Publications by authors named "F Isık"

Neurodegeneration is characteristically multifaceted, with limited therapeutic options. One of the chief pathophysiological mechanisms driving these conditions is neuroinflammation, prompting increasing clinical interest in immunomodulatory agents. Growth differentiation factor 15 (GDF15; previously also called macrophage inhibitory cytokine-1 or MIC-1), an anti-inflammatory cytokine with established neurotrophic properties, has emerged as a promising therapeutic agent in recent decades.

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Background: Extracellular vesicles are easily accessible in various biofluids and allow the assessment of disease-related changes in the proteome. This has made them a promising target for biomarker studies, especially in the field of neurodegeneration where access to diseased tissue is very limited. Genetic variants in the LRRK2 gene have been linked to both familial and sporadic forms of Parkinson's disease.

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Purpose: To investigate the potential effects of systemic fingolimod treatment on parameters of the anterior segment of the eye and tear film function tests in patients with multiple sclerosis (MS).

Methods: Forty-eight eyes of 24 individuals who were started on systemic fingolimod treatment for relapsing-remitting MS were prospectively enrolled in this study. Patients underwent examinations immediately before initiation of systemic fingolimod treatment, and at the first and sixth months of treatment.

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Amniotic membrane extract (AME) and Wharton's jelly mesenchymal stem cells derived-exosomes (WJ-MSC-Exos) are promising therapeutic solutions explored for their potential in tissue engineering and regenerative medicine, particularly in skin and corneal wound healing applications. AME is an extract form of human amniotic membrane and known to contain a plethora of cytokines and growth factors, making it a highly attractive option for topical applications. Similarly, WJ-MSC-Exos have garnered significant interest for their wound healing properties.

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Objectives: In this study, we developed a machine learning approach for postoperative corneal endothelial cell images of patients who underwent Descemet's membrane keratoplasty (DMEK).

Methods: An AlexNet model is proposed and validated throughout the study for endothelial cell segmentation and cell location determination. The 506 images of postoperative corneal endothelial cells were analyzed.

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