Bülent Ecevit University

Background To assess the role of inflammation in the pathogenesis of idiopathic epiretinal membrane (iERM) by evaluating blood-count-derived inflammatory marker levels. Methods The medical records of patients diagnosed with iERM and cataract patients with normal fundus examinations were analyzed retrospectively. Levels of neutrophils, monocytes, lymphocytes, and thrombocytes were obtained from blood samples. Systemic inflammatory markers, including neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and systemic inflammatory response index (SIRI) were calculated and compared between the two groups. The receiver operating characteristic curve (ROC) analysis was performed to determine the best cutoff value of NLR, PLR, SII, and SIRI in iERM. Results In total, 91 iERM cases and 95 controls were included in the study. iERM patients had significantly higher NLR (2.25 vs. 1.91, p = 0.003), PLR (117.22 vs. 113.33, p = 0.042), SII (529.45 vs. 472.57, p = 0.003), and SIRI (1.25 vs. 0.90, p < 0.001). The area under the curve of NLR, PLR, SII, and SIRI in differentiating patients with iERM and controls was 0.637, 0.608, 0.645 and 0.660, respectively, according to ROC analysis. The best cutoff values (with sensitivity and specificity) were 1.95 (60.4% and 52.6%) for NLR, 116.7 (54.9% and 55.7%) for PLR, 498.03 (58.2% and 58.9%) for SII, and 1.07 (62.6% and 64.6%) for SIRI.No significant differences in inflammatory markers were found across iERM stages. Conclusion Patients with iERM exhibit higher levels of blood-count-derived inflammatory markers, suggesting a link between systemic subclinical inflammation and iERM development. However, these markers do not correlate with iERM severity. Further research with larger cohorts and broader inflammatory marker analysis is needed to elucidate the role of systemic inflammation in iERM pathogenesis.

Human life is extremely valuable in any circumstance. In this regard, both physical and mental health are crucial. The way in which an individual perceives himself and the circumstances he finds himself in can provide insight into his mental well-being. A person’s life may be complicated by elements such as self-hatred, entrapment, and an inability to control one’s emotions. Nevertheless, cultivating mindfulness and attaining a state of elevated well-being serve as favorable prognostic factors for an individual’s psychological health. In the present study, an investigation was conducted into the associations between the concepts of self-hatred and entrapment and mental well-being, difficulties in emotion regulation, and mindfulness. For the first time, the relationships between these variables were analyzed. The study included 346 university students, 216 of whom were female and 76 of whom were male. In order to analyze the mediation dimension, structural equation modeling (SEM) was implemented. The results of the study indicated that mental health, difficulty regulating emotions, and mindfulness all played a partial mediating role between self-hatred and entrapment. There is a potential for individuals who despise themselves to possess mindfulness yet struggle with emotion regulation and mental health issues, which could contribute to a sense of confinement.

Purpose/objectives The objective of this study was to assess the empathy levels of dental students during their clinical practice training in pediatric dentistry and to evaluate various factors that influence changes in these empathy levels. Methods The study evaluated the empathy levels of a total of 350 students (70 third‐year, 140 fourth‐year, and 140 fifth‐year dental students) who received pediatric dentistry clinical practice training and/or observation between October 2022 and December 2023. The Jefferson Scale of Physician Empathy‐Student Version was used to assess empathy levels before and after the training. The data were subjected to statistical analysis using the Mann‐Whitney U test, Kruskal‐Wallis test, Wilcoxon test, and Dunn Test ( p < 0.05). Results The response rate of the participants was 92.10%. The highest empathy level was observed in third‐year students, while the lowest empathy level was observed in fifth‐year students. A statistically significant relationship was found between these two variables ( p < 0.001). Additionally, the empathy level of female students was statistically significantly higher than that of male students ( p < 0.001). Following the completion of the pediatric dentistry training, a statistically significant increase was observed in the empathy levels of the students in comparison to the baseline ( p < 0.001). Conclusion Empathy levels in students are found to be correlated with academic year, sibling count, and gender. It is of paramount importance to enhance empathy skills through training in order to foster the development of human‐oriented physicians capable of effective patient communication.

Obesity diagnosis using biomedical signals has received increasing attention in recent years and requires advanced signal processing techniques in order to accurately classify obesity. In this context, this study proposes an intelligent diagnostic system for obesity classification using flash electroretinogram (fERG) signals, with a specific focus on cone responses. A novel feature extraction method based on Wavelet Packet Decomposition (WPD) is employed to decompose the cone responses into high- and low-frequency components, enabling detailed time–frequency analysis with high resolution. Subsequently, statistical features, such as mean, standard deviation, skewness, and kurtosis, are extracted from the decomposed signals and refined to enhance the training of artificial neural networks (ANNs). To optimize model performance, Particle Swarm Optimization (PSO) is integrated with ANN, resulting in an ANN–PSO hybrid model. The experimental dataset, comprising fERG signals from 47 subjects across diverse obesity categories, was utilized to evaluate the proposed hybrid model. The ANN–PSO model demonstrated high classification performance, achieving average accuracies of $95.74\%$ and $96.60\%$ for right and left eye signals, respectively, outperforming traditional ANN models. These findings highlight the effectiveness of WPD in capturing intricate signal characteristics relevant to obesity levels and confirm the potential of the ANN–PSO model as a robust, efficient, and reliable diagnostic tool for clinical applications beyond conventional BMI assessments.

Obesity is a critical global health challenge, characterized by its complex etiology and association with numerous chronic diseases. Leveraging machine learning (ML) techniques offers promising avenues for improving obesity classification and risk prediction. This study aims to evaluate the efficacy of various ML algorithms, including Decision Trees (DT), Extra Trees Classifier (ETC), Multilayer Perceptron (MLP), Random Forest (RF), and Support Vector Machines (SVM), combined with diverse sampling techniques to address class imbalance. The research utilizes the publicly available Obesity Dataset, encompassing demographic and lifestyle variables. A stratified k-fold cross-validation approach was employed for robust model evaluation, and data balancing methods such as SMOTE and SVMSMOTE were implemented to enhance classification performance. Among the evaluated models, ETC demonstrated the highest accuracy (91.93%) and AUC (97.99%) when paired with SMOTE, underscoring its potential for scalable and precise obesity classification. These findings highlight the importance of integrating advanced ML methods and sampling strategies to tackle class imbalance. In addition, this study provides an important basis for the development of more effective decision-support systems in public health and clinical applications and paves the way for innovative approaches in the fight against obesity.

Objective The present study aimed to design and synthesize a new series of benzothiazole analogues containing 1,3,4-thiadiazole, and assess their biological activities as potential anticancer agents. Methods N-(5,6-dimethylbenzo[d]thiazol-2-yl)-2-((5-(substituted amino)-1,3,4-thiadiazol-2-yl)thio)acetamide derivatives (4a-4h) were synthesized via the reaction of thiadiazole derivatives (3a-3h) with 2-chloro-N-(5,6- dimethylbenzo[d]thiazol-2-yl)acetamide (1) in the presence of potassium carbonate. All the target compounds have been characterized by spectral analysis. The anticancer activities of compounds 4a-4h were tested against two human HT-1376 bladder and HT-29 colorectal carcinoma cells using the WST-1 assay. Flow cytometry was used for the determination of apoptosis, cell cycle, and caspase 3/7 activity. Moreover, wound-healing assay was utilized to evaluate cell migration. In silico physicochemical, pharmacokinetics, and toxicological properties of compound 4g were determined by pkCSM, SwissADME, and SwissTargetPrediction online web tools. Results Among all synthesized derivatives, compound 4g (N-(5,6-dimethylbenzo[d]thiazol-2-yl)-2-((5-((3- methoxyphenyl)amino)-1,3,4-thiadiazol-2-yl)thio)acetamide) recorded the highest antiproliferative activity against HT-1376 cells with an IC50 as 26.51 μM at 24 h, which was less cytotoxic than cisplatin (IC50=14.85 μM). The combined treatment with compound 4g and cisplatin increased the cellular apoptosis with a higher impact compared with the cisplatin group. The higher accumulation of cells in the G2 phase, a significant increase of caspase 3/7 activity, and the inhibition of migration rate were also observed in HT-1376 following a combination of compound 4g and cisplatin treatment versus cisplatin alone, which might be involved in the apoptotic effects of compound 4g. Conclusion The in vitro anticancer potential of compound 4g lays the foundation for future research to focus on its value as a novel and advanced cancer therapy.

This study examines the inviolable and admonitory norms for graduate teaching and mentorship in the Turkish higher education sector. Research data were gathered using a quantitative survey from 633 graduate students at 100 public and foundation higher education institutions (HEIs) in Turkey. The Graduate Teaching and Mentoring Behaviors Inventory by Braxton et al. (Professors behaving badly: Faculty misconduct in graduate education, 2011) was used to evaluate normative behaviors. These actions were distributed and gathered under inviolable and admonitory norms by taking into account the severity of the sanction. Graduate students appear to place greater value on inviolable norms, according to the results of descriptive and inferential statistics. Additionally, the participants place more importance on the admonitory norms of mentoring and advising than they do on instructional techniques. The findings of the study suggest that significant differences do exist between graduate students’ perceptions of normative behaviors linked to mentoring and teaching by their gender, academic discipline, and occupational status, but not by the university type. Some implications are offered in the paper’s conclusion.

Ambrosia artemisiifolia L., or short ragweed, is an invasive species known for its highly allergenic pollen and impact on agriculture. Native to North America, it has spread to northern Türkiye, with models suggesting pollen influx through the Black Sea region. This study had several objectives: (1) to investigate the dynamics and origin of Ambrosia pollen and Amb a 1 allergen emissions in Ankara, a Central Anatolian city with 6 million residents; (2) to examine the effects of meteorological factors on pollen and allergen emissions; (3) to determine the duration of possible risky days for Ambrosia allergy; and (4) to determine the localization of Amb a 1 allergens within the pollen structure using immunolabeling with transmission electron microscopy (TEM). Daily pollen concentrations were obtained using a Burkard spore trap, and Amb a 1 allergen concentrations were measured using a BGI900 high-volume air sampler. Filters capturing PM>10 and PM10>2.5 fractions were analyzed via sandwich ELISA. Seasonal Ambrosia pollen indices were 189 in 2015 and 21 in 2016, with allergen concentrations peaking on August 29, 2015 (1620 pg/m³) and August 17, 2016 (201 pg/m³), primarily in PM>10 fractions. Backward trajectory analysis (HYSPLIT) identified air masses from Ukraine, Crimea and Russia as probable sources, with higher pollen levels linked to northeast and east winds. This is the first study to detail Amb a 1 allergen localization in ragweed pollen. Immunolabeling localized allergens in the pollen wall (columella, cavea and intine) and ribosome-rich cytoplasmic areas, with no labeling observed in starch grains.

The study presents seasonal changes in nitrosamine concentrations in inhalable particulate matter (PM10) collected from the atmosphere of Zonguldak, Turkey, during heating and non-heating periods, possible source apportionment, and risk assessment of human health. The daily collected PM2.5 and PM2.5–10 samples were analyzed for nitrosodimethylamine, nitrosomethylethylamine, nitrosodiethylamine, nitrosopyrrolidine, nitrosodipropylamine, nitrosomorpholine, nitrosoethylbutylamine, nitrosopiperidine, mono-nitrosopiperazine, di-nitrosopiperazine, nitrosodibutylamine, and nitrosodiphenylamine by gas chromatography–mass spectrometry (GC–MS). The mean concentrations of total nitrosamines in PM10 were found to be 19.04 ng/m³ in summer, 113.67 ng/m³ in winter, and 98.88 ng/m³ annually, with a peak of 253.56 ng/m³ occurring in winter. The source apportionment of the analyzed data was conducted using principal component analysis, resulting in two primary factors: “Coal-Fuel Oil Combustion-Cooking” and “Traffic Emissions-Secondary Atmospheric Reaction-Landfill.” These two factors collectively accounted for 82.944% of the total variance. In order to evaluate the health risks associated with the inhalation of mutagenic and carcinogenic nitrosamines present in airborne PM10, cumulative lifetime cancer risks (LCR) were calculated for different age groups based on exposure time (ET) using annual mean concentrations. The average cumulative lifetime cancer risks, represented as the number of additional cancer cases per million exposed population, were in the range of 1.57–12.57 for the 0– < 1 age group, 4.18–33.52 for the 1– < 6 age group, 5.48–43.96 for the 6– < 21 age group, and 7.70–61.61 for the 21 < 70 age group. The estimated average cumulative lifetime cancer risks from inhalation exposure to nitrosamines in urban PM10 exceed the US Environmental Protection Agency’s guideline for a negligible risk level of 1 excess cancer case per 1 million exposed individuals across all age groups. LCRs exceed the maximum acceptable value of 10 at different exposure times in all age groups but do not exceed the intolerable value of 100 in any age group.

Background Exercise ECG testing is a widely used, noninvasive tool for detecting obstructive coronary artery disease (OCAD). However, its diagnostic performance is often limited by low specificity, leading to false-positive results and unnecessary invasive procedures. Objective This study aims to assess the potential of combining the Selvester QRS score with exercise ECG to enhance diagnostic specificity for OCAD in patients with suspected stable angina. Methods This retrospective study included 203 patients who presented with chest pain, underwent exercise ECG and were assessed for OCAD by coronary angiography or computed tomography angiography. Receiver operating characteristic analysis identified the optimal Selvester QRS score cutoff and assessed the diagnostic performance of exercise ECG and the combined model. Multivariable logistic regression was performed in the exercise ECG positive and negative groups. Results Of the 203 patients, 116 were diagnosed with OCAD. The optimal Selvester QRS score cutoff was ≥3, with a sensitivity of 83.6% and a specificity of 93.1%. The combination of a positive exercise ECG and a Selvester QRS score ≥3 achieved the highest specificity (98.9%). Regression analyses showed that Selvester QRS score ≥3 was an independent predictor of OCAD, even in patients with negative exercise ECG results (adjusted odds ratio: 7.018; P < 0.001). Conclusion The Selvester QRS score can improve the specificity of the exercise ECG in detecting OCAD in patients with suspected stable angina. This approach has the potential to reduce false positives and unnecessary invasive procedures by improving risk stratification.

Due to its nutritional qualities, donkey milk is a newly popular food. Because it has a high added value, it may be adulterated with using cheaper milks, like cow milk. This study has investigated a rapid method for the authentication of pure donkey milk using Raman and FTIR‐ATR spectroscopy and comparison of the methods. Three preprocessing methods were applied to the spectra. The results show that donkey milk has lower fat and protein content compared with cow milk. Notably, Raman spectroscopy successfully distinguishes donkey and cow milk according to the presence and absence of β‐carotene. Principal component analysis demonstrated a distinct separation between cow, adulterated donkey, and donkey. The variance value of 90.30% (PC1 = 72.76, PC2 = 17.53) is obtained from the first and second PCs for Raman data, and the variance value of 89.67% (PC1 = 65.25, PC2 = 24.41) is obtained from the first and second PCs for FTIR data. The Raman data could be used to separate donkey and cow milks, whereas the FTIR data were insufficient. It was observed that adulterated species could be separated between classes with Raman and FTIR. In the FTIR spectrum, there is a broad peak due to water, which accounts for about 87% of the milk composition, but this water peak is not included in the Raman spectrum. The results demonstrate the potential of Raman spectroscopy as a rapid and reliable method and suggest that it can be used as a nondestructive analytical tool for adulteration detection in donkey milk.

Polyurethane foams are frequently used to provide thermal insulation. Thanks to the blowing agents used during their synthesis, pores are created in the structure and thermal insulation is achieved through these pores. In this study, five different insulating polyurethane foam samples containing water and cyclohexane blowing agents were synthesized. Pore stabilities and their effects on pore neighboring were analyzed computationally (MP2/aug-cc-pVDZ). A digital image processing- and machine learning-based algorithm was developed to predict the mean neighboring effect distances of the produced foams. It was created using the Voronoi tessellation method used for the identification problems in industrial applications. This method showed that there was a close relationship between the calculated Voronoi neighboring effect distances of the samples and their thermal conductivity coefficients. Considering the Voronoi neighboring effect distances proposed in this study, the thermal conductivity coefficient of similar polyurethane foams could be predicted. This method required only a standard mobile phone to capture images of the samples and the algorithm developed using Python (version 3.13.2) programming language. In addition, when compared to the local surface imaging device SEM, it allowed the entire surface to be analyzed faster and at once, without any surface deterioration.

Autonomous electric vehicles use high-performance batteries to power their core systems. However, short battery lifespan remains a significant challenge, affecting the efficiency and sustainability of these vehicles. This article reviews the reasons behind the limited battery lifespan and proposes solutions to mitigate these issues. We will also discuss recent research and innovations aimed at improving battery lifespan. New proposals such as using nanomaterial-based electrolytes, continuous wireless charging, and AI-powered energy management systems will be introduced and explained in detail. The article includes comparative tables, equations, and charts to demonstrate the effectiveness of these solutions.

Objectives Color stability is crucial to the esthetic success of restorative materials. Internal and external factors affect the coloring of these materials. Research carried out on the development of restorative materials draws attention to the advantages of methods such as preheating resins, reducing the viscosity and light cure time, increasing the marginal adaptation, and increasing the degree of monomer conversion. The aim of this study was to examine the in vitro effects of preheating polyacid-modified composite resins (PMCRs) on their color values and evaluate the obtained findings comparatively. Materials and Methods: Four main groups were formed by preparing discs from A2-colored PMCR material, which were kept at four different temperatures (4°C, 23°C, 39°C, and 55°C) before polymerization. The colors of the discs were measured according to the Commission on Illumination Laboratory system before and after they were kept in distilled water for 24 hours. The data were statistically analyzed using IBM Statistical Package for the Social Sciences V3. Results It was seen that the preheating treatment did not significantly affect the color sensation (∆E) and red-green (∆a) color values of the PMCRs. It was determined that this process was effective on the lightness (∆L) and blue-yellow (∆b) color values of the materials. Conclusion It should be considered that preheating applied to PMCRs may be beneficial for the longevity of the color stability of restorations, but different oral hygiene and dietary habits may have different effects on PMCRs.

Purpose Studies investigating hyperostosis frontalis interna (HFI) in acromegaly are limited. We aimed to investigate HFI and the association of disease control with frontal bone thickness (FBT) in acromegaly. Methods Adult patients with acromegaly were grouped according to the presence of HFI on the baseline MRI: Group 1 absent, Group 2 present. We measured FBT, parietal bone thickness (PBT) and occipital bone thickness (OBT) in the mid-sagittal plane on MRI. The changes between first and last measurements were analyzed. We grouped the patients as controlled vs. uncontrolled acromegaly, and as established disease control for at least 5-year vs. 1-5-years. Results Group 1/Group 2 comprised of 23/29 patients, female/male ratio was 34/18, and mean age 55.41(± 14.21) years. Median follow-up duration was 108 months (6-408). FBTfirst (p = 0.001), FBTlast (p < 0.001), PBTlast (p = 0.025), and OBTlast (p = 0.028) were higher in Group 2 than in Group 1. FBTchange, PBTchange, and OBTchange were positive in Group 2 (p < 0.001, p = 0.008, and p = 0.008; respectively). The ratio of patients with FBT(increased) was higher in Group 2 than in Group 1 (p = 0.001). FBTfirst, FBTlast, PBTfirst, PBTlast, OBTfirst, OBTlast, FBTchange, PBTchange and OBTchange were similar in controlled or uncontrolled acromegaly groups. FBTchange and OBTchange were positive in patients with disease control established for at least 5 years (n = 30) (p = 0.027 and p = 0.002, respectively). Conclusion HFI was common in patients with acromegaly. HFI is associated with a continuous increase in FBT, PBT and OBT. HFI, bone thickness, or increase in bone thickness seems independent of disease activity. Since headaches can be related to an increase in bone thickness, patients should be evaluated and graded during baseline imaging.

Nanoimaging, crucial in endodontics, has advanced, leading to more effective and less invasive treatments. Nano-computed tomography (nano-CT) is an advanced imaging technique to evaluate bone structures or gaps in filling materials, providing submicrometer spatial resolution due to smaller focal points and voxels, higher signal-to-noise ratios, and higher tube voltages and powers compared to conventional devices, improving dental imaging precision and safety by producing detailed images with minimal radiation exposure. This study conducted a bibliometric analysis on nano-CT imaging as a nano identification tool in endodontics. Using various tools and methods, it evaluated progress and trends in nano-CT, aiming to enhance understanding of bibliometric data and complement existing endodontic knowledge. Nano-CT imaging has gained prominence in endodontics research, offering potential applications and insights into various aspects of the field. A review of relevant studies highlighted the technique's ability to visualize dentin tubules, root canal anatomy, filling quality, root resorp-tion, cracks, microcracks, soft dental tissues, cellular layers, volumetric changes post-instrumentation, hard tissue debris, root surface deposits, and bioceramic pore structures. Nano-CT has the potential to become the gold standard for imaging in endodontics, presenting opportunities and challenges for future research. These findings provide researchers and practitioners with the latest advancements in nanoimaging.

In the study conducted for the cooling systems of MALE class unmanned aerial vehicles using internal combustion engines, new type radiators were designed using spring-structure fins. Among the radiators formed with spring structures acting as fins, the radiator developed using springs with a pitch of 2.25 mm was named Radiator-Y1, the radiator developed using springs with a pitch of 4.25 mm was named Radiator-Y2, and the radiator developed using springs with a pitch of 8.25 mm was named Radiator-Y3. This design change is seen as an innovative method that can increase heat transfer on the radiator surface and increase cooling performance by increasing the turbulence effect of the air affecting the radiator. Experimental studies were carried out using single type (Al2O3 and ZnO) and hybrid (ZnO-CuO) nanofluids in addition to pure water. Experiments were carried out using different air speeds (8–10–12 m/s) and different coolant flow rates (20–22 L/min) and radiator performance was investigated. The effects of the surface area created by the spring structure and the turbulence effect on heat transfer were evaluated. As a result of the studies, Radiator-Y1 showed the best cooling performance among the radiators developed with spring structures, followed by Radiator-Y2 and Radiator-Y3. It was observed that the nanofluids used had a positive effect on the cooling performance compared with pure water, as did the hybrid nanofluid compared when compared with single type nanofluids.