The endocannabinoid anandamide mediates anti-inflammatory effects through activation of NR4A nuclear receptors.

Background And Purpose: Endocannabinoids are lipid mediators, which elicit complex biological effects that extend beyond the central nervous system. Tissue concentrations of endocannabinoids increase in atherosclerosis, and for the endocannabinoid N-arachidonoyl-ethanolamine (anandamide, AEA), this has been linked to an anti-inflammatory function. In this study, we set out to determine the anti-inflammatory mechanism of action of AEA, specifically focusing on vascular smooth muscle cells.

Physioxia rewires mitochondrial complex composition to protect stem cell viability.

Human induced pluripotent stem cells (hiPSCs) are an invaluable tool to study molecular mechanisms on a human background. Culturing stem cells at an oxygen level different from their microenvironmental niche impacts their viability. To understand this mechanistically, dermal skin fibroblasts of 52 probands were reprogrammed into hiPSCs, followed by either hyperoxic (20 % O) or physioxic (5 % O) culture and proteomic profiling.

RUNX1 interacts with lncRNA SMANTIS to regulate monocytic cell functions.

Monocytes, the circulating macrophage precursors, contribute to diseases like atherosclerosis and asthma. Long non-coding RNAs (lncRNAs) have been shown to modulate the phenotype and inflammatory capacity of monocytes. We previously discovered the lncRNA SMANTIS, which contributes to cellular phenotype expression by controlling BRG1 in mesenchymal cells.

NCoR1 limits angiogenic capacity by altering Notch signaling.

Corepressors negatively regulate gene expression by chromatin compaction. Targeted regulation of gene expression could provide a means to control endothelial cell phenotype. We hypothesize that by targeting corepressor proteins, endothelial angiogenic function can be improved.

Potential and pitfalls of eukaryotic metagenome skimming: a test case for lichens.

Whole-genome shotgun sequencing of multispecies communities using only a single library layout is commonly used to assess taxonomic and functional diversity of microbial assemblages. Here, we investigate to what extent such metagenome skimming approaches are applicable for in-depth genomic characterizations of eukaryotic communities, for example lichens. We address how to best assemble a particular eukaryotic metagenome skimming data, what pitfalls can occur, and what genome quality can be expected from these data.