Ocean Acidification Regulates the Activity, Community Structure, and Functional Potential of Heterotrophic Bacterioplankton in an Oligotrophic Gyre

Ocean acidification (OA), a consequence of increased global carbon dioxide (CO2) emissions, is considered a major threat to marine ecosystems. Its effects on bacterioplankton activity, diversity, and community composition have received considerable attention. However, the direct impact of OA on heterotrophic bacterioplankton is often masked by the significant response of phytoplankton due to the close coupling of heterotrophic bacterioplankton and autotrophs. Here we investigated the responses of a heterotrophic bacterioplankton assemblage to high pCO2 (790-ppm) treatment in warm tropical western Pacific waters by conducting a microcosm experiment in dark for 12 days. Heterotrophic bacterioplankton abundance and production were enhanced by OA over the first 6 days of incubation, while the diversity and species richness were negatively affected. Bacterioplankton community composition in the high pCO2 treatment changed faster than that in the control. The molecular ecological network analysis showed that the elevated CO2 changed the overall connections among the bacterial community and resulted in a simple network under high CO2 condition. Species-specific responses to OA were observed and could be attributed to the different life strategies and to the ability of a given species to adapt to environmental conditions. In addition, high-throughput functional gene array analysis revealed that genes related to carbon and nitrogen cycling were positively affected by acidification. Together, our findings suggest that OA has direct effects on heterotrophic bacterioplankton in a low-latitude warm ocean and may therefore affect global biogeochemical cycles

Characterization of Chlorinated Aliphatic Hydrocarbons and Environmental Variables in a Shallow Groundwater in Shanghai Using Kriging Interpolation and Multifactorial Analysis

CAHs, as a cleaning solvent, widely contaminated shallow groundwater with the development of manufacturing in China's Yangtze River Delta. This study focused on the distribution of CAHs, and correlations between CAHs and environmental variables in a shallow groundwater in Shanghai, using kriging interpolation and multifactorial analysis. The results showed that the overall CAHs plume area (above DIV) was approximately 9,000 m(2) and located in the 2-4 m underground, DNAPL was accumulated at an area of approximately 1,400 m(2) and located in the 6-8m sandy silt layer on the top of the muddy silty clay. Heat-map of PPC for CAHs and environmental variables showed that the correlation between 'Fe2+' and most CAHs such as '1,1,1-TCA', '1,1-DCA', '1,1-DCE' and '% TCA' were significantly positive (p<0.001), but '% CA' and/or '% VC' was not, and 'Cl-' was significantly positive correlated with '1,1-DCA' and '1,1-DCE' (p<0.001). The PCA demonstrated that the relative proportions of CAHs in groundwater were mostly controlled by the sources and the natural attenuation. In conclusion, the combination of geographical and chemometrics was helpful to establishing an aerial perspective of CAHs and identifying reasons for the accumulation of toxic dechlorination intermediates, and could become a useful tool for characterizing contaminated sites in general.published_or_final_versio

Safe and complete contig assembly via omnitigs

Contig assembly is the first stage that most assemblers solve when reconstructing a genome from a set of reads. Its output consists of contigs -- a set of strings that are promised to appear in any genome that could have generated the reads. From the introduction of contigs 20 years ago, assemblers have tried to obtain longer and longer contigs, but the following question was never solved: given a genome graph $G$ (e.g. a de Bruijn, or a string graph), what are all the strings that can be safely reported from $G$ as contigs? In this paper we finally answer this question, and also give a polynomial time algorithm to find them. Our experiments show that these strings, which we call omnitigs, are 66% to 82% longer on average than the popular unitigs, and 29% of dbSNP locations have more neighbors in omnitigs than in unitigs.Comment: Full version of the paper in the proceedings of RECOMB 201

Nicotinic acetylcholine receptor expression in human airway correlates with lung function

Nicotine and its derivatives, by binding to nicotinic acetylcholine receptors (nAChRs) on bronchial epithelial cells, can regulate cellular signaling and inflammatory processes. Delineation of nAChR subtypes and their responses to nicotine stimulation in bronchial epithelium may provide information for therapeutic targeting in smoking-related inflammation in the airway. Expression of nAChR subunit genes in 60 bronchial epithelial biopsies and immunohistochemical staining for the subcellular locations of nAChR subunit expression were evaluated. Seven human bronchial epithelial cell lines (HBECs) were exposed to nicotine in vitro for their response in nAChR subunit gene expression to nicotine exposure and removal. The relative normalized amount of expression of nAChR α4, α5, and α7 and immunohistochemical staining intensity of nAChR α4, α5, and β3 expression showed significant correlation with lung function parameters. Nicotine stimulation in HBECs resulted in transient increase in the levels of nAChR α5 and α6 but more sustained increase in nAChR α7 expression. nAChR expression in bronchial epithelium was found to correlate with lung function. Nicotine exposure in HBECs resulted in both short and longer term responses in nAChR subunit gene expression. These results gave insight into the potential of targeting nAChRs for therapy in smoking-related inflammation in the airway.postprin

Damage to the prefrontal cortex increases utilitarian moral judgements

The psychological and neurobiological processes underlying moral judgement have been the focus of many recent empirical studies1–11. Of central interest is whether emotions play a causal role in moral judgement, and, in parallel, how emotion-related areas of the brain contribute to moral judgement. Here we show that six patients with focal bilateral damage to the ventromedial prefrontal cortex (VMPC), a brain region necessary for the normal generation of emotions and, in particular, social emotions12–14, produce an abnor- mally ‘utilitarian’ pattern of judgements on moral dilemmas that pit compelling considerations of aggregate welfare against highly emotionally aversive behaviours (for example, having to sacrifice one person’s life to save a number of other lives)7,8. In contrast, the VMPC patients’ judgements were normal in other classes of moral dilemmas. These findings indicate that, for a selective set of moral dilemmas, the VMPC is critical for normal judgements of right and wrong. The findings support a necessary role for emotion in the generation of those judgements

Anisotropic Structure of the Order Parameter in FeSe0.45Te0.55 Revealed by Angle Resolved Specific Heat

The symmetry and structure of the superconducting gap in the Fe-based superconductors are the central issue for understanding these novel materials. So far the experimental data and theoretical models have been highly controversial. Some experiments favor two or more constant or nearly-constant gaps, others indicate strong anisotropy and yet others suggest gap zeros ("nodes"). Theoretical models also vary, suggesting that the absence or presence of the nodes depends quantitatively on the model parameters. An opinion that has gained substantial currency is that the gap structure, unlike all other known superconductors, including cuprates, may be different in different compounds within the same family. A unique method for addressing this issue, one of the very few methods that are bulk and angle-resolved, calls for measuring the electronic specific heat in a rotating magnetic field, as a function of field orientation with respect to the crystallographic axes. In this Communication we present the first such measurement for an Fe-based high-Tc superconductor (FeBSC). We observed a fourfold oscillation of the specific heat as a function of the in-plane magnetic field direction, which allowed us to identify the locations of the gap minima (or nodes) on the Fermi surface. Our results are consistent with the expectations of an extended s-wave model with a significant gap anisotropy on the electron pockets and the gap minima along the \Gamma M (or Fe-Fe bond) direction.Comment: 32 pages, 7 figure

Impact of inhaled corticosteroids on growth in children with asthma: systematic review and meta-analysis

Background: Long-term inhaled corticosteroids (ICS) may reduce growth velocity and final height of children with asthma. We aimed to evaluate the association between ICS use of >12 months and growth. Methods: We initially searched MEDLINE and EMBASE in July 2013, followed by a PubMed search updated to December 2014. We selected RCTs and controlled observational studies of ICS use in patients with asthma. We conducted random effects meta-analysis of mean differences in growth velocity (cm/year) or final height (cm) between groups. Heterogeneity was assessed using the I2 statistic. Results: We found 23 relevant studies (twenty RCTs and three observational studies) after screening 1882 hits. Meta-analysis of 16 RCTs showed that ICS use significantly reduced growth velocity at one year follow-up (mean difference -0.48 cm/year (95% CI -0.66 to -0.29)). There was evidence of a dose-response effect in three RCTs. Final adult height showed a mean reduction of -1.20 cm (95% CI -1.90 cm to -0.50 cm) with budesonide versus placebo in a high quality RCT. Meta-analysis of two lower quality observational studies revealed uncertainty in the association between ICS use and final adult height, pooled mean difference -0.85 cm (95% CI -3.35 to 1.65). Conclusion: Use of ICS for >12 months in children with asthma has a limited impact on annual growth velocity. In ICS users, there is a slight reduction of about a centimeter in final adult height, which when interpreted in the context of average adult height in England (175 cm for men and 161 cm for women), represents a 0.7% reduction compared to non-ICS users

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Definition of the σW regulon of Bacillus subtilis in the absence of stress

Bacteria employ extracytoplasmic function (ECF) sigma factors for their responses to environmental stresses. Despite intensive research, the molecular dissection of ECF sigma factor regulons has remained a major challenge due to overlaps in the ECF sigma factor-regulated genes and the stimuli that activate the different ECF sigma factors. Here we have employed tiling arrays to single out the ECF σW regulon of the Gram-positive bacterium Bacillus subtilis from the overlapping ECF σX, σY, and σM regulons. For this purpose, we profiled the transcriptome of a B. subtilis sigW mutant under non-stress conditions to select candidate genes that are strictly σW-regulated. Under these conditions, σW exhibits a basal level of activity. Subsequently, we verified the σW-dependency of candidate genes by comparing their transcript profiles to transcriptome data obtained with the parental B. subtilis strain 168 grown under 104 different conditions, including relevant stress conditions, such as salt shock. In addition, we investigated the transcriptomes of rasP or prsW mutant strains that lack the proteases involved in the degradation of the σW anti-sigma factor RsiW and subsequent activation of the σW-regulon. Taken together, our studies identify 89 genes as being strictly σW-regulated, including several genes for non-coding RNAs. The effects of rasP or prsW mutations on the expression of σW-dependent genes were relatively mild, which implies that σW-dependent transcription under non-stress conditions is not strictly related to RasP and PrsW. Lastly, we show that the pleiotropic phenotype of rasP mutant cells, which have defects in competence development, protein secretion and membrane protein production, is not mirrored in the transcript profile of these cells. This implies that RasP is not only important for transcriptional regulation via σW, but that this membrane protease also exerts other important post-transcriptional regulatory functions

Tundra soil carbon is vulnerable to rapid microbial decomposition under climate warming

Microbial decomposition of soil carbon in high-latitude tundra underlain with permafrost is one of the most important, but poorly understood, potential positive feedbacks of greenhouse gas emissions from terrestrial ecosystems into the atmosphere in a warmer world. Using integrated metagenomic technologies, we showed that the microbial functional community structure in the active layer of tundra soil was significantly altered after only 1.5 years of warming, a rapid response demonstrating the high sensitivity of this ecosystem to warming. The abundances of microbial functional genes involved in both aerobic and anaerobic carbon decomposition were also markedly increased by this short-term warming. Consistent with this, ecosystem respiration (R eco) increased up to 38%. In addition, warming enhanced genes involved in nutrient cycling, which very likely contributed to an observed increase (30%) in gross primary productivity (GPP). However, the GPP increase did not offset the extra R eco, resulting in significantly more net carbon loss in warmed plots compared with control plots. Altogether, our results demonstrate the vulnerability of active-layer soil carbon in this permafrost-based tundra ecosystem to climate warming and the importance of microbial communities in mediating such vulnerability