Welcome to the Bezmialem Academic Repository

Bezmialem Vakıf University's Institutional Academic Archive System aims to ensure that the scientific knowledge and research outputs produced by our university are made available openly and sustainably for the benefit of society and all stakeholders. Our university considers it a fundamental responsibility to contribute to the advancement of science and the dissemination of academic knowledge, in line with the principles of transparency and reliability. Within the system, various academic outputs, such as articles, theses, books, book chapters, reports, and presentations, are made accessible.

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Recent Submissions

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Footplate releasing technique for correcting short noses in revision and Asian rhinoplasty
(2026-03-01) Alp A.; YENİGÜN A.; ÖZTURAN O.
Background: To achieve aesthetically pleasing results that are in harmony with the face, it is essential that the nose length is proportionate to facial proportions. Short and upturned noses can give the impression that the tip of the nose has been cut off when viewed from the front. Objective: The aim of this study is to obtain a longer nose by increasing the prominence of the nasal tip through repositioning the medial and lateral crura using the Footplate Releasing Technique in patients with short noses, particularly in Asian patients. Materials and Methods: The Footplate Releasing Technique was applied to 37 revision cases and 32 primary Asian noses. The technique consists of three stages. In the first stage, the medial crus was cut from the nasal base. Then, the lateral crus was lengthened by stealing from the medial crus. In the final stage, the cut and shortened medial crura were sutured to a strong columellar strut placed between them and extended to the nasal floor. Patients were followed up for an average of 12 months (range: 6-18 months). Results: The Footplate Releasing Technique was successfully applied to 37 revision cases and 32 primary Asian noses. The nasal tip point was recreated at the desired level with extended lateral crura. The nasal tip was moved forward and downward, reducing cephalic rotation while achieving the desired projection. Targeted tip point, rotation, and projection results were obtained in all paConclusions: In revision cases and short nose deformities commonly seen in Asian patients, the Footplate Releasing Technique the overall nasal structure. (c) 2025 The Author(s). Published by Elsevier Ltd on behalf of Surgeons. This is an open access article under the CC BY-NC-ND
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AI-assisted design and optimization of two smart green HPLC methods for simultaneous determination of some antiviral drugs
(2026-03-01) BAY M.; TIRIS G.; Genc A. A.; ERK N.; Obaydo R. H.; Lotfy H. M.
Two novel high-performance liquid chromatography (HPLC) methods were developed and validated for the determination of dolutegravir (DTG), lamivudine (3TC), and abacavir (ABA) in pharmaceutical formulations. In this study, AI engines such as Copilot, ChatGPT 5.2, Gemini, and Perplexity were integrated into HPLC method development. The selected predicted conditions underwent experimental optimization, validation, and refinement. Their practical implementation significantly improved efficiency and accuracy in the analytical process. The first method, an isocratic HPLC, was designed for the simultaneous quantification of DTG and 3TC using an XBridge® C18 column and a mobile phase of acetonitrile:phosphate buffer (pH 3.5, 50:50 v/v ). Detection was performed at 258.0 nm for DTG and 275.0 nm for 3TC. The second method, a gradient HPLC, enabled the simultaneous quantification of DTG, 3TC, and ABA on a Spherisorb® ODS2 C18 column with methanol and TEA/TFA buffer (pH 3.15) as the mobile phase. Detection wavelengths were 258.0, 278.0, and 294.0 nm for DTG, 3TC, and ABA, respectively. The calibration ranges were wide and showed excellent linearity. Both techniques were validated in accordance with ICH Q2(R2) guidelines. The approaches align with smart analytical chemistry principles, combining green and white analytical chemistry (GAC and WAC) with AI-driven method development, resulting in accurate, fast, and sustainable techniques suitable for routine quality control applications.