WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.14627/6
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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 Evaluation of Barriers to the Integration of Renewable Energy Technologies into Industries in Türkiye(MDPI, 2026) Caloglu Buyukselcuk, Elif; Turan, HakanThe transition to renewable energy technologies is one of the most important ways to achieve the sustainable development goals (SDGs) of affordable and clean energy (SDG7); industry, innovation and infrastructure (SDG9); responsible production and consumption (SDG12); and climate action (SDG13). The widespread use of renewable energy technologies in developing countries will reduce dependence on imported fossil resources, increase industrial competitiveness, and support low-carbon development. Despite all their advantages, the integration of renewable energy technologies into industrial and domestic systems in developing countries remains slow due to a number of barriers. Financial constraints, technical and technological deficiencies, political restrictions and uncertainties, and organizational and managerial inadequacies are some of the barriers to the widespread adoption of renewable energy technologies. This study aims to identify, classify, and prioritize the barriers to the implementation of renewable energy technologies by applying multi-criteria decision-making methods in a fuzzy environment, with T & uuml;rkiye considered as a case study. The relative importance of the barriers identified using the Single-Valued Spherical Fuzzy SWARA method was assessed, and their interconnections and significance were systematically demonstrated. The findings will contribute to the development of policy and management strategies aligned with global sustainability goals, thereby facilitating a more effective and equitable transition to clean and resilient energy systems.Article From Data to Autonomy: Integrating Demographic Factors and AI Models for Expert-Free Exercise Coaching(MDPI, 2026) Ozbalkan, Ugur; Turna, Ozgur CanThis study investigates the performance of three deep learning architectures-LSTM with Attention, GRU with Attention, and Transformer-in the context of real-time, self-guided exercise classification, using coordinate data collected from 103 participants via a dual-camera system. Each model was evaluated over ten randomized runs to ensure robustness and statistical validity. The GRU + Attention and LSTM + Attention models demonstrated consistently high test accuracy (mean approximate to 98.9%), while the Transformer model yielded significantly lower accuracy (mean approximate to 96.6%) with greater variance. Paired t-tests confirmed that the difference between LSTM and GRU models was not statistically significant (p = 0.9249), while both models significantly outperformed the Transformer architecture (p < 0.01). In addition, participant-specific features, such as athletic experience and BMI, were found to affect classification accuracy. These findings support the feasibility of AI-based feedback systems in enhancing unsupervised training, offering a scalable solution to bridge the gap between expert supervision and autonomous physical practice.Article Evaluation of Octenidine Dihydrochloride-Induced Cytotoxicity, Apoptosis, and Inflammatory Responses in Human Ocular Epithelial and Retinal Cells(MDPI, 2025) Ciftci, Ihsan Hakki; Deveci Ozkan, Asuman; Erman, Gulay; Kilbas, Imdat; Aydemir, OzlemBackground/Objectives: Octenidine dihydrochloride (OCT-D) is a broad-spectrum antiseptic with high chemical stability, low toxicity, and no reported microbial resistance, making it a strong candidate for use on mucosal surfaces. Despite increasing interest in its potential ophthalmic applications, limited data exist regarding its cellular effects on ocular tissues. This study aimed to investigate the cytotoxic, apoptotic, inflammatory, and transcriptional responses induced by OCT-D in human conjunctival (IOBA-NHC) and retinal pigment epithelial (ARPE-19) cells. Methods: Cells were exposed to varying concentrations of OCT-D, and viability was assessed using the WST-1 assay to determine IC50 and IC50/2 values. These concentrations were subsequently used in molecular assays. Pro-inflammatory cytokines (IL-6, IL-1 beta, TNF-alpha, IFN-gamma) were quantified by ELISA. Apoptotic activation was evaluated through caspase-3/7 activity assays. Gene expression analysis of apoptotic (Bax, Bcl-2), DNA damage-related (ATM, Rad51), and inflammatory markers was performed using RT-qPCR. Results: OCT-D induced a marked, dose-dependent reduction in cell viability in both cell lines, with ARPE-19 showing greater sensitivity. Caspase-3/7 activity increased significantly at IC50 and IC50/2, confirming intrinsic apoptotic activation. OCT-D markedly suppressed the release of key inflammatory cytokines and downregulated transcription of inflammatory genes. RT-qPCR revealed upregulation of pro-apoptotic and DNA damage-associated genes, demonstrating coordinated activation of apoptotic and genomic stress pathways. Conclusion: OCT-D triggers integrated cytotoxic, apoptotic, and immunomodulatory responses in conjunctival and retinal epithelial cells. While these findings provide important mechanistic insights into OCT-D's cellular effects, further studies using primary cells, advanced 3D ocular models, and disease-relevant systems are required to support its potential translational use in ophthalmology.Article In Vitro Investigation of the Effects of Octenidine Dihydrochloride on Nasal Septum Squamous Carcinoma Cells(MDPI, 2025) Ciftci, Ihsan Hakki; Ozkan, Asuman Deveci; Erman, Gulay; Kilbas, Elmas Pinar Kahraman; Koroglu, Mehmet; Kahraman Kilbas, Elmas Pinar; Deveci Ozkan, AsumanBackground/Objectives: The aim of this study was to investigate the cytotoxic, genotoxic, apoptotic, and anti-inflammatory effects of the antiseptic agent octenidine dihydrochloride (OCT-D) on the RPMI-2650 cell line derived from human nasal mucosa in vitro. Methods: RPMI-2650 cells and Human Umbilical Cord Endothelial Cells (HUVECs) were treated with various concentrations of OCT-D (0.00625-0.4%) for 12 and 24 h. Cell viability was assessed using the WST-1 assay, while DNA damage was assessed using the comet and micronucleus (MN) assays. Apoptotic activity was determined using Annexin V flow cytometry and fluorescence microscopy. Intracellular reactive oxygen species (ROS) levels were measured, and inflammatory cytokines (IL-1 beta, IL-6, TNF-alpha, and IFN-gamma) were measured by Enzyme-Linked Immunosorbent Assay (ELISA). The mRNA expression of genes associated with apoptosis, oxidative stress, and inflammation was analyzed using RT-PCR. Results: OCT-D caused dose- and time-dependent cytotoxicity, and RPMI-2650 cells showed greater resistance compared to HUVECs. While a strong apoptotic response was observed in HUVECs, RPMI-2650 cells exhibited limited apoptosis. OCT-D was found to cause dose-dependent DNA damage and an increase in MN in both cell lines. OCT-D significantly reduced cytokine levels and ROS production in both cell types. RT-PCR results supported its anti-inflammatory and antioxidant effects at the molecular level. Conclusions: In conclusion, this study demonstrated that OCT-D exhibited minimal cytotoxic and apoptotic effects in RPMI-2650 cells, but affected vascular structure by inducing apoptosis in endothelial cells. These findings provide important evidence that OCT-D can be used as a potential adjunctive agent in nasal treatments, and these data need to be supported by preclinical and clinical studies.Article Evaluation of the Relationship Between Job Stress Level, Adherence to the Mediterranean Diet, and Phytochemical Index(MDPI, 2025) Cetiner Bingul, Bengi; Bas, MuratBackground/Objectives: Job stress negatively affects physical and psychological health and can lead to behavioral changes such as unhealthy eating. This study aimed to evaluate the relationship between job stress levels, adherence to the Mediterranean diet, and the phytochemical index (PI). Methods: The study included 200 healthy individuals aged 18-50 working at the Tuzla Gum Factory. Data were collected through demographic and dietary questionnaires, two-day 24-h food records, PI values, and anthropometric measurements. Job stress was assessed using the Job Stress Scale, and Mediterranean diet adherence was assessed with the Mediterranean Diet Adherence Questionnaire. Results: Waist and hip circumference, waist/hip ratio, and BMI were significantly higher in individuals with high levels of job stress (p < 0.01). Unskilled workers reported higher stress than professionals (p < 0.01). Significant differences were found in carbohydrate and fiber intake among males and in energy, protein, carbohydrate, and vitamin A intake among females with varying stress levels (p < 0.01). No significant difference in Mediterranean diet adherence was observed between medium and high stress groups. However, women had higher adherence and PI scores than men (p < 0.01). Diet adherence was better among managers than service-sales and technical staff (p < 0.01). PI scores were higher in medium stress than high stress individuals (p < 0.05) and in those with a higher BMI compared to a normal BMI (p < 0.01). Conclusions: Job stress influences both anthropometric parameters and dietary habits. Effective stress management may improve adherence to the Mediterranean diet and phytochemical intake. Workplace strategies supporting healthy eating behaviors are recommended.Article Citation - WoS: 2Citation - Scopus: 2Twenty-Year Course of Antifungal Resistance in Candida Albicans in Türkiye: A Systematic Review and Meta-Analysis(MDPI, 2025) Kilbas, Imdat; Kahraman Kilbas, Elmas Pinar; Horhat, Florin George; Ciftci, Ihsan HakkiThis study aimed to systematically evaluate the resistance rates of Candida albicans to various antifungals based on studies conducted in Turkiye and published between 2005 and 2025 and to analyze the factors contributing to resistance. A systematic literature search was conducted using various keywords in electronic databases (PubMed, Embase, Web of Science, EBSCO, Scopus, Turk Medline and Google Scholar). A total of 42 studies were included in the meta-analysis according to the determined criteria. The quality of the studies was assessed using the Joanna Briggs Institute checklist, and the analyses were performed using appropriate statistical software. The highest resistance rates for fluconazole, itraconazole, and voriconazole were observed in the Aegean and Marmara regions. In the analyses performed with the random-effects model, heterogeneity was found to be high for itraconazole, fluconazole, posaconazole, voriconazole, and caspofungin, and the strongest explanatory variable of this heterogeneity was the geographical region variable. In our study, we determined that antifungal resistance in C. albicans strains in Turkiye is generally low; however, an increasing trend has been observed over the years, especially in amphotericin B resistance. Although the low resistance rates to major antifungal agents such as fluconazole, voriconazole and echinocandins are promising, regional differences and methodological heterogeneity necessitate the development of treatment strategies based on local data.Article Evaluation of the Barriers to Maintenance 4.0 for the Textile Industry via Pythagorean Fuzzy SWARA(MDPI, 2025) Turan, Hakan; Buyukselcuk, Elif Caloglu; Çaloğlu Büyükselçuk, ElifMaintenance 4.0 studies have become a focus for managers and employees when developing effective and efficient maintenance policies. In this study, the barriers to Maintenance 4.0 applications in the textile industry are investigated, and these barriers are weighted using the Stepwise Weight Assessment Ratio Analysis (SWARA) method based on Pythagorean fuzzy numbers. Solutions to address these barriers are presented. As a result of this study, Organizational and Managerial emerged as the most important main criterion. Operational was identified as the second most significant main criterion, followed by Technical Competence. Data-Related and Cybersecurity ranked fourth in terms of importance. On the other hand, Human Resources and Training and Financial were found to be the least important main criteria. These two criteria received lower importance scores compared to the others, with Financial being the criterion with the lowest overall significance. Sensitivity analyses were performed for six different scenarios by changing the importance weights of the decision-makers. The ranking of the criteria only slightly changed with the weights; this means that the results obtained in Case 1 are robust and reliable. Even in Case 6, where the expert weight ratios were completely reversed, the results did not change significantly. This highlights an important point regarding the reliability of the assessment.Article Citation - WoS: 6Citation - Scopus: 8The Perceptions of Generation Z University Students About Their Futures: A Qualitative Study(MDPI, 2023) Dikec, Gul; Ozturk, Simge; Tasbasi, Neslihan; Figenergul, Damla; Guler, Bilal BugrahanThis study explored the future-oriented perceptions of Generation Z students in a foundation university. This study was conducted using qualitative research and a phenomenological design. The study sample consisted of 11 university students over the age of 18 who agreed to participate in the study. Data were collected online through individual interviews in Turkiye. Colaizzi's phenomenological analysis method was used in the data analysis. The content analysis determined three main themes and eleven sub-themes. The first theme was the students' knowledge acquisition about the "current situation of the country." Under this theme were four sub-themes: economic problems, the immigrant situation, the education and justice system, and the country's agenda. In the second theme, students shared their opinions about "being a student in the country." This theme included economic impossibilities, their participation in limited social activities, and housing problems. In the last theme, "future anxiety," the sub-themes of the students were found to include experiences hopelessness versus hope. Uncertainty caused anxiety, as did going abroad, finding a job, and improving themselves. It was determined that the participants were worried about the current situation in the countries they lived in during this period due to economic problems; while some were hopeful about the future, some were hopeless and would go abroad. This study might contribute to the literature on determining the future-oriented perceptions, possible stressors and hope levels of Generation Z university students in Turkiye. Additionally, intervention programs can be developed for the management these stressors to protect the mental health of Generation Z university students. On the other hand, it is necessary to protect the mental health of young people, who are the adults of the future, and to create policies for the youth of this country where social opportunities are maintained.