Tenascin-C fragments are endogenous inducers of cartilage matrix degradation

Cartilage destruction is a hallmark of osteoarthritis (OA) and is characterized by increased protease activity resulting in the degradation of critical extracellular matrix (ECM) proteins essential for maintaining cartilage integrity. Tenascin-C (TN-C) is an ECM glycoprotein, and its expression is upregulated in OA cartilage. We aimed to investigate the presence of TN-C fragments in arthritic cartilage and establish whether they promote cartilage degradation. Expression of TN-C and its fragments was evaluated in cartilage from subjects undergoing joint replacement surgery for OA and RA compared with normal subjects by western blotting. The localization of TN-C in arthritic cartilage was also established by immunohistochemistry. Recombinant TN-C fragments were then tested to evaluate which regions of TN-C are responsible for cartilage-degrading activity in an ex vivo cartilage explant assay measuring glycosaminoglycan (GAG) release, aggrecanase and matrix metalloproteinase (MMP) activity. We found that specific TN-C fragments are highly upregulated in arthritic cartilage. Recombinant TN-C fragments containing the same regions as those identified from OA cartilage mediate cartilage degradation by the induction of aggrecanase activity. TN-C fragments mapping to the EGF-L and FN type III domains 3-8 of TN-C had the highest levels of aggrecan-degrading ability that was not observed either with full-length TN-C or with other domains of TN-C. TN-C fragments represent a novel mechanism for cartilage degradation in arthritis and may present new therapeutic targets for the inhibition of cartilage degradation.     

Recent advances in incretin‐based therapies

The global burden of type 2 diabetes is growing. Traditional therapies are suboptimal and there is a clear unmet need for treatments that offer effective glucose control while addressing the comorbid factors associated with diabetes, such as obesity and risk of cardiovascular disease, without the fear of hypoglycaemia. Glucagon‐like peptide‐1 receptor agonists and dipeptidyl peptidase‐4 inhibitors offer a novel way of reducing hyperglycaemia by targeting the incretin system. This review provides an overview of the development of incretin‐based therapies and explains their differing modes of action compared with traditional interventions. A comparison of the clinical profiles of current glucagon‐like peptide‐1 receptor agonists [liraglutide and exenatide (twice‐daily and once‐weekly)] and dipeptidyl peptidase‐4 inhibitors (sitagliptin, saxagliptin, vildagliptin and linagliptin) is performed alongside a discussion of the placement of incretin‐based therapies in treatment guidelines. Further improvements in this class are expected, and we will examine some of the novel glucagon‐like peptide‐1 receptor agonists and dipeptidyl peptidase‐4 inhibitors currently under development.     

Tumor-specific but not nonspecific cell-free circulating DNA can be used to monitor disease response in lymphoma

Recently, nontumor specific circulating DNA was shown to be elevated in a broad range of lymphomas, implicating a role as a potential biomarker. Epstein-Barr virus' (EBV) presence within a proportion of lymphomas implies EBV-DNA has potential as a lymphoma-specific disease response biomarker. However, application would be restricted to EBV-associated lymphomas. Neither detailed comparison has been performed of lymphoma-specific versus nonspecific DNA as disease response biomarkers nor have the kinetics of circulating DNA during treatment been established, and the optimal methodology remains unknown. We prospectively evaluated DNA levels and clinical response of 63 lymphoma patients. DNA was measured in paired serum, plasma, and cell samples at five predetermined time-points taken prior, during and following treatment. Both cell-free (c-f) circulating EBV-DNA (in EBV-associated lymphoma) and nonspecific c-f DNA levels (in all lymphomas) were elevated and discriminatory at presentation compared to healthy controls. Nonspecific c-f DNA was significantly associated with baseline serum lactate dehydrogenase. Within EBV-associated lymphomas at presentation, there was a strong correlation between specific and nonspecific circulating c-f DNA (r = 0.9, P < 0.0001). However, only c-f EBV-DNA correlated with clinical/radiological response. In addition, c-f EBV-DNA, and not nonspecific c-f DNA, provided an early marker of relapsed and refractory disease. Serum versus plasma, and single versus multiple-copy EBV-gene targets were equivalent. Lymphoma-specific DNA is a disease response biomarker; however, nonspecific DNA reflected neither lymphoma-specific DNA nor therapeutic response. Lymphoma disease response can be monitored by blood tests, but new lymphoma-specific biomarkers need to be identified to broaden applicability.     

Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging

It has long been recognized that the diffusion tensor model is inappropriate to characterize complex fiber architecture, causing tensor‐derived measures such as the primary eigenvector and fractional anisotropy to be unreliable or misleading in these regions. There is however still debate about the impact of this problem in practice. A recent study using a Bayesian automatic relevance detection (ARD) multicompartment model suggested that a third of white matter (WM) voxels contain crossing fibers, a value that, whilst already significant, is likely to be an underestimate. The aim of this study is to provide more robust estimates of the proportion of affected voxels, the number of fiber orientations within each WM voxel, and the impact on tensor‐derived analyses, using large, high‐quality diffusion‐weighted data sets, with reconstruction parameters optimized specifically for this task. Two reconstruction algorithms were used: constrained spherical deconvolution (CSD), and the ARD method used in the previous study. We estimate the proportion of WM voxels containing crossing fibers to be ～90% (using CSD) and 63% (using ARD). Both these values are much higher than previously reported, strongly suggesting that the diffusion tensor model is inadequate in the vast majority of WM regions. This has serious implications for downstream processing applications that depend on this model, particularly tractography, and the interpretation of anisotropy and radial/axial diffusivity measures. Hum Brain Mapp 34:2747–2766, 2013. © 2012 Wiley Periodicals, Inc.     

Surface Dyslexia in Semantic Dementia: A Comparison of the Influence of Consistency and Regularity

Abstract

This study addressed the question of exactly which aspects of spelling-sound consistency influence accuracy of reading aloud in surface dyslexic patients with semantic dementia. Oral reading data were obtained from twelve patients on three sets of words that varied in regularity (defined according to grapheme-phoneme correspondences) and consistency (defined according to the pronunciation of word body neighbours). The patients were less accurate for irregular/inconsistent words, which they commonly pronounced in line with sound-spelling regularities, as expected in surface dyslexia. They produced plausible but incorrect responses for some regular as well as many irregular words, suggesting that their reading performance was influenced by sound-spelling relationships not captured by grapheme-phoneme correspondences. On a set of items that varied consistency and regularity independently, the patients showed a large effect of regularity and a smaller but significant effect of consistency in reading aloud. In addition, there was a correlation between degree of semantic impairment and level of reading accuracy for inconsistent items. These findings are discussed in terms of two influential models of reading: the dual-route-cascaded model (Coltheart et al., 2001 Coltheart, M, Rastle, K, Perry, C, Langdon, R and Ziegler, J. 2001. DRC: A dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 108: 204–56. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) and the triangle model (Plaut et al., 1996 Plaut, DC. 1997. Structure and function in the lexical system: Insights from distributed models of word reading and lexical decision. Language and Cognitive Processes, 12: 765–805. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). It is argued that the triangle model provides a more straightforward account of the relationship between word comprehension and consistency effects in reading.