Search results for: Breast Cancer Screening
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 471

Search results for: Breast Cancer Screening

351 The Effect of Aerobic Training and Taxol Consumption on IL 8 and PAI-1 in Cervical Cancer

Authors: Alireza Barari, Maryam Firoozi, Maryam Ebrahimzadeh, Romina Roohani Ardeshiri, Maryam Kamarloeei

Abstract:

Background: The purpose of this study was to analyze the effect of six-week aerobic training and taxol consumption on interleukin-8 and Plasminogen Activator Inhibitor-1 (PAI-1) in mice with cervical cancer. Materials and Methods: In this experimental study, 40 female C57 mice with cervical cancer, eight weeks old, were randomly divided into 4 groups including: control, taxol supplement, training, and training-taxol supplement. The implantation of cancerous tumors was performed under the skin at the upper of the pelvis. The program training was included: endurance training for six weeks, 3 sessions per week and 50 minutes per session, at the speed of 14-18 m/s. Taxol supplement at a dose of 60 mg/kg per day was injected intraperitoneally. Data analysis was performed using t-test and one-way ANOVA and if statistically significant, Bonferroni post hoc was used at the significance level p < .05. Results: The results showed that there was a significant difference between the levels of interleukin 8 (P < 0.05, F = 12.25) and the PAI-1 (P < 0.05, P = 0.10737 between the 4 groups. The results of this study showed a significant difference between the control group and the training - complementary group. Six weeks of aerobic training and taxol consumption have a significant effect on the level of PAI-1 and interleukin-8 mice with cervical cancer. Conclusion: Considering the effect of training on these variables, this type of exercise can be used as a complementary therapeutic approach with other therapies for cervical cancer.

Keywords: Cervical cancer, taxol, endurance training, interleukin 8, plasminogen activator inhibitor-1.

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350 Screening of Process Variables for the Production of Extracellular Lipase from Palm Oil by Trichoderma Viride using Plackett-Burman Design

Authors: R. Rajendiran, S. Gayathri devi, B.T. SureshKumar, V. Arul Priya

Abstract:

Plackett-Burman statistical screening of media constituents and operational conditions for extracellular lipase production from isolate Trichoderma viride has been carried out in submerged fermentation. This statistical design is used in the early stages of experimentation to screen out unimportant factors from a large number of possible factors. This design involves screening of up to 'n-1' variables in just 'n' number of experiments. Regression coefficients and t-values were calculated by subjecting the experimental data to statistical analysis using Minitab version 15. The effects of nine process variables were studied in twelve experimental trials. Maximum lipase activity of 7.83 μmol /ml /min was obtained in the 6th trail. Pareto chart illustrates the order of significance of the variables affecting the lipase production. The present study concludes that the most significant variables affecting lipase production were found to be palm oil, yeast extract, K2HPO4, MgSO4 and CaCl2.

Keywords: lipase, submerged fermentation, statistical optimization, Trichoderma viride

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349 An Automated Method to Segment and Classify Masses in Mammograms

Authors: Viet Dzung Nguyen, Duc Thuan Nguyen, Tien Dzung Nguyen, Van Thanh Pham

Abstract:

Mammography is the most effective procedure for an early diagnosis of the breast cancer. Nowadays, people are trying to find a way or method to support as much as possible to the radiologists in diagnosis process. The most popular way is now being developed is using Computer-Aided Detection (CAD) system to process the digital mammograms and prompt the suspicious region to radiologist. In this paper, an automated CAD system for detection and classification of massive lesions in mammographic images is presented. The system consists of three processing steps: Regions-Of- Interest detection, feature extraction and classification. Our CAD system was evaluated on Mini-MIAS database consisting 322 digitalized mammograms. The CAD system-s performance is evaluated using Receiver Operating Characteristics (ROC) and Freeresponse ROC (FROC) curves. The archived results are 3.47 false positives per image (FPpI) and sensitivity of 85%.

Keywords: classification, computer-aided detection, featureextraction, mass detection.

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348 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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347 Study of Peptide Fragment of Alpha-Fetoprotein as a Radionuclide Vehicle

Authors: Alesya Ya. Maruk, Olga E. Klementyeva, Ekaterina I. Lesik, Anton A. Larenkov, Alexander B. Bruskin

Abstract:

Alpfa-fetoprotein and its fragments may be an important vehicle for targeted delivery of radionuclides to the tumor. We investigated the effect of conditions on the labeling of biologically active synthetic peptide based on the (F-afp) with technetium-99m. The influence of the nature of the buffer solution, pH, concentration of reductant, concentration of the peptide and the reaction temperature on the yield of labeling was examined. As a result, the following optimal conditions for labeling of (F-afp) are found: pH 8.5 (phosphate and bicarbonate buffers) and pH from 1.7 to 7.0 (citrate buffer). The reaction proceeds with sufficient yield at room temperature for 30 min at the concentration of SnCl2 and (Fafp) (F-afp) is to be less than 10 mkg/ml and 25 mkg/ml, respectively. Investigations of the test drug accumulation in the tumor cells of human breast cancer were carried out. Results can be assumed that the in vivo study of the (F-afp) in experimental tumor lesions will show concentrations sufficient for imaging these lesions by SPECT.

Keywords: peptide, technetium-99m, tumor, SPECT.

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346 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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345 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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344 Association between Single Nucleotide Polymorphism of Calpain1 Gene and Meat Tenderness Traits in Different Genotypes of Chicken: Malaysian Native and Commercial Broiler Line

Authors: Abtehal Y. Anaas, Mohd. Nazmi Bin Abd. Manap

Abstract:

Meat Tenderness is one of the most important factors affecting consumers' assessment of meat quality. Variation in meat tenderness is genetically controlled and varies among breeds, and it is also influenced by environmental factors that can affect its creation during rigor mortis and postmortem. The final postmortem meat tenderization relies on the extent of proteolysis of myofibrillar proteins caused by the endogenous activity of the proteolytic calpain system. This calpain system includes different calcium-dependent cysteine proteases, and an inhibitor, calpastatin. It is widely accepted that in farm animals including chickens, the μ-calpain gene (CAPN1) is a physiological candidate gene for meat tenderness. This study aimed to identify the association of single nucleotide polymorphism (SNP) markers in the CAPN1 gene with the tenderness of chicken breast meat from two Malaysian native and commercial broiler breed crosses. Ten, five months old native chickens and ten, 42 days commercial broilers were collected from the local market and breast muscles were removed two hours after slaughter, packed separately in plastic bags and kept at -20ºC for 24 h. The tenderness phenotype for all chickens’ breast meats was determined by Warner-Bratzler Shear Force (WBSF). Thawing and cooking losses were also measured in the same breast samples before using in WBSF determination. Polymerase chain reaction (PCR) was used to identify the previously reported C7198A and G9950A SNPs in the CAPN1 gene and assess their associations with meat tenderness in the two breeds. The broiler breast meat showed lower shear force values and lower thawing loss rates than the native chickens (p<0.05), whereas there were similar in the rates of cooking loss. The study confirms some previous results that the markers CAPN1 C7198A and G9950A were not significantly associated with the variation in meat tenderness in chickens. Therefore, further study is needed to confirm the functional molecular mechanism of these SNPs and evaluate their associations in different chicken populations.

Keywords: CAPNl, chicken, meat tenderness, meat quality, SNPs.

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343 A Nano-Scaled SRAM Guard Band Design with Gaussian Mixtures Model of Complex Long Tail RTN Distributions

Authors: Worawit Somha, Hiroyuki Yamauchi

Abstract:

This paper proposes, for the first time, how the challenges facing the guard-band designs including the margin assist-circuits scheme for the screening-test in the coming process generations should be addressed. The increased screening error impacts are discussed based on the proposed statistical analysis models. It has been shown that the yield-loss caused by the misjudgment on the screening test would become 5-orders of magnitude larger than that for the conventional one when the amplitude of random telegraph noise (RTN) caused variations approaches to that of random dopant fluctuation. Three fitting methods to approximate the RTN caused complex Gamma mixtures distributions by the simple Gaussian mixtures model (GMM) are proposed and compared. It has been verified that the proposed methods can reduce the error of the fail-bit predictions by 4-orders of magnitude.

Keywords: Mixtures of Gaussian, Random telegraph noise, EM algorithm, Long-tail distribution, Fail-bit analysis, Static random access memory, Guard band design.

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342 Extended Shelf Life of Chicken Meat Using Carboxymethyl Cellulose Coated Polypropylene Films Containing Zataria multiflora Essential Oil

Authors: Z. Honarvar, M. Farhoodi, M. R. Khani, S. Shojaee-Aliabadi

Abstract:

The purpose of the present study was to evaluate carboxymethyl cellulose (CMC) coated polypropylene (PP) films containing Zataria multiflora (ZEO) essential oils (4%) as an antimicrobial packaging for chicken breast stored at 4 °C. To increase PP film hydrophilicity, it was treated by atmospheric cold plasma prior to coating by CMC. Then, different films including PP, PP/CMC, PP/CMC containing 4% of ZEO were used for the chicken meat packaging in vapor phase. Total viable count and pseudomonads population and oxidative (TBA) changes of the chicken breast were analyzed during shelf life. Results showed that the shelf life of chicken meat kept in films containing ZEO improved from three to nine days compared to the control sample without any direct contact with the film. Study of oxygen barrier properties of bilayer film without essential oils (0.096 cm3 μm/m2 d kPa) in comparison with PP film (416 cm3 μm/m2 d kPa) shows that coating of PP with CMC significantly reduces oxygen permeation of the obtained packaging (P<0.05), which reduced aerobic bacteria growth. Chemical composition of ZEO was also evaluated by gas chromatography–mass spectrometry (GC–MS), and this shows that thymol was the main antimicrobial and antioxidant component of the essential oil. The results revealed that PP/CMC containing ZEO has good potential for application as active food packaging in indirect contact which would also improve sensory properties of product.

Keywords: Shelf life, chicken breast, polypropylene, carboxymethyl cellulose, essential oil.

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341 Application of Robot Formation Scheme for Screening Solar Energy in a Greenhouse

Authors: George K. Fourlas, Konstantinos Kalovrektis, Evangelos Fountas

Abstract:

Many agricultural and especially greenhouse applications like plant inspection, data gathering, spraying and selective harvesting could be performed by robots. In this paper multiple nonholonomic robots are used in order to create a desired formation scheme for screening solar energy in a greenhouse through data gathering. The formation consists from a leader and a team member equipped with appropriate sensors. Each robot is dedicated to its mission in the greenhouse that is predefined by the requirements of the application. The feasibility of the proposed application includes experimental results with three unmanned ground vehicles (UGV).

Keywords: Greenhouses application, robot formation, solarenergy.

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340 Classification of Prostate Cell Nuclei using Artificial Neural Network Methods

Authors: M. Sinecen, M. Makinacı

Abstract:

The purpose of this paper is to assess the value of neural networks for classification of cancer and noncancer prostate cells. Gauss Markov Random Fields, Fourier entropy and wavelet average deviation features are calculated from 80 noncancer and 80 cancer prostate cell nuclei. For classification, artificial neural network techniques which are multilayer perceptron, radial basis function and learning vector quantization are used. Two methods are utilized for multilayer perceptron. First method has single hidden layer and between 3-15 nodes, second method has two hidden layer and each layer has between 3-15 nodes. Overall classification rate of 86.88% is achieved.

Keywords: Artificial neural networks, texture classification, cancer diagnosis.

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339 Wound Healing Dressing and Some Composites Such as Zeolite, TiO2, Chitosan and PLGA: A Review

Authors: L. B. Naves, L. Almeida

Abstract:

The development of Drugs Delivery System (DDS) has been widely investigated in the last decades. In this paper, first a general overview of traditional and modern wound dressing is presented. This is followed by a review of what scientists have done in the medical environment, focusing on the possibility to develop a new alternative for DDS through transdermal pathway, aiming to treat melanoma skin cancer.

Keywords: Cancer Therapy, Dressing Polymers, Melanoma, wound healing.

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338 ‘Memory Mate’ as Boundary Object in Cancer Treatment for Patients with Dementia

Authors: Rachel Hurdley, Jane Hopkinson

Abstract:

This article is based on observation of a cross-disciplinary, cross-institutional team that worked on an intervention called ‘Memory Mate’ for use in a UK Cancer Centre. This aimed to improve treatment outcomes for patients who had comorbid dementia or other memory impairment. Comorbid patients present ambiguous, spoiled identities, problematising the boundaries of health specialisms and frames of understanding. Memory Mate is theorised as a boundary object facilitating service transformation by changing relations between oncology and mental health care practice. It crosses the boundaries between oncology and mental health. Its introduction signifies an important step in reconfiguring relations between the specialisms. As a boundary object, it contains parallel, even contesting worlds, with potential to enable an eventual synthesis of the double stigma of cancer and dementia. Memory Mate comprises physical things, such as an animation, but its principal value is in the interaction it initiates across disciplines and services. It supports evolution of practices to address a newly emergent challenge for health service provision, namely the cancer patient with comorbid dementia/cognitive impairment. Getting clinicians from different disciplines working together on a practical solution generates a dialogue that can shift professional identity and change the culture of practice.

Keywords: Boundary object, cancer, dementia, interdisciplinary teams.

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337 Bayesian Meta-Analysis to Account for Heterogeneity in Studies Relating Life Events to Disease

Authors: Elizabeth Stojanovski

Abstract:

Associations between life events and various forms of cancers have been identified. The purpose of a recent random-effects meta-analysis was to identify studies that examined the association between adverse events associated with changes to financial status including decreased income and breast cancer risk. The same association was studied in four separate studies which displayed traits that were not consistent between studies such as the study design, location, and time frame. It was of interest to pool information from various studies to help identify characteristics that differentiated study results. Two random-effects Bayesian meta-analysis models are proposed to combine the reported estimates of the described studies. The proposed models allow major sources of variation to be taken into account, including study level characteristics, between study variance and within study variance, and illustrate the ease with which uncertainty can be incorporated using a hierarchical Bayesian modelling approach.

Keywords: Random-effects, meta-analysis, Bayesian, variation.

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336 A Study on Exclusive Breastfeeding using Over-dispersed Statistical Models

Authors: Naushad Mamode Khan, Cheika Jahangeer, Maleika Heenaye-Mamode Khan

Abstract:

Breastfeeding is an important concept in the maternal life of a woman. In this paper, we focus on exclusive breastfeeding. Exclusive breastfeeding is the feeding of a baby on no other milk apart from breast milk. This type of breastfeeding is very important during the first six months because it supports optimal growth and development during infancy and reduces the risk of obliterating diseases and problems. Moreover, in Mauritius, exclusive breastfeeding has decreased the incidence and/or severity of diarrhea, lower respiratory infection and urinary tract infection. In this paper, we give an overview of exclusive breastfeeding in Mauritius and the factors influencing it. We further analyze the local practices of exclusive breastfeeding using the Generalized Poisson regression model and the negative-binomial model since the data are over-dispersed.

Keywords: Exclusive breast feeding, regression model, generalized poisson, negative binomial.

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335 Feature Subset Selection approach based on Maximizing Margin of Support Vector Classifier

Authors: Khin May Win, Nan Sai Moon Kham

Abstract:

Identification of cancer genes that might anticipate the clinical behaviors from different types of cancer disease is challenging due to the huge number of genes and small number of patients samples. The new method is being proposed based on supervised learning of classification like support vector machines (SVMs).A new solution is described by the introduction of the Maximized Margin (MM) in the subset criterion, which permits to get near the least generalization error rate. In class prediction problem, gene selection is essential to improve the accuracy and to identify genes for cancer disease. The performance of the new method was evaluated with real-world data experiment. It can give the better accuracy for classification.

Keywords: Microarray data, feature selection, recursive featureelimination, support vector machines.

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334 Segmentation of Breast Lesions in Ultrasound Images Using Spatial Fuzzy Clustering and Structure Tensors

Authors: Yan Xu, Toshihiro Nishimura

Abstract:

Segmentation in ultrasound images is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, a segmentation scheme using fuzzy c-means (FCM) clustering incorporating both intensity and texture information of images is proposed to extract breast lesions in ultrasound images. Firstly, the nonlinear structure tensor, which can facilitate to refine the edges detected by intensity, is used to extract speckle texture. And then, a spatial FCM clustering is applied on the image feature space for segmentation. In the experiments with simulated and clinical ultrasound images, the spatial FCM clustering with both intensity and texture information gets more accurate results than the conventional FCM or spatial FCM without texture information.

Keywords: fuzzy c-means, spatial information, structure tensor, ultrasound image segmentation

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333 Awareness for Air Pollution Impacts on Lung Cancer in Southern California: A Pilot Study for Designed Smartphone Application

Authors: M. Mohammed Raoof, A. Enkhtaivan, H. Aljuaid

Abstract:

This study follows the design science research methodology to design and implement a smartphone application artifact. The developed artifact was evaluated through three phases. The System Usability Scale (SUS) metric was used for the evaluation. The designed artifact aims to spread awareness about reducing air pollution, decreasing lung cancer development, and checking the air quality status in Southern California Counties. Participants have been drawn for a pilot study to facilitate awareness of air pollution. The study found that smartphone applications have a beneficial effect on the study’s aims.

Keywords: Air pollution, design science research, indoor air pollution, lung cancer, outdoor air pollution, smartphone application.

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332 Gene Expression Signature for Classification of Metastasis Positive and Negative Oral Cancer in Homosapiens

Authors: A. Shukla, A. Tarsauliya, R. Tiwari, S. Sharma

Abstract:

Cancer classification to their corresponding cohorts has been key area of research in bioinformatics aiming better prognosis of the disease. High dimensionality of gene data has been makes it a complex task and requires significance data identification technique in order to reducing the dimensionality and identification of significant information. In this paper, we have proposed a novel approach for classification of oral cancer into metastasis positive and negative patients. We have used significance analysis of microarrays (SAM) for identifying significant genes which constitutes gene signature. 3 different gene signatures were identified using SAM from 3 different combination of training datasets and their classification accuracy was calculated on corresponding testing datasets using k-Nearest Neighbour (kNN), Fuzzy C-Means Clustering (FCM), Support Vector Machine (SVM) and Backpropagation Neural Network (BPNN). A final gene signature of only 9 genes was obtained from above 3 individual gene signatures. 9 gene signature-s classification capability was compared using same classifiers on same testing datasets. Results obtained from experimentation shows that 9 gene signature classified all samples in testing dataset accurately while individual genes could not classify all accurately.

Keywords: Cancer, Gene Signature, SAM, Classification.

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331 Evolutionary of Prostate Cancer Stem Cells in Prostate Duct

Authors: Zachariah Sinkala

Abstract:

A systems approach model for prostate cancer in prostate duct, as a sub-system of the organism is developed. It is accomplished in two steps. First this research work starts with a nonlinear system of coupled Fokker-Plank equations which models continuous process of the system like motion of cells. Then extended to PDEs that include discontinuous processes like cell mutations, proliferation and deaths. The discontinuous processes is modeled by using intensity poisson processes. The model incorporates the features of the prostate duct. The system of PDEs spatial coordinate is along the proximal distal axis. Its parameters depend on features of the prostate duct. The movement of cells is biased towards distal region and mutations of prostate cancer cells is localized in the proximal region. Numerical solutions of the full system of equations are provided, and are exhibit traveling wave fronts phenomena. This motivates the use of the standard transformation to derive a canonically related system of ODEs for traveling wave solutions. The results obtained show persistence of prostate cancer by showing that the non-negative cone for the traveling wave system is time invariant. The traveling waves have a unique global attractor is proved also. Biologically, the global attractor verifies that evolution of prostate cancer stem cells exhibit the avascular tumor growth. These numerical solutions show that altering prostate stem cell movement or mutation of prostate cancer cells lead to avascular tumor. Conclusion with comments on clinical implications of the model is discussed.

Keywords: Fokker-Plank equations, global attractor, stem cell.

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330 Boundary Segmentation of Microcalcification using Parametric Active Contours

Authors: Abdul Kadir Jumaat, Siti Salmah Yasiran, Wan Eny Zarina Wan Abd Rahman, Aminah Abdul Malek

Abstract:

A mammography image is composed of low contrast area where the breast tissues and the breast abnormalities such as microcalcification can hardly be differentiated by the medical practitioner. This paper presents the application of active contour models (Snakes) for the segmentation of microcalcification in mammography images. Comparison on the microcalcifiation areas segmented by the Balloon Snake, Gradient Vector Flow (GVF) Snake, and Distance Snake is done against the true value of the microcalcification area. The true area value is the average microcalcification area in the original mammography image traced by the expert radiologists. From fifty images tested, the result obtained shows that the accuracy of the Balloon Snake, GVF Snake, and Distance Snake in segmenting boundaries of microcalcification are 96.01%, 95.74%, and 95.70% accuracy respectively. This implies that the Balloon Snake is a better segmentation method to locate the exact boundary of a microcalcification region.

Keywords: Balloon Snake, GVF Snake, Distance Snake, Mammogram, Microcalcifications, Segmentation

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329 Evolution of Cord Absorbed Dose during of Larynx Cancer Radiotherapy, with 3D Treatment Planning and Tissue Equivalent Phantom

Authors: Mohammad Hassan Heidari, Amir Hossein Goodarzi, Majid Azarniush

Abstract:

Radiation doses to tissues and organs were measured using the anthropomorphic phantom as an equivalent to the human body. When high-energy X-rays are externally applied to treat laryngeal cancer, the absorbed dose at the laryngeal lumen is lower than given dose because of air space, which it should pass through, before reaching the lesion. Specially, in case of high-energy X-rays, the loss of dose is considerable. Three-dimensional absorbed dose distributions have been computed for high-energy photon radiation therapy of laryngeal and hypopharyngeal cancers, using a coaxial pair of opposing lateral beams in fixed positions. Treatment plans obtained under various conditions of irradiation.

Keywords: 3D Treatment Planning, anthropomorphic phantom, larynx cancer, radiotherapy.

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328 Anticancer Effect of Doxorubicin Loaded Heparin based Super-paramagnetic Iron oxide Nanoparticles against the Human Ovarian Cancer Cells

Authors: Amaneh Javid, Shahin Ahmadian, Ali A. Saboury, Saeed Rezaei-Zarchi

Abstract:

This study determines the effect of naked and heparinbased super-paramagnetic iron oxide nanoparticles on the human cancer cell lines of A2780. Doxorubicin was used as the anticancer drug, entrapped in the SPIO-NPs. This study aimed to decorate nanoparticles with heparin, a molecular ligand for 'active' targeting of cancerous cells and the application of modified-nanoparticles in cancer treatment. The nanoparticles containing the anticancer drug DOX were prepared by a solvent evaporation and emulsification cross-linking method. The physicochemical properties of the nanoparticles were characterized by various techniques, and uniform nanoparticles with an average particle size of 110±15 nm with high encapsulation efficiencies (EE) were obtained. Additionally, a sustained release of DOX from the SPIO-NPs was successful. Cytotoxicity tests showed that the SPIO-DOX-HP had higher cell toxicity than the individual HP and confocal microscopy analysis confirmed excellent cellular uptake efficiency. These results indicate that HP based SPIO-NPs have potential uses as anticancer drug carriers and also have an enhanced anticancer effect.

Keywords: Heparin, A2780 cells, ovarian cancer, nanoparticles, doxorubicin.

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327 Massive Lesions Classification using Features based on Morphological Lesion Differences

Authors: U. Bottigli, D.Cascio, F. Fauci, B. Golosio, R. Magro, G.L. Masala, P. Oliva, G. Raso, S.Stumbo

Abstract:

Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based on morphological lesion differences. Some classifiers as a Feed Forward Neural Network, a K-Nearest Neighbours and a Support Vector Machine are used to distinguish the pathological records from the healthy ones. The results obtained in terms of sensitivity (percentage of pathological ROIs correctly classified) and specificity (percentage of non-pathological ROIs correctly classified) will be presented through the Receive Operating Characteristic curve (ROC). In particular the best performances are 88% ± 1 of area under ROC curve obtained with the Feed Forward Neural Network.

Keywords: Neural Networks, K-Nearest Neighbours, SupportVector Machine, Computer Aided Diagnosis.

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326 Non-Melanoma Skin Cancer in Ha’il Region in the Kingdom of Saudi Arabia: A Clinicopathological Study

Authors: Laila Seada, Nouf Al Gharbi, Shaimaa Dawa

Abstract:

Although skin cancers are prevalent worldwide, it is uncommon in Ha’il region in the Kingdom of Saudi Arabia, mostly non-melanoma sub-type. During a 4-year period from 2014 to 2017, out of a total of 120 cases of skin lesions, 29 non-melanoma cancers were retrieved from histopathology files obtained from King Khalid Hospital. As part of the study, all cases of skin cancer diagnosed during 2014 -2017 have been revised and the clinicopathological data recorded. The results show that Basal cell carcinoma (BCC) was the most common neoplasm (36%), followed by cutaneous lymphomas (mostly mycosis fungoides 25%), squamous cell carcinoma (SCC) (21%) and dermatofibrosarcoma protuberans (DFSP) (11%). Only one case of metastatic carcinoma was recorded. BCC nodular type was the most prevalent, with a mean age 57.6 years and mean size 2.73 cm. SCC was mostly grade 2, with mean size 1.9 cm and an older mean age of 72.3 cm. Increased size of lesion positively correlated with older age (p = 0.001). Non-melanoma skin cancer in Ha’il region is not frequently encountered. BCC is the most frequent followed by cutaneous T-cell lymphomas and SCC. The findings in this study were in accordance with other parts of, but much lower than other parts of the world.

Keywords: Non melanoma skin cancer, Hail Region, histopathology, BCC.

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325 Evaluation of Systemic Immune-Inflammation Index in Obese Children

Authors: Mustafa M. Donma, Orkide Donma

Abstract:

A growing list of cancers might be influenced by obesity. Obesity is associated with an increased risk for the occurrence and development of some cancers. Inflammation can lead to cancer. It is one of the characteristic features of cancer and plays a critical role in cancer development. C-reactive protein (CRP) is under evaluation related to the new and simple prognostic factors in patients with metastatic renal cell cancer. Obesity can predict and promote systemic inflammation in healthy adults. BMI is correlated with hs-CRP. In this study, SII index and CRP values were evaluated in children with normal BMI and those within the range of different obesity grades to detect the tendency towards cancer in pediatric obesity. A total of one hundred and ninety-four children; thirty-five children with normal BMI, twenty overweight (OW), forty-seven obese (OB) and ninety-two morbid obese (MO) participated in the study. Age- and sex-matched groups were constituted using BMI-for age percentiles. Informed consent was obtained. Ethical Committee approval was taken. Weight, height, waist circumference (C), hip C, head C and neck C of the children were measured. The complete blood count test was performed. C-reactive protein analysis was performed. Statistical analyses were performed using SPSS. The degree for statistical significance was p≤0.05. SII index values were progressively increasing starting from normal weight (NW) to MO children. There is a statistically significant difference between NW and OB as well as MO children. No significant difference was observed between NW and OW children, however, a correlation was observed between NW and OW children. MO constitutes the only group, which exhibited a statistically significant correlation between SII index and CRP. Obesity-related bladder, kidney, cervical, liver, colorectal, endometrial cancers are still being investigated. Obesity, characterized as a chronic low-grade inflammation, is a crucial risk factor for colon cancer. Elevated childhood BMI values may be indicative of processes leading to cancer, initiated early in life. Prevention of childhood adiposity may decrease the cancer incidence in adults. To authors’ best knowledge, this study is the first to introduce SII index values during obesity of varying degrees of severity. It is suggested that this index seems to affect all stages of obesity with an increasing tendency and may point out the concomitant status of obesity and cancer starting from very early periods of life.

Keywords: Children, c- reactive protein, systemic immune-inflammation index, obesity.

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324 ALDH1A1 as a Cancer Stem Cell Marker: Value of Immunohistochemical Expression in Benign Prostatic Hyperplasia, Prostatic Intraepithelial Neoplasia, and Prostatic Adenocarcinoma

Authors: H. M. Abdelmoneim, N. A. Babtain, A. S. Barhamain, A. Z. Kufiah, A. S. Malibari, S. F. Munassar, R. S. Rawa

Abstract:

Introduction: Prostate cancer is one of the most common causes of morbidity and mortality in men in developed countries. Cancer Stem Cells (CSCs) could be responsible for the progression and relapse of cancer. Therefore, CSCs markers could provide a prognostic strategy for human malignancies. Aldehyde dehydrogenase 1A1 (ALDH1A1) activity has been shown to be associated with tumorigenesis and proposed to represent a functional marker for tumor initiating cells in various tumor types including prostate cancer. Material & Methods: We analyzed the immunohistochemical expression of ALDH1A1 in benign prostatic hyperplasia (BPH), prostatic intraepithelial neoplasia (PIN) and prostatic adenocarcinoma and assessed their significant correlations in 50 TURP sections. They were microscopically interpreted and the results were correlated with histopathological types and tumor grade. Results: In different prostatic histopathological lesions we found that ALDH1A1 expression was low in BPH (13.3%) and PIN (6.7%) and then its expression increased with prostatic adenocarcinoma (40%), and this was statistically highly significant (P value = 0.02). However, in different grades of prostatic adenocarcinoma we found that the higher the Gleason grade the higher the expression for ALDH1A1 and this was statistically significant (P value = 0.02). We compared the expression of ALDH1A1 in PIN and prostatic adenocarcinoma. ALDH1A1 expression was decreased in PIN and highly expressed in prostatic adenocarcinoma and this was statistically significant (P value = 0.04). Conclusion: Increasing ALDH1A1 expression is correlated with aggressive behavior of the tumor. Immunohistochemical expression of ALDH1A1 might provide a potential approach to study tumorigenesis and progression of primary prostate carcinoma.

Keywords: ALDH1A1, BPH, PIN, prostatic adenocarcinoma.

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323 A Study of Liver Checkup in Patients with Hepatitis C in the Region of Batna

Authors: A. Zidani, M. Yahia K. Belhadi, S. Benbia

Abstract:

Hepatitis C is an infectious disease transmitted by blood and due to hepatitis C virus (HCV), which attacks the liver. The infection is characterized by liver inflammation (hepatitis) that is often asymptomatic but can progress to chronic hepatitis and later cirrhosis and liver cancer. Our problem tends to highlight on the one hand the prevalence of infectious disease in the population of the region of Batna and on other hand the biological characteristics of this disease by a screening and a specific diagnosis based on serological tests, liver checkup (measurement of haematological and biochemical parameters). The results showed: The serology of hepatitis C establishes the diagnosis of infection with hepatitis C. In this study and with the serological test, 24 cases of the disease of hepatitis C were found in 1000 suspected cases (7 cases with normal transaminases and 17 cases with elevated transaminases). The prevalence of this disease in this study population was 2.4%. The presence of hepatitis C disrupts liver function including the onset of cytolysis, cholestasis, jaundice, thrombocytopenia, and coagulation disorders.

Keywords: Disease hepatitis C, serology, liver checkup

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322 Attention Multiple Instance Learning for Cancer Tissue Classification in Digital Histopathology Images

Authors: Afaf Alharbi, Qianni Zhang

Abstract:

The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper presents a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network-based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation on an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.

Keywords: Attention Multiple Instance Learning, Multiple Instance Learning, transfer learning, histopathological slides, cancer tissue classification.

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