Adipose triglyceride lipase regulates eicosanoid production in activated human mast cells

Human mast cells (MCs) contain TG-rich cytoplasmic lipid droplets (LDs) with high arachidonic acid (AA) content. Here, we investigated the functional role of adipose TG lipase (ATGL) in TG hydrolysis and the ensuing release of AA as substrate for eicosanoid generation by activated human primary MCs in culture. Silencing of ATGL in MCs by siRNAs induced the accumulation of neutral lipids in LDs. IgE-dependent activation of MCs triggered the secretion of the two major eicosanoids, prostaglandin D2 (PGD2) and leukotriene C4 (LTC4). The immediate release of PGD2 from the activated MCs was solely dependent on cyclooxygenase (COX) 1, while during the delayed phase of lipid mediator production, the inducible COX-2 also contributed to its release. Importantly, when ATGL-silenced MCs were activated, the secretion of both PGD2 and LTC4 was significantly reduced. Interestingly, the inhibitory effect on the release of LTC4 was even more pronounced in ATGL-silenced MCs than in cytosolic phospholipase A₂-silenced MCs. These data show that ATGL hydrolyzes AA-containing TGs present in human MC LDs and define ATGL as a novel regulator of the substrate availability of AA for eicosanoid generation upon MC activation.     

Finite elements/Taguchi method based procedure for the identification of the geometrical parameters significantly affecting the biomechanical behavior of a lumbar disc

The aim of this work is to show a quick and simple procedure able to identify the geometrical parameters of the intervertebral disc that strongly affect the behavior of the FEM model. First, we allocated a selection criterion for the minimum number of geometrical parameters that describe, with a good degree of approximation, a healthy human vertebra. Next, we carried out a sensitivity analysis using the ‘Taguchi orthogonal array’ to arrive at a quick identification of the parameters that strongly affect the behavior of the Fem model.     

Docking and molecular dynamics studies of peripheral site ligand–oximes as reactivators of sarin-inhibited human acetylcholinesterase

In the present work, we performed docking and molecular dynamics simulations studies on two groups of long-tailored oximes designed as peripheral site binders of acetylcholinesterase (AChE) and potential penetrators on the blood brain barrier. Our studies permitted to determine how the tails anchor in the peripheral site of sarin-inhibited human AChE, and which aminoacids are important to their stabilization. Also the energy values obtained in the docking studies corroborated quite well with the experimental results obtained before for these oximes.     

Reliably Detecting Clinically Important Variants Requires Both Combined Variant Calls and Optimized Filtering Strategies

A diversity of tools is available for identification of variants from genome sequence data. Given the current complexity of incorporating external software into a genome analysis infrastructure, a tendency exists to rely on the results from a single tool alone. The quality of the output variant calls is highly variable however, depending on factors such as sequence library quality as well as the choice of short-read aligner, variant caller, and variant caller filtering strategy. Here we present a two-part study first using the high quality ‘genome in a bottle’ reference set to demonstrate the significant impact the choice of aligner, variant caller, and variant caller filtering strategy has on overall variant call quality and further how certain variant callers outperform others with increased sample contamination, an important consideration when analyzing sequenced cancer samples. This analysis confirms previous work showing that combining variant calls of multiple tools results in the best quality resultant variant set, for either specificity or sensitivity, depending on whether the intersection or union, of all variant calls is used respectively. Second, we analyze a melanoma cell line derived from a control lymphocyte sample to determine whether software choices affect the detection of clinically important melanoma risk-factor variants finding that only one of the three such variants is unanimously detected under all conditions. Finally, we describe a cogent strategy for implementing a clinical variant detection pipeline; a strategy that requires careful software selection, variant caller filtering optimizing, and combined variant calls in order to effectively minimize false negative variants. While implementing such features represents an increase in complexity and computation the results offer indisputable improvements in data quality.