Transport of Explosive Residue Surrogates in Saturated Porous Media

Department of Defense operational ranges may become contaminated by particles of explosives residues (ER) as a result of low-order detonations of munitions. The goal of this study was to determine the extent to which particles of ER could migrate through columns of sandy sediment, representing model aquifer materials. Transport experiments were conducted in saturated columns (2 × 20 cm) packed with different grain sizes of clean sand or glass beads. Fine particles (approximately 2 to 50 μm) of 2,6-dinitrotoluene (DNT) were used as a surrogate for ER. DNT particles were applied to the top 1 cm of sand or beads in the columns, and the columns were subsequently leached with artificial groundwater solutions. DNT migration occurred as both dissolved and particulate phases. Concentration differences between unfiltered and filtered samples indicate that particulate DNT accounted for up to 41% of the mass recovered in effluent samples. Proportionally, more particulate than dissolved DNT was recovered in effluent solutions from columns with larger grain sizes, while total concentrations of DNT in effluent were inversely related to grain size. Of the total DNT mass applied to the uppermost layer of the column, <3% was recovered in the effluent with the bulk remaining in the top 2 cm of the column. Our results suggest there is some potential for subsurface migration of ER particles and that most of the particles will be retained over relatively short transport distances

Abnormal septal convexity into the left ventricle occurs in subclinical hypertrophic cardiomyopathy.

BACKGROUND: Sarcomeric gene mutations cause hypertrophic cardiomyopathy (HCM). In gene mutation carriers without left ventricular (LV) hypertrophy (G + LVH-), subclinical imaging biomarkers are recognized as predictors of overt HCM, consisting of anterior mitral valve leaflet elongation, myocardial crypts, hyperdynamic LV ejection fraction, and abnormal apical trabeculation. Reverse curvature of the interventricular septum (into the LV) is characteristic of overt HCM. We aimed to assess LV septal convexity in subclinical HCM. METHODS: Cardiovascular magnetic resonance was performed on 36 G + LVH- individuals (31 ± 14 years, 33 % males) with a pathogenic sarcomere mutation, and 36 sex and age-matched healthy controls (33 ± 12 years, 33 % males). Septal convexity (SCx) was measured in the apical four chamber view perpendicular to a reference line connecting the mid-septal wall at tricuspid valve insertion level and the apical right ventricular insertion point. RESULTS: Septal convexity was increased in G + LVH- compared to controls (maximal distance of endocardium to reference line: 5.0 ± 2.5 mm vs. 1.6 ± 2.4 mm, p ≤ 0.0001). Expected findings occurred in G + LVH- individuals: longer anterior mitral valve leaflet (23.5 ± 3.0 mm vs. 19.9 ± 3.1 mm, p ≤ 0.0001), higher relative wall thickness (0.31 ± 0.05 vs. 0.29 ± 0.04, p ≤ 0.05), higher LV ejection fraction (70.8 ± 4.3 % vs. 68.3 ± 4.4 %, p ≤ 0.05), and smaller LV end-systolic volume index (21.4 ± 4.4 ml/m(2) vs. 23.7 ± 5.8 ml/m(2), p ≤ 0.05). Other morphologic measurements (LV angles, sphericity index, and eccentricity index) were not different between G + LVH- and controls. CONCLUSIONS: Septal convexity is an additional previously undescribed feature of subclinical HCM

TRPV1 in Brain Is Involved in Acetaminophen-Induced Antinociception

Background: Acetaminophen, the major active metabolite of acetanilide in man, has become one of the most popular overthe- counter analgesic and antipyretic agents, consumed by millions of people daily. However, its mechanism of action is still a matter of debate. We have previously shown that acetaminophen is further metabolized to N-(4-hydroxyphenyl)-5Z,8Z,11Z,14Z-eicosatetraenamide (AM404) by fatty acid amide hydrolase (FAAH) in the rat and mouse brain and that this metabolite is a potent activator of transient receptor potential vanilloid 1 (TRPV1) in vitro. Pharmacological activation of TRPV1 in the midbrain periaqueductal gray elicits antinociception in rats. It is therefore possible that activation of TRPV1 in the brain contributes to the analgesic effect of acetaminophen. Methodology/Principal Findings: Here we show that the antinociceptive effect of acetaminophen at an oral dose lacking hypolocomotor activity is absent in FAAH and TRPV1 knockout mice in the formalin, tail immersion and von Frey tests. This dose of acetaminophen did not affect the global brain contents of prostaglandin E-2 (PGE(2)) and endocannabinoids. Intracerebroventricular injection of AM404 produced a TRPV1-mediated antinociceptive effect in the mouse formalin test. Pharmacological inhibition of TRPV1 in the brain by intracerebroventricular capsazepine injection abolished the antinociceptive effect of oral acetaminophen in the same test. Conclusions: This study shows that TRPV1 in brain is involved in the antinociceptive action of acetaminophen and provides a strategy for developing central nervous system active oral analgesics based on the coexpression of FAAH and TRPV1 in the brain

The effectiveness of mindfulness-based interventions in the perinatal period: a systematic review and meta-analysis

Perinatal mental health difficulties are associated with adverse consequences for parents and infants. However, the potential risks associated with the use of psychotropic medication for pregnant and breastfeeding women and the preferences expressed by women for non-pharmacological interventions mean it is important to ensure that effective psychological interventions are available. It has been argued that mindfulness-based interventions may offer a novel approach to treating perinatal mental health difficulties, but relatively little is known about their effectiveness with perinatal populations. This paper therefore presents a systematic review and meta-analysis of the effectiveness of mindfulness-based interventions for reducing depression, anxiety and stress and improving mindfulness skills in the perinatal period. A systematic review identified seventeen studies of mindfulness-based interventions in the perinatal period, including both controlled trials (n = 9) and pre-post uncontrolled studies (n = 8). Eight of these studies also included qualitative data. Hedge’s g was used to assess uncontrolled and controlled effect sizes in separate meta-analyses, and a narrative synthesis of qualitative data was produced. Pre- to post-analyses showed significant reductions in depression, anxiety and stress and significant increases in mindfulness skills post intervention, each with small to medium effect sizes. Completion of the mindfulness-based interventions was reasonable with around three quarters of participants meeting study-defined criteria for engagement or completion where this was recorded. Qualitative data suggested that participants viewed mindfulness interventions positively. However, between-group analyses failed to find any significant post-intervention benefits for depression, anxiety or stress of mindfulness-based interventions in comparison to control conditions: effect sizes were negligible and it was conspicuous that intervention group participants did not appear to improve significantly more than controls in their mindfulness skills. The interventions offered often deviated from traditional mindfulness-based cognitive therapy or mindfulness-based stress reduction programmes, and there was also a tendency for studies to focus on healthy rather than clinical populations, and on antenatal rather than postnatal populations. It is argued that these and other limitations with the included studies and their interventions may have been partly responsible for the lack of significant between-group effects. The implications of the findings and recommendations for future research are discussed

Defining functional diversity for lignocellulose degradation in a microbial community using multi-omics studies

Abstract\ud \ud Background\ud Lignocellulose is one of the most abundant forms of fixed carbon in the biosphere. Current industrial approaches to the degradation of lignocellulose employ enzyme mixtures, usually from a single fungal species, which are only effective in hydrolyzing polysaccharides following biomass pre-treatments. While the enzymatic mechanisms of lignocellulose degradation have been characterized in detail in individual microbial species, the microbial communities that efficiently breakdown plant materials in nature are species rich and secrete a myriad of enzymes to perform “community-level” metabolism of lignocellulose. Single-species approaches are, therefore, likely to miss important aspects of lignocellulose degradation that will be central to optimizing commercial processes.\ud \ud \ud Results\ud Here, we investigated the microbial degradation of wheat straw in liquid cultures that had been inoculated with wheat straw compost. Samples taken at selected time points were subjected to multi-omics analysis with the aim of identifying new microbial mechanisms for lignocellulose degradation that could be applied in industrial pre-treatment of feedstocks. Phylogenetic composition of the community, based on sequenced bacterial and eukaryotic ribosomal genes, showed a gradual decrease in complexity and diversity over time due to microbial enrichment. Taxonomic affiliation of bacterial species showed dominance of Bacteroidetes and Proteobacteria and high relative abundance of genera Asticcacaulis, Leadbetterella and Truepera. The eukaryotic members of the community were enriched in peritrich ciliates from genus Telotrochidium that thrived in the liquid cultures compared to fungal species that were present in low abundance. A targeted metasecretome approach combined with metatranscriptomics analysis, identified 1127 proteins and showed the presence of numerous carbohydrate-active enzymes extracted from the biomass-bound fractions and from the culture supernatant. This revealed a wide array of hydrolytic cellulases, hemicellulases and carbohydrate-binding modules involved in lignocellulose degradation. The expression of these activities correlated to the changes in the biomass composition observed by FTIR and ssNMR measurements.\ud \ud \ud Conclusions\ud A combination of mass spectrometry-based proteomics coupled with metatranscriptomics has enabled the identification of a large number of lignocellulose degrading enzymes that can now be further explored for the development of improved enzyme cocktails for the treatment of plant-based feedstocks. In addition to the expected carbohydrate-active enzymes, our studies reveal a large number of unknown proteins, some of which may play a crucial role in community-based lignocellulose degradation.This work was funded by Biotechnology and Biological Sciences Research\ud Council (BBSRC) Grants BB/1018492/1, BB/K020358/1 and BB/P027717/1, the\ud BBSRC Network in Biotechnology and Bioenergy BIOCATNET and São Paulo\ud Research Foundation (FAPESP) Grant 10/52362-5. ERdA thanks EMBRAPA\ud Instrumentation São Carlos and Dr. Luiz Alberto Colnago for providing the\ud NMR facility and CNPq Grant 312852/2014-2. The authors would like to thank\ud Deborah Rathbone and Susan Heywood from the Biorenewables Develop‑\ud ment Centre for technical assistance in rRNA amplicon sequencing

Uncovering spatial topology represented by rat hippocampal population neuronal codes

Hippocampal population codes play an important role in representation of spatial environment and spatial navigation. Uncovering the internal representation of hippocampal population codes will help understand neural mechanisms of the hippocampus. For instance, uncovering the patterns represented by rat hippocampus (CA1) pyramidal cells during periods of either navigation or sleep has been an active research topic over the past decades. However, previous approaches to analyze or decode firing patterns of population neurons all assume the knowledge of the place fields, which are estimated from training data a priori. The question still remains unclear how can we extract information from population neuronal responses either without a priori knowledge or in the presence of finite sampling constraint. Finding the answer to this question would leverage our ability to examine the population neuronal codes under different experimental conditions. Using rat hippocampus as a model system, we attempt to uncover the hidden “spatial topology” represented by the hippocampal population codes. We develop a hidden Markov model (HMM) and a variational Bayesian (VB) inference algorithm to achieve this computational goal, and we apply the analysis to extensive simulation and experimental data. Our empirical results show promising direction for discovering structural patterns of ensemble spike activity during periods of active navigation. This study would also provide useful insights for future exploratory data analysis of population neuronal codes during periods of sleep.National Institutes of Health (U.S.) (NIH Grant DP1-OD003646)National Institutes of Health (U.S.) (Grant MH061976