N-Palmitoyl Glycine, a Novel Endogenous Lipid That Acts As a Modulator of Calcium Influx and Nitric Oxide Production in Sensory Neurons

N-arachidonoyl glycine is an endogenous arachidonoyl amide that activates the orphan G protein-coupled receptor (GPCR) GPR18 in a pertussis toxin (PTX)-sensitive manner and produces antinociceptive and antiinflammatory effects. It is produced by direct conjugation of arachidonic acid to glycine and by oxidative metabolism of the endocannabinoid anandamide. Based on the presence of enzymes that conjugate fatty acids with glycine and the high abundance of palmitic acid in the brain, we hypothesized the endogenous formation of the saturated N-acyl amide N-palmitoyl glycine (PalGly). PalGly was partially purified from rat lipid extracts and identified using nano-high-performance liquid chromatography/hybrid quadrupole time-of-flight mass spectrometry. Here, we show that PalGly is produced after cellular stimulation and that it occurs in high levels in rat skin and spinal cord. PalGly was up-regulated in fatty acid amide hydrolase knockout mice, suggesting a pathway for enzymatic regulation. PalGly potently inhibited heat-evoked firing of nociceptive neurons in rat dorsal horn. In addition, PalGly induced transient calcium influx in native adult dorsal root ganglion (DRG) cells and a DRG-like cell line (F-11). The effect of PalGly on the latter cells was characterized by strict structural requirements, PTX sensitivity, and dependence on the presence of extracellular calcium. PalGly-induced calcium influx was blocked by the nonselective calcium channel blockers ruthenium red, 1-(beta-[3-(4-methoxyphenyl)propoxy]-4-methoxyphenethyl)-1H-imidazole (SK&F96365), and La3+. Furthermore, PalGly contributed to the production of NO through calcium-sensitive nitric-oxide synthase enzymes present in F-11 cells and was inhibited by the nitric-oxide synthase inhibitor 7-nitroindazole

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

An Experimentally Validated Genome-Scale Metabolic Reconstruction of Klebsiella pneumoniae MGH 78578, iYL1228▿ †

Klebsiella pneumoniae is a Gram-negative bacterium of the family Enterobacteriaceae that possesses diverse metabolic capabilities: many strains are leading causes of hospital-acquired infections that are often refractory to multiple antibiotics, yet other strains are metabolically engineered and used for production of commercially valuable chemicals. To study its metabolism, we constructed a genome-scale metabolic model (iYL1228) for strain MGH 78578, experimentally determined its biomass composition, experimentally determined its ability to grow on a broad range of carbon, nitrogen, phosphorus and sulfur sources, and assessed the ability of the model to accurately simulate growth versus no growth on these substrates. The model contains 1,228 genes encoding 1,188 enzymes that catalyze 1,970 reactions and accurately simulates growth on 84% of the substrates tested. Furthermore, quantitative comparison of growth rates between the model and experimental data for nine of the substrates also showed good agreement. The genome-scale metabolic reconstruction for K. pneumoniae presented here thus provides an experimentally validated in silico platform for further studies of this important industrial and biomedical organism

Targeted lipidomics: Discovery of new fatty acyl amides

The discovery of endogenous fatty acyl amides such asN-arachidonoyl ethanolamide (anandamide),N-oleoyl ethanolamide (OEA), andN-arachidonoyl dopamine (NADA) as important signaling molecules in the central and peripheral nervous system has led us to pursue other unidentified signaling molecules. Until recently, technical challenges, particularly those associated with lipid purification and chemical analysis, have hindered the identification of low abundance signaling lipids. Improvements in chromatography and mass spectrometry (MS) such as miniaturization of high-performance liquid chromatography components, hybridization of multistage mass spectrometers and time-of-flight technology, the development of electrospray ionization (ESI) and of information-dependent acquisition, now permit rapid identification of novel, low abundance, signaling lipids