Browsing by Subject "Quantitative analysis"

Now showing 1 - 4 of 4

Open Access
Colon cancer associated transcript-1 (CCAT1) expression in adenocarcinoma of the stomach
(Ivyspring International Publisher, 2015) Mizrahi, I.; Mazeh, H.; Grinbaum, R.; Beglaibter, N.; Wilschanski, M.; Pavlov, V.; Adileh, M.; Stojadinovic, A.; Avital, I.; Gure, A. O.; Halle, D.; Nissan, A.
Background: Long non-coding RNAs (lncRNAs) have been shown to have functional roles in cancer biology and are dys-regulated in many tumors. Colon Cancer Associated Transcript -1 (CCAT1) is a lncRNA, previously shown to be significantly up-regulated in colon cancer. The aim of this study is to determine expression levels of CCAT1 in gastric carcinoma (GC). Methods: Tissue samples were obtained from patients undergoing resection for gastric carcinoma (n=19). For each patient, tumor tissue and normal appearing gastric mucosa were taken. Normal gastric tissues obtained from morbidly obese patients, undergoing laparoscopic sleeve gastrectomy served as normal controls (n=19). A human gastric carcinoma cell line (AGS) served as positive control. RNA was extracted from all tissue samples and CCAT1 expression was analyzed using quantitative real time-PCR (qRT-PCR). Results: Low expression of CCAT1 was identified in normal gastric mucosa samples obtained from morbidly obese patients [mean Relative Quantity (RQ) = 1.95±0.4]. AGS human gastric carcinoma cell line showed an elevated level of CCAT1 expression (RQ=8.02). Expression levels of CCAT1 were approximately 10.8 fold higher in GC samples than in samples taken from the negative control group (RQ=21.1±5 vs. RQ=1.95±0.4, respectively, p<0.001). Interestingly, CCAT1 expression was significantly overexpressed in adjacent normal tissues when compared to the negative control group (RQ = 15.25±2 vs. RQ=1.95±0.4, respectively, p<0.001). Tissues obtained from recurrent GC cases showed the highest expression levels (RQ = 88.8±31; p<0.001). Expression levels increased with tumor stage (T4- 36.4±15, T3- 16.1±6, T2- 4.7±1), however this did not reach statistical significance (p=0.2). There was no difference in CCAT1 expression between intestinal and diffuse type GC (RQ=22.4±7 vs. 22.4±16, respectively, p=0.9). Within the normal gastric tissue samples, no significant difference in CCAT1 expression was observed in helicobacter pylori negative and positive patients (RQ= 2.4±0.9 vs. 0.93±0.2, respectively, p=0.13). Conclusion: CCAT1 is up-regulated in gastric cancer, and may serve as a potential bio-marker for early detection and surveillance.
Open Access
Increasing the effectiveness of time-use survey with qualitative methods: the analysis of time-space interaction
(Routledge, 2010-03) Erkip, F.; Mugana, G.
Time-use surveys have been rich data sources in many countries for a long time. Turkey was among the countries that realized the potential of time-use surveys quite late and completed the first national survey in 2006. Despite its importance for a wide range of issues and applications, the first survey has flaws in design, which reduce its effectiveness and reliability. This is mostly due to disregarding cultural factors while tracking the methodology of European examples. This study aims to propose more appropriate methods of gathering time-use data in the Turkish context through a field survey in Ankara, the capital city. A mixed methodology that combines quantitative and qualitative methods effectively was applied and used to enrich data. The influence of space use was stressed and leisure activities were utilized to exemplify the use and benefits of mixed methods. © 2010 Interdisciplinary Centre for Comparative Research in the Social Sciences and ICCR Foundation.
Open Access
Nicotine coregulates multiple pathways involved in protein modification/degradation in rat brain
(Elsevier, 2004) Kane, J. K.; Konu, Özlem; Ma, J. Z.; Li, M. D.
Previously, we used cDNA microarrays to demonstrate that the phosphatidylinositol and MAP kinase signaling pathways are regulated by nicotine in different rat brain regions. In the present report, we show that, after exposure to nicotine for 14 days, ubiquitin, ubiquitin-conjugating enzymes, 20S and 19S proteasomal subunits, and chaperonin-containing TCP-1 protein (CCT) complex members are upregulated in rat prefrontal cortex (PFC) while being downregulated in the medial basal hypothalamus (MBH). In particular, relative to saline controls, ubiquitins B and C were upregulated by 33% and 47% (P<0.01), respectively, in the PFC. The proteasome beta subunit 1 (PSMB1) and 26S ATPase 3 (PSMC3) genes were upregulated in the PFC by 95% and 119% (P<0.001), respectively. In addition to the protein degradation pathway of the ubiquitin-proteasome complexes, we observed in the PFC an increase in the expression of small, ubiquitin-related modifiers (SUMO) 1 and 2 by 80% and 33%, respectively (P<0.001), and in 3 of 6 CCT subunits by up to 150% (P<0.0001). To a lesser extent, a change in the opposite direction was obtained in the expression of the same gene families in the MBH. Quantitative real-time RT-PCR was used to validate the microarray results obtained with some representative genes involved in these pathways. Taken together, our results suggest that, in response to systemic nicotine administration, the ubiquitin-proteasome, SUMO, and chaperonin complexes provide an intricate control mechanism to maintain cellular homeostasis, possibly by regulating the composition and signaling of target neurons in a region-specific manner.
Open Access
Object-oriented texture analysis for the unsupervised segmentation of biopsy images for cancer detection
(Elsevier BV, 2009-06) Tosun, A. B.; Kandemir, M.; Sokmensuer, C.; Gunduz Demir, C.
Staining methods routinely used in pathology lead to similar color distributions in the biologically different regions of histopathological images. This causes problems in image segmentation for the quantitative analysis and detection of cancer. To overcome this problem, unlike previous methods that use pixel distributions, we propose a new homogeneity measure based on the distribution of the objects that we define to represent tissue components. Using this measure, we demonstrate a new object-oriented segmentation algorithm. Working with colon biopsy images, we show that this algorithm segments the cancerous and normal regions with 94.89 percent accuracy on the average and significantly improves the segmentation accuracy compared to its pixel-based counterpart. © 2008 Elsevier Ltd. All rights reserved.