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A Positive Deviance Approach to Roma Education
(Sage Publications Ltd, 2025) Sayan, Pinar
Across Europe, Roma students suffer from high abstention and dropout rates due to segregation in schools and classrooms, discrimination they face from the administrations, teachers, and peers, poverty, seasonal migration, and low expectations regarding education. This article, on the other hand, focuses on successful Roma students, asking whether there are any common structural factors that explain their success. The research is based on the "positive deviance approach", which suggests that solutions to community problems already exist within the community. Therefore, this article aims to contribute to developing effective policies or strategies to address the educational challenges faced by Roma by focusing on solutions employed by the community members themselves. I conduct in-depth interviews with successful Roma individuals from T & uuml;rkiye, and complement the research with existing data and reports. The main findings suggest that material and non-material support, socialization, mixed schools and guidance had a positive impact for success. The findings have the potential to influence the policy responses of international organizations, governments, and civil society.
Alterations in Niban Gene Expression as a Response to Stress Conditions in 3t3-L1 Adipocytes
(Springer, 2020) Cevik, Mehtap; Gunduz, Meliha Koldemir; Deliorman, Gokce; Susleyici, Belgin
Adipocyte death is important in obesity development. Understanding and prevention of adipocyte deaths may be a molecular approach in the treatment. In the study, we aimed to understand role of Niban gene, which acts as an anti-apoptotic molecule as a response to stress conditions, in adipocytes. 3T3-L1 adipocytes were treated with different doses of linoleic acid, hydrogen peroxide and ethanol; and proliferation of the cells examined with real time monitoring iCELLingence system. Gene expression levels were measured by q-PCR. As a response to 24h 480 mu M linoleic acid treatment, Niban gene expression was found to be higher than control group (p = 0.008), whereas 24 h 90 mM ethanol treatment was determined to be lower than control group (p = 0.008). The highest value of Niban gene expression among H2O2 treatment groups was detected in 4h 600 mu M H2O2 in comparison to control group (p = 0.008). To understand role of Niban in adipogenesis, Niban gene expressions were compared between pre-adipocytes and advanced fat accumulated adipocytes and determined to be significantly different (p = 0.042). Our results suggest that Niban might be involved in stress response process in adipocytes. However, the exact molecular role of Niban needs to be investigated in further studies.
Applications of Exosome Vesicles in Different Cancer Types as Biomarkers
(Bentham Science Publishing Ltd, 2024) Ihlamur, Murat; Kelleci, Kubra; Zengin, Yagmur; Allahverdiyev, M. Adil; Abamor, Emrah Sefik
One of the biggest challenges in the fight against cancer is early detection. Early diagnosis is vital, but there are some barriers such as economic, cultural, and personal factors. Considering the disadvantages of radiological imaging techniques or serological analysis methods used in cancer diagnosis, such as being expensive, requiring expertise, and being time-consuming, there is a need to develop faster, more reliable, and cost-effective diagnostic methods for use in cancer diagnosis.Exosomes, which are responsible for intercellular communication with sizes ranging from 30-120 nm, are naturally produced biological nanoparticles. Thanks to the cargo contents they carry, they are a potential biomarker to be used in the diagnosis of cancer. Exosomes, defined as extracellular vesicles of endosomal origin, are effective in cancer growth, progression, metastasis, and drug resistance, and changes in microenvironmental conditions during tumor development change exosome secretion. Due to their high cellular activity, tumor cells produce much higher exosomes than healthy cells. Therefore, it is known that the number of exosomes in body fluids is significantly rich compared to other cells and can act as a stand-alone diagnostic biomarker. Cancer-derived exosomes have received great attention in recent years for the early detection of cancer and the evaluation of therapeutic response.In this article, the content, properties, and differences of exosomes detected in common types of cancer (lung, liver, pancreas, ovaries, breast, colorectal), which are the leading causes of cancer-related deaths, are reviewed. We also discuss the potential utility of exosome contents as a biomarker for early detection, which is known to be important in targeted cancer therapy.
Balancing Accuracy and Efficiency in Fine-Grained Image Classification: A Systematic Comparison of CNN, Vision Transformer, and Hybrid Architectures
(Springer Wien, 2026) Eraslan, Emre Cem; Salehi, Hakan; Guzel, Mehmet Serdar; Oztas, Demir Mesut; Ekinci, Fatih; Acici, Koray; Demir, Ozge
Fine-grained image classification remains a challenging problem in computer vision due to high inter-class visual similarity and pronounced intra-class variability. In this study, a systematic and architecture-centric comparison of convolutional neural networks (CNNs), Vision Transformer (ViT) models, and hybrid architectures is presented using the Oxford 102 Flowers dataset, which comprises 8189 images across 102 visually similar categories. Rather than proposing a new architecture or training strategy, this work focuses on a controlled and comparative analysis of widely adopted deep learning paradigms under a unified experimental framework. All models are evaluated under a strictly controlled experimental protocol with fixed data splits, identical preprocessing, and unified optimization settings to reduce experimental confounding factors and enable architecture-level analysis. The experimental results show that large-scale Vision Transformers achieve the highest absolute classification performance within this benchmark setting, with ViT-L/16 attaining an accuracy of 99.37% and an F1-score of 99.27%. However, this performance is accompanied by substantial computational cost, including 303.4 million parameters and an inference time of 27.4 ms per image. In contrast, hybrid architectures exhibit a more favorable accuracy-efficiency trade-off under the same experimental conditions. Notably, ConvNeXt-V2-Tiny achieves 98.13% accuracy and a 98.05% F1-score while requiring only 27.9 million parameters and an inference time below 1 ms, achieving competitive performance with significantly lower computational complexity. Conventional CNN architectures demonstrate comparatively lower performance within this specific transfer learning configuration, with average accuracy remaining below 90%, suggesting potential limitations in capturing highly subtle inter-class variations under the evaluated setup rather than indicating general architectural inadequacy. The findings indicate that the highest classification accuracy does not necessarily correspond to the most practically efficient solution, particularly in deployment-constrained environments. Importantly, the conclusions of this study are restricted to the Oxford 102 Flowers dataset under transfer learning and standardized input resolution, and should not be interpreted as universal claims of architectural superiority. By jointly analyzing accuracy, model size, and inference latency, this work provides a structured and decision-oriented assessment of architectural trade-offs for fine-grained image classification. The results offer practical insights for selecting appropriate deep learning architectures under varying computational constraints and contribute to a more nuanced understanding of how convolutional, transformer-based, and hybrid representations behave within a controlled fine-grained benchmark setting.
Binary Particle Swarm Optimization as a Detection Tool for Influential Subsets in Linear Regression
(Taylor & Francis Ltd, 2021) Deliorman, G.; Inan, D.
An influential observation is any point that has a huge effect on the coefficients of a regression line fitting the data. The presence of such observations in the data set reduces the sensitivity and validity of the statistical analysis. In the literature there are many methods used for identifying influential observations. However, many of those methods are highly influenced by masking and swamping effects and require distributional assumptions. Especially in the presence of influential subsets most of these methods are insufficient to detect these observations. This study aims to develop a new diagnostic tool for identifying influential observations using the meta-heuristic binary particle swarm optimization algorithm. This proposed approach does not require any distributional assumptions and also not affected by masking and swamping effects as the known methods. The performance of the proposed method is analyzed via simulations and real data set applications.
CBT vs. Ericksonian Hypnotherapy for Subclinical Depression and Anxiety: 12-Month Follow-Up
(Routledge Journals, Taylor & Francis Ltd, 2026) Yılmazer, Eda; Çınaroğlu, Metin
Subclinical depression and anxiety are associated with significant psychological suffering, functional impairment, and increased risk of progression to clinical disorders, highlighting the importance of early intervention. This study examined the long-term outcomes of Cognitive Behavioral Therapy (CBT) and Ericksonian Hypnotherapy (EH) in individuals with subclinical symptoms. Participants from a randomized controlled trial (n = 45) were followed over 12 months, with assessments at baseline, mid-intervention, post-intervention, and follow-up using the Beck Depression Inventory-II and Beck Anxiety Inventory. Linear mixed-effects models indicated significant reductions in both depression and anxiety over time, with both CBT and EH outperforming the control condition. Improvements were largely maintained at follow-up, with only minor attenuation. No significant differences were observed between CBT and EH in overall effectiveness, although CBT showed slightly greater stability in depressive symptoms, while EH demonstrated marginally better maintenance of anxiety-related outcomes. Overall, both interventions produced durable and clinically meaningful improvements, supporting the role of early psychological intervention and highlighting EH as a viable complementary or alternative approach.
Cognitive Behavioral Therapy Reduces Symptom Severity and Normalizes Neurophysiological and Attentional Reactivity in Anorexia Nervosa: A Randomized Controlled Trial
(MDPI, 2026) Yılmazer, Eda; Çınaroğlu, Metin; Hızlı Sayar, Gökben; Ülker, Selami Varol
Background: Anorexia nervosa (AN) is a severe psychiatric disorder marked by restrictive eating, distorted body image, and high relapse rates. While cognitive-behavioral therapy (CBT) is a widely used treatment, its mechanisms of action in AN remain incompletely understood, particularly beyond self-reported symptom change. This study investigated the effects of a 12-week CBT intervention on both clinical and multimodal laboratory-based outcomes in women with restrictive-type AN. Methods: In a two-arm, pre-post randomized controlled trial (ClinicalTrials.gov: NCT07037017), 59 women with restrictive-type AN were randomized to a CBT intervention (n = 30) or no-treatment control (n = 29). A total of 50 participants (CBT: 26; control: 24) completed baseline and post-intervention assessments and were included in analyses. Outcomes included psychometric measures (eating disorder symptoms, depression, anxiety, body image-related obsessive-compulsive symptoms, and cognitive emotion regulation) and laboratory-based indices: electroencephalography (EEG), galvanic skin response (GSR), and eye-tracking during exposure to food- and body-related stimuli. Group & times; Time effects were analyzed using repeated-measures mixed-effects models, and statistical analyses were conducted using SPSS (Version 31; IBM Corp., Armonk, NY, USA). Results: Significant Group & times; Time interactions indicated greater improvements in the CBT group across all psychometric outcomes, including reduced eating disorder symptom severity (p < 0.001, eta(2)(p) = 0.28) and increased adaptive emotion regulation. CBT participants also showed significant reductions in EEG P300 and late positive potential (LPP) amplitudes to body-related stimuli, increased frontal alpha asymmetry, decreased visual fixation on salient body and food cues, and attenuated GSR reactivity (all p < 0.05). Exploratory correlations revealed that symptom improvements were associated with reductions in neurophysiological and attentional reactivity. Conclusions: To our knowledge, this is the first RCT in AN to demonstrate that CBT not only improves self-reported outcomes but also modulates neurophysiological and attentional processes implicated in the maintenance of the disorder. Multimodal laboratory assessments provided mechanistic insight into treatment effects and may inform personalized intervention strategies. CBT appears to facilitate recovery through both cognitive-emotional and physiological recalibration.
Comparing Cognitive Behavioral Therapy and Ericksonian Hypnotherapy for Subclinical Depression and Anxiety: A Randomized Controlled Trial
(Routledge Journals, Taylor & Francis Ltd, 2025) Cinaroglu, Metin; Yilmazer, Eda; Odabasi, Cemre; Ulker, Selami Varol; Sayar, Gokben Hizli; Hızlı Sayar, Gökben
This randomized controlled trial examined the effectiveness of Cognitive Behavioral Therapy (CBT) and Ericksonian Hypnotherapy (EH) in reducing symptoms of depression and anxiety among individuals with subclinical levels of distress. A total of 150 participants were screened, and 45 eligible participants were randomized into three groups: CBT (n = 15), EH (n = 15), and a waitlist control group (n = 15). Interventions consisted of 12 weekly sessions, with assessments conducted at baseline, mid-intervention, and post-intervention using the Beck Depression Inventory-II (BDI-II) and Beck Anxiety Inventory (BAI). Both CBT and EH significantly reduced symptoms of depression and anxiety compared to the control group, with no significant differences in efficacy between the two interventions. CBT's structured approach demonstrated consistent improvements across both depression and anxiety, while EH showed a slightly faster reduction in anxiety symptoms at mid-intervention, highlighting its potential for addressing somatic and cognitive dimensions of anxiety. This study extends previous findings by focusing on a non-clinical population, emphasizing the potential of these interventions as early strategies for preventing symptom escalation. Unlike prior work primarily targeting diagnosed populations, this research underscores the applicability of CBT and EH in addressing subthreshold distress. Limitations include a small sample size, lack of follow-up assessments, and reliance on self-reported measures. Future research should explore long-term outcomes, larger samples, and the integration of CBT and EH. These findings contribute to the growing body of evidence supporting diverse psychotherapeutic modalities for early mental health intervention.
Ericksonian Hypnotherapy versus Cognitive Behavioral Therapy for Post-Traumatic Stress Disorder
(Routledge Journals, Taylor & Francis Ltd, 2026) Çınaroğlu, Metin; Yılmazer, Eda; Noyan Ahlatcıoğlu, Esra; Hızlı Sayar, Gökben; Ülker, Selami Varol
Post-traumatic stress disorder (PTSD) is characterized by persistent psychological distress and heightened neurophysiological reactivity. While trauma-focused cognitive behavioral therapy (CBT) is an established treatment, Ericksonian Hypnotherapy (EH) may offer comparable benefits via different therapeutic mechanisms. In this randomized clinical trial, 63 adults meeting DSM-5 criteria for PTSD were allocated (1:1:1) to EH, CBT, or a waitlist control; 54 participants completed post-treatment assessments. Both active interventions consisted of 12 weekly individual sessions. Outcomes included PTSD symptom severity (PCL-5), depression (BDI-II), anxiety (BAI), EEG markers (N2, P3, frontal alpha asymmetry), and autonomic reactivity (galvanic skin response, heart rate). Group & times; Time effects were analyzed using mixed-effects models. Treatment fidelity was independently evaluated. Both EH and CBT produced large and significant reductions in PTSD symptoms compared with waitlist, with no significant difference between the two therapies in total PCL-5 improvement. Depression and anxiety symptoms also decreased substantially in both active groups. Subscale analyses suggested slightly greater reductions in intrusion, hyperarousal, and somatic anxiety symptoms in EH, whereas CBT showed modestly greater improvement in cognitive depressive symptoms. Neurophysiological findings demonstrated parallel treatment-related changes across therapies, including normalization of ERP components, shifts toward left-frontal alpha activity, and reduced autonomic reactivity to trauma cues. No adverse events were observed. In this study, Ericksonian Hypnotherapy was as effective as trauma-focused CBT for reducing PTSD symptoms and associated psychological and physiological dysregulation, supporting EH as a viable alternative intervention for PTSD.
Explainable Brain Tumor Detection in Skull Base CT Using Continuous Neural Representations: Comparative Evaluation of Neural Fields, Neural Operators, and Vision Transformers
(Pergamon-Elsevier Science Ltd, 2026) Dagli, Ozlem; Guzel, Mehmet Serdar; Kirik, Berk; Ekinci, Fatih; Acici, Koray; Demir, Ozge; Akarkamci, Hilal
Reliable brain tumor detection in CT remains challenging due to low soft-tissue contrast, skull base complexity, and imaging artifacts. This study evaluates whether continuous neural representation learning improves classification performance and interpretability for CT-based brain tumor detection. We performed a comparative evaluation of coordinate-based neural models, neural operators, and transformer-based vision models using a skull base CT dataset from Gazi University Faculty of Medicine. The dataset includes 200 patients and 40,000 slices (12,000 tumor-positive, 28,000 tumor-negative). An automated multi-stage slice selection framework was developed to extract three anatomically consistent skull base slices per patient using similarity-based ranking and anatomical validation. Ten models were evaluated, including Neural Fields, Implicit Neural Representations, DeepONet, HyperNetworks, FunCNets, Rational Neural Networks, Fourier Neural Networks, and ViT-Base/ Small/Large. Neural Fields achieved the best performance with 98.90% accuracy, 98.90% sensitivity, 98.90% specificity, 0.978 MCC, and 0.990 AUC. FunCNets ranked second overall while DeepONet achieved the highest sensitivity but lower overall balance. Transformer-based models underperformed compared to neural representation approaches. Statistical analysis confirmed significant performance differences with Neural Fields significantly outperforming competing methods. LIME analysis showed that Neural Fields focused on clinically relevant lesion regions while reducing influence from skull base artifacts. Continuous neural representations, particularly Neural Fields, provide superior accuracy and robustness for CT-based brain tumor classification compared to transformer and operator-based models. The findings demonstrate that neural field-based learning offers both high diagnostic performance and improved interpretability, supporting its potential for clinical decision-support in challenging skull base CT analysis.
Factors Affecting the Presence of Renal Cortical Cysts in Kidney Donors
(AVES, 2024) Kuşlu Çiçek, S.N.; Hüseynov, A.
Objective: Simple renal cysts (SRCs) represent the most frequently occurring type of renal cysts, frequently observed in the elderly population. While generally considered benign, SRCs may sometimes be connected to comorbid conditions such as hypertension, aortic diseases, and renal dysfunction. This research aims to investigate the factors influencing the development of SRCs in kidney donors and the associated risks. Materials and Methods: This retrospective cohort study included 1012 living kidney donors, aged 18-87 years, who underwent renal transplant donor nephrectomy between 2008 and 2023. Data on demographic information, cyst characteristics, comorbidities, and associated risk factors were collected and analyzed using statistical methods, including Binary Logistic Regression Analysis. Renal cysts were identified and classified using computed tomography (CT) and magnetic resonance imaging (MRI) methods. Results: Renal cortical cysts were more frequently observed in males (52.76%) compared to females (47.24%), with a significant difference (P =.031). Donors with renal cortical cysts were significantly older (mean age 54.43 ± 12.17 years) compared to those without cysts (46.26 ± 12.35 years, P <.001). Substantial differences were likewise noted in fasting blood glucose, uric acid, creatinine, HbA1c, and glomerular filtration rate (GFR). The prevalence of aortic atherosclerosis was notably elevated in donors with cysts (47.74%) compared to those without (23.57%, P <.001). Binary logistic regression analysis indicated that older age and being male were significant factors influencing the presence of cortical cysts. Conclusion: The study confirms that SRCs are the most common renal cyst type and are more frequently observed in the elderly population. While generally benign, SRCs may be associated with increased uric acid levels and other comorbidities, suggesting potential impacts on kidney health. Additional studies are required to investigate these associations. The presence of SRCs in kidney donors is significantly associated with male gender, age, uric acid levels, and creatinine levels. These findings should be considered during the evaluation of potential kidney donors, particularly regarding the associated risks and management of SRCs. © 2024, AVES. All rights reserved.
Factors Affecting the Presence of Renal Cortical Cysts in Kidney Donors
(Aves, 2024) Cicek, Sevim Nuran Kuslu; Huseynov, Amil
Objective: Simple renal cysts (SRCs) represent the most frequently occurring type of renal cysts, frequently observed in the elderly population. While generally considered benign, SRCs may sometimes be connected to comorbid conditions such as hypertension, aortic diseases, and renal dysfunction. This research aims to investigate the factors influencing the development of SRCs in kidney donors and the associated risks. Methods: This retrospective cohort study included 1012 living kidney donors, aged 18-87 years, who underwent renal transplant donor nephrectomy between 2008 and 2023. Data on demographic information, cyst characteristics, comorbidities, and associated risk factors were collected and analyzed using statistical methods, including Binary Logistic Regression Analysis. Renal cysts were identified and classified using computed tomography (CT) and magnetic resonance imaging (MRI) methods. Results: Renal cortical cysts were more frequently observed in males (52.76%) compared to females (47.24%), with a significant difference (P = .031). Donors with renal cortical cysts were significantly older (mean age 54.43 +/- 12.17 years) compared to those without cysts (46.26 +/- 12.35 years, P < .001). Substantial differences were likewise noted in fasting blood glucose, uric acid, creatinine, HbA1c, and glomerular filtration rate (GFR).The prevalence of aortic atherosclerosis was notably elevated in donors with cysts (47.74%) compared to those without (23.57%, P < .001). Binary logistic regression analysis indicated that older age and being male were significant factors influencing the presence of cortical cysts. Conclusion: The study confirms that SRCs are the most common renal cyst type and are more frequently observed in the elderly population. While generally benign, SRCs may be associated with increased uric acid levels and other comorbidities, suggesting potential impacts on kidney health. Additional studies are required to investigate these associations. The presence of SRCs in kidney donors is significantly associated with male gender, age, uric acid levels, and creatinine levels. These findings should be considered during the evaluation of potential kidney donors, particularly regarding the associated risks and management of SRCs.
Fault Detection in Pipelines with Graph Convolutional Networks (GCN) Method
(Gazi Üniversitesi, 2025) Şahin, E.; Yüce, H.
Pipeline networks have a wide range of applications, from the transportation of energy sources such as oil and natural gas to the conveyance and distribution of water resources. However, leaks and ruptures in pipelines can cause significant harm to the environment. Therefore, it is crucial to accurately detect pipeline faults in order to avoid economic losses and protect the environment. In this study, pipeline networks carrying water fluid are represented using graph structures. The graph convolutional network (GCN) algorithm is employed for the detection of leaks and blockages in pipeline networks. Experimental methods are employed to collect the necessary data (pressure data) for the GCN algorithm, creating two datasets by considering five different scenarios. The fault detection performance of the GCN algorithm is compared with other graph machine learning algorithms, namely, RGCN, HinSAGE, and GraphSAGE. The results of this study indicate that the performance of the GCN model surpasses that of the other algorithms. Reviewing the literature, accuracy rates for fault diagnosis in pipeline networks using machine learning algorithms range from 78.51% to 99%. In this study, it is found that the GCN, GraphSAGE, HinSAGE, and RGCN algorithms achieve fault detection accuracies of 91%, 90%, 87%, and 89%, respectively, in pipeline networks. Classical machine learning SVM model was used to compare the performance of graph-based algorithms. It is seen that the performances of the algorithms face the literature and the results are above the literature average. © 2024 Gazi Universitesi. All rights reserved.
Fondillón Wine Adulteration by Addition of Other Monastrell Wines
(MDPI, 2023) Issa-Issa, H.; Hernández, F.; López-Lluch, D.; Uysal, R.S.; Carbonell-Barrachina, A.A.
Authenticity and traceability are two issues of great importance to quality and food safety in the food industry. For wine producers and authorities, it is essential to know how to detect adulterations because wine is one of the alcoholic beverages most prone to adulteration, as indicated by the European Commission. Fondillón is one of the most important naturally sweet Spanish wines and is certainly the core of the Alicante PDO. Fondillón is a wine that is prone to be adulteration due to its limited production and high price. The aim of this study was to identify potential markers of Fondillón adulteration by mixing it with other Monastrell wines. The experimental results showed that Fondillón is characterized by high concentrations of acetic acid, furfural, benzaldehyde, vitispirane, and TDN and low concentrations of citric, tartaric, and malic acids; a low total phenolic content; and low values of antioxidant activity. © 2023 by the authors.
How the Rule of Law Shapes Trust? The Role of the Transplant Effect and Legal Families
(Akademiai Kiado ZRt., 2025) Sağlam, G.; Yanikkaya, H.
This study empirically examines the argument that the borrowing of laws and legal institutions from other countries affects the effectiveness of the legal system and, in turn, interpersonal trust. We utilise instruments on legal transplantation to understand the effectiveness of the legal system. Our instrumental variables estimations suggest that successful legal transplantation fosters trust by improving the effectiveness of the legal system. If a recipient country is familiar or culturally close to the transplanted law, or adaptation of the transplanted law has been achieved, a better legal system through mitigating the transplant effect promotes trust. Moreover, diverse and weak estimates for legal families suggest that they do not consistently affect the effectiveness of a legal system. Moreover, even after the addition of legal families into the instrument list, the transplant type variable still has a robust and consistent effect on the effectiveness of a legal system and, in turn, on trust. Regardless of the legal family of the transplanted law, if a transplant country shares cultural similarities with the country of origin, it tends to have higher interpersonal trust due to its better legal system. Therefore, lawmakers should carefully consider the importance of the nexus between legal transplantation, the legal system, and trust in addressing the economic and social challenges faced by countries. © 2025 Akadémiai Kiadó, Budapest
Investigation of Dpyd, Mthfr and Tyms Polymorphisms on 5-Fluorouracil Related Toxicities in Colorectal Cancer
(Newlands Press Ltd, 2022) Cevik, M.; Namal, E.; Şener, N.D.; Köksal, U.I.; Çaǧatay, P.; Deliorman, G.; Çiftçi, C.; Susleyici, Belgin
Aim: To investigate the association of DPYD, MTHFR and TYMS polymorphisms on 5-fluorouracil (5-FU) related toxicities and patient survival. Materials & methods: A total of 103 colorectal cancer patients prescribed 5-FU were included in the study. Genotyping was conducted for several DPYD, MTHFR and TYMS polymorphisms using a microarray analyzer. Results: DPYD 496A>G polymorphism was found to be significantly associated with 5-FU related grade 0-2, but not severe toxicities (p = 0.02). Furthermore, patients with DPYD 85TC and CC genotypes had longer progression and overall survival times compared to TT genotypes in our study group (log rank = 6.60; p = 0.01 and log rank = 4.40; p = 0.04, respectively). Conclusion: According to our results, DPYD 496AG and GG genotypes might be protective against severe adverse events compared to the AA genotype. Another DPYD polymorphism, 85T>C, may be useful in colorectal cancer prognosis. Further studies for both polymorphisms should be conducted in larger populations to achieve accurate results. © 2022 Future Medicine Ltd.
Laparoscopic Hand-Assisted Donor Nephrectomy: A Decade of Single-Center Experience and Outcomes
(AVES, 2024) Cicek, Sevim Nuran Kuslu; Huseynov, Amil
Objective: Kidney transplantation is the most effective treatment for end-stage renal disease, but the shortage of cadaveric donors has increased reliance on living donors. Traditional open donor nephrectomy, while effective, is associated with significant morbidity. Hand-assisted laparoscopic donor nephrectomy (HALDN) combines the advantages of minimally invasive surgery with the tactile feedback of open surgery. This study presents the outcomes of HALDN procedures performed at the center. Methods: A total of 1221 living donor nephrectomies performed between September 2009 and August 2021 at Medicana & Idot;stanbul Hospital were analyzed. Donor characteristics, surgical details, and postoperative outcomes were recorded. Data analysis was conducted using SPSS version 22.0, with continuous variables assessed for normality and expressed accordingly. Results: Donor ages ranged from 19 to 87 years (mean 48.50 +/- 12.75 years), with 54.8% female donors. The average body mass index (BMI) was 27.99 +/- 3.7 kg/m2. Left-sided nephrectomies constituted 78.5% of cases, with HALDN performed in 94.7% of these surgeries. Warm ischemia time averaged 99.21 +/- 56.67 seconds. The average blood loss was 70 mL, and the mean hospital stay was 4.12 +/- 1.2 days. Complications included conversion to open surgery due to bleeding in 3.3% of cases, postoperative atelectasis (0.6%), incisional hernia (0.33%), wound infection (0.16%), and scrotal swelling (0.25%). The findings indicate that HALDN is a safe and effective method for donor nephrectomy, aligning with similar studies regarding operation and warm ischemia times. The minimally invasive nature of HALDN contributes to shorter hospital stays and quicker postoperative recovery. The rate of conversion to open surgery was within acceptable limits, and complications were manageable. Obesity (BMI > 30 kg/m2) was identified as a risk factor for incisional hernia, suggesting the need for careful surgical technique in this group. Conclusion: Hand-assisted laparoscopic donor nephrectomy offers a minimally invasive, safe, and effective alternative for living donor nephrectomy, enhancing donor recovery and potentially encouraging organ donation. Its adoption may play a significant role in reducing the number of patients awaiting organ transplants.
Lumbar Spine Implant Design with Finite Element Method and Determination of Biomechanical Effects
(Gazi Univ, Fac Engineering Architecture, 2023) Taherzadeh, Paniz; Kelleci, Kubra; Ozer, Sevil
Graphical/Tabular The restoration percentages of two different implants designed and simulated in six different directions are given in Figure A. Figure A. Restoration percentages of theimplant 1 and implant 2 devices in six different directionsPurpose: In this study, it was aimed to design a new pedicle-screw based posterior dynamic stabilization implant that can help stabilize the spine normally. In the study, two different implants were designed using the finite element method (FEM) and their biomechanical effects were compared.Theory and Methods: Stable and treated models of the lumbar spine with two different implants were simulated under physiological loading conditions according to Computed tomography data. Implant and device components were created with the SOLIDWORKS program. All designed devices were used together with ABAQUS CAD simulation program and MATLAB program to calculate range of motion, adjacent level effect and restoration percentages in six different directions (right-left axial rotation, right-left lateral bending and flexion-extension). In the study, 70% restoration percentage, which is an acceptable value in the movement of the spine with the implant, was tried to be achieved in all directions.Results: With the second device, which obtained optimum data and was found to be more flexible, a higher percentage of restoration was obtained in the Z and Y axes. Restoration values are 33% for extension, 53% for flexion, and 68% and 55% for lateral bending and axial rotations, respectively.Conclusion: It can be said that pedicle-screw implants designed with this simulation study will be applicable after experimental validation and clinical trials.
Making Sense of Turkey’s Foreign Policy from the Perspective of Neorealism
(Uluslararası İlişkiler Konseyi Derneği, 2023) Oguzlu, Tarik; Han, Ahmet Kasim
This study singles out the impact of systemic and external factors on Turkey's foreign policy from the establishment of the Republic until now. Such an exercise accords with a neorealist interpretation of foreign policy, as the key emphasis is on the impact of the anarchical nature of the external environment, and the influence of the distribution of material power capabilities among states at a given time on foreign policy preferences. This in no way suggests that the internal and individual level of factors holds a secondary place in comparison to systemic/external factors. Yet this article simply highlights the importance of systemic factors, for the main reason that neorealism seems to account for foreign policy choices and behaviors of middle powers more convincingly than in the case of great powers.
On Modelling of Surface Tension of Cmc-Α Nanoparticles by Fuzzy-Hybrid Approach: A Comparison Study
(Wiley, 2023) Kocken, Hale Gonce; Insel, Mert Akin; Temelcan, Gizem; Karakus, Selcan; Albayrak, Inci; Gonce Kocken, Hale
Surface tension is one of the most important rheological parameters of nanoliquids. It influences the thermophysical and mass transfer properties of nanostructures. Accurate estimation of the surface tension from operating variables is critical for determining optimal production processes. However, the challenges of producing nanoparticles and measuring their properties introduce experimental errors in the data used for mathematical modelling. Crisp regression approaches provide adequate representation of the data, but they do not provide information about the experimental uncertainty. In this study, a fuzzy-hybrid approach is proposed for mathematical modelling of surface tension of carboxymethyl cellulose/chitosan-alpha-Fe2O3 nanoparticles. Then, the proposed model is compared with a crisp model from a previous study. Error analysis is conducted to validate the constructed fuzzy model. It is observed that the fuzzy-hybrid modelling approach has yielded significantly lower error values (a 60%-90% improvement in all error metrics on average), and thus, it is superior to the crisp approach. This study contributes to the subject of modelling rheological properties. It is shown that the fuzzy-hybrid approach has impressive potential to be utilized for modelling the rheological properties of nanostructures.