Metabolism and pharmacokinetic studies of propionylpromazine in horses

The propionylpromazine concentrations in plasma after intramuscular administration to horses were determined using gas chromatography with nitrogen-phosphorus detection. After hydrolysis by beta-glucuronidase/arylsulphatase, the parent drug and three metabolites were detected in urine. The metabolites were identified as 2-(1-hydroxypropyl)promazine, 2-(1-propenyl)promazine and 7-hydroxypropionylpromazine by gas chromatography-mass spectrometry. No N-demethylated or sulphoxidated metabolites of propionylpromazine were observed in the horse urine.     

Kopsifolines A–F: a New Structural Class of Monoterpenoid Indole Alkaloids from Kopsia

Six new indole alkaloids, named kopsifolines A–F ( 1 – 6 ), with an unprecedented hexacyclic carbon skeleton, constituting a new structural group of monoterpenoid indole alkaloids, were obtained from the leaf extract of a Malayan Kopsia species, and their structures were established by spectroscopic analysis.     

Improved Optimum Radius for Robust Stability of Schur Polynomials

An approach based on the Rouché theorem was introduced in the literature to compute the optimum radius for robust stability of Schur polynomials. Later an attempt was made to improve the result, but it was shown to be incorrect. The purpose of this note is to show that an improved optimum radius still can be obtained by modifying the proposed method. The result of this note can be easily extended to the multidimensional cases.     

Locally adaptive bilateral clustering for universal image denoising

This paper presents a novel and efficient locally adaptive denoising method based on clustering of pixels into regions of similar geometric and radiometric structures. Clustering is performed by adaptively segmenting pixels in the local kernel based on their augmented variational series. Then, noise pixels are restored by selectively considering the radiometric and spatial properties of every pixel in the formed clusters. The proposed method is exceedingly robust in conveying reliable local structural information even in the presence of noise. As a result, the proposed method substantially outperforms other state-of-the-art methods in terms of image restoration and computational cost. We support our claims with ample simulated and real data experiments. The relatively fast runtime from extensive simulations also suggests that the proposed method is suitable for a variety of image-based products ?? either embedded in image capturing devices or applied as image enhancement software.     

Development and validation of a multiplex real-time PCR method to simultaneously detect 47 targets for the identification of genetically modified organisms

Considering the increase of the total cultivated land area dedicated to genetically modified organisms (GMO), the consumers’ perception toward GMO and the need to comply with various local GMO legislations, efficient and accurate analytical methods are needed for their detection and identification. Considered as the gold standard for GMO analysis, the real-time polymerase chain reaction (RTi-PCR) technology was optimised to produce a high-throughput GMO screening method. Based on simultaneous 24 multiplex RTi-PCR running on a ready-to-use 384-well plate, this new procedure allows the detection and identification of 47 targets on seven samples in duplicate. To comply with GMO analytical quality requirements, a negative and a positive control were analysed in parallel. In addition, an internal positive control was also included in each reaction well for the detection of potential PCR inhibition. Tested on non-GM materials, on different GM events and on proficiency test samples, the method offered high specificity and sensitivity with an absolute limit of detection between 1 and 16 copies depending on the target. Easy to use, fast and cost efficient, this multiplex approach fits the purpose of GMO testing laboratories.

Transition Metal (Mn,Fe, Co,Ni)‐Doped Graphene Hybrids for Electrocatalysis

The development of electrocatalysts is crucial for renewable energy applications. Metal‐doped graphene hybrid materials have been explored for this purpose, however, with much focus on noble metals, which are limited by their low availability and high costs. Transition metals may serve as promising alternatives. Here, transition metal‐doped graphene hybrids were synthesized by a simple and scalable method. Metal‐doped graphite oxide precursors were thermally exfoliated in either hydrogen or nitrogen atmosphere; by changing exfoliation atmospheres from inert to reductive, we produced materials with different degrees of oxidation. Effects of the presence of metal nanoparticles and exfoliation atmosphere on the morphology and electrocatalytic activity of the hybrid materials were investigated using electron microscopy, energy‐dispersive X‐ray spectroscopy, X‐ray photoelectron spectroscopy, and cyclic voltammetry. Doping of graphene with transition metal nanoparticles of the 4th period significantly influenced the electrocatalysis of compounds important in energy production and storage applications, with hybrid materials exfoliated in nitrogen atmosphere displaying superior performance over those exfoliated in hydrogen atmosphere. Moreover, nickel‐doped graphene hybrids displayed outstanding electrocatalytic activities towards reduction of O₂ when compared to bare graphenes. These findings may be exploited in the research field of renewable energy.