Objective: Using CT texture analysis and machine learning methods, this study aims to distinguish the lesions imaged via 68Ga-prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/CT as metastatic and completely responded in patients with known bone metastasis and who were previously treated. Methods: We retrospectively reviewed the 68Ga-PSMA PET/CT images of 75 patients after treatment, who were previously diagnosed with prostate cancer and had known bone metastasis. A texture analysis was performed on the metastatic lesions showing PSMA expression and completely responded sclerotic lesions without PSMA expression through CT images. Textural features were compared in two groups. Thus, the distinction of metastasis/completely responded lesions and the most effective parameters in this issue were determined by using various methods [decision tree, discriminant analysis, support vector machine (SVM), k-nearest neighbor (KNN), ensemble classifier] in machine learning. Results: In 28 of the 35 texture analysis findings, there was a statistically significant difference between the two groups. The Weighted KNN method had the highest accuracy and area under the curve, has been chosen as the best model. The weighted KNN algorithm was succeeded to differentiate sclerotic lesion from metastasis or completely responded lesions with 0.76 area under the curve. GLZLM_SZHGE and histogram-based kurtosis were found to be the most important parameters in differentiating metastatic and completely responded sclerotic lesions. Conclusions: Metastatic lesions and completely responded sclerosis areas in CT images, as determined by 68Ga-PSMA PET, could be distinguished with good accuracy using texture analysis and machine learning (Weighted KNN algorithm) in prostate cancer. Advances in knowledge: Our findings suggest that, with the use of newly emerging software, CT imaging can contribute to identifying the metastatic lesions in prostate cancer.

Background/aim: Natural products are popular insights for researchers to investigate promising anti-cancer agents since some of these substances have lesser adverse effects restricting the treatment than traditional chemotherapeutic agents. A well-known monoterpene Carvacrol, widely consumed in Mediterranean cuisine and lower risks of cancer, has efficient anticancer effects. However, the mechanism of action is yet to be discovered. Materials and methods: The investigation aims to illuminate a new perceptive in the role of this substance on colorectal cancer treatment, by the means of differences in a well-defined range of soluble factors. Carvacrol effect on both HT-29 and HCT-116 cell lines was evaluated on proliferation and the IC 50 values were calculated by the RTCA xCELLigence device. Then MAGPIX assay was performed to obtain the changes in soluble factors of the cell lines. Results: The Multiplexing assay suggests some of these factors were altered in favor of surviving and proliferation in aggressive cell line HCT-116 whereas they were altered against these characters in HT-29, were correlated with the increased IC 50 concentration of HCT-116 in carvacrol treatment. Conclusion: The current study indicates that differences in the levels of these soluble factors could modulate the anticancer effect related to carvacrol.

Background/aim Established reference values are critical for the interpretation of immunologic assessments. In particular, the proportion and absolute counts of T- and B- cell subpopulations are subject to change with age and ethnicity. We aimed to establish age-specific reference values for lymphocyte subsets using updated immunophenotyping panels. Materials and methods We studied a total of 297 healthy Turkish subjects aged 0 to 50 years, stratified into major age brackets in a cluster factor of 10 per age-group. The predetermined age intervals contained randomly allocated participants enrolled over a period of 6 months, who were homogenously distributed by sex. We analyzed a complete blood count test and simultaneously with detailed immunophenotyping enumerated the percent and absolute cell counts of lymphocyte subsets. Results The percentage and absolute counts of lymphocyte subsets show a marked surge across the age-span. T helper, T cytotoxic, and the natural killer cell numbers were increasing from birth until 6 months, followed by a gradual decrease thereafter. B cell numbers were rising until 2 years, followed by a gradual decrease for the upcoming years, accompanied by a steady expansion of unclass-switched- and class-switched- B cells. Conclusion We provide updated extensive reference intervals for lymphocyte subpopulations in Turkish people.

As in all living cells, cancer cells are evaluating is very important in the frames of tumor development and treatment. As in all evolutionary process, the environment of living cells has an important role. Tumor cells have an environment is called tumor microenvironment, affects the therapeutic response and clinical results. Tumor microenvironments involve various cell types, extracellular matrix substances that are in the niche of cancer cells. The microenvironment is not only important in tumorigenesis but it is effective on therapeutic efficacy. In this review, we carried out the interaction between non-small cell lung cancer and its microenvironment to point out the significance of the tumor environment.

Adenomatous polyps of the colon are the most common neoplastic polyps. Although most of adenomatous polyps do not show malign transformation, majority of colorectal carcinomas originate from neoplastic polyps. Therefore, understanding of this transformation process would help in both preventive therapies and evaluation of malignancy risks. This study uncovers alterations in gene expressions as potential biomarkers that are revealed by integration of several network-based approaches. In silico analysis performed on a unified microarray cohort, which is covering 150 normal colon and adenomatous polyp samples. Significant gene modules were obtained by a weighted gene co-expression network analysis. Gene modules with similar profiles were mapped to a colon tissue specific functional interaction network. Several clustering algorithms run on the colon-specific network and the most significant sub-modules between the clusters were identified. The biomarkers were selected by filtering differentially expressed genes which also involve in significant biological processes and pathways. Biomarkers were also validated on two independent datasets based on their differential gene expressions. To the best of our knowledge, such a cascaded network analysis pipeline was implemented for the first time on a large collection of normal colon and polyp samples. We identified significant increases in TLR4 and MSX1 expressions as well as decrease in chemokine profiles with mostly pro-tumoral activities. These biomarkers might appear as both preventive targets and biomarkers for risk evaluation. As a result, this research proposes novel molecular markers that might be alternative to endoscopic approaches for diagnosis of adenomatous polyps.