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Glucuronidation is a common phase II metabolic process for drugs and xenobiotics which increases their solubility for excretion. Acyl glucuronides (glucuronides of carboxylic acids) present concerns of toxicity as they have been implicated in gastrointestinal toxicity and hepatic failure. Despite the substantial success in the bulk analysis of these species, little is known about their localization in tissues. Herein, we used nanospray desorption electrospray ionization mass spectrometry imaging (nano-DESI-MSI) to examine the localization of diclofenac, a widely used nonsteroidal anti-inflammatory drug, and its metabolites in mouse kidney and liver tissues. Nano-DESI allows for label-free imaging with high spatial resolution and sensitivity without special sample pretreatment. Using nano-DESI-MSI, ion images for diclofenac and its major metabolites were produced. MSI data acquired over a broad m/z range showed fairly low signals of the drug and its metabolites. At least an order of magnitude improvement in the signals was obtained using selected ion monitoring (SIM), with m/z windows centered around the low-abundance ions of interest. Using nano-DESI MSI in SIM mode, we observed that diclofenac acyl glucuronide is localized to the inner medulla and hydroxydiclofenac to the cortex of the kidney. The distributions observed for both metabolites closely match the previously reported localization of enzymes that process diclofenac into its respective metabolites. The localization of diclofenac acyl glucuronide to medulla likely indicates that the toxic metabolite is being excreted from the tissue. In contrast, a uniform distribution of diclofenac, hydroxydiclofenac and the diclofenac acyl glucuronide metabolite was observed in the liver tissue. Semiquantitative analysis found the metabolite to diclofenac ratios calculated from nano-DESI in agreement to those calculated from liquid chromatography tandem mass spectrometry (LC-MS/MS) experiments. Collectively, our results demonstrate nano-DESI-MSI can be successfully used to image diclofenac and its primary metabolites in dosed liver and kidney tissues from mice and derive semi-quantitative data from localized tissue regions. 

Context.The nearby elliptical galaxy M87 contains one of only two supermassive black holes whose emission surrounding the event horizon has been imaged by the Event Horizon Telescope (EHT). In 2018, more than two dozen multi-wavelength (MWL) facilities (from radio toγ-ray energies) took part in the second M87 EHT campaign. Aims.The goal of this extensive MWL campaign was to better understand the physics of the accreting black hole M87*, the relationship between the inflow and inner jets, and the high-energy particle acceleration. Understanding the complex astrophysics is also a necessary first step towards performing further tests of general relativity. Methods.The MWL campaign took place in April 2018, overlapping with the EHT M87* observations. We present a new, contemporaneous spectral energy distribution (SED) ranging from radio to very high-energy (VHE)γ-rays as well as details of the individual observations and light curves. We also conducted phenomenological modelling to investigate the basic source properties. Results.We present the first VHEγ-ray flare from M87 detected since 2010. The flux above 350 GeV more than doubled within a period of ≈36 hours. We find that the X-ray flux is enhanced by about a factor of two compared to 2017, while the radio and millimetre core fluxes are consistent between 2017 and 2018. We detect evidence for a monotonically increasing jet position angle that corresponds to variations in the bright spot of the EHT image. Conclusions.Our results show the value of continued MWL monitoring together with precision imaging for addressing the origins of high-energy particle acceleration. While we cannot currently pinpoint the precise location where such acceleration takes place, the new VHEγ-ray flare already presents a challenge to simple one-zone leptonic emission model approaches, and it emphasises the need for combined image and spectral modelling.