Search results for: cancer classification

Authors: Saad Al-Shibli, Nasser Amjad, Muna Al Kubaisi, Norra Harun, Shaikh Mizan

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Leptin is a multifunctional hormone produced mainly by adipocyte. Leptin and its receptor have long been found associated with breast cancer. The main aim of this study is to investigate the correlation between Leptin/Leptin receptor and the clinicopathological features of breast cancer. Blood samples for ELISA, tissue samples from tumors and adjacent breast tissue were taken from 51 women with breast cancer with a control group of 40 women with a negative mammogram. Leptin and Leptin receptor in the tissues were estimated by immunohistochemistry (IHC). They were localized at the subcellular level by immunocytochemistry using transmission electron microscopy (TEM). Our results showed significant difference in serum leptin level between control and the patient group, but no difference between pre and post-operative serum leptin levels in the patient group. By IHC, we found that the majority of the breast cancer cells studied, stained positively for leptin and leptin receptors with co-expression of leptin and its receptors. No significant correlation was found between leptin/leptin receptors expression with the race, menopausal status, lymph node metastasis, estrogen receptor expression, progesterone receptor expression, HER2 expression and tumor size. Majority of the patients with distant metastasis were associated with high leptin and leptin receptor expression. TEM views both Leptin and Leptin receptor were found highly concentrated within and around the nucleus of the cancer breast cells, indicating nucleus is their principal seat of actions while the adjacent breast epithelial cells showed that leptin gold particles are scattered all over the cell with much less than that of the cancerous cells. However, presence of high concentration of leptin does not necessarily prove its over-expression, because it could be internalized from outside by leptin receptor in the cells. In contrast, leptin receptor is definitely over-expressed in the ductal breast cancer cells. We conclude that reducing leptin levels, blocking its downstream tissue specific signal transduction, and/or blocking the upstream leptin receptor pathway might help in prevention and therapy of breast cancer.

Keywords: breast cancer, expression, leptin, leptin receptors

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Authors: Fakhrosadat Sajjadian, Ramin Ghasemi Shayan

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The tumor microenvironment plays an fundamental part in tumor start, movement, metastasis, and treatment resistance. It varies from ordinary tissue in terms of its extracellular network, vascular and lymphatic arrange, as well as physiological conditions. The clinical application of atomic cancer imaging is regularly prevented by the tall commercialization costs of focused on imaging operators as well as the constrained clinical applications and little showcase measure of a few operators. . Since numerous cancer types share comparable characteristics of the tumor microenvironment, the capacity to target these biomarkers has the potential to supply clinically translatable atomic imaging advances for numerous types encompassing cancer and broad clinical applications. Noteworthy advance has been made in focusing on the tumor microenvironment for atomic cancer imaging. In this survey, we summarize the standards and methodologies of later progresses in atomic imaging of the tumor microenvironment, utilizing distinctive imaging modalities for early discovery and conclusion of cancer. To conclude, The tumor microenvironment (TME) encompassing tumor cells could be a profoundly energetic and heterogeneous composition of safe cells, fibroblasts, forerunner cells, endothelial cells, flagging atoms and extracellular network (ECM) components.

Keywords: molecular, imaging, TME, medicine

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Authors: Taner Ersoz, Filiz Ersoz, Seyma Ozbilge

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In this study, the clients who applied to a bank branch for loan were analyzed through data mining. The study was composed of the information such as amounts of loans received by personal and SME clients working with the bank branch, installment numbers, number of delays in loan installments, payments available in other banks and number of banks to which they are in debt between 2010 and 2013. The client risk profile was examined through Classification and Regression Tree (CART) analysis, one of the decision tree classification methods. At the end of the study, 5 different types of customers have been determined on the decision tree. The classification of these types of customers has been created with the rating of those posing a risk for the bank branch and the customers have been classified according to the risk ratings.

Keywords: client classification, loan suitability, risk rating, CART analysis

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Authors: Mohd Farooq Naqshbandi

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The four fractions of aqueous extract of Sesame Seeds (Sesamum indicum L.) were studied for invitro DNA fragmentation, cell migration, and cellular apoptosis on SW480 and HTC116 human colorectal cancer cell lines. The seeds of Sesamum indicum were extracted with six solvents, including Methanol, Ethanol, Aqueous, Chloroform, Acetonitrile, and Hexane. The aqueous extract (IC₅₀ value 154 µg/ml) was found to be the most active in terms of cytotoxicity with SW480 human colorectal cancer cell lines. Further fractionation of this aqueous extract on flash chromatography gave four fractions. These four fractions were studied for anticancer and DNA binding studies. Cell viability was assessed by colorimetric assay (MTT). IC₅₀ values for all these four fractions ranged from 137 to 548 µg/mL for the HTC116 cancer cell line and 141 to 402 µg/mL for the SW480 cancer cell line. The four fractions showed good anticancer and DNA binding properties. The DNA binding constants ranged from 10.4 ×10⁴ 5 to 28.7 ×10⁴, showing good interactions with DNA. The DNA binding interactions were due to intercalative and π-π electron forces. The results indicate that aqueous extract fractions of sesame showed inhibition of cell migration of SW480 and HTC116 human colorectal cancer cell lines and induced DNA fragmentation and apoptosis. This was demonstrated by calculating the low wound closure percentage in cells treated with these fractions as compared to the control (80%). Morphological features of nuclei of cells treated with fractions revealed chromatin compression, nuclear shrinkage, and apoptotic body formation, which indicate cell death by apoptosis. The flow cytometer of fraction-treated cells of SW480 and HTC116 human colorectal cancer cell lines revealed death due to apoptosis. The results of the study indicate that aqueous extract of sesame seeds may be used to treat colorectal cancer.

Keywords: Sesamum indicum, cell migration inhibition, apoptosis induction, anticancer activity, colorectal cancer

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Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

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Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: evolutionary computation, feature selection, classification, clustering

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Authors: Jacklynn Walters, Amanda A. Alblas, Linda M. Greyling

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Cervical carcinoma is the second most common cancer found in women. Diagnosis of skeletal metastases is uncommon in cervical cancer patients. The aim of this study was to determine the prevalence of skeletal metastases in in a Western Cape skeletal population. Skeletal samples (n=14) from the Kirsten Skeletal Collection at Stellenbosch University, diagnosed pre-mortem with cervical cancer, were examined. Macroscopic analysis was done using low magnification to examine each skeletal element for signs of disease. Skeletons were also x-rayed using the Lodox® Statscan® Imaging system and the scans evaluated by a musculoskeletal radiologist. Three (21%) of the skeletons showed metastases, with the os coxae and lower vertebral column affected in all three cases. Furthermore, metastases occurred in the scapulae and ribs in two of the cases and in one case the skull, mandible, and long bones were affected. Additionally, three skeletons without evidence of skeletal metastases presented with a periosteal reaction on the os coxae in response to the diseased adjacent soft tissue. Previous studies observed that skeletal metastases are more common than what is diagnosed pre-mortem with the vertebral spine most commonly affected. The findings of this study agree with previous reports and illustrate the effectiveness of the Lodox® scanner in diagnoses of metastases in skeletal material.

Keywords: cancer, cervix, radiology, skeletal metastases

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Authors: Vishwa Joshi

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The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques and many audio features contributing considerably to analyze and identify the relation of mood plus music. In this paper we consider the same idea forward and come up with making an effort to build a system for automatic recognition of mood underlying the audio song’s clips by mining their audio features and have evaluated several data classification algorithms in order to learn, train and test the model describing the moods of these audio songs and developed an open source framework. Before classification, Preprocessing and Feature Extraction phase is necessary for removing noise and gathering features respectively.

Keywords: music, mood, features, classification

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Authors: Abdelhadi Adam Salih Denei

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Silver nanoparticles (AgNPs) have been used in cancer therapy, and the area of nanomedicine has made unheard-of strides in recent years. A thorough summary of the development and assessment of AgNPs for their possible use in the fight against cancer is the goal of this review. Targeted delivery methods have been designed to optimise therapeutic efficacy by using AgNPs' distinct physicochemical features, such as their size, shape, and surface chemistry. Firstly, the study provides an overview of the several synthesis routes—both chemical and green—that are used to create AgNPs. Natural extracts and biomolecules are used in green synthesis techniques, which are becoming more and more popular since they are biocompatible and environmentally benign. It is next described how synthesis factors affect the physicochemical properties of AgNPs, emphasising how crucial it is to modify these parameters for particular therapeutic uses. An extensive analysis is conducted on the anticancer potential of AgNPs, emphasising their capacity to trigger apoptosis, impede angiogenesis, and alter cellular signalling pathways. The analysis also investigates the potential benefits of combining AgNPs with currently used cancer treatment techniques, including radiation and chemotherapy. AgNPs' safety profile for use in clinical settings is clarified by a comprehensive evaluation of their cytotoxicity and biocompatibility.

Keywords: silver nanoparticles, cancer, nanocarrier system, targeted delivery

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Authors: Shazia Bano

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Nanoconjugates that integrate photo-based therapeutics and diagnostics within a single platform promise great advances in revolutionizing cancer treatments. However, to achieve high therapeutic efficacy, designing functionally efficacious nanocarriers to tightly retain the drug, promoting selective drug localization and release, and the validation of the efficacy of these nanoconjugates is a great challenge. Here we have designed smart multiagent, liposome based targeted photoactivatable multiagent nanoconjugates, doped with a photoactivatable chromophore benzoporphyrin derivative (BPD) labelled with an active targeting ligand cetuximab to target the EGFR receptor (over expressed in various cancer cells) to deliver a combination of therapeutic agents. This study establishes a tunable nanoplatform for the delivery of the photoactivatable multiagent nanoconjugates for tumor-specific accumulation and targeted destruction of cancer cells in complex cancer model to enhance the therapeutic index of the administrated drugs.

Keywords: targeting, photodynamic therapy, photoactivatable, nanoconjugates

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Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

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In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent Transportation Systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning

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Authors: Patsorn Worawattananutai, Srisopa Ruangnoo, Arunporn Itharat

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Hibiscus sabdariffa (HS) leaves are vegetables which are extensively used as blood tonic and laxatives in Thai traditional medicine. They are popularly used as healthy sour soup for prevention of chronic diseases such as cancer. Therefore, the cytotoxic activity of different extracts of fresh and dried Hibiscus sabdariffa leaves were investigated via the sulforhodamine B (SRB) assay against three types of women’s cancer cell lines, namely the human cervical adenocarcinoma cell line (HeLa), the human ovarian adenocarcinoma cell line (SKOV-3), and the human breast adenocarcinoma cell line (MCF-7). Extraction methods were squeezing, boiling with water and maceration with 95% or 50% ethanol. The 95% ethanolic extracts of Hibiscus sabdariffa dry leaves (HSDE95) showed the highest cytotoxicity against all types of women’s cancer cell lines with the IC50 values in range 7.51±0.33 to 12.13±1.85 µg/ml. Its IC50 values against SKOV-3, HeLa and MCF-7 were 7.51±0.33, 9.44±1.41 and 12.13±1.85 µg/ml, respectively. In these results, this extract can be classified as “active” according to the NCI guideline which indicated that IC50 values of the active cytotoxic plant extracts have to be beneath 20 µg/ml. Thus, HSDE95 was concluded to be a potent cytotoxic drug for all women’s cancer cells. This extract should be further investigated to isolate active compounds against women’s cancer cells.

Keywords: breast adenocarcinoma, cervical adenocarcinoma, cytotoxic activity, Hibiscus sabdariffa, ovarian adenocarcinoma

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Authors: Rabah Iratni, Husain El Hasasna, Khawlah Athamneh, Halima Al Sameri, Nehla Benhalilou, Asma Al Rashedi

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Background: Cancer therapies have witnessed great advances in the recent past, however, cancer continues to be a leading cause of death, with colorectal cancer being the fourth cause of cancer-related deaths. Colorectal cancer affects both sexes equally with poor survival rate once it metastasizes. Phytochemicals, which are plant derived compounds, have been on a steady rise as anti-cancer drugs due to the accumulation of evidences that support their potential. Here, we investigated the anticancer effect of Rhus coriaria on colon cancer cells. Material and Method: Human colon cancer HT-29 cell line was used. Protein expression and protein phosphorylation were examined using Western blotting. Transcription activity was measure using Quantitative RT-PCR. Human tumoral clonogenic assay was used to assess cell survival. Senescence was assessed by the senescence-associated beta-galactosidase assay. Results: Rhus coriaria extract (RCE) was found to significantly inhibit the viability and colony growth of human HT-29 colon cancer cells. RCE induced senescence and cell cycle arrest at G1 phase. These changes were concomitant with upregulation of p21, p16, downregulation of cyclin D1, p27, c-myc and expression of Senescence-associated-β-Galactosidase activity. Moreover, RCE induced non-canonical beclin-1independent autophagy and subsequent apoptotic cell death through activation of activation caspase 8 and caspase 7. The blocking of autophagy by 3-methyladenine (3-MA) or chloroquine (CQ) reduced RCE-induced cell death. Further, RCE induced DNA damage, reduced mutant p53 protein level and downregulated phospho-AKT and phospho-mTOR, events that preceded autophagy. Mechanistically, we found that RCE inhibited the AKT and mTOR pathway, a regulator of autophagy, by promoting the proteasome-dependent degradation of both AKT and mTOR proteins. Conclusion: Our findings provide strong evidence that Rhus coriaria possesses strong anti-colon cancer activity through induction of senescence and autophagic cell death, making it a promising alternative or adjunct therapeutic candidate against colon cancer.

Keywords: autophagy, proteasome degradation, senescence, mTOR, apoptosis, Beclin-1

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Authors: Mai Ashraf Talaat

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Objectives: The aim of this review article is to assess the success of dental implants in breast cancer patients receiving bisphosphonate therapy and to evaluate the risk of developing bisphosphonate-related osteonecrosis of the jaw following dental implant surgery. Materials and Methods: A thorough search was conducted, with no time or language restriction, using: PubMed, PubMed Central, Web of Science, and ResearchGate electronic databases. Medical Subject Headings (MeSH) terms such as “bisphosphonate”, “dental implant”, “bisphosphonate-related osteonecrosis of the jaw (BRONJ)”, “osteonecrosis”, “breast cancer, MRONJ”, and their related entry terms were used. Eligibility criteria included studies and clinical trials that evaluated the impact of bisphosphonates on dental implants. Conclusion: Breast cancer patients undergoing bisphosphonate therapy may receive dental implants. However, the risk of developing BRONJ and implant failure is high. Risk factors such as the type of BP received, the route of administration, and the length of treatment prior to surgery should be considered. More randomized controlled trials with long-term follow-ups are needed to draw more evidence-based conclusions.

Keywords: dental implants, breast cancer, bisphosphonates, osteonecrosis, bisphosphonate-related osteonecrosis of the jaw

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Authors: C. Lanzerstorfer

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The off-gas from the basic oxygen furnace (BOF), where pig iron is converted into steel, is treated in the primary ventilation system. This system is in full operation only during oxygen-blowing when the BOF converter vessel is in a vertical position. When pig iron and scrap are charged into the BOF and when slag or steel are tapped, the vessel is tilted. The generated emissions during charging and tapping cannot be captured by the primary off-gas system. To capture these emissions, a secondary ventilation system is usually installed. The emissions are captured by a canopy hood installed just above the converter mouth in tilted position. The aim of this study was to investigate the dependence of Zn and other components on the particle size of BOF secondary ventilation dust. Because of the high temperature of the BOF process it can be expected that Zn will be enriched in the fine dust fractions. If Zn is enriched in the fine fractions, classification could be applied to split the dust into two size fractions with a different content of Zn. For this air classification experiments with dust from the secondary ventilation system of a BOF were performed. The results show that Zn and Pb are highly enriched in the finest dust fraction. For Cd, Cu and Sb the enrichment is less. In contrast, the non-volatile metals Al, Fe, Mn and Ti were depleted in the fine fractions. Thus, air classification could be considered for the treatment of dust from secondary BOF off-gas cleaning.

Keywords: air classification, converter dust, recycling, zinc

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Authors: Jin Boo Jeong

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In this study, we elucidated anti-cancer activity and potential molecular mechanism of DKC against human colorectal cancer cells. DKC-E70 suppressed the proliferation of human colorectal cancer cell lines such as HCT116, SW480, LoVo and HT-29. Although DKC-E70 decreased cyclin D1 expression in protein and mRNA level, decreased level of cyclin D1 protein by DKC-E70 occurred at the earlier time than that of cyclin D1 mRNA, which indicates that DKC-E70-mediated downregulation of cyclin D1 protein may be a consequence of the induction of degradation and transcriptional inhibition of cyclin D1. In cyclin D1 degradation, we found that cyclin D1 downregulation by DKC-E70 was attenuated in presence of MG132. In addition, DKC-E70 phosphorylated threonine-286 (T286) of cyclin D1 and T286A abolished cyclin D1 downregulation by DKC-E70. We also observed that DKC-E70-mediated T286 phosphorylation and subsequent cyclin D1 degradation was blocked in presence of the inhibitors of ERK1/2, p38 or GSK3β. In cyclin D1 transcriptional inhibition, DKC-E70 inhibited the expression of β-catenin and TCF4, and β–catenin/TCF-dependent luciferase activity. Our results suggest that DKC-E70 may downregulate cyclin D1 as one of the potential anti-cancer targets through cyclin D1 degradation by T286 phosphorylation dependent on ERK1/2, p38 or GSK3β, and cyclin D1 transcriptional inhibition through Wnt signaling. From these findings, DKC-E70 has potential to be a candidate for the development of chemoprevention or therapeutic agents for human colorectal cancer. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2016R1D1A3B03931713).

Keywords: anticancer, calyx of persimmon, cyclin D1, Diospyros kaki Thunb., human colorectal cancer

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Authors: Jiahe Liu, Hongyang Yu, Feng Qian, Miao Luo

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SMPL-X was a powerful parametric human body model that included male, neutral, and female models, with significant gender differences between these three models. During the process of 3D human body reconstruction, the correct selection of standard templates was crucial for obtaining accurate results. To address this issue, we developed an efficient gender classification algorithm to automatically select the appropriate template for 3D human body reconstruction. The key to this gender classification algorithm was the precise analysis of human body features. By using the SMPL-X model, the algorithm could detect and identify gender features of the human body, thereby determining which standard template should be used. The accuracy of this algorithm made the 3D reconstruction process more accurate and reliable, as it could adjust model parameters based on individual gender differences. SMPL-X and the related gender classification algorithm have brought important advancements to the field of 3D human body reconstruction. By accurately selecting standard templates, they have improved the accuracy of reconstruction and have broad potential in various application fields. These technologies continue to drive the development of the 3D reconstruction field, providing us with more realistic and accurate human body models.

Keywords: gender classification, joint detection, SMPL-X, 3D reconstruction

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Authors: Olivia Rachel Hwang, Yu-Hsuan Joni Shao

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Androgen Deprivation Therapy (ADT) has been a primary treatment for patients with advanced prostate cancer. However, it is associated with numerous adverse effects related to Metabolic Syndrome (MetS), including hypertension, diabetes, hyperlipidaemia, heart diseases and ischemic strokes. However, complications associated with ADT for prostate cancer in Taiwan is not well documented. The purpose of this study is to utilize the data from NHIRD (National Health Insurance Research Database) to examine the trajectory changes of MetS-related complications in men receiving ADT. The risks of developing complications after the treatment were analyzed with multivariate Cox regression model. Covariates including in the model were the complications before the diagnosis of prostate cancer, the age, and the year at cancer diagnosis. A total number of 17268 patients from 1997-2013 were included in this study. The exclusion criteria were patients with any other types of cancer or with the existing MetS-related complications. Changes in MetS-related complications were observed among two treatment groups: 1) ADT (n=9042), and 2) non-ADT (n=8226). The ADT group appeared to have an increased risk in hypertension (hazard ratio 1.08, 95% confidence interval 1.03-1.13, P = 0.001) and hyperlipidemia (hazard ratio 1.09, 95% confidence interval 1.01-1.17, P = 0.02) when compared with non-ADT group in the multivariate Cox regression analyses. In the risk of diabetes, heart diseases, and ischemic strokes, ADT group appeared to have an increased but not significant hazard ratio. In conclusion, ADT was associated with an increased risk in hypertension and hyperlipidemia in prostate cancer patients in Taiwan. The risk of hypertension and hyperlipidemia should be considered while deciding on ADT, especially those with the known history of hypertension and hyperlipidemia.

Keywords: androgen deprivation therapy, ADT, complications, metabolic syndrome, MetS, prostate cancer

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Authors: Dominika Pihikova, Stefan Belicky, Tomas Bertok, Roman Sokol, Petra Kubanikova, Jan Tkac

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Since aberrant glycosylation is frequently accompanied by both physiological and pathological processes in a human body (cancer, AIDS, inflammatory diseases, etc.), the analysis of tumor-associated glycan patterns have a great potential for the development of novel diagnostic approaches. Moreover, altered glycoforms may assist as a suitable tool for the specificity and sensitivity enhancement in early-stage prostate cancer diagnosis. In this paper we discuss the construction and optimization of ultrasensitive sandwich biosensor platform employing lectin as glycan-binding protein. We focus on the immunoassay development, reduction of non-specific interactions and final glycoprofiling of human serum samples including both prostate cancer (PCa) patients and healthy controls. The fabricated biosensor was measured by label-free electrochemical impedance spectroscopy (EIS) with further lectin microarray verification. Furthermore, we analyzed different biosensor interfaces with atomic force microscopy (AFM) in nanomechanical mapping mode showing a significant differences in the altitude. These preliminary results revealing an elevated content of α-2,3 linked sialic acid in PCa patients comparing with healthy controls. All these experiments are important step towards development of point-of-care devices and discovery of novel glyco-biomarkers applicable in cancer diagnosis.

Keywords: biosensor, glycan, lectin, prostate cancer

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Authors: C. Soh, S. Muktar, C. M. Malata, J. R. Benson

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Introduction Reasons for requesting CPM include prevention of recurrence, peace of mind and moving on after breast cancer. Some women seek CPM as a delayed procedure but factors influencing this are poorly understood. Methods A retrospective analysis examined patients undergoing CPM as either an immediate or delayed procedure with or without breast reconstruction (BR) between January 2009 and December 2019. A cross-sectional survey based on validated questionnaires (5 point Likert scale) explored patients’ decision-making process in terms of timing of CPM and any BR. Results A total of 123 patients with unilateral breast cancer underwent CPM with 39 (32.5%) delayed procedures with or without BR. The response rate amongst patients receiving questionnaires (n=33) was 22/33 (66%). Within this delayed CPM cohort were three reconstructive scenarios 1) unilateral immediate BR with CPM (n=12); 2) delayed CPM with concomitant bilateral BR (n=22); 3) delayed bilateral BR after delayed CPM (n=3). Two patients had delayed CPM without BR. The most common reason for delayed CPM was to complete all cancer treatments (including radiotherapy) before surgery on the unaffected breast (score 2.91). The second reason was unavailability of genetic test results at the time of therapeutic mastectomy (score 2.64) whilst the third most cited reason was a subsequent change in family cancer history. Conclusion Factors for delayed CPM are patient-driven with few women spontaneously changing their mind having initially decided against immediate CPM for reasons also including surgical duration. CPM should be offered as a potentially delayed option with informed discussion of risks and benefits.

Keywords: Breast Cancer, CPM, Prophylactic, Rationale

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Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

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Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization

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Authors: Qamar Iqbal

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Companies strive to improve their forecasting methods to predict the fluctuations in customer demand. These fluctuation and variation in demand affect the manufacturing operations and can limit a company’s ability to fulfill customer demand on time. Companies keep the inventory buffer and maintain the stocking levels to reduce the impact of demand variation. A mid-size company deals with thousands of stock keeping units (skus). It is neither easy and nor efficient to control and manage each sku. Inventory classification provides a tool to the management to increase their ability to support customer demand. The paper presents a framework that shows how inventory classification can play a role to increase supply chain responsiveness. A case study will be presented to further elaborate the method both for build-to-order and build-to-forecast manufacturing environments. Results will be compared that will show which manufacturing setting has advantage over another under different circumstances. The outcome of this study is very useful to the management because this will give them an insight on how inventory classification can be used to increase their ability to respond to changing customer needs.

Keywords: inventory classification, supply chain responsiveness, forecast, manufacturing environment

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Authors: Ying Yi Wu

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The study of finite groups is a central topic in algebraic structures, and one of the most fundamental questions in this field is the classification of finite groups up to isomorphism. In this paper, we investigate the cyclic property of groups of prime order, which is a crucial result in the classification of finite abelian groups. We prove the following statement: If p is a prime, then every group G of order p is cyclic. Our proof utilizes the properties of group actions and the class equation, which provide a powerful tool for studying the structure of finite groups. In particular, we first show that any non-identity element of G generates a cyclic subgroup of G. Then, we establish the existence of an element of order p, which implies that G is generated by a single element. Finally, we demonstrate that any two generators of G are conjugate, which shows that G is a cyclic group. Our result has significant implications in the classification of finite groups, as it implies that any group of prime order is isomorphic to the cyclic group of the same order. Moreover, it provides a useful tool for understanding the structure of more complicated finite groups, as any finite abelian group can be decomposed into a direct product of cyclic groups. Our proof technique can also be extended to other areas of group theory, such as the classification of finite p-groups, where p is a prime. Therefore, our work has implications beyond the specific result we prove and can contribute to further research in algebraic structures.

Keywords: group theory, finite groups, cyclic groups, prime order, classification.

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Authors: Marcelino Caetano Noronha, Vosco Pereira, Jose Soares Pinto, Ferdinando Da C. Saores

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One particularly popular social media platform is Youtube. It’s a video-sharing platform where users can submit videos, and other users can like, dislike or comment on the videos. In this study, we conduct a binary classification task on YouTube’s video comments and review from the users regarding the accession process of Timor Leste to become the eleventh member of the Association of South East Asian Nations (ASEAN). We scrape the data directly from the public YouTube video and apply several pre-processing and weighting techniques. Before conducting the classification, we categorized the data into two classes, namely positive and negative. In the classification part, we apply Support Vector Machine (SVM) algorithm. By comparing with Naïve Bayes Algorithm, the experiment showed SVM achieved 84.1% of Accuracy, 94.5% of Precision, and Recall 73.8% simultaneously.

Keywords: classification, YouTube, sentiment analysis, support sector machine

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Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

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In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss

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Authors: Molnar Catalina, Lexi Frankel, Amalia Ardeljan, Enoch Kim, Marissa Dallara, Omar Rashid

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Introduction: Clostridium difficile (C. diff) is a toxin-producing bacteria that can cause diarrhea and colitis. U.S. Center for Disease Control and Prevention revealed that C. difficile infection (CDI) has increased from 31 cases per 100,000 persons per year in 1996 to 61 per 100,000 in 2003. Approximately 500,000 cases per year occur in the United States. After exposure, the bacteria colonize the colon, where it adheres to the intestinal epithelium where it produces two toxins: TcdA and TcdB. TcdA affects the intestinal epithelium, causing fluid secretion, inflammation, and tissue necrosis, while TcdB acts as a cytotoxin purpose of this study was to evaluate the association between C diff infection and bronchial lung cancer development. Methods: Using ICD- 9 and ICD-10 codes, the data was provided by a Health Insurance Portability and Accountability Act (HIPAA) compliant national database to assess the patients infected with C diff as opposed to the non-infected patients. The Holy Cross Health, Fort Lauderdale, granted access to the database for the purpose of academic research. Patients were matched for age and Charlson Comorbidity Index (CCI). Standard statistical methods were used. Results: Bronchial lung cancer occurrence in the population not infected with C diff infection was 4741, as opposed to the population infected with C. diff, where 2039 cases of lung cancer were observed. The difference was statistically significant (p-value < 2.2x10^e-16), which reveals that C diff might be protective against bronchial lung cancer. The data was then matched by treatment to create to minimize the effect of treatment bias. Bronchial cancer incidence was 422 and 861 in infected vs. non-infected (p-value of < 2.2x10^e-16), which once more indicates that C diff infection could be beneficial in diminishing bronchial cancer development. Conclusion: This retrospective study conveys a statistical correlation between C diff infection and decreased incidence of lung bronchial cancer. Further studies are needed to comprehend the protective mechanisms of C. Diff infection on lung cancer.

Keywords: C. diff, lung cancer, protective, microbiology

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Authors: Nuhi Arslani, Stojan Potrc, Timotej Mikuljan

Abstract:

Background: In Department of Abdominal and General Surgery of University Medical Centre Maribor, we treated 578 patients for rectal cancer between 2004 and 2014. During and after treatment we especially concentrated on monitoring local and systemic complications. Methods: For analysis, we used data gathered from preoperative diagnostic tests, reports gathered during operation, reports from the pathohistologic review, and reports on complications after surgery and follow up. Results: In the case of 573 (out of 578) patients (99.1%) we performed resection. R0 was achieved in 551 patients (96,1%). R1 was achieved in 8 patients (1,4%). R2 was achieved in 14 patients (2,4%). Local complications were reported in 78 (13.5%) patients and systemic complications were reported in 68 (11.7%). We would like to point out the low number of local and systemic complications. Conclusions: With advances in surgical techniques, with a multimodal-multidisciplinary approach and with the use of total mesorectal excision we experienced a significant improvement in reducing the number of local and systemic complications in patients with rectal cancer. However, there still remains the question for truly optimal care for each patient with rectal cancer and his quality of life after surgical treatment.

Keywords: local complications, rectal cancer, resection, systemic complications

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Authors: M. Aghili, S. Tabarestani, C. Freytes, M. Shojaie, M. Cabrerizo, A. Barreto, N. Rishe, R. E. Curiel, D. Loewenstein, R. Duara, M. Adjouadi

Abstract:

A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on the classification of the four classes of AD, NC, EMCI, and LMCI. Using 10-fold cross validation technique, XGBoost is shown to outperform other state-of-the-art classification algorithms by 3% in terms of accuracy and F-score. Our model achieved an accuracy of 80.52%, a precision of 80.62% and recall of 80.51%, supporting the more natural and promising multiclass classification.

Keywords: eXtreme gradient boosting, missing data, Alzheimer disease, early mild cognitive impairment, late mild cognitive impair, multiclass classification, ADNI, support vector machine, random forest

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Authors: Kyung Min Kwom, Young Joo Lee

Abstract:

Purpose: Up to 90% of pancreatic cancer patient suffer from neuropathic pain. In palliative care setting, pain control in a pancreatic cancer patient is one of the major goals. Ketamine is a NMDA receptor antagonist effective in neuropathic pain. Also, there have been studies about opioid sparing effect of ketamine. This study was held in palliative care unit among pancreatic cancer patients to find out the factors related to ketamine use and the opioid sparing effect. Methods: Medical records of pancreatic cancer patients admitted to St. Mary’s hospital palliative care unit from 2013.1 to 2014.12 were reviewed. Patients were divided into two categories according to ketamine use. Also, opioid use before and after ketamine use was compared in ketamine group. Results: Compared to non ketamine use group, patients in ketamine group required a higher dose of opioid. Total opioid dose, daily opioid dose, number of daily rescue medication, daily average rescue dose were statistically significantly higher in ketamine group. Opioid requirement was increased after ketamine administration. Conclusion: In this study, ketamine group required more opioid. Ketamine is frequently considered in patients with severe pain, requiring high amount of opioid. Also, ketamine did not have an opioid sparing effect. Future studies about palliative use of ketamine in a larger number of patients are required.

Keywords: ketamine, opioid sparing, palliative care, pancreatic cancer

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Authors: Vasudha Devi, Arul Amuthan, K. Narayanan, Praveen KS, Venkata Rao J

Abstract:

Background: Siddha Medicine is one of the Indian traditional medical systems, in which the cancer disease is mentioned as 'putrunoi' which literally means the disease of growth like termite mound. There are number of formulations available for the treatment of cancer disease. Neeradi muthu vallathymezugu (NMV) and thamira kattu chendooram (TKC) are two drugs commonly prescribed by Siddha physicians. These drugs have been clinically reported to be safe and effective when given orally. Though these formulations are in practice for centuries, no efforts have been made to standardize them and explore their anti-cancer potential systematically. Objective: To compare the cytotoxic activity of NMV and TKC with doxorubicin using cancer cell lines. Materials and methods: For this study, ethanol extract of NMV was taken, whereas TKC was used as such. In vitro cytotoxic activity was evaluated by sulphorhodamine (SRB) assay against human hepatic cancer cells (HepG2), human breast cancer cells (MCF-7) and human cervical cancer cells [KeLa]. Doxorubicin was used as the standard. The SRB assay is based on the ability of cellular proteins to bind with sulphorhodamine-B. The number of live cells in drug treated cell lines directly affects the color formation in the assay, which is estimated calorimetrically by measuring the absorbance at 540 nm to calculate the cytotoxicity (inhibitory concentration - IC50 value) of the drug. Results: The IC50values of NMV, TKC and doxorubicin against HepG2 were 3.08 µg/ml, 20.21 µg/ml and 1.21µg/ml respectively. In MCF-7, it was 11.75 µg/ml, 17.67 µg/ml and 2.8µg/ml. In HeLa, the values were 24.76 µg/ml, 73.35 µg/ml and 1.12µg/ml. Conclusions: The study proves the possible anti-cancer potential of these two formulations. Compared to TKC, NMV showed good cytotoxic effect even at low dose. Human hepatic cancer cells responded well even at very low dose, when compared to other cancer cells. Though, cytotoxic potential of these compounds was found to be less compared to doxorubicin, the isolated lead compound may have the potential to be used as an anticancer drug clinically.

Keywords: Neeradi muthu vallathymezugu (Hydnocarpus laurifolia), thamira kattu chendooram, cytotoxicity, in-vitro, Siddha Medicine

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Authors: Philippa Saunders, Claire Fletcher

Abstract:

INTRODUCTION: Prostate cancer is the most prevalent malignancy affecting Western males. It is initially an androgen-dependent disease: androgens bind to the androgen receptor and drive the expression of genes that promote proliferation and evasion of apoptosis. Despite reduced androgen dependence in advanced prostate cancer, androgen receptor signaling remains a key driver of growth. Androgen deprivation therapy (ADT) is, therefore, a first-line treatment approach and works well initially, but resistance inevitably develops. Abiraterone and Enzalutamide are drugs widely used in ADT and are androgen synthesis and androgen receptor signaling inhibitors, respectively. The shortage of other treatment options means acquired resistance to these drugs is a major clinical problem. MicroRNAs (miRs) are important mediators of post-transcriptional gene regulation and show altered expression in cancer. Several have been linked to the development of resistance to ADT. Manipulation of such miRs may be a pathway to breakthrough treatments for advanced prostate cancer. This study aimed to validate ADT resistance-implicated miRs and their clinically relevant targets. MATERIAL AND METHOD: Small RNA-sequencing of Abiraterone- and Enzalutamide-resistant C42 prostate cancer cells identified subsets of miRs dysregulated as compared to parental cells. Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) was used to validate altered expression of candidate ADT resistance-implicated miRs 195-5p, 497-5p and 29a-5p in ADT-resistant and -responsive prostate cancer cell lines, patient-derived xenografts (PDXs) and primary prostate cancer explants. RESULTS AND DISCUSSION: This study suggests a possible role for miR-497-5p in the development of ADT resistance in prostate cancer. MiR-497-5p expression was increased in ADT-resistant versus ADT-responsive prostate cancer cells. Importantly, miR-497-5p expression was also increased in Enzalutamide-treated, castrated (ADT-mimicking) PDXs versus intact PDXs. MiR-195-5p was also elevated in ADT-resistant versus -responsive prostate cancer cells, while there was a drop in miR-29a-5p expression. Candidate clinically relevant targets of miR-497-5p in prostate cancer were identified by mining AGO-PAR-CLIP-seq data sets and may include AVL9 and FZD6. CONCLUSION: In summary, this study identified microRNAs that are implicated in prostate cancer resistance to androgen deprivation therapy and could represent novel therapeutic targets for advanced disease.

Keywords: microRNA, androgen deprivation therapy, Enzalutamide, abiraterone, patient-derived xenograft

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