Cell surface antigen expression by peripheral blood monocytes in allergic asthma: results of 2.5 years therapy with inhaled beclomethasone dipropionate

At present, inhaled glucocorticoids are widely accepted as the therapy of choice in chronic asthma. Treatment with inhaled glucocorticoids significantly suppresses local airway inflammation in asthmatics, but may also have systemic effects, e.g. a reduction of the number of circulating hypodense eosinophils or a down-modulation of HLA-DR antigen (Ag) expression by T lymphocytes in peripheral blood. However, the effect of long-term therapy with inhaled glucocorticoids on peripheral blood monocytes (PBM), which are the precursors of the most numerous cell type in the lung, the alveolar macrophage, have not yet been evaluated. We therefore investigated the expression of various cell surface Ag on PBM from non-smoking patients with allergic asthma who were treated for 2.5 years with a β2-receptor agonist plus either an inhaled glucocorticoid (beclomethasone dipropionate, BDP) (n = 4) or an anticholinergic or placebo (n = 8). We compared the results with healthy volunteers (n = 7). Long-term treatment of allergic asthmatics with inhaled BDP, but not anticholinergic or placebo therapy, was associated with a significantly lower CDllb Ag expression (p < 0.04) and higher expression of CD13, CD14 and CD18 Ag (p < 0.05, p < 0.02 and p < 0.04, respectively) when compared with the healthy control subjects (n = 7). Most interestingly, PBM of asthmatics treated with inhaled BDP expressed an almost two-fold higher level of CD14 Ag on their cell surface than PBM of patients treated with anticholinergic or placebo (p < 0.03). No significant differences in the expression of CD16, CD23, CD25, CD32 and CD64 Ag or HLA-DR were observed between PBM from the different patient groups or healthy controls. Taken together, this study shows that long-term local therapy with inhaled BDP coincides with an altered expression of at least one cell surface Ag on PBM from allergic asthmatics

First-principles extrapolation method for accurate CO adsorption energies on metal surfaces

We show that a simple first-principles correction based on the difference between the singlet-triplet CO excitation energy values obtained by DFT and high-level quantum chemistry methods yields accurate CO adsorption properties on a variety of metal surfaces. We demonstrate a linear relationship between the CO adsorption energy and the CO singlet-triplet splitting, similar to the linear dependence of CO adsorption energy on the energy of the CO 2$\pi$* orbital found recently {[Kresse {\em et al.}, Physical Review B {\bf 68}, 073401 (2003)]}. Converged DFT calculations underestimate the CO singlet-triplet excitation energy $\Delta E_{\rm S-T}$, whereas coupled-cluster and CI calculations reproduce the experimental $\Delta E_{\rm S-T}$. The dependence of $E_{\rm chem}$ on $\Delta E_{\rm S-T}$ is used to extrapolate $E_{\rm chem}$ for the top, bridge and hollow sites for the (100) and (111) surfaces of Pt, Rh, Pd and Cu to the values that correspond to the coupled-cluster and CI $\Delta E_{\rm S-T}$ value. The correction reproduces experimental adsorption site preference for all cases and obtains $E_{\rm chem}$ in excellent agreement with experimental results.Comment: Table sent as table1.eps. 3 figure

A decision aid to rule out pneumonia and reduce unnecessary prescriptions of antibiotics in primary care patients with cough and fever

BACKGROUND: Physicians fear missing cases of pneumonia and treat many patients with signs of respiratory infection unnecessarily with antibiotics. This is an avoidable cause for the increasing worldwide problem of antibiotic resistance. We developed a user-friendly decision aid to rule out pneumonia and thus reduce the rate of needless prescriptions of antibiotics. METHODS: This was a prospective cohort study in which we enrolled patients older than 18 years with a new or worsened cough and fever without serious co-morbidities. Physicians recorded results of a standardized medical history and physical examination. C-reactive protein was measured and chest radiographs were obtained. We used Classification and Regression Trees to derive the decision tool. RESULTS: A total of 621 consenting eligible patients were studied, 598 were attending a primary care facility, were 48 years on average and 50% were male. Radiographic signs for pneumonia were present in 127 (20.5%) of patients. Antibiotics were prescribed to 234 (48.3%) of patients without pneumonia. In patients with C-reactive protein values below 10 μg/ml or patients presenting with C-reactive protein between 11 and 50 μg/ml, but without dyspnoea and daily fever, pneumonia can be ruled out. By applying this rule in clinical practice antibiotic prescription could be reduced by 9.1% (95% confidence interval (CI): 6.4 to 11.8). CONCLUSIONS: Following validation and confirmation in new patient samples, this tool could help rule out pneumonia and be used to reduce unnecessary antibiotic prescriptions in patients presenting with cough and fever in primary care. The algorithm might be especially useful in those instances where taking a medical history and physical examination alone are inconclusive for ruling out pneumonia

Potential impact of a new sepsis prediction model for the primary care setting: early health economic evaluation using an observational cohort

OBJECTIVES: To estimate the potential referral rate and cost impact at different cut-off points of a recently developed sepsis prediction model for general practitioners (GPs). DESIGN: Prospective observational study with decision tree modelling. SETTING: Four out-of-hours GP services in the Netherlands. PARTICIPANTS: 357 acutely ill adult patients assessed during home visits. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome is the cost per patient from a healthcare perspective in four scenarios based on different cut-off points for referral of the sepsis prediction model. Second, the number of hospital referrals for the different scenarios is estimated. The potential impact of referral of patients with sepsis on mortality and hospital admission was estimated by an expert panel. Using these study data, a decision tree with a time horizon of 1 month was built to estimate the referral rate and cost impact in case the model would be implemented. RESULTS: Referral rates at a low cut-off (score 2 or 3 on a scale from 0 to 6) of the prediction model were higher than observed for patients with sepsis (99% and 91%, respectively, compared with 88% observed). However, referral was also substantially higher for patients who did not need hospital assessment. As a consequence, cost-savings due to referral of patients with sepsis were offset by increased costs due to unnecessary referral for all cut-offs of the prediction model. CONCLUSIONS: Guidance for referral of adult patients with suspected sepsis in the primary care setting using any cut-off point of the sepsis prediction model is not likely to save costs. The model should only be incorporated in sepsis guidelines for GPs if improvement of care can be demonstrated in an implementation study. TRIAL REGISTRATION NUMBER: Dutch Trial Register (NTR 7026)

Quantification of lateral repulsion between coadsorbed CO and N on Rh(100) using temperature-programmed desorption, low-energy electron diffraction, and Monte Carlo simulations

Temp. programmed desorption of CO coadsorbed with at. N on Rh(100), reveals both long- and short-range interactions between adsorbed CO and N. For CO desorption from Rh(100) at low coverage we find an activation energy Ea of 137+-2 kJ/mol and a preexponential factor of 1013.8+-0.2 s-1. Coadsorption with N partially blocks CO adsorption and destabilizes CO by lowering Ea for CO desorption. Destabilization at low N coverage is explained by long-range electronic modification of the Rh(100) surface. At high N and CO coverage, we find evidence for a short-range repulsive lateral interaction between COads and Nads in neighboring positions. We derive a pairwise repulsive interaction wCO-NNN=19 kJ/mol for CO coadsorbed to a c(2*2) arrangement of N atoms. This has important implications for the lateral distribution of coadsorbed CO and N at different adsorbate coverages. Regarding the different lateral interactions and mobility of adsorbates, we propose a structural model which satisfactorily explains the obsd. effects of at. N on the desorption of CO. Dynamic Monte Carlo simulations were used to verify the exptl. obtained value for the CO-N interaction, by using the kinetic parameters and interaction energy derived from the temp.-programmed desorption expts. [on SciFinder (R)