Telomere shortening leads to genomic instability and has been correlated with poor outcome in several types of cancer. A recently described, robust titration assay was used to quantify telomere DNA content in frozen and paraffin-embedded specimens of 49 invasive human breast carcinomas, including tumors with normal or abnormal contents of genomic DNA, which produced regional, distant, or local disease. Telomere DNA contents ranged from 53% to 370% of the content in a reference DNA purified from normal placenta. Tumors were divided into three groups of approximately equal size based on increasing telomere DNA content. All of 16 tumors in the group with the least telomere DNA (Group I), were aneuploid compared to 9/17 tumors in the group with the most telomere DNA (Group III). The Chi-square test for trend indicated that tumors with the least telomere DNA were significantly more likely to be aneuploid than tumors with the most telomere DNA (p < 0.002). Twelve of 14 tumors in Group I also produced metastatic disease compared to 8/15 tumors in Group III. The Fischer Exact Test indicated that tumors with the least telomere DNA were significantly more likely to be metastatic than tumors with the most telomere DNA (p < 0.05). There was no association between telomere DNA content and patients' age, tumors' size, grade, stage, or fraction of cells in S-phase. The correlation of reduced telomere DNA content with aneuploidy and metastasis, both of which are associated with poor outcome in invasive breast carcinoma, implies that telomere DNA content also could have prognostic value.

Telomeres, nucleoprotein complexes at the ends of eukaryotic chromosomes, are 10-12 kbp in length in somatic cells, but as small as 1-2 kbp in rapidly growing cancer cells. Southern blot analysis is currently the standard method for the measurement of telomere length. However, accurate determinations are not possible when DNA is broken or scant. To avoid these problems, a slot blot assay that quantitates the relative content, instead of length, of telomere DNA was developed. The relative contents of telomere DNA determined by this slot blot assay were directly proportional to the relative lengths of telomere DNA determined in parallel by Southern blot analysis. Relative telomere DNA content could be measured in samples containing as little as 15 ng of total DNA. Relative telomere DNA content, but not length, also was unaffected by breakage of DNA into fragments 1 kbp or less in length.

Diabetes is an independent risk factor of cardiovascular disease that can eventually cause cardiomyopathy and heart failure. Cardiac fibroblasts (CF) are the critical mediators of physiological and pathological cardiac remodeling, however, the effects of hyperglycemia on cardiac fibroblast function and differentiation is not well known. Here, we performed a comprehensive investigation on the effects of hyperglycemia on cardiac fibroblasts and show that hyperglycemia enhances cardiac fibroblast function and differentiation. We found that high glucose treatment increased collagen I, III and VI gene expression in rat adult cardiac fibroblasts. Interestingly, hyperglycemia increased CF migration and proliferation which is augmented by collagen I and III. Surprisingly, we found that short term hyperglycemia transiently inhibited ERK1/2 activation but increased AKT phosphorylation. Finally, high glucose treatment increased spontaneous differentiation of cardiac fibroblasts to myofibroblasts with increasing passage compared to low glucose. Taken together, these findings suggest that hyperglycemia induces cardiac fibrosis by modulating collagen expression, migration, proliferation and differentiation of cardiac fibroblasts.

MEG and EEG measure electrophysiological activity in the brain with exquisite temporal resolution. Because of this unique strength relative to noninvasive hemodynamic-based measures (fMRI, PET), the complementary nature of hemodynamic and electrophysiological techniques is becoming more widely recognized (e.g., Human Connectome Project). However, the available analysis methods for solving the inverse problem for MEG and EEG have not been compared and standardized to the extent that they have for fMRI/PET. A number of factors, including the non-uniqueness of the solution to the inverse problem for MEG/EEG, have led to multiple analysis techniques which have not been tested on consistent datasets, making direct comparisons of techniques challenging (or impossible). Since each of the methods is known to have their own set of strengths and weaknesses, it would be beneficial to quantify them. Toward this end, we are announcing the establishment of a website containing an extensive series of realistic simulated data for testing purposes (http://cobre.mrn.org/megsim/). Here, we present: 1) a brief overview of the basic types of inverse procedures; 2) the rationale and description of the testbed created; and 3) cases emphasizing functional connectivity (e.g., oscillatory activity) suitable for a wide assortment of analyses including independent component analysis (ICA), Granger Causality/Directed transfer function, and single-trial analysis.

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