PubMed İndeksli Yayınlar Koleksiyonu

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Citation - WoS: 8
Citation - Scopus: 9
A novel stabilized artificial neural network model enhanced by variational mode decomposing
(CELL PRESS, 2024-07) Ali Danandeh Mehr; Sadra Shadkani; Laith Abualigah; Mir Jafar Sadegh Safari; Hazem Migdady; Mehr, Ali Danandeh; Migdady, Hazem; Shadkani, Sadra; Safari, Mir Jafar Sadegh; Abualigah, Laith; Danandeh Mehr, Ali
Existing artificial neural networks (ANNs) have attempted to efficiently identify underlying patterns in environmental series but their structure optimization needs a trial-and-error process or an external optimization effort. This makes ANNs time consuming and more complex to be applied in practice. To alleviate these issues we propose a stabilized ANNs called SANN. The SANN efficiently optimizes ANN structure via incorporation of an additional numeric parameter into every layer of the ANN. To exemplify the efficacy and efficiency of the proposed approach we provided two practical case studies involving meteorological drought forecasting at cities of Burdur and Isparta T & uuml,rkiye. To enhance SANN forecasting accuracy we further suggested the hybrid VMD-SANN that integrated variation mode decomposition (VMD) with SANN. To validate the new hybrid model we compared its results with those obtained from hybrid VMD-ANN and VMD-Radial Base Function (VMD-RBF) models. The results showed superiority of the VMD-SANN to its counterparts. Regarding Nash Sutcliffe Efficiency measure the VMD-SANN achieves accurate forecasts as high as 0.945 and 0.980 in Burdur and Isparta cities respectively.
A preliminary study on the role of personal history of infectious and parasitic diseases on self-reported health across countries
(W B SAUNDERS CO LTD, 2025-05) Gerit Pfuhl; Filipe Prazeres; Marta Kowal; Toivo Aavik; Beatriz Abad-Villaverde; Reza Afhami; Leonardo Aguilar; Grace Akello; Laith Al-Shawaf; Jan Antfolk; Chiemezie S. Atama; Derya Atamturk Duyar; Roberto Baiocco; Sercan Balim; Carlota Batres; Yakhlef Belkacem; Theo Besson; Adam Bode; Merve Boga; Jordane Boudesseul; Mahmoud Boussena; Hamdaoui Brahim; Nana Burduli; Ali R. Can; Hakan Cetinkaya; Antonio Chirumbolo; Dimitri Chubinidze; Clement Cornec; Bojana M. Dinic; Seda Dural; Izzet Duyar; Samuel O. Ebimgbo; Edgardo Etchezahar; Peter Fedor; Tomasz Frackowiak; David A. Frederick; Katarzyna Galasinska; Felipe E. Garcia; Talia Gomez Yepes; Dmitry Grigoryev; Farida Guemaz; Ivana Hromatko; Gozde Ikizer; Steve M. J. Janssen; Julia A. Kamburidis; Tina Kavcic; Nicolas Kervyn; Farah Khan; Aleksander Kobylarek; Mehmet Koyuncu; Yoshihiko Kunisato; David Lacko; Miguel Landa-Blanco; Linda H. Lidborg; Samuel Lins; Tetyana Mandzyk; Silvia Mari; Tiago A. Marot; Martha Martinez-Banfi; Alan D. A. Mattiassi; Marlon Mayorga-Lascano; Moises Mebarak; Norbert Mesko; Maria Rosa Miccoli; Vita Mikuliciute; Taciona L. Milfont; Katarina Misetic; Mara Morelli; Jean C. Natividade; Izuchukwu L. G. Ndukaihe; Felipe Novaes; Salma S. Omar; Mohd Sofian Omar Fauzee; Tobias Otterbring; Baris Ozener; Simon Ozer; Ju Hee Park; Irena Pavela Banai; Farid Pazhoohi; Mariia Perun; Martin Pirko; Ekaterine Pirtskhalava; Katarzyna Pisanski; Nejc Plohl; Koen Ponnet; Pavol Prokop; Matheus F. F. Ribeiro; Frederico Rosario; Aysegul Sahin; Fatima Zahra Sahli; Dusana Sakan; Oksana Senyk; Henrik Siepelmeyer; Diana Ribeiro da Silva; Sangeeta Singh; Caglar Solak; Sinem Soylemez; Anna Studzinska; Chee-Seng Tan; Gulmira T. Topanova; Merve Bulut Topcu; Ezgi Toplu-Demirtas; Bastien Tremoliere; Singha Tulyakul; Joaquin Ungaretti; Jaroslava V. Valentova; Marco A. C. Varella; Mona Vintila; Tatiana Volkodav; Anna Wlodarczyk; Yao-Yuan Yeh; Gyesook Yoo; Oulmann Zerhouni; Marcos Zumarraga-Espinosa; Maja Zupancic; Piotr Sorokowski
Objectives: Infectious diseases are often associated with decline in quality of life. The aim of this study is to analyze the relationship between personal history of communicable i.e. infectious and parasitic diseases and self-rated health. Study design: Secondary analysis of a large dataset multi-country observational study. Methods: We used a four-pronged analysis approach to investigate whether personal history of infectious and parasitic diseases is related to self-reported health measured with a single item. Results: Three of the four analyses found a small positive effect on self-reported health among those reporting a history of pathogen exposure. The meta-analysis found no support but large heterogeneity that was not reduced by two classifications of countries. Conclusion: Personal history of infectious and parasitic diseases does not reduce self-reported health across a global sample.
A review of ADHD detection studies with machine learning methods using rsfMRI data
(WILEY, 2024-03-12) Gurcan Taspinar; Nalan Ozkurt
Attention deficit hyperactivity disorder (ADHD) is a common mental health condition that significantly affects school-age children causing difficulties with learning and daily functioning. Early identification is crucial and reliable and objective diagnostic tools are necessary. However current clinical evaluations of behavioral symptoms can be inconsistent and subjective. Functional magnetic resonance imaging (fMRI) is a non-invasive technique that has proven effective in detecting brain abnormalities in individuals with ADHD. Recent studies have shown promising outcomes in using resting state fMRI (rsfMRI)-based brain functional networks to diagnose various brain disorders including ADHD. Several review papers have examined the detection of other diseases using fMRI data and machine learning or deep learning methods. However no review paper has specifically addressed ADHD. Therefore this study aims to contribute to the literature by reviewing the use of rsfMRI data and machine learning methods for detection of ADHD. The study provides general information about fMRI databases and detailed knowledge of the ADHD-200 database which is commonly used for ADHD detection. It also emphasizes the importance of examining all stages of the process including network and atlas selection feature extraction and feature selection before the classification stage. The study compares the performance advantages and disadvantages of previous studies in detail. This comprehensive approach may be a useful starting point for new researchers in this area. This review paper aims to give a comprehensive study that summarizes the state of the art. We believe this kind of review will accelerate researchers new to ADHD detection studies and will be a great starting point. image
A robotic system to prepare IV solutions
(ELSEVIER IRELAND LTD, 2018-11) Mehmet S. Unluturk; Ozgur Tamer; Semih Utku
Drugs need to be used regularly and correctly in order to be effective. When medicines are used correctly negativities that threaten human health and life can be avoided but they can cause unwanted situations that can occur until the end of life when they are used incorrectly. The most common drug administration errors in hospitals are: The wrong dosage of the drug given to the patient the timing and / or the method of administration the wrong drug given to the patient the drug given to the wrong patient or even not given. Furthermore the information about the drug that is administered to the patient may not be registered at all. In this research a robotic drug preparation system and a communication server accepting prescription orders have been developed. Component engineering methodology is further utilized in the design of the Drug Preparation System to maximize reuse increase product reliability reduce design code and test efforts. The IV Robotic Drug Preparation Robot is composed of a robotic work station and a Cartesian carrier to carry the work station to the desired location. The robotic work station has several grippers to handle syringes to pull the piston of the syringe and to lock the closed system connector to the vial. The IV Robotic Drug Preparation System and communication server are developed and being used in the hospitals. Due to this system medicines left unused in vials can be used and a great amount of savings is obtained from the drug purchases.
Citation - WoS: 1
Citation - Scopus: 2
Aggregation for Computing Multi-Modal Stationary Distributions in 1-D Gene Regulatory Networks
(IEEE COMPUTER SOC, 2018-05-01) Neslihan Avcu; Nihal Pekergin; Ferhan Pekergin; Cuneyt Guzelis; Pekergin, Nihal; Pekergin, Ferhan; Avcu, Neslihan; Guzelis, Cuneyt
This paper proposes aggregation-based three-stage algorithms to overcome the numerical problems encountered in computing stationary distributions and mean first passage times for multi-modal birth-death processes of large state space sizes. The considered birth-death processes which are defined by Chemical Master Equations are used in modeling stochastic behavior of gene regulatory networks. Computing stationary probabilities for a multi-modal distribution from Chemical Master Equations is subject to have numerical problems due to the probability values running out of the representation range of the standard programming languages with the increasing size of the state space. The aggregation is shown to provide a solution to this problem by analyzing first reduced size subsystems in isolation and then considering the transitions between these subsystems. The proposed algorithms are applied to study the bimodal behavior of the lac operon of E. coli described with a one-dimensional birth-death model. Thus the determination of the entire parameter range of bimodality for the stochastic model of lac operon is achieved.
Alternative electron sinks in chloroplasts and mitochondria of halophytes as a safety valve for controlling ROS production during salinity
(WILEY, 2024-05) Nil Demircan; Mustafa Cemre Sonmez; Turgut Yigit Akyol; Rengin Ozgur Ozgur; Ismail Turkan; Karl-Josef Dietz; Baris Uzilday
Electron flow through the electron transport chain (ETC) is essential for oxidative phosphorylation in mitochondria and photosynthesis in chloroplasts. Electron fluxes depend on environmental parameters e.g. ionic and osmotic conditions and endogenous factors and this may cause severe imbalances. Plants have evolved alternative sinks to balance the reductive load on the electron transport chains in order to avoid overreduction generation of reactive oxygen species (ROS) and to cope with environmental stresses. These sinks act primarily as valves for electron drainage and secondarily as regulators of tolerance-related metabolism utilizing the excess reductive energy. High salinity is an environmental stressor that stimulates the generation of ROS and oxidative stress which affects growth and development by disrupting the redox homeostasis of plants. While glycophytic plants are sensitive to high salinity halophytic plants tolerate grow and reproduce at high salinity. Various studies have examined the ETC systems of glycophytic plants however information about the state and regulation of ETCs in halophytes under non-saline and saline conditions is scarce. This review focuses on alternative electron sinks in chloroplasts and mitochondria of halophytic plants. In cases where information on halophytes is lacking we examined the available knowledge on the relationship between alternative sinks and gradual salinity resilience of glycophytes. To this end transcriptional responses of involved components of photosynthetic and respiratory ETCs were compared between the glycophyte Arabidopsis thaliana and the halophyte Schrenkiella parvula and the time-courses of these transcripts were examined in A. thaliana. The observed regulatory patterns are discussed in the context of reactive molecular species formation in halophytes and glycophytes.
Citation - WoS: 20
Citation - Scopus: 26
An analysis of Emergency Medical Services demand: Time of day- day of the week- and location in the city
(ELSEVIER, 2017-06) Gorkem Sariyer; Mustafa Gokalp Ataman; Serhat Akay; Turhan Sofuoglu; Zeynep Sofuoglu; Ataman, Mustafa Gokalp; Sariyer, Gorkem; Sofuoglu, Turhan; Akay, Serhat; Sofuoglu, Zeynep
Objective: Effective planning of Emergency Medical Services (EMS) which is highly dependent on the analysis of past data trends is important in reducing response time. Thus we aimed to analyze demand for these services based on time and location trends to inform planning for an effective EMS. Materials and methods: Data for this retrospective study were obtained from the Izmir EMS 112 system. All calls reaching these services during first six months of 2013 were descriptively analyzed based on time and location trends as a heat-map form. Results: The analyses showed that demand for EMS varied within different time periods of day and according to day of the week. For the night period demand was higher at the weekend compared to weekdays whereas for daytime hours demand was higher during the week. For weekdays a statistically significant relation was observed between the call distribution of morning and evening periods. It was also observed that the percentage of demand changed according to location. Among 30 locations the five most frequent destinations for ambulances which are also correlated with high population densities accounted for 55.66% of the total. Conclusion: The results of this study shed valuable light on the areas of call center planning and optimal ambulance locations of Izmir which can also be served as an archetype for other cities. Copyright (C) 2016 The Emergency Medicine Association of Turkey. Production and hosting by Elsevier B.V. on behalf of the Owner. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
An information geometrical evaluation of Shannon information metrics on a discrete n-dimensional digital manifold
(Elsevier Ltd, 2023-06) Ahmet Hasan Koltuksuz; Cagatay Yucel; Anas Maazu Kademi; Yucel, Cagatay; Maazu Kademi, Anas; Kademi, Anas Maazu; Koltuksuz, Ahmet
The definition and nature of information have perplexed scientists due to its dual nature in measurements. The information is discrete and continuous when evaluated on a metric scale and the Laplace-Beltrami operator and Gauss-Bonnet Theorem can map one to another. On the other hand defining the information as a discrete entity on the surface area of an n-dimensional discrete digital manifold provides a unique way of calculating the entropy of a manifold. The software simulation shows that the surface area of the discrete n-dimensional digital manifold is an effectively computable function. Moreover it also provides the information-geometrical evaluation of Shannon information metrics. © 2023 Elsevier B.V. All rights reserved.
Analyzing Main and Interaction Effects of Length of Stay Determinants in Emergency Departments
(KERMAN UNIV MEDICAL SCIENCES, 2019-11-16) Gorkem Sariyer; Mustafa Gokalp Ataman; Ilker Kiziloglu
Background: Measuring and understanding main determinants of length of stay (LOS) in emergency departments (EDs) is critical from an operations perspective since LOS is one of the main performance indicators of ED operations. Therefore this study analyzes both the main and interaction effects of four widely-used independent determinants of ED-LOS. Methods: The analysis was conducted using secondary data from an ED of a large urban hospital in Izmir Turkey. Between-subject factorial analysis of variance (ANOVA) was used to test the main and interaction effects of the corresponding factors. P values <.05 were considered statistically significant. Results: While the main effect of gender was insignificant age mode of arrival and clinical acuity had significant effects whereby ED-LOS was significantly higher for the elderly those arriving by ambulance and clinically-categorized high-acuity patients. Additionally there was an interaction between the age and clinical acuity in that while ED-LOS increased with age for high acuity patients the opposite trend occurred for low acuity patients. When ED-LOS was modeled using gender age and mode of arrival there was a significant interaction between age and mode of arrival. However this interaction was not significant when the model included age mode of arrival and clinical acuity. Conclusion: Significant interactions exist between commonly used ED-LOS determinants. Therefore interaction effects should be considered in analyzing and modelling ED-LOS.
Citation - WoS: 8
Citation - Scopus: 10
Automated personnel-assets-consumables-drug tracking in ambulance services for more effective and efficient medical emergency interventions
(ELSEVIER IRELAND LTD, 2016-04) Semih Utku; Mehmet Hilal Ozcanhan; Mehmet Suleyman Unluturk; Unluturk, Mehmet Suleyman; Utku, Semih; Özcanhan, Mehmet Hilal
Patient delivery time is no longer considered as the only critical factor in ambulatory services. Presently five clinical performance indicators are used to decide patient satisfaction. Unfortunately the emergency ambulance services in rapidly growing metropolitan areas do not meet current satisfaction expectations, because of human errors in the management of the objects onboard the ambulances. But human involvement in the information management of emergency interventions can be reduced by electronic tracking of personnel assets consumables and drugs (PACD) carried in the ambulances. Electronic tracking needs the support of automation software which should be integrated to the overall hospital information system. Our work presents a complete solution based on a centralized database supported by radio frequency identification (RFID) and bluetooth low energy (BLE) identification and tracking technologies. Each object in an ambulance is identified and tracked by the best suited technology. The automated identification and tracking reduces manual paper documentation and frees the personnel to better focus on medical activities. The presence and amounts of the PACD are automatically monitored warning about their depletion non-presence or maintenance dates. The computerized two way hospital-ambulance communication link provides information sharing and instantaneous feedback for better and faster diagnosis decisions. A fully implemented system is presented with detailed hardware and software descriptions. The benefits and the clinical outcomes of the proposed system are discussed which lead to improved personnel efficiency and more effective interventions. (C) 2015 Elsevier Ireland Ltd. All rights reserved.
Citation - WoS: 10
Citation - Scopus: 13
Big data analytics and the effects of government restrictions and prohibitions in the COVID-19 pandemic on emergency department sustainable operations
(SPRINGER, 2022-09-15) Gorkem Sariyer; Mustafa Gokalp Ataman; Sachin Kumar Mangla; Yigit Kazancoglu; Manoj Dora; Ataman, Mustafa Gokalp; Dora, Manoj; Sariyer, Gorkem; Mangla, Sachin Kumar; Kazancoglu, Yigit
Grounded in dynamic capabilities this study mainly aims to model emergency departments' (EDs) sustainable operations in the current situation caused by the COVID-19 pandemic by using emerging big data analytics (BDA) technologies. Since government may impose some restrictions and prohibitions in coping with emergencies to protect the functioning of EDs it also aims to investigate how such policies affect ED operations. The proposed model is designed by collecting big data from multiple sources and implementing BDA to transform it into action for providing efficient responses to emergencies. The model is validated in modeling the daily number of patients the average daily length of stay (LOS) and daily numbers of laboratory tests and radiologic imaging tests ordered. It is applied in a case study representing a large-scale ED. The data set covers a seven-month period which collectively means the periods before COVID-19 and during COVID-19 and includes data from 238152 patients. Comparing statistics on daily patient volumes average LOS and resource usage both before and during the COVID-19 pandemic we found that patient characteristics and demographics changed in COVID-19. While 18.92% and 27.22% of the patients required laboratory and radiologic imaging tests before-COVID-19 study period these percentages were increased to 31.52% and 39.46% during-COVID-19 study period. By analyzing the effects of policy-based variables in the model we concluded that policies might cause sharp decreases in patient volumes. While the total number of patients arriving before-COVID-19 was 158347 it decreased to 79805 during-COVID-19. On the other hand while the average daily LOS was 117.53 min before-COVID-19 this value was calculated to be 16503 min during-COVID-19 study period. We finally showed that the model had a prediction accuracy of between 80 to 95%. While proposing an efficient model for sustainable operations management in EDs for dynamically changing environments caused by emergencies it empirically investigates the impact of different policies on ED operations.
Citation - WoS: 3
Citation - Scopus: 3
Carbon Footprint of Food Production: A Systematic Review and Meta-Analysis
(Nature Portfolio, 2025-10-13) 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: 44
Citation - Scopus: 48
Childhood Emotional Abuse and Cyberbullying Perpetration: The Role of Dark Personality Traits
(SAGE Publications Inc., 2019-12-02) Kağan Kircaburun; Peter Karl Jonason; Mark D. Griffiths; Engin Aslanargun; Emrah Emirtekin; Şule Betül Tosuntaş; Joël Billieux; Emirtekin, Emrah; Billieux, Joel; Aslanargun, Engin; Kircaburun, Kagan; Jonason, Peter; Griffiths, Mark D.; Tosuntas, Sule B.
Dark personality traits (i.e. Machiavellianism psychopathy narcissism spitefulness and sadism) are associated with adverse childhood experiences and deviant online behaviors. However their mediating role between childhood emotional abuse and cyberbullying has never previously been investigated. We examined direct and indirect associations of childhood emotional abuse and cyberbullying via dark personality traits among 772 participants. Men were better characterized by dark personality traits and were more likely to engage in cyberbullying than women and there were no sex differences in childhood emotional abuse. Collectively dark traits fully mediated the relationship between childhood emotional abuse and cyberbullying in men with partial mediation in the total sample and women. More specifically Machiavellianism and spitefulness were mediators in both samples sadism was a mediator in men and the total sample and psychopathy was a mediator in the total sample and women. The dark personality traits can account for the association between childhood emotional abuse and cyberbullying especially among men. © 2021 Elsevier B.V. All rights reserved.
Classification of EEG recordings by using fast independent component analysis and artificial neural network
(SPRINGER, 2007-10-26) Yucel Kocyigit; Ahmet Alkan; Halil Erol
Since there is no definite decisive factor evaluated by the experts visual analysis of EEG signals in time domain may be inadequate. Routine clinical diagnosis requests to analysis of EEG signals. Therefore a number of automation and computer techniques have been used for this aim. In this study we aim at designing a MLPNN classifier based on the Fast ICA that accurately identifies whether the associated subject is normal or epileptic. By analyzing a data set consisting of 100 normal and 100 epileptic EEG time series we have found that the MLPNN classifier based on the Fast ICA achieved and sensitivity rate of 98% and specificity rate of 90.5%. The results demonstrate that the testing performance of the neural network diagnostic system is found to be satisfactory and we think that this system can be used in clinical studies. Since the time series analysis of EEG signals is unsatisfactory and requires specialist clinicians to evaluate this application brings objectivity to the evaluation of EEG signals.
Citation - WoS: 43
Citation - Scopus: 48
Consumer Response to Novel Foods: A Review of Behavioral Barriers and Drivers
(MDPI, 2024-06-27) Cihat Guenden; Pelin Atakan; Murat Yercan; Konstadinos Mattas; Marija Knez; Yercan, Murat; Atakan, Pelin; Mattas, Konstadinos; Günden, Cihat; Guenden, Cihat; Knez, Marija
There is a pressing need for a transition toward more sustainable diets which has become a shared priority for both consumers and businesses. Innovation is becoming increasingly widespread across all facets of the food supply chain. This innovation spans various domains related to production including sustainable cultivation methods as well as new food technologies like gene editing new product development like functional foods and revitalizing underutilized and genetically diverse varieties to preserve biodiversity. However not all innovative efforts are accepted by consumers and survive in markets. The interwoven and long agri-food supply chains often obscure the feedback loop between production and consumption. Consequently it is important to understand to what extent consumers embrace these food innovations and form new eating habits. This review aims to investigate the consumer response to novel foods focusing on behavioral factors which have yet to receive as much attention as sensory factors. Peer-reviewed empirical articles from the last decade are examined inductively to develop a bird's-eye view of the behavioral barriers to and drivers of consumer acceptance of novel foods. In addition strategies to overcome the identified challenges associated with the behavioral barriers are reviewed and examined. Based on this the study links cognitive biases with behavioral factors influencing consumer acceptance of novel foods. This study concludes that the inconvenience associated with abandoning established eating habits is typically perceived as a loss and avoiding this inconvenience is deemed more worth the risk than the potential gains associated with novel food consumption. This study suggests that framing and placing pro-diversity labels could serve as effective behavioral interventions for marketing strategists and food policymakers.
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, 2025-10-27) 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: 4
Citation - Scopus: 4
Deciphering melatonin biosynthesis pathway in Chenopodium quinoa: genome-wide analysis and expression levels of the genes under salt and drought
(SPRINGER, 2025-06-12) Seher Yolcu; Ece Fidan; Muhammed Fatih Kaya; Emre Aksoy; Ismail Turkan; Kaya, Muhammed Fatih; Turkan, Ismail; Fidan, Ece; Aksoy, Emre; Yolcu, Seher
Main conclusionIn this study we identified a total of ten melatonin biosynthesis genes (3 TDCs 2 TSHs 3 SNATs and 2 ASMTs) in Chenopodium quinoa through bioinformatics methods and analyzed physiological traits and gene expression levels in drought- and salt-treated plants with or without melatonin. Gene expression levels showed variations depending on tissues genotypes and abiotic stress.AbstractMelatonin is involved in distinct biological processes such as growth development and stress response in plants. The tryptophan decarboxylase (TDC) tryptamine 5-hydroxylase (T5H) serotonin N-acetyltransferase (SNAT) and N-acetylserotonin O-methyltransferase (ASMT) enzymes are involved in melatonin biosynthesis. Exogenous melatonin reduces the adverse effects of salt stress in different plants but the roles of melatonin biosynthesis pathway in quinoa (Chenopodium quinoa) remain elusive. This study aims to identify and characterize the melatonin biosynthetic genes encoding TDCs T5Hs SNATs and ASMTs in C. quinoa genome through bioinformatics methods and determine their transcript abundances under salt and drought stress. In total ten genes were identified in C. quinoa genome including 3 TDCs 2 TSHs 3 SNATs and 2 ASMTs. TDCs have a pyridoxal-dependent decarboxylase domain T5Hs possess a cytochrome P450 SNAT proteins contain the Acetyltransf_1 domain and ASMTs include the O-methyltransferase domain. We also examined some physiological characteristics such as growth and water relations along with electrolyte leakage. For that purpose two quinoa genotypes (Salcedo and Ames 1377) were subjected to salt and drought stress with or without melatonin. Exogenous melatonin remarkably reduced the negative effects of salt and drought on shoot length RWC and electrolyte leakage in the sensitive Salcedo genotype. However it showed limited impact on the stress-tolerant Ames 1377 genotype. Expression patterns showed variations depending on tissues genotypes and the type of abiotic stress. Promoter analysis indicated that the cis-elements in TDC T5H and SNAT promoters were mostly associated with stress-response while those in ASMT promoters were related to light response.
Determining a continuous marker for sleep depth
(PERGAMON-ELSEVIER SCIENCE LTD, 2007-11) Musa H. Asyali; Richard B. Berry; Michael C. K. Khoo; Ayse Altinok
Detection and quantification of sleep arousals is an important issue as the frequent arousals are known to reduce the quality of sleep and cause daytime sleepiness. In typical sleep staging electroencephalograph (EEG) is the core signal and based on the visual inspection of the frequency content of EEG. non-rapid eye movement sleep is staged into four somewhat rough categories. In this study we aimed at developing a continuous marker based on a more rigorous spectral analysis of EEG to measure or quantify the depth of sleep. In order to develop such a marker we obtained the time-frequency map of two EEG channels around sleep arousals and identified the frequency bands that show the most change during arousals. We then evaluated classification performance of the potential signals for representing the depth of sleep using receiver operating characteristic analysis. Our comparisons based on the area under the curve values revealed that the sum of absolute powers in alpha and beta bands is a good continuous marker to represent the depth of sleep. Higher values of this marker indicate low-quality sleep and vice versa. We believe that use of this marker will lead to a better quantification of sleep quality. (C) 2007 Published by Elsevier Ltd.
Citation - WoS: 2
Citation - Scopus: 2
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, 2025-12) 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.
Citation - WoS: 31
Citation - Scopus: 42
Effects of Environment Social and Governance (ESG)disclosures on ESGscores: Investigating therole ofcorporategovernance forpubliclytraded Turkishcompanies
(Academic Press, 2024-09) Mustafa Tevfik Kartal; Dilvin Taşkın; Muhammad Shahbaz; Serpil Kılıç Depren; Ugur Korkut Pata; Taşkın, Dilvin; Korkut Pata, Ugur; Pata, Ugur Korkut; Kılıç Depren, Serpil; Shahbaz, Muhammad; Depren, Serpil Kilic; Kartal, Mustafa Tevfik
The world has experienced climate-related issues which increase the importance of ESG disclosures and corporate governance (CG) of companies which take place at the heart of economies. Therefore improving ESG disclosures and CG practices becomes significant to combat climate change at the company level. Considering that Türkiye restructured ESG disclosures in 2022 this study investigates the role of CG on the nexus between ESG scores of publicly traded companies (PTC) and ESG reports. So the study analyzes 102 PTC (full sample) 51 PTC in Borsa Istanbul Corporate Governance Index (in-sample) and the remaining 51 PTC (out-sample) using ESG disclosures of 2022 and applying novel super learner (SL) algorithm. Our results show that (i) SL has a higher prediction performance reaching ∼94.3%, (ii) the environment (governance) layer has the highest (lowest) total relative importance (contribution) to ESG scores in all samples, (iii) C8 S6 and E5 are the most important ESG principles in the full sample in-sample and out-sample respectively, (iv) the contribution of each ESG principles to the total ESG scores varies by sample, (v) CG plays a smoothing role for the relative importance of each ESG principle while the relative importance in the out-sample shows much higher volatility. Overall the study reveals the non-linear contributions of ESG principles on ESG scores and suggests that PTC should prioritize highly important ESG principles consider the moderating role of CG on the link between ESG scores and ESG disclosures and use ESG disclosures as a strategic tool to develop ESG scores and disclosures. © 2024 Elsevier B.V. All rights reserved.

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