Search results for: cancer prediction

Authors: M. R. Vijayakumar, K. Priyanka, Ramoji Kosuru, Lakshmi, Sanjay Singh

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Trans resveratrol (RES) is a non-flavonoid poly-phenolic compound proved for its therapeutic and preventive effect against various types of cancer. However, the practical application of RES in cancer treatment is limited because of its higher dose (up to 7.5 g/day in humans), low biological half life, rapid metabolism and faster elimination in mammals. PEGylated core-shell type lipid polymer hybrid nanoparticles are the novel drug delivery systems for long circulation and improved anti cancer effect of its therapeutic payloads. Therefore, the main objective of this study is to extend the biological half life (long circulation) and improve the therapeutic efficacy of RES through core shell type of nanoparticles. D-α-tocopheryl polyethylene glycol 1000 succinate (vitamin E TPGS), a novel surfactant is applied for the preparation of PEGylated lipid polymer hybrid nanoparticles. The prepared nanoparticles were evaluated by various state of the art techniques such as dynamic light scattering (DLS) technique for particle size and zeta potential, TEM for shape, differential scanning calorimetry (DSC) for interaction analysis and XRD for crystalline changes of drug. Entrapment efficiency and invitro drug release were determined by ultracentrifugation method and dialysis bag method, respectively. Cancer cell viability studies were performed by MTT assay, respectively. Pharmacokinetic studies after i.v administration were performed in sprague dawley rats. The prepared NPs were found to be spherical in shape with smooth surfaces. Particle size and zeta potential of prepared NPs were found to be in the range of 179.2±7.45 to 266.8±9.61 nm and -0.63 to -48.35 mV, respectively. DSC revealed absence of potential interaction. XRD study revealed presence of amorphous form in nanoparticles. Entrapment efficiency was found to be 83.7 % and drug release was found to be in controlled manner. MTT assay showed low MEC and pharmacokinetic studies showed higher AUC of nanoformulaition than its pristine drug. All these studies revealed that the RES loaded PEG modified core-shell type lipid polymer hybrid nanoparticles can be an alternative tool for chemopreventive and therapeutic application of RES in cancer.

Keywords: trans resveratrol, cancer nanotechnology, long circulating nanoparticles, bioavailability enhancement, core shell nanoparticles, lipid polymer hybrid nanoparticles

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Authors: Shauma L. Tamba

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This study examined whether morality is the most important aspect in actual behavior. The prediction was that people tend to behave in line with moral (as compared to competence) norms, especially when such norms are presented by their ingroup. The actual behavior that was tested was support for a military intervention without a mandate from the UN. In addition, this study also examined whether identification with the ingroup and religion moderated the effect of group and norm on support for the norm that was prescribed by their ingroup. The prediction was that those who identified themselves higher with the ingroup moral would show a higher support for the norm. Furthermore, the prediction was also that those who have religion would show a higher support for the norm in the ingroup moral rather than competence. In an online survey, participants were asked to read a scenario in which a military intervention without a mandate was framed as either the moral (but stupid) or smart (but immoral) thing to do by members of their own (ingroup) or another (outgroup) society. This study found that when people identified themselves with the smart (but immoral) norm, they showed a higher support for the norm. However, when people identified themselves with the moral (but stupid) norm, they tend to show a lesser support towards the norm. Most of the results in the study did not support the predictions. Possible explanations and implications are discussed.

Keywords: morality, competence, ingroup identification, religion, group norm

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Authors: Nima Dastanboo, Xiao-Qing Li, Hamed Gharibdoost

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The purpose of this study is to investigate about the geological properties ahead of a tunnel face with using Electrical Resistivity Tomography ERT and Tunnel Seismic Prediction TSP303 methods. In deep tunnels with hydro-geological conditions, it is important to study the geological structures of the region before excavating tunnels. Otherwise, it would lead to unexpected accidents that impose serious damage to the project. For constructing Nosoud tunnel in west of Iran, the ERT and TSP303 methods are employed to predict the geological conditions dynamically during the excavation. In this paper, based on the engineering background of Nosoud tunnel, the important results of applying these methods are discussed. This work demonstrates seismic method and electrical tomography as two geophysical techniques that are able to detect a tunnel. The results of these two methods were being in agreement with each other but the results of TSP303 are more accurate and quality. In this case, the TSP 303 method was a useful tool for predicting unstable geological structures ahead of the tunnel face during excavation. Thus, using another geophysical method together with TSP303 could be helpful as a decision support in excavating, especially in complicated geological conditions.

Keywords: tunnel seismic prediction (TSP303), electrical resistivity tomography (ERT), seismic wave, velocity analysis, low-velocity zones

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Authors: Behzad Behnia, Noah LaRussa-Trott

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In recent years, fibers have been successfully used as an additive to reinforce asphalt concrete materials and to enhance the sustainability and resiliency of transportation infrastructure. Roads covered with fiber-reinforced asphalt concrete (FRAC) require less frequent maintenance and tend to have a longer lifespan. The present work investigates the application of sasobit-coated aramid fibers in asphalt pavements and employs machine learning to develop prediction models to evaluate the cracking performance of FRAC materials. For the experimental part of the study, the effects of several important parameters such as fiber content, fiber length, and testing temperature on fracture characteristics of FRAC mixtures were thoroughly investigated. Two mechanical performance tests, i.e., the disk-shaped compact tension [DC(T)] and indirect tensile [ID(T)] strength tests, as well as the non-destructive acoustic emission test, were utilized to experimentally measure the cracking behavior of the FRAC material in both macro and micro level, respectively. The experimental results were used to train the supervised machine learning approach in order to establish prediction models for fracture performance of the FRAC mixtures in the field. Experimental results demonstrated that adding fibers improved the overall fracture performance of asphalt concrete materials by increasing their fracture energy, tensile strength and lowering their 'embrittlement temperature'. FRAC mixtures containing long-size fibers exhibited better cracking performance than regular-size fiber mixtures. The developed prediction models of this study could be easily employed by pavement engineers in the assessment of the FRAC pavements.

Keywords: fiber reinforced asphalt concrete, machine learning, cracking performance tests, prediction model

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Authors: Amira ben Hassine, A. Valverde, V. Serafín, C. Muñoz-San Martín, M. Garranzo-Asensio, M. Gamella, R. Barderas, M. Pedrero, N. Raouafi, S. Campuzano, P. Yáñez-Sedeño, J. M. Pingarrón

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This work describes the development of a dual electrochemical immunosensing platform for accurate determination of two target proteins, IL-13 Receptor α2 (IL-13Rα2) and E-cadherin (E-cad). The proposed methodology is based on the use of sandwich immunosensing approaches (involving horseradish peroxidase-labeled detector antibodies) implemented onto magnetic microbeads (MBs) and amperometric transduction at screen-printed dual carbon electrodes (SPdCEs). The magnetic bioconjugates were captured onto SPdCEs and the amperometric transduction was performed using the H2O2/hydroquinone (HQ) system. Under optimal experimental conditions, the developed bio platform demonstrates linear concentration ranges of 1.0–25 and 5.0-100 ng mL-1, detection limits of 0.28 and 1.04 ng mL-1 for E-cad and IL-13Rα2, respectively, and excellent selectivity against other non-target proteins. The developed immuno-platform also offers a good reproducibility among amperometric responses provided by nine different sensors constructed in the same manner (Relative Standard Deviation values of 3.1% for E-cad and 4.3% for IL-13Rα2). Moreover, obtained results confirm the practical applicability of this bio-platform for the accurate determination of the endogenous levels of both extracellular receptors in colon cancer cells (both intact and lysed) with different metastatic potential and serum and tissues from patients diagnosed with colorectal cancer at different grades. Interesting features in terms of, simplicity, speed, portability and sample amount required to provide quantitative results, make this immuno-platform more compatible than conventional methodologies with the clinical diagnosis and prognosis at the point of care.

Keywords: electrochemistry, mmunosensors, biosensors, E-cadherin, IL-13 receptor α2, cancer colorectal

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Authors: Yusuf S. Dambatta, Ahmed A. D. Sarhan

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Fused deposition modelling (FDM) is one of the most prominent rapid prototyping (RP) technologies which is being used to efficiently fabricate CAD 3D geometric models. However, the process is coupled with many drawbacks, of which the surface quality of the manufactured RP parts is among. Hence, studies relating to improving the surface roughness have been a key issue in the field of RP research. In this work, a technique of modelling the surface roughness in FDM is presented. Using experimentally measured surface roughness response of the FDM parts, an ANFIS prediction model was developed to obtain the surface roughness in the FDM parts using the main critical process parameters that affects the surface quality. The ANFIS model was validated and compared with experimental test results.

Keywords: surface roughness, fused deposition modelling (FDM), adaptive neuro fuzzy inference system (ANFIS), orientation

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Authors: Ammar Asma, Bouafia Nabiha, Dhahri Meriem, Ben Cheikh Asma, Ezzi Olfa, Chafai Rim, Njah Mansour

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Despite recent advances in treatment of the lung cancer patients, the prognosis remains poor. Information is limited regarding health related quality of life (QOL) status of advanced lung cancer patients. The purposes of this study were: to assess patient reported symptom burden, to measure their QOL, and to identify determinant factors associated with QOL. Materials/Methods: A cross sectional study of 60 patients was carried out from over the period of 03 months from February 1st to 30 April 2016. Patients were recruited in two department of health care: Pneumology department in a university hospital in Sousse and an oncology unit in a University Hospital in Kairouan. Patients with advanced stage (III and IV) of lung cancer who were hospitalized or admitted in the day hospital were recruited by convenience sampling. We used a questionnaire administrated and completed by a trained interviewer. This questionnaire is composed of three parts: demographic, clinical and therapeutic information’s, QOL measurements: based on the SF-36 questionnaire, Symptom’s burden measurement using the Lung Cancer Symptom Scale (LCSS). To assess Correlation between symptoms burden and QOL, we compared the scores of two scales two by two using the Pearson correlation. To identify factors influencing QOL in Lung cancer, a univariate statistical analysis then, a stepwise backward approach, wherein the variables with p< 0.2, were carried out to determine the association between SF-36 scores and different variables. Results: During the study period, 60 patients consented to complete symptom and quality of life questionnaires at a single point time (72% were recruited from day hospital). The majority of patients were male (88%), age ranged from 21 to 79 years with a mean of 60.5 years. Among patients, 48 (80%) were diagnosed as having non-small cell lung carcinoma (NSCLC). Approximately, 60 % (n=36) of patients were in stage IV, 25 % in stage IIIa and 15 % in stage IIIb. For symptom burden, the symptom burden index was 43.07 (Standard Deviation, 21.45). Loss of appetite and fatigue were rated as the most severe symptoms with mean scores (SD): 49.6 (25.7) and 58.2 (15.5). The average overall score of SF36 was 39.3 (SD, 15.4). The physical and emotional limitations had the lowest scores. Univariate analysis showed that factors which influence negatively QOL were: married status (p<0.03), smoking cessation after diagnosis (p<0.024), LCSS total score (p<0.001), LCSS symptom burden index (p<0.001), fatigue (p<0.001), loss of appetite (p<0.001), dyspnea (p<0.001), pain (p<0.002), and metastatic stage (p<0.01). In multivariate analysis, unemployment (p<0.014), smoking cessation after diagnosis (p<0.013), consumption of analgesic (p<0.002) and the indication of an analgesic radiotherapy (p<0.001) are revealed as independent determinants of QOL. The result of the correlation analyses between total LCSS scores and the total and individual domain SF36 scores was significant (p<0.001); the higher total LCSS score is, the poorer QOL is. Conclusion: A built in support of lung cancer patients would better control the symptoms and promote the QOL of these patients.

Keywords: quality of life, lung cancer, metastasis, symptoms burden

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Authors: Aneta Oblouková, Eva Vítková

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The article deals with the issue of water and sewerage charge rate prices in the Czech Republic. The research is specifically focused on the analysis of the development of the average prices of water and sewerage charge rate in the Czech Republic in the years 1994-2021 and on the validation of the chosen methodology relevant for the prediction of the development of the average prices of water and sewerage charge rate in the Czech Republic. The research is based on data collection. The data for this research was obtained from the Czech Statistical Office. The aim of the paper is to validate the relevance of the mathematical linear trend estimate technique for the calculation of the predicted average prices of water and sewerage charge rates. The real values of the average prices of water and sewerage charge rates in the Czech Republic in the years 1994-2018 were obtained from the Czech Statistical Office and were converted into a mathematical equation. The same type of real data was obtained from the Czech Statistical Office for the years 2019-2021. Prediction of the average prices of water and sewerage charge rates in the Czech Republic in the years 2019-2021 were also calculated using a chosen method -a linear trend estimation technique. The values obtained from the Czech Statistical Office and the values calculated using the chosen methodology were subsequently compared. The research result is a validation of the chosen mathematical technique to be a suitable technique for this research.

Keywords: Czech Republic, linear trend estimation, price prediction, water and sewerage charge rate

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Authors: Malo Pocheau-Lesteven, Olivier Le Maître

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Engineering and optimisation of complex systems is often achieved through multi-disciplinary analysis of the system, where each subsystem is modeled and interacts with other subsystems to model the complete system. The coherence of the output of the different sub-systems is achieved through the use of compatibility constraints, which enforce the coupling between the different subsystems. Due to the complexity of some sub-systems and the computational cost of evaluating their respective models, it is often necessary to build surrogate models of these subsystems to allow repeated evaluation these subsystems at a relatively low computational cost. In this paper, gaussian processes are used, as their probabilistic nature is leveraged to evaluate the likelihood of satisfying the compatibility constraints. This paper presents infilling strategies to build accurate surrogate models of the subsystems in areas where they are likely to meet the compatibility constraint. It is shown that these infilling strategies can reduce the computational cost of building surrogate models for a given level of accuracy. An application of these methods to velocity prediction programs used in offshore racing naval architecture further demonstrates these method's applicability in a real engineering context. Also, some examples of the application of uncertainty quantification to field of naval architecture are presented.

Keywords: infilling strategy, gaussian process, multi disciplinary analysis, velocity prediction program

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Authors: Herlin Vallejo, Jhon Osorio

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Quality is a concept that has gained importance in different scenarios over time, especially in the area of health. The nursing staff is one of the actors that contributes most to the care process and the satisfaction of the users in the evaluation of quality. However, until now, there are few tools to measure the quality of care in specialized performance scenarios. Patients receiving ambulatory cancer treatments can face various problems, which can increase their level of distress, so improving the quality of outpatient care for cancer patients should be a priority for oncology nursing. The experience of the patient in relation to the care in these services has been little investigated. The purpose of this study was to understand the perception that patients have about quality care in outpatient chemotherapy services. A qualitative, exploratory, descriptive study was carried out in 9 patients older than 18 years, diagnosed with cancer, who were treated at the Institute of Cancerology, in outpatient chemotherapy rooms, with a minimum of three months of treatment with curative intention and which had given your informed consent. The total of participants was determined by the theoretical saturation, and the selection of these was for convenience. Unstructured interviews were conducted, recorded and transcribed. The analysis of the information was done under the technique of content analysis. Three categories emerged that reflect the perception that patients have regarding quality care: patient-centered care, care with love and effects of care. Patients highlighted situations that show that care is centered on them, incorporating elements of patient-centered care from the institutional, infrastructure, qualities of care and what for them, in contrast, means inappropriate care. Care with love as a perception of quality care means for patients that the nursing staff must have certain qualities, perceive caring with love as a family affair, limits on care with love and the nurse-patient relationship. Quality care has effects on both the patient and the nursing staff. One of the most relevant effects was the confidence that the patient develops towards the nurse, besides to transform the unreal images about cancer treatment with chemotherapy. On the other hand, care with quality generates a commitment to self-care and is a facilitator in the transit of oncological disease and chemotherapeutic treatment, but from the perception of a healing transit. It is concluded that care with quality from the perception of patients, is a construction that goes beyond the structural issues and is related to an institutional culture of quality that is reflected in the attitude of the nursing staff and in the acts of Care that have positive effects on the experience of chemotherapy and disease. With the results, it contributes to better understand how quality care is built from the perception of patients and to open a range of possibilities for the future development of an individualized instrument that allows evaluating the quality of care from the perception of patients with cancer.

Keywords: nursing care, oncology service hospital, quality management, qualitative studies

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Authors: Aragorn Joaquin Pineda Dela Cruz

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Road traffic congestion is continually deteriorating in Hong Kong. The largest contributing factor is the increase in vehicle fleet size, resulting in higher competition over the utilisation of road space. This study proposes a project that can process closed-circuit television images and videos to provide real-time traffic detection and prediction capabilities. Specifically, a deep-learning model involving computer vision techniques for video and image-based vehicle counting, then a separate model to detect and predict traffic congestion levels based on said data. State-of-the-art object detection models such as You Only Look Once and Faster Region-based Convolutional Neural Networks are tested and compared on closed-circuit television data from various major roads in Hong Kong. It is then used for training in long short-term memory networks to be able to predict traffic conditions in the near future, in an effort to provide more precise and quicker overviews of current and future traffic conditions relative to current solutions such as navigation apps.

Keywords: intelligent transportation system, vehicle detection, traffic analysis, deep learning, machine learning, computer vision, traffic prediction

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Authors: Arezoo Fallahi, Fateme Aslibigi, Parvaneh Taymoori, Babak Nematshahrbabaki

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Background and Aims: Cancer of the cervix, one of cancer-related death, is the second most common cancer in women worldwide. It develops over time but it is one of the most preventable types of cancer and there is the available proper screening program for its preventing. Since Pap smear test is vital to prevent and control of disease but women do not accomplish it regularly. Therefore, this study was aimed to explore women's needs referring to health care centers for doing Pap smear test. Material and methods: In this study, an inductive qualitative method with content analysis approach was used. This survey was done in varamin city (is located capital of Iran) in year 2014. Through the purposive sampling 15 women's view of point referring to health care centers of for doing Pap smear test was surveyed. Inclusion criteria were: 20-50 years old married women, having experience Pap smear test and attendance to participate in the Study. Recorded semi- structured interviews were typed and analyzed through of content analysis method. To obtain trustworthiness and rigor of the data, the criteria of credibility, dependability, confirmability and transferability was used. Results: During the data analysis, four main categories of “role of health care team”, “role of organizations”, “social support” and “policies and administration system” were developed. The participants emphasized on making motivational rules and coordination among organizations to do behaviors related to women health. Conclusion: The findings of study showed that doing Pap smear test are attributed to appropriate and intimate interactions with health professionals, family support, encouraging legislation and policies and coordination and notification of organizations. Therefore, designers and stockholders of policies and health system should more consider to growth and involve other organizations toward women's health.

Keywords: qualitative approach, pap smear test, women, health care centers

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Authors: Lavinia B. Dulla

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The exploration study of the fuzzy regression approach attempts to present that fuzzy regression can be used as a possible alternative to classical regression. It likewise seeks to assess the differences and characteristics of simple linear regression and fuzzy regression using the width of prediction interval, mean absolute deviation, and variance of residuals. Based on the simple linear regression model, the fuzzy regression approach is worth considering as an alternative to simple linear regression when the sample size is between 10 and 20. As the sample size increases, the fuzzy regression approach is not applicable to use since the assumption regarding large sample size is already operating within the framework of simple linear regression. Nonetheless, it can be suggested for a practical alternative when decisions often have to be made on the basis of small data.

Keywords: fuzzy regression approach, minimum fuzziness criterion, interval regression, prediction interval

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Authors: Debasish Pradhan, Shaktiprasad Pradhan, Rakesh Kumar Pradhan, Gitanjali Tripathy

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Suppressors of cytokine signalling (SOCS1), a newly indentified antiapoptotic molecule is a downstream effector of the receptor tyrosine kinase-Ras signalling pathway. The current study has uncovered that SOCS1 may have wide and imperative capacities, particularly because of its close correlation with malignant tumors. To investigate the impact of SOCS1 on MDR, we analyzed the expression of P-gp and SOCS1 by immunohistochemistry and found there was a positive correlation between them. At that point, we effectively interfered with RNA translation by the contamination of siRNA of SOCS1 into MCF7/ADM breast cancer cell lines through a lentivirus, and the expression of the target gene was significantly inhibited. After RNAi, the drug resistance was reduced altogether and the expression of MDR1 mRNA and P-gp in MCF7/ADM cell lines demonstrated a significant decrease. Likewise, the expression of P53 protein increased in a statistically significant manner (p ≤ 0.01) after RNAi exposure. Moreover, flow cytometry analysis uncovers that cell cycle and anti-apoptotic enhancing capacity of cells changed after RNAi treatment. These outcomes proposed SOCS1 may take part in breast cancer MDR by managing MDR1 and P53 expression, changing cell cycle and enhancing the anti-apoptotic ability.

Keywords: breast cancer, multidrug resistance, SOCS1 gene, MDR1 gene, RNA interference

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Authors: Grzegorz Raniszewski, Zbigniew Kolacinski, Lukasz Szymanski, Slawomir Wiak, Lukasz Pietrzak, Dariusz Koza

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One of the most promising area for carbon nanotubes (CNTs) application is medicine. One of the most devastating diseases is cancer. Carbon nanotubes may be used as carriers of a slowly released drug. It is possible to use of electromagnetic waves to destroy cancer cells by the carbon nanotubes (CNTs). In our research we focused on thermal ablation by ferromagnetic carbon nanotubes (Fe-CNTs). In the cancer cell hyperthermia functionalized carbon nanotubes are exposed to radio frequency electromagnetic field. Properly functionalized Fe-CNTs join the cancer cells. Heat generated in nanoparticles connected to nanotubes warm up nanotubes and then the target tissue. When the temperature in tumor tissue exceeds 316 K the necrosis of cancer cells may be observed. Several techniques can be used for Fe-CNTs synthesis. In our work, we use high-temperature methods where arc-discharge is applied. Low-temperature systems are microwave plasma with assisted chemical vapor deposition (MPCVD) and hybrid physical-chemical vapor deposition (HPCVD). In the arc discharge system, the plasma reactor works with a pressure of He up to 0,5 atm. The electric arc burns between two graphite rods. Vapors of carbon move from the anode, through a short arc column and forms CNTs which can be collected either from the reactor walls or cathode deposit. This method is suitable for the production of multi-wall and single-wall CNTs. A disadvantage of high-temperature methods is a low purification, short length, random size and multi-directional distribution. In MPCVD system plasma is generated in waveguide connected to the microwave generator. Then containing carbon and ferromagnetic elements plasma flux go to the quartz tube. The additional resistance heating can be applied to increase the reaction effectiveness and efficiency. CNTs nucleation occurs on the quartz tube walls. It is also possible to use substrates to improve carbon nanotubes growth. HPCVD system involves both chemical decomposition of carbon containing gases and vaporization of a solid or liquid source of catalyst. In this system, a tube furnace is applied. A mixture of working and carbon-containing gases go through the quartz tube placed inside the furnace. As a catalyst ferrocene vapors can be used. Fe-CNTs may be collected then either from the quartz tube walls or on the substrates. Low-temperature methods are characterized by higher purity product. Moreover, carbon nanotubes from tested CVD systems were partially filled with the iron. Regardless of the method of Fe-CNTs synthesis the final product always needs to be purified for applications in medicine. The simplest method of purification is an oxidation of the amorphous carbon. Carbon nanotubes dedicated for cancer cell thermal ablation need to be additionally treated by acids for defects amplification on the CNTs surface what facilitates biofunctionalization. Application of ferromagnetic nanotubes for cancer treatment is a promising method of fighting with cancer for the next decade. Acknowledgment: The research work has been financed from the budget of science as a research project No. PBS2/A5/31/2013

Keywords: arc discharge, cancer, carbon nanotubes, CVD, thermal ablation

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Authors: Ghada Esheba, Ghadeer Aldoobi, Salwa Almalk, Abrar Alshareef, Eman Al-khairi, Eman Yaseen

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Background: In Saudi Arabia, ovarian cancer ranked seventh among female population and is the most common female genital tract malignancy after endometrial cancer. A slight increase in the incidence of ovarian cancer was observed from 2001–2008. Makkah, Riyadh, and the eastern region of Saudi Arabia had the highest incidence rate ratio for the number of ovarian cancer cases (1). Differentiating metastatic adenocarcinomas from primary ovarian carcinomas, especially those of endometrioid and mucinous type is clinically significant and a challenge for clinicians and pathologists, yet the distinction has important therapeutic and prognostic implications. Aim: To clarify the most important histopathological criteria to differentiate between primary ovarian surface epithelial tumors especially mucinous and endometrioid subtypes, and metastatic adenocarcinoma and to evaluate the value of a panel of antibodies consisting of CK7, CK20, and CDX-2 in the distinction between primary ovarian surface epithelial tumors and metastatic adenocarcinoma. Material and methods: This study was carried out on 26 cases of primary ovarian surface epithelial neoplasms and 14 cases of metastatic ovarian adenocarcinoma. All cases were studied immunohistochemically using CK7, CK20, and CDX-2. Results: All cases of primary ovarian adenocarcinoma were positive for CK7. 25% and 58% of mucinous borderline mucinous tumor and mucinous carcinoma respectively were positive for CK20. Only 42% of mucinous carcinoma were positive for CDX-2. All cases of endometrioid carcinomas were negative for both CK20 and CDX-2. All cases of metastatic adenocarcinoma from the colon were negative for CK7 and positive for CK20 and CDX-2. Conclusions: CK7 is an important positive marker for primary ovarian tumors, while CK20 and CDX-2 are useful markers for colorectal carcinoma metastatic to the ovary. Caution should be taken as primary ovarian mucinous tumors may stain positive for CK20, CDX-2, or both, however, they usually exhibit a focal pattern of reactivity.

Keywords: adenoma, endometrioid, malignancy, ovarian

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Authors: Kasi Viswanadh Matte, Abhisheh Kumar Mehata, M.S. Muthu

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Brest cancer, up-regulated with human epidermal growth factor receptor type-2 (HER-2) led to the concept of developing HER-2 targeted anticancer therapeutics. Docetaxel-loaded D-α-tocopherol polyethylene glycol succinate 1000 conjugated chitosan (TPGS-g-chitosan) nanoparticles were prepared with or without Trastuzumab decoration. The particle size and entrapment efficiency of conventional, non-targeted and targeted nanoparticles were found to be in the range of 126-186 nm and 74-78% respectively. In-vitro, MDA-MB-231 cells showed that docetaxel-loaded non-targeted and HER-2 receptor targeted TPGS-g-chitosan nanoparticles have enhanced the cellular uptake and cytotoxicity with a promising bioadhesion property, in comparison to conventional nanoparticles. The IC50 values of non-targeted and targeted nanoparticles from cytotoxic assay were found to be 43 and 223 folds higher than DocelTM. The in-vivo pharmacokinetic study showed 2.33, and 2.82-fold enhancement in relative bioavailability of docetaxel for non-targeted and HER-2 receptor targeted nanoparticles, respectively than DocelTM, and after i.v administration, non-targeted and targeted nanoparticle achieved 3.48 and 5.94 times prolonged half-life in comparison to DocelTM. The area under the curve (AUC), relative bioavailability (FR) and mean residence time (MRT) were found to be higher for non-targeted and targeted nanoparticles compared to DocelTM. Further, histopathology results of non-targeted and targeted nanoparticles showed less toxicity on vital organs such as lungs, liver, and kidney compared to DocelTM.

Keywords: breast cancer, HER-2 receptor, targeted nanomedicine, chitosan, TPGS

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Authors: Philippa Sambevski

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Breast cancer is the most common cancer diagnosed in Australian women. The incidence of breast cancer for Aboriginal and Torres Strait Islander (ATSI) women is lower than for non-indigenous women. However, the mortality rate for ATSI women is higher. The participation rate of ATSI women in BreastScreen Australia is below the general population. In this thematic literature review, the author collates viable strategies to increase breast screening rates among culturally and linguistically diverse individuals and provide culturally competent care. Barriers to accessing BreastScreen for ATSI women include language or communication limits, isolation, and a lack of culturally sensitive information. Culturally competent strategies require healthcare workers with an appropriate cultural and social background, clear messages, and the embedding of cultural respect within healthcare organisations. Cultural safety is determined by partnering with local indigenous groups, recognising the consumer experience, and allowing people to raise their concerns. The corresponding academic poster identifies strategies for healthcare workers to provide culturally competent care in a BreastScreen setting.

Keywords: breast screen, closing the gap, Australia, cultural safety, Aboriginal and Torres Strait Islander

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Authors: Amir Hossein Hejazi, Nima Amjady

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In recent years, due to environmental issues traditional energy sources had been replaced by renewable ones. Wind energy as the fastest growing renewable energy shares a considerable percent of energy in power electricity markets. With this fast growth of wind energy worldwide, owners and operators of wind farms, transmission system operators, and energy traders need reliable and secure forecasts of wind energy production. In this paper, a new forecasting strategy is proposed for short-term wind power prediction based on Echo State Networks (ESN). The forecast engine utilizes state-of-the-art training process including dynamical reservoir with high capability to learn complex dynamics of wind power or wind vector signals. The study becomes more interesting by incorporating prediction of wind direction into forecast strategy. The Big Bang-Big Crunch (BB-BC) evolutionary optimization algorithm is adopted for adjusting free parameters of ESN-based forecaster. The proposed method is tested by real-world hourly data to show the efficiency of the forecasting engine for prediction of both wind vector and wind power output of aggregated wind power production.

Keywords: wind power forecasting, echo state network, big bang-big crunch, evolutionary optimization algorithm

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Authors: Amiel Satvedi, Richard Pyne

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Injuries in professional sports occur on a regular basis. Some may be minor, while others can cause huge impact on a player's career and earning potential. In soccer, there is a high risk of players picking up injuries during game time. This research work seeks to help soccer players reduce the risk of getting injured by predicting the likelihood of injury while playing in the near future and then providing recommendations for intervention. The injury prediction tool will use a soccer player's number of minutes played on the field, number of appearances, distance covered and performance data for the current and previous seasons as variables to conduct statistical analysis and provide injury predictive results using a machine learning linear regression model.

Keywords: injury predictor, soccer injury prevention, machine learning in soccer, big data in soccer

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Authors: Noor Shafifiyaz Mohd Yazid, Najihah Mohd Hashim, Hapipah Mohd Ali, Syam Mohan, Rosea Go

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Artocarpus kemando is a plant species from Moraceae family. This plant is used as household utensil by the local and the fruits are edible. The plants’ bark was used for the extraction process and yielded the chloroform crude extract which was used to screen for anticancer potential. The cytotoxic effect of the extract on CAOV-3 and WRL 68 cell lines were determined using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide or MTT assays. Qualitative AO/PI assay was performed to confirm the apoptosis and necrosis process. Meanwhile, the measurement of cell loss, nuclear morphology, DNA content, cell membrane permeability, mitochondrial membrane potential changes and cytochrome c release from mitochondria were detected through cytotoxicity 3 assay. In MTT assay, A. kemando inhibited 50% growth of CAOV-3 cells at 27.9 ± 0:03, 20.1± 0:03, 18.21± 0:04 µg/mL after 24, 48 and 72 hour, respectively. The morphology changes can be seen on CAOV-3 with a production of cell membrane blebbing, cromatin condensation and apoptotic bodies. Evaluation of cytotoxicity 3 on CAOV-3 cells after treated with extract resulting loss of mitochondrial membrane potential and release of cytochrome c from mitochondria. The results demonstrated A. kemando has potentially anticancer agent, particularly on human ovarian cancer.

Keywords: anticancer, Artocarpus kemando, ovarian cancer, cytotoxicity

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Authors: Ibtissem El Ouar, Cornelia Braicu, Dalila Naimi, Alexendru Irimie, Ioana Berindan-Neagoe

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Helix aspersa, 'the garden snail' is a big land snail widely found in the Mediterranean countries, it is one of the most consumed species in the west of Algeria. It is commonly used in zootherapy to purify blood and to treat cardiovascular diseases and liver problems. The aim of our study is to investigate, the antitumor activity of an aqueous extract from Helix aspersa prepared by the traditional method on Hs578T; a triple negative breast cancer cell line. Firstly, the free radical scavenging activity of H. aspersa extract was assessed by measuring its capability for scavenging the radical 2,2-diphenyl-1-picrylhydrazyl (DPPH), as well as its ability to reduce ferric ion by the FRAP assay (ferric reducing ability). The cytotoxic effect of H. aspersa extract against Hs578T cells was evaluated by the MTT test (3-(4,5- dimethylthiazl-2-yl)-2,5- diphenyltetrazolium bromide)) while the mode of cell death induced by the extract has been determined by fluorescence microscopy using acredine orange/ethidium bromide (AO/EB) probe. The level of TNFα has also measured in cell medium by ELISA method. The results suggest that H. aspersa extract has an antioxidant activity, especially at high concentrations, it can reduce DPPH radical and ferric ion. The MTT test shows that H. aspersa extract has a great cytotoxic effect against breast cancer cells, the IC50 value correspond of the dilution 1% of the crude extract. Moreover, the AO/EB staining shows that TNFα induced necrosis is the main form of cell death induced by the extract. In conclusion, the present study may open new perspectives in the search for new natural anticancer drugs.

Keywords: breast cancer, Helix aspersa, Hs578t cell line, necrosis

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Authors: M. Marjaneh, M. Y. Narazah, H. Shahrul

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Array-based gene expression analysis is a powerful tool to profile expression of genes and to generate information on therapeutic effects of new anti-cancer compounds. Anti-apoptotic effect of thymoquinone was studied in MCF7 breast cancer cell line using gene expression profiling with cDNA micro array. The purity and yield of RNA samples were determined using RNeasyPlus Mini kit. The Agilent RNA 6000 Nano LabChip kit evaluated the quantity of the RNA samples. AffinityScript RT oligo-dT promoter primer was used to generate cDNA strands. T7 RNA polymerase was used to convert cDNA to cRNA. The cRNA samples and human universal reference RNA were labelled with Cy-3-CTP and Cy-5-CTP, respectively. Feature Extraction and GeneSpring software analysed the data. The single experiment analysis revealed involvement of 64 pathways with up-regulated genes and 78 pathways with down-regulated genes. The MAPK and p38-MAPK pathways were inhibited due to the up-regulation of PTPRR gene. The inhibition of p38-MAPK suggested up-regulation of TGF-ß pathway. Inhibition of p38 - MAPK caused up-regulation of TP53 and down-regulation of Bcl2 genes indicating involvement of intrinsic apoptotic pathway. Down-regulation of CARD16 gene as an adaptor molecule regulated CASP1 and suggested necrosis-like programmed cell death and involvement of caspase in apoptosis. Furthermore, down-regulation of GPCR, EGF-EGFR signalling pathways suggested reduction of ER. Involvement of AhR pathway which control cytochrome P450 and glucuronidation pathways showed metabolism of Thymoquinone. The findings showed differential expression of several genes in apoptosis pathways with thymoquinone treatment in estrogen receptor-positive breast cancer cells.

Keywords: cDNA microarray, thymoquinone, CARD16, PTPRR, CASP10

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Authors: L. Mallesha, P. Mallu, B. Veeresh

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In the present study, 2, 6-diflurobenzohydrazide and 4-fluorophenylisothiocyanate were used as the starting materials to synthesize 5-phenyl-N3-(4-fluorophenyl)-4H-1, 2, 4-triazole-3, 4-diamine. Further, compound 5-phenyl-N3-(4-fluorophenyl)-4H-1, 2, 4-triazole-3,4-diamine reacted with fluoro substituted benzaldehydes to yield a series of Schiff bases. All the final compounds were characterized using IR, 1H NMR, 13C NMR, MS and elemental analyses. New compounds were evaluated for their antiproliferative effect using the MTT assay method against four human cancer cell lines (K562, COLO-205, MDA-MB231, and IMR-32) for the time period of 24 h. Among the series, few compounds showed good activity on all cell lines, whereas the other compounds in the series exhibited moderate activity.

Keywords: Schiff bases, MTT assay, antiproliferative activity, human cancer cell lines, 1, 2, 4-triazoles

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

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The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: big data, machine learning, smart city, social cost, transportation network

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Authors: Hacer Kobya Bulut, Ilknur Kahriman, Birsel C. Demirbag

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Introduction and Purpose: The lives of children with cancer are affected by long term hospitalizations in a negative way due to complications arising from diagnosis or treatment. However, the children's parents are known to have difficulties in meeting their children’s needs and providing home care after cancer treatment or during remission process. Supporting these children and their parents by giving a planned discharge training starting from the hospital and home care leads to reducing hospital applications, hospitalizations, hospital costs, shortening the length of hospital stay and increasing the satisfaction of the children with cancer and their families. This study was conducted to investigate the status of children and their parents' unplanned application to hospital and re-hospitalization. Methods: The study was carried out with 65 children with hematological malignancy in 0-17 age group and their families in a hematology clinic and polyclinic of a university hospital in Trabzon. Data were collected with survey methodology between August-November, 2015 through face to face interview using numbers, percentage and chi-square test in the evaluation. Findings: Most of the children were leukemia (90.8%) and 49.2% had been ill over 13 months. Few of the parents (32.3%) stated that they had received discharge and home care training (24.6%) but most of them (69.2%) found themselves enough in providing home care. Very few parents (6.2%) received home care training after their children being discharged and the majority of parents (61.5%) faced difficulties in home care and had no one to call around them. The parents expressed that in providing care to their children with hematological malignance, they faced difficulty in feeding them (74.6%), explaining their disease (50.0%), giving their oral medication (47.5%), providing hygiene (43.5%) and providing oral care (39.3%). The question ‘What are the emergency situations in which you have to bring your children to a doctor immediately?' was replied as fever (89.2%), severe nausea and vomiting (87.7%), hemorrhage (86.2%) and pain (81.5%). The study showed that 50.8% of the children had unplanned applications to hospitals and 33.8% of them identified as unplanned hospitalization and the first causes of this were fever and pain. The study showed that the frequency of applications (%78.8) and hospitalizations (%81.8) was higher for boys and a statistically significant difference was found between gender and unplanned applications (X=4.779; p=0.02). Applications (48.5%) and hospitalizations (40.9%) were found lower for the parents who had received hospital discharge training, and a significant difference was determined between receiving training and unplanned hospitalizations (X=8.021; p=0.00). Similarly, applications (30.3%) and hospitalizations (40.9%) was found lower for the ones who had received home care training, and a significant difference was determined between receiving home care training and unplanned hospitalizations (X=4.758; p=0.02). Conclusion: It was found out that caregivers of children with cancer did not receive training related to home care and complications about treatment after discharging from hospital, so they faced difficulties in providing home care and this led to an increase in unplanned hospital applications and hospitalizations.

Keywords: cancer, children, unplanned application, unplanned hospitalization

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Authors: Hui Zhang, Sherif Beskhyroun

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Structural Health monitoring systems (SHM) are commonly used to identify and assess structural damage. In terms of damage detection, SHM needs to periodically collect data from sensors placed in the structure as damage-sensitive features. This includes abnormal changes caused by the strain field and abnormal symptoms of the structure, such as damage and deterioration. Currently, deploying sensors on a large scale in a building structure is a challenge. In this study, a highly stretchable strain sensors are used in this study to collect data sets of strain generated on the surface of full-size reinforced concrete (RC) frames under extreme cyclic load application. This sensing sheet can be switched freely between the test bending strain and the axial strain to achieve two different configurations. On this basis, the deep neural network prediction model of the frame beam and frame column is established. The training results show that the method can accurately predict the strain value and has good generalization ability. The two deep neural network prediction models will also be deployed in the SHM system in the future as part of the intelligent strain sensor system.

Keywords: strain sensing sheets, deep neural networks, strain measurement, SHM system, RC frames

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Authors: Fernanda Rodriguez

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Breast cancer is pervasive among women, and an increasing number of women are opting for a mastectomy: a medical operation in which one or both breasts are removed with the intention of treating or averting breast cancer. However, there is an emerging population of cancer survivors in European nations that, rather than attempting to reconstruct their breasts to resemble as much as possible ‘normal’ breasts, have turned to dress their scars with decorative tattoos. At a practical level, this study hopes to improve the support systems of these women by possibly providing professionals in the medical field, tattoo artists, and family members of cancer survivors with a deeper understanding of their motivations and decision-making processes for choosing an alternative restorative route - such as decorative tattoos - after their mastectomy. At an intellectual level, however, this study aims to narrow a gap in the academic field concerning the relationship between mastectomies and alternative methods of healing, such as decorative tattoos, as well as to broaden the understanding regarding meaning-making and the ‘normal’ feminine body. Thus, by means of semi-structured interviews and a phenomenological standpoint, this research set itself the goal to understand why do women who have undergone a mastectomy choose to dress their scars with decorative tattoos instead of attempting to regain ‘normalcy’ through breast reconstruction or 3D areola tattoos? The results obtained from the interviews with fifteen women showed that the disillusionment with one part of the other of breast restoration techniques had led these women to find an alternative form of healing that allows them not only to close a painful chapter of their life but also to regain control over their bodies after a period of time in which agency was taking away from them. Decorative post-mastectomy tattoos allow these women to grant their bodies with new meanings and produce their own interpretation of their feminine body and identity.

Keywords: alternative femininity, decorative mastectomy tattoos, gender embodiment, social stigmatization

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Authors: Pedro Paulo Galindo Francisco, Eli Dhadad Junior

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This study addresses the Meese-Rogoff Puzzle by introducing the latest machine learning techniques as alternatives for predicting the exchange rates. Using RMSE as a comparison metric, Meese and Rogoff discovered that economic models are unable to outperform the random walk model as short-term exchange rate predictors. Decades after this study, no statistical prediction technique has proven effective in overcoming this obstacle; although there were positive results, they did not apply to all currencies and defined periods. Recent advancements in artificial intelligence technologies have paved the way for a new approach to exchange rate prediction. Leveraging this technology, we applied five machine learning techniques to attempt to overcome the Meese-Rogoff puzzle. We considered daily data for the real, yen, British pound, euro, and Chinese yuan against the US dollar over a time horizon from 2010 to 2023. Our results showed that none of the presented techniques were able to produce an RMSE lower than the Random Walk model. However, the performance of some models, particularly LSTM and N-BEATS were able to outperform the ARIMA model. The results also suggest that machine learning models have untapped potential and could represent an effective long-term possibility for overcoming the Meese-Rogoff puzzle.

Keywords: exchage rate, prediction, machine learning, deep learning

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Authors: Poonam Goswami

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Background: The diagnosis of a serious illness like cancer can have an impact on a patient’s emotional well-being and may result in psychological symptoms, anxiety, depression, and loss of control. Advance care planning discussions ensure patients’ values and goals of care, including patients’ freedom to choose their place of death, are respected. Unfortunately, these discussions are often delayed and are not initiated early in patients’ cancer trajectory. As a result, patients’ wishes often remains unknown until the last phase of their life. Evidence suggests that many patients inappropriately receive aggressive treatment near the end of life, which does lead to higher resource utilization, decreased quality of life, and increased cost. Additionally, the novel coronavirus disease 2019 (COVID-19) pandemic challenged the health care systems worldwide and raised important ethical issues, especially regarding the potential need for rationing health care in the context of scarce resources and crisis capacity. The importance of goal concordant care is now even substantially important and is heightened in the context of this pandemic. Problem: Although there is growing evidence on the effects of the ACP on the completion of advanced directives, improved patient and family concordance for preferences for medical care, and receipt of care, there is still a lack of standardized ACP conversation strategies for patients with cancer. Methods: The Key concepts of ACP include (1) assessing patient and family readiness, (2) identifying a surrogate decision maker ( medical power of attorney), (3) exploring patient and family understanding of the disease and treatment options,(4) discussing the values and goals of care, and options for end-of-life care, (5) documenting patient preferences in the medical record, and (6) revisiting the discussions at every change in the treatment plan and /or change in clinical status, including at every hospitalization. Conclusion/Implication for practice: Advance Care Planning (ACP) and end-of-life (EOL) discussions are important for patients, families, and health care providers. Adopting the verbal and nonverbal communication strategies can help overcome the barriers to effective communication on these difficult discussions. ACP with goals of care discussions should not be delayed until the patient is hospitalized.

Keywords: advance care planning, end of life, cancer, global, pandemic

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