WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7150

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  • Editorial
    A Thin Film Micro-Extraction Based Salivary Metabolomics and Chemometric Strategy for Rapid Lung Cancer Diagnosis
    (Galenos Publ House, 2025) Pelit, Levent; Basbinar, Yasemin; Goksel, Ozlem; Goksel, Tuncay; Erbas, İlknur; Pelit, Fusun; Ozdemir, Durmus
    INTRODUCTION: Lung cancer (LC) remains one of the leading causes of cancer-related mortality worldwide, largely due to the lack of reliable biomarkers for early detection.1 Despite advances in di-agnostic imaging and targeted therapies, the five-year survival rate remains low because most cases are diagnosed at advanced stages. Consequently, the development of sensitive, non-invasive, and cost-effective diagnostic approaches is a major clinical priority. Metabolomics, the comprehensive profiling of small-molecule metabolites, has emerged as a powerful tool for uncovering cancer-associated metabolic alterations, providing insights into tumor biology and facilitating the discovery of novel biomarkers for accurate diagnosis and disease monitoring. Among biological matrices, saliva is a promising diagnostic biofluid because it can be collected non-invasively, is simple to obtain, and reflects systemic and local metabolic changes. Recent studies have demonstrated its potential for detecting various cancers, including lung cancer, highlighting its value for biomarker-based early di-agnosis.2,3 In this study, a novel thin-film microextraction (TFME) technique integrated with liquid chromatography-tandem mass spectrometry (LC-MS/MS) is introduced for the rapid, selective, and reproducible extraction of salivary metabolites. The developed TFME approach offers high throughput, reduced solvent consumption, and enhanced analytical performance, enabling the identification and quantification of key metabolic biomarkers associated with lung cancer. The objective of this workflow is to advance saliva-based metabolomics toward clinical translation, offering a promising avenue for the early and non-invasive diagnosis of lung cancer. MATERIAL AND METHODS: Synthesis of SiO2 Nanoparticles and TFME blade Preparation: SiO2 nanoparticles were synthesized using the Stöber method, followed by post-coating with tetraethyl orthosilicate, centrifugation, wash-ing with ethanol, and drying. The nanoparticles were incorporated into a polyacrylonitrile (PAN) matrix and coated onto steel TFME blades via a controlled dip-coating process to ensure uniform film thick-ness. Participants and Sample Collection: Saliva samples were collected from 40 histopathologically con-firmed lung cancer patients and 38 healthy volunteers following an overnight fast and an oral rinse. Ethical approval and informed consent were obtained (Ege University Ethics Committee, protocol: 15-11.1/46). Saliva samples were centrifuged, diluted (1:2), and stored at -80 °C until analysis. TFME Sampling and Analysis: A 96-well plate system equipped with PAN/SiO2-coated TFME blades was used for metabolite extraction (Figure 1). Blades were immersed in diluted saliva samples and rotated at 850 rpm for 150 minutes to allow analyte adsorption, followed by desorption of analytes in 0.1% formic acid for 30 minutes. Desorbed solutions were spiked with 0.5 µg/mL ornidazole as an internal standard prior to LC-MS/MS analysis. RESULTS: The TFME method was optimized to detect 18 metabolites in pre-treatment saliva samples from lung cancer patients. Chromatographic evaluation demonstrated that the Inertsil 100 column, employing isocratic elution with ornidazole as the internal standard, provided optimal separation effi-ciency and reproducibility. Extraction parameters, including desorption solution type and pH, were optimized; desorption solution type 2 at pH 8-9 yielding the highest metabolite recovery. Analytical validation indicated robust linearity (R2: 0.9841-0.9975), sensitivity (limit of detection: 0.014-0.97 μg/mL; limit of quantification: 0.046-3.20 μg/mL), precision (%relative standard deviation <20%), and accuracy (85-125% for most metabolites). Pathway analysis revealed significant alterations in the me-tabolism of phenylalanine, purine, tyrosine, histidine, and methionine. The Heatmap visualization showed increased levels of proline, hypoxanthine, phenylalanine, and tyrosine in lung cancer pa-tients. receiver operating characteristic curve analysis highlighted these metabolites as potential bi-omarkers, with proline exhibiting the highest diagnostic performance [area under the curve (AUC): 0.946], followed by hypoxanthine (AUC: 0.933) and phenylalanine (AUC: 0.905) CONCLUSION: The findings of this study demonstrate that the TFME approach is a reliable and effi-cient platform for metabolomic profiling in lung cancer. Using pre-treatment saliva samples, the method achieved a sensitivity exceeding 90% for detecting newly diagnosed histopathologically con-firmed patients. Among the metabolites analyzed, proline, hypoxanthine, and phenylalanine showed strong diagnostic potential, consistent with the pathway analyses implicating purine and phenylala-nine metabolism. These results underscore the potential of salivary metabolomics as a non-invasive screening alternative in the absence of validated early lung cancer biomarkers. Additionally, TFME’s high-throughput capacity, cost-effectiveness, and environmental sustainability support its feasibility for routine clinical application.
  • Editorial
    Materials Science and Engineering for Circularity: Challenges, Strategies and Solution
    (Elsevier, 2026) Beck, Gesa; Balle, Frank; Gokelma, Mertol; Shamsuyeva, Madina; Perotto, Giovanni; Gulia, Kiran
  • Editorial
    Editorial on: 22nd International Symposium on Boron, Borides and Related Materials (ISBB 2024)
    (Elsevier, 2025) Balci-Cagiran, Ozge; Yucel, Onuralp; Somer, Mehmet
  • Editorial
    Editorial: Advancing Biotechnology in Turkiye: a Dedication To All Women
    (Springer, 2025) Cadirci, Bilge Hilal; Buyukkileci, Ali Oguz; Binay, Baris
  • Editorial
    Comments on “Relaxed Conditions for the Input-to-State Stability of Switched Nonlinear Time-Varying Systems”
    (Ieee-inst Electrical Electronics Engineers inc, 2025) Sahan, Gokhan; Trenn, Stephan
    This study addresses the deficiencies in the assumptions of the results in (Chen and Yang, 2017) due to the lack of uniformity. We first show the missing hypothesis by presenting a counterexample. Then, we prove why they are wrong in that form and show the errors in the proof of the main result of (Chen and Yang, 2017). Next, we compare the assumptions and related results of (Chen and Yang, 2017) with similar works in the literature. Lastly, we give suggestions to complement the shortcomings of the hypotheses and thus correct them.
  • Editorial
    Citation - WoS: 5
    Citation - Scopus: 5
    Rna M<sup>6</Sup>a Methylation at the Juxtaposition of Apoptosis and Rna Therapeutics
    (Cell Press, 2024) Akguel, Buenyamin; Akcaoez-Alasar, Azime; Saglam, Buket
    Targeting RNA m(6)A marks in apoptosis-related transcripts holds promise for RNA therapeutics. However, pathway-specific RNA m(6)A sites on pro- or antiapoptotic transcripts have not been fully unveiled, let alone characterized. This article summarizes the current knowledge and gaps in the cellular response modulated by apoptotic stimulus-specific RNA m(6)A marks.
  • Editorial
    Citation - WoS: 20
    Citation - Scopus: 21
    Editorial. Counterurbanisation, Again: Rural Mobilities, Representations, Power and Policies
    (Elsevier Ltd, 2023) Gkartzios, M.; Halfacree, K.
    [No abstract available]
  • Editorial
    The Editorial Preface: Contemporary Histories of Design and Transience
    (Univ Oviedo, 2023) Emgin, Bahar; Ata, Zeynep; Tunç Cox, Ayça; Kılınç, Kıvanç
    [No abstract available]
  • Editorial
    Citation - WoS: 1
    Citation - Scopus: 1
    Editorial: Biomaterial Applications in Soft Tissue Engineering and Replacement
    (Frontiers Media S.A., 2023) Hornyak, Istvan; Jedlovszky-Hajdu, Angela; Kehr, Seda
    The research related to the application of biomaterials encompasses a large area within the field of tissue engineering and regenerative medicine (TERM), and this Research Topic was dedicated to the versatile possibilities in the use of biomaterials. The sum of 10 manuscripts were submitted to this Research Topic and six were selected for this Research Topic with the contribution of 35 authors, Four of the accepted manuscripts were original research articles and two were review articles
  • Editorial
    Citation - WoS: 2
    Citation - Scopus: 2
    Editorial: Population Genomics and Adaptation To Novel Environments: Challenges and Opportunities
    (Frontiers Media S.A., 2023) Matur, Ferhat; Keskin, Emre; Sezgin, Efe
    Understanding how organisms adapt to novel environments is an active Research Topic in ecological and evolutionary studies. Most ecological and evolutionary studies focus on how organisms find food (utilization of ecological resources), how they avoid being the food (avoidance of predators), or form the next generation (reproductive strategies) in changing environmental conditions. Yet, some novel environments may present with extreme challenges that organisms may need to evolve novel metabolic pathways even just to exist. Population genomics methods can offer reliable estimates of basic population characteristics such as effective population size, inbreeding, demographic history, and population structure, all of which are also important for conservation efforts. Furthermore, population genomics studies can pinpoint specific genetic loci and variants that are under selection for a populations’ ability to evolve and adapt in response to environmental change and manage adaptive variation. The last 10 years have seen a rise in the study of population genetics of non-model organisms, and the findings of this research are increasingly being applied to the conservation and management of wildlife. To understand population genetics and adaptations, it is equally crucial to share and disseminate the research done using these techniques.