Explore the vast range of titles available.

The compatibility of W -boson mass measurements performed by the ATLAS, LHCb, CDF, and D0 experiments is studied using a coherent framework with theory uncertainty correlations. The measurements are combined using a number of recent sets of parton distribution functions (PDF), and are further combined with the average value of measurements from the Large Electron–Positron collider. The considered PDF sets generally have a low compatibility with a suite of global rapidity-sensitive Drell–Yan measurements. The most compatible set is CT18 due to its larger uncertainties. A combination of all m W measurements yields a value of m W = 80 , 394.6 ± 11.5  MeV with the CT18 set, but has a probability of compatibility of 0.5% and is therefore disfavoured. Combinations are performed removing each measurement individually, and a 91% probability of compatibility is obtained when the CDF measurement is removed. The corresponding value of the W boson mass is 80 , 369.2 ± 13.3  MeV, which differs by 3.6 σ from the CDF value determined using the same PDF set.

Adverse effects of prenatal stress or environmental chemical exposures on fetal growth are well described, yet their combined effect remains unclear. To conduct a systematic review on the combined impact and interaction of prenatal exposure to stress and chemicals on developmental outcomes. We used the first three steps of the Navigation Guide systematic review. We wrote a protocol, performed a robust literature search to identify relevant animal and human studies and extracted data on developmental outcomes. For the most common outcome (fetal growth), we evaluated risk of bias, calculated effect sizes for main effects of individual and combined exposures, and performed a random effects meta-analysis of those studies reporting on odds of low birthweight (LBW) by smoking and socioeconomic status (SES). We identified 17 human- and 22 animal-studies of combined chemical and stress exposures and fetal growth. Human studies tended to have a lower risk of bias across nine domains. Generally, we found stronger effects for chemicals than stress, and these exposures were associated with reduced fetal growth in the low-stress group and the association was often greater in high stress groups, with limited evidence of effect modification. We found smoking associated with significantly increased odds of LBW, with a greater effect for high stress (low SES; OR 4.75 (2.46-9.16)) compared to low stress (high SES; OR 1.95 (95% CI 1.53-2.48)). Animal studies generally had a high risk of bias with no significant combined effect or effect modification. We found that despite concern for the combined effects of environmental chemicals and stress, this is still an under-studied topic, though limited available human studies indicate chemical exposures exert stronger effects than stress, and this effect is generally larger in the presence of stress.

Beauty and charm quarks are ideal probes of pertubative Quantum Chromodymanics in proton–proton collisions, owing to their large masses. In this paper the role of multi-parton interactions in the production of doubly-heavy hadrons is studied using simulation samples generated with Pythia, a Monte Carlo event generator. Comparisons are made to the stand-alone generators BcVegPy and GenXicc. New methods of speeding up Pythia simulations for events containing heavy quarks are described, enabling the production of large samples with multiple heavy-quark pairs. We show that significantly higher production rates of doubly-heavy hadrons are predicted in models that allow heavy quarks originating from different parton–parton interactions (within the same hadron–hadron collision) to combine to form such hadrons. Quantitative predictions are sensitive to the modelling of colour reconnections. We suggest a set of experimental measurements capable of differentiating these additional contributions.

A bstract It is well known that in b -hadron decays with a single unreconstructible final state particle, the decay kinematics can be solved up to a quadratic ambiguity, without any knowledge of the b -hadron momentum. We present a method to infer the momenta of b -hadrons produced in hadron collider experiments using information from their reconstructed flight vectors. Our method is strictly agnostic to the decay itself, which implies that it can be validated with control samples of topologically similar decays to fully reconstructible final states. A multivariate regression algorithm based on the flight information provides a b -hadron momentum estimate with a resolution of around 60% which is sufficient to select the correct solution to the quadratic equation in around 70% of cases. This will improve the ability of hadron collider experiments to make differential decay rate measurements with semileptonic b -hadron decays.

Addressing critical global health issues, such as antimicrobial resistance, infectious disease outbreaks, and natural disasters, requires strong coordination and management across sectors. The One Health approach is the integrative effort of multiple sectors working to attain optimal health for people, animals, and the environment, and is increasingly recognized by experts as a means to address complex challenges. However, practical application of the One Health approach has been challenging. The One Health Systems Mapping and Analysis Resource Toolkit (OH-SMART) introduced in this paper was designed using a multistage prototyping process to support systematic improvement in multi-sectoral coordination and collaboration to better address complex health concerns through an operational, stepwise, and practical One Health approach. To date, OH-SMART has been used to strengthen One Health systems in 17 countries and has been deployed to revise emergency response frameworks, improve antimicrobial resistance national action plans and create multi agency infectious disease collaboration protocols. OH-SMART has proven to be user friendly, robust, and capable of fostering multi-sectoral collaboration and complex system-wide problem solving.

Background: Malignant glioma is an aggressive tumour commonly associated with a dismal outcome despite optimal surgical and radio-chemotherapy. Since 2005 temozolomide has been established as first-line chemotherapy. We investigate the role of in vivo glioma models in predicting clinical efficacy. Methods: We searched three online databases to systematically identify publications testing temozolomide in animal models of glioma. Median survival and number of animals treated were extracted and quality was assessed using a 12-point scale; random effects meta-analysis was used to estimate efficacy. We analysed the impact of study design and quality and looked for evidence of publication bias. Results: We identified 60 publications using temozolomide in models of glioma, comprising 2443 animals. Temozolomide prolonged survival by a factor of 1.88 (95% CI 1.74–2.03) and reduced tumour volume by 50.4% (41.8–58.9) compared with untreated controls. Study design characteristics accounted for a significant proportion of between-study heterogeneity, and there was evidence of a significant publication bias. Conclusion: These data reflect those from clinical trials in that temozolomide improves survival and reduces tumour volume, even after accounting for publication bias. Experimental in vivo glioma studies of temozolomide differ from those of other glioma therapies in their consistent efficacy and successful translation into clinical medicine.

To develop and implement an evidence based framework to select, from drugs already licenced, candidate oral neuroprotective drugs to be tested in secondary progressive multiple sclerosis. Systematic review of clinical studies of oral putative neuroprotective therapies in MS and four other neurodegenerative diseases with shared pathological features, followed by systematic review and meta-analyses of the in vivo experimental data for those interventions. We presented summary data to an international multi-disciplinary committee, which assessed each drug in turn using pre-specified criteria including consideration of mechanism of action. We identified a short list of fifty-two candidate interventions. After review of all clinical and pre-clinical evidence we identified ibudilast, riluzole, amiloride, pirfenidone, fluoxetine, oxcarbazepine, and the polyunsaturated fatty-acid class (Linoleic Acid, Lipoic acid; Omega-3 fatty acid, Max EPA oil) as lead candidates for clinical evaluation. We demonstrate a standardised and systematic approach to candidate identification for drug rescue and repurposing trials that can be applied widely to neurodegenerative disorders.

Background: In other neurological diseases, the failure to translate pre-clinical findings to effective clinical treatments has been partially attributed to bias introduced by shortcomings in the design of animal experiments. Objectives: Here we evaluate published studies of interventions in animal models of multiple sclerosis for methodological design and quality and to identify candidate interventions with the best evidence of efficacy. Methods: A systematic review of the literature describing experiments testing the effectiveness of interventions in animal models of multiple sclerosis was carried out. Data were extracted for reported study quality and design and for neurobehavioural outcome. Weighted mean difference meta-analysis was used to provide summary estimates of the efficacy for drugs where this was reported in five or more publications. Results: The use of a drug in a pre-clinical multiple sclerosis model was reported in 1152 publications, of which 1117 were experimental autoimmune encephalomyelitis (EAE). For 36 interventions analysed in greater detail, neurobehavioural score was improved by 39.6% (95% CI 34.9—44.2%, p < 0.001). However, few studies reported measures to reduce bias, and those reporting randomization or blinding found significantly smaller effect sizes. Conclusions: EAE has proven to be a valuable model in elucidating pathogenesis as well as identifying candidate therapies for multiple sclerosis. However, there is an inconsistent application of measures to limit bias that could be addressed by adopting methodological best practice in study design. Our analysis provides an estimate of sample size required for different levels of power in future studies and suggests a number of interventions for which there are substantial animal data supporting efficacy.

In future measurements of the dilepton ( Z / γ ∗ ) transverse momentum, Q T , at both the Tevatron and LHC, the achievable bin widths and the ultimate precision of the measurements will be limited by experimental resolution rather than by the available event statistics. In a recent paper the variable a T , which corresponds to the component of Q T that is transverse to the dilepton thrust axis, has been studied in this regard. In the region, Q T < 30 GeV, a T has been shown to be less susceptible to experimental resolution and efficiency effects than the Q T . Extending over all Q T , we now demonstrate that dividing a T (or Q T ) by the measured dilepton invariant mass further improves the resolution. In addition, we propose a new variable, , that is determined exclusively from the measured lepton directions; this is even more precisely determined experimentally than the above variables and is similarly sensitive to the Q T . The greater precision achievable using such variables will enable more stringent tests of QCD and tighter constraints on Monte Carlo event generator tunes.

Large-scale atmospheric models, which typically describe secondary organic aerosol (SOA) formation based on chamber experiments, tend to systematically underestimate observed organic aerosol burdens. Since SOA constitutes a significant fraction of atmospheric aerosol, this discrepancy translates into an underestimation of SOA contribution to radiative forcing of atmospheric aerosol. Here we show that the underestimation of SOA yields can be partly explained by wall losses of SOA forming compounds during chamber experiments. We present a chamber experiment where α-pinene and ozone are injected into a Teflon chamber. When these two compounds react, we observe rapid formation and growth of new particles. Theoretical analysis of this formation and growth event indicates rapid formation of oxidized volatile organic compounds (OVOC) of very low volatility in the chamber. If these oxidized organic compounds form in the gas phase, their wall losses will have significant implications on their partitioning between the gas and particle phase. Although these OVOCs of very low volatility contribute to the growth of new particles, their mass will almost completely be depleted to the chamber walls during the experiment, while the depletion of OVOCs of higher volatilities is less efficient. According to our model simulations, the volatilities of OVOC contributing to the new particle formation event can be of the order of 10−5 μg m−3.