Excessive alcohol consumption induces methane production in humans and rats.

Various studies have established the possibility of non-bacterial methane (CH4) generation in oxido-reductive stress conditions in plants and animals. Increased ethanol input is leading to oxido-reductive imbalance in eukaryotes, thus our aim was to provide evidence for the possibility of ethanol-induced methanogenesis in non-CH4 producer humans, and to corroborate the in vivo relevance of this pathway in rodents. Healthy volunteers consumed 1.15 g/kg/day alcohol for 4 days and the amount of exhaled CH4 was recorded by high sensitivity photoacoustic spectroscopy. Additionally, Sprague-Dawley rats were allocated into control, 1.15 g/kg/day and 2.7 g/kg/day ethanol-consuming groups to detect the whole-body CH4 emissions and mitochondrial functions in liver and hippocampus samples with high-resolution respirometry. Mitochondria-targeted L-alpha-glycerylphosphorylcholine (GPC) can increase tolerance to liver injury, thus the effects of GPC supplementations were tested in further ethanol-fed groups. Alcohol consumption was accompanied by significant CH4 emissions in both human and rat series of experiments. 2.7 g/kg/day ethanol feeding reduced the oxidative phosphorylation capacity of rat liver mitochondria, while GPC significantly decreased the alcohol-induced CH4 formation and hepatic mitochondrial dysfunction as well. These data demonstrate a potential for ethanol to influence human methanogenesis, and suggest a biomarker role for exhaled CH4 in association with mitochondrial dysfunction.

Early evolution of endoparasitic group in powdery mildews: molecular phylogeny suggests missing link between Phyllactinia and Leveillula.

Of the 17 genera of the Erysiphaceae, only four genera (viz. Leveillula, Phyllactinia, Pleochaeta and Queirozia) exhibit (partly) endoparasitism. To investigate early evolution of this endoparasitic nature, we performed molecular phylogenetic analyses of powdery mildews belonging to the tribe Phyllactinieae collected in North and South America. The most ancestral taxa in the tribe Phyllactinieae belong to the Pleochaeta/Queirozia group, from which the genus Phyllactinia was derived. Finally, the truly endoparasitic genus Leveillula emerged from a part of Phyllactinia The present study showed clear evolutional polarity in the powdery mildews concerned (that is, partly endoparasitic group evolved from ectoparasitic group) and then a truly endoparasitic group emerged from a partly endoparasitic group. In addition, a group with distinctly dimorphic conidia proved to be basal in the Phyllactinieae, and a group without distinctly dimorphic conidia was derived from that group. The present analyses clearly showed that Leveillula derived from a part of the "Basal Phyllactinia group". However, all sister taxa to Leveillula were distributed in North and South America. Because the putative geographic origin of Leveillula is assumed to be Central and Western Asia or the Mediterranean region, we postulate a missing link during the evolution of Leveillula from Phyllactinia Based on the present phylogenetic studies and the new rules of the International Code of Nomenclature for algae, fungi, and plants (McNeill et al. 2012), the following new species and taxonomic re-allocations are proposed: Phyllactinia bougainvilleae sp. nov., Ph. caricae comb. nov., Ph. caricicola comb. nov., Ph. durantae comb. nov., Ph. leveilluloides sp. nov., Ph. obclavata comb. nov., and Ph. papayae comb. nov.

Studies of responsiveness in the R-EGFR and Rcerb-B2 oncogenes spaces: a customized application for thyroid lesions.

Among variety of diagnostic approaches suitable for clinical analysis of thyroid lesions, the two oncogenes (R-EGFR and Rcerb-B2) are believed to be of discriminative power. In a retrospectively collected patient material we have defined different lesion types (normal tissue, benign and malignant tumours). Those were taken as class definitions in analysis performed to assign discriminating performance. Standard multivariate statistics has not performed satisfactory partly due to the data distribution and partly due to presence of the noise. Therefore we have developed a method for the classification purpose, which was based on principle of minimising generalised classification error. Results of the separation between carcinoma and normal tissue reached accuracy 70%, other classification attempts ended up in poor results. In general, misclassifications could be explained with the data quality (noise) and, when it came to benign lesions, with responsiveness of the oncogenes to tumour tissues.