Search results for: cancer prediction

Authors: Christopher G. Harris, Guy D. Eslick

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Purpose: Lobular carcinoma in situ (LCIS) is a known risk factor for breast cancer of unclear significance when detected in association with invasive carcinoma. This meta-analysis aims to determine the impact of LCIS on local recurrence risk for individuals with breast cancer treated with breast conservation therapy to help guide appropriate treatment strategies. Methods: We identified relevant studies from five electronic databases. Studies were deemed suitable for inclusion where they compared patients with invasive breast cancer and concurrent LCIS to those with breast cancer alone, all patients underwent breast conservation therapy (lumpectomy with adjuvant radiation therapy), and local recurrence was evaluated. Recurrence data were pooled by use of a random effects model. Results: From 1488 citations screened by our search, 8 studies were deemed suitable for inclusion. These studies comprised of 908 cases and 10638 controls. Median follow-up time was 90 months. There was a significantly increased overall risk of local breast cancer recurrence for individuals with LCIS in association with breast cancer following breast conservation therapy [pOR 1.87; 95% CI 1.14-3.04; p = 0.012]. The risk of local recurrence was non-significantly increased at 5 [pOR 1.09; 95% CI 0.48-2.48; p = 0.828] and 10 years [pOR 1.90; 95% CI 0.89-4.06; p = 0.096]. Conclusions: Individuals with LCIS in association with invasive breast cancer have an increased risk of local recurrence following breast conservation therapy. This supports consideration of aggressive local control of LCIS by way of completion mastectomy or re-excision for certain high-risk patients.

Keywords: breast cancer, breast conservation therapy, lobular carcinoma in situ, lobular neoplasia, local recurrence, meta-analysis

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Authors: Suriya

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Rapid socio-economic development and urbanization have led to an increasingly serious air pollution problem in Ulaanbaatar (UB), the capital of Mongolia. PM₂.₅ pollution has become the most pressing aspect of UB air pollution. Therefore, monitoring and predicting PM₂.₅ concentration in UB is of great significance for the health of the local people and environmental management. As of yet, very few studies have used models to predict PM₂.₅ concentrations in UB. Using data from 0:00 on June 1, 2018, to 23:00 on April 30, 2020, we proposed two deep learning models based on Bayesian-optimized LSTM (Bayes-LSTM) and CNN-LSTM. We utilized hourly observed data, including Himawari8 (H8) aerosol optical depth (AOD), meteorology, and PM₂.₅ concentration, as input for the prediction of PM₂.₅ concentrations. The correlation strengths between meteorology, AOD, and PM₂.₅ were analyzed using the gray correlation analysis method; the comparison of the performance improvement of the model by using the AOD input value was tested, and the performance of these models was evaluated using mean absolute error (MAE) and root mean square error (RMSE). The prediction accuracies of Bayes-LSTM and CNN-LSTM deep learning models were both improved when AOD was included as an input parameter. Improvement of the prediction accuracy of the CNN-LSTM model was particularly enhanced in the non-heating season; in the heating season, the prediction accuracy of the Bayes-LSTM model slightly improved, while the prediction accuracy of the CNN-LSTM model slightly decreased. We propose two novel deep learning models for PM₂.₅ concentration prediction in UB, Bayes-LSTM, and CNN-LSTM deep learning models. Pioneering the use of AOD data from H8 and demonstrating the inclusion of AOD input data improves the performance of our two proposed deep learning models.

Keywords: deep learning, AOD, PM2.5, prediction, Ulaanbaatar

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

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Background: The The purpose of this study was to evaluate the effect of six-week aerobic training and taxol consumption on interleukin 8 and Plasminogen Activator Inhibitor-1 (PAI-1) in mice with cervical cancer. Material and method: In this experimental study, 40 female C57 mice, eight weeks old, were randomly divided into 4 groups: cancer, cancer-taxol complement, cancer-training and cancer-training - taxol complement with 10 mice in each group. The implantation of cancerous tumors was performed under the skin of the upper pelvis. The training group completed the endurance training protocol, which included 3 sessions per week, 50 minutes per session, at a speed of 14-18 m/s for six weeks. A dose of 60 mg/ kg/day, a pure extract of Taxol was injected peritoneal Data were analyzed by t-test, One-way ANOVA and post hoc Bonferron's at the significant level P<0. 05. Results: The results showed that there was a significant difference between mean values of interleukin-8 (P < 0.05, F = 12.25) and the plasminogen activator inhibitor-1 (P < 0.05, P=0.10737) in four groups. A significance level of less than 0.05 in Tukey test for both variables also showed a significant difference between the "control" group and the complementary "exercise" group. Namely, six weeks of aerobic training, along with taxol, have a significant effect on the level of plasminogen activator inhibitor-1 and interleukin-8 mice with cervical cancer. Conclusion: Considering the effect of training on these variables, this type of exercise can be used as a complementary therapeutic approach along with other therapies for cervical cancer.

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

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Authors: Xiaoping Su, Gabriel G. Malouf

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Introduction: Breast cancer is a heterogeneous disease that can be classified in 4 subgroups using transcriptional profiling. The role of lncRNA expression in human breast cancer biology, prognosis, and molecular classification remains unknown. Methods and results: Using an integrative comprehensive analysis of lncRNA, mRNA and DNA methylation in 900 breast cancer patients from The Cancer Genome Atlas (TCGA) project, we unraveled the molecular portraits of 1,700 expressed lncRNA. Some of those lncRNAs (i.e, HOTAIR) are previously reported and others are novel (i.e, HOTAIRM1, MAPT-AS1). The lncRNA classification correlated well with the PAM50 classification for basal-like, Her-2 enriched and luminal B subgroups, in contrast to the luminal A subgroup which behaved differently. Importantly, estrogen receptor (ESR1) expression was associated with distinct lncRNA networks in lncRNA clusters III and IV. Gene set enrichment analysis for cis- and trans-acting lncRNA showed enrichment for breast cancer signatures driven by breast cancer master regulators. Almost two third of those lncRNA were marked by enhancer chromatin modifications (i.e., H3K27ac), suggesting that lncRNA expression may result in increased activity of neighboring genes. Differential analysis of gene expression profiling data showed that lncRNA HOTAIRM1 was significantly down-regulated in basal-like subtype, and DNA methylation profiling data showed that lncRNA HOTAIRM1 was highly methylated in basal-like subtype. Thus, our integrative analysis of gene expression and DNA methylation strongly suggested that lncRNA HOTAIRM1 should be a tumor suppressor in basal-like subtype. Conclusion and significance: Our study depicts the first lncRNA molecular portrait of breast cancer and shows that lncRNA HOTAIRM1 might be a novel tumor suppressor.

Keywords: lncRNA profiling, breast cancer, HOTAIRM1, tumor suppressor

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Authors: A. Majidian

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The life prediction of thermal power plant components is necessary to prevent the unexpected outages, optimize maintenance tasks in periodic overhauls and plan inspection tasks with their schedules. One of the main critical components in a power plant is condenser because its failure can affect many other components which are positioned in downstream of condenser. This paper deals with factors affecting life of condenser. Failure rates dependency vs. these factors has been investigated using Artificial Neural Network (ANN) and fuzzy logic algorithms. These algorithms have shown their capabilities as dynamic tools to evaluate life prediction of power plant equipments.

Keywords: life prediction, condenser tube, neural network, fuzzy logic

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Authors: Neda Menbari, Ramin Mehdiabadi

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Background: breast cancer remains a critical global health issue, constituting a leading cause of cancer-related mortality in women. MicroRNAs (miRs) are natural RNA molecules that play an important role in cellular processes and regulate post-transcriptional gene expression. MiR-216b-5p is a miR that acts as a tumor suppressor. The expression levels of FoxM1 and miR-216b-5p in malignant and control cells have been evaluated by quantitative polymerase chain reaction (qPCR) technique and flow cytometry. Results: the results of this study revealed a significant downregulation of miR-216b-5p in cancerous cells compared to the control MCF-10A cells (P=0.0004). Interestingly, the expression of miR-216b-5p exhibited an inverse relationship with key clinical indicators such as tumor size, grade, and lymph node invasion. Conclusion: The study's findings showed the prognostic value of miR-216b-5p levels in breast cancer, and its reduced expression correlates with unfavorable tumor characteristics. This research recommends performing more studies on the role of FoxM1 and miR-216b-5p in breast cancer pathology which potentially paving the way for targeted therapeutic interventions.

Keywords: breast cancer, gene expression, FOXM1, microRNA

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Authors: Omer Ibrahim Abdallh Omer

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Cancer patients often face complex medication regimens, leading to challenges in treatment adherence and clinical outcomes. Pharmacist-led medication therapy management (MTM) has emerged as a potential solution to optimize medication use and improve patient outcomes in oncology settings. In this prospective intervention study, we aimed to evaluate the impact of pharmacist-led MTM on treatment adherence and clinical outcomes among cancer patients. Participants were randomized to receive either pharmacist-led MTM or standard care, with assessments conducted at baseline and follow-up visits. Pharmacist interventions included medication reconciliation, adherence counseling, and personalized care plans. Our findings reveal that pharmacist-led MTM significantly improved medication adherence rates and clinical outcomes compared to standard care. Patients receiving pharmacist interventions reported higher satisfaction levels and perceived value in pharmacist involvement in their cancer care. These results underscore the critical role of pharmacists in optimizing medication therapy and enhancing patient-centered care in oncology settings. Integration of pharmacist-led MTM into routine cancer care pathways holds promise for improving treatment outcomes and quality of life for cancer patients.

Keywords: cancer, medications adherence, medication therapy management, pharmacist

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Authors: Shaik Asha Begum, S. Joshna Rani, Shaik Abdul Rahaman

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INTRODUCTION: Breast cancer is a disease that creates in breast cells. "KAP" study estimates the Knowledge, Attitude, and Practices of a local area. More than 1.5 million ladies (25% of all ladies with malignancy) are determined to have bosom disease consistently all through the world. Understanding the degrees of Knowledge, Attitude and Practice will empower a more effective cycle of mindfulness creation as it will permit the program to be custom-made all the more properly to the necessities of the local area. OBJECTIVES: The objective of this study is to assess the knowledge on signs and symptoms, risk factors, provide awareness on the practicing of the early detection techniques of breast cancer and provide knowledge on the overall breast cancer including preventive techniques. METHODOLOGY: This is an expressive cross-sectional investigation. This investigation of KAP was done in the Nirmala Educational Institutions from January to April 2021. A total of 300 participants are included from women students in pharmacy graduates & lecturers, and also from graduates other than the pharmacy. The examiners are taken from the BCAM (Breast Cancer Awareness Measure), tool compartment (Version 2). RESULT: According to the findings of the study, the majority of the participants were not well informed about breast cancer. A lump in the breast was the most commonly mentioned sign of breast cancer, followed by pain in the breast or nipple. The percentage of knowledge related to the breast cancer risk factors was also very less. The correct answers for breast cancer risk factors were radiation exposure (58.20 percent), a positive family history (47.6 percent), obesity (46.9 percent), a lack of physical activity (43.6 percent), and smoking (43.2 percent). Breast cancer screening, on the other hand, was uncommon (only 30 and 11.3 percent practiced clinical breast examination and mammography respectively). CONCLUSION: In this study, the knowledge on the signs and symptoms, risk factors of breast cancer - pharmacy graduates have more knowledge than the non-pharmacy graduates but in the preventive techniques and early detective tools of breast cancer -had poor knowledge in the pharmacy and non-pharmacy graduate. After the awareness program, pharmacy and non-pharmacy graduates got supportive knowledge on the preventive techniques and also practiced the early detective techniques of breast cancer.

Keywords: breast cancer, mammography, KAP study, early detection

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Authors: Rizwan Arshad, Alessio Panza, Nimra Inayat, Syeda Mariam Batool Kazmi, Shawana Azmat

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The rapidly expanding use of immunotherapy for a wide range of cancers from late to early stages has, predictably, been accompanied by evidence of inequities in access to these highly effective but costly treatments. In this survey-based case study, we aimed to develop a One-window services model (OWSM) based on Anderson’s behavioral model to enhance competence in accessing cancer medications, particularly immunotherapies, through the analysis of 20 patient surveys conducted in the Armed forces bone marrow transplant center of the district, Rawalpindi from November to December 2022. The purposive sampling technique was used. Cronbach’s alpha coefficient was found to be 0.71. It was analyzed using SPSS version 26 with descriptive analysis, and results showed that the majority of the cancer patients were non-competent to access their prescribed cancer immunotherapy because of individual-level, socioeconomic, and organizational barriers.

Keywords: cancer immunotherapy, one-window services model, accessibility, competence

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Authors: Carlos Huertas, Reyes Juarez-Ramirez

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Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: biomarker discovery, cancer, feature selection, mass spectrometry

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Authors: Tarek Aboueldahab, Amin Mohamed Nassar

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Wind energy is a fluctuating energy source unlike conventional power plants, thus, it is necessary to accurately predict short term wind speed to integrate wind energy in the electricity supply structure. To do so, we present a hybrid artificial intelligence model of short term wind speed prediction based on passive aggregation of the particle swarm optimization and neural networks. As a result, improvement of the prediction accuracy is obviously obtained compared to the standard artificial intelligence method.

Keywords: artificial intelligence, neural networks, particle swarm optimization, passive aggregation, wind speed prediction

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Authors: Azar Heidarizadi, Mahdieh Salimi, Hossein Mozdarani

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Introduction: As a complex disease, breast cancer results from several genetic and epigenetic changes. Lactoferrin, a member of the transferrin family, is reported to have a number of biological functions, including DNA synthesis, immune responses, iron transport, etc., any of which could play a role in tumor progression. The aim of this study was to investigate the bioinformatics data and experimental assay to find the pattern of promoter methylation and gene expression of LTF in breast cancer in order to study its potential role in cancer management. Material and Methods: In order to evaluate the methylation status of the LTF promoter, we studied the MS-PCR and Real-Time PCR on samples from patients with breast cancer and normal cases. 67 patient samples were conducted for this study, including tumoral, plasma, and normal tissue adjacent samples, as well as 30 plasma from normal cases and 10 tissue breast reduction cases. Subsequently, bioinformatics analyses such as cBioPortal databases, string, and genomatix were conducted to disclose the prognostic value of LTF in breast cancer progression. Results: The analysis of LTF expression showed an inverse relationship between the expression level of LTF and the stages of tissues of breast cancer patients (p<0.01). In fact, stages 1 and 2 had a high expression in LTF, while, in stages 3 and 4, a significant reduction was observable (p < 0.0001). LTF expression frequently alters with a decrease in the expression in ER⁺, PR⁺, and HER2⁺ patients (P < 0.01) and an increase in the expression in the TNBC, LN¯, ER¯, and PR- patients (P < 0.001). Also, LTF expression is significantly associated with metastasis and lymph node involvement factors (P < 0.0001). The sensitivity and specificity of LTF were detected, respectively. A negative correlation was detected between the results of level expression and methylation of the LTF promoter. Conclusions: The altered expression of LTF observed in breast cancer patients could be considered as a promotion in cell proliferation and metastasis even in the early stages of cancer.

Keywords: LTF, expression, methylation, breast cancer

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Authors: Abigail Tan, Heng Liang Tan, Vanessa Ding, James Hui, Eng Hin Lee, Andre Choo

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Introduction: Comparative oncology investigates the similarities in spontaneous carcinogenesis between humans and animals, in order to identify treatments that can benefit these patients. Companion animals (CA), like canines and felines, are of special interest when it comes to studying human cancers due to their exposure to the same environmental factors and develop tumours with similar features. The purpose of this study is to explore the cross-reactivity of monoclonal antibodies (mAbs) across cancers in humans and CA. Material and Methods: A panel of CA mAbs generated in the lab was screened on multiple human cancer cell lines through flow cytometry to identify for positive binders. Shortlisted candidates were then characterised by biochemical and functional assays e.g., antibody-drug conjugate (ADC) and western blot assays, including glycan studies. Results: Candidate mAb KP52 was generated from whole-cell immunisation using feline mammary carcinoma. KP52 showed strong positive binding to human cancer cells, such as breast cancer and ovarian cancer. Furthermore, KP52 demonstrated strong killing ( > 50%) as an ADC with Saporin as the payload. Western blot results revealed the molecular weight of the antigen targets to be approximately 45kD and 50kD under reduced conditions. Glycan studies suggest that the epitope is glycan in nature, specifically an O-linked glycan. Conclusion: Candidate mAb KP52 has a therapeutic potential as an ADC against feline mammary cancer, human ovarian cancer, human mammary cancer, human pancreatic cancer, and human gastric cancer.

Keywords: ADC, comparative oncology, mAb, therapeutic

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Authors: Dina Fatmawati, Sofia Mubarika, Mae Sri Wahyuningsih

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Chemotherapy for breast cancer is largely ineffective, but innovative combinations of chemotherapeutic agents and natural compounds represent a promising strategy. In our previous study, the combination of Doxorubicin (Dox) and ethanolic extract of Dioscorea esculenta tuber ((EED) was found to have a synergistic effect on T47D human breast cancer cell line. In this study, we investigated the apoptotic effect of the combination on T47D human breast cancer cells and normal fibroblasts cell line and its effects on the expression of Caspase-3 and cleaved poly (ADP-Ribose) Polymerase-1 (cPARP-1) protein. T47D cell lines and fibroblasts cells were treated with the combination of Dox and EED. Apoptotic effect of the combination was determined using flow cytrometry assay. Protein expressions were determined by immunocytochemistry staining. The percentage of apoptotic cells were significantly higher in T47D cell lines (75%) than that of in fibroblast cells (23%). The expression of Caspase 3 (84.53%) and cPARP-1 (83.36%) were significantly higher in the cancer cell lines than those of normal cells. These results indicate that the combination of doxorubicin and Dioscorea esculenta is a promising candidate for the treatment of breast cancer cells.

Keywords: Dioscorea esculenta, Doxorubicin, apoptosis, immunocytochemistry, cancer cells

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Authors: Thinh Ngo, Paul Rad, Brian Kelley

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Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: classification, CNN, deep learning, prediction, SNR

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Authors: Srisopa Ruangnoo, Arunporn Itharat

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The ethanolic and aqueous extracts of Parkia javanica Merr. germinating seeds and Parkia speciosa Hassk. seeds were evaluated for cytotoxic activity against three different types of human cancer cell lines including colon cancer (LS174T), breast cancer (MCF-7) and prostate cancer (PC3) using sulforhodamine B (SRB) assay. The fresh plant parts were divided into 2 parts. The first part was extracted by maceration with 95% ethanol for 3 days and then filtered, and the filtrates were evaporated by rotary evaporator. The other part was squeezed and filtered. Then the filtrates were dried by freeze dryer. The screening found that the aqueous extract of P. javanica Merr. germinating seeds exhibited more than 70% inhibition (at concentration 50 µg/ml) against all types of human cancer cells. The aqueous extract of P. javanica Merr. germinating seeds showed the highest cytotoxic activity against MCF-7 with the IC50 value as 5.63 µg/ml. The aqueous extract of P. javanica Merr. germinating seeds also showed high cytotoxic activity against PC3 and LS174T with the IC50 values as 10.79 and 11.40 µg/ml, respectively. In conclusion, P. javanica Merr. germinating seed is a natural source of anticancer activity and further research to isolate active compounds from this plant should be undertaken.

Keywords: cytotoxic activity, Parkia javanica Merr., Parkia speciosa Hassk., human cancer cell lines

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Authors: Pengwei Qiao, Sucai Yang, Wenxia Wei

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Soil pollution has become an important issue in China. Accurate spatial distribution prediction of pollutants with interpolation methods is the basis for soil remediation in the site. However, a relatively strong variability of pollutants would decrease the prediction accuracy. Theoretically, partition interpolation can result in accurate prediction results. In order to verify the applicability of partition interpolation for a site, benzo (b) fluoranthene (BbF) in four soil layers was adopted as the research object in this paper. IDW (inverse distance weighting)-, RBF (radial basis function)-and OK (ordinary kriging)-based partition interpolation accuracies were evaluated, and their influential factors were analyzed; then, the uncertainty and applicability of partition interpolation were determined. Three conclusions were drawn. (1) The prediction error of partitioned interpolation decreased by 70% compared to unpartitioned interpolation. (2) Partition interpolation reduced the impact of high CV (coefficient of variation) and high concentration value on the prediction accuracy. (3) The prediction accuracy of IDW-based partition interpolation was higher than that of RBF- and OK-based partition interpolation, and it was suitable for the identification of highly polluted areas at a contaminated site. These results provide a useful method to obtain relatively accurate spatial distribution information of pollutants and to identify highly polluted areas, which is important for soil pollution remediation in the site.

Keywords: accuracy, applicability, partition interpolation, site, soil pollution, uncertainty

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Authors: Hui-Hsin Huang, Sheng-Tung Huang, Chi-Ming Lee, Chiao-Han Yen, Chun-Mao Lin

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At initiation stage, there are no symptoms at initiation stage; however, at late stage, patients suffer symptoms as soon as ovarian cancer metastasis. Moreover, ovarian cancer cells are resistant to some anti-ovarian cancer drugs in clinical. Thus, it is very important to find an effective treatment for resistant ovarian cancer. Anthraquinone derivatives are able to induce DNA damage and lead to cell apoptosis, so several derivatives have been used for clinical application. Therefore, to explore more effective anti-ovarian cancer drugs, this study investigates the mechanism of three new anthraquinone compounds bearing different functional groups to camptothecin-resistance ovarian cell line A2780R2000. Cell viability was determined by MTT assay after treating A2780R2000 with the three new anthraquinone compounds. The results indicated that IC50 values are 33.44μM (Compound I), 25.77μM (Compound II) and 24.59μM (Compound III). Next, through cell cycle analysis, the results demonstrated that three new anthraquinone compounds not only induced A2780R2000 cell cycle arrest at early stage but also apoptosis at late stage. Besides, through apoptosis assay, the results indicated new anthraquinone compound induced apoptosis at late stage. Furthermore, the results of western blot show that the three new anthraquinone compounds lead to A2780R2000 apoptosis through intrinsic pathway. Theses results suggested that three new anthraquinone compounds may be potential new drugs for clinical cancer treatment in the future.

Keywords: anthraquinone, camptothecin, resistance, ovarian cancer

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Authors: Lubomir Vecera, Tomas Gabrhelik, Benjamin Tolmaci, Josef Srovnal, Emil Berta, Petr Prasil, Petr Stourac

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Cancer is the second leading cause of death worldwide and colon cancer is the second most common type of cancer. Currently, there are only a few studies evaluating the effect of postoperative analgesia on the prognosis of patients undergoing radical colon cancer surgery. Postoperative analgesia in patients undergoing colon cancer surgery is usually managed in two ways, either with strong opioids (morphine, piritramide) or epidural analgesia. In our prospective study, we evaluated the effect of postoperative analgesia on the presence of circulating tumor cells or minimal residual disease after colon cancer surgery. A total of 60 patients who underwent radical colon cancer surgery were enrolled in this prospective, randomized, two-center study. Patients were randomized into three groups, namely piritramide, morphine and postoperative epidural analgesia. We evaluated the presence of carcinoembryonic antigen (CEA) and cytokeratin 20 (CK-20) mRNA positive circulating tumor cells in peripheral blood before surgery, immediately after surgery, on postoperative day two and one month after surgery. The presence of circulating tumor cells was assessed by quantitative real-time reverse transcriptase-polymerase chain reaction (qRT-PCR). In the priritramide postoperative analgesia group, the presence of CEA mRNA positive cells was significantly lower on a postoperative day two compared to the other groups (p=0.04). The value of CK-20 mRNA positive cells was the same in all groups on all days. In all groups, both types of circulating tumor cells returned to normal levels one month after surgery. Demographic and baseline clinical characteristics were similar in all groups. Compared with morphine and epidural analgesia, piritramide significantly reduces the amount of CEA mRNA positive circulating tumor cells after radical colon cancer surgery.

Keywords: cancer progression, colon cancer, minimal residual disease, perioperative analgesia.

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Authors: Wenxing Chen, Guangying Chen, Yin Lu, Shile Huang

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Cryptotanshinone (CPT), a fat-soluble tanshinone from Salvia miltiorrhiza Bunge, has been demonstrated to inhibit mTOR pathway, resulting in inhibition of cancer cell proliferation. However, the molecular mechanism how CPT acts on mTOR is unknown. Here, cancer cells expressing rapamycin-resistant mutant mTOR are also sensitive to CPT, while phosphorylation of AMPK and TSC2 was activated, suggesting that CPT inhibition of mTOR maybe due to activating upstream of mTOR, AMPK, but not directly binding to and inhibiting mTOR. Further results indicated that Compound C, inhibitor of AMPK, could partially reversed CPT inhibition effect on cancer cells, and dominant-negative AMPK in cancer cells conferred resistance to CPT inhibition of 4EBP1 and phosphorylation of S6K1, as well as sh-AMPK. Furthermore, compared with MEF cells with AMPK positive, MEF cells with AMPK knock out are less sensitive to CPT by the findings that 4E-BP1 and phosphorylation of S6K1 express comparatively much. Furthermore, downexpression of TSC2 slightly recovered expression of 4EBP1 and phosphorylation of S6K1, while co-immunoprecipitation of TSC2 did not affect expression of TSC1 by CPT. Collectively, the above-mentioned results suggest that CPT inhibited mTOR pathway mostly was due to activation of AMPK-TSC2 pathway rather than specific inhibition of mTOR and then induction of subsequent lethal cellular effect.

Keywords: cryptotanshinone, AMPK, TSC2, mTOR, cancer cells

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Authors: Engin Eyceyurt, Josko Zec

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The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: drive test, LTE, machine learning, uplink throughput prediction

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Authors: Emad A. Shalaby

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Cancer is a disease that causes abnormal cell proliferation and invades nearby tissues. Lung cancer is the second most frequent cancer worldwide. Natural anti-cancer drugs have been developed with low side effects and toxicity. Citrus peels and extracts have been demonstrated to have significant pharmacological and physiological effects as a result of the high concentration of phenolic compounds found in citrus fruits, particularly peels. Tangerine peels can serve as an effective source of bioactive substances such as phenolics, flavonoids, and catechins, which have antioxidant, antibacterial, anticancer, and anti-inflammatory properties. Consequently, this work aims to determine the anticancer activity of ethanol extract of Tangerine peels against the A549 cell line and identify the phenolic compound profile (19 compounds) by using HPLC. Anticancer and antioxidant potentials of the extract were evaluated by MTT assay and TLC- TLC-bioautography sprayed with DPPH reagent, respectively. The obtained results revealed that tangerine peel extract showed significant activity against the A549 cell line with IC50 of 97.66 μg/mL. HPLC analysis proved that the highest concentration is naringenin 464.05 mg/g. More studies indicate that naringenin has significant anticancer potential on A549 cancer cells. The results showed that naringenin binds t0 EGFR protein in A549 with high binding affinity and thus may reduce lung cancer cell migration and enhance the apoptosis of cancer cells. From the obtained results it could be concluded that tangerine peel extract is an effective anti-cancer agent that may potentially serve as a natural therapeutic option for lung cancer treatment.

Keywords: tangerine peel, A549 cell line, anticancer, naringenin, HPLC analysis, naringenin, TLC bioautography

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Authors: Pingshan Chen, Zhiliang Dong

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In order to estimate the post-construction settlement more objectively, the power-polynomial model is proposed, which can reflect the trend of settlement development based on the observed settlement data. It was demonstrated by an actual case history of an embankment, and during the prediction. Compared with the other three prediction models, the power-polynomial model can estimate the post-construction settlement more accurately with more simple calculation.

Keywords: prediction, model, post-construction settlement, soft ground

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Authors: Cecília M. Antão, Paulo Jorge Nogueira

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Breast cancer (BC) is the first cause of cancer mortality among Portuguese women. This retrospective observational study aimed at identifying comorbidities associated with BC female patients admitted to Portuguese public hospitals (2010-2018), investigating the effect of comorbidities on BC mortality rate, and building a predictive model using logistic regression. Results showed that the BC mortality in Portugal decreased in this period and reached 4.37% in 2018. Adjusted odds ratio indicated that secondary malignant neoplasms of liver, of bone and bone marrow, congestive heart failure, and diabetes were associated with an increased chance of dying from breast cancer. Although the Lisbon district (the most populated area) accounted for the largest percentage of BC patients, the logistic regression model showed that, besides patient’s age, being resident in Bragança, Castelo Branco, or Porto districts was directly associated with an increase of the mortality rate.

Keywords: breast cancer, comorbidities, logistic regression, adjusted odds ratio

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

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Gastric cancer (GC) has high morbidity and fatality rate in various countries and is still one of the most frequent and deadly diseases. Novel mitogenic and motogenic Gastrokine1 (GKN1) and Gastrokine 2 (GKN2) genes that are highly expressed in the normal stomach epithelium and plays an important role in maintaining the integrity and homeostasis of stomach mucosal epithelial cells. Significant loss of copy number and mRNA transcript of GKN1 and GKN2 gene expression were frequently observed in all types of gastric cancer. In this study, 47 paired samples that were grouped according to the types of gastric cancer and the clinical characteristics of the patients, including gender and average of age were investigated with gene expression analysis and mutation screening by monetering RT-PCR, SSCP and nucleotide sequencing techniques. Both GKN1 and GKN2 genes were observed significantly reduced found by (Wilcoxon signed rank test; p<0.05). As a result of gene screening, no mutation (no different genotype) was detected. It is considered that gene mutations are not the cause of inactivation of gastrokines. In conclusion, the mRNA expression level of GKN1 and GKN2 genes statistically was decreased regardless the gender, age or cancer type of patients. Reduced of gastrokine genes seems to occur at the initial steps of cancer development. In order to understand the investigation between gastric cancer and diagnostic biomarker; further analysis is necessary.

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

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Authors: Yang Zhang, Jian He

Abstract:

Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: Gökçe Erdemir, İlhan Yaylım, Serap Erdem-Kuruca, Musa Mutlu Can

Abstract:

It has been determined that the main reason for the death of cancer disease is caused by metastases rather than the primary tumor. The cells that leave the primary tumor and enter the circulation and cause metastasis in the secondary organs are called "circulating tumor cells" (CTCs). The presence and number of circulating tumor cells has been associated with poor prognosis in many major types of cancer, including breast, prostate, and colorectal cancer. It is thought that knowledge of circulating tumor cells, which are seen as the main cause of cancer-related deaths due to metastasis, plays a key role in the diagnosis and treatment of cancer. The fact that tissue biopsies used in cancer diagnosis and follow-up are an invasive method and are insufficient in understanding the risk of metastasis and the progression of the disease have led to new searches. Liquid biopsy tests performed with a small amount of blood sample taken from the patient for the detection of CTCs are easy and reliable, as well as allowing more than one sample to be taken over time to follow the prognosis. However, since these cells are found in very small amounts in the blood, it is very difficult to capture them and specially designed analytical techniques and devices are required. Methods based on the biological and physical properties of the cells are used to capture these cells in the blood. Early diagnosis is very important in following the prognosis of tumors of epithelial origin such as breast, lung, colon and prostate. Molecules such as EpCAM, vimentin, and cytokeratins are expressed on the surface of cells that pass into the circulation from very few primary tumors and reach secondary organs from the circulation, and are used in the diagnosis of cancer in the early stage. For example, increased EpCAM expression in breast and prostate cancer has been associated with prognosis. These molecules can be determined in some blood or body fluids to be taken from patients. However, more sensitive methods are required to be able to determine when they are at a low level according to the course of the disease. The aim is to detect these molecules found in very few cancer cells with the help of sensitive, fast-sensing biosensors, first in breast cancer cells reproduced in vitro and then in blood samples taken from breast cancer patients. In this way, cancer cells can be diagnosed early and easily and effectively treated.

Keywords: electrochemical biosensors, breast cancer, circulating tumor cells, EpCAM, Vimentin, Cytokeratins

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Authors: Dipali Dhawan

Abstract:

Cancerous epithelial cells are confined to a primary site by the continued expression of adhesion molecules and the intact basal lamina. However, as the cancer progresses some cells are believed to undergo an epithelial-mesenchymal transition (EMT) event, leading to increased motility, invasion and, ultimately, metastasis of the cells from the primary tumour to secondary sites within the body. These disseminated cancer cells need the ability to self-renew, as stem cells do, in order to establish and maintain a heterogeneous metastatic tumour mass. Identification of the specific subpopulation of cancer stem cells amenable to the process of metastasis is highly desirable. In this study, we have isolated and characterized cancer stem cells from luminal and basal breast cancer cell lines (MDA-MB-231, MDA-MB-453, MDA-MB-468, MCF7 and T47D) on the basis of cell surface markers CD44 and CD24; as well as Side Populations (SP) using Hoechst 33342 dye efflux. The isolated populations were analysed for epithelial and mesenchymal markers like E-cadherin, N-cadherin, Sfrp1 and Vimentin by Western blotting and Immunocytochemistry. MDA-MB-231 cell lines contain a major population of CD44+CD24- cells whereas MCF7, T47D and MDA-MB-231 cell lines show a side population. We observed higher expression of N-cadherin in MCF-7 SP cells as compared to MCF-7NSP (Non-side population) cells suggesting that the SP cells are mesenchymal like cells and hence express increased N-cadherin with stem cell-like properties. There was an expression of Sfrp1 in the MCF7- NSP cells as compared to no expression in MCF7-SP cells, which suggests that the Wnt pathway is expressed in the MCF7-SP cells. The mesenchymal marker Vimentin was expressed only in MDA-MB-231 cells. Hence, understanding the breast cancer heterogeneity would enable a better understanding of the disease progression and therapeutic targeting.

Keywords: cancer stem cells, epithelial to mesenchymal transition, biomarkers, breast cancer

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Authors: Atif Zafar Khan, Swarnendra Singh, Imrana Naseem

Abstract:

Breast cancer is one of the most frequent malignancies in women worldwide and a leading cause of cancer-related deaths among women. Therefore, there is a need to identify new chemotherapeutic strategies for cancer treatment. Unlike normal cells, cancer cells contain elevated copper levels which play an integral role in angiogenesis. Copper is an important metal ion associated with the chromatin DNA, particularly with guanine. Thus, targeting copper via copper-specific chelators in cancer cells can serve as effective anticancer strategy. Keeping in view these facts, we evaluated the anticancer activity and copper-dependent cytotoxic effect of coumestrol (phytoestrogen in soybean products) in breast cancer MCF-7 cells. Coumestrol inhibited proliferation and induced apoptosis in MCF-7 cells, which was prevented by copper chelator neocuproine and ROS scavengers. Coumestrol treatment induced ROS generation coupled to DNA fragmentation, up-regulation of p53/p21, cell cycle arrest at G1/S phase, mitochondrial membrane depolarization and caspases 9/3 activation. All these effects were suppressed by ROS scavengers and neocuproine. These results suggest that coumestrol targets elevated copper for redox cycling to generate ROS leading to DNA fragmentation. DNA damage leads to p53 up-regulation which directs the cell cycle arrest at G1/S phase and promotes caspase-dependent apoptosis of MCF-7 cells. In conclusion, coumestrol induces pro-oxidant cell death by chelating cellular copper to produce copper-coumestrol complexes that engages in redox cycling in breast cancer cells. Thus, targeting elevated copper levels might be a potential therapeutic strategy for selective cytotoxic action against malignant cells.

Keywords: apoptosis, breast cancer, copper chelation, coumestrol, reactive oxygens species, redox cycling

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Authors: Siddhant Rao

Abstract:

Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.

Keywords: breast cancer, mitotic count, machine learning, convolutional neural networks

Procedia PDF Downloads 202