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- MakaleYalnız künye2026Scopus SJRQ1Phytochemical profiling, biological activities, and molecular docking analysis of Dorycnium pentaphyllum subsp. haussknechtii
Ayna, Adnan; Hakan, Oguzhan; Yapıcı, İsmail; İzol, Ebubekir; Yılmaz, Mustafa Abdullah; Necip, Adem; Yapar, Yakup
BACKGROUND: In the current study, the biological activity fingerprint of Dorycnium pentaphyllum subsp. haussknechtii was investigated by an interdisciplinary approach through analysis of its phytochemical content, antioxidant capacity, enzyme inhibitory potential and molecular docking. RESULTS: The analysis of the phytochemical content by liquid chromatography–tandem mass spectrometry was characterized by the presence of flavan-3-ols, such as epicatechin, epigallocatechin, and catechin, as well as quercetin-derived flavonoids such as isoquercitrin. Analysis of the antioxidant capacity by 2,2-diphenyl-1-picrylhydrazyl, 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid), ferric reducing antioxidant power, Fe3+–Fe2+ reducing and cupric reducing antioxidant capacity methods indicated the strong antioxidant capacity of the plant extract. In addition, the plant extract was able to modulate biological enzyme activity effectively, with IC50 values of 111.78 μg mL−1 for acetylcholinesterase, 22.07 μg mL−1 for butyrylcholinesterase, 1.39 μg mL−1 for α-glucosidase, 7.34 μg mL−1 for carbonic anhydrase I, and 17.41 μg mL−1 for carbonic anhydrase II. To have a better understanding of the molecular mechanism for the plant extract's properties, the major phenolic compounds present in the plant extract were investigated for molecular docking with their respective enzymes. As such, the results revealed a strong binding affinity and conformational stability, with strong hydrogen bonding and π–π interactions. CONCLUSION: Generally, the properties revealed by the plant extract indicate that the phenolic content, strong antioxidant properties, and enzyme inhibition activity of D. pentaphyllum subsp. haussknechtii have shown great potential for being a useful natural source for therapeutic lead compounds.
AtıfScopus1WoS1OpenAlex3
İncele - MakaleYalnız künye2026Scopus SJRQ2Improving the hydrothermal reduced graphene oxide supercapacitor with heat-moisture-treated potato starch as binder
Daulay, Amru; Yassaroh, Yassaroh; Samada, Lukmanul Hakim; Amrulloh, M. Hanif; Kumaş, Cavit; Nariswari, Mentari Kirana; Putri, Devi Mariska; Chambioso, Yugo
Alternative binders that can be processed in water are still in the early stages of development for more efficient and sustainable supercapacitors. However, their electrochemical performance is still below average. This study uses heat-moisture-treated starch (starch HMT) as a binder for reduced graphene oxide (rGO) supercapacitors. Starch HMT has been fabricated at 120 °C. The XRD diffractogram exhibits peaks at 2θ angles of 15°, 17°, 22°, and 24°. The 2θ values indicate that potato starch is of type B. FTIR spectra show the formation of OH, C–O–C, C-O, C–O–C, and C-H bonds. SEM images show cracks in the morphology. Electrochemical testing shows a specific capacity of 230 F/g at a current density of 1 A/g. The charge–discharge stability of the electrodes at 5000 cycles is 90%. These results offer a framework for developing electrode materials and binders for supercapacitors.
- MakaleAçık Erişim2026Scopus SJRQ1Toward Sustainable Financial Behavior: The Role of Financial Socialization and FinTech in Enhancing Green Financial Literacy
Soydaş, Şafak Sönmez; Özbek, Adem; Çam, Alper Veli; Radulescu, Magdalena; Alofaysan, Hind
This study examines how financial literacy and financial socialization influence green financial literacy through the mediating role of FinTech usage within a sustainability-oriented framework. Green financial literacy is treated as a proxy for sustainable financial behavior rather than a direct behavioral measure. Based on financial socialization theory, the study proposes an integrated model linking individual competencies, social learning processes, and digital financial technologies. Data were collected from 539 individuals using a structured questionnaire and analyzed with structural equation modeling (SEM) employing a robust weighted least squares estimator. The findings show that financial literacy (β = 0.76, p < 0.001) and financial socialization (β = 0.23, p < 0.001) significantly increase FinTech usage. While financial literacy does not directly affect green financial literacy (β = −0.13, p > 0.05), FinTech usage has a strong positive impact (β = 0.88, p < 0.001), indicating a full mediation effect. Bootstrapping results further confirm the robustness of the mediation effects. Financial socialization also has a direct positive effect (β = 0.20, p < 0.01). The results suggest that financial knowledge alone is insufficient to support sustainability-oriented financial awareness unless it is supported by digital financial technologies. The study highlights the key role of FinTech in facilitating the integration of financial knowledge and social learning into sustainability-oriented financial awareness and decision-making and offers practical implications for promoting sustainable finance.
AtıfOpenAlex1İncele - MakaleYalnız künye2026Scopus SJRQ1Multi-scale deep fusion architecture for brain tumor detection via local-contextual feature integration
Reis, Hatice Catal; Turk, Veysel
Early detection of brain tumors is crucial for enhancing treatment strategies and improving clinical prognosis. However, current conventional methods limit diagnostic accuracy and slow down diagnostic processes due to subjective interpretations and dependence on experts. Deep learning-based approaches have the potential to enhance diagnostic accuracy and facilitate early diagnosis by mitigating current limitations in automatic learning techniques for feature extraction and modeling processes. In this study, an advanced deep learning model, Multi-Scale Local-Context Fusion Network (MSLCFNet), is proposed for automatic diagnosis of brain tumors within the scope of oncological diseases. The proposed model evaluates local spatial features, global patterns, and long-range contextual relationships holistically through multi-layered representations, enabling effective identification of complex structures of tumor morphology. This architecture has the potential to increase diagnostic consistency and minimize the risk of misdiagnosis by reducing inter-observer variability, especially in cases where limited contrast and unclear boundaries lead to diagnostic uncertainty. The proposed model achieved accuracy rates of 96.51% and 98.17% on two different MRI brain tumor datasets, respectively. Additionally, a hybrid model based on MSLCFNet+ResNet50 was proposed in the study to obtain high-level feature representations for brain tumor diagnosis. The model offers a significant improvement in the diagnosis process by reducing misdiagnosis rates to 98.86% and 99.50% accuracy. The proposed methods make a significant contribution to enhancing diagnostic accuracy in clinical decision support systems, as they enable the efficient processing of complex morphological structures.
- MakaleAçık Erişim2026Scopus SJRQ2Synthesis, Characterization, Biological Properties, and Sensor Applications of Novel Thiosemicarbazone Derivatives
Gezegen, Hayreddin; Özbek, Oguz; Topal, Meryem; Şahin, Hatice; Koçyiğit, Ümit M.
In this study, novel thiosemicarbazone derivative molecules (5a–j) were synthesized. The characterization of the synthesized molecules was carried out using 1H–, 13C–NMR, FT–IR, and Q–TOF spectroscopic techniques. Then, the inhibitory effect of these compounds was examined for human carbonic anhydrase I and II (hCA I, and II) and acetylcholinesterase (AChE). The hCA I II, and AChE were efficiently inhibited by synthesized thiosemicarbazone derivatives, with Ki values in the range of 0.293–1.666 µM for hCA I, 0.298–1.332 µM for hCA II, and 52.51–138.63 µM for AChE, respectively. Finally, the sensor properties of the synthesized thiosemicarbazone derivatives were investigated. The newly synthesized thiosemicarbazone derivative molecules exhibited high selectivity towards Pb2+ ions. The sensor prepared with 5a from these molecules had a Nernstian behavior of 28.8 ± 1.5 mV/decade and a low detection limit of 2.86 × 10−6 M in a wide concentration range of 1.0 × 10−1–1.0 × 10−5 M. The newly proposed sensor also had a wide pH working range (5.0–10.0), a very fast response time (5 s), and good reproducibility. The newly fabricated sensors were used as indicator electrodes for the potentiometric titration of Pb2+ ions with ethylenediaminetetraacetic acid (EDTA) and were successfully applied for the determination of Pb2+ ion content in different water samples.
AtıfScopus7WoS7OpenAlex5İncele - MakaleYalnız künye2026Scopus SJRQ3Burned area detection using Sentinel-1 and Sentinel-2 features and analysis of ensemble models with explainable AI
Günen, Mehmet Akif; Türk, Salih
Wildfires are serious environmental disasters that threaten ecosystem sustainability, reduce biodiversity, and disrupt the global carbon cycle. This study aimed to improve the accuracy and interpretability of burned area mapping in the Bodrum, Köyceğiz, and Marmaris districts of Muğla province, Türkiye, by integrating multi-sensor satellite data with ensemble machine learning and explainable artificial intelligence (XAI). Sentinel-1 and Sentinel-2 imagery were processed to derive 50 optical and radar-based features, which were classified using four ensemble methods: AdaBoost.M1, Random Forest, GentleBoost, and RUSBoost. The SHapley Additive exPlanations framework was applied to quantify the contribution of each feature and guide feature selection. Results indicated that Sentinel-2 spectral indices, particularly NBR, NBRSWIR, and bands B12 and B8, were the most decisive variables for burned area classification, while Sentinel-1 features contributed less strongly overall but the IVH_ratio variable emerged as the most informative radar-based indicator. Among the classifiers, AdaBoost.M1 achieved the most stable and accurate performance, Random Forest showed strong sensitivity to spectral variability, GentleBoost performed effectively with reduced feature sets, and RUSBoost addressed class imbalance but showed weaker spatial continuity. Importantly, classification accuracy saturated after approximately 15 features, demonstrating that high accuracy can be achieved with fewer inputs and lower computational demand. Moreover, McNemar’s statistical test confirmed that the observed differences among classifiers were significant, highlighting GentleBoost’s clear superiority over other methods. Overall, the integration of optical and radar data with XAI provides a transparent, efficient, and replicable framework for operational burned area monitoring in Mediterranean ecosystems.
AtıfScopus2WoS3OpenAlex2İncele - MakaleAçık Erişim2026Scopus SJRQ1Factors affecting hospital personnel’s disaster management performance
Kaya, Burak; Mızrak, Sefa
Background: Hospital personnel with strong disaster management skills will work effectively and efficiently during disasters, ensuring better health services for staff, patients, and injured individuals. Purpose: This study aimed to investigate the factors affecting the hospital personnel disaster management performance (HPDMP) of Giresun Training and Research Hospital (Türkiye) according to the opinions of all hospital personnel. Method: In this study, survey data were collected from 797 hospital personnel between July and August 2023. HPDMP was employed as a dependent variable. Demographic characteristics, working conditions of personnel, disaster education, awareness of hospital disaster plans, and hospital disaster plan duty were used as independent variables. In addition, the arrangement of the hospital in relation to disaster risks, personnel self-efficacy, personnel coordination, coordination with other institutions, and disaster preparedness were also employed as independent variables. Results: The hospital’s disaster management performance was good. Personnel who received sufficient disaster education and had more knowledge about hospital disaster plans believed that HPDMP was greater. According to hospital personnel, disaster preparedness and coordination with other institutions were the factors that most strongly increased HPDMP. Conclusion: This study will provide insight for scientists, decision makers, and practitioners working in the field of hospital disaster planning and management.
- MakaleYalnız künye2026Scopus SJRQ2Financial Simulation of Remote Healthcare Implementation Strategies in Türkiye: A Monte Carlo Analysis Based on Specialty-Specific Eligibility
Demir, Hüseyin; Akar, Tuncay; Mertoğlu, Süleyman; Burmaoğlu, Serhat; Tekinarslan, Merve
The expansion of universal health coverage in Türkiye has intensified pressure on public healthcare providers through high outpatient volumes that strain capacity and financial sustainability. Remote healthcare delivery has emerged as a potential strategy to improve efficiency and access. However, limited evidence exists on how remote outpatient care should be implemented across medical specialties within a universal payer system, or how alternative implementation strategies perform financially. This study evaluates the specialty-specific feasibility and financial impact of remote outpatient care using comprehensive administrative data from a large public training and research hospital in Izmir, supplemented by qualitative input from clinical specialists. The analysis includes 577,984 outpatient visits recorded in 2022 across major medical specialties. Eligibility for remote delivery is identified using observable clinical proxies—imaging requests, laboratory tests, and prescription issuance—to capture visits not requiring physical examination or procedural intervention. Results show that 121,248 visits (21.0%) are suitable for remote delivery, accounting for 16.2% of expenditures ($0.68 million out of $4.20 million). Remote eligibility varies substantially across specialties, with high suitability in dermatology and infectious diseases but limited applicability in device-dependent fields such as pulmonology. Four implementation scenarios are simulated over a 10-year horizon: Regulatory Compliance, Evidence-Based Specialty-Specific, Follow-Up Only, and Hybrid Progressive. The Regulatory Compliance scenario yields the shortest break-even period (3 years) and highest ROI (1185%). The Hybrid Progressive scenario, incorporating phased specialty expansion and AI-supported triage, requires higher upfront costs but generates the largest cumulative net savings ($1.39 million). The findings demonstrate that financially sustainable remote outpatient care can be achieved through carefully designed, specialty-specific implementation strategies.
- MakaleAçık Erişim2026Scopus SJRQ3Investigation of Noise Exposure Levels in Furniture Industry: The Impact of Enterprise Scale and Machine Operational States; [Istraživanje razina izloženosti buci u industriji namještaja: utjecaj veličine poduzeća i radnih stanja strojeva]
Öztürk, Erhan; Komut, Osman; Fidan, Muhammed Said
The furniture industry is characterized by the intensive use of cutting, shaping, and surface-treating machinery, which naturally generates high noise levels. This study aimed to assess noise exposure levels in furniture manufacturing facilities by examining the effects of enterprise scale, machine types, and working conditions (loaded and unloaded) on occupational health and safety (OHS). The study was conducted in a total of 30 enterprises, 10 at each enterprise scale level. Physical risk factor data for noise were recorded using on-site measurements for the machines and production lines used at each enterprise level, depending on various variables. ANOVA, T-test, and Correlation analyses were performed to determine the relationships between the variables. The results revealed that small-scale businesses were the riskiest group in terms of noise levels. Generally, although measured noise levels in workplaces remain below the highest exposure action value of 85 dB, critical levels have been detected under specific machinery and working conditions. In machine-based assessments, the critical machines exceeding the highest exposure value of 85 dB are: In small-scale businesses – planing machine (95.26 dB), circular saw (88.08 dB) and band saw (86.81 dB); in micro-scale businesses – CNC drilling machine (91.13 dB), CNC sizing machine (88.01 dB) and band saw (85.95 dB); and in medium-scale businesses – circular saw (85.24 dB). As a result of the study, it has been emphasized that long-term noise exposure poses a risk to employees’ hearing health and that preventive measures are therefore mandatory.
- Derleme MakaleYalnız künye2026Scopus SJRQ2Activated Carbon Derived from Coal and its Application for Wastewater Treatment
Daulay, Amru; Yassaroh, Yassaroh; Huda, Miftahul; Sumardi, Slamet; Prasetia, Hendra; Kumaş, Cavit; Yusmiati; Lestari, Devi
Coal is used to produce fuels, chemicals, and other high-value-added products to improve efficiency. Activated carbon (AC) derived from coal is an important part of coal’s resource utilization and is high-value-added. This study presents relevant research on AC derived from coal, including raw material selection, preparation methods, modification techniques, and regeneration methods. The potential applications of AC derived from coal for the adsorption of contaminants, including heavy metals, pesticides, pharmaceutical compounds, and organic and inorganic compounds, are reviewed. One of the advantages of using AC derived from coal in wastewater treatment is high adsorption, low cost, and sustainability.
- MakaleAçık Erişim2026Scopus SJRQ2Real maritime measurement-driven machine learning for path loss modeling in shore-to-ship wireless links
Sağır, Nuğman; Eyüboğlu, Ekrem; Kuzulugil, Kenan; Tuğcu, Zeynep Hasırcı; Çavdar, İsmail Hakkı
Reliable propagation modeling remains a fundamental requirement for the design and deployment of maritime wireless communication systems, particularly in shore-to-ship scenarios characterized by highly variable environmental conditions. Unlike conventional empirical and deterministic models that rely on theoretical assumptions, the proposed approach is entirely measurement-driven, enabling more accurate and robust propagation modeling. Four regression algorithms—Gaussian Process Regression, Least Squares Boosting, Decision Tree, and Support Vector Regression—are evaluated using a feature set that includes transmission distance, sea state, weather conditions, and antenna configurations. Among the tested models, the Decision Tree achieves the best performance, with an RMSE of 1.18 dB and an R2 of 0.96, corresponding to an error reduction of approximately 45.6% compared to the best-performing empirical model. Feature importance analysis shows that transmission distance and antenna geometry dominate signal attenuation, while environmental variables have a limited influence at this frequency. Unlike most existing studies that emphasize deep learning or black-box models, this work demonstrates that lightweight and interpretable regression models can achieve comparable accuracy while enabling real-time link planning and practical deployment. The focus is on engineering applicability rather than proposing new learning architectures. Overall, the results indicate that measurement-driven machine learning provides accurate and interpretable solutions for shore-to-ship path loss modeling under real maritime conditions.
- Kitap BölümüYalnız künye2026Catalytic Nanocomposites in Oxidative on Adsorptive Delsulfurization Process: A Comprehensive Review
Altuner, Elif Esra; Bozbeyoglu, Pinar; Özkan, Vildan; Ozkan, Abdullah
Humanity's need for energy is an undeniable fact, and this reality is increasing day by day. To meet its growing energy needs, humanity has turned to fossil fuels. Fossil fuels are fuels derived from animal and plant fossils formed over millions of years. However, the excessive use of fossil fuels for energy needs has created a dangerous situation that threatens to deplete fossil fuel reserves. Furthermore, the burning of fossil fuels releases toxic emissions. These emissions cause serious health problems for living organisms and also harm the ecosystem. These gases include sulfate (SO2) and sulfur derivatives, carbon dioxide (CO2), carbon monoxide, and nitrogen oxide derivatives (NOx). This chapter focuses on catalytic techniques using nanocomposite materials for the removal of SO2 and sulfur derivatives, with detailed references to relevant sources. SO2 and sulfur gases are harmful gases released by the combustion of fossil fuels. Nanocomposite production methods include sol- gel formation, gel shaping, chemical vapor deposition (CVD), and physical vapor deposition (PVD), layered production, electrospinning, mechanical and ultrasonic techniques, additive manufacturing, and melting mixture. Desulfurization processes using these methods are as follows: (i) oxidative desulfurization, photocatalytic desulfurization, and absorptive- catalytic desulfurization. All techniques are explained with references to the relevant sources. This chapter provides theoretically important information for researchers working on nanotechnological catalytic studies in desulfurization.
AtıfScopus2OpenAlex1İncele - Kitap BölümüYalnız künye2026Control Tower-Driven Multi-Echelon Inventory Positioning in Pharmaceutical Supply Chains
Şimşek, Ahmet Bahadır; Şimşek, Aybala
Pharmaceutical supply chains face high shortage risk when demand uncertainty interacts with lead-time variability, while shelf-life limits, cold-chain requirements, and quality-release delays raise the cost of both stockouts and excess inventory. This chapter proposes a control tower–driven decision-support framework for multi-echelon inventory positioning that converts visibility into actionable policies. A multi-echelon optimization module generates candidate target-stock and reorder policies across manufacturing and distribution echelons. Monte Carlo–based scenario analysis tests robustness under demand, lead-time, and disruption uncertainty. An MCDA layer then ranks policies using total cost, service level, shortage probability, expediting intensity, days of supply, and recovery time, with sensitivity analysis when weights are uncertain. The framework provides a signal-to-decision map, event-triggered policy updates, and a compact metric dictionary for shortage-risk management without proprietary field data.
- MakaleAçık Erişim2026Scopus SJRQ1Does Training Make a Difference? Evaluating a Targeted Child Abuse and Neglect Education Program on Teachers’ Awareness
Türkkan, Tuğba; Odacı, Hatice
This study examined the effect of a psycho-education program on the awareness levels of teachers regarding child abuse and neglect. The study was conducted with teachers working in regions characterized by the presence of at-risk groups. Within the scope of the study, 18 teachers were assigned to the experimental group and 18 teachers to the control group. The experimental group participated in a structured psycho-education program on child abuse and neglect, while no intervention was implemented for the control group. Prior to the intervention, pre-test measurements were conducted using the Child Abuse Awareness Scale for both groups. The psycho-education program consisted of 10 weekly online sessions, each lasting approximately 100–120 min. The findings revealed a significant difference between the pre-test and post-test scores of the experimental group compared with the control group, indicating the effectiveness of the psycho-education program in increasing teachers’ awareness levels. The results suggest that such training programs may play an important role in enhancing teachers’ knowledge and awareness of child abuse and neglect, particularly in recognizing signs of abuse and understanding reporting procedures.
- Derleme MakaleAçık Erişim2026Scopus SJRQ1Postbiotics in Dairy: A Comprehensive Review of Applications and Health Impacts
Kaya, Yasemin; Aktaş, Haktan; Meral-Aktaş, Hacer; Ürkek, Bayram; Gürbüz-Kaçan, Zeynep; Çiftçi, Esengül; Erkaya-Kotan, Tuba; Şengül, Mustafa; Çetin, Bülent
Purpose of Review: This review aims to provide a comprehensive overview of postbiotics—defined as non-viable microbial cells, cell components, and microbial metabolites—and their emerging role in dairy products. It focuses on their functional, technological, and health-promoting properties in various dairy matrices, including yoghurt, cheese, kefir, fermented milk, and ice cream. Additionally, the review highlights the potential of postbiotics as stable and safe alternatives to probiotics in the development of functional dairy foods. Recent Findings: Recent evidence demonstrates that postbiotics such as exopolysaccharides (EPS), bacteriocins, short-chain fatty acids (SCFAs), bioactive peptides, and organic acids significantly enhance both the nutritional value and technological quality of dairy products. These compounds have been shown to improve texture, sensory attributes, shelf life, and microbial safety while exerting biological activities, including antimicrobial, antioxidant, immunomodulatory, and gut health–promoting effects. Compared with probiotics, postbiotics offer greater stability during processing and storage as well as reduced safety concerns, particularly for vulnerable populations. Summary: Postbiotics represent a promising strategy for advancing functional and sustainable dairy products by combining health benefits with technological improvements. Their applications in functional food formulation, biopreservation, and bioactive compound delivery are rapidly expanding. However, challenges remain regarding standardised production processes, accurate quantification of bioactive components, and clinical validation of health claims. Future research should focus on optimising postbiotic production and strengthening evidence for their physiological effects to support their broader incorporation into next-generation dairy products.
AtıfScopus3WoS3OpenAlex4İncele - MakaleYalnız künye2026Scopus SJRQ2In sepsis-associated cardiotoxicity, remifentanil reduces oxidative stress, inflammation, and apoptosis to maintain mitochondrial biogenesis by inhibiting NFkB and cas-3 immunoexpressions and enhancing SIRT1 upregulation
Tepebaşi, Muhammet Yusuf; Aşci, Halil; Selçuk, Esma; Uysal, Dinçer; Bindal, Ahmet; Yüksel, Duygu; Özmen, Özlem
Objective: Sepsis-induced cardiotoxicity (SIC) is a critical complication characterized by inflammation, oxidative stress, and apoptosis, leading to myocardial dysfunction. The short-acting opioid analgesic remifentanil (REMI) possesses antioxidant and anti-inflammatory properties. This study aimed to evaluate the cardioprotective effects of REMI on lipopolysaccharide (LPS)-induced SIC by examining inflammation, oxidative stress, apoptosis, and mitochondrial function. Materials and methods: Thirty-two female Wistar albino rats were divided into four groups: control, lipopolysaccharide (LPS), LPS+REMI, and REMI. Myocardial and aortic tissues were analyzed for histopathology, immunoexpression of Caspase-3 (Cas-3), nuclear factor kappa beta (NF-κB), and tumor necrosis factor alpha (TNF-α). Oxidative stress markers, including total oxidant status (TOS), total antioxidant status (TAS), and oxidative stress index (OSI), were measured. Mitochondrial apoptosis-related gene expression of AMP-activated protein kinase (AMPK), BCL2 Associated X (BAX), B-cell lymphoma 2 (BCL-2), Sirtuin 1 (SIRT1), and Peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α) was assessed. Results: LPS administration induced severe histopathological damage, increased oxidative stress (elevated TOS and OSI), and upregulated apoptotic (Cas-3, BAX/BCL-2 imbalance) and inflammatory (NF-κB, TNF-α) markers. REMI treatment significantly alleviated myocardial and aortic injury, reducing the histopathological score. It markedly decreased Cas-3, NF-κB, and TNF-α expression, lowered TOS and OSI levels, and modulated the BAX/BCL-2. Furthermore, REMI restored the expression of AMPK, SIRT1, and PGC-1α genes, indicating a protective effect on mitochondrial biogenesis and energy metabolism. Conclusions: REMI exhibits significant cardioprotective effects in LPS-induced SIC by attenuating inflammation, oxidative stress, and apoptosis while preserving mitochondrial homeostasis.
AtıfScopus2WoS2OpenAlex1İncele - MakaleAçık Erişim2025Scopus SJRQ2Enzyme inhibitory, antioxidant, antimicrobial activities, and phenolic profiles of the methanol extract of Gelasia sericea an endemic species
AYGÜL, İmdat; AKMEŞE, Osman; SEFALI, Abdurrahman; BALTACI, Cemalettin; ÖZ, Mehmet; FIDAN, Muhammed Said
This study aimed to investigate, for the first time, the phytochemical composition, antioxidant, antimicrobial, and enzyme inhibitory properties of the methanolic extract of Gelasia sericea (Aucher ex DC.) Zaika, Sukhor. & N.Kilian. The extract demonstrated a moderate yield (6.55 g/100 g dry plant material) and was found to be rich in phenolic acids, particularly ferulic acid (17182.97 μg g-1), followed by caffeic acid, protocatechuic acid, and p-coumaric acid. Antioxidant analyses revealed high total phenolic (388.86 mg GA eq./100 g), total flavonoid (74.03 mg QE eq./100 g), and total antioxidant capacity (503.33 mg AA eq./100 g). The extract exhibited remarkable ABTS radical scavenging activity (95.99%, IC50 = 37.59 mg ml-1) and considerable ferric-ion reducing power (974.78 mg FeSO4 eq./100 g). Antimicrobial assays indicated moderate inhibitory effects, with stronger activity against Gram-positive bacteria (Staphylococcus aureus, Enterococcus faecalis) and the yeast Candida albicans, whereas Gram-negative bacteria were less susceptible. The extract’s MIC values ranged between 0.20-3.25 mg ml-1, and MLC values between 0.41-6.50 mg ml-1, which were higher than those of standard antibiotics. Enzyme inhibition assays revealed moderate activity against carbonic anhydrase II (IC50 = 0.0136 µg ml-1) and weak inhibition of cholinesterases and α-glucosidase, while α-amylase inhibition was relatively more pronounced (IC50 = 13350.00 µg ml-1). Overall, these findings highlight G. sericea as a valuable natural source of phenolic acids and antioxidants, with promising potential for applications in functional foods, nutraceuticals, and phytopharmaceuticals. However, the relatively limited antimicrobial and enzyme inhibitory activities suggest the need for further studies on bioavailability, in vivo efficacy, and compound isolation to optimize its practical applications.
- MakaleAçık Erişim2026Scopus SJRQ2Effects of psychosocial interventions on sexual function, quality of life, and stress in women with gynecologic cancer: a systematic review and meta-analysis
Aydın, Esra; Özcan, Handan; Karakaş, Sevda; Uzun, Sevda
Objectives: To evaluate the effects of psychosocial interventions on sexual function, quality of life, and stress levels in women with gynecologic cancer. Methods: This systematic review and meta-analysis was conducted in accordance with the PRISMA 2020 guidelines. PubMed, Web of Science, EBSCOhost, Google Scholar, and the YÖK Thesis Center were searched between June and July 2024 without year restriction. Randomized controlled and quasi-experimental studies evaluating psychosocial interventions were included. Data were synthesized using meta-analysis and narrative synthesis. Outcomes were synthesized separately for sexual function, quality of life, and stress. Results: Seven studies were included in the analysis. Psychosocial interventions significantly improved sexual function (SMD: 0.868; 95% CI: 0.021 to 1.715; Z = 2.008; p = 0.045; I2 = 89.97%) and quality of life (SMD: 0.709; 95% CI: 0.060 to 1.358; Z = 2.142; p = 0.032; I2 = 88.61%) in women with gynecologic cancer. However, psychosocial interventions did not demonstrate a significant effect on stress levels (SMD: − 1.126; 95% CI: − 2.649 to 0.397; Z = − 1.449; p = 0.147; I2 = 95.65%). Conclusion: This systematic review and meta-analysis indicates that psychosocial interventions are associated with improvements in sexual function and quality of life among women with gynecologic cancer, whereas no statistically significant reduction in stress was observed. Although substantial between-study heterogeneity was present, the overall evidence supports the integration of psychosocial approaches into supportive oncology nursing care.
AtıfScopus1WoS1OpenAlex1İncele - MakaleYalnız künye2026Scopus SJRQ3Synthesis, antioxidant, and antiurease activities of novel benzimidazole-based 1,3,4-thiadiazole derivatives
Gümrükçüoğlu, Taner İlker; Akgün, Hakan; Bektaş, Hakan; Sökmen, Bahar Bilgin; Menteşe, Emre
In this study, we report the synthesis and characterisation of five new benzimidazole-based 1, 3, 4-thiadiazole derivatives (5a–e) and the evaluation of their antioxidant and antiurease activities. The structures were confirmed by NMR (1H, 13C) and LC/TOF–MS analyses (spectra are given in the supplementary information). Biological assays (DPPH, ABTS, iron-reducing power, urease inhibition) revealed that compound 5e (bearing a 4-nitrophenyl substituent) exhibited the strongest urease inhibition (EC50 = 0.1296 ± 0.0260 µM), surpassing thiourea. One-way ANOVA revealed significant differences in urease inhibition between the compounds (p<0.001). Post-hoc Tukey tests confirmed that compound 5e was more effective than several other compounds. The compounds exhibited moderate and comparable antioxidant activities. The first SAR study shows that electron-withdrawing substituents increase urease inhibition, whereas electron-donating groups increase the reducing power. Comparison with earlier reported triazole analogues shows scaffold-dependent changes in bioactivity. These findings support thiadiazoles as promising dual-function agents for oxidative stress and urease-associated pathologies.
- MakaleYalnız künye2026Scopus SJRQ1A reliability generalization meta-analysis of job insecurity scales: Evidence from hospitality and tourism research
Polat, Eray
The study examines the pooled reliability estimates of job insecurity (JI) scales employed in hospitality and tourism (H&T) research. By synthesizing reported reliability coefficients and identifying moderators influencing score consistency, this meta-analytic study consolidates the fragmented psychometric evidence in the field. Reliability coefficients were derived from 140 independent samples comprising 56,265 respondents. Pooled reliability estimates were calculated separately for each scale, and moderator analyses were performed to explain the variability. Findings indicate that De Witte's (2000) scale is the most frequently utilized scale. Pienaar et al.’s (2013) scale yielded the highest estimate (α=.94, 95% CI [.89.,97]), whereas Hellgren and Sverke's (2003) scale demonstrated the lowest (α=.82, 95% CI [.78.,85]). Moderator analyses revealed that scale version, publication year, number of items, sample size, scale mean, and gender distribution significantly influenced reliability estimates. The study provides robust, context-dependent evidence to inform the selection of JI scales.
