Lack of antigen-specific tissue remodeling in mice deficient in the macrophage galactose-type calcium-type lectin 1/CD301a.

Macrophage galactose-type C-type lectins (MGLs), which were recently named CD301, have 2 homologues in mice: MGL1 and MGL2. MGLs are expressed on macrophages and immature dendritic cells. The persistent presence of granulation tissue induced by a protein antigen was observed in wild-type mice but not in mice lacking an endogenous, macrophage-specific, galactose-type calcium-type lectin 1 (MGL1) in an air pouch model. The anti-MGL1 antibody suppressed the granulation tissue formation in wild-type mice. A large number of cells, present only in the pouch of MGL1-deficient mice, were not myeloid or lymphoid lineage cells and the number significantly declined after administration of interleukin 1 alpha (IL-1alpha) into the pouch of MGL1-deficient mice. Furthermore, granulation tissue was restored by this treatment and the cells obtained from the pouch of MGL1-deficient mice were incorporated into the granulation tissue when injected with IL-1alpha. Taken together, MGL1 expressed on a specific subpopulation of macrophages that secrete IL-1alpha was proposed to regulate specific cellular interactions crucial to granulation tissue formation

An Integrative Multi-Network and Multi-Classifier Approach to Predict Genetic Interactions

Genetic interactions occur when a combination of mutations results in a surprising phenotype. These interactions capture functional redundancy, and thus are important for predicting function, dissecting protein complexes into functional pathways, and exploring the mechanistic underpinnings of common human diseases. Synthetic sickness and lethality are the most studied types of genetic interactions in yeast. However, even in yeast, only a small proportion of gene pairs have been tested for genetic interactions due to the large number of possible combinations of gene pairs. To expand the set of known synthetic lethal (SL) interactions, we have devised an integrative, multi-network approach for predicting these interactions that significantly improves upon the existing approaches. First, we defined a large number of features for characterizing the relationships between pairs of genes from various data sources. In particular, these features are independent of the known SL interactions, in contrast to some previous approaches. Using these features, we developed a non-parametric multi-classifier system for predicting SL interactions that enabled the simultaneous use of multiple classification procedures. Several comprehensive experiments demonstrated that the SL-independent features in conjunction with the advanced classification scheme led to an improved performance when compared to the current state of the art method. Using this approach, we derived the first yeast transcription factor genetic interaction network, part of which was well supported by literature. We also used this approach to predict SL interactions between all non-essential gene pairs in yeast (http://sage.fhcrc.org/downloads/downloads/predicted_yeast_genetic_interactions.zip). This integrative approach is expected to be more effective and robust in uncovering new genetic interactions from the tens of millions of unknown gene pairs in yeast and from the hundreds of millions of gene pairs in higher organisms like mouse and human, in which very few genetic interactions have been identified to date

Identification of a 4-microRNA Signature for Clear Cell Renal Cell Carcinoma Metastasis and Prognosis

Renal cell carcinoma (RCC) metastasis portends a poor prognosis and cannot be reliably predicted. Early determination of the metastatic potential of RCC may help guide proper treatment. We analyzed microRNA (miRNA) expression in clear cell RCC (ccRCC) for the purpose of developing a miRNA expression signature to determine the risk of metastasis and prognosis. We used the microarray technology to profile miRNA expression of 78 benign kidney and ccRCC samples. Using 28 localized and metastatic ccRCC specimens as the training cohort and the univariate logistic regression and risk score methods, we developed a miRNA signature model in which the expression levels of miR-10b, miR-139-5p, miR-130b and miR-199b-5p were used to determine the status of ccRCC metastasis. We validated the signature in an independent 40-sample testing cohort of different stages of primary ccRCCs using the microarray data. Within the testing cohort patients who had at least 5 years follow-up if no metastasis developed, the signature showed a high sensitivity and specificity. The risk status was proven to be associated with the cancer-specific survival. Using the most stably expressed miRNA among benign and tumorous kidney tissue as the internal reference for normalization, we successfully converted his signature to be a quantitative PCR (qPCR)-based assay, which showed the same high sensitivity and specificity. The 4-miRNA is associated with ccRCC metastasis and prognosis. The signature is ready for and will benefit from further large clinical cohort validation and has the potential for clinical application

Exposure assessment of process-related contaminants in food by biomarker monitoring

Exposure assessment is a fundamental part of the risk assessment paradigm, but can often present a number of challenges and uncertainties. This is especially the case for process contaminants formed during the processing, e.g. heating of food, since they are in part highly reactive and/or volatile, thus making exposure assessment by analysing contents in food unreliable. New approaches are therefore required to accurately assess consumer exposure and thus better inform the risk assessment. Such novel approaches may include the use of biomarkers, physiologically based kinetic (PBK) modelling-facilitated reverse dosimetry, and/or duplicate diet studies. This review focuses on the state of the art with respect to the use of biomarkers of exposure for the process contaminants acrylamide, 3-MCPD esters, glycidyl esters, furan and acrolein. From the overview presented, it becomes clear that the field of assessing human exposure to process-related contaminants in food by biomarker monitoring is promising and strongly developing. The current state of the art as well as the existing data gaps and challenges for the future were defined. They include (1) using PBK modelling and duplicate diet studies to establish, preferably in humans, correlations between external exposure and biomarkers; (2) elucidation of the possible endogenous formation of the process-related contaminants and the resulting biomarker levels; (3) the influence of inter-individual variations and how to include that in the biomarker-based exposure predictions; (4) the correction for confounding factors; (5) the value of the different biomarkers in relation to exposure scenario’s and risk assessment, and (6) the possibilities of novel methodologies. In spite of these challenges it can be concluded that biomarker-based exposure assessment provides a unique opportunity to more accurately assess consumer exposure to process-related contaminants in food and thus to better inform risk assessment

Importance of rostral ventrolateral medulla neurons in determining efferent sympathetic nerve activity and blood pressure

Accentuated sympathetic nerve activity (SNA) is a risk factor for cardiovascular events. In this review, we investigate our working hypothesis that potentiated activity of neurons in the rostral ventrolateral medulla (RVLM) is the primary cause of experimental and essential hypertension. Over the past decade, we have examined how RVLM neurons regulate peripheral SNA, how the sympathetic and renin-angiotensin systems are correlated and how the sympathetic system can be suppressed to prevent cardiovascular events in patients. Based on results of whole-cell patch-clamp studies, we report that angiotensin II (Ang II) potentiated the activity of RVLM neurons, a sympathetic nervous center, whereas Ang II receptor blocker (ARB) reduced RVLM activities. Our optical imaging demonstrated that a longitudinal rostrocaudal column, including the RVLM and the caudal end of ventrolateral medulla, acts as a sympathetic center. By organizing and analyzing these data, we hope to develop therapies for reducing SNA in our patients. Recently, 2-year depressor effects were obtained by a single procedure of renal nerve ablation in patients with essential hypertension. The ablation injured not only the efferent renal sympathetic nerves but also the afferent renal nerves and led to reduced activities of the hypothalamus, RVLM neurons and efferent systemic sympathetic nerves. These clinical results stress the importance of the RVLM neurons in blood pressure regulation. We expect renal nerve ablation to be an effective treatment for congestive heart failure and chronic kidney disease, such as diabetic nephropathy