Residential exposure to aircraft noise and hospital admissions for cardiovascular diseases: multi-airport retrospective study

Objective: To investigate whether exposure to aircraft noise increases the risk of hospitalization for cardiovascular diseases in older people (≥65 years) residing near airports. Design: Multi-airport retrospective study of approximately 6 million older people residing near airports in the United States. We superimposed contours of aircraft noise levels (in decibels, dB) for 89 airports for 2009 provided by the US Federal Aviation Administration on census block resolution population data to construct two exposure metrics applicable to zip code resolution health insurance data: population weighted noise within each zip code, and 90th centile of noise among populated census blocks within each zip code. Setting: 2218 zip codes surrounding 89 airports in the contiguous states. Participants: 6 027 363 people eligible to participate in the national medical insurance (Medicare) program (aged ≥65 years) residing near airports in 2009. Main outcome measures Percentage increase in the hospitalization admission rate for cardiovascular disease associated with a 10 dB increase in aircraft noise, for each airport and on average across airports adjusted by individual level characteristics (age, sex, race), zip code level socioeconomic status and demographics, zip code level air pollution (fine particulate matter and ozone), and roadway density. Results: Averaged across all airports and using the 90th centile noise exposure metric, a zip code with 10 dB higher noise exposure had a 3.5% higher (95% confidence interval 0.2% to 7.0%) cardiovascular hospital admission rate, after controlling for covariates. Conclusions: Despite limitations related to potential misclassification of exposure, we found a statistically significant association between exposure to aircraft noise and risk of hospitalization for cardiovascular diseases among older people living near airports

Hippocampal GABA enables inhibitory control over unwanted thoughts.

Intrusive memories, images, and hallucinations are hallmark symptoms of psychiatric disorders. Although often attributed to deficient inhibitory control by the prefrontal cortex, difficulty in controlling intrusive thoughts is also associated with hippocampal hyperactivity, arising from dysfunctional GABAergic interneurons. How hippocampal GABA contributes to stopping unwanted thoughts is unknown. Here we show that GABAergic inhibition of hippocampal retrieval activity forms a key link in a fronto-hippocampal inhibitory control pathway underlying thought suppression. Subjects viewed reminders of unwanted thoughts and tried to suppress retrieval while being scanned with functional magnetic resonance imaging. Suppression reduced hippocampal activity and memory for suppressed content. 1H magnetic resonance spectroscopy revealed that greater resting concentrations of hippocampal GABA predicted better mnemonic control. Higher hippocampal, but not prefrontal GABA, predicted stronger fronto-hippocampal coupling during suppression, suggesting that interneurons local to the hippocampus implement control over intrusive thoughts. Stopping actions did not engage this pathway. These findings specify a multi-level mechanistic model of how the content of awareness is voluntarily controlled

A new MR-SAD algorithm for the automatic building of protein models from low-resolution X-ray data and a poor starting model

Determining macromolecular structures from X-ray data with resolution worse than 3 Å remains a challenge. Even if a related starting model is available, its incompleteness or its bias together with a low observation-to-parameter ratio can render the process unsuccessful or very time-consuming. Yet, many biologically important macromolecules, especially large macromolecular assemblies, membrane proteins and receptors, tend to provide crystals that diffract to low resolution. A new algorithm to tackle this problem is presented that uses a multivariate function to simultaneously exploit information from both an initial partial model and low-resolution single-wavelength anomalous diffraction data. The new approach has been used for six challenging structure determinations, including the crystal structures of membrane proteins and macromolecular complexes that have evaded experts using other methods, and large structures from a 3.0 Å resolution F1-ATPase data set and a 4.5 Å resolution SecYEG–SecA complex data set. All of the models were automatically built by the method to Rfree values of between 28.9 and 39.9% and were free from the initial model bias

Improving primary care management of asthma:do we know what really works?

Asthma imposes a substantial burden on individuals and societies. Patients with asthma need high-quality primary care management; however, evidence suggests the quality of this care can be highly variable. Here we identify and report factors contributing to high-quality management. Twelve primary care global asthma experts, representing nine countries, identified key factors. A literature review (past 10 years) was performed to validate or refute the expert viewpoint. Key driving factors identified were: policy, clinical guidelines, rewards for performance, practice organisation and workforce. Further analysis established the relevant factor components. Review evidence supported the validity of each driver; however, impact on patient outcomes was uncertain. Single interventions (e.g. healthcare practitioner education) showed little effect; interventions driven by national policy (e.g. incentive schemes and teamworking) were more effective. The panel's opinion, supported by literature review, concluded that multiple primary care interventions offer greater benefit than any single intervention in asthma management

CSF1R+ Macrophages Sustain Pancreatic Tumor Growth through T Cell Suppression and Maintenance of Key Gene Programs that Define the Squamous Subtype.

Pancreatic ductal adenocarcinoma (PDAC) is resistant to most therapies including single-agent immunotherapy and has a dense desmoplastic stroma, and most patients present with advanced metastatic disease. We reveal that macrophages are the dominant leukocyte population both in human PDAC stroma and autochthonous models, with an important functional contribution to the squamous subtype of human PDAC. We targeted macrophages in a genetic PDAC model using AZD7507, a potent selective inhibitor of CSF1R. AZD7507 caused shrinkage of established tumors and increased mouse survival in this difficult-to-treat model. Malignant cell proliferation diminished, with increased cell death and an enhanced T cell immune response. Loss of macrophages rewired other features of the TME, with global changes in gene expression akin to switching PDAC subtypes. These changes were markedly different to those elicited when neutrophils were targeted via CXCR2. These results suggest targeting the myeloid cell axis may be particularly efficacious in PDAC, especially with CSF1R inhibitors

A new MR-SAD algorithm for the automatic building of protein models from low-resolution X-ray data and a poor starting model

Determining macromolecular structures from X-ray data with resolution worse than 3 Å remains a challenge. Even if a related starting model is available, its incompleteness or its bias together with a low observation-to-parameter ratio can render the process unsuccessful or very time-consuming. Yet, many biologically important macromolecules, especially large macromolecular assemblies, membrane proteins and receptors, tend to provide crystals that diffract to low resolution. A new algorithm to tackle this problem is presented that uses a multivariate function to simultaneously exploit information from both an initial partial model and low-resolution single-wavelength anomalous diffraction data. The new approach has been used for six challenging structure determinations, including the crystal structures of membrane proteins and macromolecular complexes that have evaded experts using other methods, and large structures from a 3.0 Å resolution F_1-ATPase data set and a 4.5 Å resolution SecYEG–SecA complex data set. All of the models were automatically built by the method to R_(free) values of between 28.9 and 39.9% and were free from the initial model bias

A charter to improve patient care in severe asthma

Severe asthma is a subtype of asthma that is difficult to treat and control. By conservative estimates, severe asthma affects approximately 5-10% of patients with asthma worldwide. Severe asthma impairs patients' health-related quality of life, and patients are at risk of life-threatening asthma attacks. Severe asthma also accounts for the majority of health care expenditures associated with asthma. Guidelines recommend that patients with severe asthma be referred to a specialist respiratory team for correct diagnosis and expert management. This is particularly important to ensure that they have access to newly available biologic treatments. However, many patients with severe asthma can suffer multiple asthma attacks and wait several years before they are referred for specialist care. As global patient advocates, we believe it is essential to raise awareness and understanding for patients, caregivers, health care professionals, and the public about the substantial impact of severe asthma and to create opportunities for improving patient care. Patients should be empowered to live a life free of symptoms and the adverse effects of traditional medications (e.g., oral corticosteroids), reducing hospital visits and emergency care, the loss of school and work days, and the constraints placed on their daily lives. Here we provide a Patient Charter for severe asthma, consisting of six core principles, to mobilize national governments, health care providers, payer policymakers, lung health industry partners, and patients/caregivers to address the unmet need and burden in severe asthma and ultimately work together to deliver meaningful improvements in care.Funding for this study, the article processing charges, and the open access charge was provided by AstraZeneca

TOI-1338 : TESS' first transiting circumbinary planet

Funding: Funding for the DPAC has been provided by national institutions, in particular, the institutions participating in the Gaia Multilateral Agreement. W.F.W. and J.A.O.thank John Hood Jr. for his generous support of exoplanet research at SDSU. Support was also provided and acknowledged through NASA Habitable Worlds grant 80NSSC17K0741 and NASA XRP grant 80NSSC18K0519. This work is partly supported by NASA Habitable Worlds grant 80NSSC17K0741. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under grant No.(DGE-1746045). A.H.M.J.T. has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 803193/BEBOP) and from a Leverhulme Trust Research Project grant No. RPG-2018-418. A.C. acknowledges support by CFisUC strategic project (UID/FIS/04564/2019).We report the detection of the first circumbinary planet (CBP) found by Transiting Exoplanet Survey Satellite (TESS). The target, a known eclipsing binary, was observed in sectors 1 through 12 at 30 minute cadence and in sectors 4 through 12 at 2 minute cadence. It consists of two stars with masses of 1.1 M⊙ and 0.3 M⊙ on a slightly eccentric (0.16), 14.6 day orbit, producing prominent primary eclipses and shallow secondary eclipses. The planet has a radius of ∼6.9 R⊕ and was observed to make three transits across the primary star of roughly equal depths (∼0.2%) but different durations—a common signature of transiting CBPs. Its orbit is nearly circular (e ≍ 0.09) with an orbital period of 95.2 days. The orbital planes of the binary and the planet are aligned to within ∼1°. To obtain a complete solution for the system, we combined the TESS photometry with existing ground-based radial-velocity observations in a numerical photometric-dynamical model. The system demonstrates the discovery potential of TESS for CBPs and provides further understanding of the formation and evolution of planets orbiting close binary stars.Publisher PDFPeer reviewe

Rational Mutational Analysis of a Multidrug MFS Transporter CaMdr1p of Candida albicans by Employing a Membrane Environment Based Computational Approach

CaMdr1p is a multidrug MFS transporter of pathogenic Candida albicans. An over-expression of the gene encoding this protein is linked to clinically encountered azole resistance. In-depth knowledge of the structure and function of CaMdr1p is necessary for an effective design of modulators or inhibitors of this efflux transporter. Towards this goal, in this study, we have employed a membrane environment based computational approach to predict the functionally critical residues of CaMdr1p. For this, information theoretic scores which are variants of Relative Entropy (Modified Relative Entropy REM) were calculated from Multiple Sequence Alignment (MSA) by separately considering distinct physico-chemical properties of transmembrane (TM) and inter-TM regions. The residues of CaMdr1p with high REM which were predicted to be significantly important were subjected to site-directed mutational analysis. Interestingly, heterologous host Saccharomyces cerevisiae, over-expressing these mutant variants of CaMdr1p wherein these high REM residues were replaced by either alanine or leucine, demonstrated increased susceptibility to tested drugs. The hypersensitivity to drugs was supported by abrogated substrate efflux mediated by mutant variant proteins and was not attributed to their poor expression or surface localization. Additionally, by employing a distance plot from a 3D deduced model of CaMdr1p, we could also predict the role of these functionally critical residues in maintaining apparent inter-helical interactions to provide the desired fold for the proper functioning of CaMdr1p. Residues predicted to be critical for function across the family were also found to be vital from other previously published studies, implying its wider application to other membrane protein families