Exercise Intolerance in Pulmonary Arterial Hypertension

Pulmonary arterial hypertension (PAH) is associated with symptoms of dyspnea and fatigue, which contribute to exercise limitation. The origins and significance of dyspnea and fatigue in PAH are not completely understood. This has created uncertainly among healthcare professionals regarding acceptable levels of these symptoms, on exertion, for patients with PAH. Dysfunction of the right ventricle (RV) contributes to functional limitation and mortality in PAH; however, the role of the RV in eliciting dyspnea and fatigue has not been thoroughly examined. This paper explores the contribution of the RV and systemic and peripheral abnormalities to exercise limitation and symptoms in PAH. Further, it explores the relationship between exercise abnormalities and symptoms, the utility of the cardiopulmonary exercise test in identifying RV dysfunction, and offers suggestions for further research

A population-level prediction tool for the incidence of first-episode psychosis: translational epidemiology based on cross-sectional data

Objectives: Specialist early intervention services (EIS) for people aged 14–35 years with first episodes of psychosis (FEP) have been commissioned throughout England since 2001. A single estimate of population need was used everywhere, but true incidence varies enormously according to sociodemographic factors. We sought to develop a realistically complex, population-based prediction tool for FEP, based on precise estimates of epidemiological risk. Design and participants: Data from 1037 participants in two cross-sectional population-based FEP studies were fitted to several negative binomial regression models to estimate risk coefficients across combinations of different sociodemographic and socioenvironmental factors. We applied these coefficients to the population at-risk of a third, socioeconomically different region to predict expected caseload over 2.5 years, where the observed rates of ICD-10 F10-39 FEP had been concurrently ascertained via EIS. Setting: Empirical population-based epidemiological data from London, Nottingham and Bristol predicted counts in the population at-risk in the East Anglia region of England. Main outcome measures: Observed counts were compared with predicted counts (with 95% prediction intervals (PI)) at EIS and local authority district (LAD) levels in East Anglia to establish the predictive validity of each model. Results: A model with age, sex, ethnicity and population density performed most strongly, predicting 508 FEP participants in EIS in East Anglia (95% PI 459, 559), compared with 522 observed participants. This model predicted correctly in 5/6 EIS and 19/21 LADs. All models performed better than the current gold standard for EIS commissioning in England (716 cases; 95% PI 664–769). Conclusions: We have developed a prediction tool for the incidence of psychotic disorders in England and Wales, made freely available online (http://www.psymaptic.org), to provide healthcare commissioners with accurate forecasts of FEP based on robust epidemiology and anticipated local population need. The initial assessment of some people who do not require subsequent EIS care means additional service resources, not addressed here, will be required

Isotopic signatures in atmospheric particulate matter suggest important contributions from recycled gasoline for lead and non-exhaust traffic sources for copper and zinc in aerosols in London, United Kingdom

The aim of this study was to improve our understanding of what controls the isotope composition of Cu, Zn and Pb in particulate matter (PM) in the urban environment and to develop these isotope systems as possible source tracers. To this end, isotope ratios (Cu, Zn and Pb) and trace element concentrations (Fe, Al, Cu, Zn, Sb, Ba, Pb, Cr, Ni and V) were determined in PM10 collected at two road sites with contrasting traffic densities in central London, UK, during two weeks in summer 2010, and in potential sources, including non-combustion traffic emissions (tires and brakes), road furniture (road paint, manhole cover and road tarmac surface) and road dust. Iron, Ba and Sb were used as proxies for emissions derived from brake pads, and Ni, and V for emissions derived from fossil fuel oil. The isotopic composition of Pb (expressed using 206Pb/207Pb) ranged between 1.1137 and 1.1364. The isotope ratios of Cu and Zn expressed as δ65CuNIST976 and δ66ZnLyon ranged between −0.01‰ and +0.51‰ and between −0.21‰ and +0.33‰, respectively. We did not find significant differences in the isotope signatures in PM10 over the two weeks sampling period and between the two sites, suggesting similar sources for each metal at both sites despite their different traffic densities. The stable isotope composition of Pb suggests significant contribution from road dust resuspension and from recycled leaded gasoline. The Cu and Zn isotope signatures of tires, brakes and road dust overlap with those of PM10. The correlation between the enrichments of Sb, Cu, Ba and Fe in PM10 support the previously established hypothesis that Cu isotope ratios are controlled by non-exhaust traffic emission sources in urban environments (Ochoa Gonzalez et al., 2016). Analysis of the Zn isotope signatures in PM10 and possible sources at the two sites suggests significant contribution from tire wear. However, temporary additional sources, likely high temperature industrial emissions, need to be invoked to explain the isotopically light Zn found in 3 out of 18 samples of PM10

Dark Matter Gravitational Interactions

We argue that the conjectured dark mater in the Universe may be endowed with a new kind of gravitational charge that couples to a short range gravitational interaction mediated by a massive vector field. A model is constructed that assimilates this concept into ideas of current inflationary cosmology. The model is also consistent with the observed behaviour of galactic rotation curves according to Newtonian dynamics. The essential idea is that stars composed of ordinary (as opposed to dark matter) experience Newtonian forces due to the presence of an all pervading background of massive gravitationally charged cold dark matter. The novel gravitational interactions are predicted to have a significant influence on pre-inflationary cosmology. The precise details depend on the nature of a gravitational Proca interaction and the description of matter. A gravitational Proca field configuration that gives rise to attractive forces between dark matter charges of like polarity exhibits homogeneous isotropic eternal cosmologies that are free of cosmological curvature singularities thus eliminating the horizon problem associated with the standard big-bang scenario. Such solutions do however admit dense hot pre-inflationary epochs each with a characteristic scale factor that may be correlated with the dark matter density in the current era of expansion. The model is based on a theory in which a modification of Einsteinian gravity at very short distances can be expressed in terms of the gradient of the Einstein metric and the torsion of a non-Riemannian connection on the bundle of linear frames over spacetime. Indeed we demonstrate that the genesis of the model resides in a remarkable simplification that occurs when one analyses the variational equations associated with a broad class of non-Riemannian actions.Comment: 40 pages, 4 Postscript figure

Development and validation of a non-remission risk prediction model in first episode psychosis:An Analysis of 2 Longitudinal Studies

Psychosis is a major mental illness with first onset in young adults. The prognosis is poor in around half of the people affected, and difficult to predict. The few tools available to predict prognosis have major weaknesses which limit their use in clinical practice. We aimed to develop and validate a risk prediction model of symptom nonremission in first-episode psychosis. Our development cohort consisted of 1027 patients with first-episode psychosis recruited between 2005 and 2010 from 14 early intervention services across the National Health Service in England. Our validation cohort consisted of 399 patients with first-episode psychosis recruited between 2006 and 2009 from a further 11 English early intervention services. The one-year nonremission rate was 52% and 54% in the development and validation cohorts, respectively. Multivariable logistic regression was used to develop a risk prediction model for nonremission, which was externally validated. The prediction model showed good discrimination C-statistic of 0.73 (0.71, 0.75) and adequate calibration with intercept alpha of 0.12 (0.02, 0.22) and slope beta of 0.98 (0.85, 1.11). Our model improved the net-benefit by 15% at a risk threshold of 50% compared to the strategy of treating all, equivalent to 15 more detected nonremitted first-episode psychosis individuals per 100 without incorrectly classifying remitted cases. Once prospectively validated, our first episode psychosis prediction model could help identify patients at increased risk of nonremission at initial clinical contact.</p

Genome Sequence of the Model Mushroom Schizophyllum Commune

Much remains to be learned about the biology of mushroom-forming fungi, which are an important source of food, secondary metabolites and industrial enzymes. The wood-degrading fungus Schizophyllum commune is both a genetically tractable model for studying mushroom development and a likely source of enzymes capable of efficient degradation of lignocellulosic biomass. Comparative analyses of its 38.5-megabase genome, which encodes 13,210 predicted genes, reveal the species\u27s unique wood-degrading machinery. One-third of the 471 genes predicted to encode transcription factors are differentially expressed during sexual development of S. commune. Whereas inactivation of one of these, fst4, prevented mushroom formation, inactivation of another, fst3, resulted in more, albeit smaller, mushrooms than in the wild-type fungus. Antisense transcripts may also have a role in the formation of fruiting bodies. Better insight into the mechanisms underlying mushroom formation should affect commercial production of mushrooms and their industrial use for producing enzymes and pharmaceuticals

Challenges in quantifying changes in the global water cycle

Human influences have likely already impacted the large-scale water cycle but natural variability and observational uncertainty are substantial. It is essential to maintain and improve observational capabilities to better characterize changes. Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes

COVID-19 risk-mitigation in reopening mass events: population-based observational study for the UK Events Research Programme in Liverpool City Region

OBJECTIVES: To understand severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission risks, perceived risks and the feasibility of risk mitigations from experimental mass cultural events before coronavirus disease 2019 (COVID-19) restrictions were lifted. DESIGN: Prospective, population-wide observational study. SETTING: Four events (two nightclubs, an outdoor music festival and a business conference) open to Liverpool City Region UK residents, requiring a negative lateral flow test (LFT) within the 36 h before the event, but not requiring social distancing or face-coverings. PARTICIPANTS: A total of 12,256 individuals attending one or more events between 28 April and 2 May 2021. MAIN OUTCOME MEASURES: SARS-CoV-2 infections detected using audience self-swabbed (5-7 days post-event) polymerase chain reaction (PCR) tests, with viral genomic analysis of cases, plus linked National Health Service COVID-19 testing data. Audience experiences were gathered via questionnaires, focus groups and social media. Indoor CO2 concentrations were monitored. RESULTS: A total of 12 PCR-positive cases (likely 4 index, 8 primary or secondary), 10 from the nightclubs. Two further cases had positive LFTs but no PCR. A total of 11,896 (97.1%) participants with scanned tickets were matched to a negative pre-event LFT: 4972 (40.6%) returned a PCR within a week. CO2 concentrations showed areas for improving ventilation at the nightclubs. Population infection rates were low, yet with a concurrent outbreak of >50 linked cases around a local swimming pool without equivalent risk mitigations. Audience anxiety was low and enjoyment high. CONCLUSIONS: We observed minor SARS-CoV-2 transmission and low perceived risks around events when prevalence was low and risk mitigations prominent. Partnership between audiences, event organisers and public health services, supported by information systems with real-time linked data, can improve health security for mass cultural events

Clinical Impact of Ceftriaxone Resistance in Escherichia coli Bloodstream Infections: A Multicenter Prospective Cohort Study

BACKGROUND: Ceftriaxone-resistant (CRO-R) Escherichia coli bloodstream infections (BSIs) are common. METHODS: This is a prospective cohort of patients with E coli BSI at 14 United States hospitals between November 2020 and April 2021. For each patient with a CRO-R E coli BSI enrolled, the next consecutive patient with a ceftriaxone-susceptible (CRO-S) E coli BSI was included. Primary outcome was desirability of outcome ranking (DOOR) at day 30, with 50% probability of worse outcomes in the CRO-R group as the null hypothesis. Inverse probability weighting (IPW) was used to reduce confounding. RESULTS: Notable differences between patients infected with CRO-R and CRO-S E coli BSI included the proportion with Pitt bacteremia score ≥4 (23% vs 15%, P = .079) and the median time to active antibiotic therapy (12 hours [interquartile range {IQR}, 1-35 hours] vs 1 hour [IQR, 0-6 hours]; P \u3c .001). Unadjusted DOOR analyses indicated a 58% probability (95% confidence interval [CI], 52%-63%) for a worse clinical outcome in CRO-R versus CRO-S BSI. In the IPW-adjusted cohort, no difference was observed (54% [95% CI, 47%-61%]). Secondary outcomes included unadjusted and adjusted differences in the proportion of 30-day mortality between CRO-R and CRO-S BSIs (-5.3% [95% CI, -10.3% to -.4%] and -1.8 [95% CI, -6.7% to 3.2%], respectively), postculture median length of stay (8 days [IQR, 5-13 days] vs 6 days [IQR, 4-9 days]; P \u3c .001), and incident admission to a long-term care facility (22% vs 12%, P = .045). CONCLUSIONS: Patients with CRO-R E coli BSI generally have poorer outcomes compared to patients infected with CRO-S E coli BSI, even after adjusting for important confounders