Recep Tayyip Erdoğan Üniversitesi Kurumsal Akademik Arşivi
DSpace@RTEÜ, Recep Tayyip Erdoğan Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
Integrated iron foliar application and phosphorus fertilization enhance yield and nutrient dynamics of mung bean in calcareous soils
(BioMed Central, 2026) Khan, Maaz; Ali, Mehran; Ahmad, Haris; Soury, Sher Shah; Altaf, Muhammad Tanveer; Liaqat, Waqas; Aasim, Muhammad
Background: Mung bean production in calcareous soils is often constrained by low nutrient availability, particularly iron (Fe) and phosphorus (P), which limit plant growth and yield. This study aimed to evaluate the effects of Fe foliar application and P fertilization on growth, yield, and nutrient dynamics of mung bean under calcareous soil conditions.
Results: A two-year field experiment (2022-2023) was conducted using a randomized complete block design with Fe foliar application (0, 0.2, 0.4, and 0.6%) and P fertilization rates (0, 30, 60 and 90 kg ha- 1). Iron and phosphorus applications significantly influenced yield components, physiological traits and nutrient accumulation. Foliar application of 0.4% Fe resulted in the highest thousand seed weight (39.42 g), biological yield (3132 kg ha- 1), seed yield (790 kg ha- 1) and crop growth rate (13.58 g m- 2 day- 1), representing increases of 12.21%, 12.54%, 23.44% and 44.47%, respectively over the control treatment. Similarly, phosphorus application at 60 kg ha- 1 significantly enhanced thousand seed weight (39.83 g), biological yield (3156 kg ha- 1) and seed yield (796 kg ha- 1), chlorophyll content (3.12 mg g- 1) and crop growth rate (13.48 g m- 2 day- 1) with increase of 14.49%, 14.06%, 32.89% and 26.22%, respectively compared with the unfertilized control. Seed and straw N (3.58% and 1.27%) and Fe concentrations (36.2 mg kg- 1 and 315 mg kg- 1) were highest under 0.6% Fe, while in case of phosphorus, the plots with 90 kg P ha- 1 produced the maximum seed and straw N (3.97% and 1.06%). The highest seed and straw P concentration (0.31% and 0.16%) was observed at 0% Fe, while application of 90 kg P ha- 1 also enhanced seed and straw P content (0.38% and 0.20%). Agronomic phosphorus efficiency peaked at 30 kg P ha- 1 (4.26 kg kg- 1) and 0.4% Fe (4.29 kg kg- 1), while total N uptake (41.51 kg ha- 1), seed carbohydrate content (62.79%) and soil P (7.02 mg kg- 1) were highest with application of 90 kg P ha- 1. The foliar spray of 0.6% Fe resulted in higher total N uptake (40.45 kg ha- 1), seed carbohydrate content (61.19%) and soil P (6.79 mg kg- 1). Economic analysis revealed that the combined application of 0.4% Fe and 60 kg P ha- 1 produced the highest value cost ratio.
Conclusion: The combined application of 0.4% Fe and 60 kg P ha- 1 is recommended for farmers to enhance mung bean yield and profitability under calcareous soil conditions, where Fe and P availability is often limited, whereas 0.6% Fe with 90 kg P ha- 1 is more effective for enhancing nutrient accumulation. This nutrient management strategy can be effectively adopted under field conditions to improve productivity and nutrient use efficiency.
Genome-wide identification and characterization of 1-amino-cyclopropane-1- carboxylate synthase (ACS) gene family in Carica papaya and expression insights in response to hormone stress
(BioMed Central, 2026) Mudasar Muhammad; Nabi, Hafiz Ghulam; Ahmad, Arsalan; Shafiq, Muhammad; Liaqat, Waqas; Akbulut, Mustafa; Altaf, Muhammad Tanveer
ACC-synthase (1-aminocyclopropane-1-carboxylate synthase), also known as the ACS gene, plays a pivotal role in ethylene production, which is of great importance in the fruit ripening process for producing saleable yield (marketable fruit). The ACS gene family presumably controls stress responses, plant growth and development, and particularly fruit ripening. Computational biology was used as an essential tool to identify seven ACS genes in Carica papaya (red hermaphrodite) using an RNA-seq database (NCBI GEO). Further, the phylogenetic relationships of ACS genes determined gene family resemblance in the genomes of Hordeum vulgare, Musa acuminata, C. papaya, and Arabidopsis thaliana; therefore, the identified gene families were further classified into four distinct clades (Type-I, Type-II, Type-III, and Type-IV) in alignment with the well-established Arabidopsis classification. Moreover, encompassing gene structure, domain motifs, cis-element phylogenetic profiling, synteny, and transcriptomic profiling unveiled latent structural and functional attributes within CpACS genes. Through segmental duplication of CpACS, insights into evolutionary duplication events were predicted. The paralogous behavior of ACS genes in C. papaya and a comprehensive transcriptomic analysis demonstrated both up- and down-regulation patterns in response to ethylene treatment at different time points during the fruit ripening process, using the papaya manual handbook V2 (2021). Gene expression showed upregulation of two essential CpACS genes, CpACS5 and CpACS6. RT-qPCR validates the expression of these important genes during fruit ripening. However, one gene, CpACS7, is expressed in the later stages of fruit development. Our results demonstrated novel avenues for understanding the expression pathways of the ACS gene family in red hermaphrodite papaya, and most of these genes were linked to regulating various abiotic stresses, plant growth, and fruit development.
Comparison of serum irisin and leptin levels in obese and non-obese women with polycystic ovary syndrome
(Nature Publishing Group, 2026) Çolakoğlu, Yeliz; Şentürk, Şenol; Arpa, Medeni; Aksan, Alperen
Polycystic ovary syndrome (PCOS) is a common endocrine disorder affecting reproductive-age women, often associated with obesity and metabolic dysfunction. This study investigated the relationship between two key metabolic biomarkers, irisin and leptin, in obese and non-obese women with PCOS compared to healthy controls. This prospective case-control study included 80 women, with 40 diagnosed with PCOS and 40 healthy controls. Each group was further divided into obese and non-obese subgroups, forming four groups. Serum irisin and leptin levels were measured using ELISA kits. Clinical and metabolic parameters (body mass index [BMI], insulin resistance, and fasting glucose) were analyzed, and correlations were evaluated. Leptin levels differed between groups, with lower levels observed in PCOS compared to controls. Irisin levels were significantly lower in obese subgroups, irrespective of PCOS status (p < 0.05). Leptin positively correlated with BMI, insulin levels, and insulin resistance, while irisin negatively correlated with BMI and insulin resistance. Obesity plays a role in modulating irisin and leptin levels in PCOS. These findings provide an integrated perspective on adipokine-myokine interactions in PCOS, rather than identifying novel biomarkers. Larger, longitudinal studies are needed to confirm these findings.
Diagnostic and localization performance of multimodal large language models in the interpretation of dental periapical radiographs
(BioMed Central, 2026) Hatipoğlu, Ömer; Baytar, Muhammed; Hatipoğlu, Fatma Pertek
Objective: This study aimed to comparatively evaluate the performance of multiple multimodal large language models (MLLMs) in interpreting dental periapical radiographs using a structured framework that incorporates diagnostic accuracy, tooth-level anatomical precision, localization, and composite correctness across various attributes.
Materials and methods: This paired, cross-sectional study assessed six contemporary MLLMs (Microsoft Copilot, ChatGPT-o4-mini-high, ChatGPT-5.2 Thinking, Gemini 2.5 Flash, Gemini 3 Pro, and Grok-3) using 55 de-identified dental periapical radiographs selected from a clinical archive according to predefined inclusion and exclusion criteria. Radiographs were selected to represent mutually exclusive tooth-status categories, including dental caries, composite restorations, amalgam restorations, and sound teeth. The reference labels for tooth status and anatomical identifiers were established before model evaluation through independent assessment and consensus by experienced clinicians. Each image was evaluated by all models under standardized prompting conditions. Performance was assessed across tasks of increasing complexity, including tooth-status diagnosis, jaw identification, tooth region, side determination, FDI tooth numbering, localization accuracy, and overall correctness across all attributes. Paired statistical analyses were performed using Cochran's Q test and generalized estimating equations with Holm's adjustment for multiple comparisons.
Results: Tooth status diagnosis accuracy was moderate and comparable across models (45.5-60.0%), with no significant between-model differences. In contrast, significant heterogeneity was observed for localization-related tasks, including side determination, FDI tooth numbering, composite localization, and complete accuracy (p < 0.05). Adjusted analyses demonstrated that Gemini 3 Pro showed the highest adjusted accuracy for localization-dependent outcomes and overall correctness, with higher odds than several other models in pairwise comparisons. None of the models showed a consistent advantage for tooth status diagnosis alone.
Conclusion: The performance of MLLMs in dental periapical radiograph interpretation is task-dependent and increasingly model-specific as anatomical precision requirements increase. While MLLMs may support education and structured discussions of radiographic findings, their reliability for autonomous tooth-level diagnosis and localization remains limited.
Clinical significance: MLLMs may support dental education and patient communication by assisting with the explanation of basic radiographic features. However, their reliability decreases for tooth-level localization and comprehensive anatomical accuracy, indicating that MLLMs should not be used as stand-alone tools for clinical decision-making based on periapical radiographs.
Fluopyram in agricultural ecosystems: environmental fate, microbial transformation, ecotoxicity, and resistance risks of an SDHI fungicide
(Frontiers Media SA, 2026) Zhang, Chaoqun; Ullah, Muhammad Zafar; Guan, Chengwei; Mubeen, Mustansar; Ding, Yongliang; Altaf, Muhammad Tanveer; Wang, Jie
Fluopyram is a next-generation succinate dehydrogenase inhibitor (SDHI) fungicide, which is very popular in the management of economically significant fungal conditions in cereals, fruits, vegetables, and ornamental crops. It works by inhibiting the complex II present in the mitochondria by blocking succinate dehydrogenase, which electron transport and energy generation, eventually hindering fungal development leading to death of the pathogen. Besides having good fungicidal effects, fluopyram has also demonstrated a nematicidal effect, which has also enhanced its utility in various agricultural systems. Empirical studies indicate that SDHIs can induce mortality, mitochondrial dysfunction, oxidative stress, and developmental delays in non-target organisms. Additionally, the environmental persistence of these compounds raises concerns about their potential for ecological disruption. The extensive and growing use of SDHIs however has also given rise to the issue of resistance development with recorded resistance cases in a number of fungal populations and has placed a strong demand on the need to use crop rotation strategies, combination formulations and resistance monitoring initiatives. In addition to its agronomic advantages, the environmental fate of fluopyram such as its mobility, persistence and degradation characteristics in soil and water and the possibility of food system residues have been the subject of attention. Unlike previous studies focusing on isolated aspects, this review comprehensively links efficacy, environmental dynamics, and mechanistic toxicity of fluopyram across multiple biological systems. It highlights underexplored areas including metabolite toxicity, chronic ecological exposure, and resistance risks. This integrated approach offers valuable insights for safer pesticide management and future research directions.
