Objective measurement of cough frequency during COPD exacerbation convalescence

Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide. Cough and sputum production are associated with adverse outcomes in COPD and are common during COPD exacerbation (AE-COPD). This study of objective cough monitoring using the Hull Automated Cough Counter and Leicester Cough Monitor software confirms that this system has the ability to detect a significant decrease in cough frequency during AE-COPD convalescence. The ability to detect clinically meaningful change indicates a potential role in home monitoring of COPD patients

A high level interface to SCOP and ASTRAL implemented in Python

BACKGROUND: Benchmarking algorithms in structural bioinformatics often involves the construction of datasets of proteins with given sequence and structural properties. The SCOP database is a manually curated structural classification which groups together proteins on the basis of structural similarity. The ASTRAL compendium provides non redundant subsets of SCOP domains on the basis of sequence similarity such that no two domains in a given subset share more than a defined degree of sequence similarity. Taken together these two resources provide a 'ground truth' for assessing structural bioinformatics algorithms. We present a small and easy to use API written in python to enable construction of datasets from these resources. RESULTS: We have designed a set of python modules to provide an abstraction of the SCOP and ASTRAL databases. The modules are designed to work as part of the Biopython distribution. Python users can now manipulate and use the SCOP hierarchy from within python programs, and use ASTRAL to return sequences of domains in SCOP, as well as clustered representations of SCOP from ASTRAL. CONCLUSION: The modules make the analysis and generation of datasets for use in structural genomics easier and more principled

Continuous cough monitoring using ambient sound recording during convalescence from a COPD exacerbation

Purpose Cough is common in chronic obstructive pulmonary disease (COPD) and is associated with frequent exacerbations and increased mortality. Cough increases during acute exacerbations (AE-COPD), representing a possible metric of clinical deterioration. Conventional cough monitors accurately report cough counts over short time periods. We describe a novel monitoring system which we used to record cough continuously for up to 45 days during AE-COPD convalescence. Methods This is a longitudinal, observational study of cough monitoring in AE-COPD patients discharged from a single teaching-hospital. Ambient sound was recorded from two sites in the domestic environment and analysed using novel cough classifier software. For comparison, the validated hybrid HACC/LCM cough monitoring system was used on days 1, 5, 20 and 45. Patients were asked to record symptoms daily using diaries. Results Cough monitoring data were available for 16 subjects with a total of 568 monitored days. Daily cough count fell significantly from mean±SEM 272.7±54.5 on day 1 to 110.9±26.3 on day 9 (p<0.01) before plateauing. The absolute cough count detected by the continuous monitoring system was significantly lower than detected by the hybrid HACC/LCM system but normalised counts strongly correlated (r=0.88, p<0.01) demonstrating an ability to detect trends. Objective cough count and subjective cough scores modestly correlated (r=0.46). Conclusions Cough frequency declines significantly following AE-COPD and the reducing trend can be detected using continuous ambient sound recording and novel cough classifier software. Objective measurement of cough frequency has the potential to enhance our ability to monitor the clinical state in patients with COPD

The ongoing value of first few X studies for COVID-19 in the Western Pacific Region

First few ‘X’ (FFX) studies for COVID-19 involve data collection from confirmed cases and their close contacts. They remain relevant especially as many remain susceptible to infection, and as they can provide detailed insight into vaccine effectiveness and the epidemiology of variants of concern, helping to inform a proportionate health response

The Hypervariable Loops of Free TCRs Sample Multiple Distinct Metastable Conformations in Solution

CD4+ and CD8+ αβ T cell antigen recognition is determined by the interaction between the TCR Complementarity Determining Region (CDR) loops and the peptide-presenting MHC complex. These T cells are known for their ability to recognize multiple pMHC complexes, and for a necessary promiscuity that is required for their selection and function in the periphery. Crystallographic studies have previously elucidated the role of structural interactions in TCR engagement, but our understanding of the dynamic process that occurs during TCR binding is limited. To better understand the dynamic states that exist for TCR CDR loops in solution, and how this relates to their states when in complex with pMHC, we simulated the 2C T cell receptor in solution using all-atom molecular dynamics in explicit water and constructed a Markov State Model for each of the CDR3α and CDR3β loops. These models reveal multiple metastable states for the CDR3 loops in solution. Simulation data and metastable states reproduce known CDR3β crystal conformations, and reveal several novel conformations suggesting that CDR3β bound states are the result of search processes from nearby pre-existing equilibrium conformational states. Similar simulations of the invariant, Type I Natural Killer T cell receptor NKT15, which engages the monomorphic, MHC-like CD1d ligand, demonstrate that iNKT TCRs also have distinct states, but comparatively restricted degrees of motion

Uncertainty in United States coastal wetland greenhouse gas inventorying

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Environmental Research Letters 13 (2018): 115005, doi:10.1088/1748-9326/aae157.Coastal wetlands store carbon dioxide (CO2) and emit CO2 and methane (CH4) making them an important part of greenhouse gas (GHG) inventorying. In the contiguous United States (CONUS), a coastal wetland inventory was recently calculated by combining maps of wetland type and change with soil, biomass, and CH4 flux data from a literature review. We assess uncertainty in this developing carbon monitoring system to quantify confidence in the inventory process itself and to prioritize future research. We provide a value-added analysis by defining types and scales of uncertainty for assumptions, burial and emissions datasets, and wetland maps, simulating 10 000 iterations of a simplified version of the inventory, and performing a sensitivity analysis. Coastal wetlands were likely a source of net-CO2-equivalent (CO2e) emissions from 2006–2011. Although stable estuarine wetlands were likely a CO2e sink, this effect was counteracted by catastrophic soil losses in the Gulf Coast, and CH4 emissions from tidal freshwater wetlands. The direction and magnitude of total CONUS CO2e flux were most sensitive to uncertainty in emissions and burial data, and assumptions about how to calculate the inventory. Critical data uncertainties included CH4 emissions for stable freshwater wetlands and carbon burial rates for all coastal wetlands. Critical assumptions included the average depth of soil affected by erosion events, the method used to convert CH4 fluxes to CO2e, and the fraction of carbon lost to the atmosphere following an erosion event. The inventory was relatively insensitive to mapping uncertainties. Future versions could be improved by collecting additional data, especially the depth affected by loss events, and by better mapping salinity and inundation gradients relevant to key GHG fluxes. Social Media Abstract: US coastal wetlands were a recent and uncertain source of greenhouse gasses because of CH4 and erosion.Financial support was provided primarily by NASA Carbon Monitoring Systems (NNH14AY67I) and the USGS Land Carbon Program, with additional support from The Smithsonian Institution, The Coastal Carbon Research Coordination Network (DEB-1655622), and NOAA Grant: NA16NMF4630103

Ozone exposure is associated with acute changes in inflammation, fibrinolysis, and endothelial cell function in coronary artery disease patients

Air pollution is a major risk factor for cardiovascular disease, of which ozone is a major contributor. Several studies have found associations between ozone and cardiovascular morbidity, but the results have been inconclusive. We investigated associations between ozone and changes across biological pathways associated with cardiovascular disease

The Association between Dust Storms and Daily Non-Accidental Mortality in the United States, 1993–2005

BACKGROUND: The impact of dust storms on human health has been studied in the context of Asian, Saharan, Arabian, and Australian storms, but there has been no recent population-level epidemiological research on the dust storms in North America. The relevance of dust storms to public health is likely to increase as extreme weather events are predicted to become more frequent with anticipated changes in climate through the 21st century. OBJECTIVES: We examined the association between dust storms and county-level non-accidental mortality in the United States from 1993 through 2005. METHODS: Dust storm incidence data, including date and approximate location, are taken from the U.S. National Weather Service storm database. County-level mortality data for the years 1993-2005 were acquired from the National Center for Health Statistics. Distributed lag conditional logistic regression models under a time-stratified case-crossover design were used to study the relationship between dust storms and daily mortality counts over the whole United States and in Arizona and California specifically. End points included total non-accidental mortality and three mortality subgroups (cardiovascular, respiratory, and other non-accidental). RESULTS: We estimated that for the United States as a whole, total non-accidental mortality increased by 7.4% (95% CI: 1.6, 13.5; p = 0.011) and 6.7% (95% CI: 1.1, 12.6; p = 0.018) at 2- and 3-day lags, respectively, and by an average of 2.7% (95% CI: 0.4, 5.1; p = 0.023) over lags 0-5 compared with referent days. Significant associations with non-accidental mortality were estimated for California (lag 2 and 0-5 day) and Arizona (lag 3), for cardiovascular mortality in the United States (lag 2) and Arizona (lag 3), and for other non-accidental mortality in California (lags 1-3 and 0-5). CONCLUSIONS: Dust storms are associated with increases in lagged non-accidental and cardiovascular mortality. Citation: Crooks JL, Cascio WE, Percy MS, Reyes J, Neas LM, Hilborn ED. 2016. The association between dust storms and daily non-accidental mortality in the United States, 1993-2005. Environ Health Perspect 124:1735-1743; http://dx.doi.org/10.1289/EHP216

The Vehicle, 1962, Vol. 4

Vol. 4 Table of Contents The SearchLarry Pricepage 7 If We Should MeetPauline B. Smithpage 16 Sonnet No. 1Linda Campbellpage 17 SnowflakesPauline B. Smithpage 17 Encounter in the VoidEric Crookspage 18 symbolBen Polkpage 24 The Sound of SilenceJames Wilhelmpage 24 ColoursJean Ellen Danenbargerpage 26 vegetableBen Polkpage 27 The GiftJan Holstlawpage 29 The Tiled OvenRichard Glassonpage 30 This Lover Ever WeepsBen Polkpage 31 El DoradoPauline B. Smithpage 32 I\u27m SorryMary Jean Pitratpage 32 The WalkDavid Schwarzpage 33 The Twenty-Third ChannelBen Polkpage 34 After the PicnicLinda Campbellpage 35 SoliloquyJanice Brookspage 35 JulieMyra Edmanpage 36 Poems (1) (2)Gale Crousepage 40 Boardwalk at NightSheran Broadwaypage 41 SunsetPauline B. Smithpage 42 SummerC.E.M.page 42 It\u27s Spring AgainJanice Brookspage 43 Chinese SymbolsJean Ellen Danenbargerpage 43 Why Do You Wait?Gale Crousepage 44 seekerBen Polkpage 46 Poems (3) (4) (5)Gale Crousepage 47 Opposite AttractionsC.E.M.page 48 Illustrations for the winning short story and poemDouglas Koertgehttps://thekeep.eiu.edu/vehicle/1010/thumbnail.jp