Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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  • Article
    Storage Protein Allergen Sensitization Patterns in Children: Insights from Multiplex Microarray Profiling and Hierarchical Clustering
    (Wiley, 2025) Caka, Canan; Ozcivici, Engin; Karakus, Ceyda Oksel; Sekerel, Bulent Enis
    Background Storage proteins (SPs), including 2S albumins, vicilins, and legumins, are key allergenic molecules (AMs) of peanuts, tree nuts (TNs), and sesame. Their structural stability contributes to allergenicity and sensitization. This study explored SP AM clustering patterns and evaluated the test performance of multiplex microarray (MM) testing in a pediatric cohort. Methods We retrospectively analyzed 350 children (median age: 3.7 years) with detectable SP sensitizations (>= 0.1 kU(A)/L) using the ALEX(2) MM platform. Sensitization interrelationships were analyzed using correlation heatmaps, hierarchical clustering (HC), dimensionality reduction, and feature elimination. Predictive utility was assessed through ROC curve analysis at different sensitization cut-offs (>0.1 and >0.3 kU(A)/L) and total IgE thresholds (>0, >20, and >50 kU/L). Results HC identified a broad SP cluster spanning peanuts, TNs, sesame, poppy seed, and buckwheat. Strong correlations and early HC linkages suggested extensive cross-sensitization (e.g., Ana o 3-Pis v 1 and Jug r 4-Cor a 9), alongside evidence of co-sensitization and molecular spreading. Unexpected clustering of structurally dissimilar peanut and pistachio AMs pointed to shared epitopes and/or cross-contamination. 2S albumins (Ara h 2, Cor a 14, Jug r 1, Ana o 3, and Ses i 1) were most predictive for clinical reactivity. Lower cut-offs and exclusion of patients with low total IgE improved test performance. Alpha-hairpinin (Pap s 2S albumin) showed potential as specific markers. Conclusions MM testing enables detailed SP sensitization profiling. Cluster-based interpretation may clarify cross- vs. co-sensitization, supporting informed clinical decisions. Use of recombinant AMs and IgE stratification may further enhance MM utility in food allergy diagnostics.
  • Article
    Citation - WoS: 56
    Citation - Scopus: 67
    Characterization of Concrete Matrix/Steel Fiber De-Bonding in an Sfrc Beam: Principal Component Analysis and K-Mean Algorithm for Clustering Ae Data
    (Elsevier, 2018) Tayfur, Sena; Alver, Ninel; Abdi, Saeed; Saatçi, Selçuk; Ghiami, Amir
    Steel fibers have been used in concrete structures to increase the tensile strength and ductility of concrete. Fibers bridging cracks reduce micro cracking and improve post-cracking strength in concrete. Propagation of damage in a fiber reinforced concrete member occurs by concrete matrix cracking and widening of these cracks, which is accompanied by de-bonding of steel fibers from the concrete matrix. Fiber de-bonding is the main factor affecting the post-peak behavior of these members. Therefore, distinguishing the matrix cracking and fiber de-bonding mechanisms is important in nondestructive structural health monitoring methods. This study is focused on characterizing steel fiber/matrix de-bonding events apart from concrete matrix cracking sources in acoustic emission (AE) method. Two reinforced concrete beams, one of which included steel fibers within the concrete matrix, were tested under three point bending and monitored by AE. Afterwards, Principal Component Analysis (PCA) was applied to AE data and the failure mechanisms were clustered for characterization of steel fiber/matrix de-bonding. Finally, different AE features of these clusters were evaluated and applicable AE parameter distributions, which are useful to clarify steel fiber de-bonding mechanisms, were revealed.