Second messenger/signal transduction pathways in major mood disorders: Moving from membrane to mechanism of action, part II: bipolar disorder

The etiopathogenesis and treatment of major mood disorders have historically focused on modulation of monoaminergic (serotonin, norepinephrine, dopamine) and amino acid [γ-aminobutyric acid (GABA), glutamate] receptors at the plasma membrane. Although the activation and inhibition of these receptors acutely alter local neurotransmitter levels, their neuropsychiatric effects are not immediately observed. This time lag implicates intracellular neuroplasticity as primary in the mechanism of action of antidepressants and mood stabilizers. The modulation of intracellular second messenger/signal transduction cascades affects neurotrophic pathways that are both necessary and sufficient for monoaminergic and amino acid–based treatments. In this review, we will discuss the evidence in support of intracellular mediators in the pathophysiology and treatment of preclinical models of despair and major depressive disorder (MDD). More specifically, we will focus on the following pathways: cAMP/PKA/CREB, neurotrophin-mediated (MAPK and others), p11, Wnt/Fz/Dvl/GSK3β, and NFκB/ΔFosB. We will also discuss recent discoveries with rapidly acting antidepressants, which activate the mammalian target of rapamycin (mTOR) and release of inhibition on local translation via elongation factor stimulation. Throughout this discourse, we will highlight potential intracellular targets for therapeutic intervention. Finally, future clinical implications are discussed

Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human speech analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis which can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling, but also from decisions regarding the quantification of the measured behavior. In the present study, we gave the same speech production data set to 46 teams of researchers and asked them to answer the same research question, resulting insubstantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further find little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system and calibrate their (un)certainty in their conclusions

Total Lipids and Fatty Acids in Major New Zealand Grape Varieties during Ripening, Prolonged Pomace Contacts and Ethanolic Extractions Mimicking Fermentation

Despite the important roles of lipids in winemaking, changes in lipids during grape ripening are largely unknown for New Zealand (NZ) varieties. Therefore, we aimed to determine the fatty acid profiles and total lipid content in two of NZ’s major grape varieties. Using gas chromatography–mass spectrometry, absolute quantification of 45 fatty acids was determined in Sauvignon blanc (SB) and Pinot noir (PN) grapes harvested at two different stages of ripeness. Lipid concentrations were as high as 0.4 g/g in seeds of both varieties, while pulp contained the least amount. Many unsaturated fatty acids were present, particularly in grape seeds, while skin contained relatively higher amounts of saturated fatty acids that increased throughout ripening. For both varieties, a significant increase in lipid concentration was observed in grapes harvested at the later stage of ripeness, indicating an association between lipids and grape maturity, and providing a novel insight about the use of total lipids as another parameter of grape ripeness. A variety-specific trend in the development and extraction of grape lipids was found from the analysis of the must and ethanolic extracts. Lipid extraction increased linearly with the ethanol concentration and with the extended pomace contact time. More lipids were extracted from the SB pomace to the must than PN within 144 h, suggesting a must matrix effect on lipid extraction. The knowledge generated here is relevant to both industry and academia and can be used to develop lipid diversification strategies to produce different wine styles

Fully Automated Trimethylsilyl (TMS) Derivatisation Protocol for Metabolite Profiling by GC-MS

Gas Chromatography-Mass Spectrometry (GC-MS) has long been used for metabolite profiling of a wide range of biological samples. Many derivatisation protocols are already available and among these, trimethylsilyl (TMS) derivatisation is one of the most widely used in metabolomics. However, most TMS methods rely on off-line derivatisation prior to GC-MS analysis. In the case of manual off-line TMS derivatisation, the derivative created is unstable, so reduction in recoveries occurs over time. Thus, derivatisation is carried out in small batches. Here, we present a fully automated TMS derivatisation protocol using robotic autosamplers and we also evaluate a commercial software, Maestro available from Gerstel GmbH. Because of automation, there was no waiting time of derivatised samples on the autosamplers, thus reducing degradation of unstable metabolites. Moreover, this method allowed us to overlap samples and improved throughputs. We compared data obtained from both manual and automated TMS methods performed on three different matrices, including standard mix, wine, and plasma samples. The automated TMS method showed better reproducibility and higher peak intensity for most of the identified metabolites than the manual derivatisation method. We also validated the automated method using 114 quality control plasma samples. Additionally, we showed that this online method was highly reproducible for most of the metabolites detected and identified (RSD < 20) and specifically achieved excellent results for sugars, sugar alcohols, and some organic acids. To the very best of our knowledge, this is the first time that the automated TMS method has been applied to analyse a large number of complex plasma samples. Furthermore, we found that this method was highly applicable for routine metabolite profiling (both targeted and untargeted) in any metabolomics laboratory