Browsing by Author "Sahin, Ali"

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    Evidence that osteogenic and neurogenic differentiation capability of epidural adipose tissue-derived stem cells was more pronounced than in subcutaneous cells
    (2020) Solmaz, Bilgehan; Sahin, Ali; Kelestemur, Taha; Kilic, Ertugrul; Kaptanoglu, Erkan; 32222128
    Background/aim: The management of dura-related complications, such as the repairment of dural tears and reconstruction of large dural defects, remain the most challenging subjects of neurosurgery. Numerous surgical techniques and synthetic or autologous adjuvant materials have emerged as an adjunct to primary dural closure, which may result in further complications or side effects. Therefore, the subcutaneous autologous free adipose tissue graft has been recommended for the protection of the central nervous system and repairment of the meninges. In addition, human adipose tissue is also a source of multipotent stem cells. However, epidural adipose tissue seems more promising than subcutaneous because of the close location and intercellular communication with the spinal cord. Herein, it was aimed to define differentiation capability of both subcutaneous and epidural adipose tissue-derived stem cells (ASCs). Materials and methods: Human subcutaneous and epidural adipose tissue specimens were harvested from the primary incisional site and the lumbar epidural space during lumbar spinal surgery, and ASCs were isolated. Results: The results indicated that both types of ASCs expressed the cell surface markers, which are commonly expressed stem cells; however, epidural ASCs showed lower expression of CD90 than the subcutaneous ASCs. Moreover, it was demonstrated that the osteogenic and neurogenic differentiation capability of epidural adipose tissue-derived ASCs was more pronounced than that of the subcutaneous ASCs. Conclusion: Consequently, the impact of characterization of epidural ASCs will allow for a new understanding for dural as well as central nervous system healing and recovery after an injury.
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    Methodology of a new inflammatory arthritis registry: TReasure
    (2018) Tufan, Muge Aydin; Kalyoncu, Umut; Tascilar, Etem Koray; Ertenli, Ali Ihsan; Dalkilic, Huseyin Ediz; Bes, Cemal; Kucuksahin, Orhan; Kasifoglu, Timucin; Alpay Kanitez, Nilufer; Emmungil, Hakan; Kimyon, Gezmis; Yasar Bilge, Nafize Sule; Akar, Servet; Atagunduz, Mehmet Pamir; Koca, Suleyman Serdar; Ates, Askin; Yazisiz, Veli; Terzioglu, Ender; Ersozlu, Emine Duygu; Tufan, Muge Aydin; Cinar, Muhammet; Mercan, Ridvan; Sahin, Ali; Erten, Sukran; Pehlivan, Yavuz; Yilmaz, Sedat; Kelesoglu Dincer, Ayse Bahar; Gercik, Onay; Coskun, Belkis Nihan; Yagiz, Burcu; Kaymaz Tahra, Sema; Aksoy, Aysun; Karadag, Omer; Kilic, Levent; Kiraz, Sedat; 30119164
    Background/aim: The TReasure registry, created in 2017, is an observational multicenter cohort that includes inflammatory arthritis patients. This article reviews the methodology and objectives of the TReasure registry established to collect data from rheumatoid arthritis (RA) and spondyloarthritis (SpA) patients. Methodology: Fifteen rheumatology centers in Turkey will contribute data to the TReasure database. The actual proprietor of the database is the Hacettepe Rheumatology Association (HRD) and Hacettepe Financial Enterprises. Pharmaceutical companies that operate in Turkey (in alphabetical or er), Abbvie, Amgen, BMS, Celltrion Healthcare, Novartis, Pfizer, Roche, and UCB, support the TReasure registry. TReasure is a web-based database to which users connect through a URL (https://www.trials-network.org/treasure) with their unique identifier and passwords provided for data entry and access. TReasure records demographic and clinical features, comorbidities, radiology and laboratory results, measures of disease activity, and treatment data. Discussion: TReasure will provide us with various types of data, such as a cross-sectional view of the current nationwide status of the patients currently receiving these treatments, and retrospective data as much as allowed by the participating centers' records. Finally, a high-quality prospective dataset will be built over the ensuing years from patients with a new diagnosis of RA or SpA.