WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article Anticancer Properties of Newly Synthesized Pyrrole Derivatives as Potential Tyrosine Kinase Inhibitors(Wiley, 2026) Kaya, Meltem; Kara, Yunus; Sanli-Mohamed, GulsahThe anticancer activity of a series of newly synthesized pyrrole derivatives was systematically evaluated in HeLa cervical cancer cells, focusing on their potential as tyrosine kinase inhibitors and modulators of the mTOR signaling pathway. This study builds on our previous synthetic work by investigating the biological effects of seven structurally characterized compounds (d1-d7). Among them, compounds d1 and d3 exhibited the most potent cytotoxicity, with IC50 values of 140.6 mu M and 366.4 mu M, respectively, after 48 h of treatment. Both compounds significantly impaired cell cycle progression-d1 induced S-phase arrest, while d3 caused G1-phase arrest-and markedly suppressed cell migration in wound healing assays. Mechanistically, these effects were accompanied by reduced phosphorylation of p70S6K (Thr389, Ser421/424) and increased p-4EBP1, indicating inhibition of mTORC1 signaling. These findings suggest that d1 and d3 are promising lead compounds with dual antiproliferative and anti-migratory activity in cervical cancer, mediated through modulation of the PI3K/Akt/mTOR axis.Article Liposomal Encapsulation of a Synthetic Bromophenol for Antitumor Efficacy and Apoptotic Activity in Cancer Cells(Springer, 2026) Oztanrikulu, Bercem Dilan; Ozdemir, Ekrem; Avci, Bahri; Goksu, Suleyman; Bayrakceken, Handan Uguz; Askin, HakanA novel synthetic bromophenol (BP), inspired by marine-derived natural bromophenols, was evaluated for its antitumor activity and for the enhancement of its in vitro performance through liposomal encapsulation (LipoBP). Etoposide was used as a reference in characterization, release, and loading studies. PEGylated liposomes were employed to improve BP's solubility, bioavailability, and therapeutic potential. The cytotoxicity, apoptosis, and gene expression effects of free BP and LipoBP were assessed in A549 (lung) and MCF-7 (breast) cancer cell lines. WST-8 assays showed that encapsulation significantly increased BP's cytotoxic activity, particularly in A549 cells, while flow cytometry and Annexin V-FITC/PI analyses indicated more pronounced apoptotic induction by LipoBP compared with free BP. qRT-PCR analyses revealed upregulation of proapoptotic genes (BAX, CASP6, CASP3 and CASP9) and downregulation of antiapoptotic/survival genes (BCL-XL, IQSEC2) in both cell lines, indicating activation of intrinsic apoptotic pathways. Plain liposomes exhibited minimal cytotoxicity, confirming their biocompatibility. Liposomal bromophenol, which we have introduced to the literature for the first time, is expected to be a promising nanocarrier system that could be effective in cancer treatment by improving the therapeutic index of new drug candidates such as marine bromophenols.Article Robust Scheduling of Crude Oil Farming and Processing Under Uncertainty(Elsevier, 2026) Yalcin, Damla; Sildir, HasanThe sulphur content in crude oil has a significant impact on refinery operations, influencing the feasibility of crude blending, the distribution of product yields, and overall economic performance. Variations in sulphur content introduce uncertainty in the short-term scheduling of crude oil loading, blending, and distillation processes. This study introduces a scenario-based stochastic optimization framework in which sulphur uncertainty is treated as a central modeling element, represented through a regression-based relationship with specific gravity (SG). The approach systematically propagates uncertainty through blending decisions, crude distillation unit (CDU) feed composition, and product yields. The problem is modeled as a mixed-integer quadratically constrained programming (MIQCP) formulation within a continuous-time scheduling framework, enabling the simultaneous optimization of timing, blending, and processing strategies. The results indicate that increased sulphur uncertainty adversely affects the distribution of yields for nine end-products, resulting in profit losses. These findings underscore the importance of explicitly managing compositional uncertainty and provide insights into cost-performance trade-offs in refinery scheduling.Article Fluid-CO2 Injection in a Hypersaline Volcanic Systems: A Reactive Transport and Experimental Evaluation with Application to the Tuzla Geothermal Field, Turkiye(Springer, 2026) Tonkul, Serhat; Erol, Selcuk; Baba, Alper; Regenspurg, SimonaThis study evaluates the CO2 sequestration capability of the Tuzla Geothermal Field (TGF) in northwest T & uuml;rkiye under reservoir conditions (200 degrees C and 4.4 MPa). While ongoing studies at TGF have investigated CO2 co-injection primarily for geothermal heat extraction, the present study focuses on the associated potential for long-term CO2 storage. To this end, CO2-brine-rock interactions were examined through batch reactor experiments and reaction path modeling using the PhreeqC geochemical tool. The experiments revealed complex dissolution/precipitation reactions that altered reservoir properties, with mineralogical analyses (XRD, XRF, SEM, and EDS) showing the formation of secondary phases such as calcite, kaolinite, and Ca-rich aluminosilicates. These results indicate that the Tuzla reservoir rocks provide sufficient divalent cations to support mineral trapping under reservoir conditions. Overall, our findings highlight that, in addition to its promise for heat extraction, CO2 co-injection at TGF offers an opportunity for permanent geological storage, thereby strengthening the dual benefits of this approach.Article Mn2+ Removal From Water Using a Strong Acidic Shallow Shell Resin: Performance and Response Surface Optimization(Springer, 2026) Gucur, G.; Recepoglu, Y. K.; Ozcan, D. O.; Arar, O.The removal of manganese ions (Mn2+) from aqueous solutions using a strong acid cation-exchange resin, Purolite SST60, was investigated in the present study. The influences of resin dosage, temperature, and pH on Mn2(+) removal were optimized using Response Surface Methodology based on a Central Composite Design. Results showed that removal efficiency was highly pH-dependent, increasing from 63% at pH 1.0 to over 99% at pH 3.0 and above. Even with only 0.01 g of resin, 98% removal was achieved, indicating high performance at low dosages. Equilibrium data aligned with the Langmuir isotherm, indicating monolayer sorption with a maximum capacity of 91.06 mg/g. Kinetic data followed a pseudo-second-order model. Thermodynamic analysis confirmed a spontaneous and exothermic process, supported by a negative enthalpy change and positive entropy change, likely due to dehydration of Mn2+ ions upon binding. Competitive ion studies revealed that divalent ions, particularly calcium and magnesium, significantly hinder Mn2+ removal, whereas monovalent ions had minimal impact. Complete desorption of Mn2+ was achieved using hydrochloric or nitric acid at concentrations of 0.5 mol/L and above, confirming the resin's reusability. Overall, Purolite SST60 offers an efficient, regenerable, and robust solution for manganese removal in water treatment applications.Correction Development of Tissue-Engineered Vascular Grafts from Decellularized Parsley Stems (Vol 20, Pg 338, 2024)(Royal Society Chemistry, 2024) Cevik, Merve; Dikici, SerkanArticle A Physics-Informed Neural Network (PINN) Approach to Over-Equilibrium Dynamics in Conservatively Perturbed Linear Equilibrium Systems(MDPI, 2025) Dutta, Abhishek; Mukherjee, Bitan; Hosen, Sk Aftab; Turan, Meltem; Constales, Denis; Yablonsky, GregoryConservatively perturbed equilibrium (CPE) experiments yield transient concentration extrema that surpass steady-state equilibrium values. A physics-informed neural network (PINN) framework is introduced to simulate these over-equilibrium dynamics in linear chemical reaction networks without reliance on extensive time-series data. The PINN incorporates the reaction kinetics, stoichiometric invariants, and equilibrium constraints directly into its loss function, ensuring that the learned solution strictly satisfies physical conservation laws. Applied to three- and four-species reversible mechanisms (both acyclic and cyclic), the PINN surrogate matches conventional ODE integration results, reproducing the characteristic early concentration extrema (maxima or minima) in unperturbed species and the subsequent relaxation to equilibrium. It captures the timing and magnitude of these extrema with high accuracy while inherently preserving total mass. Through the physics-informed approach, the model achieves accurate results with minimal data and a compact network architecture, highlighting its parameter efficiency.Article K41-A Enhances the Antiproliferative Efficacy of Cisplatin in Neuroblastoma by Modulating Apoptosis and Autophagy(Oxford University Press, 2026) Sanlav, Gamze; Kum Ozsengezer, Selen; Altun, Zekiye; Bedir, Erdal; Aktas, Safiye; Olgun, NurObjectives Neuroblastoma (NB), the most common extracranial tumor in childhood, has a poor prognosis, especially in cases with MYC gene amplification. Cisplatin (CDDP) is widely used in treatment, but its effectiveness is limited due to chemotherapy resistance. Autophagy plays a dual role in cancer progression, either promoting survival or contributing to cell death.Methods This study explores the anticancer effects of K41-A, a polycyclic polyether molecule, alone and in combination with CDDP in SH-SY5Y and KELLY NB cell lines, the HE-IOC1 noncancerous cochlear cell line, and the NB xenograft model.Key findings For the first time, we demonstrate that K41-A, either alone or combined with CDDP, significantly inhibits cell proliferation selectively in NB cells, sparing noncancerous cells. This study confirmed that K41-A alone and in combination with CDDP induced changes in both apoptotic and autophagic cell death components in NB, resulting in antiproliferative activity in vitro and in vivo. In addition, the combination with CDDP enhanced the therapeutic efficacy of K41-A.Conclusions These results highlight the potential of K41-A as a candidate drug for the treatment of NB.Article Uncertainty Assessment of the Impacts of Climate Change on Streamflow in the Iznik Lake Watershed, Türkiye(MDPI, 2026) Tezel, Anil Caliskan; Akpinar, Adem; Bor, Asli; Elci, SebnemStudy region: This study focused on the Iznik Lake Watershed in northwestern T & uuml;rkiye. Study focus: Climate change is increasingly affecting water resources worldwide, raising concerns about future hydrological sustainability. This study investigates the impacts of climate change on river streamflow in the Iznik Lake Watershed, a critical freshwater resource in northwestern T & uuml;rkiye. To capture possible future conditions, downscaled climate projections were integrated with the SWAT+ hydrological model. Recognizing the inherent uncertainties in climate models and model parameterization, the analysis examined the relative influence of climate realizations, emission scenarios, and hydrological parameters on streamflow outputs. By quantifying both the magnitude of climate-induced changes and the contribution of different sources of uncertainty, the study provides insights that can guide decision-makers in future management planning and be useful for forthcoming modeling efforts. New hydrological insights for the region: Projections indicate wetter winters and springs but drier summers, with an overall warming trend in the study area. Based on simulations driven by four representative grid points, the results at the Karadere station, which represents the main inflow of the watershed, indicate modest changes in mean annual streamflow, ranging from -7% to +56% in the near future and from +19% to +54% in the far future. Maximum flows (Qmax) exhibit notable increases, ranging from +0.9% to +47% in the near future and from +21% to +63% in the far future, indicating a tendency toward higher peak discharges under future climate conditions. Low-flow conditions, especially in summer, exhibit the greatest relative variability due to near-zero baseline discharges. Relative change analysis revealed considerable differences in Karadere and Findicak sub-catchments, reflecting heterogeneous hydrological responses even within the same basin. Uncertainty analysis, conducted using both an ANOVA-based approach and Bayesian Model Averaging (BMA), highlighted the dominant influence of climate projections and potential evapotranspiration calculation methods, while land use change contributed negligibly to overall uncertainty.Article Advancing Hydrological Prediction With Hybrid Quantum Neural Networks: A Comparative Study for Mile Mughan Dam(MDPI, 2025) Abdi, Erfan; Sattari, Mohammad Taghi; Samadianfard, Saeed; Ahmad, SajjadPredicting dam inflow is critical for human life safety, water resource management, and hydroelectric power generation. While machine learning (ML) models address complex, nonlinear hydrological problems, quantum machine learning (QML) offers greater potential to overcome classical computational limits. This study compares a hybrid quantum neural network (HQNN) with the following two classical models: bidirectional CNN-LSTM and support vector regression (SVR). These models were evaluated to predict monthly inflow to the Mile Mughan Dam, a transboundary hydroelectric and irrigation dam located on the Aras River between Azerbaijan and Iran, using a 14-year dataset (2010-2023) under two scenarios. In total, 70% of data was used for training and 30% for testing. The first scenario encompassed meteorological variables plus three months of inflow lags, and the second included inflow lags only. Model performance was assessed using Coefficient of Determination (R2), Root Mean Squared Error (RMSE), Nash-Sutcliffe efficiency (NSE), Mean Absolute Percentage Error (MAPE), and graphical plots. HQNN showed superior performance across all metrics. In Scenario 1, HQNN achieved R2 = 0.915, RMSE = 37.318 MCM, NSE = 0.908, MAPE = 8.343%; CNN-BiLSTM had R2 = 0.867, RMSE = 46.506 MCM, NSE = 0.858, MAPE = 10.795%; SVR had R2 = 0.846, RMSE = 52.372 MCM, NSE = 0.821, MAPE = 12.772%. In Scenario 2, HQNN maintained strong performance (R2 = 0.855, RMSE = 48.56 MCM, NSE = 0.845, MAPE = 9.979%) and outperformed CNN-BiLSTM (R2 = 0.810, RMSE = 56.126 MCM, NSE = 0.793, MAPE = 11.456%) and SVR (R2 = 0.801, RMSE = 60.336 MCM, NSE = 0.761, MAPE = 12.901%). In Scenario 1 and Scenario 2, HQNN increased the prediction accuracy by 19.76% and 13.47%, respectively, compared to the CNN-BiLSTM model. These results confirm HQNN's reliability in both multivariate and univariate modeling.