The Anticancer Activity of Cetraria Islandica (L.) Ach in Breast Cancer Cells Through Crosstalk of Ampk-α1 and Erk1/2 Signalling

In the present study, we aimed to evaluate the anticancer activities of Cetraria islandica (C.islandica) extracts on MCF-7 breast cancer cell lines. Cell viability, protein levels, apoptotic cells number, F-actin distribution were measured. Cell viability of MCF-7 breast cancer cells was found to be reduced in a dose-dependent manner.EC50 values of C.islandica on MCF-7 cells were found to be 9.2047 E-5 g/ml (cell amount) by using intelligence system. Expressions of p53, caspase 3 and Bcl-2, were shown to be elevated after low doses of extract and diminished after high dose treatments. PPAR- protein level was decreased, although AMP-activated kinases-α1 (AMPK-α1) protein level was increasedin its extract groups. ERK1/2 protein level was also elevated in its extract groups. 125 mg/ml of extract treated cells show a low decrease in actin filament density. MCF-7 cells with C.islandica treatment for 24 h increased the apoptotic cell percentage, though the cells-treated with C.islandica for 48 was high necrotic cells percentage. Consequently, the C.islandica extract treatment causes to elevate ERK1/2 and AMPK-α1 protein levels, resulting in PPAR- and then triggers the apoptosis by modulation caspase-3 and P53 protein levels. Therefore, C.islandica might be a good candidate for anticancer tissue, especially soft tissue tumours

Is trans-radial approach related to an increased risk of radiation exposure in patients who underwent diagnostic coronary angiography or percutaneous coronary intervention? (The SAKARYA study)

Conclusion: In spite of an increased experience with trans-radial approach, PCI of coronary lesions via radial route was associated with a relatively small but significant radiation exposure in our study. Compared to femoral access, diagnostic CA via radial access was not related to an increased radiation exposure

MMASS: an optimized array-based method for assessing CpG island methylation

We describe an optimized microarray method for identifying genome-wide CpG island methylation called microarray-based methylation assessment of single samples (MMASS) which directly compares methylated to unmethylated sequences within a single sample. To improve previous methods we used bioinformatic analysis to predict an optimized combination of methylation-sensitive enzymes that had the highest utility for CpG-island probes and different methods to produce unmethylated representations of test DNA for more sensitive detection of differential methylation by hybridization. Subtraction or methylation-dependent digestion with McrBC was used with optimized (MMASS-v2) or previously described (MMASS-v1, MMASS-sub) methylation-sensitive enzyme combinations and compared with a published McrBC method. Comparison was performed using DNA from the cell line HCT116. We show that the distribution of methylation microarray data is inherently skewed and requires exogenous spiked controls for normalization and that analysis of digestion of methylated and unmethylated control sequences together with linear fit models of replicate data showed superior statistical power for the MMASS-v2 method. Comparison with previous methylation data for HCT116 and validation of CpG islands from PXMP4, SFRP2, DCC, RARB and TSEN2 confirmed the accuracy of MMASS-v2 results. The MMASS-v2 method offers improved sensitivity and statistical power for high-throughput microarray identification of differential methylation

Systematic evaluation of genome-wide methylated DNA enrichment using a CpG island array

<p>Abstract</p> <p>Background</p> <p>Recent progress in high-throughput technologies has greatly contributed to the development of DNA methylation profiling. Although there are several reports that describe methylome detection of whole genome bisulfite sequencing, the high cost and heavy demand on bioinformatics analysis prevents its extensive application. Thus, current strategies for the study of mammalian DNA methylomes is still based primarily on genome-wide methylated DNA enrichment combined with DNA microarray detection or sequencing. Methylated DNA enrichment is a key step in a microarray based genome-wide methylation profiling study, and even for future high-throughput sequencing based methylome analysis.</p> <p>Results</p> <p>In order to evaluate the sensitivity and accuracy of methylated DNA enrichment, we investigated and optimized a number of important parameters to improve the performance of several enrichment assays, including differential methylation hybridization (DMH), microarray-based methylation assessment of single samples (MMASS), and methylated DNA immunoprecipitation (MeDIP). With advantages and disadvantages unique to each approach, we found that assays based on methylation-sensitive enzyme digestion and those based on immunoprecipitation detected different methylated DNA fragments, indicating that they are complementary in their relative ability to detect methylation differences.</p> <p>Conclusions</p> <p>Our study provides the first comprehensive evaluation for widely used methodologies for methylated DNA enrichment, and could be helpful for developing a cost effective approach for DNA methylation profiling.</p

Biomechanical assessment of brachioradialis pronatorplasty

Objective: Transfer of the brachioradialis muscle, proposed by Ozkan et al. can be applied to cases, in which, the biceps rerouting technique is not appropriate for the correction of forearm supination contracture and restoration of active pronation. We have aimed to assess the biomechanical effects of the brachioradialis transfer

Performance of IRI-based ionospheric critical frequency calculations with reference to forecasting

Ionospheric critical frequency (foF2) is an important ionospheric parameter in telecommunication. Ionospheric processes are highly nonlinear and time varying. Thus, mathematical modeling based on physical principles is extremely difficult if not impossible. The authors forecast foF2 values by using neural networks and, in parallel, they calculate foF2 values based on the IRI model. The foF2 values were forecast 1 h in advance by using the Middle East Technical University Neural Network model (METU-NN) and the work was reported previously. Since then, the METU-NN has been improved. In this paper, 1 h in advance forecast foF2 values and the calculated foF2 values have been compared with the observed values considering the Slough (51.5 degrees N, 0.6 degrees W), Uppsala (59.8 degrees N, 17.6 degrees E), and Rome (41.8 degrees N, 12.5 degrees E) station foF2 data. The authors have considered the models alternative to each other. The performance results of the models are promising. The METU-NN foF2 forecast errors are smaller than the calculated foF2 errors. The models may be used in parallel employing the METU-NN as the primary source for the foF2 forecasting