Search results for: cancer classification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4132

Search results for: cancer classification

2452 Proteomic Analysis of Excretory Secretory Antigen (ESA) from Entamoeba histolytica HM1: IMSS

Authors: N. Othman, J. Ujang, M. N. Ismail, R. Noordin, B. H. Lim

Abstract:

Amoebiasis is caused by the Entamoeba histolytica and still endemic in many parts of the tropical region, worldwide. Currently, there is no available vaccine against amoebiasis. Hence, there is an urgent need to develop a vaccine. The excretory secretory antigen (ESA) of E. histolytica is a suitable biomarker for the vaccine candidate since it can modulate the host immune response. Hence, the objective of this study is to identify the proteome of the ESA towards finding suitable biomarker for the vaccine candidate. The non-gel based and gel-based proteomics analyses were performed to identify proteins. Two kinds of mass spectrometry with different ionization systems were utilized i.e. LC-MS/MS (ESI) and MALDI-TOF/TOF. Then, the functional proteins classification analysis was performed using PANTHER software. Combination of the LC -MS/MS for the non-gel based and MALDI-TOF/TOF for the gel-based approaches identified a total of 273 proteins from the ESA. Both systems identified 29 similar proteins whereby 239 and 5 more proteins were identified by LC-MS/MS and MALDI-TOF/TOF, respectively. Functional classification analysis showed the majority of proteins involved in the metabolic process (24%), primary metabolic process (19%) and protein metabolic process (10%). Thus, this study has revealed the proteome the E. histolytica ESA and the identified proteins merit further investigations as a vaccine candidate.

Keywords: E. histolytica, ESA, proteomics, biomarker

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2451 Autophagy Acceleration and Self-Healing by the Revolution against Frequent Eating, High Glycemic and Unabsorbable Substances as One Meal a Day Plan

Authors: Reihane Mehrparvar

Abstract:

Human age could exceed further by altering gene expression through food intaking, although as a consequence of recent century eating patterns, human life-span getting shorter by emerging irregulating in autophagy mechanism, insulin, leptin, gut microbiota which are important etiological factors of type-2 diabetes, obesity, infertility, cancer, metabolic and autoimmune diseases. However, restricted calorie intake and vigorous exercise might be beneficial for losing weight and metabolic regulation in a short period but could not be implementable in the long term as a way of life. Therefore, the lack of a dietary program that is compatible with the genes of the body is essential. Sweet and high-glycemic-index (HGI) foods were associated with type-2 diabetes and cancer morbidity. The neuropsychological perspective characterizes the inclination of sweet and HGI-food consumption as addictive behavior; hence this process engages preference of gut microbiota, neural node, and dopaminergic functions. Moreover, meal composition is not the only factor that affects body hemostasis. In this narrative review, it is believed to attempt to investigate how the body responded to different food intakes and represent an accurate model based on current evidence. Eating frequently and ingesting unassimilable protein and carbohydrates may not be compatible with human genes and could cause impairments in the self-renovation mechanism. This trajectory indicates our body is more adapted to starvation and eating animal meat and marrow. Here has been recommended a model that takes into account three important factors: frequent eating, meal composition, and circadian rhythm, which may offer a promising intervention for obesity, inflammation, cardiovascular, autoimmune disorder, type-2 diabetes, insulin resistance, infertility, and cancer through intensifying autophagy-mechanism and eliminate medical costs.

Keywords: metabolic disease, anti-aging, type-2 diabetes, autophagy

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2450 The Antibacterial and Anticancer Activity of Marine Actinomycete Strain HP411 Isolated in the Northern Coast of Vietnam

Authors: Huyen T. Pham, Nhue P. Nguyen, Tien Q. Phi, Phuong T. Dang, Hy G. Le

Abstract:

Since the marine environmental conditions are extremely different from the other ones, so that marine actinomycetes might produce novel bioactive compounds. Therefore, actinomycete strains were screened from marine water and sediment samples collected from the coastal areas of Northern Vietnam. Ninety-nine actinomycete strains were obtained on starch-casein agar media by dilution technique, only seven strains, named HP112, HP12, HP411, HPN11, HP 11, HPT13 and HPX12, showed significant antibacterial activity against both gram-positive and gram-negative bacteria (Bacillus subtilis ATCC 6633, Staphylococcus epidemidis ATCC 12228, Escherichia coli ATCC 11105). Further studies were carried out with the most active HP411strain against Candida albicans ATCC 10231. This strain could grow rapidly on starch casein agar and other media with high salt containing 7-10% NaCl at 28-30oC. Spore-chain of HP411 showed an elongated and circular shape with 10 to 30 spores/chain. Identification of the strain was carried out by employing the taxonomical studies including the 16S rRNA sequence. Based on phylogenetic and phenotypic evidence it is proposed that HP411 to be belongs to species Streptomyces variabilis. The potent of the crude extract of fermentation broth of HP411that are effective against wide range of pathogens: both gram-positive, gram-negative and fungi. Further studies revealed that the crude extract HP411 could obtain the anticancer activity for cancer cell lines: Hep-G2 (liver cancer cell line); RD (cardiac and skeletal muscle letters cell line); FL (membrane of the uterus cancer cell line). However, the actinomycetes from marine ecosystem will be useful for the discovery of new drugs in the furture.

Keywords: marine actinomycetes, antibacterial, anticancer, Streptomyces variabilis

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2449 Using Machine-Learning Methods for Allergen Amino Acid Sequence's Permutations

Authors: Kuei-Ling Sun, Emily Chia-Yu Su

Abstract:

Allergy is a hypersensitive overreaction of the immune system to environmental stimuli, and a major health problem. These overreactions include rashes, sneezing, fever, food allergies, anaphylaxis, asthmatic, shock, or other abnormal conditions. Allergies can be caused by food, insect stings, pollen, animal wool, and other allergens. Their development of allergies is due to both genetic and environmental factors. Allergies involve immunoglobulin E antibodies, a part of the body’s immune system. Immunoglobulin E antibodies will bind to an allergen and then transfer to a receptor on mast cells or basophils triggering the release of inflammatory chemicals such as histamine. Based on the increasingly serious problem of environmental change, changes in lifestyle, air pollution problem, and other factors, in this study, we both collect allergens and non-allergens from several databases and use several machine learning methods for classification, including logistic regression (LR), stepwise regression, decision tree (DT) and neural networks (NN) to do the model comparison and determine the permutations of allergen amino acid’s sequence.

Keywords: allergy, classification, decision tree, logistic regression, machine learning

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2448 Shared Decision Making in Oropharyngeal Cancer: The Development of a Decision Aid for Resectable Oropharyngeal Carcinoma, a Mixed Methods Study

Authors: Anne N. Heirman, Lisette van der Molen, Richard Dirven, Gyorgi B. Halmos, Michiel W.M. van den Brekel

Abstract:

Background: Due to the rising incidence of oropharyngeal squamous cell cancer (OPSCC), many patients are challenged with choosing between transoral(robotic) surgery and radiotherapy, with equal survival and oncological outcomes. Also, functional outcomes are of little difference over the years. With this study, the wants and needs of patients and caregivers are identified to develop a comprehensible patient decision aid (PDA). Methods: The development of this PDA is based on the International Patient Decision Aid Standards criteria. In phase 1, relevant literature was reviewed and compared to current counseling papers. We interviewed ten post-treatment patients and ten doctors from four head and neck centers in the Netherlands, which were transcribed verbatim and analyzed. With these results, the first draft of the PDA was developed. Phase 2 beholds testing the first draft for comprehensibility and usability. Phase 3 beholds testing for feasibility. After this phase, the final version of the PDA was developed. Results: All doctors and patients agreed a PDA was needed. Phase 1 showed that 50% of patients felt well-informed after standard care and 35% missed information about treatment possibilities. Side effects and functional outcomes were rated as the most important for decision-making. With this information, the first version was developed. Doctors and patients stated (phase 2) that they were satisfied with the comprehensibility and usability, but there was too much text. The PDA underwent text reduction revisions and got more graphics. After revisions, all doctors found the PDA feasible and would contribute to regular counseling. Patients were satisfied with the results and wished they would have seen it before their treatment. Conclusion: Decision-making for OPSCC should focus on differences in side-effects and functional outcomes. Patients and doctors found the PDA to be of great value. Future research will explore the benefits of the PDA in clinical practice.

Keywords: head-and-neck oncology, oropharyngeal cancer, patient decision aid, development, shared decision making

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2447 Change of Endocrine and Exocrine Insufficiency on Non-Diabetes Patients after Distal Pancreatectomy: A Nationwide Database Study

Authors: Jin-Ming Wu, Te-Wei Ho, Yu-Wen Tien

Abstract:

Background: The aim of this population-based study was to determine the occurrence of diabetes and exocrine pancreatic insufficiencies (EPI) on non-diabetes subjects receiving distal pancreatectomy (DP). Method: A nationwide cohort study between 2000 and 2010 was collected from the Taiwan National Health Insurance Research Database. Among 3264 DP patients, we identified 1410 non-diabetes and 966 non-diabetes non-EPI. Results. Of 1410 non-diabetes DP subjects, 312 patients (22.1%) developed newly-diagnosed diabetes after PD. On a multiple logistic regression model, co-morbid hyperlipidemia (odds ratio, 1.640; 95% CI, 1.362–2.763; P < 0.001) and pancreatitis (odds ratio, 2.428; 95% CI, 1.889–3.121; P < 0.001) significantly contributed to higher incidences of diabetes after DP. Moreover, 380 subjects (39.3%) developed EPI, and pancreatic cancer is the statistically significant risk factor (odds ratio, 4.663; 95% CI, 2.108–6.085; P < 0.001). Conclusion: The patients with co-morbid hyperlipidemia and chronic pancreatitis had higher rates of newly-diagnosed diabetes after DP, moreover, pancreatic cancer subjects had higher rates of pancreatic exocrine insufficiency after DP. The clinicians should be alert to follow up glucose metabolism and clinical symptoms of fat intolerance for DP patients.

Keywords: distal pancreatectomy, National database, diabetes, exocrine insufficiency

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2446 Camptothecin Promotes ROS-Mediated G2/M Phase Cell Cycle Arrest, Resulting from Autophagy-Mediated Cytoprotection

Authors: Rajapaksha Gedara Prasad Tharanga Jayasooriya, Matharage Gayani Dilshara, Yung Hyun Choi, Gi-Young Kim

Abstract:

Camptothecin (CPT) is a quinolone alkaloid which inhibits DNA topoisomerase I that induces cytotoxicity in a variety of cancer cell lines. We previously showed that CPT effectively inhibited invasion of prostate cancer cells and also combined treatment with subtoxic doses of CPT and TNF-related apoptosis-inducing ligand (TRAIL) potentially enhanced apoptosis in a caspase-dependent manner in hepatoma cancer cells. Here, we found that treatment with CPT caused an irreversible cell cycle arrest in the G2/M phase. CPT-induced cell cycle arrest was associated with a decrease in protein levels of cell division cycle 25C (Cdc25C) and increased the level of cyclin B and p21. The CPT-induced decrease in Cdc25C was blocked in the presence of proteasome inhibitor MG132, thus reversed the cell cycle arrest. In addition to that treatment of CPT-increased phosphorylation of Cdc25C was the resulted of activation of checkpoint kinase 2 (Chk2), which was associated with phosphorylation of ataxia telangiectasia-mutated. Interestingly CPT induced G2/M phase of the cell cycle arrest is reactive oxygen species (ROS) dependent where ROS inhibitors NAC and GSH reversed the CPT-induced cell cycle arrest. These results further confirm by using transient knockdown of nuclear factor-erythroid 2-related factor 2 (Nrf2) since it regulates the production of ROS. Our data reveal that treatment of siNrf2 increased the ROS level as well as further increased the CPT induce G2/M phase cell cycle arrest. Our data also indicate CPT-enhanced cell cycle arrest through the extracellular signal-regulated kinase (ERK) and the c-Jun N-terminal kinase (JNK) pathway. Inhibitors of ERK and JNK more decreased the Cdc25C expression and protein expression of p21 and cyclin B. These findings indicate that Chk2-mediated phosphorylation of Cdc25C plays a major role in G2/M arrest by CPT.

Keywords: camptothecin, cell cycle, checkpoint kinase 2, nuclear factor-erythroid 2-related factor 2, reactive oxygen species

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2445 The Relationships among Self-Efficacy, Critical Thinking and Communication Skills Ability in Oncology Nurses for Cancer Immunotherapy in Taiwan

Authors: Yun-Hsiang Lee

Abstract:

Cancer is the main cause of death worldwide. With advances in medical technology, immunotherapy, which is a newly developed advanced treatment, is currently a crucial cancer treatment option. For better quality cancer care, the ability to communicate and critical thinking plays a central role in clinical oncology settings. However, few studies have explored the impact of communication skills on immunotherapy-related issues and their related factors. This study was to (i) explore the current status of communication skill ability for immunotherapy-related issues, self-efficacy for immunotherapy-related care, and critical thinking ability; and (ii) identify factors related to communication skill ability. This is a cross-sectional study. Oncology nurses were recruited from the Taiwan Oncology Nursing Society, in which nurses came from different hospitals distributed across four major geographic regions (North, Center, South, East) of Taiwan. A total of 123 oncology nurses participated in this study. A set of questionnaires were used for collecting data. Communication skill ability for immunotherapy issues, self-efficacy for immunotherapy-related care, critical thinking ability, and background information were assessed in this survey. Independent T-test and one-way ANOVA were used to examine different levels of communication skill ability based on nurses having done oncology courses (yes vs. no) and education years (< 1 year, 1-3 years, and > 3 years), respectively. Spearman correlation was conducted to understand the relationships between communication skill ability and other variables. Among the 123 oncology nurses in the current study, the majority of them were female (98.4%), and most of them were employed at a hospital in the North (46.8%) of Taiwan. Most of them possessed a university degree (78.9%) and had at least 3 years of prior work experience (71.7%). Forty-three of the oncology nurses indicated in the survey that they had not received oncology nurses-related training. Those oncology nurses reported moderate to high levels of communication skill ability for immunotherapy issues (mean=4.24, SD=0.7, range 1-5). Nurses reported moderate levels of self-efficacy for immunotherapy-related care (mean=5.20, SD=1.98, range 0-10) and also had high levels of critical thinking ability (mean=4.76, SD=0.60, range 1-6). Oncology nurses who had received oncology training courses had significantly better communication skill ability than those who had not received oncology training. Oncology nurses who had higher work experience (1-3 years, or > 3 years) had significantly higher levels of communication skill ability for immunotherapy-related issues than those with lower work experience (<1 year). When those nurses reported better communication skill ability, they also had significantly better self-efficacy (r=.42, p<.01) and better critical thinking ability (r=.47, p<.01). Taken altogether, courses designed to improve communication skill ability for immunotherapy-related issues can make a significant impact in clinical settings. Communication skill ability for oncology nurses is the major factor associated with self-efficacy and critical thinking, especially for those with lower work experience (< 1 year).

Keywords: communication skills, critical thinking, immunotherapy, oncology nurses, self-efficacy

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2444 Emotion Classification Using Recurrent Neural Network and Scalable Pattern Mining

Authors: Jaishree Ranganathan, MuthuPriya Shanmugakani Velsamy, Shamika Kulkarni, Angelina Tzacheva

Abstract:

Emotions play an important role in everyday life. An-alyzing these emotions or feelings from social media platforms like Twitter, Facebook, blogs, and forums based on user comments and reviews plays an important role in various factors. Some of them include brand monitoring, marketing strategies, reputation, and competitor analysis. The opinions or sentiments mined from such data helps understand the current state of the user. It does not directly provide intuitive insights on what actions to be taken to benefit the end user or business. Actionable Pattern Mining method provides suggestions or actionable recommendations on what changes or actions need to be taken in order to benefit the end user. In this paper, we propose automatic classification of emotions in Twitter data using Recurrent Neural Network - Gated Recurrent Unit. We achieve training accuracy of 87.58% and validation accuracy of 86.16%. Also, we extract action rules with respect to the user emotion that helps to provide actionable suggestion.

Keywords: emotion mining, twitter, recurrent neural network, gated recurrent unit, actionable pattern mining

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2443 Mage Fusion Based Eye Tumor Detection

Authors: Ahmed Ashit

Abstract:

Image fusion is a significant and efficient image processing method used for detecting different types of tumors. This method has been used as an effective combination technique for obtaining high quality images that combine anatomy and physiology of an organ. It is the main key in the huge biomedical machines for diagnosing cancer such as PET-CT machine. This thesis aims to develop an image analysis system for the detection of the eye tumor. Different image processing methods are used to extract the tumor and then mark it on the original image. The images are first smoothed using median filtering. The background of the image is subtracted, to be then added to the original, results in a brighter area of interest or tumor area. The images are adjusted in order to increase the intensity of their pixels which lead to clearer and brighter images. once the images are enhanced, the edges of the images are detected using canny operators results in a segmented image comprises only of the pupil and the tumor for the abnormal images, and the pupil only for the normal images that have no tumor. The images of normal and abnormal images are collected from two sources: “Miles Research” and “Eye Cancer”. The computerized experimental results show that the developed image fusion based eye tumor detection system is capable of detecting the eye tumor and segment it to be superimposed on the original image.

Keywords: image fusion, eye tumor, canny operators, superimposed

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2442 Represent Light and Shade of Old Beijing: Construction of Historical Picture Display Platform Based on Geographic Information System (GIS)

Authors: Li Niu, Jihong Liang, Lichao Liu, Huidi Chen

Abstract:

With the drawing of ancient palace painter, the layout of Beijing famous architect and the lens under photographers, a series of pictures which described whether emperors or ordinary people, whether gardens or Hutongs, whether historical events or life scenarios has emerged into our society. These precious resources are scattered around and preserved in different places Such as organizations like archives and libraries, along with individuals. The research combined decentralized photographic resources with Geographic Information System (GIS), focusing on the figure, event, time and location of the pictures to map them with geographic information in webpage and to display them productively. In order to meet the demand of reality, we designed a metadata description proposal, which is referred to DC and VRA standards. Another essential procedure is to formulate a four-tier classification system to correspond with the metadata proposals. As for visualization, we used Photo Waterfall and Time Line to display our resources in front end. Last but not the least, leading the Web 2.0 trend, the research developed an artistic, friendly, expandable, universal and user involvement platform to show the historical and culture precipitation of Beijing.

Keywords: historical picture, geographic information system, display platform, four-tier classification system

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2441 A New Approach of Preprocessing with SVM Optimization Based on PSO for Bearing Fault Diagnosis

Authors: Tawfik Thelaidjia, Salah Chenikher

Abstract:

Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approach

Keywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement

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2440 Network Based Molecular Profiling of Intracranial Ependymoma over Spinal Ependymoma

Authors: Hyeon Su Kim, Sungjin Park, Hae Ryung Chang, Hae Rim Jung, Young Zoo Ahn, Yon Hui Kim, Seungyoon Nam

Abstract:

Ependymoma, one of the most common parenchymal spinal cord tumor, represents 3-6% of all CNS tumor. Especially intracranial ependymomas, which are more frequent in childhood, have a more poor prognosis and more malignant than spinal ependymomas. Although there are growing needs to understand pathogenesis, detailed molecular understanding of pathogenesis remains to be explored. A cancer cell is composed of complex signaling pathway networks, and identifying interaction between genes and/or proteins are crucial for understanding these pathways. Therefore, we explored each ependymoma in terms of differential expressed genes and signaling networks. We used Microsoft Excel™ to manipulate microarray data gathered from NCBI’s GEO Database. To analyze and visualize signaling network, we used web-based PATHOME algorithm and Cytoscape. We show HOX family and NEFL are down-regulated but SCL family is up-regulated in cerebrum and posterior fossa cancers over a spinal cancer, and JAK/STAT signaling pathway and Chemokine signaling pathway are significantly different in the both intracranial ependymoma comparing to spinal ependymoma. We are considering there may be an age-dependent mechanism under different histological pathogenesis. We annotated mutation data of each gene subsequently in order to find potential target genes.

Keywords: systems biology, ependymoma, deg, network analysis

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2439 Compartmental Model Approach for Dosimetric Calculations of ¹⁷⁷Lu-DOTATOC in Adenocarcinoma Breast Cancer Based on Animal Data

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

Abstract:

Dosimetry is an indispensable and precious factor in patient treatment planning; to minimize the absorbed dose in vital tissues. In this study, In accordance with the proper characteristics of DOTATOC and ¹⁷⁷Lu, after preparing ¹⁷⁷Lu-DOTATOC at the optimal conditions for the first time in Iran, radionuclidic and radiochemical purity of the solution was investigated using an HPGe spectrometer and ITLC method, respectively. The biodistribution of the compound was assayed for treatment of adenocarcinoma breast cancer in bearing BALB/c mice. The results have demonstrated that ¹⁷⁷Lu-DOTATOC is a profitable selection for therapy of the tumors. Because of the vital role of internal dosimetry before and during therapy, the effort to improve the accuracy and rapidity of dosimetric calculations is necessary. For this reason, a new method was accomplished to calculate the absorbed dose through mixing between compartmental model, animal dosimetry and extrapolated data from animal to human and using MIRD method. Despite utilization of compartmental model based on the experimental data, it seems this approach may increase the accuracy of dosimetric data, confidently.

Keywords: ¹⁷⁷Lu-DOTATOC, biodistribution modeling, compartmental model, internal dosimetry

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2438 Predictive Modelling of Aircraft Component Replacement Using Imbalanced Learning and Ensemble Method

Authors: Dangut Maren David, Skaf Zakwan

Abstract:

Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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2437 Pancreatic Adenocarcinoma Correctly Diagnosed by EUS but nor CT or MRI

Authors: Yousef Reda

Abstract:

Pancreatic cancer has an overall dismal prognosis. CT, MRI and Endoscopic Ultrasound are most often used to establish the diagnosis. We present a case of a patient found on abdominal CT and MRI to have an 8 mm cystic lesion within the head of the pancreas which was thought to be a benign intraductal papillary mucinous neoplasm (IPMN). Further evaluation by EUS demonstrated a 1 cm predominantly solid mass that was proven to be an adenocarcinoma by EUS-guided FNA. The patient underwent a Whipple procedure. The final pathology confirmed a 1 cm pT1 N0 pancreatic ductal adenocarcinoma. Case: A 63-year-old male presented with left upper quadrant pain and an abdominal CT demonstrated an 8 mm lesion within the head of the pancreas that was thought to represent a side branch IPMN. An MRI also showed similar findings. Four months later due to ongoing symptoms an EUS was performed to re-evaluate the pancreatic lesion. EUS revealed a predominantly solid hypoechoic, homogeneous mass measuring 12 mm x 9 mm. EUS-guided FNA was performed and was positive for adenocarcinoma. The patient underwent a Whipple procedure that confirmed it to be a ductal adenocarcinoma, pT1N0. The solid mass was noted to be adjacent to a cystic dilation with no papillary architecture and scant epithelium. The differential diagnosis resided between cystic degeneration of a primary pancreatic adenocarcinoma versus malignant degeneration within a side-branch IPMN. Discussion: The reported sensitivity of CT for pancreatic cancer is approximately 90%. For pancreatic tumors, less than 3 cm the sensitivity of CT is reduced ranging from 67-77%. MRI does not significantly improve overall detection rates compared to CT. EUS, however is superior to CT in the detection of pancreatic cancer, in particular among lesions smaller than 3 cm. EUS also outperforms CT and MRI in distinguishing neoplastic from non-neoplastic cysts. In this case, both MRI and CT failed to detect a small pancreatic adenocarcinoma. The addition of EUS and FNA to abdominal imaging can increase overall accuracy for the diagnosis of neoplastic pancreatic lesions. It may be prudent that when small lesions although appearing as a benign IPMN should further be evaluated by EUS as this would lead to potentially identifying earlier stage pancreatic cancers and improve survival in a disease which has a dismal prognosis.

Keywords: IPMN, MRI, EUS, CT

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2436 Masked Candlestick Model: A Pre-Trained Model for Trading Prediction

Authors: Ling Qi, Matloob Khushi, Josiah Poon

Abstract:

This paper introduces a pre-trained Masked Candlestick Model (MCM) for trading time-series data. The pre-trained model is based on three core designs. First, we convert trading price data at each data point as a set of normalized elements and produce embeddings of each element. Second, we generate a masked sequence of such embedded elements as inputs for self-supervised learning. Third, we use the encoder mechanism from the transformer to train the inputs. The masked model learns the contextual relations among the sequence of embedded elements, which can aid downstream classification tasks. To evaluate the performance of the pre-trained model, we fine-tune MCM for three different downstream classification tasks to predict future price trends. The fine-tuned models achieved better accuracy rates for all three tasks than the baseline models. To better analyze the effectiveness of MCM, we test the same architecture for three currency pairs, namely EUR/GBP, AUD/USD, and EUR/JPY. The experimentation results demonstrate MCM’s effectiveness on all three currency pairs and indicate the MCM’s capability for signal extraction from trading data.

Keywords: masked language model, transformer, time series prediction, trading prediction, embedding, transfer learning, self-supervised learning

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2435 Application of Principle Component Analysis for Classification of Random Doppler-Radar Targets during the Surveillance Operations

Authors: G. C. Tikkiwal, Mukesh Upadhyay

Abstract:

During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving army, moving convoys etc. The Radar operator selects one of the promising targets into Single Target Tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper we present a technique using mathematical and statistical methods like Fast Fourier Transformation (FFT) and Principal Component Analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, fft, principal component analysis, eigenvector, octave-notes, dsp

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2434 The Role of Txnrd2 Deficiency in Epithelial-to-Mesenchymal-Transition (EMT) and Tumor Formation in Pancreatic Cancer

Authors: Chao Wu

Abstract:

Thioredoxin reductase 2 is a mitochondrial enzyme that belongs to the cellular defense against oxidative stress. We deleted mitochondrial Txnrd2 in a KrasG12D-driven pancreatic tumor model. Despite an initial increase in precursor lesions, tumor incidence decreased significantly. We isolated cancer cell lines from these genetically engineered mice and observed an impaired proliferation and colony formation. Reactive Oxygen Species, as determined by DCF fluorescence, were increased. We detected a higher mitochondrial copy number in Txnrd2-deficient cells (KTP). However, measurement of mitochondrial bioenergetics showed no impairment of mitochondrial function and comparable O₂-consumption and extracellular acidification rates. In addition, the mitochondrial complex composition was affected in Txnrd2 deleted cell lines. To gain better insight into the role of Txnrd2, we deleted Txnrd2 in clones from parental KrasG12D cell lines using Crispr/Cas9 technology. The deletion was confirmed by western blot and activity assay. Interestingly, and in line with previous RNA expression analysis, we saw changes in EMT markers in Txnrd2 deleted cell lines and control cell lines. This might help us explain the reduced tumor incidence in KrasG12D; Txnrd2∆panc mice.

Keywords: PDAC, TXNRD2, epithelial-to-mesenchymal-transition, ROS

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2433 Curative Role of Bromoenol Lactone, an Inhibitor of Phospholipase A2 Enzyme, during Cigarette Smoke Condensate Induced Anomalies in Lung Epithelium

Authors: Subodh Kumar, Sanjeev Kumar Sharma, Gaurav Kaushik, Pramod Avti, Phulen Sarma, Bikash Medhi, Krishan Lal Khanduja

Abstract:

Background: It is well known that cigarette smoke is one of the causative factors in various lung diseases especially cancer. Carcinogens and oxidant molecules present in cigarette smoke not only damage the cellular constituents (lipids, proteins, DNA) but may also regulate the molecular pathways involved in inflammation and cancer. Continuous oxidative stress caused by the constituents of cigarette smoke leads to higher PhospholipaseA₂ (PLA₂) activity, resulting in elevated levels of secondary metabolites whose role is well defined in cancer. To reduce the burden of chronic inflammation as well as oxidative stress, and higher levels of secondary metabolites, we checked the curative potential of PLA₂ inhibitor Bromoenol Lactone (BEL) during continuous exposure of cigarette smoke condensate (CSC). Aim: To check the therapeutic potential of Bromoenol Lactone (BEL), an inhibitor of PhospholipaseA₂s, in pathways of CSC-induced changes in type I and type II alveolar epithelial cells. Methods: Effect of BEL on CSC-induced PLA2 activity were checked using colorimetric assay, cellular toxicity using cell viability assay, membrane integrity using fluorescein di-acetate (FDA) uptake assay, reactive oxygen species (ROS) levels and apoptosis markers through flow cytometry, and cellular regulation using MAPKinases levels, in lung epithelium. Results: BEL significantly mimicked CSC-induced PLA₂ activity, ROS levels, apoptosis, and kinases level whereas improved cellular viability and membrane integrity. Conclusions: Current observations revealed that BEL may be a potential therapeutic agent during Cigarette smoke-induced anomalies in lung epithelium.

Keywords: cigarette smoke condensate, phospholipase A₂, oxidative stress, alveolar epithelium, bromoenol lactone

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2432 Targeting Apoptosis by Novel Adamantane Analogs as an Emerging Therapy for the Treatment of Hepatocellular Carcinoma Through EGFR, Bcl-2/BAX Cascade

Authors: Hanan M. Hassan, Laila Abouzeid, Lamya H. Al-Wahaibi, George S. G. Shehatou, Ali A. El-Emam

Abstract:

Cancer is a major public health problem and the second leading cause of death worldwide. In 2020, cancer diagnosis and treatment have been negatively affected by the coronavirus 2019 (COVID-19) pandemic. During the quarantine, because of the limited access to healthcare and avoiding exposure to COVID-19 as a contagious disease; patients of cancer suffered deferments in follow-up and treatment regimens leading to substantial worsening of disease, death, and increased healthcare costs. Thus, this study is designed to investigate the molecular mechanisms by which adamantne derivatives attenuate hepatocllular carcinoma experimentally and theoretically. There is a close association between increased resistance to anticancer drugs and defective apoptosis that considered a causative factor for oncogenesis. Cancer cells use different molecular pathways to inhibit apoptosis, BAX and Bcl-2 proteins have essential roles in the progression or inhibition of intrinsic apoptotic pathways triggered by mitochondrial dysfunction. Therefore, their balance ratio can promote the cellular apoptotic fate. In this study, the in vitro cytotoxic effects of seven synthetic adamantyl isothiorea derivatives were evaluated against five human tumor cell lines by MTT assay. Compounds 5 and 6 showed the best results, mostly against hepatocellular carcinoma (HCC). Hence, in vivo studies were performed in male Sprague-Dawley (SD) rats in which experimental hepatocellular carcinoma was induced with thioacetamide (TAA) (200 mg/kg, i.p., twice weekly) for 16 weeks. The most promising compounds, 5 and 6, were administered to treat liver cancer rats at a dose of 10 mg/kg/day for an additional two weeks, and the effects were compared with doxorubicin (DR), the anticancer drug. Hepatocellular carcinoma was evidenced by a dramatic increase in liver indices, oxidative stress markers, and immunohistochemical studies that were accompanied by a plethora of inflammatory mediators and alterations in the apoptotic cascade. Our results showed that treatment with adamantane derivatives 5 and 6 significantly suppressed fibrosis, inflammation, and other histopathological insults resulting in the diminished formation of hepatocyte tumorigenesis. Moreover, administration of the tested compounds resulted in amelioration of EGFR protein expression, upregulation of BAX, and lessening down of Bcl-2 levels that prove their role as apoptosis inducers. Also, the docking simulations performed for adamantane showed good fit and binding to the EGFR protein through hydrogen bond formation with conservative amino acids, which gives a shred of strong evidence for its hepatoprotective effect. In most analyses, the effects of compound 6 were more comparable to DR than compound 5. Our findings suggest that adamantane derivatives 5 and 6 are shown to have cytotoxic activity against HCC in vitro and in vivo, by more than one mechanism, possibly by inhibiting the TLR4-MyD88-NF-κB pathway and targeting EGFR signaling.

Keywords: adamantane, EGFR, HCC, apoptosis

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2431 Surfactant Free Synthesis of Magnetite/Hydroxyapatite Composites for Hyperthermia Treatment

Authors: M. Sneha, N. Meenakshi Sundaram

Abstract:

In recent times, magnetic hyperthermia is used for cancer treatment as a tool for active targeting of delivering drugs to the targeted site. It has a potential advantage over other heat treatment because there is no systemic buildup in organs and large doses are possible. The aim of this study is to develop a suitable magnetic biomaterial that can destroy the cancer cells as well as induce bone regeneration. In this work, the composite material was synthesized in two-steps. First, porous iron oxide nano needles were synthesized by hydrothermal process. Second, the hydroxyapatite, were synthesized from natural calcium (i.e., egg shell) and inorganic phosphorous source using wet chemical method. The crystalline nature is confirmed by powder X-ray diffraction analysis (XRD). Thermal analysis and the surface area of the material is studied by Thermo Gravimetric Analysis (TGA), Brunauer-Emmett and Teller (BET) technique. Scanning electron microscope (SEM) images show that the particles have nanoneedle-like morphology. The magnetic property is studied by vibrating sample magnetometer (VSM) technique which confirms the superparamagnetic behavior. This paper presents a simple and easy method for synthesis of magnetite/hydroxyapatite composites materials.

Keywords: iron oxide nano needles, hydroxyapatite, superparamagnetic, hyperthermia

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2430 Cytotoxicity of 13 South African Macrofungal Species and Mechanism/s of Action against Cancer Cell Lines

Authors: Gerhardt Boukes, Maryna Van De Venter, Sharlene Govender

Abstract:

Macrofungi have been used for the past two thousand years in Asian countries, and more recently in Western countries, for their medicinal properties. Biological activities include antimicrobial, antioxidant, anti-inflammatory, antidiabetic, anticancer and immunomodulatory to name a few. Several biologically active compounds have been identified and isolated. Macrofungal research in Africa is poorly documented and to the best of our knowledge non-existent. South Africa has a rich macrofungal biodiversity, which includes endemic and exotic macrofungal species. Ethanolic extracts of 13 macrofungal species, including mushrooms, bracket fungi and puffballs, were prepared and screened for cytotoxicity against a panel of seven cell lines, including A549 (human lung adenocarcinoma), HeLa (human cervical adenocarcinoma), HT-29 (human colorectal adenocarcinoma), MCF7 (human breast adenocarcinoma), MIA PaCa-2 (human pancreatic ductal adenocarcinoma), PC-3 (human prostate adenocarcinoma) and Vero (African green monkey kidney epithelial) cells using MTT. Cell lines were chosen according to the most prevalent cancer types affecting males and females in South Africa and globally, and the mutations they contain. Preliminary results have shown that three of the macrofungal genera, i.e. Fomitopsis, Gymnopilus and Pycnoporus, have shown cytotoxic activity, ranging between IC50 ~20 and 200 µg/mL. The molecular mechanism of action contributing to cell death investigated and being investigated include apoptosis (i.e. DNA cell cycle arrest, caspase-3 activation and mitochondrial membrane potential), autophagy (i.e. acridine orange and LC3B staining) and ER stress (i.e. thioflavin T staining and caspase-12) in the presence of melphalan, chloroquine and thapsigargin/tuncamycin as positive controls, respectively. The genus, Pycnoporus, has shown the best cytotoxicity of the three macrofungal genera. Future work will focus on the identification and isolation of novel active compounds and elucidating the mechanism/s of action.

Keywords: cancer, cytotoxicity, macrofungi, mechanism/s of action

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2429 A Case Study of Deep Learning for Disease Detection in Crops

Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

Abstract:

In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

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2428 Explainable Graph Attention Networks

Authors: David Pham, Yongfeng Zhang

Abstract:

Graphs are an important structure for data storage and computation. Recent years have seen the success of deep learning on graphs such as Graph Neural Networks (GNN) on various data mining and machine learning tasks. However, most of the deep learning models on graphs cannot easily explain their predictions and are thus often labelled as “black boxes.” For example, Graph Attention Network (GAT) is a frequently used GNN architecture, which adopts an attention mechanism to carefully select the neighborhood nodes for message passing and aggregation. However, it is difficult to explain why certain neighbors are selected while others are not and how the selected neighbors contribute to the final classification result. In this paper, we present a graph learning model called Explainable Graph Attention Network (XGAT), which integrates graph attention modeling and explainability. We use a single model to target both the accuracy and explainability of problem spaces and show that in the context of graph attention modeling, we can design a unified neighborhood selection strategy that selects appropriate neighbor nodes for both better accuracy and enhanced explainability. To justify this, we conduct extensive experiments to better understand the behavior of our model under different conditions and show an increase in both accuracy and explainability.

Keywords: explainable AI, graph attention network, graph neural network, node classification

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2427 Comparing the Detection of Autism Spectrum Disorder within Males and Females Using Machine Learning Techniques

Authors: Joseph Wolff, Jeffrey Eilbott

Abstract:

Autism Spectrum Disorders (ASD) are a spectrum of social disorders characterized by deficits in social communication, verbal ability, and interaction that can vary in severity. In recent years, researchers have used magnetic resonance imaging (MRI) to help detect how neural patterns in individuals with ASD differ from those of neurotypical (NT) controls for classification purposes. This study analyzed the classification of ASD within males and females using functional MRI data. Functional connectivity (FC) correlations among brain regions were used as feature inputs for machine learning algorithms. Analysis was performed on 558 cases from the Autism Brain Imaging Data Exchange (ABIDE) I dataset. When trained specifically on females, the algorithm underperformed in classifying the ASD subset of our testing population. Although the subject size was relatively smaller in the female group, the manual matching of both male and female training groups helps explain the algorithm’s bias, indicating the altered sex abnormalities in functional brain networks compared to typically developing peers. These results highlight the importance of taking sex into account when considering how generalizations of findings on males with ASD apply to females.

Keywords: autism spectrum disorder, machine learning, neuroimaging, sex differences

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2426 The Effectiveness of Scalp Cooling Therapy on Reducing Chemotherapy Induced Alopecia: A Critical Literature Review

Authors: M. Krishna

Abstract:

The study was intended to identify if scalp cooling therapy is effective on preventing chemotherapy-induced hair loss among cancer patients. Critical literature of non-randomized controlled trials was used to investigate whether scalp cooling therapy is effective on preventing chemotherapy-induced alopecia. The review identified that scalp cooling therapy is effective on preventing chemotherapy-induced alopecia. Most of the patients receiving chemotherapy experience alopecia. It is also perceived as the worst effect of chemotherapy. This may be severe and lead the patients to withdraw the chemo treatment. The image disturbance caused by alopecia will make the patient depressed and will lead to declined immunity. With the knowledge on effectiveness of scalp cooling therapy on preventing chemotherapy-induced alopecia, patient undergoing chemotherapy will not be hesitant to undergo the treatment. Patients are recommended to go through scalp cooling therapy every chemo cycle and the proper therapy duration is 30 minutes before, during chemo. The suggested duration of the scalp cooling therapy is 45-90 minutes for an effective and positive outcome. This finding is excluding other factors of alopecia such as menopause, therapeutic drugs, poor hair density, liver function problems, and drug regimes.

Keywords: alopecia, cancer, chemotherapy, scalp cooling therapy

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2425 Substantiate the Effects of Reactive Dyes and Aloe Vera on the Ultra Violet Protective Properties on Cotton Woven and Knitted Fabrics

Authors: Neha Singh

Abstract:

The incidence of skin cancer has been rising worldwide due to excessive exposure to sun light. Climatic changes and depletion of ozone layer allow the easy entry of UV rays on earth, resulting skin damages such as sunburn, premature skin ageing, allergies and skin cancer. Researches have suggested many modes for protection of human skin against ultraviolet radiation; avoidance to outdoor activities, using textiles for covering the skin, sunscreen and sun glasses. However, this paper gives an insight about how textile material specially woven and knitted cotton can be efficiently utilized for protecting human skin from the harmful ultraviolet radiations by combining reactive dyes with Aloe Vera. Selection of the fabric was based on their utility and suitability as per the climate condition of the country for the upper and lower garment. A standard dyeing process was used, and Aloe Vera molecules were applied by in-micro encapsulation technique. After combining vat dyes with Aloe Vera excellent UPF (Ultra violet Protective Factor) was observed. There is a significant change in the UPF of vat dyed cotton fabric after treatment with Aloe Vera.

Keywords: UV protection, aloe vera, protective clothing, reactive dyes, cotton, woven and knits

Procedia PDF Downloads 253
2424 Aboriginal Head and Neck Cancer Patients Have Different Patterns of Metastatic Involvement, and Have More Advanced Disease at Diagnosis

Authors: Kim Kennedy, Daren Gibson, Stephanie Flukes, Chandra Diwakarla, Lisa Spalding, Leanne Pilkington, Andrew Redfern

Abstract:

Introduction: The mortality gap in Aboriginal Head and Neck Cancer is well known, but the reasons for poorer survival are not well established. Aim: We aimed to evaluate the locoregional and metastatic involvement, and stage at diagnosis, in Aboriginal compared with non-Aboriginal patients. Methods: We performed a retrospective cohort analysis of 320 HNC patients from a single centre in Western Australia, identifying 80 Aboriginal patients and 240 non-Aboriginal patients matched on a 1:3 ratio by sites, histology, rurality, and age. We collected data on the patient characteristics, tumour features, regions involved, stage at diagnosis, treatment history, and survival and relapse patterns, including sites of metastatic and locoregional involvement. Results: Aboriginal patients had a significantly higher incidence of lung metastases (26.3% versus 13.7%, p=0.009). Aboriginal patients also had a numerically but non-statistically significant higher incidence of thoracic nodal involvement (10% vs 5.8%) and malignant pleural effusions (3.8% vs 2.5%). Aboriginal patients also had a numerically but not statistically significantly higher incidence of adrenal and bony involvement. Interestingly, non-Aboriginal patients had an increased rate of cutaneous (2.1% vs 0%) and liver metastases (4.6% vs 2.5%) compared with Aboriginal patients. In terms of locoregional involvement, Aboriginal patients were more than twice as likely to have contralateral neck involvement (58.8% vs 24.2%, p<0.00001), and 30% more likely to have ipsilateral neck lymph node involvement (78.8% vs 60%, p=0.002) than non-Aboriginal patients. Aboriginal patients had significantly more advanced disease at diagnosis (p=0.008). Aboriginal compared with non-Aboriginal patients were less likely to present with stage I (7.5% vs 22.5%), stage II (11.3% vs 13.8%), or stage III disease (13.8% vs 17.1%), and more likely to present with more advanced stage IVA (42.5% vs 34.6%), stage IVB (15% vs 7.1%), or stage IVC (10% vs 5%) disease (p=0.008). Number of regions of disease involvement was higher in Aboriginal patients (median 3, mean 3.64, range 1-10) compared with non-Aboriginal patients (median 2, mean 2.80, range 1-12). Conclusion: Aboriginal patients had a significantly higher incidence of lung metastases, and significantly more frequent involvement of ipsilateral and contralateral neck lymph nodes. Aboriginal patients also had significantly more advanced disease at presentation with a higher stage at diagnosis. We are performing further analyses to investigate explanations for these findings.

Keywords: head and neck cancer, Aboriginal, metastases, locoregional, pattern of relapse, sites of disease

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2423 Traditional Medicine and Islamic Holistic Approach in Palliative Care Management of Terminal Illpatient of Cancer

Authors: Mohammed Khalil Ur Rahman, Mohammed Alsharon, Arshad Muktar, Zahid Shaik

Abstract:

Any ailment can go into terminal stages, cancer being one such disease which is many times detected in latent stages. Cancer is often characterized by constitutional symptoms which are agonizing in nature which disturbs patients and their family as well. In order to relieve such intolerable symptoms treatment modality employed is known to be ‘Palliative Care’. The goal of palliative care is to enhance patient’s quality of life by relieving or rather reducing the distressing symptoms of patients such as pain, nausea/ vomiting, anorexia/loss of appetite, excessive salivation, mouth ulcers, weight loss, constipation, oral thrush, emaciation etc. which are due to the effect of disease or due to the undergoing treatment such as chemotherapy, radiation etc. Ayurveda and Unani as well as other traditional medicines is getting more and more international attention in recent years and Ayurveda and Unani holistic perspective of the disease, it seems that there are many herbs and herbomineral preparation which can be employed in the treatment of malignancy and also in palliative care. Though many of them have yet to be scientifically proved as anti-cancerous but there is definitely a positive lead that some of these medications relieve the agonising symptoms thereby making life of the patient easy. Health is viewed in Islam in a holistic way. One of the names of the Quran is al-shifa' meaning ‘that which heals’ or ‘the restorer of health’ to refer to spiritual, intellectual, psychological, and physical health. The general aim of medical science, according to Islam, is to secure and adopt suitable measures which, with Allah’s permission, help to preserve or restore the health of the human body. Islam motivates the Physician to view the patient as one organism. The patient has physical, social, psychological, and spiritual dimensions that must be considered in synthesis with an integrated, holistic approach. Aims & Objectives: - To suggest herbs which are mentioned in Ayurveda Unani with potential palliative activity in case of Cancer patients. - Most of tibb nabawi [Prophetic Medicine] is preventive medicine and must have been divinely inspired. - Spiritual Aspects of Healing: Prayer, dua, recitation of the Quran - Remembrance of Allah play a central role.Materials & Method: Literary review of the herbs supported with experiential evidence will be discussed. Discussion: On the basis of collected data subject will be discussed in length. Conclusion: Will be presented in paper.

Keywords: palliative care, holistic, Ayurvedic and Unani traditional system of medicine, Quran, hadith

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