Biotic carbon feedbacks in a materially-closed soil-vegetation-atmosphere system

The magnitude and direction of the coupled feedbacks between the biotic and abiotic components of the terrestrial carbon cycle is a major source of uncertainty in coupled climate–carbon-cycle models1, 2, 3. Materially closed, energetically open biological systems continuously and simultaneously allow the two-way feedback loop between the biotic and abiotic components to take place4, 5, 6, 7, but so far have not been used to their full potential in ecological research, owing to the challenge of achieving sustainable model systems6, 7. We show that using materially closed soil–vegetation–atmosphere systems with pro rata carbon amounts for the main terrestrial carbon pools enables the establishment of conditions that balance plant carbon assimilation, and autotrophic and heterotrophic respiration fluxes over periods suitable to investigate short-term biotic carbon feedbacks. Using this approach, we tested an alternative way of assessing the impact of increased CO2 and temperature on biotic carbon feedbacks. The results show that without nutrient and water limitations, the short-term biotic responses could potentially buffer a temperature increase of 2.3 °C without significant positive feedbacks to atmospheric CO2. We argue that such closed-system research represents an important test-bed platform for model validation and parameterization of plant and soil biotic responses to environmental changes

Bench-to-bedside review : targeting antioxidants to mitochondria in sepsis

Peer reviewedPublisher PD

Pergumulan as the starter and sustainer of Servant Leadership A case of academic leadership in a private University in Indonesia

In the disruptive era, every organization is expected to cope with change. This includes the ones in the sector of higher education. Servant leadership is considered as the leadership approach that enables Higher Educational Institutions (HEIs) to deal with the inevitable changes. This research explores an academic leadership in a private university in Indonesia, which endorses servant leadership as its leadership approach. The case study involves the interview of twenty-six academic leaders who have asked to answer two fundamental questions: 1) How do they perceive the invitation to lead as an academic leader and 2) What did they do as they consider whether to take the offer to lead as an academic leader? The gathered data was processed using the Qualitative Data Analysis consisting data condensation, data display and drawing and verifying conclusion. Twenty-five academic leaders said no when they first offer and this initial refusal drives the researcher to find a term called �pergumulan� as the common theme across the interviewees. �Pergumulan� or a spiritual struggle happened during the pre-leadership journey and during the leadership journey of these academic leaders. The former suggests that �pergumulan� is spiritual, intrapersonal and interpersonal. The latter indicates that pergumulan happens when the servant leaders search their motivation and figure out the way to improve themselves while serving their followers. Lastly, during their leadership, the servant leaders are also having the �pergumulan� as they have to confront or rebuke their followers

Mycobacterium abscessus Glycopeptidolipid Prevents Respiratory Epithelial TLR2 Signaling as Measured by HβD2 Gene Expression and IL-8 Release

Mycobacterium abscessus has emerged as an important cause of lung infection, particularly in patients with bronchiectasis. Innate immune responses must be highly effective at preventing infection with M. abscessus because it is a ubiquitous environmental saprophyte and normal hosts are not commonly infected. M. abscessus exists as either a glycopeptidolipid (GPL) expressing variant (smooth phenotype) in which GPL masks underlying bioactive cell wall lipids, or as a variant lacking GPL which is immunostimulatory and invasive in macrophage infection models. Respiratory epithelium has been increasingly recognized as playing an important role in the innate immune response to pulmonary pathogens. Respiratory epithelial cells express toll-like receptors (TLRs) which mediate the innate immune response to pulmonary pathogens. Both interleukin-8 (IL-8) and human β-defensin 2 (HβD2) are expressed by respiratory epithelial cells in response to toll-like receptor 2 (TLR2) receptor stimulation. In this study, we demonstrate that respiratory epithelial cells respond to M. abscessus variants lacking GPL with expression of IL-8 and HβD2. Furthermore, we demonstrate that this interaction is mediated through TLR2. Conversely, M. abscessus expressing GPL does not stimulate expression of IL-8 or HβD2 by respiratory epithelial cells which is consistent with “masking” of underlying bioactive cell wall lipids by GPL. Because GPL-expressing smooth variants are the predominant phenotype existing in the environment, this provides an explanation whereby initial M. abscessus colonization of abnormal lung airways escapes detection by the innate immune system

A Histone Map of Human Chromosome 20q13.12

We present a systematic search for regulatory elements in a 3.5 Mb region on human chromosome 20q13.12, a region associated with a number of medical conditions such as type II diabetes and obesity.We profiled six histone modifications alongside RNA polymerase II (PolII) and CTCF in two cell lines, HeLa S3 and NTERA-2 clone D1 (NT2/D1), by chromatin immunoprecipitation using an in-house spotted DNA array, constructed with 1.8 kb overlapping plasmid clones. In both cells, more than 90% of transcription start sites (TSSs) of expressed genes showed enrichments with PolII, di-methylated lysine 4 of histone H3 (H3K4me2), tri-methylated lysine 4 of histone H3 (H3K4me3) or acetylated H3 (H3Ac), whereas mono-methylated lysine 4 of histone H3 (H3K4me1) signals did not correlate with expression. No TSSs were enriched with tri-methylated lysine 27 of histone H3 (H3K27me3) in HeLa S3, while eight TSSs (4 expressed) showed enrichments in NT2/D1. We have also located several CTCF binding sites that are potential insulator elements.In summary, we annotated a number of putative regulatory elements in 20q13.12 and went on to verify experimentally a subset of them using dual luciferase reporter assays. Correlating this data to sequence variation can aid identification of disease causing variants

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Efficient Utilization of Rare Variants for Detection of Disease-Related Genomic Regions

When testing association between rare variants and diseases, an efficient analytical approach involves considering a set of variants in a genomic region as the unit of analysis. One factor complicating this approach is that the vast majority of rare variants in practical applications are believed to represent background neutral variation. As a result, analyzing a single set with all variants may not represent a powerful approach. Here, we propose two alternative strategies. In the first, we analyze the subsets of rare variants exhaustively. In the second, we categorize variants selectively into two subsets: one in which variants are overrepresented in cases, and the other in which variants are overrepresented in controls. When the proportion of neutral variants is moderate to large we show, by simulations, that the both proposed strategies improve the statistical power over methods analyzing a single set with total variants. When applied to a real sequencing association study, the proposed methods consistently produce smaller p-values than their competitors. When applied to another real sequencing dataset to study the difference of rare allele distributions between ethnic populations, the proposed methods detect the overrepresentation of variants between the CHB (Chinese Han in Beijing) and YRI (Yoruba people of Ibadan) populations with small p-values. Additional analyses suggest that there is no difference between the CHB and CHD (Chinese Han in Denver) datasets, as expected. Finally, when applied to the CHB and JPT (Japanese people in Tokyo) populations, existing methods fail to detect any difference, while it is detected by the proposed methods in several regions

Large-Scale Phylogenetic Analysis of Emerging Infectious Diseases

Microorganisms that cause infectious diseases present critical issues of national security, public health, and economic welfare.  For example, in recent years, highly pathogenic strains of avian influenza have emerged in Asia, spread through Eastern Europe and threaten to become pandemic. As demonstrated by the coordinated response to Severe Acute Respiratory Syndrome (SARS) and influenza, agents of infectious disease are being addressed via large-scale genomic sequencing.  The goal of genomic sequencing projects are to rapidly put large amounts of data in the public domain to accelerate research on disease surveillance, treatment, and prevention. However, our ability to derive information from large comparative genomic datasets lags far behind acquisition.  Here we review the computational challenges of comparative genomic analyses, specifically sequence alignment and reconstruction of phylogenetic trees.  We present novel analytical results on from two important infectious diseases, Severe Acute Respiratory Syndrome (SARS) and influenza.SARS and influenza have similarities and important differences both as biological and comparative genomic analysis problems.  Influenza viruses (Orthymxyoviridae) are RNA based.  Current evidence indicates that influenza viruses originate in aquatic birds from wild populations. Influenza has been studied for decades via well-coordinated international efforts.  These efforts center on surveillance via antibody characterization of the hemagglutinin (HA) and neuraminidase (N) proteins of the circulating strains to inform vaccine design. However we still do not have a clear understanding of: 1) various transmission pathways such as the role of intermediate hosts such as swine and domestic birds and 2) the key mutation and genomic recombination events that underlie periodic pandemics of influenza.  In the past 30 years, sequence data from HA and N loci has become an important data type. In the past year, full genomic data has become prominent.  These data present exciting opportunities to address unanswered questions in influenza pandemics.SARS is caused by a previously unrecognized lineage of coronavirus, SARS-CoV, which like influenza has an RNA based genome.  Although SARS-CoV is widely believed to have originated in animals there remains disagreement over the candidate animal source that lead to the original outbreak of SARS.  In contrast to the long history of the study of influenza, SARS was only recognized in late 2002 and the virus that causes SARS has been documented primarily by genomic sequencing.In the past, most studies of influenza were performed on a limited number of isolates and genes suited to a particular problem.  Major goals in science today are to understand emerging diseases in broad geographic, environmental, societal, biological, and genomic contexts. Synthesizing diverse information brought together by various researchers is important to find out what can be done to prevent future outbreaks {JON03}.  Thus comprehensive means to organize and analyze large amounts of diverse information are critical.  For example, the relationships of isolates and patterns of genomic change observed in large datasets might not be consistent with hypotheses formed on partial data.  Moreover when researchers rely on partial datasets, they restrict the range of possible discoveries.Phylogenetics is well suited to the complex task of understanding emerging infectious disease. Phylogenetic analyses can test many hypotheses by comparing diverse isolates collected from various hosts, environments, and points in time and organizing these data into various evolutionary scenarios.  The products of a phylogenetic analysis are a graphical tree of ancestor-descendent relationships and an inferred summary of mutations, recombination events, host shifts, geographic, and temporal spread of the viruses.  However, this synthesis comes at a price.  The cost of computation of phylogenetic analysis expands combinatorially as the number of isolates considered increases. Thus, large datasets like those currently produced are commonly considered intractable.  We address this problem with synergistic development of heuristics tree search strategies and parallel computing.Fil: Janies, D.. Ohio State University; Estados UnidosFil: Pol, Diego. Ohio State University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin