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    Clinicopathological features of breast cancer cases and their relationship with immunohistochemical findings
    (2020) Tuncel, Ferah; Gokalp Satici, Fadime Eda; Duman, Aslihan Alpaslan; Bozkurt, Funda; Dag, Ahmet
    Aim: To determine the relationship between established prognostic markers and Ki67 proliferative index in breast cancer patients and investigate variations of prognostic parameters between material types (tru-cut biopsy or resection). Material and Methods: Breast cancer cases reported in our laboratory between July 2015 and December 2019, as well as estrogen receptor (ER), progesterone receptor (PR), CerbB2, Ki-67 staining results, tumor type, histologic grade, tumor size, lymph node metastasis status parameters were obtained from the automation system. Tru-cut biopsy and resection materials were evaluated and the parameters were compared. Results: 726 materials taken from 571 adult patients were included in this study. 297 (40.9%) of the cases were evaluated by tru-cut biopsy and 430 (59.1%) were resection material. The mean ER staining percentage was 86.5 (± 10.36) and it was 61.65 (± 22.84) for PR. Ki-67 proliferative index had an average value of 26.58 (± 17.67). There was no difference between the material types in terms of immunohistochemical markers, whereas there were differences between the two material types in histological grade results.Conclusion: Besides established immunohistochemical prognostic markers, Ki67 proliferative index should be utilized in breast cancer cases and determination of histological grade in tru-cut biopsies is valuable for the clinical management of the tumor.
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    Mapping water chemical variables with spatially correlated errors
    (Springer, 2013) Tutmez, Bulent; Dag, Ahmet
    One of the most important considerations in many environmental studies is need to allow for correlations among the variables. Monitoring and analyzing relationships between chemical environmental parameters using spatial correlation based regression modelling is the main motivation of this applied study. For this purpose, some noticeable environmental parameters of data sets obtained from two lakes have been considered and the concentrations of chemical variables such as cadmium and nitrate have been appraised by a regression-based geostatistical methodology. The modelling procedure consists of two stages. In the first stage, spatial variables are analyzed via multi-linear regression and some relationships are provided. Next, by using the spatial auto-correlations of the residuals, a type of regression-based kriging procedure is applied. The capacity of the model for appraising the water chemical variables is also tested and performance comparisons with ordinary kriging are conducted. Finally, the applications showed that analyzing water chemical variables with spatially correlated errors is a convenient and applicable approach for assessing the environmental systems.
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    Regression-based algorithms for exploring the relationships in a cement raw material quarry
    (Techno-Press, 2012) Tutmez, Bulent; Dag, Ahmet
    Using appropriate raw materials for cement is crucial for providing the required products. Monitoring relationships and analyzing distributions in a cement material quarry are important stages in the process. CaO, one of the substantial chemical components, is included in some raw materials such as limestone and marl; furthermore, appraising spatial assessment of this chemical component is also very critical. In this study, spatial evaluation and monitoring of CaO concentrations in a cement site are considered. For this purpose, two effective regression-based models were applied to a cement quarry located in Turkey. For the assessment, some spatial models were developed and performance comparisons were carried out. The results show that the regression-based spatial modelling is an efficient methodology and it can be employed to evaluate spatially varying relationships in a cement quarry.