, 64 incident cases registered at the RT Dept, RIMS (Regional Institute of Medical Sciences), Imphal, Manipur, India during 2008-09 participated. Data were entered in Microsoft Excel and the results were expressed in percentages. Among the 64 patients with cervical cancer, 56 (88.9%) were in the age group of 40+ years. The majority of the patients were from rural areas (68.75%) and 31.25% were from urban areas. The majority of the patients were Hindus (73%), 55(85.9%) were of low educational level, 43(67.2%) were married, and 36 (56.25%) belonged to Class IV socioeconomic status. In conclusion, if detected early, cervical cancer is preventable and curable. The potential risk factors need to be identified and women in the risk group need to be motivated for screening. Affordable screening programmes and health care resources will help in lessening the burden of the disease.

Keywords: Cervical cancer, Manipuri women, RIIMS, Socio-demographic risk factors.

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Authors: C. Gunavathi, K. Premalatha

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Microarray technology is universally used in the study of disease diagnosis using gene expression levels. The main shortcoming of gene expression data is that it includes thousands of genes and a small number of samples. Abundant methods and techniques have been proposed for tumor classification using microarray gene expression data. Feature or gene selection methods can be used to mine the genes that directly involve in the classification and to eliminate irrelevant genes. In this paper statistical measures like T-Statistics, Signal-to-Noise Ratio (SNR) and F-Statistics are used to rank the genes. The ranked genes are used for further classification. Particle Swarm Optimization (PSO) algorithm and Shuffled Frog Leaping (SFL) algorithm are used to find the significant genes from the top-m ranked genes. The Naïve Bayes Classifier (NBC) is used to classify the samples based on the significant genes. The proposed work is applied on Lung and Ovarian datasets. The experimental results show that the proposed method achieves 100% accuracy in all the three datasets and the results are compared with previous works.

Keywords: Microarray, T-Statistics, Signal-to-Noise Ratio, FStatistics, Particle Swarm Optimization, Shuffled Frog Leaping, Naïve Bayes Classifier.

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Authors: Ali M. Mutlag, Yang Zhiqiang, Meng Jiaren, Zhang Jingyan, Li Jianxi

Abstract:

The object of this study was to investigate several hormones correlated to the reproduction and inhibin A, inhibin B and NO levels in the infertile dairy cows as attempt to illustrate the physiological causes of dairy cows infertility.

40 Holstein cow (21 infertile and 19 fertile) were used at estrous phase of the cycle, Hormones FSH, LH, E2, Testosterone, were measured using ELISA method. inhibin A and B also estimated by ELISA method, Nitric oxide was measured by Greiss reagent method.

The results showed different concentrations of the hormone in which FSH illustrated significantly higher concentration in the infertile cows than fertile cows (P<0.05). LH and E2 showed significant decrease in the infertile cows than the fertile cows (P<0.05), no significant difference appeared in testosterone concentrations in the fertile cows and infertile cows (P>0.05). The both inhibins A and B showed significant P<0.05 decrease concentrations in the infertile cows also NO showed clearly significant decrease P<0.05 in the infertile cows.

In conclusion, the present study approved the poorly ovarian activities and reproduction disturbance of infertile cows in spite of trigger estrous signs, the study confirmed a positive correlation between inhibins and NO to regulate the ovarian physiology. These inhibins represent effective markers of dairy cow infertility.

Keywords: Cows, Inhibin (A, B), Infertility, Nitric oxide (NO).

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Authors: M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani, S. Zolghadri, S. Kakaei

Abstract:

Despite the appropriate characteristics of ¹⁷⁷Lu and DOTATOC, to our best knowledge, the therapeutic benefit of ¹⁷⁷Lu-DOTATOC complex in breast cancer has not been reported until now. In this study, biodistribution of ¹⁷⁷Lu-DOTA-TOC in mouse tumor model for evaluation of possible utilization of this complex in breast cancer treatment was investigated.¹⁷⁷Lu was prepared with the specific activity of 2.6-3 GBq.mg^-1 and radionuclidic purity higher than 99%. The radiolabeled complex was prepared in the optimized conditions with the radiochemical purity higher than 99%. The final solution was injected to the BALB/c mice with adenocarcinoma breast cancer. The biodistribution results showed major accumulation in the kidneys as the major excretion route and the somatostatin receptor-positive tissues such as pancreas compared with the other tissues. Also, significant uptake was observed in tumor even in longer time after injection. According to the results obtained in this research study, somatostatin receptors expressed in breast cancers can be targeted with DOTATOC analogues especially with ¹⁷⁷Lu-DOTATOC as an ideal therapeutic agent.

Keywords: 177Lu, DOTATOC, adenocarcinoma, breast cancer, BALB/c mice.

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Authors: Chien-Hung Huang, Chia-Wei Weng, Chang-Chih Chiang, Shih-Hua Wu, Chih-Hsien Huang, Ka-Lok Ng

Abstract:

MicroRNAs (miRNAs) are a class of non-coding RNAs that hybridize to mRNAs and induce either translation repression or mRNA cleavage. Recently, it has been reported that miRNAs could possibly play an important role in human diseases. By integrating miRNA target genes, cancer genes, miRNA and mRNA expression profiles information, a database is developed to link miRNAs to cancer target genes. The database provides experimentally verified human miRNA target genes information, including oncogenes and tumor suppressor genes. In addition, fragile sites information for miRNAs, and the strength of the correlation of miRNA and its target mRNA expression level for nine tissue types are computed, which serve as an indicator for suggesting miRNAs could play a role in human cancer. The database is freely accessible at http://ppi.bioinfo.asia.edu.tw/mirna_target/index.html.

Keywords: MicroRNA, miRNA expression profile, mRNAexpression profile, cancer genes, oncogene, tumor suppressor gene

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