Erzincan University

The benefits that different technologies provide to the educational processes have been experienced by educators for years. The advantages hat teachers gain from computers, the internet, different software and technologies that change and develop every passing day have caused students to develop different skills and have also made it a necessity for teachers to be able to use these systems. As a result of these requirements, as a result of the studies of the Higher Education Council and the Ministry of National Education, which regulate higher education in Turkey, courses addressing technology education and the integration of technology into the course have been added to the process. This study aims to understand the technology-based meanings developed by teacher candidates taking the Instructional Technologies (IT) course. Within the scope of the study designed according to Husserl's phenomenology understanding, the study was conducted by 12 English Language Teaching undergraduate students and 3 researchers. It has been observed that the socio-cultural capital of the primary subjects of the study, English Language Teaching students, has shaped their lives along with their technological capital in the post-truth period. It has been seen that gods with high technology skills have created digital victims through digital world tools. It has been observed that people who were victims in the past can become resisters who engage in passive resistance against the digital world, while individuals who were not victims in the past but were aware of their victimization can become characters who actively resist the process.

The essential oil extracted from the aerial parts of Ferulago setifolia K. Koch was analysed using GC/MS, revealing 33 compounds, with 2,3,4‐trimethyl benzaldehyde (41.24%), α‐pinene (21.58%) and sabinene (10.46%) as major constituents. The biological activity profile of essential oils, including antifungal, insecticidal and antiproliferative activities, was documented for the first time. The oil demonstrated significant antifungal activity, completely inhibiting the growth of Verticillium dahliae at higher doses and showing dose‐dependent inhibition against Alternaria solani . It also exhibited moderate insecticidal activity against Rhyzopertha dominica and Tribolium confusum , achieving a mortality rate of up to 49.3% after 48 h at a 5% concentration. Furthermore, the essential oil showed potent antiproliferative effects against a wide range of cancer cell lines, including lung (Calu1), breast (MCF7), colon (HT29) and gynaecological (HeLa) cancers, while maintaining low cytotoxicity on normal cell lines (MRC5, FL). The IC 50 values ranged from 8.13 μg/mL (A2780) to 92.88 μg/mL (HT29), with notable results such as 22.84 μg/mL for Calu1 and 58.26 μg/mL for MCF7. Compared to the standard anticancer drug 5‐fluorouracil, the essential oil exhibited superior or comparable activity against certain cancer cell lines. The results showed that essential oils have specificity against cancer cell lines. These findings suggest that the essential oil of F. setifolia holds potential as a natural source for antifungal, insecticidal and antiproliferative agents. The results contribute significantly to the pharmacological and agricultural potential of this species.

In this study, machine learning (ML) algorithms were employed to predict analyte concentrations using sensing results and evaluate the anticancer effects of nanostructures. Multifunctional oolong tea extract-mediated silver nanoparticles (OTE-Ag NPs) were synthesized via a photo/ultrasound method and utilized in various applications, including a smartphone-based H2O2 sensor and electrochemical sensors for urea and fructose. Key features were extracted from electrochemical results, and feature importance analysis was used to select the most predictive features. The artificial neural network (ANN) model provided accurate predictions, particularly strong for urea (R² = 0.8575, RMSE = 0.4266, MAE = 0.3380). The study revealed the selective toxicity of OTE-Ag NPs to MCF-7 breast cancer cells through analyses of cytotoxicity, apoptosis, cell cycle phases, and CD44 surface marker expression using Annexin V/PI dye and flow cytometry. Experimental results demonstrated that OTE-Ag NPs suppressed MCF-7 cell proliferation while exhibiting lower cytotoxicity in normal HUVEC cells (46% cell death). OTE-Ag NPs arrested MCF-7 cells in the G2/M phase, induced apoptosis, and reduced CD44 expression, suggesting metastasis suppression. The CD44+/CD24- ratio decreased from 84.79% in control MCF-7 cells to 47.7% in OTE-Ag NP-treated cells. Overall, OTE-Ag NPs significantly inhibited MCF-7 cell proliferation through the apoptotic pathway by regulating the cell cycle in the G2/M phase.

The increasing world population has also increased the demand for vehicles and brought along various problems such as traffic delays, accidents, and air pollution. In addition, the increase in the number of vehicles causes an increase in the time spent at intersections, negatively affecting people’s quality of life, distracting drivers, and unsafe driving practices. Moreover, greenhouse gas emissions, including CO2 and NOx from vehicles, cause climate change and deterioration of air quality. To solve these problems, in this study, seven signalized intersections on a corridor in the city center of Erzincan province were examined. Using the Aimsun traffic simulation program, factors such as CO2, VOC, NOx emissions, queue length, delay time, travel time, and speed were evaluated. Using one of the multiple criteria decision methods, the TOPSIS method, the ideal scenario was determined based on the simulation results, considering the construction costs. The study revealed significant improvements in several parameters. CO2 emissions were reduced by 10%, delay time by 35%, VOC emissions by 14%, NOx emissions by 13%, queue length by 35%, delay by 38%, and travel by 19%. Furthermore, the speed was increased by 15%.

The aim of this study was to determine the secondary metabolites of the n ‐hexane, ethyl acetate, methanol, and water extracts of Achillea sintenisii Hub. Mor. and to ascertain their divergent biological properties. LC–MS/MS analysis was performed to identify the bioactive compounds. The anticancer properties of the samples were tested against human breast (MCF‐7 and MDA‐MB‐453) and colon (HT‐29) cancer cell lines by XTT assay. The anti‐Alzheimer's studies were performed using Ellman's assay. The antimicrobial studies were carried out by Kirby–Bauer disc diffusion method. The antioxidative potential of the samples was evaluated on the basis of 2,2‐diphenyl‐1‐picrylhydrazyl scavenging and ferric reducing antioxidant power assays, LC–MS/MS analysis revealed 27 phytochemicals, including high concentrations of quinic acid, gentisic acid, chlorogenic acid, luteolin, cynaroside, and caffeic acid. Ethyl acetate extract exhibited the most potent cytoxicity against MDA‐MB‐453 cells, with an IC 50 value of 83.05 µg/mL. All extracts showed stronger inhibitory activity against acetylcholinesterase and butyrylcholinesterase compared to tacrine. The n ‐hexane, ethyl acetate, and methanol extracts exhibited considerable antimicrobial activity against Enterococcus faecalis , approaching the level of vancomycin. Methanol extract possessed the highest DPPH scavenging and ferric reducing antioxidant power. These findings render A, sintenisii a promising source for the pharmaceutical, cosmetic, and food industries.

Artificial intelligence (AI) is significantly shaping education and currently influencing pre‐service teachers' academic and professional journeys. To explore this influence, the present study examines 389 Generation Z pre‐service teachers' attitudes towards AI and its impact on educational decision‐making at two state universities, using an explanatory sequential mixed‐methods research design. Quantitative data were collected through the General Attitudes to Artificial Intelligence Scale (GAAIS) and an AI decision‐making survey. It was followed by qualitative data gathered via semi‐structured interviews to enrich the statistical trends with deeper thematic insights. SPSS was used for quantitative data analysis while MAXQDA was employed for a systematic analysis of the qualitative data. The analysis revealed that female pre‐service teachers held more positive attitudes towards AI, with higher levels of AI knowledge contributing to these attitudes. Negative attitudes, however, were independent of gender, academic discipline or AI familiarity. Findings also reveal that AI tools, particularly ChatGPT, are primarily used as advisors, and pre‐service teachers often adapt AI's suggestions to their preferences. AI is predominantly preferred for assignments, reports, projects and presentations. In AI acceptance, time and effort savings, innovative suggestions and unbiased recommendations are stated as key factors. However, there are ongoing trust concerns highlighting the necessity of keeping final decisions under human control. Based on these findings, comprehensive AI training for teachers and students in higher education is suggested.

The distribution of the neutral component of genetic diversity is the interplay of historical and ongoing processes resulting in the species-specific genetic structure of populations, which can, however, be disrupted by interspecific hybridisation and introgression. In this study, we focused on two species of water frogs, Pelophylax epeiroticus and P. kurtmuelleri, which live in sympatry in the southwestern Balkans, to investigate the rate of hybridisation and population genetic structure using cytogenetic, mitochondrial (ND2) and nuclear DNA (microsatellite) markers. The overall hybridisation rate was 2.6%, with rates reaching up to 10% at specific sites. The course of gametogenesis and the occurrence of later generations of hybrids (beyond the F1 generation) indicate a sexual mode of hybrid reproduction. The bimodal structure of hybrid populations and the rarity of hybrids suggest substantial reproductive isolation between the two species; however, this isolation is unlikely attributable to differences in ecological niche occupation. In P. epeiroticus, sequence variation in the ND2 gene revealed two divergent lineages with a clear geographic pattern that corresponds

Chloroplast genome analysis provides crucial insights into plant evolution, classification, and conservation strategies. This study aimed to conduct a comprehensive comparative analysis of chloroplast genome architecture, gene content, and evolutionary relationships among five species of Lamiaceae (Lavandula angustifolia, Mentha × piperita, Ocimum × africanum, Salvia japonica, and Thymus serpyllum). Complete chloroplast genome sequences were retrieved from the NCBI database and analyzed using a systematic bioinformatics pipeline. Genome annotation was performed using Geneious Prime software, while repetitive sequence analysis was conducted using Tandem Repeats Finder. Phylogenetic relationships were reconstructed using MEGA software, implementing both the DualBrothers model and Neighbor-Joining method. The analyzed genomes exhibited the characteristic quadripartite structure, with sizes ranging from 152,048 to 153,995 base pairs and GC content between 37.8 and 38.0%. Each genome contained 131–134 genes, including 50 protein-coding sequences, 8 rRNA genes, and 37 tRNA genes. Comparative analysis revealed region-specific GC content variations, with IR regions showing the highest (43.0–43.4%), followed by LSC (35.9–36.2%) and SSC regions (31.6–32.1%). Codon usage analysis demonstrated a significant bias toward T/C-ending codons, particularly TTT, AAA, and AAT, correlating with the high AT content. Notable variations were observed at the LSC/IR/SSC junction regions, attributed to IR expansion and contraction. Molecular clock analyses indicated consistent evolutionary rates across the studied species. These findings provide valuable insights into the molecular evolution of Lamiaceae chloroplast genomes and establish a foundation for future research in plant molecular biology, systematic studies, and conservation efforts.

Objective The main objective of this study is to investigate the level of disaster preparedness and associated socio-demographic characteristics of Meskhetian Turks as a marginalized population who migrated to Erzincan, Turkey due to war and conflict. Methods A total of 426 individuals between the ages of 18-65 participated in this study. Data were collected through face-to-face interview technique by utilizing the General Disaster Preparedness Belief Scale. The t test and one-way ANOVA test and multiple regression analysis (Enter model) were used to analyze the data. Results The total scale scores of the participants ranged between 80-138, with a mean score of 105.43±10.88. It was determined that the disaster preparedness levels of those who were between 32-38 years of age, who had bachelor’s degree, who had disaster experience, and who received disaster training were higher. It was determined that there was a significant positive relationship between the disaster preparedness levels of the participants and age, education level, and disaster training. Conclusions Disaster preparedness levels of Meskhetian Turks were determined to be high. According to the results of the analyses, it was revealed that age, education level, and disaster training variables have a positive and significant effect on the level of disaster preparedness.

Introduction Laurus nobilis (LN), has traditional medicinal uses, and this study investigates its therapeutic potential by focusing on its phenolic content and bioactivities such as antioxidant, antidiabetic, and anticholinergic properties. Phenolic compounds play key roles in reducing oxidative stress and modulating enzymatic activities, relevant to metabolic and neurodegenerative disorders. Methods LN leaf extracts were prepared via ethanol maceration, followed by filtration and concentration. Phenolic content was analyzed using LC-MS/MS. Antioxidant activity was assessed through ferric thiocyanate, DPPH, ABTS, and FRAP assays. Enzyme inhibition assays targeted AChE, BChE, and α-GLY, with IC50 values from dose-response curves. In silico analyses were conducted using molecular docking techniques to predict the binding mechanisms of identified phenolic compounds with the active sites of target enzymes, evaluating binding affinities and interaction profiles. Results Vanillic acid and catechin hydrate were the most abundant phenolics. LN extract showed strong lipid peroxidation inhibition (50.53%) compared to Trolox (28.33%) and α-tocopherol (37.79%). Moderate radical scavenging and metal reduction potentials were observed. IC50 values were 2.57 µg/L for AChE, 3.78 µg/L for BChE, and 4.65 µg/L for α-GLY, indicating notable bioactivity. In silico studies confirmed strong binding affinities of phenolics to target enzymes. Discussion LN extracts demonstrated promising antioxidant, antidiabetic, and anticholinergic activities, attributed to high phenolic content. Enzyme inhibition results suggest potential in managing metabolic and neurodegenerative disorders. In silico findings support these bioactivities, highlighting LN’s therapeutic potential.

AIM: To investigate the effects of adenosine triphosphate (ATP) and melatonin, which have antioxidant and anti-inflammatory activities, on potential 5-fluorouracil (5-FU)-induced optic nerve damage in rats. METHODS: Twenty-four rats were categorized into four groups of six rats: healthy (HG), 5-FU (FUG), ATP+5-FU (AFU), and melatonin+5-FU (MFU). ATP (4 mg/kg) and melatonin (10 mg/kg) were administered intraperitoneally and orally, respectively. One hour after ATP and melatonin administration, rats in the AFU, MFU, and FUG were intraperitoneally injected with 5-FU (100 mg/kg). ATP and melatonin were administered once daily for 10d. 5-FU was administered at a single dose on days 1, 3, and 5 of the experiment. After 10d, the rats were euthanized and optic nerve tissues were extracted. Optic nerve tissues were biochemically and histopathologically examined. RESULTS: ATP and melatonin treatments inhibited the increase in malondialdehyde (MDA) and interleukin-6 (IL-6) levels, which were elevated in the FUG. The treatments also prevented the decrease in total glutathione (tGSH) levels and the superoxide dismutase (SOD) and catalase (CAT) activities (P<0.001). This inhibition was higher in the ATP group than in the melatonin group (P<0.001). ATP prevented histopathological damage better than melatonin (P<0.05). CONCLUSION: ATP and melatonin have the potential to be used in alleviating 5-FU-induced optic nerve damage. In addition, ATP treatment shows better protective effects than melatonin.

This study compares the performance of various models in predicting monthly maximum and average temperatures across three distinct regions: Samsun, Amasya, and Çorum. The evaluated models include Artificial Neural Network (ANN), Shuffled Frog Leaping Algorithm coupled with ANN (SFLA-ANN), Firefly Algorithm coupled with ANN (FFA-ANN), and Genetic Algorithm coupled with ANN (GA-ANN). In setting up the models, the dataset was divided into 70% for training and 30% for testing, and the outputs of the models were evaluated using various graphical and statistical indicators. The model with the smallest root mean square error (RMSE) value was selected for the maximum and average temperature predictions. Accordingly, for maximum and average temperature predictions, SFLA-ANN (RMSE of 2.93) and GA-ANN (RMSE of 3.55) in Samsun, GA-ANN (RMSE of 2.91) and GA-ANN (RMSE of 2.50) in Amasya and GA-ANN (RMSE of 2.97) and GA-ANN (RMSE of 2.50) in Çorum performed better than the other models, respectively. In addition, for the maximum temperature prediction with the highest accuracy, the R² value of the SFLA-ANN model in Samsun was 0.89. In contrast, the R² values of the GA-ANN model in Amasya and Çorum were determined as 0.91 and 0.91, respectively. Similarly, it was observed that the R² values of the GA-ANN model for the average temperature prediction with the highest accuracy at Samsun, Amasya and Çorum stations were 0.78, 0.92 and 0.92, respectively. Overall, the GA-ANN consistently demonstrated superior performance in predicting both maximum and average temperatures across all three regions, as evidenced by its consistently low RMSE values. These findings provide valuable insights into selecting effective models for temperature prediction tasks in different geographical regions.

The dual-functional nanostructures show great promise for biomedical applications, exhibiting selective cytotoxicity against cancer cells while also serving as a crucial component in textile screen-printing for smart materials. In this study, we successfully synthesized polyethylene glycol-hibiscus extract copper (II) oxide nanoparticles (PEG/HS/CuO NPs) using a simple one-step sonosynthesis method that leverages ultrasonic irradiation. Comprehensive characterization of the synthesized PEG/HS/CuO NPs was performed using transmission electron microscopy (TEM), X-ray diffraction (XRD), scanning electron microscopy (SEM) coupled with energy-dispersive X-ray (EDX) analysis, and Fourier-transform infrared spectroscopy (FTIR). The incorporation of PEG/HS/CuO NPs into guar gum photochromic solution (GP) caused a significant color change after 6 ± 1 min of UV light exposure and resulted in visible coloration on cellulose-based textiles after screen printing, providing an alternative strategy for smart fabrics. Moreover, cytotoxicity experiments demonstrated the selective toxicity of green PEG/HS/CuO NPs against cancer cells. In this study, the human colon cancer cell line HCT116, breast cancer cell line MCF-7, and normal HUVEC cells were examined. PEG/HS/CuO NPs NPs induced apoptosis, cell cycle arrest, and down-regulation of CD44 antibody expression in MCF-7 cells, highlighting their potential as effective chemotherapy agents.

Bee venom is secreted by a gland in the abdominal cavity of bees. The venom, especially that of honeybees, contains certain enzymes and peptides that, when administered in high doses, are effective against various diseases. Peptides such as melittin and phospholipase A2 can target various cancer cells. In this study, we investigated the antiproliferative effects of administering low-dose bee venom in K-562 chronic myeloid leukaemia cells. Our proteomic study revealed regional variation of the content of bee venom and high levels of melittin, apamin and secapin, as well as phospholipase A2 and hyaluronidase. In addition, eight new, previously unidentified proteins were identified. The effects of bee venom on cell viability and drug–cell interaction were investigated at 24, 48 and 72 h. According to the MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide) results, the bee venom decreased K-562 cell viability dose-dependently at all time points. Cell viability decreased 48 and 72 h after bee venom administration but increased in the control group left untreated for 72 h. The inhibition percentages for the highest bee venom concentration (0.4 µM) at 24, 48 and 72 h were 55%, 80% and 92%, respectively. The cell–drug interactions indicated that the cell surfaces, which were smooth and clear before drug application, gradually deteriorated and started to shrink after the application. In conclusion, at increasing doses, bee venom was found to have a strong antiproliferative effect in K-562 chronic myeloid leukaemia cell lines.

Purpose The aim of this study was to construct an osteological map of the morphological projection of the coracoclavicular ligament on the clavicle. Methods In this study, 93 dry clavicles without age and sex records were used. The attachment sites of the trapezoid and conoid ligaments were examined structurally and formally. Results The attachment sites of the trapezoid ligament were triangular in 9 clavicles, ellipsoidal in 18 clavicles and trapezoidal in 62 clavicles. The anatomical structures of the attachment sites of the trapezoid ligament were as follows: 57 were tuberosities, 12 were tubercles, 11 were lines, and 9 were fovea. The attachments of the conoid ligament on the clavicle were low in 23 clavicles, moderate in 37 clavicles and high in 29 clavicles. The anatomical structure of the attachment sites of the conoid ligament was as follows: 50 were tubercles, 20 were tuberosities, 8 were adhesions, 6 were crests, 3 were impressions, and 2 were spines. The attachments of the conoid ligament on the clavicle were low in 20 clavicles, moderate in 50 clavicles, and high in 19 clavicles. The prevalence of the coracoclavicular joint was 6% in this study. Conclusion In conclusion, we believe that this study provides guidance for clinicians by revealing the osteological traces of the components of the coracoclavicular ligament or the coracoclavicular joint on the clavicle.

The enzyme-linked immunosorbent assay (ELISA) detects antigen-antibody interactions by using enzyme-labelled conjugates and enzyme substrates that generate colour changes. This review aims to provide an overview of ELISA, its various types, and its applications in detecting metabolites in biological fluids. The article discusses the history of the assay, its underlying principles and procedures, common ELISA protocols, and the most accurate and reliable techniques for measuring peptide molecules in biological fluids. Additionally, we emphasize best laboratory practices to achieve consistent, high-quality results and outline the essential materials for setting up an ELISA laboratory, drawing from our over 30 years of experience in the field.