Feasibility and Acceptability of a Multifaceted Observational Protocol to Investigate Lucidity in Advanced Dementia

OBJECTIVE

Episodes of lucidity (ELs), characterized by spontaneous, transient recovery of abilities, are reported across neurological conditions, including advanced dementia. Despite the significance of these events, existing research is limited to retrospective reports. Approaches to prospectively capturing and characterizing ELs in dementia are lacking.

METHODS

This pilot study determined the feasibility and acceptability of a multifaceted observational protocol to capture, characterize, and validate ELs in individuals with advanced dementia in hospice. Feasibility was measured through enrollment/retention rates, workload/usability assessment of video observation, and data processing procedures to facilitate the measurement of verbal and nonverbal features for EL characterization. The acceptability of observation and informant validation procedures was qualitatively examined with clinician and family caregiver participants.

RESULTS

Study procedures were endorsed as highly acceptable among clinician (N = 49) and caregiver (N = 16) participants, demonstrating higher than anticipated thresholds for observation duration. Enrollment and retention rates for patient participants (N = 6) were 100% and 84%, respectively. Workload and usability measures demonstrated low disruptiveness and high ease of use after training.

DISCUSSION

Longitudinal video observation among individuals with advanced dementia in hospice care for the detection of lucidity was feasible and highly acceptable. Multidimensional, temporal coding of features of ELs is feasible but time-intensive.

Methane Emissions Show Recent Decline but Strong Seasonality in Two US Northeastern Cities

Urban methane emissions estimated using atmospheric observations have been found to exceed estimates derived by using traditional inventory methods in several northeastern US cities. In this work, we leveraged a nearly five-year record of observations from a dense tower network coupled with a newly developed high-resolution emissions map to quantify methane emission rates in Washington, DC, and Baltimore, Maryland. Annual emissions averaged over 2018-2021 were 80.1 [95% CI: 61.2, 98.9] Gg in the Washington, DC urban area and 47.4 [95% CI: 35.9, 58.5] Gg in the Baltimore urban area, with a decreasing trend of approximately 4-5% per year in both cities. We also find wintertime emissions 44% higher than summertime emissions, correlating with natural gas consumption. We further attribute a large fraction of total methane emissions to the natural gas sector using a least-squares regression on our spatially resolved estimates, supporting previous findings that natural gas systems emit the plurality of methane in both cities. This study contributes to the relatively sparse existing knowledge base of urban methane emissions sources and variability, adding to our understanding of how these emissions change in time and providing evidence to support efforts to mitigate natural gas emissions.

Anti-HEV seroprevalence and rate of viremia in a German cohort of dogs, cats, and horses

Hepatitis E virus (HEV) genotype 3 infections in Germany are mainly transmitted zoonotically through the consumption of swine meat. Furthermore, there is evidence that pets might come into contact with HEV, but the relevance of companion animals as possible sources of HEV transmission in Germany still needs to be defined. A monitoring study was therefore carried out on dogs, cats, and horses from Germany. In total 365 serum samples from pets (124 dogs, 119 cats, and 122 horses) were tested for HEV by PCR and for anti-HEV antibodies by a commercial ELISA. The HEV seroprevalence determined by the sero-assay varied significantly between dogs (10%), cats (6%), and horses (2%). Liver injury-related enzymes, alanine transaminase (ALT), and aspartate transaminase (AST) showed no differences between HEV-positive or negative animals. None of the pet serum samples tested positive for PCR. This serological study suggests that dogs and cats are significantly exposed to HEV in Germany, while horses are of minor relevance.

Associations between self-reported sleep patterns and health, cognition and amyloid measures: results from the Wisconsin Registry for Alzheimer's Prevention

Previous studies suggest associations between self-reported sleep problems and poorer health, cognition, Alzheimer's disease pathology and dementia-related outcomes. It is important to develop a deeper understanding of the relationship between these complications and sleep disturbance, a modifiable risk factor, in late midlife, a time when Alzheimer's disease pathology may be accruing. The objectives of this study included application of unsupervised machine learning procedures to identify distinct subgroups of persons with problematic sleep and the association of these subgroups with concurrent measures of mental and physical health, cognition and PET-identified amyloid. Dementia-free participants from the Wisconsin Registry for Alzheimer's Prevention (n = 619) completed sleep questionnaires including the Insomnia Severity Index, Epworth Sleepiness Scale and Medical Outcomes Study Sleep Scale. K-means clustering analysis identified discrete sleep problem groups who were then compared across concurrent health outcomes (e.g. depression, self-rated health and insulin resistance), cognitive composite indices including episodic memory and executive function and, in a subset, Pittsburgh Compound B PET imaging to assess amyloid burden. Significant omnibus tests (P < 0.05) were followed with pairwise comparisons. Mean (SD) sample baseline sleep assessment age was 62.6 (6.7). Cluster analysis identified three groups: healthy sleepers [n = 262 (42.3%)], intermediate sleepers [n = 229 (37.0%)] and poor sleepers [n = 128 (20.7%)]. All omnibus tests comparing demographics and health measures across sleep groups were significant except for age, sex and apolipoprotein E e4 carriers; the poor sleepers group was worse than one or both of the other groups on all other measures, including measures of depression, self-reported health and memory complaints. The poor sleepers group had higher average body mass index, waist-hip ratio and homeostatic model assessment of insulin resistance. After adjusting for covariates, the poor sleepers group also performed worse on all concurrent cognitive composites except working memory. There were no differences between sleep groups on PET-based measures of amyloid. Sensitivity analyses indicated that while different clustering approaches resulted in different group assignments for some (predominantly the intermediate group), between-group patterns in outcomes were consistent. In conclusion, distinct sleep characteristics groups were identified with a sizable minority (20.7%) exhibiting poor sleep characteristics, and this group also exhibited the poorest concurrent mental and physical health and cognition, indicating substantial multi-morbidity; sleep group was not associated with amyloid PET estimates. Precision-based management of sleep and related factors may provide an opportunity for early intervention that could serve to delay or prevent clinical impairment.

FEASIBILITY OF A LONGITUDINAL AUDIOVISUAL OBSERVATION PROTOCOL TO CHARACTERIZE LUCIDITY IN ADVANCED AD/ADRD

Episodes of lucidity (EL) among individuals with advanced dementia, which are predominantly reported near end of life, are clinically and potentially epidemiologically significant events. Audiovisual observation offers a valuable approach to studying EL, providing opportunities to characterize verbal/non-verbal features of EL as well as their surrounding contexts. Approaches to capturing and characterizing audiovisual data and potential verbal/non-verbal indicators of EL near end of life are lacking. We determined the acceptability and feasibility of a multi-faceted observational study protocol among people with advanced dementia near end of life incorporating longitudinal audiovisual observation, informant field interviews/logs, and case review of high likelihood EL events. Five eligible individuals were enrolled, yielding a 100% enrollment/retention rate, 54 observations/140 hours of observation across participants. Task load and usability ratings indicate study procedures with iterative refinements were feasible; surveys and qualitative appraisal from participants and staff endorse high rates of acceptability and feasibility.

APPROACHES TO INVESTIGATING LUCIDITY IN ADRD: A PRELIMINARY RESEARCH FRAMEWORK TO GUIDE OPERATIONAL HARMONIZATION

Episodes of lucidity (EL) in Alzheimer’s disease and Alzheimer’s disease related dementias (AD/ADRD), also termed “paradoxical lucidity,” have garnered increasing attention as an important area of research. Efforts to study lucidity suffer from a lack of clear definitional criteria, inconsistent conceptualization and diverse approaches to operationalizing features of these events. To advance systematic investigation of EL in AD/ADRD, there is a need for clarity and precision in labeling event attributes, markers, and specific measurement strategies that enable operational harmonization across distinct approaches to investigating the relatively broad and nascent phenomenon. To that end, we propose a preliminary research framework to guide harmonization of approaches to investigating EL in AD/ADRD. Our goal is to provide a systematized approach to characterizing operational decisions that facilitates comparability across different methodological approaches and measurement strategies while allowing for exploration of multiple definitional criteria, measurement standards, and interpretive approaches.

Automated semantic relevance as an indicator of cognitive decline: Out-of-sample validation on a large-scale longitudinal dataset

We developed and evaluated an automatically extracted measure of cognition (semantic relevance) using automated and manual transcripts of audio recordings from healthy and cognitively impaired participants describing the Cookie Theft picture from the Boston Diagnostic Aphasia Examination. We describe the rationale and metric validation. We developed the measure on one dataset and evaluated it on a large database (>2000 samples) by comparing accuracy against a manually calculated metric and evaluating its clinical relevance. The fully automated measure was accurate (r = .84), had moderate to good reliability (intra-class correlation = .73), correlated with Mini-Mental State Examination and improved the fit in the context of other automatic language features (r = .65), and longitudinally declined with age and level of cognitive impairment. This study demonstrates the use of a rigorous analytical and clinical framework for validating automatic measures of speech, and applied it to a measure that is accurate and clinically relevant.

Accounting for Transport Error in Inversions: An Urban Synthetic Data Experiment

We present and discuss the use of a high-dimensional computational method for atmospheric inversions that incorporates the space-time structure of transport and dispersion errors. In urban environments, transport and dispersion errors are largely the result of our inability to capture the true underlying transport of greenhouse gas (GHG) emissions to observational sites. Motivated by the impact of transport model error on estimates of fluxes of GHGs using in situ tower-based mole-fraction observations, we specifically address the need to characterize transport error structures in high-resolution large-scale inversion models. We do this using parametric covariance functions combined with shrinkage-based regularization methods within an Ensemble Transform Kalman Filter inversion setup. We devise a synthetic data experiment to compare the impact of transport and dispersion error component of the model-data mismatch covariance choices on flux retrievals and study the robustness of the method with respect to fewer observational constraints. We demonstrate the analysis in the context of inferring CO2 fluxes starting with a hypothesized prior in the Washington D.C. /Baltimore area constrained by a synthetic set of tower-based CO2 measurements within an observing system simulation experiment framework. This study demonstrates the ability of these simple covariance structures to substantially improve the estimation of fluxes over standard covariance models in flux estimation from urban regions.

The Impact of COVID-19 on CO2 Emissions in the Los Angeles and Washington DC/Baltimore Metropolitan Areas

Responses to COVID-19 have resulted in unintended reductions of city-scale carbon dioxide (CO2) emissions. Here, we detect and estimate decreases in CO2 emissions in Los Angeles and Washington DC/Baltimore during March and April 2020. We present three lines of evidence using methods that have increasing model dependency, including an inverse model to estimate relative emissions changes in 2020 compared to 2018 and 2019. The March decrease (25%) in Washington DC/Baltimore is largely supported by a drop in natural gas consumption associated with a warm spring whereas the decrease in April (33%) correlates with changes in gasoline fuel sales. In contrast, only a fraction of the March (17%) and April (34%) reduction in Los Angeles is explained by traffic declines. Methods and measurements used herein highlight the advantages of atmospheric CO2 observations for providing timely insights into rapidly changing emissions patterns that can empower cities to course-correct CO2 reduction activities efficiently.

Under-reporting of greenhouse gas emissions in U.S. cities

Cities dominate greenhouse gas emissions. Many have generated self-reported emission inventories, but their value to emissions mitigation depends on their accuracy, which remains untested. Here, we compare self-reported inventories from 48 US cities to independent estimates from the Vulcan carbon dioxide emissions data product, which is consistent with atmospheric measurements. We found that cities under-report their own greenhouse gas emissions, on average, by 18.3% (range: -145.5% to +63.5%) - a difference which if extrapolated to all U.S. cities, exceeds California's total emissions by 23.5%. Differences arise because city inventories omit particular fuels and source types and estimate transportation emissions differently. These results raise concerns about self-reported inventories in planning or assessing emissions, and warrant consideration of the new urban greenhouse gas information system recently developed by the scientific community.

Background conditions for an urban greenhouse gas network in the Washington, D.C. and Baltimore metropolitan region

As city governments take steps towards establishing emissions reduction targets, the atmospheric research community is increasingly able to assist in tracking emissions reductions. Researchers have established systems for observing atmospheric greenhouse gases in urban areas with the aim of attributing greenhouse gas concentration enhancements (and thus, emissions) to the region in question. However, to attribute enhancements to a particular region, one must isolate the component of the observed concentration attributable to fluxes inside the region by removing the background, which is the component due to fluxes outside. In this study, we demonstrate methods to construct several versions of a background for our carbon dioxide and methane observing network in the Washington, DC and Baltimore, MD metropolitan region. Some of these versions rely on transport and flux models, while others are based on observations upwind of the domain. First, we evaluate the backgrounds in a synthetic data framework, then we evaluate against real observations from our urban network. We find that backgrounds based on upwind observations capture the variability better than model-based backgrounds, although care must be taken to avoid bias from biospheric carbon dioxide fluxes near background stations in summer. Model-based backgrounds also perform well when upwind fluxes can be modeled accurately. Our study evaluates different background methods and provides guidance determining background methodology that can impact the design of urban monitoring networks.

Examination of Advanced Function and Its Correlates in a Cohort of Community-Dwelling Older Adults

Function in older adults includes multiple domains, from basic to “advanced,” but we remain limited in detection of advanced function (engagement in social, leisure, and productive activities). The objective is to describe advanced function and examine relationships with basic function and health outcomes in community-dwelling older adults aged 55-65 years. This is an analysis of existing data from a large, ongoing cohort study, The Wisconsin Registry for Alzheimer’s Prevention (WRAP R01 AG027161). We used a 1:1 prospective case–control design to examine whether older adults with lower advanced function (lower functioning group) at wave 3 showed lower IADLs and poorer health outcomes in wave 4, compared to those with higher advanced function (higher functioning group). The lower functioning group had a mean advanced function score of 74.4 (SD = 10.1), compared to 98.7 (SD = 11.1) in the higher functioning group. The mean IADL scores were similar in the two groups (p = 0.123). The lower functioning group had significantly lower self-rated health (mean = 3.52; SD = .79) than higher functioning group (3.70; 0.79) and a significantly lower proportion of individuals with unimpaired, stable cognition (77%) than the higher functioning group (85%). The lower functioning group had higher rates of comorbidities (4.25 vs. 3.96), mortality (4 vs. 1), and depressive symptoms (CES-D: 7.17 vs. 6.09), although results were not significant at α=0.05. This study provides a foundation for examining advanced function, which may be an early indicator of poor health outcomes in older adults.

Interrater Reliability in the Measurement of Flow Characteristics on Color-Coded Quantitative DSA of Brain AVMs

BACKGROUND AND PURPOSE

Hemodynamic features of brain AVMs may portend increased hemorrhage risk. Previous studies have suggested that MTT is shorter in ruptured AVMs as assessed on quantitative color-coded parametric DSA. This study assesses the interrater reliability of MTT measurements obtained using quantitative color-coded DSA.

MATERIALS AND METHODS

Thirty-five color-coded parametric DSA images of 34 brain AVMs were analyzed by 4 neuroradiologists with experience in interventional neuroradiology. Hemodynamic features assessed included MTT of the AVM and TTP of the dominant feeding artery and draining vein. Agreement among the 4 raters was assessed using the intraclass correlation coefficient.

RESULTS

The interrater reliability among the 4 raters was poor (intraclass correlation coefficient = 0.218; 95% CI, 0.062-0.414; P value = .002) as it related to MTT assessment. When the analysis was limited to cases in which the raters selected the same image to analyze and selected the same primary feeding artery and the same primary draining vein, interrater reliability improved to fair (intraclass correlation coefficient  = 0.564; 95% CI, 0.367-0.717; P < .001).

CONCLUSIONS

Interrater reliability in deriving color-coded parametric DSA measurements such as MTT is poor so minor differences among raters may result in a large variance in MTT and TTP results, partly due to the sensitivity and 2D nature of the technique. Reliability can be improved by defining a standard projection, feeding artery, and draining vein for analysis.

Case report of a cervical myelomalacia caused by a thoracolumbar intradural disc herniation leading to intracranial hypotension

A 50-year-old patient was admitted with symptoms of intracranial hypotension. MRI revealed a cervical myelomalacia caused by engorged epidural veins leading to a stenosis of the spinal canal. This condition is rarely described in patients with hydrocephalus and ventricular shunts suffering from chronic overdrainage. However, the reason in this patient was a CSF leak caused by an intradural disc herniation at T12/L1. After surgery, symptoms resolved and the cervical myelomalacia and the swollen epidural veins disappeared on postoperative MRI. In patients with engorged cervical epidural veins without a ventricular shunt, a CSF leak has to be considered.

Seasonally Resolved Excess Urban Methane Emissions from the Baltimore/Washington, DC Metropolitan Region

Urban areas are increasingly recognized as an important source of methane (CH₄), but we have limited seasonally resolved observations of these regions. In this study, we quantify seasonal and annual urban CH₄ emissions over the Baltimore, Maryland, and Washington, DC metropolitan regions. We use CH₄ atmospheric observations from four tall tower stations and a Lagrangian particle dispersion model to simulate CH₄ concentrations at these stations. We directly compare these simulations with observations and use a geostatistical inversion method to determine optimal emissions to match our observations. We use observations spanning four seasons and employ an ensemble approach considering multiple meteorological representations, emission inventories, and upwind CH₄ values. Forward simulations in winter, spring, and fall underestimate observed atmospheric CH₄ while in summer, simulations overestimate observations because of excess modeled wetland emissions. With ensemble geostatistical inversions, the optimized annual emissions in DC/Baltimore are 39 ± 9 Gg/month (1 δ), 2.0 ± 0.4 times higher than the ensemble mean of bottom-up emission inventories. We find a modest seasonal variability of urban CH₄ emissions not captured in current inventories, with optimized summer emissions ∼41% lower than winter, broadly consistent with expectations if emissions are dominated by fugitive natural gas sources that correlate with natural gas usage.

P3641Matrix Metalloproteinase-2 polymorphisms are associated with prognosis of patients with symptomatic coronary artery disease

Background

Matrix Metalloproteinase-2 (MMP-2) is involved in regulation and proliferation of vascular and endothelial cells and is therefore an important component of atherosclerotic vessels. Inhibition of MMP-2 activity is associated with improvement of cardiac function in animal models after myocardial infarction. MMP-2 single nucleotide polymorphisms (SNPs) might alter MMP-2 expression and therefore influence prognosis in patients with symptomatic coronary artery disease (CAD).

Methods and results

Genotyping for selected MMP-2 SNPs variants (rs2241145, rs2285053, rs2287076, rs243865, rs7201) was performed in 943 consecutive patients with symptomatic CAD. All patients were followed-up for all-cause death (ACD), myocardial infarction (MI) and ischemic stroke (IS) for 360 days. The primary combined endpoint (CE) consisted of either first occurrence of ACD, and/or MI, and/or IS. Secondary endpoints were defined as the single events of ACD or MI. Homozygous carriers of major allele (rs2241145, rs2287076) showed significantly better event-free survival than carriers of the minor allele for CE (Log rank = 0.022 and Log rank= 0.015, respectively). Furthermore, homozygous carriers of major allele (rs2241145, rs2285053, rs2287076) showed significantly better event-free survival for ACD (Log rank= 0.047, Log rank= 0.006 and Log rank= 0.023, respectively). In multivariate analysis, MMP-2 rs2241145, rs2287076 and rs2285053 were significantly and independently associated with CE and ACD.

Figure 1

Conclusions

MMP-2 rs2241145, rs2287076 and rs2285053 are associated with prognosis and might be valuable for further risk stratification in CAD patients.

Acknowledgement/Funding

DFG, KFO 274, CRC TR 240

P3643Junctional Adhesion Molecule-A (JAM-A) polymorphisms influence serum levels of soluble JAM-A and are associated with long term prognosis in coronary artery disease

Aims

Junctional adhesion molecule A (JAM-A/F11R) is a cell adhesion molecule. Membrane associated JAM-A mediates platelet aggregation, secretion, adhesion, and spreading. Plasma levels of JAM-A are elevated in hypertension and atherosclerosis. This study was designed to investigate the impact of JAM-A single nucleotide polymorphisms (SNPs) on circulatory JAM-A levels and prognosis in patients with symptomatic coronary artery disease (CAD).

Methods and results

JAM-A SNP analysis (JAM-A F11R rs2774276 and rs790056) was performed in 943 patients with symptomatic CAD. All patients were tracked for all-cause death (ACD), myocardial infarction (MI), and ischemic stroke (IS) for 1080 days. The primary combined endpoint (CE) was defined as a composite of ACD and/or MI and/or IS. Secondary endpoints were defined as the single events of ACD and MI. Homozygote carriers of the minor allele (F11R rs2774276 and rs790056) showed significantly worse event-free survival for MI when compared with major allele carriers (Log rank = 0.011 and log rank = 0.031, respectively). No significant differences could be shown for the CE and ACD. Of note, in multivariate analysis, both SNPs were significantly and independently associated with MI. Furthermore, serum levels of soluble JAM-A were elevated in homozygote carriers of minor allele when compared to major allele carriers. Finally, serum levels of soluble JAM-A were significantly elevated in patients with MI when compared to stable CAD (p=0.036).

Figure 1

Conclusion

JAM-A SNPs are associated with prognosis in patients with symptomatic coronary artery disease. Furthermore, JAM-A SNPs might influence serum concentration of soluble JAM-A. Finally, serum concentration of soluble JAM-A is higher in patients with myocardial infarction when compared to stable coronary artery disease. These findings suggest JAM-A as a valuable biomarker for risk stratification and tailoring therapies in patients with coronary artery disease.

Acknowledgement/Funding

DFG-KFO274, CRC/Transregio 240

In vitro supplementation with unsaturated fatty acids improves boar sperm viability after storage at 6 °C

Liquid preservation of the cold-sensitive boar sperm at a lesser temperature than the standard 17 °C would reduce bacterial growth and minimize the use of antibiotics. There was assessment, therefore, of the capacity of individual fatty acids bound to fatty acid free BSA to improve sperm survival at 6 °C because oxidative stress and lipid degradation are prominent detrimental factors. Different effects of the fatty acids were observed. Supplementation with naturally occurring fatty acids (linolenic, linoleic, oleic, palmitoleic acid), which may become metabolically incorporated into sperm lipids, increased the number of motile and progressively motile sperm after 2 days of storage during a thermo-resistance test (5 h at 38 °C) to that of control samples preserved at 17 °C in pure Beltsville Thawing Solution. With the exception of linolenic acid, all naturally occurring fatty acids enhanced the number of sperm with active mitochondria after 3 days of storage. Palmitoleic acid was the most effective supplement with effects already present when sperm were re-warmed for 30 min after 2 and 7 days of storage. The non-endogenous, non-integrated timnodonic acid (20:5) had no effect on sperm variables. Because the application of individual fatty acids attached to BSA had differing effects in preserving boar sperm at 6 °C, the use of combinations of fatty acids could be more efficacious than with use of natural lipid supplements for low temperature preservation of sperm.

Defining and measuring 'eczema control': an international qualitative study to explore the views of those living with and treating atopic eczema

Background

Atopic eczema (also known as eczema) is a chronic, inflammatory skin condition that often afflicts patients’ health and well‐being. The Harmonising Outcome Measures for Eczema (HOME) initiative recommends that ‘long‐term control of eczema’ is measured in all clinical trials 3 months or longer in duration. However, little has been published on what eczema control means to those living with or treating atopic eczema.

Objectives

To (i) develop understanding of what eczema control means to patients, carers and clinicians and (ii) explore the feasibility and acceptability of different ways of measuring eczema control in the long term.

Methods

Online focus groups explored patients/carers experiences in the UK, the United States, the Netherlands, France, Sweden and Japan, and an international online survey gathered views of clinicians. The framework method was used to analyse the focus groups, and thematic analysis was used to analyse survey data. All findings were integrated into a theoretical framework to create overarching themes that cut across these diverse groups.

Results

Eight focus groups with patients (16 years+) and eight groups with carers of children took place (N = 97). Sixty‐two people took part in the survey. Eczema control was described as a multifaceted construct involving changes in disease activity, the treatment and management of the condition and psychological, social and physical functioning. Patient/carer measurement allows personal accounts and frequent measurement, whilst clinician measurement was deemed less subjective. The burden on patients/carers and issues for analysing and interpreting data should be considered.

Conclusions

This study formed the basis of judging the content validity and feasibility of measurement instruments/methods to assess control of eczema in clinical trials. This online approach to an international qualitative study is an example of how core outcome set developers with limited resources can engage with multiple stakeholder groups on an international basis to inform consensus meeting discussions.

Intercomparison of atmospheric trace gas dispersion models: Barnett Shale case study

Greenhouse gas emissions mitigation requires understanding the dominant processes controlling fluxes of these trace gases at increasingly finer spatial and temporal scales. Trace gas fluxes can be estimated using a variety of approaches that translate observed atmospheric species mole fractions into fluxes or emission rates, often identifying the spatial and temporal characteristics of the emission sources as well. Meteorological models are commonly combined with tracer dispersion models to estimate fluxes using an inverse approach that optimizes emissions to best fit the trace gas mole fraction observations. One way to evaluate the accuracy of atmospheric flux estimation methods is to compare results from independent methods, including approaches in which different meteorological and tracer dispersion models are used. In this work, we use a rich data set of atmospheric methane observations collected during an intensive airborne campaign to compare different methane emissions estimates from the Barnett Shale oil and natural gas production basin in Texas, USA. We estimate emissions based on a variety of different meteorological and dispersion models. Previous estimates of methane emissions from this region relied on a simple model (a mass balance analysis) as well as on ground-based measurements and statistical data analysis (an inventory). We find that in addition to meteorological model choice, the choice of tracer dispersion model also has a significant impact on the predicted down-wind methane concentrations given the same emissions field. The dispersion models tested often underpredicted the observed methane enhancements with significant variability (up to a factor of 3) between different models and between different days. We examine possible causes for this result and find that the models differ in their simulation of vertical dispersion, indicating that additional work is needed to evaluate and improve vertical mixing in the tracer dispersion models commonly used in regional trace gas flux inversions.

Intercomparison of atmospheric trace gas dispersion models: Barnett Shale case study

Greenhouse gas emissions mitigation requires understanding the dominant processes controlling fluxes of these trace gases at increasingly finer spatial and temporal scales. Trace gas fluxes can be estimated using a variety of approaches that translate observed atmospheric species mole fractions into fluxes or emission rates, often identifying the spatial and temporal characteristics of the emission sources as well. Meteorological models are commonly combined with tracer dispersion models to estimate fluxes using an inverse approach that optimizes emissions to best fit the trace gas mole fraction observations. One way to evaluate the accuracy of atmospheric flux estimation methods is to compare results from independent methods, including approaches in which different meteorological and tracer dispersion models are used. In this work, we use a rich data set of atmospheric methane observations collected during an intensive airborne campaign to compare different methane emissions estimates from the Barnett Shale oil and natural gas production basin in Texas, USA. We estimate emissions based on a variety of different meteorological and dispersion models. Previous estimates of methane emissions from this region relied on a simple model (a mass balance analysis) as well as on ground-based measurements and statistical data analysis (an inventory). We find that in addition to meteorological model choice, the choice of tracer dispersion model also has a significant impact on the predicted down-wind methane concentrations given the same emissions field. The dispersion models tested often underpredicted the observed methane enhancements with significant variability (up to a factor of 3) between different models and between different days. We examine possible causes for this result and find that the models differ in their simulation of vertical dispersion, indicating that additional work is needed to evaluate and improve vertical mixing in the tracer dispersion models commonly used in regional trace gas flux inversions.

[Instantaneous wave-free ratio (iFR®) in patients with coronary artery disease]

Coronary angiography is considered as the gold standard in the morphological representation of coronary artery stenosis. Coronary angiography is often performed without preprocedural non-invasive proof of ischemia and the assessment of the severity of a coronary lesion by morphology is very subjective. Thus, invasive fractional flow reserve (FFR) measurement represents the current standard for estimation of the hemodynamic relevance of coronary artery stenosis and facilitates decision making for percutaneous coronary intervention (PCI) and stenting. The FFR-guided revascularization strategy has been classified as a class IA recommendation in the 2014 ESC/EACTS guidelines on myocardial revascularization. Both the DEFER and the FAME studies showed no treatment advantage of hemodynamically irrelevant stenosis. By use of FFR (and targeted interventions), clinical results could be improved as well as the procedure costs were reduced; however, the use in clinical practice is still limited due to the need of adenosine administration and a significant prolongation of the procedure. Instantaneous wave-free ratio (iFR®) is a new innovative approach for the determination of the hemodynamic relevance of coronary stenosis which can be obtained at rest without the use of vasodilators. Regarding periprocedural complications as well as prognosis, iFR® showed non-inferiority compared to FFR in the SWEDEHEART and DEFINE-FLAIR trials.

Measurement of the centrality dependence of the charged-particle pseudorapidity distribution in proton-lead collisions at [Formula: see text] TeV with the ATLAS detector

The centrality dependence of the mean charged-particle multiplicity as a function of pseudorapidity is measured in approximately 1 [Formula: see text]b[Formula: see text] of proton-lead collisions at a nucleon-nucleon centre-of-mass energy of [Formula: see text] [Formula: see text] using the ATLAS detector at the Large Hadron Collider. Charged particles with absolute pseudorapidity less than 2.7 are reconstructed using the ATLAS pixel detector. The [Formula: see text] collision centrality is characterised by the total transverse energy measured in the Pb-going direction of the forward calorimeter. The charged-particle pseudorapidity distributions are found to vary strongly with centrality, with an increasing asymmetry between the proton-going and Pb-going directions as the collisions become more central. Three different estimations of the number of nucleons participating in the [Formula: see text] collision have been carried out using the Glauber model as well as two Glauber-Gribov inspired extensions to the Glauber model. Charged-particle multiplicities per participant pair are found to vary differently for these three models, highlighting the importance of including colour fluctuations in nucleon-nucleon collisions in the modelling of the initial state of [Formula: see text] collisions.

Study of the [Formula: see text] and [Formula: see text] decays with the ATLAS detector

The decays [Formula: see text] and [Formula: see text] are studied with the ATLAS detector at the LHC using a dataset corresponding to integrated luminosities of 4.9 and 20.6 fb[Formula: see text] of pp collisions collected at centre-of-mass energies [Formula: see text] TeV and 8 TeV, respectively. Signal candidates are identified through [Formula: see text] and [Formula: see text] decays. With a two-dimensional likelihood fit involving the [Formula: see text] reconstructed invariant mass and an angle between the [Formula: see text] and [Formula: see text] candidate momenta in the muon pair rest frame, the yields of [Formula: see text] and [Formula: see text], and the transverse polarisation fraction in [Formula: see text] decay are measured. The transverse polarisation fraction is determined to be [Formula: see text], and the derived ratio of the branching fractions of the two modes is [Formula: see text], where the first error is statistical and the second is systematic. Finally, a sample of [Formula: see text] decays is used to derive the ratios of branching fractions [Formula: see text] and [Formula: see text], where the third error corresponds to the uncertainty of the branching fraction of [Formula: see text] decay. The available theoretical predictions are generally consistent with the measurement.

Measurements of the Higgs boson production and decay rates and coupling strengths using pp collision data at [Formula: see text] and 8 TeV in the ATLAS experiment

Combined analyses of the Higgs boson production and decay rates as well as its coupling strengths to vector bosons and fermions are presented. The combinations include the results of the analyses of the [Formula: see text] and [Formula: see text] decay modes, and the constraints on the associated production with a pair of top quarks and on the off-shell coupling strengths of the Higgs boson. The results are based on the LHC proton-proton collision datasets, with integrated luminosities of up to 4.7 [Formula: see text] at [Formula: see text] TeV and 20.3 [Formula: see text] at [Formula: see text] TeV, recorded by the ATLAS detector in 2011 and 2012. Combining all production modes and decay channels, the measured signal yield, normalised to the Standard Model expectation, is [Formula: see text]. The observed Higgs boson production and decay rates are interpreted in a leading-order coupling framework, exploring a wide range of benchmark coupling models both with and without assumptions on the Higgs boson width and on the Standard Model particle content in loop processes. The data are found to be compatible with the Standard Model expectations for a Higgs boson at a mass of 125.36 GeV for all models considered.

Two-particle Bose-Einstein correlations in pp collisions at [Formula: see text] 0.9 and 7 TeV measured with the ATLAS detector

The paper presents studies of Bose-Einstein Correlations (BEC) for pairs of like-sign charged particles measured in the kinematic range [Formula: see text] 100 MeV and [Formula: see text] 2.5 in proton collisions at centre-of-mass energies of 0.9 and 7 TeV with the ATLAS detector at the CERN Large Hadron Collider. The integrated luminosities are approximately 7 [Formula: see text]b[Formula: see text], 190 [Formula: see text]b[Formula: see text] and 12.4 nb[Formula: see text] for 0.9 TeV, 7 TeV minimum-bias and 7 TeV high-multiplicity data samples, respectively. The multiplicity dependence of the BEC parameters characterizing the correlation strength and the correlation source size are investigated for charged-particle multiplicities of up to 240. A saturation effect in the multiplicity dependence of the correlation source size parameter is observed using the high-multiplicity 7 TeV data sample. The dependence of the BEC parameters on the average transverse momentum of the particle pair is also investigated.

Search for Dark Matter in Events with Missing Transverse Momentum and a Higgs Boson Decaying to Two Photons in pp Collisions at sqrt[s]=8 TeV with the ATLAS Detector

Results of a search for new phenomena in events with large missing transverse momentum and a Higgs boson decaying to two photons are reported. Data from proton-proton collisions at a center-of-mass energy of 8 TeV and corresponding to an integrated luminosity of 20.3 fb^{-1} have been collected with the ATLAS detector at the LHC. The observed data are well described by the expected standard model backgrounds. Upper limits on the cross section of events with large missing transverse momentum and a Higgs boson candidate are also placed. Exclusion limits are presented for models of physics beyond the standard model featuring dark-matter candidates.

Search for Higgs boson pair production in the [Formula: see text] final state from pp collisions at [Formula: see text] TeVwith the ATLAS detector

A search for Higgs boson pair production [Formula: see text] is performed with 19.5 fb[Formula: see text] of proton-proton collision data at [Formula: see text] TeV, which were recorded by the ATLAS detector at the Large Hadron Collider in 2012. The decay products of each Higgs boson are reconstructed as a high-momentum [Formula: see text] system with either a pair of small-radius jets or a single large-radius jet, the latter exploiting jet substructure techniques and associated b-tagged track-jets. No evidence for resonant or non-resonant Higgs boson pair production is observed. The data are interpreted in the context of the Randall-Sundrum model with a warped extra dimension as well as the two-Higgs-doublet model. An upper limit on the cross-section for [Formula: see text] of 3.2 (2.3) fb is set for a Kaluza-Klein graviton [Formula: see text] mass of 1.0 (1.5) TeV, at the 95 % confidence level. The search for non-resonant Standard Model hh production sets an observed 95 % confidence level upper limit on the production cross-section [Formula: see text] of 202 fb, compared to a Standard Model prediction of [Formula: see text] fb.

Measurements of the Total and Differential Higgs Boson Production Cross Sections Combining the H→γγ and H→ZZ^{*}→4ℓ Decay Channels at sqrt[s]=8 TeV with the ATLAS Detector

Measurements of the total and differential cross sections of Higgs boson production are performed using 20.3  fb^{-1} of pp collisions produced by the Large Hadron Collider at a center-of-mass energy of sqrt[s]=8  TeV and recorded by the ATLAS detector. Cross sections are obtained from measured H→γγ and H→ZZ^{*}→4ℓ event yields, which are combined accounting for detector efficiencies, fiducial acceptances, and branching fractions. Differential cross sections are reported as a function of Higgs boson transverse momentum, Higgs boson rapidity, number of jets in the event, and transverse momentum of the leading jet. The total production cross section is determined to be σ_{pp→H}=33.0±5.3 (stat)±1.6 (syst)  pb. The measurements are compared to state-of-the-art predictions.