PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection

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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
    Editorial: Advancing Biotechnology in Turkiye: a Dedication To All Women
    (Springer, 2025) Cadirci, Bilge Hilal; Buyukkileci, Ali Oguz; Binay, Baris
  • 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: 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 - Scopus: 1
    Lessons From a Ten-Year Journey: Building a Student-Driven Computational Biology Society Across Turkey
    (F1000 Research, 2022) Kaya, Yasin; Karakulak, Tülay; Saylan, Cemil Can; Gür, E. Ravza; Tatlıdil, Engin; Güleşen, Sevilay; Betül Dinçaslan, Fatma; Dönertaş, Handan Melike
    The Regional Student Group Turkey (RSG-Turkey) is officially associated with the International Society for Computational Biology (ISCB) Student Council (SC). At the RSG-Turkey, we aim to contribute to the early-career researchers in computational biology and bioinformatics fields by providing opportunities for improving their academic and technical skills in the field. Over the last ten years, we have built a well-known student-driven academic society in Turkey that organizes numerous events every year and continues to grow with over 650 current members. Celebrating the 10th anniversary of RSG-Turkey, in this communication, we share our experiences, five main lessons we learned, and the steps to establish a long-standing academic community: having a clear mission, building a robust structure, effective communication, turning challenges into opportunities, and building collaborations. We believe that our experiences can help students and academics establish long-standing communities in fast-developing areas like bioinformatics.
  • Editorial
    Citation - WoS: 8
    Citation - Scopus: 9
    Kras(g12c) Inhibitors on the Horizon
    (Future Science, 2019) Çağır, Ali; Azmi, Asfar S.
    RAS proteins (the four isoforms KRAS4A, KRAS4B, NRAS and HRAS encoded by three genes KRAS, NRAS and HRAS) act as molecular switches that when activated drive several key cellular processes such as cell growth, proliferation and survival [1]. In normal cells, RAS activity is under tight control by the precise activation (binding to GTP) and inactivation (GTP hydrolysis to GDP) [1]. As with other critical proteins, it is not at all surprising to note that the gene encoding the RAS protein isoforms is found mutated or altered in a significant proportion of tumors [2]. Mutant RAS loses its ability to hydrolyze GTP and remains in a permanently activated state (bound to GTP) leading to uncontrolled growth.
  • Editorial
    Citation - WoS: 3
    Citation - Scopus: 4
    La médecine de précision en oncologie: challenges, enjeux et nouveaux paradigmes
    (John Libbey Eurotext Ltd, 2019) Cox, Stephanie; Rousseau-Tsangaris, Marina; Abou-Zeid, Nancy; Dalle, Stephane; Leurent, Pierre; Cutivet, Arnaud; Baran, Yusuf
    L'oncologie médicale a pris, depuis quelques années, un tournant substantiel en intégrant la dimension génomique dans la prise de décision thérapeutique. En raison de l'accès aux technologies de séquençage (exome complet, séquençage ciblé du génome, séquençage de l'ARN, ADN circulant. . .) facilité par la mise en place de plateformes de biologie moléculaire et la diminution des coûts par échantillon, la caractérisation moléculaire est devenue un outil supplémentaire à la disposition du clinicien, s'ajoutant au diagnostic histologique et immunohistochimique et aux données d'imagerie radiologique. Cette approche moléculaire a permis d'identifier de nouvelles formes nosologiques et permet, au-delà de l'aspect cognitif, de renseigner sur les altérations qui sont à prendre en compte dans les décisions thérapeutiques (biomarqueurs prédictifs, activation de voies spécifiques, mutations de résistance). C'est dans ce contexte de profond et rapide changement de pratique médicale et scientifique qu'il a été proposé de réfléchir collectivement aux nouveaux enjeux sous la forme d'un workshop à l'occasion de Biovision qui s'est tenu à Lyon, du 4 au 6 avril 2017.
  • Editorial
    Citation - WoS: 2
    Computational Mirnomics - Integrative Approaches
    (Informationsmanagement in der Biotechnologie e.V. (IMBio e.V.), 2017) Hofestaedt, Ralf; Schreiber, Falk; Sommer, Bjoern; Allmer, Jens
    With this special issue on Computational miRNomics, we would like to start a new generation of publications in the Journal of Integrative Bioinformatics (JIB). From 2017 onwards, JIB will be published by De Gruyter which is one of the largest Open Access publishers in Germany with a long history. Established in 1918 with roots reaching even further back, the JIB editorial board decided that De Gruyter is the perfect partner to increase the level of professionalism for our publication processing and journal development.