Assessment of airway inflammation using sputum, BAL, and endobronchial biopsies in current and ex-smokers with established COPD

Rationale: Smoking effects on physiological and gross pathology in chronic obstructive pulmonary disease (COPD) are relatively well described. However, there is little known in COPD about the detailed interrelationships between lung function and inflammatory profiles in different airway compartments from the same individual and whether airway inflammation in these different compartments differs in ex- and current smokers with established COPD. Objectives: We compared sputum, bronchoalveolar (BAL), and airway wall inflammatory profiles in current versus ex-smokers and related this to smoking intensity and lung function in 17 current and 17 ex-smokers with mild to moderate COPD. Results: Current smokers had more sputum mast cells (% differential and absolute numbers), whereas ex-smokers had increased sputum neutrophils. In BAL, there was a significant increase in eosinophils in current smokers, but ex-smokers had significantly increased neutrophils, lymphocytes, and epithelial cells. There were no cell profile differences observed in airway biopsies between current and ex-smokers and there were no correlations between the individual inflammatory cell populations in any of the airway compartments. In current smokers only, smoking intensity was negatively correlated with lung function, and associated with a reduction in overall cellularity of both sputum and BAL. Conclusion: Airway inflammation persists in ex-smokers with COPD, but differs from COPD current smokers. The impact of smoking appears to vary in different airway compartments and any direct relationships between cellularity and lung function tended to be negative, ie, worse lung function indicated the presence of fewer cells

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Quantum algorithm and circuit design solving the Poisson equation

The Poisson equation occurs in many areas of science and engineering. Here we focus on its numerical solution for an equation in d dimensions. In particular we present a quantum algorithm and a scalable quantum circuit design which approximates the solution of the Poisson equation on a grid with error \varepsilon. We assume we are given a supersposition of function evaluations of the right hand side of the Poisson equation. The algorithm produces a quantum state encoding the solution. The number of quantum operations and the number of qubits used by the circuit is almost linear in d and polylog in \varepsilon^{-1}. We present quantum circuit modules together with performance guarantees which can be also used for other problems.Comment: 30 pages, 9 figures. This is the revised version for publication in New Journal of Physic

Quantifying Uncertainties in Land Surface Microwave Emissivity Retrievals

Uncertainties in the retrievals of microwave land surface emissivities were quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including SSM/I, TMI and AMSR-E, were studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors in the retrievals. Generally these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 1~4% (3~12 K) over desert and 1~7% (3~20 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.5~2% (2~6 K). In particular, at 85.0/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are mostly likely caused by rain/cloud contamination, which can lead to random errors up to 10~17 K under the most severe conditions

Complex I assembly function and fatty acid oxidation enzyme activity of ACAD9 both contribute to disease severity in ACAD9 deficiency

Acyl-CoA dehydrogenase 9 (ACAD9) is an assembly factor for mitochondrial respiratory chain Complex I (CI), and ACAD9 mutations are recognized as a frequent cause of CI deficiency. ACAD9 also retains enzyme ACAD activity for long-chain fatty acids in vitro, but the biological relevance of this function remains controversial partly because of the tissue specificity of ACAD9 expression: high in liver and neurons and minimal in skin fibroblasts. In this study, we hypothesized that this enzymatic ACAD activity is required for full fatty acid oxidation capacity in cells expressing high levels of ACAD9 and that loss of this function is important in determining phenotype in ACAD9-deficient patients. First, we confirmed that HEK293 cells express ACAD9 abundantly. Then, we showed that ACAD9 knockout in HEK293 cells affected long-chain fatty acid oxidation along with Cl, both of which were rescued by wild type ACAD9. Further, we evaluated whether the loss of ACAD9 enzymatic fatty acid oxidation affects clinical severity in patients with ACAD9 mutations. The effects on ACAD activity of 16 ACAD9 mutations identified in 24 patients were evaluated using a prokaryotic expression system. We showed that there was a significant inverse correlation between residual enzyme ACAD activity and phenotypic severity of ACAD9-deficient patients. These results provide evidence that in cells where it is strongly expressed, ACAD9 plays a physiological role in fatty acid oxidation, which contributes to the severity of the phenotype in ACAD9-deficient patients. Accordingly, treatment of ACAD9 patients should aim at counteracting both CI and fatty acid oxidation dysfunction

A New Tool for CME Arrival Time Prediction using Machine Learning Algorithms: CAT-PUMA

Coronal mass ejections (CMEs) are arguably the most violent eruptions in the solar system. CMEs can cause severe disturbances in interplanetary space and can even affect human activities in many aspects, causing damage to infrastructure and loss of revenue. Fast and accurate prediction of CME arrival time is vital to minimize the disruption that CMEs may cause when interacting with geospace. In this paper, we propose a new approach for partial-/full halo CME Arrival Time Prediction Using Machine learning Algorithms (CAT-PUMA). Via detailed analysis of the CME features and solar-wind parameters, we build a prediction engine taking advantage of 182 previously observed geo-effective partial-/full halo CMEs and using algorithms of the Support Vector Machine. We demonstrate that CAT-PUMA is accurate and fast. In particular, predictions made after applying CAT-PUMA to a test set unknown to the engine show a mean absolute prediction error of ∼5.9 hr within the CME arrival time, with 54% of the predictions having absolute errors less than 5.9 hr. Comparisons with other models reveal that CAT-PUMA has a more accurate prediction for 77% of the events investigated that can be carried out very quickly, i.e., within minutes of providing the necessary input parameters of a CME. A practical guide containing the CAT-PUMA engine and the source code of two examples are available in the Appendix, allowing the community to perform their own applications for prediction using CAT-PUMA

A Mutation in Intracellular Loop 4 Affects the Drug-Efflux Activity of the Yeast Multidrug Resistance ABC Transporter Pdr5p

Multidrug resistance protein Pdr5p is a yeast ATP-binding cassette (ABC) transporter in the plasma membrane. It confers multidrug resistance by active efflux of intracellular drugs. However, the highly polymorphic Pdr5p from clinical strain YJM789 loses its ability to expel azole and cyclohexmide. To investigate the role of amino acid changes in this functional change, PDR5 chimeras were constructed by segmental replacement of homologous BY4741 PDR5 fragments. Functions of PDR5 chimeras were evaluated by fluconazole and cycloheximide resistance assays. Their expression, ATPase activity, and efflux efficiency for other substrates were also analyzed. Using multiple lines of evidence, we show that an alanine-to-methionine mutation at position 1352 located in the predicted short intracellular loop 4 significantly contributes to the observed transport deficiency. The degree of impairment is likely correlated to the size of the mutant residue

Coronavirus Papain-like Proteases Negatively Regulate Antiviral Innate Immune Response through Disruption of STING-Mediated Signaling

Viruses have evolved elaborate mechanisms to evade or inactivate the complex system of sensors and signaling molecules that make up the host innate immune response. Here we show that human coronavirus (HCoV) NL63 and severe acute respiratory syndrome (SARS) CoV papain-like proteases (PLP) antagonize innate immune signaling mediated by STING (stimulator of interferon genes, also known as MITA/ERIS/MYPS). STING resides in the endoplasmic reticulum and upon activation, forms dimers which assemble with MAVS, TBK-1 and IKKε, leading to IRF-3 activation and subsequent induction of interferon (IFN). We found that expression of the membrane anchored PLP domain from human HCoV-NL63 (PLP2-TM) or SARS-CoV (PLpro-TM) inhibits STING-mediated activation of IRF-3 nuclear translocation and induction of IRF-3 dependent promoters. Both catalytically active and inactive forms of CoV PLPs co-immunoprecipitated with STING, and viral replicase proteins co-localize with STING in HCoV-NL63-infected cells. Ectopic expression of catalytically active PLP2-TM blocks STING dimer formation and negatively regulates assembly of STING-MAVS-TBK1/IKKε complexes required for activation of IRF-3. STING dimerization was also substantially reduced in cells infected with SARS-CoV. Furthermore, the level of ubiquitinated forms of STING, RIG-I, TBK1 and IRF-3 are reduced in cells expressing wild type or catalytic mutants of PLP2-TM, likely contributing to disruption of signaling required for IFN induction. These results describe a new mechanism used by CoVs in which CoV PLPs negatively regulate antiviral defenses by disrupting the STING-mediated IFN induction

Antagonistic Changes in Sensitivity to Antifungal Drugs by Mutations of an Important ABC Transporter Gene in a Fungal Pathogen

Fungal pathogens can be lethal, especially among immunocompromised populations, such as patients with AIDS and recipients of tissue transplantation or chemotherapy. Prolonged usage of antifungal reagents can lead to drug resistance and treatment failure. Understanding mechanisms that underlie drug resistance by pathogenic microorganisms is thus vital for dealing with this emerging issue. In this study, we show that dramatic sequence changes in PDR5, an ABC (ATP-binding cassette) efflux transporter protein gene in an opportunistic fungal pathogen, caused the organism to become hypersensitive to azole, a widely used antifungal drug. Surprisingly, the same mutations conferred growth advantages to the organism on polyenes, which are also commonly used antimycotics. Our results indicate that Pdr5p might be important for ergosterol homeostasis. The observed remarkable sequence divergence in the PDR5 gene in yeast strain YJM789 may represent an interesting case of adaptive loss of gene function with significant clinical implications