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Impact of Refractive Errors on Da Vinci SI Robotic System
(SOC LAPAROENDOSCOPIC SURGEONS, 2020-01-01) Tuna, Mustafa Bilal; Kilavuzoglu, Ayse Ebru; Mourmouris, Panogiotis; Argun, Omer Burak; Doganca, Tunkut; Obek, Can; Ozisik, Ozan; Kural, Ali Riza
Objective: To investigate the impact of refractive errors on binocular visual acuity while using the Da Vinci SI robotic system console. Methods: Eighty volunteers were examined on the Da Vinci SI robotic system console by using a near vision chart. Refractive errors, anisometropia status, and Fly Stereo Acuity Test scores were recorded. Spherical equivalent (SE) were calculated for all volunteers' right and left eyes. Visual acuity was assessed by the logarithm of the minimal angle of resolution (LogMAR) method. Binocular uncorrected and best corrected (with proper contact lens or glasses) LogMAR values of the subjects were recorded. The difference between these values (DiffLogMAR) are affected by different refractive errors. Results: In the myopia and/or astigmatism group, uncorrected SE was found to have significant impact on the DiffLogMAR (P < 0.001) and myopia greater than 1.75 diopter had significantly higher DiffLogMAR values (p < 0.05). Subjects with presbyopia had significantly higher DiffLogMAR values (p < 0.01), and we observed positive correlation between presbyopia and DiffLogMAR values (p = 0.33, p < 0.01). The cut off value of presbyopia that correlated the most with DiffLogMAR differences was found to be 1.25 diopter (P< 0.001). In 13 hypermetropic volunteers, we found significant correlation between hypermetropia value and DiffLogMAR (p > 0.7, p < 0.01). The statistical analysis between Fly test and SE revealed a significant impact of presbyopia and hypermetropia to the stereotactic view of the subject (p = -0.734, p < 0.05). Conclusion: Surgeons suffering from myopia greater than 1.75 diopter, presbyopia greater than 1.25 diopter (D), and hypermetropia regardless of grade must always perform robotic surgeries with the proper correction.
Progesterone at high doses reduces the growth of U87 and A172 glioblastoma cells: Proteomic changes regarding metabolism and immunity
(WILEY, 2020-01-01) Altinoz, Meric A.; Ucal, Yasemin; Yilmaz, Muazzez C.; Kiris, Irem; Ozisik, Ozan; Sezerman, Ugur; Ozpinar, Aysel; Elmaci, Ilhan
While pregnancy may accelerate glioblastoma multiforme (GBM) growth, parity and progesterone (P4) containing treatments (ie, hormone replacement therapy) reduce the risk of GBM development. In parallel, low and high doses of P4 exert stimulating and inhibitory actions on GBM growth, respectively. The mechanisms behind the high-dose P4-suppression of GBM growth is unknown. In the present study, we assessed the changes in growth and proteomic profiles when high-dose P4 (100 and 300 mu M) was administered in human U87 and A172 GBM cell lines. The xCELLigence system was used to examine cell growth when different concentrations of P4 (20, 50, 100, and 300 mu M) was administered. The protein profiles were determined by two-dimensional gel electrophoresis in both cell lines when 100 and 300 mu M P4 were administered. Finally, the pathways enriched by the differentially expressed proteins were assessed using bioinformatic tools. Increasing doses of P4 blocked the growth of both GBM cells. We identified 26 and 51 differentially expressed proteins (fc > 2) in A172 and U87 cell lines treated with P4, respectively. Only the pro-tumorigenic mitochondrial ornithine aminotransferase and anti-apoptotic mitochondrial 60 kDa heat shock protein were downregulated in A172 cell line and U87 cell line when treated with P4, respectively. Detoxification of reactive oxygen species, cellular response to stress, glucose metabolism, and immunity-related proteins were altered in P4-treated GBM cell lines. The paradox on the effect of low and high doses of P4 on GBM growth is gaining attention. The mechanism related to the high dose of P4 on GBM growth can be explained by the alterations in detoxification mechanisms, stress, and immune response and glucose metabolism. P4 suppresses GBM growth and as it is nontoxic in comparison to classical chemotherapeutics, it can be used as a new strategy in GBM treatment in the future.
pathfindR: An R Package for Comprehensive Identification of Enriched Pathways in Omics Data Through Active Subnetworks
(FRONTIERS MEDIA SA, 2019-01-01) Ulgen, Ege; Ozisik, Ozan; Sezerman, Osman Ugur
Pathway analysis is often the first choice for studying the mechanisms underlying a phenotype. However, conventional methods for pathway analysis do not take into account complex protein-protein interaction information, resulting in incomplete conclusions. Previously, numerous approaches that utilize protein-protein interaction information to enhance pathway analysis yielded superior results compared to conventional methods. Hereby, we present pathfindR, another approach exploiting protein-protein interaction information and the first R package for active-subnetwork-oriented pathway enrichment analyses for class comparison omics experiments. Using the list of genes obtained from an omics experiment comparing two groups of samples, pathfindR identifies active subnetworks in a protein-protein interaction network. It then performs pathway enrichment analyses on these identified subnetworks. To further reduce the complexity, it provides functionality for clustering the resulting pathways. Moreover, through a scoring function, the overall activity of each pathway in each sample can be estimated. We illustrate the capabilities of our pathway analysis method on three gene expression datasets and compare our results with those obtained from three popular pathway analysis tools. The results demonstrate that literature-supported disease-related pathways ranked higher in our approach compared to the others. Moreover, pathfindR identified additional pathways relevant to the conditions that were not identified by other tools, including pathways named after the conditions.

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