Dysregulated expression of MIG/CXCL9, IP-10/CXCL10 and CXCL16 and their receptors in systemic sclerosis

Abstract Introduction Systemic sclerosis (SSc) is characterized by fibrosis and microvascular abnormalities including dysregulated angiogenesis. Chemokines, in addition to their chemoattractant properties, have the ability to modulate angiogenesis. Chemokines lacking the enzyme-linked receptor (ELR) motif, such as monokine induced by interferon-γ (IFN-γ) (MIG/CXCL9) and IFN-inducible protein 10 (IP-10/CXCL10), inhibit angiogenesis by binding CXCR3. In addition, CXCL16 promotes angiogenesis by binding its unique receptor CXCR6. In this study, we determined the expression of these chemokines and receptors in SSc skin and serum. Methods Immunohistology and enzyme-linked immunosorbent assays (ELISAs) were used to determine chemokine and chemokine receptor expression in the skin and serum, respectively, of SSc and normal patients. Endothelial cells (ECs) were isolated from SSc skin biopsies and chemokine and chemokine receptor expression was determined by quantitative PCR and immunofluorescence staining. Results Antiangiogenic IP-10/CXCL10 and MIG/CXCL9 were elevated in SSc serum and highly expressed in SSc skin. However, CXCR3, the receptor for these chemokines, was decreased on ECs in SSc vs. normal skin. CXCL16 was elevated in SSc serum and increased in SSc patients with early disease, pulmonary arterial hypertension, and those that died during the 36 months of the study. In addition, its receptor CXCR6 was overexpressed on ECs in SSc skin. At the mRNA and protein levels, CXCR3 was decreased while CXCR6 was increased on SSc ECs vs. human microvascular endothelial cells (HMVECs). Conclusions These results show that while the expression of MIG/CXCL9 and IP-10/CXCL10 are elevated in SSc serum, the expression of CXCR3 is downregulated on SSc dermal ECs. In contrast, CXCL16 and CXCR6 are elevated in SSc serum and on SSc dermal ECs, respectively. In all, these findings suggest angiogenic chemokine receptor expression is likely regulated in an effort to promote angiogenesis in SSc skin.http://deepblue.lib.umich.edu/bitstream/2027.42/112894/1/13075_2010_Article_3001.pd

What is Islamic microfinance?

Islamic microfinance is a specialized part in a growing and diverse body of microfinance literature. To date, there are quite a few papers on Islamic microfinance that are published in reputable journals, which fairly represent the size of Islamic microfinance industry compared to the overall microfinance sector. This chapter aims to provide an overview of Islamic microfinance in the context of mainstream microfinance sector and highlights some of the salient features that differentiate Islamic microfinance with conventional or overall microfinance. It will discuss the origin, different approaches in the development, and characteristics of Islamic microfinance. These will be followed by discussion on lending models, sources and uses of funds, and poverty impact of Islamic microfinance institutions. Finally, this chapter will conclude will some thoughts on possible opportunities for future Islamic microfinance research

Large-scale targeted sequencing identifies risk genes for neurodevelopmental disorders

Most genes associated with neurodevelopmental disorders (NDDs) were identified with an excess of de novo mutations (DNMs) but the significance in case-control mutation burden analysis is unestablished. Here, we sequence 63 genes in 16,294 NDD cases and an additional 62 genes in 6,211 NDD cases. By combining these with published data, we assess a total of 125 genes in over 16,000 NDD cases and compare the mutation burden to nonpsychiatric controls from ExAC. We identify 48 genes (25 newly reported) showing significant burden of ultra-rare (MAF < 0.01%) gene-disruptive mutations (FDR 5%), six of which reach family-wise error rate (FWER) significance (p < 1.25E-06). Among these 125 targeted genes, we also reevaluate DNM excess in 17,426 NDD trios with 6,499 new autism trios. We identify 90 genes enriched for DNMs (FDR 5%; e.g., GABRG2 and UIMC1); of which, 61 reach FWER significance (p < 3.64E-07; e.g., CASZ1). In addition to doubling the number of patients for many NDD risk genes, we present phenotype-genotype correlations for seven risk genes (CTCF, HNRNPU, KCNQ3, ZBTB18, TCF12, SPEN, and LEO1) based on this large-scale targeted sequencing effort