Search results for: cancer prediction

Authors: Satoshi Furukawa, Satomu Morita, Katsuji Nishi, Masahito Hitosugi

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A 75-year-old woman took thyroidectomy forty years previously. Enlarged masses were seen at autopsy just above and below the left clavicle. We proved the diagnosis of papillary thyroid cancer (PTC) and lung metastasis by histological examinations. The prognosis of PTC is excellent; the 10-year survival rate ranges between 85 and 99%. Lung metastases may be found in 10% of the patients with PTC. We report an unusual case of recurrence of PTC with metastasis to the lung.

Keywords: papillary thyroid cancer, lung metastasis, autopsy, histopathological findings

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Authors: Asghar Arif

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Lung cancer has been recognized as one of the greatest common cancers, causing the annual mortality rate of about 1.2 million people in the world. Lung cancer is the most prevalent cancer in men and the third-most common cancer among women (after breast and digestive cancers).Recent evidences have shown the inflammatory process as one of the potential factors of cancer. Tuberculosis (TB), pneumonia, and chronic bronchitis are among the most important inflammation-inducing factors in the lungs, among which TB has a more profound role in the emergence of cancer.TB is one of the important mortality factors throughout the world, and 205,000 death cases are reported annually due to this disease. Chronic inflammation and fibrosis due to TB can induce genetic mutation and alternations. Parenchyma tissue of lung is involved in both diseases of TB and lung cancer, and continuous cough in lung cancer, morphological vascular variations, lymphocytosis processes, and generation of immune system mediators such as interleukins, are all among the factors leading to the hypothesis regarding the role of TB in lung cancer Some reports have shown that the induction of necrosis and apoptosis or TB reactivation, especially in patients with immune-deficiency, may result in increasing IL-17 and TNF_α, which will either decrease P53 activity or increase the expression of Bcl-2, decrease Bax-T, and cause the inhibition of caspase-3 expression due to decreasing the expression of mitochondria cytochrome oxidase. It has been also indicated that following the injection of BCG vaccine, the host immune system will be reinforced, and in particular, the rates of gamma interferon, nitric oxide, and interleukin-2 are increased. Therefore, CD4 + lymphocyte function will be improved, and the person will be immune against cancer.Numerous prospective studies have so far been conducted on the role of TB in lung cancer, and it seems that this disease is effective in that particular cancer.One of the main challenges of lung cancer is its correct and timely diagnosis. Unfortunately, clinical symptoms (such as continuous cough, hemoptysis, weight loss, fever, chest pain, dyspnea, and loss of appetite) and radiological images are similar in TB and lung cancer. Therefore, anti-TB drugs are routinely prescribed for the patients in the countries with high prevalence of TB, like Pakistan. Regarding the similarity in clinical symptoms and radiological findings of lung cancer, proper diagnosis is necessary for TB and respiratory infections due to nontuberculousmycobacteria (NTM). Some of the drug resistive TB cases are, in fact, lung cancer or NTM lung infections. Acid-fast staining and histological study of phlegm and bronchial washing, culturing and polymerase chain reaction TB are among the most important solutions for differential diagnosis of these diseases. Briefly, it is assumed that TB is one of the risk factors for cancer. Numerous studies have been conducted in this regard throughout the world, and it has been observed that there is a significant relationship between previous TB infection and lung cancer. However, to prove this hypothesis, further and more extensive studies are required. In addition, as the clinical symptoms and radiological findings of TB, lung cancer, and non-TB mycobacteria lung infections are similar, they can be misdiagnosed as TB.

Keywords: TB and lung cancer, TB people, TB servivers, TB and HIV aids

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Authors: Yiding Qu, Svetlana V. Komarova

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Chemokines acting through their cognate chemokine receptors guide the directional migration of the cell along the chemokine gradient. Several chemokine receptors were recently identified as non-signaling (decoy), based on their ability to bind the chemokine but produce no measurable signal in the cell. The function of these decoy receptors is not well understood. We examined the expression of a decoy receptor CCRL1 and a signaling receptor that binds to the same ligands, CCR7, in prostate cancer using publically available microarray data (www.oncomine.org). The expression of both CCRL1 and CCR7 increased in an approximately half of prostate carcinoma samples and the majority of metastatic cancer samples compared to normal prostate. Moreover, the expression of CCRL1 positively correlated with the expression of CCR7. These data suggest that CCR7 and CCRL1 can be used as clinical markers for the early detection of transformation from carcinoma to metastatic cancer. In addition, these data support our hypothesis that the non-signaling chemokine receptors actively stimulate cell migration.

Keywords: bioinformatics, cell migration, decoy receptor, meta-analysis, prostate cancer

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Authors: Rhea Kapoor

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Fractal dimension provides a way to characterize non-geometric shapes like those found in nature. The purpose of this research is to estimate Minkowski fractal dimension of human lung images for early detection of lung cancer. Lung cancer is the leading cause of death among all types of cancer and an early histopathological analysis will help reduce deaths primarily due to late diagnosis. A Python application program, PathoPy2.0, was developed for analyzing medical images in pixelated format and estimating Minkowski fractal dimension using a new box-counting algorithm that allows windowing of images for more accurate calculation in the suspected areas of cancerous growth. Benchmark geometric fractals were used to validate the accuracy of the program and changes in fractal dimension of lung images to indicate the presence of issues in the lung. The accuracy of the program for the benchmark examples was between 93-99% of known values of the fractal dimensions. Fractal dimension values were then calculated for lung images, from National Cancer Institute, taken over time to correctly detect the presence of cancerous growth. For example, as the fractal dimension for a given lung increased from 1.19 to 1.27 due to cancerous growth, it represents a significant change in fractal dimension which lies between 1 and 2 for 2-D images. Based on the results obtained on many lung test cases, it was concluded that fractal dimension of human lungs can be used to diagnose lung cancer early. The ideas behind PathoPy2.0 can also be applied to study patterns in the electrical activity of the human brain and DNA matching.

Keywords: fractals, histopathological analysis, image processing, lung cancer, Minkowski dimension

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Authors: Shima Behzadi

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Background: In many human malignant tumors, microRNA expression is aberrant. This study investigates miR-141 as a prognostic marker in colorectal cancer with K-Ras mutation. Materials and methods: In this case-control study, 100 patients, mostly over the age of 50, who were diagnosed with colorectal cancer were selected. The pathology department of the Mostoufi Pathobiology and Genetics Laboratory in Tehran confirmed the presence of colorectal cancer in samples of paraffin-embedded colon tissue. The case group was composed of patients with codon 12 and 13 mutations in exon 2 of the K-Ras gene, while tumor samples of individuals without these mutations in exon 2 of the K-Ras gene were selected as the control group, with patient consent. The changes in the expression of miR-141 were examined in both groups. Results: The study found that 20% of the patients tested positive for codon 12 mutation, and 10% of patients had codon 13 mutation. As a result, in 30 cases, there was a higher level of miR-141 expression. The miR-141 gene expression level in K-Ras positive tumor samples was 1.5 times higher than its expression level in K-Ras negative samples. This increase in expression was statistically significant, with a p-value of less than 0.001, indicating that the observed results are highly statistically significant. Conclusion: The study revealed that the incidence of typical K-Ras gene mutations among the colorectal cancer patients in the sample matches the national average in Iran. Additionally, the expression of miR-141 can serve as a useful biomarker to aid in the prognosis of colorectal cancer.

Keywords: colorectal cancer, K-Ras gene, miR-141 marker, real time PCR, electrophoresis

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Authors: Yasser A. Ahmed, Juleen M Dickson, Evan S. Krystofiak, Julie A. Oliver

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Cancer cells urgently need folate to support their rapid division. Folate receptors (FR) are over-expressed on a wide range of tumor cells, including breast cancer cells. FR are distributed over the entire surface of cancer cells, but are polarized to the apical surface of normal cells. Targeting of cancer cells using specific surface molecules such as folate receptors may be one of the strategies used to kill cancer cells without hurting the neighing normal cells. The aim of the current study was to try a method of SEM detecting FR in a murine breast cancer cell model (4T1 cells) using secondary antibody conjugated to gold or gold-coated magnetite nanoparticles. 4T1 cells were suspended in RPMI medium witth FR antibody and incubated with secondary antibody for fluorescence microscopy. The cells were cultured on 30mm Thermanox coverslips for 18 hours, labeled with FR antibody then incubated with secondary antibody conjugated to gold or gold-coated magnetite nanoparticles and processed to scanning electron microscopy (SEM) analysis. The fluorescence microscopy study showed strong punctate FR expression on 4T1 cell membrane. With SEM, the labeling with gold or gold-coated magnetite conjugates showed a similar pattern. Specific labeling occurred in nanoparticle clusters, which are clearly visualized in backscattered electron images. The 4T1 tumor cell model may be useful for the development of FR-targeted tumor therapy using gold-coated magnetite nano-particles.

Keywords: cancer cell, nanoparticles, cell culture, SEM

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Authors: Ya-Ching Wang, Yi-Maun Subeq

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Background: There is a lack of evidence to understand differences in risk for developing breast cancer between sexual minority women and heterosexual women in Taiwan. The purpose of this study is to compare differences in risk for developing breast cancer between the two groups of Taiwanese women. Methods: An online cross-sectional survey was used to collect data. A total of 238 Taiwanese women (mean age 30.69 years old, SD=8.231, range 20-60) were recruited between December 2016 and February 2017, including 115 heterosexual women and 123 sexual minority women. Results: There were no significant differences between heterosexual women and sexual minority women in body mass index, history of non-malignant breast disease, age at menarche and menopause, use of hormone replacement therapy, use of hormone replacement therapy, nor the prevalence of breast cancer. The sexual minority women had higher rates of current drinking, smoking and using breast-bindings and also reported exercise more a week; the heterosexual women had higher rates of pregnancy, children, breastfeed, miscarriages, abortion and use of birth control pills. Discussion/Conclusion: There were significant differences between heterosexual women and sexual minority women in reproductive factors and behavioral risk factors for the development of breast cancer. In particular, the finding that the sexual minority women had higher rate of using breast-bindings (56.6%) than the heterosexual women (4.7%) should be further explore, in order to understand whether long-term breast compression is associated with the development of breast cancer.

Keywords: breast cancer, risk, sexual orientation, Taiwan

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Authors: Radia Chemlal, Salim Mehenni, Dahbia Leila Anes-boulahbal, Mohamed Kherat, Nabil Mameri

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The application of the electric field is considered to be a very promising method in cancer therapy. Indeed, cancer cells are very sensitive to the electric field, although the cellular response is not entirely clear. The tests carried out consisted in subjecting the RD cell line under the effect of the continuous electric field while varying certain parameters (voltage, exposure time, and cell concentration). The response surface methodology (RSM) was used to assess the effect of the chosen parameters, as well as the existence of interactions between them. The results obtained showed that the voltage, the cell concentration as well as the interaction between voltage and exposure time have an influence on the mortality rate of the RD cell line.

Keywords: continuous electric field, RD cancer cell line, RSM, voltage

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Authors: Andleeb Zahra, Itrat Rubab, Sumaira Malik, Amina Khan, Muhammad Jawad Khan, M. Qaiser Fatmi

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Oral squamous cell carcinoma (OSCC) is one of the most common cancers worldwide. Recent studies have highlighted the role of miRNA in disease pathology, indicating its potential use in an early diagnostic tool. miRNAs are small, double stranded, non-coding RNAs that regulate gene expression by deregulating mRNAs. miRNAs play important roles in modifying various cellular processes such as cell growth, differentiation, apoptosis, and immune response. Dis-regulated expression of miRNAs is known to affect the cell growth, and this may function as tumor suppressors or oncogenes in various cancers. Objectives: The main objectives of this study were to characterize the extracellular miRNAs involved in oral cancer (OC) to assist early detection of cancer as well as to propose a list of genes that can potentially be used as biomarkers of OC. We used gene expression data by microarrays already available in literature. Materials and Methods: In the first step, a total of 318 miRNAs involved in oral carcinoma were shortlisted followed by the prediction of their target genes. Simultaneously, the differentially expressed genes (DEGs) of oral carcinoma from all experiments were identified. The common genes between lists of DEGs of OC based on experimentally proven data and target genes of each miRNA were identified. These common genes are the targets of specific miRNA, which is involved in OC. Finally, a list of genes was generated which may be used as biomarker of OC. Results and Conclusion: In results, we included some of pathways in cancer to show the change in gene expression under the control of specific miRNA. Ingenuity pathway analysis (IPA) provided a list of major biomarkers like CDH2, CDK7 and functional enrichment analysis identified the role of miRNA in major pathways like cell adhesion molecules pathway affected by cancer. We observed that at least 25 genes are regulated by maximum number of miRNAs, and thereby, they can be used as biomarkers of OC. To better understand the role of miRNA with respect to their target genes further experiments are required, and our study provides a platform to better understand the miRNA-OC relationship at genomics level.

Keywords: biomarkers, gene expression, miRNA, oral carcinoma

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Authors: Y. Pilehvar-Soltanahmadi, F. Badrzadeh, N. Zarghami, S. Jalilzadeh-Tabrizi, R. Zamani

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Herbal compounds such as curcumin which decrease telomerase and gene expression have been considered as beneficial tools for lung cancer treatment. In this article, we compared the effects of pure curcumin and curcumin-loaded NIPAAm-MAA nanoparticles on telomerase and PinX1 gene expression in a lung cancer cell line. A tetrazolium-based assay was used for determination of cytotoxic effects of curcumin on the Calu-6 lung cancer cell line and telomerase and pinX1 gene expression was measured with real-time PCR. MTT assay showed that Curcumin-loaded NIPAAm-MAA inhibited the growth of the Calu-6 lung cancer cell line in a time and dose-dependent manner. Our q-PCR results showed that the expression of telomerase gene was effectively reduced as the concentration of curcumin-loaded NIPAAm-MAA increased while expression of the PinX1 gene became elevated. The results showed that curcumin loaded NIPAAm-MAA exerted cytotoxic effects on the Calu-6 cell line through down-regulation of telomerase and stimulation of pinX1 gene expression. NIPPAm-MAA could be the good carrier for such kinds of hydrophobic agent.

Keywords: curcumin, NIPAAm-MAA, PinX1, telomerase, lung cancer cells

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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: Syed Sameer Aga, Saniya Nissar

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The Xeroderma pigmentosum group D gene (XPD) plays a key role in nucleotide excision repair (NER) pathway of the damaged DNA. Genetic polymorphisms in the coding region of the XPD gene may alter DNA repair capacity of the protein and hence can modulate the risk of colorectal cancer (CRC) risk. The aim of the study was to determine the genetic association of XPD Lys751Gln polymorphism with the risk of colorectal cancer (CRC) development. 120 CRC patients and 160 normal controls were assessed for genotype frequencies of XPD Lys751Gln polymorphism using PCR-RFLP technique. We observed a significant association (p < 0.05) between the XPD Lys751Gln polymorphism and the risk of developing CRC (p < 0.05). Additionally, Gln/Gln genotype of the XPD gene doubled the risk for the development of CRC [p < 0.05; OR=2.25 95% CI (1.07-4.7)]. Our results suggest that there is a significant association between the XPD Lys751Gln polymorphism and the risk of CRC.

Keywords: colorectal cancer, polymorphism, RFLP, DNA Repair, NER, XPD

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Authors: Asmir Gogic, Aljo Mujcic, Sandra Ibric, Nermin Suljanovic

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Ubiquity of natural disasters during last few decades have risen serious questions towards the prediction of such events and human safety. Every disaster regardless its proportion has a precursor which is manifested as a disruption of some environmental parameter such as temperature, humidity, pressure, vibrations and etc. In order to anticipate and monitor those changes, in this paper we propose an overall system for disaster prediction and monitoring, based on wireless sensor network (WSN). Furthermore, we introduce a modified and simplified WSN routing protocol built on the top of the trickle routing algorithm. Routing algorithm was deployed using the bluetooth low energy protocol in order to achieve low power consumption. Performance of the WSN network was analyzed using a real life system implementation. Estimates of the WSN parameters such as battery life time, network size and packet delay are determined. Based on the performance of the WSN network, proposed system can be utilized for disaster monitoring and prediction due to its low power profile and mesh routing feature.

Keywords: bluetooth low energy, disaster prediction, mesh routing protocols, wireless sensor networks

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Authors: Farah Naja, Romy Abi Fadel, Yasmin Aridi, Aya Zarif, Dania Hariri, Mohammad Alameddine, Anas Mugharbel, Maya Khalil, Zeina Nahleh, Arafat Tfayli

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The objective of this study is to assess the prevalence and determinants of CAM use among breast cancer patients in Beirut, Lebanon. A secondary objective is to evaluate the association between CAM use and quality of life (QOL). A cross-sectional survey was conducted on 180 breast cancer patients recruited from two major referral centers in Beirut. In a face to face interview, participants completed a questionnaire comprised of three sections: socio-demographic and lifestyle characteristics, breast cancer condition, and CAM use. The assessment of QOL was carried using the FACT-B Arabic version. Prevalence of CAM use since diagnosis was 40%. CAM use was negatively associated with age, treatment at a philanthropic hospital and positively associated with having an advanced stage of disease. The most commonly used CAM was ‘Special food’ followed by ‘Herbal teas’. Only 4% of CAM users cited health care professionals as influencing their choice of CAM. One in four patients disclosed CAM use to their treating physician. There was no significant association between CAM use and QOL. The use of CAM therapies among breast cancer patients is prevalent in Lebanon. Efforts should be dedicated at educating physicians to discuss CAM use with their patients and advising patients to disclose of their use with their physicians.

Keywords: breast cancer , complementary medicine, alternative medicine, lebanon , quality of life

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Authors: Dimitrios Binas, Marianna Konidari, Charis Bourgioti, Lia Angela Moulopoulou, Theodore Economopoulos, George Matsopoulos

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High grade ovarian epithelial cancer (OEC) is fatal gynecological cancer and the poor prognosis of this entity is closely related to considerable intratumoral genetic heterogeneity. By examining imaging data, it is possible to assess the heterogeneity of tumorous tissue. This study proposes a methodology for aligning, segmenting and finally visualizing information from various magnetic resonance imaging series in order to construct 3D models of heterogeneity maps from the same tumor in OEC patients. The proposed system may be used as an adjunct digital tool by health professionals for personalized medicine, as it allows for an easy visual assessment of the heterogeneity of the examined tumor.

Keywords: image segmentation, ovarian epithelial cancer, quantitative characteristics, image registration, tumor visualization

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Authors: F. Ghazalnaz Sharifonnasabi, Iman Makhdoom

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Breast cancer is a serious health concern that affects many people around the world. According to a study published in the Breast journal, the global burden of breast cancer is expected to increase significantly over the next few decades. The number of deaths from breast cancer has been increasing over the years, but the age-standardized mortality rate has decreased in some countries. It’s important to be aware of the risk factors for breast cancer and to get regular check- ups to catch it early if it does occur. Machin learning techniques have been used to aid in the early detection and diagnosis of breast cancer. These techniques, that have been shown to be effective in predicting and diagnosing the disease, have become a research hotspot. In this study, we consider two deep learning approaches including: Multi-Layer Perceptron (MLP), and Convolutional Neural Network (CNN). We also considered the five-machine learning algorithm titled: Decision Tree (C4.5), Naïve Bayesian (NB), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) Algorithm and XGBoost (eXtreme Gradient Boosting) on the Breast Cancer Wisconsin Diagnostic dataset. We have carried out the process of evaluating and comparing classifiers involving selecting appropriate metrics to evaluate classifier performance and selecting an appropriate tool to quantify this performance. The main purpose of the study is predicting and diagnosis breast cancer, applying the mentioned algorithms and also discovering of the most effective with respect to confusion matrix, accuracy and precision. It is realized that CNN outperformed all other classifiers and achieved the highest accuracy (0.982456). The work is implemented in the Anaconda environment based on Python programing language.

Keywords: breast cancer, multi-layer perceptron, Naïve Bayesian, SVM, decision tree, convolutional neural network, XGBoost, KNN

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Authors: Kumar Dron Shrivastav, Ankan Mukherjee Das, Arti Taneja, Harpreet Singh, Priya Ranjan, Rajiv Janardhanan

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Cervical cancer is one of the most common cancer among women worldwide which can be cured if detected early. Manual pathology which is typically utilized at present has many limitations. The current gold standard for cervical cancer diagnosis is exhaustive and time-consuming because it relies heavily on the subjective knowledge of the oncopathologists which leads to mis-diagnosis and missed diagnosis resulting false negative and false positive. To reduce time and complexities associated with early diagnosis, we require an interactive diagnostic tool for early detection particularly in developing countries where cervical cancer incidence and related mortality is high. Incorporation of digital pathology in place of manual pathology for cervical cancer screening and diagnosis can increase the precision and strongly reduce the chances of error in a time-specific manner. Thus, we propose a robust and interactive cervical cancer image analysis and diagnostic tool, which can categorically process both histopatholgical and cytopathological images to identify abnormal cells in the least amount of time and settings with minimum resources. Furthermore, incorporation of a set of specific parameters that are typically referred to for identification of abnormal cells with the help of open source software -’R’ is one of the major highlights of the tool. The software has the ability to automatically identify and quantify the morphological features, color intensity, sensitivity and other parameters digitally to differentiate abnormal from normal cells, which may improve and accelerate screening and early diagnosis, ultimately leading to timely treatment of cervical cancer.

Keywords: cervical cancer, early detection, digital Pathology, screening

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Authors: Lakmali Anthony, Madeline Gillies

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Purpose: Decreasing mortality has led to increased focus on patient-reported outcomes such as quality of life (QoL) in breast cancer. Breast cancer patients often have decreased QoL even after treatment is complete. This systematic review of the literature aims to identify psychosocial factors associated with decreased QoL in post-treatment breast cancer patients. Methodology: This systematic review was performed in accordance with the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations. The search was conducted in MEDLINE, EMBASE, and PsychINFO using MeSH headings. The two authors screened studies for relevance and extracted data. Results: Seventeen studies were identified, including 3,150 total participants (mean = 197) with a mean age of 51.9 years. There was substantial heterogeneity in measures of QoL. The most common was the European Organisation for Research and Treatment of Cancer QLQ-C30 (n=7, 41.1%). Most studies (n=12, 70.5%) found that emotional distress correlated with poor QoL, while 3 found no significant association. The most common measure of emotional distress was the Hospital Anxiety and Depression Scale (n=12, 70.5%). Other psychosocial factors associated with QoL were unmet needs, problematic social support, and negative affect. Clinicopathologic determinants included mastectomy without reconstruction, stage IV disease, and adjuvant chemotherapy. Conclusion: This systematic review provides a summary of the psychosocial determinants of poor QoL in post-treatment breast cancer patients, as well as the most commonly reported measures of these. An understanding of these potentially modifiable determinants of poor outcome is pivotal to the provision of quality, patient-centred care in surgical oncology.

Keywords: breast cancer, quality of life, psychosocial determinants, cancer surgery

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Authors: Gabriela Ilie, Robert D. H. Rutledge

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A review of the literature reveals a need for longitudinal studies to properly understand the quality of life of prostate cancer survivors during their prostate cancer journey in order to identify opportunities for patient support and care during prostate cancer survivorship. In this study, mental health and relationship satisfaction were assessed longitudinally and by treatment modality among a population-based sample of Canadian adult men with a history of prostate cancer diagnosis. A total of 98 men, aged 51 or older with a history of prostate cancer completed an on-line 15-minute survey between May 2017 and February 2018, assessing mental health (Kessler Psychological Distress Scale) and relationship satisfaction (Dyadic Adjustment Scale) at baseline and at three months post-treatment with either active or nonactive prostate cancer treatment. Almost 1 in 6 men in this sample screened positive for mental health issues (17.34%, n=17) irrespective of treatment modality and most (n=11) were not currently on medication for depression, anxiety or both. Mental health outcomes were poorer for men with multimorbidity. For every instance of screening positive for mental health issues, 2.021 (95% CI:1.1 to 3.8) times more comorbidities were recorded. Relationship satisfaction and dyadic cohesion were statistically significantly lower from first assessment to 3 months for men who underwent multiple treatment modalities (surgery and radiation with hormonal therapy). Relationship satisfaction was also lower at 3 months for men who underwent radiation therapy. Almost 1 in 2 men in this sample (74%) indicated they did not attend a prostate cancer support group. Results suggest that treatment for mental health is underutilized in men with prostate cancer. Men who undergo multiple forms of active treatment appear more vulnerable to relationship dissatisfaction and feeling disconnected from their partner. Data points to important opportunities for patient education and care support during survivorship.

Keywords: prostate cancer survivorship, mental health, quality of life, relationship satisfaction

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Authors: Arvin Baes

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This study was conducted to assess the holistic needs of cancer patients in terms of physiological, psychological, social, and spiritual needs and to determine how they respond through coping. It was conducted from January-April 2018 from various hospitals in Laguna, with 20 respondents. It utilized a survey descriptive type of research, a checklist type of questionnaire, and purposive sampling in selecting the respondents. It was found out that in terms of physiological needs, fatigue is the most common symptoms they experienced. In terms of psychological, social, and spiritual needs, most of the patients experienced a significant concern. Meanwhile, in coping, religion dominates among the 14 strategies followed by Use of Emotional Support and Positive Reframing, and Substance Use obtained the lowest response. Most of the respondents were female, and its significant relationship in terms of Positive Reframing agrees significantly. In coping and civil status, Positive Reframing and Humor are significant among married respondents. In coping and stage of cancer, 'Positive Reframing' and 'Humor' are significant with the stage of cancer. In coping and treatment modalities, Active Coping, Use of Emotional Support, and Religion are significantly related to patients’ treatment modalities. There is also a significant relationship between Active Coping and Physiological Needs, Religion and Psychological Needs, and Self-blaming and Psychological, Social, and Spiritual Needs. Thus, it is concluded that holistic needs and coping are essential to each other to meet the wholeness of cancer patients. A formulated care intervention program would be beneficial among this group of patients.

Keywords: coping strategies, cancer, cancer patients, holistic needs

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Authors: Emad Amar, Tawfik Khattab, Fatma Zada

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Predicting earthquakes is an important issue in the study of geography. Accurate prediction of earthquakes can help people to take effective measures to minimize the loss of personal and economic damage, such as large casualties, destruction of buildings and broken of traffic, occurred within a few seconds. United States Geological Survey (USGS) science organization provides reliable scientific information of Earthquake Existed throughout history & Preliminary database from the National Center Earthquake Information (NEIC) show some useful factors to predict an earthquake in a seismic area like Aleutian Arc in the U.S. state of Alaska. The main advantage of this prediction method that it does not require any assumption, it makes prediction according to the future evolution of object's time series. The article compares between simulation data result from trained BP and RBF neural network versus actual output result from the system calculations. Therefore, this article focuses on analysis of data relating to real earthquakes. Evaluation results show better accuracy and higher speed by using radial basis functions (RBF) neural network.

Keywords: BP neural network, prediction, RBF neural network, earthquake

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Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani

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Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.

Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse

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Authors: Roohallah Fallah-Moshkani, Mohammad Ali Mohsenpour, Reza Ghiasvand, Hossein Khosravi-Boroujeni, Seyed Mehdi Ahmadi, Paula Brauer, Amin Salehi-Abargouei

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Purpose: Several investigations have proposed the protective association between dietary approaches to stop hypertension (DASH) style diet and risk of cancers; however, they have led to inconsistent results. The present study aimed to systematically review the prospective cohort studies conducted in this regard and, if possible, to quantify the overall effect of using meta-analysis. Methods: PubMed, EMBASE, Scopus, and Google Scholar were searched for cohort studies published up to December 2017. Relative risks (RRs) which were reported for fully adjusted models and their confidence intervals were extracted for meta-analysis. Random effects model was incorporated to combine the RRs. Results: Sixteen studies were eligible to be included in the systematic review from which 8 reports were conducted on the effect of DASH on the risk of mortality from all cancer types, four on the risk of colorectal cancer, and three on the risk of colon and rectal cancer. Four studies examined the association with other cancers (breast, hepatic, endometrial, and lung cancer). Meta-analysis showed that high concordance with DASH significantly decreases the risk of all cancer types (RR=0.83, 95% confidence interval (95%CI):0.80-0.85); furthermore participants who highly adhered to the DASH had lower risk of developing colorectal (RR=0.79, 95%CI: 0.75-0.83), colon (RR=0.81, 95%CI: 0.74-0.87) and rectal (RR=0.79, 95%CI: 0.63-0.98) cancer compared to those with the lowest adherence. Conclusions: DASH-style diet should be suggested as a healthy approach to protect from cancer in the community. Prospective studies exploring the effect on other cancer types and from regions other than the United States are highly recommended.

Keywords: cancer, DASH-style diet, dietary patterns, meta-analysis, systematic review

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Authors: Farah Naja, Romy Abi Fadel, Yasmin Aridi, Aya Zarif, Dania Hariri, Mohammad Alameddine, Anas Mugharbel, Maya Khalil, Zeina Nahleh, Arafat Tfayli

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The objective of this study is to assess the prevalence and determinants of CAM use among breast cancer patients in Beirut, Lebanon. A secondary objective is to evaluate the association between CAM use and quality of life (QOL). A cross-sectional survey was conducted on 180 breast cancer patients recruited from two major referral centers in Beirut. In a face to face interview, participants completed a questionnaire comprised of three sections: socio-demographic and lifestyle characteristics, breast cancer condition, and CAM use. The assessment of QOL was carried using the FACT-B Arabic version. Prevalence of CAM use since diagnosis was 40%. CAM use was negatively associated with age, treatment at a philanthropic hospital and positively associated with having an advanced stage of disease. The most commonly used CAM was ‘Special food’ followed by ‘Herbal teas’. Only 4% of CAM users cited health care professionals as influencing their choice of CAM. One in four patients disclosed CAM use to their treating physician. There was no significant association between CAM use and QOL. The use of CAM therapies among breast cancer patients is prevalent in Lebanon. Efforts should be dedicated at educating physicians to discuss CAM use with their patients and advising patients to disclose of their use with their physicians.

Keywords: breast cancer, complementary and aLternative medicine, Lebanon, quality of life

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Authors: Mahdi Bazarganigilani

Abstract:

Computer-aided diagnosis (CAD) systems can play crucial roles in diagnosing crucial diseases such as breast cancer at the earliest. In this paper, a CAD system for the diagnosis of breast cancer was introduced and evaluated. This CAD system was developed by using spatio-temporal analysis of data on a set of consecutive thermographic images by employing wavelet transformation. By using this analysis, a very accurate machine learning model using random forest was obtained. The final results showed a promising accuracy of 91% in terms of the F1 measure indicator among 200 patients' sample data. The CAD system was further extended to obtain a detailed analysis of the effect of smaller sub-areas of each breast on the occurrence of cancer.

Keywords: computer-aided diagnosis systems, thermographic analysis, spatio-temporal analysis, image processing, machine learning

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Authors: Sara Mouffouk, Fatma Belaid, Asma Hechani, Chaima Mouffouk

Abstract:

Cancer of the cervix caused by HPV (human papillomavirus ) is for many years a real public health problem, it is ranked 2nd deadly female cancer kills more than 270 000 women each year worldwide. In Algeria, the mortality of cervical cancer decreases with the impact, but the prognosis of these cancers remains bleak: The 5-year relative survival is 60 %. The mode of transmission is usually sexuel. Our study was undertaken to show the link between HPV and cervical cancer and the importance of Pap smear screening in this type of pathology. On the total sample, 76.11 % showed abnormal cervical smears of which 13% have mild cases and hormonal reaction Change, and 44% represent inflammatory smears and normal cases 35%, while long seven years from 2005 to 2012. Thus, 43% of abnormal smear results between ASCUS, AGUS, low and high grade carcinoma and adenocarcinoma and 57 % of other cases of unknown origin. The average age of women at risk of developing adenocarcinoma is 45-50 with a 67% to 33% of the same risk in women of age group 41-45 years although the percentage of cases of HPV infected patients was 2% in the past seven years. We found that with increasing age, the risk is argued. Due to several factors such as multiparty can reduced the resistance of the uterine epithelium and even as the multi that promotes contamination HPV causes repeated infections with HPV.

Keywords: cervical cancer, human papillomavirus (HPV) screening, prevention, vaccines

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Authors: Yiannis G. Smirlis

Abstract:

The classification and the prediction of efficiencies in Data Envelopment Analysis (DEA) is an important issue, especially in large scale problems or when new units frequently enter the under-assessment set. In this paper, we contribute to the subject by proposing a grid structure based on interval segmentations of the range of values for the inputs and outputs. Such intervals combined, define hyper-rectangles that partition the space of the problem. This structure, exploited by Interval DEA models and a dominance relation, acts as a DEA pre-processor, enabling the classification and prediction of efficiency scores, without applying any DEA models.

Keywords: data envelopment analysis, interval DEA, efficiency classification, efficiency prediction

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Authors: Marwa M. Abu-Serie, Marwa M. Eltarahony

Abstract:

The search for reliable, effective, and safe nanoparticles (NPs) as a treatment for cancer is a pressing priority. In this study, Cu-NPs were fabricated by Streptomyces cyaneofuscatus through simultaneous bioreduction strategy of copper nitrate salt. The as-prepared Cu-NPs subjected to structural analysis; energy-dispersive X-ray spectroscopy, elemental mapping, X-ray diffraction, transmission electron microscopy, and ζ-potential. These biological synthesized Cu-NPs were mixed with disulfiram (DS), forming a nanocomplex of Cu-DS with a size of ~135 nm. The prepared nanocomplex (nanoCu-DS) exhibited higher anticancer activity than that of free complex of DS-Cu, Cu-NPs, and DS alone. This was illustrated by the lowest IC50 of nanoCu-DS (< 4 µM) against human breast and liver cancer cell lines comparing with DS-Cu, Cu-NPs, and DS (~8, 22.98-33.51 and 11.95-14.86, respectively). Moreover, flow cytometric analysis confirmed that higher apoptosis percentage range of nanoCu-DS-treated in MDA-MB 231, MCF-7, Huh-7, and HepG-2 cells (51.24-65.28%) than free complex of Cu-DS ( < 4.5%). Regarding inhibition potency of liver and breast cancer cell migration, no significant difference was recorded between free and nanocomplex. Furthermore, nanoCu-DS suppressed gene expression of β-catenine, Akt, and NF-κB and upregulated p53 expression (> 3, >15, > 5 and ≥ 3 folds, respectively) more efficiently than free complex (all ~ 1 fold) in MDA-MB 231 and Huh-7 cells. Our finding proved this prepared nano complex has a powerful anticancer activity relative to free complex, thereby offering a promising cancer treatment.

Keywords: biologically prepared Cu-NPs, breast cancer cell lines, liver cancer cell lines, nanoCu- disulfiram

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

Abstract:

The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

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Authors: Beema Akbar, Varun P. Gopi, V. Suresh Babu

Abstract:

Colon cancer causes the deaths of about half a million people every year. The common method of its detection is histopathological tissue analysis, it leads to tiredness and workload to the pathologist. A novel method is proposed that combines both structural and statistical pattern recognition used for the detection of colon cancer. This paper presents a comparison among the different classifiers such as Multilayer Perception (MLP), Sequential Minimal Optimization (SMO), Bayesian Logistic Regression (BLR) and k-star by using classification accuracy and error rate based on the percentage split method. The result shows that the best algorithm in WEKA is MLP classifier with an accuracy of 83.333% and kappa statistics is 0.625. The MLP classifier which has a lower error rate, will be preferred as more powerful classification capability.

Keywords: colon cancer, histopathological image, structural and statistical pattern recognition, multilayer perception

Procedia PDF Downloads 565