Beryllium increases the CD14^dimCD16+ subset in the lung of chronic beryllium disease

CD14dimCD16+ and CD14brightCD16+ cells, which compose a minor population of monocytes in human peripheral blood mononuclear cells (PBMC), have been implicated in several inflammatory diseases. The aim of this study was to investigate whether this phenotype was present as a subset of lung infiltrative alveolar macrophages (AMs) in the granulomatous lung disease, chronic beryllium disease (CBD). The monocytes subsets was determined from PBMC cells and bronchoalveolar lavage (BAL) cells from CBD, beryllium sensitized Non-smoker (BeS-NS) and healthy subjects (HS) using flow cytometry. The impact of smoking on the AMs cell phenotype was determined by using BAL cells from BeS smokers (BeS-S). In comparison with the other monocyte subpopulations, CD14dimCD16+ cells were at decreased frequency in PBMCs of both BeS-NS and CBD and showed higher HLA-DR expression, compared to HS. The AMs from CBD and BeS-NS demonstrated a CD14dimCD16+phenotype, while CD14brightCD16+ cells were found at increased frequency in AMs of BeS, compared to HS. Fresh AMs from BeS-NS and CBD demonstrated significantly greater CD16, CD40, CD86 and HLA-DR than HS and BeS-S. The expression of CD16 on AMs from both CBD and BeS-NS was downregulated significantly after 10μM BeSO4 stimulation. The phagocytic activity of AMs decreased after 10μM BeSO4 treatment in both BeS-NS and CBD, although was altered or reduced in HS and BeS-S. These results suggest that Be increases the CD14dimCD16+ subsets in the lung of CBD subjects. We speculate that Be-stimulates the compartmentalization of a more mature CD16+ macrophage phenotype and that in turn these macrophages are a source of Th1 cytokines and chemokines that perpetuate the Be immune response in CBD. The protective effect of cigarette smoking in BeS-S may be due to the low expression of co-stimulatory markers on AMs from smokers as well as the decreased phagocytic function

A Close Eye on the Eagle-Eyed Visual Acuity Hypothesis of Autism

Autism spectrum disorders (ASD) have been associated with sensory hypersensitivity. A recent study reported visual acuity (VA) in ASD in the region reported for birds of prey. The validity of the results was subsequently doubted. This study examined VA in 34 individuals with ASD, 16 with schizophrenia (SCH), and 26 typically developing (TYP). Participants with ASD did not show higher VA than those with SCH and TYP. There were no substantial correlations of VA with clinical severity in ASD or SCH. This study could not confirm the eagle-eyed acuity hypothesis of ASD, or find evidence for a connection of VA and clinical phenotypes. Research needs to further address the origins and circumstances associated with altered sensory or perceptual processing in ASD

Elevated Expression of Phospholipid Transfer Protein in Bone Marrow Derived Cells Causes Atherosclerosis

Background: Phospholipid transfer protein (PLTP) is expressed by various cell types. In plasma, it is associated with high density lipoproteins (HDL). Elevated levels of PLTP in transgenic mice result in decreased HDL and increased atherosclerosis. PLTP is present in human atherosclerosis lesions, where it seems to be macrophage derived. The aim of the present study is to evaluate the atherogenic potential of macrophage derived PLTP. Methods and Findings: Here we show that macrophages from human PLTP transgenic mice secrete active PLTP. Subsequently, we performed bone marrow transplantations using either wild type mice (PLTPwt/wt), hemizygous PLTP transgenic mice (huPLTPtg/wt) or homozygous PLTP transgenic mice (huPLTPtg/tg) as donors and low density lipoprotein receptor deficient mice (LDLR-/-) as acceptors, in order to establish the role of PLTP expressed by bone marrow derived cells in diet-induced atherogenesis. Atherosclerosis was increased in the huPLTPtg/wt → LDLR-/ - mice (2.3-fold) and even further in the huPLTPtg/tg→LDLR-/ - mice (4.5-fold) compared with the control PLTPwt/wt→LDLR-/- mice (both P<0.001). Plasma PLTP activity levels and non-HDL cholesterol were increased and HDL cholesterol decreased compared with controls (all P<0.01). PLTP was present in atherosclerotic plaques in the mice as demonstrated by immunohistochemistry and appears to co-localize with macrophages. Isolated macrophages from PLTP transgenic mice do not show differences in cholesterol efflux or in cytokine production. Lipopolysaccharide activation of macrophages results in increased production of PLTP. This effect was strongly amplified in PLTP transgenic macrophages. Conclusions: We conclude that PLTP expression by bone marrow derived cells results in atherogenic effects on plasma lipids, increased PLTP activity, high local PLTP protein levels in the atherosclerotic lesions and increased atherosclerotic lesion size

Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice