Search results for: skin cancer
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 483

Search results for: skin cancer

393 Guided Wave Sensitivity for De-Bond Defects in Aluminum Skin-Honeycomb Core

Authors: A. Satour, F. Boubenider, R. Halimi, A. Badidibouda

Abstract:

Sandwich plates are finding an increasing range of application in the aircraft industry. The inspection of honeycomb composite structure by conventional ultrasonic technique is complex and very time consuming. The present study demonstrates a technique using guided Lamb waves at low frequencies to predict de-bond defects in aluminum skin-honeycomb core sandwich structure used in aeronautics. The numerical method was investigated for drawing the dispersion and displacement curves of ultrasonic Lamb wave propagated in Aluminum plate. An experimental study was carried out to check the theoretical prediction. The detection of unsticking between the skin and the core was tested by the two first modes for a low frequency. It was found that A0 mode is more sensitive to delamination defect compared to S0 mode.

Keywords: Damage detection, delamination, guided waves, Sandwich structure.

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392 Automated 3D Segmentation System for Detecting Tumor and Its Heterogeneity in Patients with High Grade Ovarian Epithelial Cancer

Authors: D. A. Binas, M. Konidari, C. Bourgioti, L. Angela Moulopoulou, T. L. Economopoulos, G. K. Matsopoulos

Abstract:

High grade ovarian epithelial cancer (OEC) is the most fatal gynecological cancer and 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 presents 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: K-means segmentation, ovarian epithelial cancer, quantitative characteristics, registration, tumor visualization.

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391 Novel Hybrid Method for Gene Selection and Cancer Prediction

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

Abstract:

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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390 Association of the p53 Codon 72 Polymorphism with Colorectal Cancer in South West of Iran

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

Abstract:

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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389 VHL, PBRM1 and SETD2 Genes in Kidney Cancer: A Molecular Investigation

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

Abstract:

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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388 Down-Regulated Gene Expression of GKN1 and GKN2 as Diagnostic Markers for Gastric Cancer

Authors: Amer A. Hasan, Mehri Igci, Ersin Borazan, Rozhgar A. Khailany, Emine Bayraktar, Ahmet Arslan

Abstract:

Gastric Cancer (GC) has high morbidity and fatality rate in various countries. It is still one of the most frequent and deadly diseases. Gastrokine1 (GKN1) and gastrokine2 (GKN2) genes are highly expressed in the normal stomach epithelium and play important roles in maintaining the integrity and homeostasis of stomach mucosal epithelial cells. In this study, 47 paired samples that were grouped according to the types of gastric cancer and the clinical characteristics of the patients, including gender and average of age. They were investigated with gene expression analysis and mutation screening by monitoring RT-PCR, SSCP and nucleotide sequencing techniques. Both GKN1 and GKN2 genes were observed significantly reduced found by (Wilcoxon signed rank test; p<0.05). As a result of gene screening, no mutation (no different genotype) was detected. It is considered that gene mutations are not the cause of gastrokines inactivation. In conclusion, the mRNA expression level of GKN1 and GKN2 genes statistically was decreased regardless the gender, age, or cancer type of patients. Reduced of gastrokine genes seem to occur at the initial steps of gastric cancer development.

Keywords: Diagnostic biomarker, gastric cancer, nucleotide sequencing, semi-quantitative RT-PCR.

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387 MITOS-RCNN: Mitotic Figure Detection in Breast Cancer Histopathology Images Using Region Based Convolutional Neural Networks

Authors: Siddhant Rao

Abstract:

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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386 Performance of Histogram-Based Skin Colour Segmentation for Arms Detection in Human Motion Analysis Application

Authors: Rosalyn R. Porle, Ali Chekima, Farrah Wong, G. Sainarayanan

Abstract:

Arms detection is one of the fundamental problems in human motion analysis application. The arms are considered as the most challenging body part to be detected since its pose and speed varies in image sequences. Moreover, the arms are usually occluded with other body parts such as the head and torso. In this paper, histogram-based skin colour segmentation is proposed to detect the arms in image sequences. Six different colour spaces namely RGB, rgb, HSI, TSL, SCT and CIELAB are evaluated to determine the best colour space for this segmentation procedure. The evaluation is divided into three categories, which are single colour component, colour without luminance and colour with luminance. The performance is measured using True Positive (TP) and True Negative (TN) on 250 images with manual ground truth. The best colour is selected based on the highest TN value followed by the highest TP value.

Keywords: image colour analysis, image motion analysis, skin, wavelet transform.

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385 Integrated Social Support through Social Networks to Enhance the Quality of Life of Metastatic Breast Cancer Patients

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

Abstract:

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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384 The Role and Importance of Genome Sequencing in Prediction of Cancer Risk

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

Abstract:

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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383 Sociodemographic Risk Factors of Cervical Cancer in Imphal, Manipur

Authors: Arundhati Devi Maibam, K. Ingocha Singh

Abstract:

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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382 Anti-Aging Effects of Retinol and Alpha Hydroxy Acid on Elastin Fibers of Artificially Photo-Aged Human Dermal Fibroblast Cell Lines

Authors: M. Jarrar, S. Behl, N. Shaheen, A. Fatima, R. Nasab

Abstract:

Skin aging is a slow multifactorial process influenced by both internal as well as external factors. Ultra-violet radiations (UV), diet, smoking and personal habits are the most common environmental factors that affect skin aging. Fat contents and fibrous proteins as collagen and elastin are core internal structural components. The direct influence of UV on elastin integrity and health is central on aging of skin especially by time. The deposition of abnormal elastic material is a major marker in a photo-aged skin. Searching for compounds that may protect against cutaneous photodamage is exceedingly valued. Retinoids and alpha hydroxy acids have been endorsed by some researchers as possible candidates for protecting and or repairing the effect of UV damaged skin. For consolidating a better system of anti- and protective effects of such anti-aging agents, we evaluated the combinatory effects of various dosages of lactic acid and retinol on the dermal fibroblast’s elastin levels exposed to UV. The UV exposed cells showed significant reduction in the elastin levels. A combination of drugs with a higher concentration of lactic acid (30 -35 mM) and a lower concentration of retinol (10-15mg/mL) showed to work better in maintaining elastin concentration in UV exposed cells. We assume this preservation could be the result of increased tropo-elastin gene expression stimulated by retinol whereas lactic acid probably repaired the UV irradiated damage by enhancing the amount and integrity of the elastin fibers.

Keywords: Alpha Hydroxy Acid, Elastin, Retinol, Ultraviolet radiations.

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381 Biodistribution Studies of 177Lu-DOTATOC in Mouse Tumor Model: Possible Utilization in Adenocarcinoma Breast Cancer Treatment

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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380 A study of Cancer-related MicroRNAs through Expression Data and Literature Search

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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379 Treatment of Mycotic Dermatitis in Domestic Animals with Poly Herbal Drug

Authors: U. Umadevi, T. Umakanthan

Abstract:

Globally, mycotic dermatitis is very common but there is no single proven specific allopathic treatment regimen. In this study, domestic animals with skin diseases of different age and breed from geographically varied regions of Tamil Nadu state, India were employed. Most of them have had previous treatment with native and allopathic medicines without success. Clinically, the skin lesions were found to be mild to severe. The trial animals were treated with poly herbal formulation (ointment) prepared using the indigenous medicinal plants – viz Andrographis paniculata, Lawsonia inermis and Madhuca longifolia. Allopathic antifungal drugs and ointments, povidone iodine and curabless (Terbinafine HCl, Ofloxacin, Ornidazole, Clobetasol propionate) were used in control. Comparatively, trial animals were found to have lesser course of treatment time and higher recovery rate than control. In Ethnoveterinary, this combination was tried for the first time. This herbal formulation is economical and an alternative for skin diseases.

Keywords: Allopathic drugs, dermatitis, domestic animals, poly herbal formulation.

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378 An Integrated CFD and Experimental Analysis on Double-Skin Window

Authors: Sheam-Chyun Lin, Wei-Kai Chen, Hung-Cheng Yen, Yung-Jen Cheng, Yu-Cheng Chen

Abstract:

Result from the constant dwindle in natural resources, the alternative way to reduce the costs in our daily life would be urgent to be found in the near future. As the ancient technique based on the theory of solar chimney since roman times, the double-skin façade are simply composed of two large glass panels in purpose of daylighting and also natural ventilation in the daytime. Double-skin façade is generally installed on the exterior side of buildings as function as the window, so there is always a huge amount of passive solar energy the façade would receive to induce the airflow every sunny day. Therefore, this article imposes a domestic double-skin window for residential usage and attempts to improve the volume flow rate inside the cavity between the panels by the frame geometry design, the installation of outlet guide plate and the solar energy collection system. Note that the numerical analyses are applied to investigate the characteristics of flow field, and the boundary conditions in the simulation are totally based on the practical experiment of the original prototype. Then we redesign the prototype from the knowledge of the numerical results and fluid dynamic theory, and later the experiments of modified prototype will be conducted to verify the simulation results. The velocities at the inlet of each case are increase by 5%, 45% and 15% from the experimental data, and also the numerical simulation results reported 20% improvement in volume flow rate both for the frame geometry design and installation of outlet guide plate.

Keywords: Solar energy, Double-skin façades, Thermal buoyancy, Fluid machinery.

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377 The Effects of Tissue Optical Parameters and Interface Reflectivity on Light Diffusion in Biological Tissues

Authors: MA. Ansari

Abstract:

In cancer progress, the optical properties of tissues like absorption and scattering coefficient change, so by these changes, we can trace the progress of cancer, even it can be applied for pre-detection of cancer. In this paper, we investigate the effects of changes of optical properties on light penetrated into tissues. The diffusion equation is widely used to simulate light propagation into biological tissues. In this study, the boundary integral method (BIM) is used to solve the diffusion equation. We illustrate that the changes of optical properties can modified the reflectance or penetrating light.

Keywords: Diffusion equation, boundary element method, refractive index

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376 Evolving Digital Circuits for Early Stage Breast Cancer Detection Using Cartesian Genetic Programming

Authors: Zahra Khalid, Gul Muhammad Khan, Arbab Masood Ahmad

Abstract:

Cartesian Genetic Programming (CGP) is explored to design an optimal circuit capable of early stage breast cancer detection. CGP is used to evolve simple multiplexer circuits for detection of malignancy in the Fine Needle Aspiration (FNA) samples of breast. The data set used is extracted from Wisconsins Breast Cancer Database (WBCD). A range of experiments were performed, each with different set of network parameters. The best evolved network detected malignancy with an accuracy of 99.14%, which is higher than that produced with most of the contemporary non-linear techniques that are computational expensive than the proposed system. The evolved network comprises of simple multiplexers and can be implemented easily in hardware without any further complications or inaccuracy, being the digital circuit.

Keywords: Breast cancer detection, cartesian genetic programming, evolvable hardware, fine needle aspiration (FNA).

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375 Design the Bowtie Antenna for the Detection of the Tumor in Microwave Tomography

Authors: Muhammd Hassan Khalil, Xu Jiadong

Abstract:

Early breast cancer detection is an emerging field of research as it can save the women infected by malignant tumors. Microwave breast imaging is based on the electrical property contrast between healthy and malignant tumor. This contrast can be detected by use of microwave energy with an array of antennas that illuminate the breast through coupling medium and by measuring the scattered fields. In this paper, author has been presented the design and simulation results of the bowtie antenna. This bowtie antenna is designed for the detection of breast cancer detection.

Keywords: Breast cancer detection, Microwave Imaging, Tomography.

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374 Removal of Lead from Aqueous Solutions by Biosorption on Pomegranate Skin: Kinetics, Equilibrium and Thermodynamics

Authors: Y. Laidani, G. Henini, S. Hanini, A. Labbaci, F. Souahi

Abstract:

In this study, pomegranate skin, a material suitable for the conditions in Algeria, was chosen as adsorbent material for removal of lead in an aqueous solution. Biosorption studies were carried out under various parameters such as mass adsorbent particle, pH, contact time, the initial concentration of metal, and temperature. The experimental results show that the percentage of biosorption increases with an increase in the biosorbent mass (0.25 g, 0.035 mg/g; 1.25 g, 0.096 mg/g). The maximum biosorption occurred at pH value of 8 for the lead. The equilibrium uptake was increased with an increase in the initial concentration of metal in solution (Co = 4 mg/L, qt = 1.2 mg/g). Biosorption kinetic data were properly fitted with the pseudo-second-order kinetic model. The best fit was obtained by the Langmuir model with high correlation coefficients (R2 > 0.995) and a maximum monolayer adsorption capacity of 0.85 mg/g for lead. The adsorption of the lead was exothermic in nature (ΔH° = -17.833 kJ/mol for Pb (II). The reaction was accompanied by a decrease in entropy (ΔS° = -0.056 kJ/K. mol). The Gibbs energy (ΔG°) increased from -1.458 to -0.305 kJ/mol, respectively for Pb (II) when the temperature was increased from 293 to 313 K.

Keywords: Biosorption, Pb(II), pomegranate skin, wastewater.

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373 Classification of Potential Biomarkers in Breast Cancer Using Artificial Intelligence Algorithms and Anthropometric Datasets

Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

Abstract:

Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: Breast cancer, health diagnosis, Machine Learning, biomarker classification, Neural Network.

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372 Detection of Breast Cancer in the JPEG2000 Domain

Authors: Fayez M. Idris, Nehal I. AlZubaidi

Abstract:

Breast cancer detection techniques have been reported to aid radiologists in analyzing mammograms. We note that most techniques are performed on uncompressed digital mammograms. Mammogram images are huge in size necessitating the use of compression to reduce storage/transmission requirements. In this paper, we present an algorithm for the detection of microcalcifications in the JPEG2000 domain. The algorithm is based on the statistical properties of the wavelet transform that the JPEG2000 coder employs. Simulation results were carried out at different compression ratios. The sensitivity of this algorithm ranges from 92% with a false positive rate of 4.7 down to 66% with a false positive rate of 2.1 using lossless compression and lossy compression at a compression ratio of 100:1, respectively.

Keywords: Breast cancer, JPEG2000, mammography, microcalcifications.

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371 Microneedles-Mediated Transdermal Delivery

Authors: M. Petchsangsai, N. Wonglertnirant, T. Rojanarata, P. Opanasopit, T. Ngawhirunpat

Abstract:

The objective of the present study was to evaluate the potential of hollow microneedles for enhancing the transdermal delivery of Bovine Serum Albumin (MW~66,000 Da)-Fluorescein Isothiocyanate (BSA-FITC) conjugate, a hydrophilic large molecular compound. Moreover, the effect of different formulations was evaluated. The series of binary mixtures composed of propylene glycol (PG) and pH 7.4 phosphate buffer solution (PBS) was prepared and used as a medium for BSA-FITC. The results showed that there was no permeation of BSA-FITC solution across the neonatal porcine skin without using hollow microneedles, whereas the cumulative amount of BSA-FITC released at 8 h through the neonatal porcine skin was about 60-70% when using hollow microneedles. Furthermore, the results demonstrated that the higher volume of PG in binary mixtures injected, the lower cumulative amount of BSA-FITC released and release rate of BSA-FITC from skin. These release profiles of BSA-FITC in binary mixtures were expressed by Fick-s law of diffusion. These results suggest the utilization of hollow microneedle to enhance transdermal delivery of protein and provide useful information for designing an effective hollow microneedle system.

Keywords: Hydrophilic macromolecules, Microneedles, Propylene glycol, Transdermal drug delivery

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370 Numerical Simulation of Heating Characteristics in a Microwave T-Prong Antenna for Cancer Therapy

Authors: M. Chaichanyut, S. Tungjitkusolmun

Abstract:

This research is presented with microwave (MW) ablation by using the T-Prong monopole antennas. In the study, three-dimensional (3D) finite-element methods (FEM) were utilized to analyse: the tissue heat flux, temperature distributions (heating pattern) and volume destruction during MW ablation in liver cancer tissue. The configurations of T-Prong monopole antennas were considered: Three T-prong antenna, Expand T-Prong antenna and Arrow T-Prong antenna. The 3D FEMs solutions were based on Maxwell and bio-heat equations. The microwave power deliveries were 10 W; the duration of ablation in all cases was 300s. Our numerical result, heat flux and the hotspot occurred at the tip of the T-prong antenna for all cases. The temperature distribution pattern of all antennas was teardrop. The Arrow T-Prong antenna can induce the highest temperature within cancer tissue. The microwave ablation was successful when the region where the temperatures exceed 50°C (i.e. complete destruction). The Expand T-Prong antenna could complete destruction the liver cancer tissue was maximized (6.05 cm3). The ablation pattern or axial ratio (Widest/length) of Expand T-Prong antenna and Arrow T-Prong antenna was 1, but the axial ratio of Three T-prong antenna of about 1.15.

Keywords: Liver cancer, T-Prong antenna, Finite element, Microwave ablation.

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369 A Recommendation to Oncologists for Cancer Treatment by Immunotherapy: Quantitative and Qualitative Analysis

Authors: Mandana Kariminejad, Ali Ghaffari

Abstract:

Today, the treatment of cancer, in a relatively short period, with minimum adverse effects is a great concern for oncologists. In this paper, based on a recently used mathematical model for cancer, a guideline has been proposed for the amount and duration of drug doses for cancer treatment by immunotherapy. Dynamically speaking, the mathematical ordinary differential equation (ODE) model of cancer has different equilibrium points; one of them is unstable, which is called the no tumor equilibrium point. In this paper, based on the number of tumor cells an intelligent soft computing controller (a combination of fuzzy logic controller and genetic algorithm), decides regarding the amount and duration of drug doses, to eliminate the tumor cells and stabilize the unstable point in a relatively short time. Two different immunotherapy approaches; active and adoptive, have been studied and presented. It is shown that the rate of decay of tumor cells is faster and the doses of drug are lower in comparison with the result of some other literatures. It is also shown that the period of treatment and the doses of drug in adoptive immunotherapy are significantly less than the active method. A recommendation to oncologists has also been presented.

Keywords: Tumor, immunotherapy, fuzzy controller, Genetic algorithm, mathematical model.

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368 Thermo-Mechanical Characterization of Skin Laser Soldering using Au Coated SiO2 Nanoshells

Authors: M.S.Nourbakhsh, M.E.khosroshahi

Abstract:

Gold coated silica core nanoparticles have an optical response dictated by the plasmon resonance. The wavelength at which the resonance occurs depends on the core and shell sizes, allowing nanoshells to be tailored for particular applications. The purposes of this study was to synthesize and use different concentration of gold nanoshells as exogenous material for skin tissue soldering and also to examine the effect of laser soldering parameters on the properties of repaired skin. Two mixtures of albumin solder and different concentration of gold nanoshells were prepared. A full thickness incision of 2×20 mm2 was made on the surface and after addition of mixtures it was irradiated by an 810nm diode laser at different power densities. The changes of tensile strength σt due to temperature rise, number of scan (Ns), and scan velocity (Vs) were investigated. The results showed at constant laser power density (I), σt of repaired incisions increases by increasing the concentration of gold nanoshells, Ns and decreasing Vs. It is therefore important to consider the trade off between the scan velocity and the surface temperature for achieving an optimum operating condition. In our case this corresponds to σt =1610 gr/cm2 at I~ 60 Wcm-2, T ~ 65ºC, Ns =10 and Vs=0.2mms-1.

Keywords: Tissue soldering, Diode laser, Gold Nanoshells, Tensile strength

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367 Community Detection-based Analysis of the Human Interactome Network

Authors: Razvan Bocu, Sabin Tabirca

Abstract:

The study of proteomics reached unexpected levels of interest, as a direct consequence of its discovered influence over some complex biological phenomena, such as problematic diseases like cancer. This paper presents a new technique that allows for an accurate analysis of the human interactome network. It is basically a two-step analysis process that involves, at first, the detection of each protein-s absolute importance through the betweenness centrality computation. Then, the second step determines the functionallyrelated communities of proteins. For this purpose, we use a community detection technique that is based on the edge betweenness calculation. The new technique was thoroughly tested on real biological data and the results prove some interesting properties of those proteins that are involved in the carcinogenesis process. Apart from its experimental usefulness, the novel technique is also computationally effective in terms of execution times. Based on the analysis- results, some topological features of cancer mutated proteins are presented and a possible optimization solution for cancer drugs design is suggested.

Keywords: Betweenness centrality, interactome networks, proteinprotein interactions, protein communities, cancer.

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366 Patterns of Malignant and Benign Breast Lesions in Hail Region: A Retrospective Study at King Khalid Hospital

Authors: Laila Seada, Ashraf Ibrahim, Amjad Al Shammari

Abstract:

Background and Objectives: Breast carcinoma is the most common cancer of females in Hail region, accounting for 31% of all diagnosed cancer cases followed by thyroid carcinoma (25%) and colorectal carcinoma (13%). Methods: In the present retrospective study, all cases of breast lesions received at the histopathology department in King Khalid Hospital, Hail, during the period from May 2011 to April 2016 have been retrieved from department files. For all cases, a trucut biopsy, lumpectomy, or modified radical mastectomy was available for histopathologic diagnosis, while 105/140 (75%) had, as well, preoperative fine needle aspirates (FNA). Results: 49 cases out of 140 (35%) breast lesions were carcinomas: 44/49 (89.75%) was invasive ductal, 2/49(4.1%) invasive lobular carcinomas, 1/49(2.05%) intracystic low grade papillary carcinoma and 2/49 (4.1%) ductal carcinoma in situ (DCIS). Mean age for malignant cases was 45.06 (+/-10.58): 32.6% were below the age of 40 and 30.6 below 50 years, 18.3% below 60 and 16.3% below 70 years. For the benign group, mean age was 32.52 (+/10.5) years. Benign lesions were in order of frequency: 34 fibroadenomas, 14 fibrocystic disease, 12 chronic mastitis, five granulomatous mastitis, three intraductal papillomas, and three benign phyllodes tumor. Tubular adenoma, lipoma, skin nevus, pilomatrixoma, and breast reduction specimens constituted the remaining specimens. Conclusion: Breast lesions are common in our series and invasive carcinoma accounts for more than 1/3rd of the lumps, with 63.2% incidence in pre-menopausal ladies, below the age of 50 years. FNA as a non-invasive procedure, proved to be an effective tool in diagnosing both benign and malignant/suspicious breast lumps and should continue to be used as a first assessment line of palpable breast masses.

Keywords: Age incidence, breast carcinoma, fine needle aspiration, Hail Region.

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365 Use of Gaussian-Euclidean Hybrid Function Based Artificial Immune System for Breast Cancer Diagnosis

Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

Abstract:

Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: Artificial Immune System, Breast Cancer Diagnosis, Euclidean Function, Gaussian Function.

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364 Numerical Investigation of Two-dimensional Boundary Layer Flow Over a Moving Surface

Authors: Mahmoud Zarrini, R.N. Pralhad

Abstract:

In this chapter, we have studied Variation of velocity in incompressible fluid over a moving surface. The boundary layer equations are on a fixed or continuously moving flat plate in the same or opposite direction to the free stream with suction and injection. The boundary layer equations are transferred from partial differential equations to ordinary differential equations. Numerical solutions are obtained by using Runge-Kutta and Shooting methods. We have found numerical solution to velocity and skin friction coefficient.

Keywords: Boundary layer, continuously moving surface, shooting method, skin friction coefficient.

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