PubMed İndeksli Yayınlar Koleksiyonu

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Citation - WoS: 2
Citation - Scopus: 2
Carbon Footprint of Food Production: A Systematic Review and Meta-Analysis
(Nature Portfolio, 2025) Onat, Nuri C.; Kucukvar, Murat; Kazançoğlu, Yiğit; Jabbar, Rateb; Al-Quradaghi, Shimaa; Al-Thani, Soud; Mandouri, Jafar
In the face of the urgent climate crisis, food production is a significant contributor to greenhouse gas emissions (GHG). We analyzed 118 life-cycle assessment (LCA) studies on GHG emissions of food production, considering LCA methods, life cycle phase, waste inclusion, and regional factors, including country, continent, and development status. Additionally, machine learning analysis identifies influential factors of GHG emissions of food production across seven categories: red meats, seafood, white meat, fruits & vegetables, animal products, other plant-based, and others (oils). Based on the gradient boosting algorithm, the LCA method choice ranks among the top determinants for GHG emissions in animal products, red meat, seafood, other plant-based products, and others food categories. Only 22% of studies include waste, revealing up to 39% higher emissions in some categories compared to those excluding waste. Our meta-analysis presents min-max-average GHG emission results for each food category, within countries, different scope settings, waste considerations, and LCA methods.
Citation - WoS: 2
Citation - Scopus: 2
Deciphering Drought-Response in Wheat (Triticum Aestivum): Physiological, Biochemical, and Transcriptomic Insights into Tolerant and Sensitive Cultivars under Dehydration Shock
(Frontiers Media SA, 2025) Sezerman, Osman Uğur; Özer, Buğra; Yıldızhan, Yasemin; Fayetorbay, Rumeysa; Cevher-Keskin, Birsen; Tör, Mahmut; Sekmen, A. Hediye
Introduction: Wheat (Triticum aestivum L.) is a major staple crop, but its productivity is severely threatened by drought, especially during reproductive stages when yield and quality are most vulnerable. Climate change and water overexploitation intensify this challenge, with yield losses of up to 80% in arid regions and projected global production declines of similar to 29%. Drought tolerance is a complex trait involving physiological, biochemical, and molecular mechanisms, including stomatal regulation, osmolyte accumulation, and activation of stress-responsive genes. Advances in transcriptomics, functional genomics, and genome editing have identified key regulators (DREB, ERF, SnRK2), antioxidant enzymes, and ABA signalling components as targets for improving drought resilience. Developing drought-tolerant wheat varieties is therefore a priority for food security. Materials and Methods: This study investigates transcriptomic responses in root and leaf tissues of three wheat cultivars, Atay 85 (drought-sensitive), Gerek 79 and Mufitbey (drought-tolerant), subjected to 4- and 8-hour shock-dehydration stress. Before RNAseq analysis, biochemical assays were conducted to assess oxidative damage (TBARS) and antioxidant enzyme activities under shock-dehydration stress for three different cultivars. Differential gene expression analysis was performed, and several highly differentially expressed genesincluding TaZFP36, TaMC5, TaGI, TaGLP9-1, and TaFer were selected to validate RNAseq data in both root and leaf tissues of tolerant and sensitive cultivars. Results: Transcriptomic analysis revealed distinct metabolic strategies for drought adaptation. Photosynthesis-related processes, including Photosystem I and II, were broadly downregulated, while extracellular and membrane-associated components were upregulated, reflecting a shift toward stress defence mechanisms. Cultivar-specific responses highlighted diverse adaptation strategies: Atay 85 exhibited severe metabolic suppression and ATP depletion, making it highly vulnerable to drought. Gerek 79 conserved energy by suppressing photosynthesis while enhancing osmoprotective sugar metabolism and reinforcing structural integrity through lignin and flavonoid biosynthesis. Mufitbey demonstrated the most robust drought tolerance by integrating metabolic dormancy, hormonal signalling, and antioxidant defence, characterized by stable CAT activity and elevated SOD activity, which mitigated oxidative damage and preserved photosynthetic stability. Root tissues prioritized metabolic adjustments for oxidative stress reduction and developmental adaptation, while leaf tissues focused on maintaining photosynthesis and limiting protein damage. Functional enrichment analysis indicated significant upregulation of stress-related pathways, including ABA-mediated signalling, protein binding, and cellular metabolic processes in tolerant cultivars. Discussion: This study advances our knowledge of the complex molecular and biochemical responses of wheat with differing tolerance levels, highlighting both key candidate genes and antioxidant defence mechanisms as central to cultivar-specific adaptation strategies. The distinct metabolic strategies observed emphasize the importance of tailored molecular mechanisms in drought tolerance, which can guide future breeding programs aimed at improving wheat resilience under water-limited conditions.
Citation - WoS: 2
Citation - Scopus: 1
Effect of AI-Related Patents, Energy Transition, Environmental Policy Stringency, Income, and Energy Consumption Sub-Types on the Environmental Sustainability: Evidence from China by KRLS Approach
(Academic Press Ltd- Elsevier Science Ltd, 2025) Taşkın, Dilvin; Kim, Eonsoo; Mukhtarov, Shahriyar; Kirikkaleli, Derviş; Kılıç Depren, Serpil; Park, Jinsu; Depren, Serpil Kilic; Kartal, Mustafa Tevfik
Due to the increasing negative effects on humanity, searching for potential solutions to combat environmental problems has been developing. Accordingly, the study examines the effect of a set of critical factors on environmental sustainability (ES) proxied by ecological footprint (EFP) and load capacity factor (LCF) in China. In this context, the study considers AI-related patents, energy transition, environmental policy stringency (EPS), income, and energy consumption (EC) sub-types and applies the Kernel Regularized Least Squares (KRLS) approach on data from 2000 to 2020 within the context of marginal effect analysis. The outcomes show that (i) AI-related patents and energy transition are completely ineffective to ensure ES; (ii) EPS are marginally effective only at 0.25th and 0.75th percentiles to support ES; (iii) economic growth as well as oil, gas, and coal EC are not good for ES across all percentiles; (iv) nuclear EC is only helpful at 0.25th percentiles, whereas renewable EC is completely unbeneficial; (v) KRLS approach presents successful prediction outcomes around 99.7 % (vi) some variables (i.e., nuclear and renewable EC as well as EPS); have marginal and varying effects across percentiles, whereas some others have not. Thus, the study empirically demonstrates the inefficiency of AI-related patents and energy transition on the ES, whereas EPS and nuclear EC can be helpful to develop ES in the Chinese case.
Evaluating the Impact of Subsurface Hydraulic Barriers on Qanat Flow Rates Using Quantile Regression Forest
(Nature Portfolio, 2025) Vaheddoost, Babak; Can, Murat; Safari, Mir Jafar Sadegh
Qanats, as hydraulic innovations, enabled the sustainable extraction and distribution of groundwater for irrigation and domestic use during history. This study presents a data-driven modeling framework that implements Quantile Regression Forest (QRF), Random Forest (RF), and Support Vector Regression (SVR) to predict Qanat discharge under altered subsurface conditions. Using field data from the Dirsak Qanat in northern Iran, a traditional drainage system recently enhanced by the construction of a subsurface dam (SD), we investigate the dam's effect on discharge potential. The modeling framework incorporates determination of multiple hydro-meteorological inputs including precipitation, temperature, evaporation, humidity, runoff depth, infiltration depth and groundwater levels observed at three monitoring wells. A binary (dummy) variable was also introduced to represent the presence or absence of the SD, thereby capturing the associated changes in boundary conditions. The analysis further revealed that the SD and evaporation are the most influential factors, highlighting the combined effects of anthropogenic modifications and climatic variations on the discharge behavior of the Qanats. It was also concluded that the QRF model with a Nash-Sutcliffe Efficiency (NSE) of 0.818, demonstrate strong predictive capability in capturing complex and non-linear hydrological interactions.
Experimental Determination of Material Behavior Under Compression of a Carbon-Reinforced Epoxy Composite Boat Damaged by Slamming-like Impact
(MDPI, 2026) Altunsaray, Erkin; Bicer, Mustafa; Neser, Gokdeniz; Karasu, Hasim Firat
Carbon-reinforced epoxy laminated composite (CREC) structures are increasingly utilized in high-speed marine vehicles (HSMVs) due to their high specific strength and stiffness; however, they are frequently subjected to impact loads like slamming and aggressive environmental agents during operation. This study experimentally investigates the Compression After Impact (CAI) behavior of CREC plates with varying lamination sequences under both atmospheric and accelerated aging conditions. The samples were produced using the vacuum-assisted resin infusion method with three specific orientation types: quasi-isotropic, cross-ply, and angle-ply. To simulate the marine environment, specimens were subjected to accelerated aging in a salt fog and cyclic corrosion cabin for periods of 2, 4, and 6 weeks. Before and following the aging process, low-velocity impact tests were conducted at an energy level of 30 J, after which the residual compressive strength was measured by CAI tests. At the end of the aging process, after the sixth week, the performance of plates with different layer configuration characteristics can be summarized as follows: Plates 1 and 2, which are quasi-isotropic, exhibit opposite behavior. Plate 1, with an initial toughness of 23,000 mJ, increases its performance to 27,000 mJ as it ages, while these values are around 27,000 and 17,000 mJ, respectively, for Plate 2. It is thought that the difference in configurations creates this difference, and the presence of the 0 degrees layer under the effect of compression load at the beginning and end of the configuration has a performance-enhancing effect. In Plates 3 and 4, which have a cross-ply configuration, almost the same performance is observed; the performance, which is initially 13,000 mJ, increases to around 23,000 mJ with the effect of aging. Among the options, angle-ply Plates 5 and 6 demonstrate the highest performance with values around 35,000 mJ, along with an undefined aging effect. Scanning Electron Microscopy (SEM) and Energy-Dispersive X-ray Spectroscopy (EDS) analyses confirmed the presence of matrix cracking, fiber breakage, and salt accumulation (Na and Ca compounds) on the aged surfaces. The study concludes that the impact of environmental aging on CRECs is not uniformly negative; while it degrades certain configurations, it can enhance the toughness and energy absorption of brittle, cross-ply structures through matrix plasticization.
Green Approaches to Enhance Bioactive Compounds in Goji Berry (Lycium Barbarum) Fruits: Comparative Optimization of Pressurized Water, Microwave-Assisted, and Ultrasound-Assisted Extraction Technologies by Using Response Surface Methodology
(Wiley, 2025) Yildiz-Ozturk, Ece
Goji berries (Lycium barbarum L.), a superfruit with a long history of usage in Asian medicine, are gaining recognition for their potential as functional foods because of their high levels of antioxidants, flavonoids, anthocyanins, and phenolic acids. With the growing demand from consumers for clean-label and naturally sourced ingredients, environmentally friendly extraction technologies are now crucial to creating bioactive-rich extracts appropriate for food and nutraceutical applications. Three eco-friendly extraction methods-pressurized water extraction (PWE), microwave-assisted extraction (MAE), and ultrasound-assisted extraction (UAE)-are thoroughly evaluated in this study to maximize the bioactive compounds' recovery from Goji berry fruits. Water was the only solvent used in all extraction processes, guaranteeing environmental sustainability and food-grade compliance. The solid/liquid ratio, temperature, duration, pressure, and power were all optimized using response surface methodology (RSM). The total phenolic content (TPC), total flavonoid content (TFC), total anthocyanin content (TAC), and antioxidant activity (DPPH inhibition) of the extracted materials were assessed. Under ideal circumstances, the extracts' rutin contents were ascertained by HPLC analysis. According to the findings, MAE had the highest DPPH inhibition rate (75.942%), whereas PWE had the most TPC (17.753 mg GAE/g extract). The flavonoid content of both techniques was comparable. The UAE produced the best energy-to-bioactivity ratio and the most anthocyanin-rich extracts (3.607 mg C3G/g). UAE is the most ecologically friendly option among the techniques, as evidenced by its highest overall efficiency in terms of bioactive recovery and antioxidant capacity. This is the first study to employ a combined approach of RSM and bioactivity-energy efficiency assessment to optimize and compare water-based PWE, MAE, and UAE methods for Goji berries. These results demonstrate that green extraction technologies can be leveraged to sustainably produce bioactive compounds from functional foods like Goji berries, which have significant applications in food, nutraceuticals, and cosmetics.
HistoNeRF: An Accessible and Intelligent Approach for Comprehensive 2D-to-3D Histological Assessment
(Wiley, 2026) Kilic, Kubilay Dogan; Ozyazici, Kaan; Yilmaz, Zeynep Simge; Ozyazici, Aysegul Taskiran; Horuz, Busra; Taşkıran Özyazici, Ayşegül; Kisaoglu, Huseyin
Histological analysis is central to biomedical research and diagnostic pathology, yet conventional two-dimensional (2D) sectioning captures only limited aspects of tissue architecture. Critical spatial relationships-such as tumor boundaries, stromal organization, and vascular networks-remain obscured, restricting diagnostic accuracy and biological interpretation. HistoNeRF addresses these limitations by adapting Neural Radiance Fields (NeRF) to reconstruct three-dimensional (3D) tissue volumes from routine histological sections. In this study, 84 toluidine blue (TB)-stained murine ovarian sections were digitized, alignment-corrected, and integrated into volumetric models. Tissue segmentation was performed using a convolutional neural network, while visualization was achieved through an interactive, GPU-accelerated interface. To ensure accessibility and reproducibility, a Python-based graphical application (HistoNeRF GUI) was developed following Human-Computer Interaction (HCI) principles and containerized with Docker, allowing installation-free deployment via Docker Hub. HistoNeRF produced high-fidelity 3D reconstructions (SSIM = 0.92; Dice similarity coefficient = 0.88), enabling expert histologists to better visualize follicular structures, stromal compartments, and vascular elements. The containerized GUI was deployed successfully from Docker Hub, providing immediate access to 3D reconstruction without a complex local setup. By overcoming the inherent constraints of 2D microscopy, HistoNeRF enhances the visualization, interpretability, and reproducibility of histological architecture. The HCI-guided, cross-platform interface supports scalability and rapid adoption in digital pathology workflows. Although validation was limited to murine ovarian tissue and one staining protocol, this framework can be extended across tissue types and clinical datasets. HistoNeRF bridges routine histology and 3D volumetric analysis through accurate, interactive reconstructions that advance diagnostic precision and biomedical research. While demonstrated on 84 serial TB-stained ovarian sections, broader validation across tissues, stains, and pathological conditions remains future work; to support this, we provide a Dockerized, modular pipeline for straightforward extension.
Legal Artificial Intelligence in Interventional Cardiology: Ethical Boundaries and Decision Support Opportunities in the Turkish Legal Context
(Kare Publ, 2026) Gocer, Hakan; Gocer, Saadet Deniz; Durukan, Ahmet Baris
Representational Context Modulates the Direction and Transiency of Practice Effects on SNARC
(SAGE Publications Ltd, 2026) Palaz, Ezgi; Cetinkaya, Hakan; Dural, Seda
The Spatial-Numerical Association of Response Codes (SNARC) effect typically results in faster left-hand responses for small numbers and right-hand responses for large numbers, aligning with the concept of the mental number line (MNL). It is a robust but a flexible phenomenon that can reverse direction depending on the spatial-numerical mappings employed. This study investigates the potential modulatory effects of two contrasting representational contexts (ruler vs. clockface) on the emergence and persistence of the SNARC effect under two opposing spatial-numerical practices (MNL-compatible vs. MNL-incompatible). In Experiment 1, a magnitude classification task was employed as a practice session including either MNL-compatible or MNL-incompatible stimulus-response mappings, and the transfer and transiency of practice effects were examined by engaging participants in three test parity judgment tasks administered 5 min, 1 day, and 1 week after the practice session. In Experiment 2, different representational contexts were introduced during practice sessions. Experiment 2a utilized an image of a ruler as the context consistent with the MNL, while Experiment 2b employed a clockface image as an inconsistent context. Participants underwent testing three times to assess changes in performance over time. Results revealed that MNL-compatible practice effects did not transfer while MNL-incompatible practice effects resulted in a reverse SNARC effect persisting for up to 1 day. However, introducing the ruler context eliminated this transfer, while the clockface context reduced the persistence of the practice effect.
Space-Magnitude Associations Modulate the Familiar-Size Stroop Effect in Visual Size Judgments
(Springer Heidelberg, 2025) Dural, Seda; Cetinkaya, Hakan; Sefikoglu, Melike
The familiar-size Stroop effect shows how prior knowledge of an object's real-world size influences visual size judgments, slowing reactions when familiar and visual sizes conflict. This study examined how space-magnitude associations, specifically mental number line (MNL) compatibility, interact with Stroop congruency. Participants compared the visual sizes of two objects, ignoring real-world sizes, and identified either the smaller or the larger object across four conditions: Stroop-congruent/MNL-compatible, Stroop-congruent/MNL-incompatible, Stroop-incongruent/MNL-compatible, and Stroop-incongruent/MNL-incompatible. Tasks followed small-then-large or large-then-small identification sequences. Results showed MNL compatibility modulates Stroop interference: MNL-compatible (small-left, large-right) presentations reduced interference, while MNL-incompatible (large-left, small-right) presentations increased it, depending on task type and order. RT distribution analyses revealed MNL effects emerged in slower bins for Stroop-congruent trials and faster bins for Stroop-incongruent trials within small-then-large sequences. These findings suggest that space-magnitude associations shape the familiar-size Stroop effect, revealing a complex relationship between spatial and conceptual representations in size judgment.

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