Luteal 20alpha-hydroxy steroid dehydrogenase and the formation of delta4-3-oxo steroids in the rat after weaning or treatment with 2-bromo-alpha-ergocryptine during lactation.

Natural or early weaning of rat litters caused an increased activity of maternal luteal 20alpha-hydroxy steroid dehydrogenase and a decreased release of delta4-3-oxo steroids in vitro. 2. Compound CB-154 (2-bromo-alpha-ergocryptine) caused an increase of 20alpha-hydroxy steroid dehydrogenase activity in mid-lactation but not in early lactation. 3. Prolaction did not prevent these increases in enzyme activity.     

Mutual interplay between phytopathogenic powdery mildew fungi and other microorganisms

Powdery mildew is a common and widespread plant disease of considerable agronomic relevance. It is caused by obligate biotrophic fungal pathogens which, in most cases, epiphytically colonize aboveground plant tissues. The disease has been typically studied as a binary interaction of the fungal pathogen with its plant hosts, neglecting, for the most part, the mutual interplay with the wealth of other microorganisms residing in the phyllo- and/or rhizosphere and roots. However, the establishment of powdery mildew disease can be impacted by the presence/absence of host-associated microbiota (epi- and endophytes) and, conversely, plant colonization by powdery mildew fungi might disturb indigenous microbial community structures. In addition, other (foliar) phytopathogens could interact with powdery mildews, and mycoparasites may affect the outcome of plant–powdery mildew interactions. In this review, we discuss the current knowledge regarding the intricate and multifaceted interplay of powdery mildew fungi, host plants and other microorganisms, and outline current gaps in our knowledge, thereby setting the basis for potential future research directions.     

A combined CaMKII inhibition and mineralocorticoid receptor antagonism via eplerenone inhibits functional deterioration in chronic pressure overloaded mice

In the diseased and remodelled heart, increased activity and expression of Ca^2+/calmodulin‐dependent protein kinase II (CaMKII), an excess of fibrosis, and a decreased electrical coupling and cellular excitability leads to disturbed calcium homeostasis and tissue integrity. This subsequently leads to increased arrhythmia vulnerability and contractile dysfunction. Here, we investigated the combination of CaMKII inhibition (using genetically modified mice expressing the autocamtide‐3‐related‐peptide (AC3I)) together with eplerenone treatment (AC3I‐Epler) to prevent electrophysiological remodelling, fibrosis and subsequent functional deterioration in a mouse model of chronic pressure overload. We compared AC3I‐Epler mice with mice only subjected to mineralocorticoid receptor (MR) antagonism (WT‐Epler) and mice with only CaMKII inhibition (AC3I‐No). Our data show that a combined CaMKII inhibition together with MR antagonism mitigates contractile deterioration as was manifested by a preservation of ejection fraction, fractional shortening, global longitudinal strain, peak strain and contractile synchronicity. Furthermore, patchy fibrosis formation was reduced, potentially via inhibition of pro‐fibrotic TGF‐β/SMAD3 signalling, which related to a better global contractile performance and a slightly depressed incidence of arrhythmias. Furthermore, the level of patchy fibrosis appeared significantly correlated to eplerenone dose. The addition of eplerenone to CaMKII inhibition potentiates the effects of CaMKII inhibition on pro‐fibrotic pathways. As a result of the applied strategy, limiting patchy fibrosis adheres to a higher synchronicity of contraction and an overall better contractile performance which fits with a tempered arrhythmogenesis.     

Correction to: Sex and race differences of cerebrospinal fluid metabolites in healthy individuals

Metabolomics - Metabolomics applications to the aquaculture research are increasing steadily. The use of standardized proton nuclear magnetic resonance (1H NMR) spectroscopy can provide the...     

Proteomic Differences Between Hepatocellular Carcinoma and Nontumorous Liver Tissue Investigated by a Combined Gel-based and Label-free Quantitative Proteomics Study

Proteomics-based clinical studies have been shown to be promising strategies for the discovery of novel biomarkers of a particular disease. Here, we present a study of hepatocellular carcinoma (HCC) that combines complementary two-dimensional difference in gel electrophoresis (2D-DIGE) and liquid chromatography (LC-MS)-based approaches of quantitative proteomics. In our proteomic experiments, we analyzed a set of 14 samples (7 × HCC versus 7 × nontumorous liver tissue) with both techniques. Thereby we identified 573 proteins that were differentially expressed between the experimental groups. Among these, only 51 differentially expressed proteins were identified irrespective of the applied approach. Using Western blotting and immunohistochemical analysis the regulation patterns of six selected proteins from the study overlap (inorganic pyrophosphatase 1 (PPA1), tumor necrosis factor type 1 receptor-associated protein 1 (TRAP1), betaine-homocysteine S-methyltransferase 1 (BHMT)) were successfully verified within the same sample set. In addition, the up-regulations of selected proteins from the complements of both approaches (major vault protein (MVP), gelsolin (GSN), chloride intracellular channel protein 1 (CLIC1)) were also reproducible. Within a second independent verification set (n = 33) the altered protein expression levels of major vault protein and betaine-homocysteine S-methyltransferase were further confirmed by Western blots quantitatively analyzed via densitometry. For the other candidates slight but nonsignificant trends were detectable in this independent cohort. Based on these results we assume that major vault protein and betaine-homocysteine S-methyltransferase have the potential to act as diagnostic HCC biomarker candidates that are worth to be followed in further validation studies.Hepatocellular carcinoma (HCC)¹ currently is the fifth most common malignancy worldwide with an annual incidence up to 500 per 100,000 individuals depending on the geographic region investigated. Whereas 80% of new cases occur in developing countries, the incidence increases in industrialized nations including Western Europe, Japan, and the United States (1). To manage patients with HCC, tumor markers are very important tools for diagnosis, indicators of disease progression, outcome prediction, and evaluation of treatment efficacy. Several tumor markers have been reported for HCC, including α-fetoprotein (AFP) (2), Lens culinaris agglutinin-reactive fraction of AFP (AFP-L3) (3), and des-γ-carboxyl prothrombin (DCP) (4). However, none of these tumor markers show 100% sensitivity or specificity, which calls for new and better biomarkers.To identify novel biomarkers of HCC, many clinical studies using “omics”-based methods have been reported over the past decade (5–6). In particular, the proteomics-based approach has turned out to be a promising one, offering several quantification techniques to reveal differences in protein expression that are caused by a particular disease. In most studies, the well-established 2D-DIGE technique has been applied for protein quantification followed by identification via mass spectrometry (7–15). Even if the quantification is very accurate and sensitive in this gel-based approach, the relatively high amount of protein sample necessary for protein identification is the major disadvantage of this technique. Several mass-spectrometry-based quantitative studies using labeling-techniques like SILAC (stable isotope labeling by amino acids in cell culture) or iTRAQ (isobaric tags for relative and absolute quantification) have also been carried out for biomarker discovery of HCC (16–18). Here, the concomitant protein quantification and identification in a mass spectrometer allows high-throughput analyses. However, such experiments imply additional labeling reactions (in case of iTRAQ) or are limited to tissue culture systems (in case of SILAC). In the latter case, one can overcome the limitation by using the isotope-labeled proteins obtained from tissue culture as an internal standard added to a corresponding tissue sample. This approach is known as CDIT (culture-derived isotope tags) and was applied in a HCC study, very recently (19). Label-free proteomics approaches based on quantification by ion-intensities or spectral counting offer another possibility for biomarker discovery. These approaches are relatively cheap compared with the labeling approaches, because they do not require any labeling reagents and furthermore they allow for high-throughput and sensitive analyses in a mass spectrometer. A quantitative study of HCC using spectral counting has been reported (20), whereas to our knowledge an ion-intensity-based study has not been performed yet. Apart from these quantification strategies, protein alterations in HCC have been studied by MALDI imaging, as well. Here, the authors could show that based on its proteomic signature, hepatocellular carcinoma can be discriminated with high accuracy from liver metastasis samples or other cancer types (21) as well as liver cirrhosis (22). Based on these results, it could be assumed that MALDI imaging might be a promising alternative to standard histological methods in the future.Here, we report a quantitative proteomic study that combines two different techniques, namely the well-established 2D-DIGE approach and a label-free ion-intensity-based quantification via mass spectrometry and liquid chromatography. To our knowledge this is the first time such a combined study was performed with regard to hepatocellular carcinoma. By comparing the results of both studies, we aim to identify high-confident biomarker candidates of HCC, as gel- and LC-MS-based techniques are complementary. To verify the differential protein expressions detected in our proteomic studies we performed additional immunological verifications for selected proteins within two different sample sets (Fig. 1).Open in a separate windowFig. 1.Schematic representation of the applied workflow.