Design principles for riboswitch function

Scientific and technological advances that enable the tuning of integrated regulatory components to match network and system requirements are critical to reliably control the function of biological systems. RNA provides a promising building block for the construction of tunable regulatory components based on its rich regulatory capacity and our current understanding of the sequence–function relationship. One prominent example of RNA-based regulatory components is riboswitches, genetic elements that mediate ligand control of gene expression through diverse regulatory mechanisms. While characterization of natural and synthetic riboswitches has revealed that riboswitch function can be modulated through sequence alteration, no quantitative frameworks exist to investigate or guide riboswitch tuning. Here, we combined mathematical modeling and experimental approaches to investigate the relationship between riboswitch function and performance. Model results demonstrated that the competition between reversible and irreversible rate constants dictates performance for different regulatory mechanisms. We also found that practical system restrictions, such as an upper limit on ligand concentration, can significantly alter the requirements for riboswitch performance, necessitating alternative tuning strategies. Previous experimental data for natural and synthetic riboswitches as well as experiments conducted in this work support model predictions. From our results, we developed a set of general design principles for synthetic riboswitches. Our results also provide a foundation from which to investigate how natural riboswitches are tuned to meet systems-level regulatory demands

Human Health Risk Assessment (HHRA) for environmental development and transfer of antibiotic resistanc

This is the final version of the article. Available from NIEHS via the DOI in this record.Open access journalBACKGROUND: Only recently has the environment been clearly implicated in the risk of antibiotic resistance to clinical outcome, but to date there have been few documented approaches to formally assess these risks. OBJECTIVE: We examined possible approaches and sought to identify research needs to enable human health risk assessments (HHRA) that focus on the role of the environment in the failure of antibiotic treatment caused by antibiotic-resistant pathogens. METHODS: The authors participated in a workshop held 4-8 March 2012 in Québec, Canada, to define the scope and objectives of an environmental assessment of antibiotic-resistance risks to human health. We focused on key elements of environmental-resistance-development "hot spots," exposure assessment (unrelated to food), and dose response to characterize risks that may improve antibiotic-resistance management options. DISCUSSION: Various novel aspects to traditional risk assessments were identified to enable an assessment of environmental antibiotic resistance. These include a) accounting for an added selective pressure on the environmental resistome that, over time, allows for development of antibiotic-resistant bacteria (ARB); b) identifying and describing rates of horizontal gene transfer (HGT) in the relevant environmental "hot spot" compartments; and c) modifying traditional dose-response approaches to address doses of ARB for various health outcomes and pathways. CONCLUSIONS: We propose that environmental aspects of antibiotic-resistance development be included in the processes of any HHRA addressing ARB. Because of limited available data, a multicriteria decision analysis approach would be a useful way to undertake an HHRA of environmental antibiotic resistance that informs risk managers.This manuscript was conceived at a workshop (Antimicrobial Resistance in the Environment: Assessing and Managing Effects of Anthropogenic Activities) held 4–8 March 2012 in Montebello, Québec, Canada. The workshop was sponsored by the Canadian Society of Microbiologists, with financial support from AstraZeneca Ltd.; Pfizer Animal Health; F. Hoffman-La Roche Ltd.; GlaxoSmithKline; Unilever; Huvepharma; the American Cleaning Institute; the Canadian Animal Health Institute; the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety; Health Canada; and the Public Health Agency of Canada

Study of Bc+B_c^+ decays to the K+K−π+K^+K^-\pi^+ final state and evidence for the decay Bc+→χc0π+B_c^+\to\chi_{c0}\pi^+

A study of $B_c^+\to K^+K^-\pi^+$ decays is performed for the first time using data corresponding to an integrated luminosity of 3.0 $\mathrm{fb}^{-1}$ collected by the LHCb experiment in $pp$ collisions at centre-of-mass energies of $7$ and $8$ TeV. Evidence for the decay $B_c^+\to\chi_{c0}(\to K^+K^-)\pi^+$ is reported with a significance of 4.0 standard deviations, resulting in the measurement of $\frac{\sigma(B_c^+)}{\sigma(B^+)}\times\mathcal{B}(B_c^+\to\chi_{c0}\pi^+)$ to be $(9.8^{+3.4}_{-3.0}(\mathrm{stat})\pm 0.8(\mathrm{syst}))\times 10^{-6}$. Here $\mathcal{B}$ denotes a branching fraction while $\sigma(B_c^+)$ and $\sigma(B^+)$ are the production cross-sections for $B_c^+$ and $B^+$ mesons. An indication of $\bar b c$ weak annihilation is found for the region $m(K^-\pi^+)<1.834\mathrm{\,Ge\kern -0.1em V\!/}c^2$, with a significance of 2.4 standard deviations.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2016-022.html, link to supplemental material inserted in the reference

Effect of cattle genotype and feeding regime on greenhouse gas emissions intensity in high producing dairy cows

Improving milk production through livestock feeding and genetics is a promising approach for reducing greenhouse gas emissions (GHG) from dairy production systems. This study investigated emissions intensity, defined as the global warming potential (GWP) per unit energy corrected milk (ECM) output, of high-producing dairy systems. Objectives of this study were: to determine the effect of forage regime and cattle genetic line on GHG emissions from the life cycle of four directly comparable dairy production systems; to examine differences amongst contributing GHG emissions sources, and to identify key parameters contributing the most uncertainty in overall GWP. Life cycle analysis (LCA) was conducted based on seven years data collected from a long-term Holstein-Friesian genetic and management systems project. The four dairy production systems comprised two feeding regimes of High and Low Forage applied to each of two genetic lines. The Control line represented the average UK genetics and Select line representing the top 5% of UK genetics for milk fat and protein. Select genetic line animals managed under Low Forage regime was estimated to hold potential to reduce emissions intensity by 24% compared to Control genetic merit cows managed under a High Forage regime. Individually, improving genetic merit of the herd and implementing Low Forage regime hold potential to reduce emissions intensity by 9% and 16%, respectively. Key factors in the differences amongst systems were greater off-farm emissions under Low Forage regime, and greater on-farm nitrous oxide emissions associated with High Forage. In contrast to overall emissions, the emissions intensity was lower in Low Forage groups than in High Forage groups because of high milk yield in Low Forage groups. Six key parameters contained the greatest influence on uncertainty in results. These included: three Intergovernmental Panel on Climate Change (IPCC) coefficients concerning indirect emissions from volatilized nitrogen (EF4), direct nitrous oxide emissions from nitrogen input to soil (EF1), and emissions from direct deposition of excreta at pasture (EF3PRP); and three system-specific emissions factors for animals’ excreted nitrogen rate, enteric methane and manure methane. The coefficients EF4, EF1, and EF3PRP should be prioritized for better definition in order to minimize uncertainty in future studies

Observation of Bc+ →j /ψD (∗)K (∗) decays

A search for the decays B+c→J/ψD(*)0K+ and B+c→J/ψD(*)+K*0 is performed with data collected at the LHCb experiment corresponding to an integrated luminosity of 3 fb−1. The decays B+c→J/ψ0K+ and B+c→J/ψD*0K+ are observed for the first time, while first evidence is reported for the B+c→JψD*+K*0 and B+c→J/ψD+K*0 decays. The branching fractions of these decays are determined relative to the B+c→J/ψπ+ decay. The B+c mass is measured, using the J/ψD0K+ final state, to be 6274.28±1.40(stat)±0.32(syst) MeV/c2. This is the most precise single measurement of the B+c mass to date

Global, regional, and national incidence, prevalence, and mortality of HIV, 1980–2017, and forecasts to 2030, for 195 countries and territories: a systematic analysis for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017

Background Understanding the patterns of HIV/AIDS epidemics is crucial to tracking and monitoring the progress of prevention and control efforts in countries. We provide a comprehensive assessment of the levels and trends of HIV/AIDS incidence, prevalence, mortality, and coverage of antiretroviral therapy (ART) for 1980–2017 and forecast these estimates to 2030 for 195 countries and territories. Methods We determined a modelling strategy for each country on the basis of the availability and quality of data. For countries and territories with data from population-based seroprevalence surveys or antenatal care clinics, we estimated prevalence and incidence using an open-source version of the Estimation and Projection Package—a natural history model originally developed by the UNAIDS Reference Group on Estimates, Modelling, and Projections. For countries with cause-specific vital registration data, we corrected data for garbage coding (ie, deaths coded to an intermediate, immediate, or poorly defined cause) and HIV misclassification. We developed a process of cohort incidence bias adjustment to use information on survival and deaths recorded in vital registration to back-calculate HIV incidence. For countries without any representative data on HIV, we produced incidence estimates by pulling information from observed bias in the geographical region. We used a re-coded version of the Spectrum model (a cohort component model that uses rates of disease progression and HIV mortality on and off ART) to produce age-sex-specific incidence, prevalence, and mortality, and treatment coverage results for all countries, and forecast these measures to 2030 using Spectrum with inputs that were extended on the basis of past trends in treatment scale-up and new infections. Findings Global HIV mortality peaked in 2006 with 1·95 million deaths (95% uncertainty interval 1·87–2·04) and has since decreased to 0·95 million deaths (0·91–1·01) in 2017. New cases of HIV globally peaked in 1999 (3·16 million, 2·79–3·67) and since then have gradually decreased to 1·94 million (1·63–2·29) in 2017. These trends, along with ART scale-up, have globally resulted in increased prevalence, with 36·8 million (34·8–39·2) people living with HIV in 2017. Prevalence of HIV was highest in southern sub-Saharan Africa in 2017, and countries in the region had ART coverage ranging from 65·7% in Lesotho to 85·7% in eSwatini. Our forecasts showed that 54 countries will meet the UNAIDS target of 81% ART coverage by 2020 and 12 countries are on track to meet 90% ART coverage by 2030. Forecasted results estimate that few countries will meet the UNAIDS 2020 and 2030 mortality and incidence targets. Interpretation Despite progress in reducing HIV-related mortality over the past decade, slow decreases in incidence, combined with the current context of stagnated funding for related interventions, mean that many countries are not on track to reach the 2020 and 2030 global targets for reduction in incidence and mortality. With a growing population of people living with HIV, it will continue to be a major threat to public health for years to come. The pace of progress needs to be hastened by continuing to expand access to ART and increasing investments in proven HIV prevention initiatives that can be scaled up to have population-level impact

A study of the Z production cross-section in pp collisions at √s = 7 using tau final states

A measurement of the inclusive Z → ττ cross-section in pp collisions at √s =7 is presented based on a dataset of 1.0 fb[superscript −1] collected by the LHCb detector. Candidates for Z → τ τ decays are identified through reconstructed final states with two muons, a muon and an electron, a muon and a hadron, or an electron and a hadron. The production cross-section for Z bosons, with invariant mass between 60 and 120 GeV/c[superscript 2], which decay to τ leptons with transverse momenta greater than 20 GeV/c and pseudorapidities between 2.0 and 4.5, is measured to be σ[subscript pp]→Z→ττ = 71.4 ± 3.5 ± 2.8 ± 2.5 pb; the first uncertainty is statistical, the second is systematic, and the third is due to the uncertainty on the integrated luminosity. The ratio of the cross-sections for Z → τ τ to Z → μμ is determined to be 0.93 ± 0.09, where the uncertainty is the combination of statistical, systematic, and luminosity uncertainties of the two measurements.National Science Foundation (U.S.

Immune correlates of CD4 decline in HIV-infected patients experiencing virologic failure before undergoing treatment interruption

<p>Abstract</p> <p>Background</p> <p>The advantage of treatment interruptions (TIs) in salvage therapy remains controversial. Regardless, characterizations of the correlates of CD4 count fall during TI are important to identify since patients with virologic failure commonly stop antiretroviral (ARV) therapy. The objective of this study was to determine the predictive value of pre-TI proliferative capacity and cell surface markers for CD4 count change in HIV-infected patients experiencing virologic failure before undergoing TI.</p> <p>Methods</p> <p>Peripheral blood mononuclear cells (PBMCs) from 13 HIV-infected patients experiencing virologic failure at baseline time points before the TI were tested for proliferation using the 5,6-carboxyfluorescein diacetate succinimidyl ester (CFSE) dilution assay and a Gag p55 peptide pool, staphylococcus enterotoxin B (SEB), cytomegalovirus (CMV) recall antigen, and anti-CD3 antibody as stimuli. CD28 and CD57 expression on CD4+ and CD8+ T-cells was measured.</p> <p>Results</p> <p>The median changes in the CD4+ T-cell count and viral load from baseline to the TI time point corresponding to the CD4 count nadir were -44 cells/mm³{Interquartile range (IQR) -17, -104} and +85,332 copies/mL (IQR +11,198, +283,327), respectively. CD4+ T-cell proliferation to CMV, pre-TI CD4+ T-cell count, and percent CD4+CD57+ cells correlated negatively with CD4 count change during TI (r = -0.59, p = 0.045, r = -0.61, p = 0.030 and r = -0.69, p = 0.0095, respectively; Spearman correlation). The presence of HIV-specific proliferative responses was not associated with a reduced decline in CD4 count during TI.</p> <p>Conclusion</p> <p>The use of pre-TI immune proliferative responses and cell surface markers may have predictive value for CD4 count decline during TI.</p

Precision measurement of the B0s-B¯0s oscillation frequency with the decay B0s → D−sπ+

A key ingredient to searches for physics beyond the Standard Model in B0s mixing phenomena is the measurement of the B0s– ${{\overline{ {\mathrm {B}}}{}}^0_{\mathrm { s}}}$ oscillation frequency, which is equivalent to the mass difference Δms of the B0s mass eigenstates. Using the world's largest B0s meson sample accumulated in a dataset, corresponding to an integrated luminosity of 1.0 fb−1, collected by the LHCb experiment at the CERN LHC in 2011, a measurement of Δms is presented. A total of about 34 000 B0s → D−sπ+ signal decays are reconstructed, with an average decay time resolution of 44 fs. The oscillation frequency is measured to be Δms = 17.768 ± 0.023 (stat) ± 0.006 (syst) ps−1, which is the most precise measurement to date