PubMed İndeksli Yayınlar Koleksiyonu

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Citation - WoS: 1
Citation - Scopus: 1
Cinnamomum Zeylanicum Extract Incorporated Electrospun Poly(Lactic Acid)/ Gelatin Membrane as a New Wound Dressing
(Elsevier, 2025) Tarhan, Seray Zora; Pepe, Nihan Aktas; Sen, Alaattin; Isoglu, Ismail Alper
In this study, we fabricated poly(lactic acid)/gelatin electrospun membranes containing various concentrations of Cinnamomum zeylanicum extract and evaluated them as a novel wound dressing. The electrospun membranes were chemically, morphologically, and mechanically characterized, and the results were discussed in comparison with the literature. Electrospun membranes' biodegradability, swelling, and release properties were evaluated, with the CE7.5 membrane having values of 29.60 f 7.20 and 542.1 f 48.3 % and 66.9 %, respectively. Antibacterial activity was observed in CE7.5 and CE10 membranes against E. coli and S. aureus strains. At the highest concentration (CE10), 111.7 f 5.6 % and 96 f 12.375 % cell viability were detected in fibroblasts and differentiated LPS-induced THP-1 cells. Cell viability was further evaluated by Annexin-V/PI staining, revealing that 97.95 f 1.63 % of the cells remained viable in the CE7.5-treated membranes, while only 1.85 f 1.49 % of necrotic cells were detected in the treated cell population. Fibroblasts treated with the CE7.5 membrane showed a 42 % improvement in wound closure compared to non-treated cells. The anti-inflammatory properties of the electrospun membranes were also investigated. Treatment with the conditioned CE7.5 membrane downregulated Tba1 and tau proteins by 45.1 and 51.055 %, respectively. This study concluded that the newly developed Cinnamomum zeylanicum extract incorporated poly(lactic acid)/gelatin electrospun membranes could be a promising wound dressing material.
Citation - WoS: 29
Citation - Scopus: 41
Optimisation of the Reaction Conditions for the Production of Cross-Linked Starch With High Resistant Starch Content
(Elsevier Sci Ltd, 2015) Kahraman, Kevser; Koksel, Hamit; Ng, Perry K. W.
The optimum reaction conditions (temperature and pH) for the preparation of cross-linked (CL) corn and wheat starches with maximum resistant starch (RS) content were investigated by using response surface methodology (RSM). According to the preliminary results, five levels were selected for reaction temperature (38-70 degrees C) and pH (10-12) in the main study. RS contents of the CL corn and wheat starch samples increased with increasing temperature and pH, and pH had a greater influence on RS content than had temperature. The maximum RS content (with a maximum p value of 0.4%) was obtained in wheat starch cross-linked at 38 degrees C and pH 12. In the case of CL corn starch, the optimum condition was 70 degrees C and pH 12. CL corn and wheat starch samples were also produced separately under the optimum conditions and their RS contents were 80.4% and 83.9%, respectively. These results were also in agreement with the values predicted by RSM. (C) 2014 Elsevier Ltd. All rights reserved.
Citation - WoS: 35
Citation - Scopus: 35
Glucose-Dependent Anaplerosis in Cancer Cells Is Required for Cellular Redox Balance in the Absence of Glutamine
(Nature Portfolio, 2016) Cetinbas, Naniye Malli; Sudderth, Jessica; Harris, Robert C.; Cebeci, Aysun; Negri, Gian L.; Yilmaz, Oemer H.; Sorensen, Poul H.
Cancer cells have altered metabolism compared to normal cells, including dependence on glutamine (GLN) for survival, known as GLN addiction. However, some cancer cell lines do not require GLN for survival and the basis for this discrepancy is not well understood. GLN is a precursor for antioxidants such as glutathione (GSH) and NADPH, and GLN deprivation is therefore predicted to deplete antioxidants and increase reactive oxygen species (ROS). Using diverse human cancer cell lines we show that this occurs only in cells that rely on GLN for survival. Thus, the preference for GLN as a dominant antioxidant source defines GLN addiction. We show that despite increased glucose uptake, GLN addicted cells do not metabolize glucose via the TCA cycle when GLN is depleted, as revealed by C-13-glucose labeling. In contrast, GLN independent cells can compensate by diverting glucose-derived pyruvate into the TCA cycle. GLN addicted cells exhibit reduced PDH activity, increased PDK1 expression, and PDK inhibition partially rescues GLN starvation-induced ROS and cell death. Finally, we show that combining GLN starvation with pro-oxidants selectively kills GLN addicted cells. These data highlight a major role for GLN in maintaining redox balance in cancer cells that lack glucose-dependent anaplerosis.
Citation - WoS: 53
Citation - Scopus: 59
Thickness-Tunable Self-Assembled Colloidal Nanoplatelet Films Enable Ultrathin Optical Gain Media
(Amer Chemical Soc, 2020) Erdem, Onur; Foroutan, Sina; Gheshlaghi, Negar; Guzelturk, Burak; Altintas, Yemliha; Demir, Hilmi Volkan
We propose and demonstrate construction of highly uniform, multilayered superstructures of CdSe/CdZnS core/shell colloidal nanoplatelets (NPLs) using liquid interface self-assembly. These NPLs are sequentially deposited onto a solid substrate into slabs having monolayer-precise thickness across tens of cm(2) areas. Because of near-unity surface coverage and excellent uniformity, amplified spontaneous emission (ASE) is observed from an uncharacteristically thin film having 6 NPL layers, corresponding to a mere 42 nm thickness. Furthermore, systematic studies on optical gain of these NPL superstructures having thicknesses ranging from 6 to 15 layers revealed the gradual reduction in gain threshold with increasing number of layers, along with a continuous spectral shift of the ASE peak (similar to 18 nm). These observations can be explained by the change in the optical mode confinement factor with the NPL waveguide thickness and propagation wavelength. This bottom-up construction technique for thickness-tunable, three-dimensional NPL superstructures can be used for large-area device fabrication.
Citation - WoS: 50
Citation - Scopus: 149
An Investigation on the Determinants of Carbon Emissions for OECD Countries: Empirical Evidence From Panel Models Robust to Heterogeneity and Cross-Sectional Dependence
(Springer Heidelberg, 2016) Dogan, Eyup; Seker, Fahri
This empirical study analyzes the impacts of real income, energy consumption, financial development and trade openness on CO2 emissions for the OECD countries in the Environmental Kuznets Curve (EKC) model by using panel econometric approaches that consider issues of heterogeneity and cross-sectional dependence. Results from the Pesaran CD test, the Pesaran-Yamagata's homogeneity test, the CADF and the CIPS unit root tests, the LM bootstrap cointegration test, the DSUR estimator, and the Emirmahmutoglu-Kose Granger causality test indicate that (i) the panel time-series data are heterogeneous and cross-sectionally dependent; (ii) CO2 emissions, real income, the quadratic income, energy consumption, financial development and openness are integrated of order one; (iii) the analyzed data are cointegrated; (iv) the EKC hypothesis is validated for the OECD countries; (v) increases in openness and financial development mitigate the level of emissions whereas energy consumption contributes to carbon emissions; (vi) a variety of Granger causal relationship is detected among the analyzed variables; and (vii) empirical results and policy recommendations are accurate and efficient since panel econometric models used in this study account for heterogeneity and cross-sectional dependence in their estimation procedures.
Citation - WoS: 27
Citation - Scopus: 22
Quantum Dot and Electron Acceptor Nano-Heterojunction for Photo-Induced Capacitive Charge-Transfer
(Nature Portfolio, 2021) Karatum, Onuralp; Eren, Guncem Ozgun; Melikov, Rustamzhon; Onal, Asim; Ow-Yang, Cleva W.; Sahin, Mehmet; Nizamoglu, Sedat
Capacitive charge transfer at the electrode/electrolyte interface is a biocompatible mechanism for the stimulation of neurons. Although quantum dots showed their potential for photostimulation device architectures, dominant photoelectrochemical charge transfer combined with heavy-metal content in such architectures hinders their safe use. In this study, we demonstrate heavy-metal-free quantum dot-based nano-heterojunction devices that generate capacitive photoresponse. For that, we formed a novel form of nano-heterojunctions using type-II InP/ZnO/ZnS core/shell/shell quantum dot as the donor and a fullerene derivative of PCBM as the electron acceptor. The reduced electron-hole wavefunction overlap of 0.52 due to type-II band alignment of the quantum dot and the passivation of the trap states indicated by the high photoluminescence quantum yield of 70% led to the domination of photoinduced capacitive charge transfer at an optimum donor-acceptor ratio. This study paves the way toward safe and efficient nanoengineered quantum dot-based next-generation photostimulation devices.
Citation - WoS: 134
Citation - Scopus: 136
The Impacts of Different Proxies for Financialization on Carbon Emissions in Top-Ten Emitter Countries
(Elsevier, 2020) Amin, Azka; Dogan, Eyup; Khan, Zeeshan
The nexus of financialization and carbon emissions has been widely discussed in the literature. A vast body of literature that estimates the impact of financialization on carbon emissions proxies financialization with either domestic credit or market capitalization. However, these representatives do not fully respond to the complicated nature of financial development. To till the gaps in the existing literature, nine different proxies for financial development are used in the links with carbon emissions in the framework of EKC theory for the years 1980-2014. This study exposes reliable and robust empirical results due to the use of a number of proxies for financialization and second-generation econometric approaches in the empirical analysis. The quantile regression approach deals with unobserved heterogeneity for each cross-section and estimates different slope parameters at varying quantiles. Because non-normality and heterogeneity are detected in datasek quantile regression provides more robust and reliable estimates than conventional econometric techniques. Results from quantile regression estimator support mixed effects of financial development on carbon emissions over quantiles: in addition, the impact of financial development on carbon emissions is varying not only for each quantile but also for different proxies of financial development. The EKC hypothesis is validated for the top-ten emitter economies. Interpretations and policy suggestions are further discussed in the present study. (C) 2020 Elsevier B.V. All rights reserved.
Citation - WoS: 17
Citation - Scopus: 24
Quality, Nutritional Properties, and Glycemic Index of Colored Whole Wheat Breads
(MDPI, 2023) Koksel, Hamit; Cetiner, Buket; Shamanin, Vladimir P.; Tekin-Cakmak, Z. Hazal; Pototskaya, Inna V.; Kahraman, Kevser; Morgounov, Alexey I.
The main aim of this study was to investigate the quality and nutritional properties (dietary fiber, phenolic, antioxidant contents, and glycemic index) of breads made from whole wheat flours of colored wheats. White (cultivar Agronomicheskaya 5), red (Element 22), purple (EF 22 and Purple 8), and blue (Blue 10) colored wheats were used in the study. The whole wheat flours of Blue 10 and Purple 8 had higher farinograph stability, lower softening degree, and higher quality numbers indicating that they had better rheological properties. Bread produced from whole wheat flour of blue-colored grain had significantly higher loaf volume and better symmetry, crust color, crumb cell structure, and softness values among others (p < 0.05). The whole wheat bread produced using Element 22 had the highest crust and crumb L* color values, while Purple 8 and EF 22 had the lowest crust and crumb L* color values, suggesting that purple-colored grains have a tendency to make whole wheat bread with darker crust and crumb color. Bread produced from cultivar Blue 10 had the lowest firmness values while Element 22 had the highest firmness values. The highest total phenolic content and antioxidant capacity values were obtained from the whole wheat bread sample from purple-colored wheat (Purple 8). The whole wheat flour of Element 22 had the highest total dietary fiber content among all samples (p < 0.05). The differences between whole wheat bread samples in terms of total dietary fiber and glycemic index were not statistically significant. The results of the present study indicated that colored wheats can be used to produce whole wheat breads with higher nutritional properties and acceptable quality characteristics.
Citation - Scopus: 4
CCPred: Global and Population-Specific Colorectal Cancer Prediction and Metagenomic Biomarker Identification at Different Molecular Levels Using Machine Learning Techniques
(Elsevier Ltd, 2024) Bakir-Güngör, Burcu; Temiz, Mustafa; Inal, Yasin; Cicekyurt, Emre; Yousef, Malik
Colorectal cancer (CRC) ranks as the third most common cancer globally and the second leading cause of cancer-related deaths. Recent research highlights the pivotal role of the gut microbiota in CRC development and progression. Understanding the complex interplay between disease development and metagenomic data is essential for CRC diagnosis and treatment. Current computational models employ machine learning to identify metagenomic biomarkers associated with CRC, yet there is a need to improve their accuracy through a holistic biological knowledge perspective. This study aims to evaluate CRC-associated metagenomic data at species, enzymes, and pathway levels via conducting global and population-specific analyses. These analyses utilize relative abundance values from human gut microbiome sequencing data and robust classification models are built for disease prediction and biomarker identification. For global CRC prediction and biomarker identification, the features that are identified by SelectKBest (SKB), Information Gain (IG), and Extreme Gradient Boosting (XGBoost) methods are combined. Population-based analysis includes within-population, leave-one-dataset-out (LODO) and cross-population approaches. Four classification algorithms are employed for CRC classification. Random Forest achieved an AUC of 0.83 for species data, 0.78 for enzyme data and 0.76 for pathway data globally. On the global scale, potential taxonomic biomarkers include ruthenibacterium lactatiformanas; enzyme biomarkers include RNA 2′ 3′ cyclic 3′ phosphodiesterase; and pathway biomarkers include pyruvate fermentation to acetone pathway. This study underscores the potential of machine learning models trained on metagenomic data for improved disease prediction and biomarker discovery. The proposed model and associated files are available at https://github.com/TemizMus/CCPRED. © 2024 Elsevier B.V., All rights reserved.
Citation - WoS: 26
Citation - Scopus: 25
Trail Promotes the Polarization of Human Macrophages Toward a Proinflammatory M1 Phenotype and Is Associated With Increased Survival in Cancer Patients With High Tumor Macrophage Content
(Frontiers Media S.A., 2023) Gunalp, Sinem; Helvaci, Derya Goksu; Oner, Aysenur; Bursali, Ahmet; Conforte, Alessandra; Guener, Hueseyin; Sag, Duygu
BackgroundTNF-related apoptosis-inducing ligand (TRAIL) is a member of the TNF superfamily that can either induce cell death or activate survival pathways after binding to death receptors (DRs) DR4 or DR5. TRAIL is investigated as a therapeutic agent in clinical trials due to its selective toxicity to transformed cells. Macrophages can be polarized into pro-inflammatory/tumor-fighting M1 macrophages or anti-inflammatory/tumor-supportive M2 macrophages and an imbalance between M1 and M2 macrophages can promote diseases. Therefore, identifying modulators that regulate macrophage polarization is important to design effective macrophage-targeted immunotherapies. The impact of TRAIL on macrophage polarization is not known.MethodsPrimary human monocyte-derived macrophages were pre-treated with either TRAIL or with DR4 or DR5-specific ligands and then polarized into M1, M2a, or M2c phenotypes in vitro. The expression of M1 and M2 markers in macrophage subtypes was analyzed by RNA sequencing, qPCR, ELISA, and flow cytometry. Furthermore, the cytotoxicity of the macrophages against U937 AML tumor targets was assessed by flow cytometry. TCGA datasets were also analyzed to correlate TRAIL with M1/M2 markers, and the overall survival of cancer patients.ResultsTRAIL increased the expression of M1 markers at both mRNA and protein levels while decreasing the expression of M2 markers at the mRNA level in human macrophages. TRAIL also shifted M2 macrophages towards an M1 phenotype. Our data showed that both DR4 and DR5 death receptors play a role in macrophage polarization. Furthermore, TRAIL enhanced the cytotoxicity of macrophages against the AML cancer cells in vitro. Finally, TRAIL expression was positively correlated with increased expression of M1 markers in the tumors from ovarian and sarcoma cancer patients and longer overall survival in cases with high, but not low, tumor macrophage content.ConclusionsTRAIL promotes the polarization of human macrophages toward a proinflammatory M1 phenotype via both DR4 and DR5. Our study defines TRAIL as a new regulator of macrophage polarization and suggests that targeting DRs can enhance the anti-tumorigenic response of macrophages in the tumor microenvironment by increasing M1 polarization.
Citation - WoS: 13
Citation - Scopus: 14
Triterpenoids and Steroids Isolated from Anatolian Capparis Ovata and Their Activity on the Expression of Inflammatory Cytokines
(Taylor & Francis Ltd, 2020) Gazioglu, Isil; Semen, Sevcan; Acar, Ozden Ozgun; Kolak, Ufuk; Sen, Alaattin; Topcu, Gulacti
Context CapparisL. (Capparaceae) is grown worldwide. Caper has been used in traditional medicine to treat various diseases including rheumatism, kidney, liver, stomach, as well as headache and toothache. Objective To isolate and elucidate of the secondary metabolites of theC. ovataextracts which are responsible for their anti-inflammatory activities. Materials and methods Buds, fruits, flowers, leaves and stems ofC. ovataDesf. was dried, cut to pieces, then ground separately. From their dichloromethane/hexane (1:1) extracts, eight compounds were isolated and their structures were elucidated by NMR, mass spectroscopic techniques. The effects of compounds on the expression of inflammatory cytokines in SH-SY5Y cell lines were examined by qRT-PCR ranging from 4 to 96 mu M. Cell viability was expressed as a percentage of the control, untreated cells. Results This is a first report on isolation of triterpenoids and steroids fromC. ovatawith anti-inflammatory activity. One new triterpenoid ester olean-12-en-3 beta,28-diol, 3 beta-pentacosanoate (1) and two new natural steroids 5 alpha,6 alpha-epoxycholestan-3 beta-ol (5) and 5 beta,6 beta-epoxycholestan-3 beta-ol (6) were elucidated besides known compounds; oleanolic acid (2), ursolic acid (3), beta-sitosterol (4), stigmast-5,22-dien-3 beta-myristate (7) and bismethyl-octylphthalate (8). mRNA expression levels as EC(10)of all the tested seven genes were decreased, particularly CXCL9 (19.36-fold), CXCL10 (8.14-fold), and TNF (18.69) by the treatment of 26 mu M of compound1on SH-SY5Y cells. Discussion and conclusions Triterpenoids and steroids isolated fromC. ovatawere found to be moderate-strong anti-inflammatory compounds. Particularly, compounds1and3were found to be promising therapeutic agents in the treatment of inflammatory and autoimmune diseases.
Citation - WoS: 14
Citation - Scopus: 21
Ultrasonic-Assisted Production of Precipitated Calcium Carbonate Particles From Desulfurization Gypsum
(Elsevier, 2021) Altiner, Mahmut; Top, Soner; Kaymakoglu, Burcin
This study aimed to investigate the effect of ultrasonic application on the production of precipitated calcium carbonate (PCC) particles from desulfurization gypsum via direct mineral carbonation method using conventional and venturi tube reactors in the presence of different alkali sources (NaOH, KOH and NH4OH). The venturi tube was designed to determine the effect of ultrasonication on PCC production. Ultrasonic application was performed three times (before, during, and after PCC production) to evaluate its exact effect on the properties of the PCC particles. Scanning electron microscope (SEM), X-ray diffraction (XRD), Atomic force microscope (AFM), specific surface area (SSA), Fourier transform infrared spectrometry (FTIR), and particle size analyses were performed. Results revealed the strong influence of the reactor types on the nucleation rate of PCC particles. The presence of Na+ or K+ ions in the production resulted in producing PCC particles containing only calcite crystals, while a mixture of vaterite and calcite crystals was observed if NH4+ ions were present. The use of ultrasonic power during PCC production resulted in producing cubic calcite rather than vaterite crystals in the presence of all ions. It was determined that ultrasonic power should be conducted in the venturi tube before PCC production to obtain PCC particles with superior properties (uniform particle size, nanosized crystals, and high SSA value). The resulting PCC particles in this study can be suitably used in paint, paper, and plastic industries according to the ASTM standards.
Citation - Scopus: 21
Analyzing the Nexus Between Environmental Sustainability and Clean Energy for the USA
(Springer, 2024) Dogan, Eyup; Si Mohammed, Kamel; Khan, Zeeshan Anis; BinSaeed, Rima Hassan
Environmental sustainability is a key target to achieve sustainable development goals (SDGs). However, achieving these targets needs tools to pave the way for achieving SDGs and COP28 targets. Therefore, the primary objective of the present study is to examine the significance of clean energy, research and development spending, technological innovation, income, and human capital in achieving environmental sustainability in the USA from 1990 to 2022. The study employed time series econometric methods to estimate the empirical results. The study confirmed the long-run cointegrating relationship among CO2 emissions, human capital, income, R&D, technological innovation, and clean energy. The results are statistically significant in the short run except for R&D expenditures. In the long run, the study found that income and human capital contribute to further aggravating the environment via increasing CO2 emissions. However, R&D expenditures, technological innovation, and clean energy help to promote environmental sustainability by limiting carbon emissions. The study recommends investment in technological innovation, clean energy, and increasing R&D expenditures to achieve environmental sustainability in the USA. © 2024 Elsevier B.V., All rights reserved.
Citation - WoS: 16
Citation - Scopus: 18
Recent Advances in Machine Learning for Network Automation in the O-RAN
(MDPI, 2023) Hamdan, Mutasem Q.; Lee, Haeyoung; Triantafyllopoulou, Dionysia; Borralho, Ruben; Kose, Abdulkadir; Amiri, Esmaeil; Tafazolli, Rahim
The evolution of network technologies has witnessed a paradigm shift toward open and intelligent networks, with the Open Radio Access Network (O-RAN) architecture emerging as a promising solution. O-RAN introduces disaggregation and virtualization, enabling network operators to deploy multi-vendor and interoperable solutions. However, managing and automating the complex O-RAN ecosystem presents numerous challenges. To address this, machine learning (ML) techniques have gained considerable attention in recent years, offering promising avenues for network automation in O-RAN. This paper presents a comprehensive survey of the current research efforts on network automation usingML in O-RAN.We begin by providing an overview of the O-RAN architecture and its key components, highlighting the need for automation. Subsequently, we delve into O-RAN support forML techniques. The survey then explores challenges in network automation usingML within the O-RAN environment, followed by the existing research studies discussing application of ML algorithms and frameworks for network automation in O-RAN. The survey further discusses the research opportunities by identifying important aspects whereML techniques can benefit.
Citation - WoS: 13
Citation - Scopus: 13
A Continuously Benchmarked and Crowdsourced Challenge for Rapid Development and Evaluation of Models to Predict COVID-19 Diagnosis and Hospitalization
(Amer Medical Assoc, 2021) Yan, Yao; Schaffter, Thomas; Bergquist, Timothy; Yu, Thomas; Prosser, Justin; Aydin, Zafer; Mooney, Sean
IMPORTANCE Machine learning could be used to predict the likelihood of diagnosis and severity of illness. Lack of COVID-19 patient data has hindered the data science community in developing models to aid in the response to the pandemic. OBJECTIVES To describe the rapid development and evaluation of clinical algorithms to predict COVID-19 diagnosis and hospitalization using patient data by citizen scientists, provide an unbiased assessment of model performance, and benchmark model performance on subgroups. DESIGN, SETTING, AND PARTICIPANTS This diagnostic and prognostic study operated a continuous, crowdsourced challenge using a model-to-data approach to securely enable the use of regularly updated COVID-19 patient data from the University of Washington by participants from May 6 to December 23, 2020. A postchallenge analysis was conducted from December 24, 2020, to April 7, 2021, to assess the generalizability of models on the cumulative data set as well as subgroups stratified by age, sex, race, and time of COVID-19 test. By December 23, 2020, this challenge engaged 482 participants from 90 teams and 7 countries. MAIN OUTCOMES AND MEASURES Machine learning algorithms used patient data and output a score that represented the probability of patients receiving a positive COVID-19 test result or being hospitalized within 21 days after receiving a positive COVID-19 test result. Algorithms were evaluated using area under the receiver operating characteristic curve (AUROC) and area under the precision recall curve (AUPRC) scores. Ensemble models aggregating models from the top challenge teams were developed and evaluated. RESULTS In the analysis using the cumulative data set, the best performance for COVID-19 diagnosis prediction was an AUROC of 0.776 (95% CI, 0.775-0.777) and an AUPRC of 0.297, and for hospitalization prediction, an AUROC of 0.796 (95% CI, 0.794-0.798) and an AUPRC of 0.188. Analysis on top models submitting to the challenge showed consistently better model performance on the female group than the male group. Among all age groups, the best performance was obtained for the 25- to 49-year age group, and the worst performance was obtained for the group aged 17 years or younger. CONCLUSIONS AND RELEVANCE In this diagnostic and prognostic study, models submitted by citizen scientists achieved high performance for the prediction of COVID-19 testing and hospitalization outcomes. Evaluation of challenge models on demographic subgroups and prospective data revealed performance discrepancies, providing insights into the potential bias and limitations in the models.
Citation - WoS: 8
Citation - Scopus: 9
Emerging DNA Methylome Targets in FLT3-ITD Acute Myeloid Leukemia: Combination Therapy With Clinically Approved FLT3 Inhibitors
(Springer, 2024) Tecik, Melisa; Adan, Aysun
The internal tandem duplication (ITD) mutation of the FMS-like receptor tyrosine kinase 3 (FLT3-ITD) is the most common mutation observed in approximately 30% of acute myeloid leukemia (AML) patients. It represents poor prognosis due to continuous activation of downstream growth-promoting signaling pathways such as STAT5 and PI3K/AKT. Hence, FLT3 is considered an attractive druggable target; selective small FLT3 inhibitors (FLT3Is), such as midostaurin and quizartinib, have been clinically approved. However, patients possess generally poor remission rates and acquired resistance when FLT3I used alone. Various factors in patients could cause these adverse effects including altered epigenetic regulation, causing mainly abnormal gene expression patterns. Epigenetic modifications are required for hematopoietic stem cell (HSC) self-renewal and differentiation; however, critical driver mutations have been identified in genes controlling DNA methylation (such as DNMT3A, TET2, IDH1/2). These regulators cause leukemia pathogenesis and affect disease diagnosis and prognosis when they co-occur with FLT3-ITD mutation. Therefore, understanding the role of different epigenetic alterations in FLT3-ITD AML pathogenesis and how they modulate FLT3I's activity is important to rationalize combinational treatment approaches including FLT3Is and modulators of methylation regulators or pathways. Data from ongoing pre-clinical and clinical studies will further precisely define the potential use of epigenetic therapy together with FLT3Is especially after characterized patients' mutational status in terms of FLT3 and DNA methlome regulators.
Citation - WoS: 3
Citation - Scopus: 3
A Subtractive Proteomics Approach for the Identification of Immunodominant Acinetobacter Baumannii Vaccine Candidate Proteins
(Frontiers Media S.A., 2022) Acar, Mustafa Burak; Ayaz-Guner, Serife; Guner, Huseyin; Dinc, Gokcen; Kilic, Aysegul Ulu; Doganay, Mehmet; Ozcan, Servet
BackgroundAcinetobacter baumannii is one of the most life-threatening multidrug-resistant pathogens worldwide. Currently, 50%-70% of clinical isolates of A. baumannii are extensively drug-resistant, and available antibiotic options against A. baumannii infections are limited. There is still a need to discover specific de facto bacterial antigenic proteins that could be effective vaccine candidates in human infection. With the growth of research in recent years, several candidate molecules have been identified for vaccine development. So far, no public health authorities have approved vaccines against A. baumannii. MethodsThis study aimed to identify immunodominant vaccine candidate proteins that can be immunoprecipitated specifically with patients' IgGs, relying on the hypothesis that the infected person's IgGs can capture immunodominant bacterial proteins. Herein, the outer-membrane and secreted proteins of sensitive and drug-resistant A. baumannii were captured using IgGs obtained from patient and healthy control sera and identified by Liquid Chromatography- Tandem Mass Spectrometry (LC-MS/MS) analysis. ResultsUsing the subtractive proteomic approach, we determined 34 unique proteins captured only in drug-resistant A. baumannii strain via patient sera. After extensively evaluating the predicted epitope regions, solubility, transverse membrane characteristics, and structural properties, we selected several notable vaccine candidates. ConclusionWe identified vaccine candidate proteins that triggered a de facto response of the human immune system against the antibiotic-resistant A. baumannii. Precipitation of bacterial proteins via patient immunoglobulins was a novel approach to identifying the proteins that could trigger a response in the patient immune system.
Citation - WoS: 4
Citation - Scopus: 5
Sustainability Assessment of Denim Fabric Made of PET Fiber and Recycled Fiber From Postconsumer PET Bottles Using LCA and LCC Approach With the EDAS Method
(Wiley, 2024) Fidan, Fatma Sener; Aydogan, Emel Kizilkaya; Uzal, Nigmet
The textile industry is under pressure to adopt sustainable production methods because its contribution to global warming is expected to rise by 50% by 2030. One solution is to increase the use of recycled raw material. The use of recycled raw material must be considered holistically, including its environmental and economic impacts. This study examined eight scenarios for sustainable denim fabric made from recycled polyethylene terephthalate (PET) fiber, conventional PET fiber, and cotton fiber. The evaluation based on the distance from average solution (EDAS) multicriteria decision-making method was used to rank scenarios according to their environmental and economic impacts, which are assessed using life cycle assessment and life cycle costing. Allocation, a crucial part of evaluating the environmental impact of recycled products, was done using cut-off and waste value. Life cycle assessments reveal that recycled PET fiber has lower freshwater ecotoxicity and fewer eutrophication and acidification impacts. Cotton outperformed PET fibers in human toxicity. Only the cut-off method reduces potential global warming with recycled PET. These findings indicated that recycled raw-material life cycle assessment requires allocation. Life cycle cost analysis revealed that conventional PET is less economically damaging than cotton and recycled PET. The scenarios were ranked by environmental and economic impacts using EDAS. This ranking demonstrated that sustainable denim fabric production must consider both economic and environmental impacts. Integr Environ Assess Manag 2024;00:1-19. (c) 2024 The Author(s). Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
Citation - WoS: 128
Citation - Scopus: 132
The Influence of Biomass Energy Consumption on CO2 Emissions: A Wavelet Coherence Approach
(Springer Heidelberg, 2016) Bilgili, Faik; Ozturk, Ilhan; Kocak, Emrah; Bulut, Umit; Pamuk, Yalcin; Mugaloglu, Erhan; Baglitas, Hayriye H.
In terms of today, one may argue, throughout observations from energy literature papers, that (i) one of the main contributors of the global warming is carbon dioxide emissions, (ii) the fossil fuel energy usage greatly contributes to the carbon dioxide emissions, and (iii) the simulations from energy models attract the attention of policy makers to renewable energy as alternative energy source to mitigate the carbon dioxide emissions. Although there appears to be intensive renewable energy works in the related literature regarding renewables' efficiency/impact on environmental quality, a researcher might still need to follow further studies to review the significance of renewables in the environment since (i) the existing seminal papers employ time series models and/or panel data models or some other statistical observation to detect the role of renewables in the environment and (ii) existing papers consider mostly aggregated renewable energy source rather than examining the major component(s) of aggregated renewables. This paper attempted to examine clearly the impact of biomass on carbon dioxide emissions in detail through time series and frequency analyses. Hence, the paper follows wavelet coherence analyses. The data covers the US monthly observations ranging from 1984:1 to 2015 for the variables of total energy carbon dioxide emissions, biomass energy consumption, coal consumption, petroleum consumption, and natural gas consumption. The paper thus, throughout wavelet coherence and wavelet partial coherence analyses, observes frequency properties as well as time series properties of relevant variables to reveal the possible significant influence of biomass usage on the emissions in the USA in both the short-term and the long-term cycles. The paper also reveals, finally, that the biomass consumption mitigates CO2 emissions in the long run cycles after the year 2005 in the USA.
Citation - WoS: 130
Citation - Scopus: 143
Analyzing the Nexus Between Energy Transition, Environment and ICT: A Step Towards COP26 Targets
(Academic Press Ltd- Elsevier Science Ltd, 2023) Tzeremes, Panayiotis; Dogan, Eyup; Alavijeh, Nooshin Karimi
In line with the Sustainable Development Goals and the recent COP26 summit, energy transition, low carbon emissions and technology have become extremely important subjects in the agenda of governments and poli-cymakers. The present study thus discusses the nexus between energy transition, economic growth, CO2 emis-sions and information and communications technology (ICT) in BRICS countries applying the novel GMM-PVAR method proposed on the annual data for the period 2000-2017. This method is strong to the issue of endogeneity which is commonly faced in the context of panel data analysis but mostly ignored in the literature. The findings of this research demonstrate that carbon emissions have a positive and significant effect on energy transition; similarly, raising economic growth augments the consumption of energy transition. Furthermore, ICT is found to be a significant choice in the development of energy transition and the solution of environmental challenges. Overall, technological factors in addition to economic and environmental factors also have great roles in the development of renewable energy and energy transition. Thus, results from this study call for government supports to develop ICT across the BRICS countries.

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