Metabonomic Investigation of Liver Profiles of Nonpolar Metabolites Obtained from Alcohol-Dosed Rats and Mice Using High Mass Accuracy MSn Analysis

Alcoholism is a complex disorder that, in man, appears to be genetically influenced, although the underlying genes and molecular pathways are not completely known. Here the intragastric alcohol feeding model in rodents was used together with high mass accuracy LC/MS(n) analysis to assess the metabonomic changes in nonpolar metabolite profiles for livers from control and alcohol treated rats and mice. Ion signals with a peak area variance of less than 30% (based on repeat analysis of a pooled quality control sample analysed throughout the batch) were submitted to multivariate statistical analysis (using principal components analysis, PCA). PCA revealed robust differences between profiles from control and alcohol-treated animals from both species. The major metabolites seen to differ between control and alcohol-treated animals were identified using high accuracy MS(n) data and verified using external search engines (http://www.lipidmaps.org; http://www.hmdb.ca; http://www.genome.jp/kegg/) and authentic standards. The main metabolite classes to show major changes in the alcoholic liver-derived samples were fatty acyls, fatty acid ethyl esters, glycerolipids and phosphatidylethanol homologues. Significant metabolites that were up-regulated by alcohol treatment in both rat and mouse livers included fatty acyls, metabolites such as octadecatrienoic acid and eicosapentaenoic acid, a number of fatty acid ethyl esters such as ethyl arachidonate, ethyl docosahexaenoic acid, ethyl linoleate and ethyl oleate and phosphatidylethanol (PEth) homologues (predominantly PEth 18:0/18:2 and PEth 16:0/18:2; PEth homologues are currently considered as potential biomarkers for harmful and prolonged alcohol consumption in man). A number of glycerophospholipids resulted in both up-regulation (m/z 903.7436 [M+H](+) corresponding to a triglyceride) and down-regulation (m/z 667.5296 [M+H](+) corresponding to a diglyceride). Metabolite profiles were broadly similar in both mouse and rat models. However, there were a number of significant differences in the alcohol-treated group particularly in the marked down-regulation of retinol and free cholesterol in the mouse compared to the rat. Unique markers for alcohol treatment included ethyl docosahexaenoic acid. Metabolites were identified with high confidence using predominantly negative ion MS(n) data for the fatty acyl components to match to www.lipidmaps.org MS and MS/MS databases; interpreting positive ion data needed to take into account possible adduct ions which may confound the identification of other lipid classes. The observed changes in lipid profiles were consistent with alcohol induced liver injury in humans

Quantitation of endogenous metabolites in mouse tumors using mass-spectrometry imaging

Described is a quantitative-mass-spectrometryimaging (qMSI) methodology for the analysis of lactate and glutamate distributions in order to delineate heterogeneity among mouse tumor models used to support drug-discovery efficacy testing. We evaluate and report on preanalysisstabilization methods aimed at improving the reproducibility and efficiency of quantitative assessments of endogenous molecules in tissues. Stability experiments demonstrate that optimum stabilization protocols consist of frozen-tissue embedding, post-tissue-sectioning desiccation, and storage at −80 °C of tissue sections sealed in vacuum-tight containers. Optimized stabilization protocols are used in combination with qMSI methodology for the absolute quantitation of lactate and glutamate in tumors, incorporating the use of two different stable-isotope-labeled versions of each analyte and spectral-clustering performed on each tissue section using k-means clustering to allow region-specific, pixel-by-pixel quantitation. Region-specific qMSI was used to screen different tumor models and identify a phenotype that has low lactate heterogeneity, which will enable accurate measurements of lactate modulation in future drug-discovery studies. We conclude that using optimized qMSI protocols, it is possible to quantify endogenous metabolites within tumors, and region-specific quantitation can provide valuable insight into tissue heterogeneity and the tumor microenvironment

Stochastic modeling and identification of an hyperelastic constitutive model for laminated composites

International audienceIn this paper, we investigate the construction and identification of a new random field model for representing the constitutive behavior of laminated composites. Here, the material is modeled as a random hyperelastic medium characterized by a spatially dependent, stochastic and anisotropic strain energy function. The latter is parametrized by a set of material parameters, modeled as non-Gaussian random fields. From a probabilistic standpoint, the construction is first achieved by invoking information theory and the principle of maximum entropy. Constraints related to existence theorems in finite elasticity are, in particular, accounted for in the formulation. The identification of the parameters defining the random fields is subsequently addressed. This issue is attacked as a two-step problem where the mean model is calibrated in a first step, by imposing a match between the linearized model and nominal values proposed in the literature. The remaining parameters controlling the fluctuations are next estimated by solving an inverse problem in which principal component analysis and the maximum likelihood method are combined. The whole framework is illustrated considering an experimental database where multi-axial measurements are performed on a carbon-epoxy laminate. This work constitutes a first step towards the development of an integrated framework that will support decision making under uncertainty for the design, certification and qualification of composite materials and structures

The exploitation of biomass for building space heating in Greece: Energy, environmental and economic considerations

The exploitation of forest and agricultural biomass residues for energy production may offer significant advantages to the energy policy of the relevant country, but it strongly depends on a number of financial, technological and political factors. The work in hand focuses on the investigation of the energy, environmental and financial benefits, resulting from the exploitation of forest and agricultural biomass residues, fully substituting the conventional fuel (diesel oil) for building space heating in Greece. For this investigation, the energy needs of a representative building are determined using the EnergyPlus software, assuming that the building is located across the various climate zones of Greece. Based on the resulting thermal energy needs, the primary energy consumption and the corresponding emissions are determined, while an elementary fiscal analysis is also performed. The results show that significant financial benefits for the end-user are associated with the substitution examined, even though increased emissions and primary energy consumption have been derived

Thoughts on two approaches for accounting for the scatter in fatigue delamination growth curves

This paper discusses two approaches that have been proposed to account for the data scatter observed in delamination growth tests under cyclic-fatigue loading and thereby enable an estimate of a worst-case delamination growth curve for use in the damage tolerance and durability assessment of composite and adhesively-bonded airframes. The two approaches discussed are: (a) the normalisation approach, whereby the energy release rate is divided by the resistance to delamination growth, GR(a), and (b) the Hartman-Schijve approach to delamination growth. It is shown that for the cases considered this normalisation approach can be used to yield curves that are similar to the ‘mean-3σ’, “worst-case”, i.e. upper-bound, curve obtained using the Hartman-Schijve equation. However, despite the reduction in the scatter that arises if this particular normalisation approach is adopted, there is still considerable scatter in the important “near-threshold” region. In this region the normalised curves are bounded above by the ‘mean-3σ’ curve obtained using the Hartman-Schijve equation. To address this issue, an alternative normalisation approach is then proposed. This alternative normalisation approach has the advantage of having reduced scatter in the near-threshold region but elsewhere is significantly more conservative than the Hartman-Schijve approach

Probing synergies between lignin-rich and cellulose compounds for gasification

The fixed bed gasification of lignin rich and deficient mixtures was carried out to probe the synergistic effects between two model compounds, Lignin Pink (LP) rich in Na and Cellulose Microcrystalline (CM). Reaction conditions utilized the most commonly used air ratios in current wood gasifiers at 750 °C and 850 °C. It was found that by increasing the lignin content in the mixture, there was a selectivity change from solid to gas products, contrary to a similar study previously carried out for pyrolysis. This change in product mix was promoted by the catalytic effect of Na edge recession deposits on the surface of the char. As a result, the water gas shift reaction was enhanced at 850 °C for the LP48CM52 mixture across all air ratios, this was evidenced by a strong correlation between the produced H2 and COx. Meanwhile, by lowering the lignin content in the mixtures, the reactivity of cellulose microcrystalline was found to generate more char at higher temperature, similar to lignin mixtures when undergoing pyrolysis

Amygdala DCX and blood Cdk14 are implicated as cross-species indicators of individual differences in fear, extinction, and resilience to trauma exposure

Doublecortin (DCX) has long been implicated in, and employed as a marker for, neurogenesis, yet little is known about its function in non-neurogenic brain regions, including the amygdala. This study sought first to explore, in rodents, whether fear learning and extinction modulate amygdala DCX expression and, second, to assess the utility of peripheral DCX correlates as predictive biomarkers of trauma response in rodents and humans. Pavlovian conditioning was found to alter DCX protein levels in mice 24 h later, resulting in higher DCX expression associated with enhanced learning in paradigms examining both the acquisition and extinction of fear (p < 0.001). This, in turn, is associated with differences in freezing on subsequent fear expression tests, and the same relationship between DCX and fear extinction was replicated in rats (p < 0.001), with higher amygdala DCX levels associated with more rapid extinction of fear. RNAseq of amygdala and blood from mice identified 388 amygdala genes that correlated with DCX (q < 0.001) and which gene ontology analyses revealed were significantly over-represented for neurodevelopmental processes. In blood, DCX-correlated genes included the Wnt signaling molecule Cdk14 which was found to predict freezing during both fear acquisition (p < 0.05) and brief extinction protocols (p < 0.001). High Cdk14 measured in blood immediately after testing was also associated with less freezing during fear expression testing (p < 0.01). Finally, in humans, Cdk14 expression in blood taken shortly after trauma was found to predict resilience in males for up to a year post-trauma (p < 0.0001). These data implicate amygdala DCX in fear learning and suggest that Cdk14 may serve as a predictive biomarker of trauma response

U-Shaped Relation between Plasma Oxytocin Levels and Behavior in the Trust Game

10.1371/journal.pone.0051095PLoS ONE712

Different control conditions can produce different effect estimates in psychotherapy trials for depression

OBJECTIVES: Control conditions' influence on effect estimates of active psychotherapeutic interventions for depression has not been fully elucidated. We used network meta-analysis to estimate the differences between control conditions. STUDY DESIGN AND SETTING: We have conducted a comprehensive literature search of randomized trials of psychotherapies for adults with depression up to January 1, 2019 in four major databases (PubMed, PsycINFO, Embase, and Cochrane). The network meta-analysis included broadly conceived cognitive behavior therapies in comparison with the following control conditions: Waiting List (WL), No Treatment (NT), Pill Placebo (PillPlacebo), Psychological Placebo (PsycholPlacebo). RESULTS: 123 studies with 12,596 participants were included. The I-squared was 55.9% (95% CI: 45.9%; to 64.0%) (moderate heterogeneity). The design-by-treatment global test of inconsistency was not significant (P = 0.44). Different control conditions led to different estimates of efficacy for the same intervention. WL appears to be the weakest control (odds ratio of response against NT = 1.93 (1.30 to 2.86), PsycholPlacebo = 2.03 (1.21 to 3.39), and PillPlacebo = 2.66 (1.45 to 4.89), respectively). CONCLUSIONS: Different control conditions produce different effect estimates in psychotherapy randomized controlled trials for depression. WL was the weakest, followed by NT, PsycholPlacebo, and PillPlacebo in this order. When conducting meta-analyses of psychotherapy trials, different control conditions should not be lumped into a single group

Methylomic profiles reveal sex-specific differences in leukocyte composition associated with post-traumatic stress disorder

Post-traumatic stress disorder (PTSD) is a debilitating mental disorder precipitated by trauma exposure. However, only some persons exposed to trauma develop PTSD. There are sex differences in risk; twice as many women as men develop a lifetime diagnosis of PTSD. Methylomic profiles derived from peripheral blood are well-suited for investigating PTSD because DNA methylation (DNAm) encodes individual response to trauma and may play a key role in the immune dysregulation characteristic of PTSD pathophysiology. In the current study, we leveraged recent methodological advances to investigate sex-specific differences in DNAm-based leukocyte composition that are associated with lifetime PTSD. We estimated leukocyte composition on a combined methylation array dataset (483 participants, ∼450 k CpG sites) consisting of two civilian cohorts, the Detroit Neighborhood Health Study and Grady Trauma Project. Sex-stratified Mann-Whitney U test and two-way ANCOVA revealed that lifetime PTSD was associated with significantly higher monocyte proportions in males, but not in females (Holm-adjusted p-val < 0.05). No difference in monocyte proportions was observed between current and remitted PTSD cases in males, suggesting that this sex-specific difference may reflect a long-standing trait of lifetime history of PTSD, rather than current state of PTSD. Associations with lifetime PTSD or PTSD status were not observed in any other leukocyte subtype and our finding in monocytes was confirmed using cell estimates based on a different deconvolution algorithm, suggesting that our sex-specific findings are robust across cell estimation approaches. Overall, our main finding of elevated monocyte proportions in males, but not in females with lifetime history of PTSD provides evidence for a sex-specific difference in peripheral blood leukocyte composition that is detectable in methylomic profiles and that may reflect long-standing changes associated with PTSD diagnosis