Untargeted NMR Spectroscopic Analysis of the Metabolic Variety of New Apple Cultivars

Metabolome analyses by NMR spectroscopy can be used in quality control by generating unique fingerprints of different species. Hundreds of components and their variation between different samples can be analyzed in a few minutes/hours with high accuracy and low cost of sample preparation. Here, apple peel and pulp extracts of a variety of apple cultivars were studied to assess their suitability to discriminate between the different varieties. The cultivars comprised mainly newly bred varieties or ones that were brought onto the market in recent years. Multivariate analyses of peel and pulp extracts were able to unambiguously identify all cultivars, with peel extracts showing a higher discriminative power. The latter was increased if the highly concentrated sugar metabolites were omitted from the analysis. Whereas sugar concentrations lay within a narrow range, polyphenols, discussed as potential health promoting substances, and acids varied remarkably between the cultivars

Loss of chloroplast protease SPPA function alters high light acclimation processes in Arabidopsis thaliana L. (Heynh.)

SPPA1 is a protease in the plastids of plants, located in non-appressed thylakoid regions. In this study, T-DNA insertion mutants of the single-copy SPPA1 gene in Arabidopsis thaliana (At1g73990) were examined. Mutation of SPPA1 had no effect on the growth and development of plants under moderate, non-stressful conditions. It also did not affect the quantum efficiency of photosynthesis as measured by dark-adapted Fv/Fm and light-adapted ΦPSII. Chloroplasts from sppA mutants were indistinguishable from the wild type. Loss of SPPA appears to affect photoprotective mechanisms during high light acclimation: mutant plants maintained a higher level of non-photochemical quenching of Photosystem II chlorophyll (NPQ) than the wild type, while wild-type plants accumulated more anthocyanin than the mutants. The quantum efficiency of Photosystem II was the same in all genotypes grown under low light, but was higher in wild type than mutants during high light acclimation. Further, the mutants retained the stress-related Early Light Inducible Protein (ELIP) longer than wild-type leaves during the early recovery period after acute high light plus cold treatment. These results suggest that SPPA1 may function during high light acclimation in the plastid, but is non-essential for growth and development under non-stress conditions

Analysis of LhcSR3, a Protein Essential for Feedback De-Excitation in the Green Alga Chlamydomonas reinhardtii

To prevent photodamage by excess light, plants use different proteins to sense pH changes and to dissipate excited energy states. In green microalgae, however, the LhcSR3 gene product is able to perform both pH sensing and energy quenching functions

Cardiopoietic cell therapy for advanced ischemic heart failure: results at 39 weeks of the prospective, randomized, double blind, sham-controlled CHART-1 clinical trial

Cardiopoietic cells, produced through cardiogenic conditioning of patients' mesenchymal stem cells, have shown preliminary efficacy. The Congestive Heart Failure Cardiopoietic Regenerative Therapy (CHART-1) trial aimed to validate cardiopoiesis-based biotherapy in a larger heart failure cohort

Publisher: Institute for Animal Husbandry, Belgrade-Zemun UDC 639.112 RABBIT PRODUCTION IN BULGARIA**

Bulgarian board of bird and rabbit meat processin

tRNA-like Transcripts from the <i>NEAT1-MALAT1</i> Genomic Region Critically Influence Human Innate Immunity and Macrophage Functions

The evolutionary conserved NEAT1-MALAT1 gene cluster generates large noncoding transcripts remaining nuclear, while tRNA-like transcripts (mascRNA, menRNA) enzymatically generated from these precursors translocate to the cytosol. Whereas functions have been assigned to the nuclear transcripts, data on biological functions of the small cytosolic transcripts are sparse. We previously found NEAT1−/− and MALAT1−/− mice to display massive atherosclerosis and vascular inflammation. Here, employing selective targeted disruption of menRNA or mascRNA, we investigate the tRNA-like molecules as critical components of innate immunity. CRISPR-generated human ΔmascRNA and ΔmenRNA monocytes/macrophages display defective innate immune sensing, loss of cytokine control, imbalance of growth/angiogenic factor expression impacting upon angiogenesis, and altered cell–cell interaction systems. Antiviral response, foam cell formation/oxLDL uptake, and M1/M2 polarization are defective in ΔmascRNA/ΔmenRNA macrophages, defining first biological functions of menRNA and describing new functions of mascRNA. menRNA and mascRNA represent novel components of innate immunity arising from the noncoding genome. They appear as prototypes of a new class of noncoding RNAs distinct from others (miRNAs, siRNAs) by biosynthetic pathway and intracellular kinetics. Their NEAT1-MALAT1 region of origin appears as archetype of a functionally highly integrated RNA processing system

Metabolite patterns predicting sex and age in participants of the Karlsruhe Metabolomics and Nutrition (KarMeN) study

<div><p>Physiological and functional parameters, such as body composition, or physical fitness are known to differ between men and women and to change with age. The goal of this study was to investigate how sex and age-related physiological conditions are reflected in the metabolome of healthy humans and whether sex and age can be predicted based on the plasma and urine metabolite profiles.</p><p>In the cross-sectional KarMeN (<u>Kar</u>lsruhe <u>Me</u>tabolomics and <u>N</u>utrition) study 301 healthy men and women aged 18–80 years were recruited. Participants were characterized in detail applying standard operating procedures for all measurements including anthropometric, clinical, and functional parameters. Fasting blood and 24 h urine samples were analyzed by targeted and untargeted metabolomics approaches, namely by mass spectrometry coupled to one- or comprehensive two-dimensional gas chromatography or liquid chromatography, and by nuclear magnetic resonance spectroscopy. This yielded in total more than 400 analytes in plasma and over 500 analytes in urine. Predictive modelling was applied on the metabolomics data set using different machine learning algorithms.</p><p>Based on metabolite profiles from urine and plasma, it was possible to identify metabolite patterns which classify participants according to sex with > 90% accuracy. Plasma metabolites important for the correct classification included creatinine, branched-chain amino acids, and sarcosine. Prediction of age was also possible based on metabolite profiles for men and women, separately. Several metabolites important for this prediction could be identified including choline in plasma and sedoheptulose in urine. For women, classification according to their menopausal status was possible from metabolome data with > 80% accuracy.</p><p>The metabolite profile of human urine and plasma allows the prediction of sex and age with high accuracy, which means that sex and age are associated with a discriminatory metabolite signature in healthy humans and therefore should always be considered in metabolomics studies.</p></div