WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.14627/6
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Article Comprehensive Proteomic and Metabolomic Analysis of Novel Substituted Fluoroquinolone Derivatives in Escherichia Coli Isolates(John Wiley and Sons Ltd, 2026) Nigiz Ş.; Kulabaş N.; Türe A.; Kablan S.; Koçak E.; Özkul C.; Küçükgüzel İ.; Koçak, Engin; Nigiz, Şeyma; Kablan, Sevilay Erdoğan; Özkul, Ceren; Kulabaş, Necla; Küçükgüzel, İlkay; Türe, AslıAntimicrobial resistance is one of the most important global problems, and new antibiotic requirements have been emerging as a key point in this issue. In the present work, we focused on the efficiency of two novel promising fluoroquinolone derivatives on resistant Escherichia coli isolates at the molecular level. Their mode of action and adaptation process were evaluated by using proteomics and metabolomics analysis. Proteomics analysis showed that two compounds have an effect mainly on the ribosomal process and energy metabolism. Moreover, we observed compounds that affect various important antimicrobial targets, such as ribosomal subunits, phosphotransacetylase, and chaperone proteins. In metabolomics analysis, we found that compounds altered bacterial metabolism directly. Pathway analysis showed that cofactor biosynthesis and energy metabolism were affected mainly by undertreated groups. Our experiments demonstrated that novel fluoroquinolone derivatives have promising results at the molecular level and results will contribute to further studies. © 2026 John Wiley & Sons Ltd.Article Fully Synthetic, Nature-Inspired Exosome-Mimetics for Melanoma Therapy(Elsevier B.V., 2026) Arda Ozturk N.Z.; Majchrzak O.B.; Ulivi G.; Kirmizibayrak P.B.; Borchard G.; Patrulea V.; Ozer O.; Ozturk, Nahide Zeren Arda; Borchard, Gerrit; Ozer, Ozgen; Patrulea, Viorica; Majchrzak, Oliwia Barbara; Arda Ozturk, Nahide Zeren; Kirmizibayrak, Petek Ballar; Ulivi, GianlucaFully synthetic exosome-mimetics (FSEMs) represent a nature-inspired drug delivery system designed to replicate the key physicochemical and biological properties of natural exosomes, while offering the potential to address limitations in scalability and reproducibility associated with natural exosomes. In this study, we prepared FSEMs at the laboratory scale. We loaded them with (–)-epigallocatechin-3-gallate (EGCG) and microRNA-23a (miR-23a), aiming to co-deliver therapeutic small molecules and nucleic acids for the treatment of melanoma. FSEMs were fabricated using three methods: thin-film hydration, ethanol injection, and microfluidics. They were surface-functionalized with either CD9, a tetraspanin involved in membrane fusion, or TSP-1, an adhesion protein promoting cellular interactions. Through physicochemical characterization via dynamic light scattering, we found that FSEMs were ∼ 100 nm in size, of low polydispersity (∼0.2) and showed a negative zeta potential (∼–55 mV). Both EGCG and miR-23a were efficiently encapsulated. SDS-PAGE analysis confirmed successful protein incorporation and correct positioning. In vitro release studies showed minimal premature leakage, supporting their suitability for cellular uptake-mediated delivery. When tested on melanoma cells (MDA-MB-435) and progenitor human dermal fibroblasts (FE002-SK2), FSEMs selectively killed melanoma cells while sparing fibroblasts. Importantly, EGCG within FSEMs was more effective than the free compound. Compared to conventional DOTAP-based liposomes, FSEMs were more selective and induced less off-target cytotoxicity. This study presents a proof-of-concept for fully synthetic, protein-functionalized FSEMs as dual carriers for both chemical and gene-based agents, offering a safer and potentially more effective alternative to traditional cationic liposomes. These results lay the groundwork for future in vivo validation and translational cancer research. © 2026 The Author(s)Article Components of Design Thinking in Spatial Design Education and a Model Proposal(Konya Technical Univ, Fac Architecture & Design, 2025) Coruk, Ipek YildirimDesign thinking, defined in its simplest form as a creative problem-solving process, is interpreted in various ways in the literature, with differing models and components. This study, motivated by the need to identify gaps in existing approaches and to clarify the concept of design thinking, aims to define its key components within the context of spatial design education. To achieve this objective, the study employed qualitative research methods. To collect data, the study utilized both a literature review and content analysis techniques. By categorizing the collected data, it was concluded that design thinking consists of three fundamental components: cognitive-rational, emotional-intuitive, and practical. These components were elaborated upon with subcategories based on literature data, and a comprehensive model proposal for use in space design education was developed. The proposal put forward in this study is significant in clarifying the concept of design thinking and its constituent components. On the other hand, the potential of the proposed model to offer guiding alternatives for the problem-solving process in design studios at various levels and to make design thinking more explicit can be attributed to the pedagogical contributions of this study. From a practical perspective, the study is considered to have the potential to directly inform practice by proposing concrete and applicable steps that can be implemented within the design process. For future research based on this study, it is recommended that the potential contributions of the proposed model be explored through its application in actual design processes. Furthermore, expandingthe theoretical scope by questioning different approaches to the components of design thinking is also suggested.Article Effects of Combined Triflow, Deep Breathing and Coughing Exercises on Postoperative Pulmonary Function After Mitral Valve Replacement: A Randomized Controlled Trial(BMC, 2026) Akinci, Naile; Eren, EsraBackground Postoperative pulmonary complications remain a major cause of morbidity after cardiac valve surgery. Although incentive spirometry (Triflow) is routinely used in postoperative care, evidence regarding the additional benefits of combining Triflow with deep breathing and coughing exercises remains limited. This study aimed to evaluate the effects of combined Triflow, deep breathing, and coughing exercises on postoperative pulmonary function in adult patients undergoing mitral valve replacement. Methods This randomized controlled, single-blind trial was conducted between May and August 2025 in a private hospital in Istanbul. A total of 60 adult patients undergoing mitral valve replacement were randomly allocated to an experimental group (n = 30) or a control group (n = 30) using simple randomization. The experimental group performed Triflow combined with deep breathing and coughing exercises, while the control group performed Triflow alone. Results Postoperative SpO(2) levels were significantly higher in the experimental group at T1 (p = 0.009; 95% CI: 0.46-3.14), T2 (p < 0.001; 95% CI: 1.57-3.43), and T3 (p < 0.001; 95% CI: 2.72-4.54). The FEV1/FVC ratio increased significantly in the experimental group compared with the control group at discharge (p < 0.001; 95% CI: 4.46-6.41). Respiratory rate was significantly higher in the experimental group at T1 (p < 0.001; 95% CI: 1.68-4.45), T2 (p < 0.001; 95% CI: 3.34-6.26), and T3 (p < 0.001; 95% CI: 5.23-8.37). Hematocrit levels were significantly lower in the experimental group at T1 (p = 0.039; 95% CI: -8.32 to - 0.24), T2 (p = 0.007; 95% CI: -8.29 to - 1.40), and T3 (p = 0.034; 95% CI: -6.54 to - 0.28). Pain scores were significantly lower in the experimental group at T1 (p < 0.001; 95% CI: -2.82 to - 1.71) and T2 (p < 0.001; 95% CI: -1.98 to - 1.08). Time to first mobilization was significantly shorter in the experimental group (p < 0.001; 95% CI: -2.94 to - 1.26). No postoperative pulmonary complications were observed in either group. Conclusion The combined application of Triflow, deep breathing, and coughing exercises was associated with significant improvements in postoperative pulmonary function, oxygen saturation, pain reduction, and earlier mobilization compared with Triflow alone in patients undergoing mitral valve replacement. These findings suggest that a structured, combined respiratory exercise protocol may provide additional clinical benefits in the early postoperative period.Article The Relationship Between Nurses Anxiety and Attitudes Towards Artificial Intelligence and Examination of Influencing Factors(BMC, 2026) Nirgiz, Cansu; Sari, Merve Kiymac; Cayli, NazanAim to explore the relationships between nurses'anxiety and attitudes toward artificial intelligence (AI) and the factors associated with them. Background Although AI technologies are increasingly integrated into healthcare, research exploring nurses ' psychological readiness and emotional responses to AI remains limited. Existing studies have primarily focused on nursing students or general healthcare professionals, leaving a gap in understanding how practicing nurses perceive and emotionally adapt to AI within real clinical environments-particularly in T & uuml;rkiye, where digital transformation in healthcare is accelerating. Addressing this gap is essential, as nurses play a pivotal role in ensuring the safe and ethical implementation of AI-driven tools in patient care. Methods This descriptive and correlational study included 562 nurses from 14 branches of a private hospital chain across seven Turkish cities between November 2024 and January 2025.This sample was selected because it represents nurses actively engaged in clinical decision-making within healthcare systems that are rapidly adopting AI technologies. According to a power analysis performed in G*Power (rho = 0.25, alpha = 0.05, power = 0.95), the required sample size was 202 participants. Data were collected through an online questionnaire comprising a Descriptive Information Form, the AI Anxiety Scale, and the General Attitudes toward AI Scale. Descriptive statistics, independent samples t-tests, ANOVA (F), Tukey post hoc test, Pearson correlation, and multiple regression analyses were conducted. Ethical approval was obtained from the Fenerbah & ccedil;e University Ethics Committee, and informed consent was obtained digitally. Results Nurses reported moderate anxiety levels and generally positive attitudes toward AI. Male nurses showed an association with lower anxiety levels and higher positive attitude scores than female nurses. Single individuals and those with higher levels of education showed higher positive attitudes toward AI. Those with 0-3 years of experience in the profession were associated with lower anxiety and higher positive attitude scores. Nurses who used AI in practice, were knowledgeable about its use, or perceived it as reliable showed a relationship with lower anxiety and more positive attitudes. Regression analysis showed that each one-unit increase in the learning and AI configuration subscales of the AI Anxiety Scale was associated with a 0.740-and 0.716-point lower score in the total attitude score, respectively. Conclusion The findings suggest that lower levels of anxiety related to learning and AI configuration are associated with more positive attitudes toward AI. Addressing these specific anxiety domains may be related to the successful integration of AI technologies into clinical practice and could be linked to the digital transformation in healthcare.Article Evaluation of Barriers Toward Data-Driven Supply Chain Sustainability Via Single-Valued Pythagorean Piprecia(Amer Inst Mathematical Sciences-AIMS, 2026) Turan, Hakan; Buyukselcuk, Elif CalogluSustainable supply chain management (SSCM) is a holistic approach that encompasses economic, social, and environmental dimensions, enabling firms to enhance their long-term competitiveness by meeting legal requirements and strengthening brand equity. The effective implementation of this approach necessitates a strong emphasis on data-driven decision-making. Accordingly, we aimed to identify the key barriers hindering the implementation of data-driven sustainable supply chain practices and to explore potential strategies to overcome these challenges. In the initial phase of the study, a comprehensive literature review was conducted to identify the major barriers to implementing data-driven sustainable supply chains. Subsequently, the relative importance of these barriers was assessed with input from top and mid-level managers working in manufacturing sector enterprises. The identified barriers were then prioritized using the Pivot Pairwise Relative Criteria Importance Assessment (PIPRECIA) method based on Pythagorean fuzzy numbers. Finally, solution proposals were developed to address the most critical barriers. The study revealed that organizational barriers constitute the most prominent category, representing 29.86% of the total identified obstacles. Closely following are technical barriers, which account for 26.41% and reflect the difficulties associated with implementing and integrating digital technologies. Internal and external environmental barriers are similarly substantial, comprising 25.87% of the total. In comparison, economic barriers make up the smallest share, with a relative weight of 17.86%. The number of researchers analyzing the importance weights of barriers in the context of SSCM 4.0 remains limited. The utilization of a more contemporary and robust method compared to previously applied techniques for determining these weights enhances the originality of this study.Article Mapping the Evolution of Stigmatization in Mental Disorders: A Bibliometric Analysis From 1974 to 2024(Springer Heidelberg, 2026) Goktas, Polat; Dikec, GulBackgroundThis bibliometric study scrutinizes the thematic evolution of research on stigma and discrimination in mental disorders, covering a span of five decades. It reflects on the shifting paradigms within the stigma-focused mental health research community from 1974 to 2024.MethodsA comprehensive bibliometric analysis was employed using the Bibliometrix R package and VOSviewer software, analyzing 1,892 articles from databases like Scopus, Web of Science, PubMed Central, and APA PsycInfo. Adherence to PRIBA guidelines ensured a holistic representation of the evolving research narrative.ResultsThe analysis outlined three distinct periods: the Genesis Period (1974 - 2007), focusing on foundational concepts of mental disorders and stigma; the Growth Period (2008 - 2015), which experienced a broadening into themes of discrimination and diagnostic refinement; and the Rapid Growth Period (2016 - 2024), characterized by a surge in research on child mental disorders and the impacts of posttraumatic stress disorder. Network analyses highlighted significant journals, key authors, and international collaborations that have shaped this field.ConclusionsThe study maps a significant transformation in stigma-focused mental health research themes over fifty years, highlighting the growing complexity and the need for ongoing research into stigma and discrimination. It calls for interdisciplinary approaches to tackle these enduring challenges effectively.Article Machine Learning Model for Predicting Multidrug Resistance in Clinical Klebsiella pneumoniae Isolates(MDPI, 2026) Akkaya, Yuksel; Aydin, Irfan; Tanyildizi-Kokkulunk, Handan; Erturk, Ayse; Kilic, Ibrahim HalilBackground/Objectives: Klebsiella pneumoniae is an opportunistic pathogen increasingly resistant to carbapenems and broad-spectrum antibiotics, complicating timely infection management. In critical cases like septic shock, where initiating effective antibiotics within 3 h improves survival, culture-based resistance testing is often too slow. This study evaluates machine learning (ML) algorithms for faster antimicrobial resistance prediction than conventional methods. Methods: In this retrospective study, antibiogram results of 607 Klebsiella pneumoniae isolates collected between 2017 and 2024 were combined with demographic and clinical information of the patients from whom the isolates were obtained. Four different ML algorithms, namely Decision Tree (DT), Support Vector Classifier (SVC), K-Nearest Neighbors (KNN) and Random Forest (RF), were applied to classify the resistance status for 22 antibiotics. Model performances were evaluated using accuracy, precision, recall, F-score, AUC and feature importance metrics. Results: The RF model showed the highest overall performance in accurately predicting resistance to 22 antibiotics, achieving an average AUC value of 0.96. In particular, it predicted resistance to treatment-critical antibiotics such as Ertapenem (100%), Imipenem (93%) and Meropenem (95%) with high accuracy. Conclusions: ML models, especially RF, offer a powerful tool for rapid antibiotic resistance prediction, supporting accurate empirical treatment decisions and antimicrobial stewardship.Article Sexual Problems of Women with Kidney Transplant: A Qualitative Study(Galenos Publ House, 2026) Akinci, Naile; Varisoglu, Yeliz Yildirim; Dogan, BayramObjective: This qualitative study aimed to explore the experiences, perspectives, and challenges faced by women who underwent kidney transplantation, particularly regarding the impact of transplantation on their own and their partner's sexual lives. Methods: The study was conducted with 15 women who had received kidney transplants at a private hospital in & Idot;stanbul. Data were gathered using a two-part semi-structured interview form developed by the researcher based on a review of the relevant literature. The data obtained from the interviews were analyzed using content analysis. Data analysis was carried out concurrently with data collection. This study adhered to the consolidated criteria for reporting qualitative research. Results: Based on a thematic analysis of the interviews, four main themes emerged: concerns about reproductive health, including subthemes of fear of infertility and anxiety about pregnancy; disease-associated sexual reluctance, including subthemes of reduced sexual interest, fatigue, weakness, sleep disturbances, and depression; perception of femininity and body image, including subthemes of feelings of incompleteness and inadequacy; concerns about the spouse/partner, including subthemes of fears about being unable to meet the sexual needs of the spouse/partner and feelings of guilt related to their partner's sexual dissatisfaction. Conclusion: In conclusion, sexual dysfunction continues to persist among women even after kidney transplantation due to various physical and psychological factors. To support patients in maintaining a healthy sexual life as part of their overall well-being, sexual health should be routinely assessed by a multidisciplinary team, including transplant surgeons, surgical and obstetric/ gynecology nurses, and psychologists.Article Social Media and Financial Decisions: The Influence of Socio-Demographics and Financial Literacy(John Wiley and Sons Inc, 2026) Altinbas, H.This study investigates the predictors of individuals' reliance on social media for financial decision-making within the context of Türkiye's high-inflation environment and the associated surge in retail investor participation. Data were collected via an online survey utilizing the OECD's financial literacy toolkit. The results indicate that gender, family structure, high-risk asset preferences, and financial literacy predict social media usage for financial information. Specifically, males, individuals who invest in stocks or cryptocurrencies, and those with higher financial literacy demonstrate a greater propensity to access financial information on social media; conversely, households with children exhibit lower reliance on social media information. © 2026 American Association of Family and Consumer Sciences.