Systematic review of prognostic models in traumatic brain injury

BACKGROUND: Traumatic brain injury (TBI) is a leading cause of death and disability world-wide. The ability to accurately predict patient outcome after TBI has an important role in clinical practice and research. Prognostic models are statistical models that combine two or more items of patient data to predict clinical outcome. They may improve predictions in TBI patients. Multiple prognostic models for TBI have accumulated for decades but none of them is widely used in clinical practice. The objective of this systematic review is to critically assess existing prognostic models for TBI METHODS: Studies that combine at least two variables to predict any outcome in patients with TBI were searched in PUBMED and EMBASE. Two reviewers independently examined titles, abstracts and assessed whether each met the pre-defined inclusion criteria. RESULTS: A total of 53 reports including 102 models were identified. Almost half (47%) were derived from adult patients. Three quarters of the models included less than 500 patients. Most of the models (93%) were from high income countries populations. Logistic regression was the most common analytical strategy to derived models (47%). In relation to the quality of the derivation models (n:66), only 15% reported less than 10% pf loss to follow-up, 68% did not justify the rationale to include the predictors, 11% conducted an external validation and only 19% of the logistic models presented the results in a clinically user-friendly way CONCLUSION: Prognostic models are frequently published but they are developed from small samples of patients, their methodological quality is poor and they are rarely validated on external populations. Furthermore, they are not clinically practical as they are not presented to physicians in a user-friendly way. Finally because only a few are developed using populations from low and middle income countries, where most of trauma occurs, the generalizability to these setting is limited

Chromosomal Rearrangements Formed by rrn Recombination Do Not Improve Replichore Balance in Host-Specific Salmonella enterica Serovars

operons. One hypothesis explaining these rearrangements suggests that replichore imbalance introduced from horizontal transfer of pathogenicity islands and prophages drives chromosomal rearrangements in an attempt to improve balance.This hypothesis was directly tested by comparing the naturally-occurring chromosomal arrangement types to the theoretically possible arrangement types, and estimating their replichore balance using a calculator. In addition to previously characterized strains belonging to host-specific serovars, the arrangement types of 22 serovar Gallinarum strains was also determined. Only 48 out of 1,440 possible arrangement types were identified in 212 host-specific strains. While the replichores of most naturally-occurring arrangement types were well-balanced, most theoretical arrangement types had imbalanced replichores. Furthermore, the most common types of rearrangements did not change replichore balance.The results did not support the hypothesis that replichore imbalance causes these rearrangements, and suggest that the rearrangements could be explained by aspects of a host-specific lifestyle

Climate change and environmental impacts on maternal and newborn health with focus on Arctic populations

In 2007, the Intergovernmental Panel on Climate Change (IPCC) presented a report on global warming and the impact of human activities on global warming. Later the Lancet commission identified six ways human health could be affected. Among these were not environmental factors which are also believed to be important for human health. In this paper we therefore focus on environmental factors, climate change and the predicted effects on maternal and newborn health. Arctic issues are discussed specifically considering their exposure and sensitivity to long range transported contaminants. Considering that the different parts of pregnancy are particularly sensitive time periods for the effects of environmental exposure, this review focuses on the impacts on maternal and newborn health. Environmental stressors known to affects human health and how these will change with the predicted climate change are addressed. Air pollution and food security are crucial issues for the pregnant population in a changing climate, especially indoor climate and food security in Arctic areas. The total number of environmental factors is today responsible for a large number of the global deaths, especially in young children. Climate change will most likely lead to an increase in this number. Exposure to the different environmental stressors especially air pollution will in most parts of the world increase with climate change, even though some areas might face lower exposure. Populations at risk today are believed to be most heavily affected. As for the persistent organic pollutants a warming climate leads to a remobilisation and a possible increase in food chain exposure in the Arctic and thus increased risk for Arctic populations. This is especially the case for mercury. The perspective for the next generations will be closely connected to the expected temperature changes; changes in housing conditions; changes in exposure patterns; predicted increased exposure to Mercury because of increased emissions and increased biological availability. A number of environmental stressors are predicted to increase with climate change and increasingly affecting human health. Efforts should be put on reducing risk for the next generation, thus global politics and research effort should focus on maternal and newborn health

Activation-Induced Cytidine Deaminase Deficiency Causes Organ-Specific Autoimmune Disease

Activation-induced cytidine deaminase (AID) expressed by germinal center B cells is a central regulator of somatic hypermutation (SHM) and class switch recombination (CSR). Humans with AID mutations develop not only the autosomal recessive form of hyper-IgM syndrome (HIGM2) associated with B cell hyperplasia, but also autoimmune disorders by unknown mechanisms. We report here that AID−/− mice spontaneously develop tertiary lymphoid organs (TLOs) in non-lymphoid tissues including the stomach at around 6 months of age. At a later stage, AID−/− mice develop a severe gastritis characterized by loss of gastric glands and epithelial hyperplasia. The disease development was not attenuated even under germ-free (GF) conditions. Gastric autoantigen -specific serum IgM was elevated in AID−/− mice, and the serum levels correlated with the gastritis pathological score. Adoptive transfer experiments suggest that autoimmune CD4+ T cells mediate gastritis development as terminal effector cells. These results suggest that abnormal B-cell expansion due to AID deficiency can drive B-cell autoimmunity, and in turn promote TLO formation, which ultimately leads to the propagation of organ-specific autoimmune effector CD4+ T cells. Thus, AID plays an important role in the containment of autoimmune diseases by negative regulation of autoreactive B cells

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

Genome-wide evolutionary dynamics of influenza B viruses on a global scale

The global-scale epidemiology and genome-wide evolutionary dynamics of influenza B remain poorly understood compared with influenza A viruses. We compiled a spatio-temporally comprehensive dataset of influenza B viruses, comprising over 2,500 genomes sampled worldwide between 1987 and 2015, including 382 newly-sequenced genomes that fill substantial gaps in previous molecular surveillance studies. Our contributed data increase the number of available influenza B virus genomes in Europe, Africa and Central Asia, improving the global context to study influenza B viruses. We reveal Yamagata-lineage diversity results from co-circulation of two antigenically-distinct groups that also segregate genetically across the entire genome, without evidence of intra-lineage reassortment. In contrast, Victoria-lineage diversity stems from geographic segregation of different genetic clades, with variability in the degree of geographic spread among clades. Differences between the lineages are reflected in their antigenic dynamics, as Yamagata-lineage viruses show alternating dominance between antigenic groups, while Victoria-lineage viruses show antigenic drift of a single lineage. Structural mapping of amino acid substitutions on trunk branches of influenza B gene phylogenies further supports these antigenic differences and highlights two potential mechanisms of adaptation for polymerase activity. Our study provides new insights into the epidemiological and molecular processes shaping influenza B virus evolution globally

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

Exploring Fold Space Preferences of New-born and Ancient Protein Superfamilies

The evolution of proteins is one of the fundamental processes that has delivered the diversity and complexity of life we see around ourselves today. While we tend to define protein evolution in terms of sequence level mutations, insertions and deletions, it is hard to translate these processes to a more complete picture incorporating a polypeptide's structure and function. By considering how protein structures change over time we can gain an entirely new appreciation of their long-term evolutionary dynamics. In this work we seek to identify how populations of proteins at different stages of evolution explore their possible structure space. We use an annotation of superfamily age to this space and explore the relationship between these ages and a diverse set of properties pertaining to a superfamily's sequence, structure and function. We note several marked differences between the populations of newly evolved and ancient structures, such as in their length distributions, secondary structure content and tertiary packing arrangements. In particular, many of these differences suggest a less elaborate structure for newly evolved superfamilies when compared with their ancient counterparts. We show that the structural preferences we report are not a residual effect of a more fundamental relationship with function. Furthermore, we demonstrate the robustness of our results, using significant variation in the algorithm used to estimate the ages. We present these age estimates as a useful tool to analyse protein populations. In particularly, we apply this in a comparison of domains containing greek key or jelly roll motifs

Multimodal Stimulation of Colorado Potato Beetle Reveals Modulation of Pheromone Response by Yellow Light

Orientation of insects to host plants and conspecifics is the result of detection and integration of chemical and physical cues present in the environment. Sensory organs have evolved to be sensitive to important signals, providing neural input for higher order multimodal processing and behavioral output. Here we report experiments to determine decisions made by Colorado potato beetle (CPB), Leptinotarsa decemlineata, in response to isolated stimuli and multimodal combinations of signals on a locomotion compensator. Our results show that in complete darkness and in the absence of other stimuli, pheromonal stimulation increases attraction behavior of CPB as measured in oriented displacement and walking speed. However, orientation to the pheromone is abolished when presented with the alternative stimulation of a low intensity yellow light in a dark environment. The ability of the pheromone to stimulate these diurnal beetles in the dark in the absence of other stimuli is an unexpected but interesting observation. The predominance of the phototactic response over that to pheromone when low intensity lights were offered as choices seems to confirm the diurnal nature of the insect. The biological significance of the response to pheromone in the dark is unclear. The phototactic response will play a key role in elucidating multimodal stimulation in the host-finding process of CPB, and perhaps other insects. Such information might be exploited in the design of applications to attract and trap CPB for survey or control purposes and other insect pests using similar orientation mechanisms