Browsing by Publisher "Tech Science Press"

Now showing 1 - 9 of 9
  • No Thumbnail Available
    Item
    Role of intercellular communications in breast cancer multicellular tumor spheroids after chemotherapy
    (Tech Science Press, 2006) Oktem G.; Bilir A.; Ayla S.; Yavasoglu A.; Goksel G.; Saydam G.; Uysal A.
    Tumor heterogeneity is an important feature that is especially involved in tumor aggressiveness. Multicellular tumor spheroids (MTS) may provide some benefits in different steps for investigation of the aggregation, organization, differentiation, and network formation of tumor cells in 3D space. This model offers a unique opportunity for improvements in the capability of a current strategy to detect the effect of an appropriate anticancer agent. The aim of this study was to investigate the cellular interactions and morphological changes following chemotherapy in a 3D breast cancer spheroid model. Distribution of the gap junction protein "connexin-43" and the tight junction protein "occludin" was investigated by immunohistochemistry. Cellular interactions were examined by using transmission and scanning electron microscopies as well as light microscopy with Giemsa staining after treating cells with doxorubicin, docetaxel, and doxorubicin/docetaxel combination. Statistical analyses showed significant changes and various alterations that were observed in all groups; however, the most prominent effect was detected in the doxorubicin/docetaxel combination group. Distinct composition as a vessel-like structure and a pseudoglandular pattern of control spheroids were detected in drug-administered groups. Immunohistochemical results were consistent with the ultrastructural changes. In conclusion, doxorubicin/ docetaxel combination may be more effective than the single drug usage as shown in a 3D model. The MTS model has been found to be an appropriate and reliable method for the detection of the changes in the expression of cellular junction proteins as well as other cellular proteins occurring after chemotherapy. The MTS model can be used to validate the effects of various combinations or new chemotherapeutic agents as well as documentation of possible mechanisms of new drugs. Copyright © 2006 Cognizant Comm. Corp.
  • No Thumbnail Available
    Item
    Chemotherapy influences inducible nitric oxide synthase (iNOS) and endothelial nitric oxide synthase (eNOS) activity on 3D breast cancer cell line
    (Tech Science Press, 2006) Öktem G.; Bilir A.; Selvi N.; Yurtseven M.E.; Vatansever S.; Ates U.; Uysal A.; Omay S.B.
    Multicellular tumor spheroids (MTS) are three-dimensional structural forms of tumors grown in vitro in the laboratory. In this study, the aim was to determine the regulation of inducible nitric oxide synthase (iNOS) and endothelial nitric oxide synthase (eNOS) expressions on MTS in response to treatment with the commonly used anti-cancer drugs Doxorubicin and Docetaxel. The spheroids were generated using the "liquid overlay" technique. The distribution of both iNOS and eNOS was detected using indirect immunohistochemistry, while the expression of both iNOS and eNOS was measured using Western blots. Additionally, S-phase analysis using 5-bromo-2′- deoxyuridine (BrdU) was done on the MTS after treatment with doxorubicin, docetaxel, and a combination of the two. The Griess method was used to measure nitric oxide (NO) production in the cells. An increase in iNOS immunoreactivity and a decrease in eNOS immunoreactivity were observed after doxorubicin treatment, when compared with the other groups. Furthermore, upregulation of iNOS and downregulation of eNOS were detected in doxorubicin-treated cells using Western blotting. Insignificant iNOS expression was observed in all of the groups, and it was particularly low in the control and drug combination groups. NO production was also found to be significantly high after docetaxel treatment, and cell proliferation decreased after doxorubicin treatment. In conclusion, chemotherapy influences NOS activity differently with the presence of different drugs. The results with iNOS show that doxorubicin is a more effective drug than docetaxel, and a drug combination may play a helpful role in the suppression of tumorigenicity and cancer metastasis. Interestingly, eNOS expression increased after the addition of both docetaxel and the drug combination, and it was found to negatively correlate with the histological grade of the tumor. Therefore, analyzing the expression of both iNOS and eNOS might be very useful for targeting the treatment of breast carcinoma and obtaining better information on prognosis. Copyright © 2006 Cognizant Comm. Corp.
  • No Thumbnail Available
    Item
    A study on the estimation of prefabricated glass fiber reinforced concrete panel strength values with an artificial neural network model
    (Tech Science Press, 2016) Yildizel S.A.; Öztürk A.U.
    In this study, artificial neural networks trained with swarm based artificial bee colony optimization algorithm was implemented for prediction of the modulus of rapture values of the fabricated glass fiber reinforced concrete panels. For the application of the ANN models, 143 different four-point bending test results of glass fiber reinforced concrete mixes with the varied parameters of temperature, fiber content and slump values were introduced the artificial bee colony optimization and conventional back propagation algorithms. Training and the testing results of the corresponding models showed that artificial neural networks trained with the artificial bee colony optimization algorithm have remarkable potential for the prediction of modulus of rupture values and this method can be used as a preliminary decision criterion for quality check of the fabricated products. © 2016 Tech Science Press.
  • No Thumbnail Available
    Item
    Glass fibre reinforced concrete rebound optimization
    (Tech Science Press, 2017) Yildizel S.A.; Yiǧit M.E.; Kaplan G.
    Glass fibre reinforced concrete placement technique generates losses due to rebound effects of the already sprayed concrete particles. Rebounded concrete amount cause a significant difference between the initial mix design and emplaced mix compositions. Apart from the structural differences, it comes with a cost increase which was resulted by the splashed concrete amount. Many factors such as viscosity and quantity of mixes dominate this rebound amount in sprayed glass fibre reinforced concrete applications depending on production technologies and processes; however, this research focuses on the spray distance and the angle of the spray gun which mainly effects the rebound amount in glass fibre reinforced concrete production. This paper aims to understand the required angle and distance for glass fibre reinforced concrete mixes having on-site plastic viscosity values. Glass fibre reinforced mixtures were also modelled with a finite element method based software and, the analysis results were compared with production line results. Results of the analysis and on-site studies showed a decisive correlation between, discharge distance, discharge angle and the viscosity of the concrete. © Copyright 2017 Tech Science Press.
  • No Thumbnail Available
    Item
    Bell polynomial approach for the solutions of Fredholm integro-differential equations with variable coefficients
    (Tech Science Press, 2020) Yıldız G.; Tınaztepe G.; Sezer M.
    In this article, we approximate the solution of high order linear Fredholm integro-differential equations with a variable coefficient under the initial-boundary conditions by Bell polynomials. Using collocation points and treating the solution as a linear combination of Bell polynomials, the problem is reduced to linear system of equations whose unknown variables are Bell coefficients. The solution to this algebraic system determines the approximate solution. Error estimation of approximate solution is done. Some examples are provided to illustrate the performance of the method. The numerical results are compared with the collocation method based on Legendre polynomials and the other two methods based on Taylor polynomials. It is observed that the method is better than Legendre collocation method and as accurate as the methods involving Taylor polynomials. © 2020 Tech Science Press. All rights reserved.
  • No Thumbnail Available
    Item
    Multi-institutional analysis of cervical esophageal carcinoma patients treated with definitive chemoradiotherapy: TROD 01-005 study
    (Tech Science Press, 2023) Guler O.C.; Oymak E.; Yazici G.; Akagunduz O.O.; Cetinayak O.; Erpolat P.; Aksoy A.; Duzova M.; Yildirim B.A.; Kurt M.; Canyilmaz E.; Yavas G.; Akyurek S.; Oksuz D.C.; Saglam E.K.; Celik O.K.; Ozyar E.; Cengiz M.; Onal C.
    The aim of this study was to examine the prognostic factors and treatment outcomes of cervical esophageal carcinoma (CEC) patients who underwent definitive chemoradiotherapy (CRT). The clinical data of 175 biopsy-confirmed CEC patients treated with definitive CRT between April 2005 and September 2021 were retrospectively analyzed. The prognostic factors predicting overall survival (OS), progression-free survival (PFS), and local recurrence-free survival (LRFS) were assessed in uni-and multivariable analyses. The median age of the entire cohort was 56 years (range: 26–87 years). All patients received definitive radiotherapy with a median total dose of 60 Gy, and 52% of the patients received cisplatin-based concurrent chemotherapy. The 2-year OS, PFS, and LRFS rates were 58.8%, 46.9%, and 52.4%, respectively, with a median follow-up duration of 41.6 months. Patients’ performance status, clinical nodal stage, tumor size, and treatment response were significant prognostic factors for OS, PFS, and LRFS in univariate analysis. Non-complete treatment response was an independent predictor for poor OS (HR = 4.41, 95% CI, 2.78–7.00, p < 0.001) and PFS (HR = 4.28, 95% CI, 2.79–6.58, p < 0.001), whereas poor performance score was a predictor for worse LRFS (HR = 1.83, 95% CI, 1.12–2.98, p = 0.02) in multivariable analysis. Fifty-two patients (29.7%) experienced grade II or higher toxicity. In this multicenter study, we demonstrated that definitive CRT is a safe and effective treatment for patients with CEC. Higher radiation doses were found to have no effect on treatment outcomes, but a better response to treatment and a better patient performance status did. © 2023, Tech Science Press. All rights reserved.
  • No Thumbnail Available
    Item
    A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems
    (Tech Science Press, 2023) Altay E.V.; Altay O.; Özçevik Y.
    Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve. Such design problems are widely experienced in many engineering fields, such as industry, automotive, construction, machinery, and interdisciplinary research. However, there are established optimization techniques that have shown effectiveness in addressing these types of issues. This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues. The algorithms used in the study are listed as: transient search optimization (TSO), equilibrium optimizer (EO), grey wolf optimizer (GWO), moth-flame optimization (MFO), whale optimization algorithm (WOA), slime mould algorithm (SMA), harris hawks optimization (HHO), chimp optimization algorithm (COA), coot optimization algorithm (COOT), multi-verse optimization (MVO), arithmetic optimization algorithm (AOA), aquila optimizer (AO), sine cosine algorithm (SCA), smell agent optimization (SAO), and seagull optimization algorithm (SOA), pelican optimization algorithm (POA), and coati optimization algorithm (CA). As far as we know, there is no comparative analysis of recent and popular methods against the concrete conditions of real-world engineering problems. Hence, a remarkable research guideline is presented in the study for researchers working in the fields of engineering and artificial intelligence, especially when applying the optimization methods that have emerged recently. Future research can rely on this work for a literature search on comparisons of metaheuristic optimization methods in real-world problems under similar conditions. © 2023 Tech Science Press. All rights reserved.
  • No Thumbnail Available
    Item
    In vitro engineered models of neurodegenerative diseases
    (Tech Science Press, 2024) Morçimen Z.G.; Taşdemir Ş.; Şendemir A.
    Neurodegeneration is a catastrophic process that develops progressive damage leading to functional and structural loss of the cells of the nervous system and is among the biggest unavoidable problems of our age. Animal models do not reflect the pathophysiology observed in humans due to distinct differences between the neural pathways, gene expression patterns, neuronal plasticity, and other disease-related mechanisms in animals and humans. Classical in vitro cell culture models are also not sufficient for pre-clinical drug testing in reflecting the complex pathophysiology of neurodegenerative diseases. Today, modern, engineered techniques are applied to develop multicellular, intricate in vitro models and to create the closest microenvironment simulating biological, biochemical, and mechanical characteristics of the in vivo degenerating tissue. In THIS review, the capabilities and shortcomings of scaffold-based and scaffold-free techniques, organoids, and microfluidic models that best reflect neurodegeneration in vitro in the biomimetic framework are discussed. © 2024 Tech Science Press. All rights reserved.
  • No Thumbnail Available
    Item
    HybridGAD: Identification of AI-Generated Radiology Abstracts Based on a Novel Hybrid Model with Attention Mechanism
    (Tech Science Press, 2024) Çelikten T.; Onan A.
    The purpose of this study is to develop a reliable method for distinguishing between AI-generated, paraphrased, and human-written texts, which is crucial for maintaining the integrity of research and ensuring accurate information flow in critical fields such as healthcare. To achieve this, we propose HybridGAD, a novel hybrid model that combines Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Bidirectional Gated Recurrent Unit (Bi-GRU) architectures with an attention mechanism. Our methodology involves training this hybrid model on a dataset of radiology abstracts, encompassing texts generated by AI, paraphrased by AI, and written by humans. The major findings of our analysis indicate that HybridGAD achieves a high accuracy of 98%, significantly outperforming existing state-of-the-art models. This high performance is attributed to the model’s ability to effectively capture the contextual nuances and structural differences between AI-generated and human-written texts. In conclusion, HybridGAD not only enhances the accuracy of text classification in the field of radiology but also paves the way for more advanced medical diagnostic processes by ensuring the authenticity of textual information. Future research will focus on integrating textual and visual data for comprehensive radiology assessments and improving model generalization with partially labeled data. This study underscores the potential of HybridGAD in transforming medical text classification and highlights its applicability in ensuring the integrity and reliability of research in healthcare and beyond. © 2024 Tech Science Press. All rights reserved.