Abstract: Background: Inhaled formulations using extrafine particles of long-acting beta(2)-agonists and corticosteroids were developed to optimize asthma treatment. Findings that these combinations reach and treat smaller airways more effectively are predominantly based on general non-specific outcomes with little information on regional characteristics. Objectives: This study aims to assess long-term effects of extrafine beclomethasone/formoterol on small airways of asthmatic patients using novel functional imaging methods. Methods: Twenty-four stable asthma patients were subdivided into three groups (steroid naive, n = 7; partially controlled, n = 6; well controlled, n = 11). Current treatment was switched to a fixed combination of extrafine beclomethasone/formoterol (Foster (R); Chiesi Pharmaceuticals, Parma, Italy). Patients underwent lung function evaluation and thorax high-resolution computerized tomography (HRCT) scan. Local airway resistance was obtained from computational fluid dynamics (CFD). Results: After 6 months, the entire population showed improvement in pre-bronchodilation imaging parameters, including small airway volume (p = 0.0007), resistance (p = 0.011), and asthma control score (p = 0.016). Changes in small airway volume correlated with changes in asthma control score (p = 0.004). Forced expiratory volume in 1 s (p = 0.044) and exhaled nitric oxide (p = 0.040) also improved. Functional imaging provided more detail and clinical relevance compared to lung function tests, especially in the well-controlled group where only functional imaging parameters showed significant improvement, while the correlation with asthma control score remained. Conclusions: Extrafine beclomethasone/formoterol results in a significant reduction of small airway obstruction, detectable by functional imaging (HRCT/CFD). Changes in imaging parameters correlated significantly with clinically relevant improvements. This indicates that functional imaging is a useful tool for sensitive assessment of changes in the respiratory system after asthma treatment. Copyright (C) 2013 S. Karger AG, Basel

Abstract: The agri-food value chain is a major cause of nitrogen (N) and phosphorus (P) emissions and associated environmental and health impacts. The EU's farm-to-fork strategy (F2F) demands an agri-food value chain approach to reduce nutrient emissions by 50% and fertilizer use by 20%. Substance flow analysis (SFA) is a method that can be applied to study complex systems such as the agri-food chain. A review of 60 SFA studies shows that they often lack detail by not sufficiently distinguishing between nodes, products and types of emissions. The present study aims to assess the added value of detail in SFAs and to illustrate that valuable indicators can be derived from detailed assessments. This aim will be attained by presenting a highly-detailed SFA for the livestock-intensive region of Flanders, Belgium. The SFA distinguishes 40 nodes and 1827 flows that are classified into eight different categories (e.g. by-products, point source emissions) following life cycle methods. Eight novel indicators were calculated, including indicators that assess the N and P recovery potential. Flanders has a low overall nutrient use efficiency (11% N, 18% P). About 55% of the N and 56% of the P embedded in recoverable streams are reused providing 35% and 37% of the total N and P input. Optimized nutrient recycling could replace 45% of N and 48% of P of the external nutrient input, exceeding the target set by the F2F strategy. Detailed accounting for N and P flows and nodes leads to the identification of more recoverable streams and larger N and P flows. More detailed flow accounting is a prerequisite for the quantification of technological intervention options. Future research should focus on including concentration and quality as a parameter in SFAs.

Abstract: In this paper, two types of melanoma and glioblastoma cancer cell lines are treated with cold atmospheric plasma to assess the effect of several parameters on the cell viability. The cell viability decreases with treatment duration and time until analysis in all cell lines with varying sensitivity. The majority of dead cells stains both AnnexinV (AnnV) and propidium iodide, indicating that the plasma-treated non-viable cells are mostly late apoptotic or necrotic. Genetic mutations might be involved in the response to plasma. Comparing the effects of two gas mixtures, as well as indirect plasma-activated medium versus direct treatment, gives different results per cell line. In conclusion, this study confirms the potential of plasma for cancer therapy and emphasizes the influence of experimental parameters on therapeutic outcome.

Abstract: Ru catalysts are part of a set of late transition metal nanocatalysts that have garnered much interest for catalytic applications such as ammonia synthesis and fuel cell production. Their performance varies greatly depending on their morphology and size, these catalysts are widely studied using electron microscopy. Using recent developments in Annular Dark Field (ADF) Scanning Transmission Electron Microscopy (STEM) quantification techniques, a rapid atom counting procedure was utilized to document the evolution of a heterogeneous Ru catalyst supported on carbon black. Areas of the catalyst were imaged for approximately 15 minutes using ADF STEM. When the Ru clusters were exposed to the electron beam, the clusters changed phase from amorphous to crystalline. To quantify the thickness of the crystalline clusters, two techniques were applied (simulation and statistical decomposition) and compared. These techniques show that stable face centredcubic crystal structures in the form of rafts, between 2 and 8 atoms thick, were formed after the initial wetting of the carbon support.

Abstract: In two subjects with a unilateral diaphragmatic paralysis and complaints of dyspnea, a completely different treatment approach was chosen despite similar anatomical and physiological abnormalities. These decisions were supported by the results generated by Functional Respiratory Imaging (FRI). FRI was able to generate functional information with respect to lobar ventilation and local drug deposition. In one subject, it was found that some lobes were poorly ventilated and drug deposition simulation showed that some regions were undertreated. This subject underwent a diaphragm plication to restore the ventilation. In the other subject, it was found that all lobes were still ventilated. A conservative approach with regular follow-up was chosen to wait for spontaneous recovery of the diaphragmatic function. Both subjects improved subjectively and objectively. These cases demonstrate how novel medical imaging techniques such as FRI can be used to personalize respiratory treatment in subjects with unilateral diaphragmatic paralysis.

Abstract: The obstructive sleep apnea-hypopnea syndrome (OSAHS) is a sleep related breathing disorder. A popular treatment is the use of a mandibular repositioning appliance (MRA) which advances the mandibula during the sleep and decreases the collapsibility of the upper airway. The success rate of such a device is, however, limited and very variable within a population of patients. Previous studies using computational fluid dynamics have shown that there is a decrease in upper airway resistance in patients who improve clinically due to an MRA. In this article, correlations between patient-specific anatomical and functional parameters are studied to examine how MRA induced biomechanical changes will have an impact on the upper airway resistance. Low-dose computed tomography (CT) scans are made from 143 patients suffering from OSAHS. A baseline scan and a scan after mandibular repositioning (MR) are performed in order to study variations in parameters. It is found that MR using a simulation bite is able to induce resistance changes by changing the pharyngeal lumen. The change in minimal cross-sectional area is the best parameter to predict the change in upper airway resistance. Looking at baseline values, the ideal patients for MR induced resistance decrease seem to be women with short airways, high initial resistance and no baseline occlusion.

Abstract: Energy filtered TEM, EFTEM, provides three-dimensional data, two spatial and one spectral dimension. We propose to acquire these data by measuring a series of images with a defocused energy filter. It will be shown that each image is a projection of the data on the detector and that reconstruction of the data out of a sufficient number of such projections using a tomographic reconstruction algorithm is possible. This technique uses only a fraction of the electron dose an energy filtered series (EFS) needs for the same spectral and spatial resolution and the same mean signal-to-noise ratio. (c) 2005 Elsevier B.V. All rights reserved.

Abstract: The atomic lensing model has been proposed as a promising method facilitating atom-counting in heterogeneous nanocrystals [1]. Here, image simulations will validate the model, which describes dynamical diffraction as a superposition of individual atoms focussing the incident electrons. It will be demonstrated that the model is reliable in the annular dark field regime for crystals having columns containing dozens of atoms. By using the principles of statistical detection theory, it will be shown that this model gives new opportunities for detecting compositional differences.

Abstract: We report a method to reliably count the number of atoms from high-angle annular dark field scanning transmission electron microscopy images. A model-based analysis of the experimental images is used to measure scattering cross sections at the atomic level. The high sensitivity of these measurements in combination with a thorough statistical analysis enables us to count atoms with single-atom sensitivity. The validity of the results is confirmed by means of detailed image simulations. We will show that the method can be applied to nanocrystals of arbitrary shape, size, and atom type without the need for a priori knowledge about the atomic structure.

Abstract: Understanding nanostructures down to the atomic level is the key to optimizing the design of advancedmaterials with revolutionary novel properties. This requires characterization methods capable of quantifying the three-dimensional (3D) atomic structure with the highest possible precision. A successful approach to reach this goal is to count the number of atoms in each atomic column from 2D annular dark field scanning transmission electron microscopy images. To count atoms with single atom sensitivity, a minimum electron dose has been shown to be necessary, while on the other hand beam damage, induced by the high energy electrons, puts a limit on the tolerable dose. An important challenge is therefore to develop experimental strategies to optimize the electron dose by balancing atom-counting fidelity vs the risk of knock-on damage. To achieve this goal, a statistical framework combined with physics-based modeling of the dose-dependent processes is here proposed and experimentally verified. This model enables an investigator to theoretically predict, in advance of an experimental measurement, the optimal electron dose resulting in an unambiguous quantification of nanostructures in their native state with the highest attainable precision.

Abstract: In this paper, a methodology is presented to count the number of atoms in heterogeneous nanoparticles based on the combination of multiple annular dark field scanning transmission electron microscopy (ADF STEM) images. The different non-overlapping annular detector collection regions are selected based on the principles of optimal statistical experiment design for the atom-counting problem. To count the number of atoms, the total intensities of scattered electrons for each atomic column, the so-called scattering cross-sections, are simultaneously compared with simulated library values for the different detector regions by minimising the squared differences. The performance of the method is evaluated for simulated Ni@Pt and Au@Ag core-shell nanoparticles. Our approach turns out to be a dose efficient alternative for the investigation of beam-sensitive heterogeneous materials as compared to the combination of ADF STEM and energy dispersive X-ray spectroscopy.

Abstract: The present contribution gives a review of recent quantification work of atom displacements, atom site occupations and level of crystallinity in various systems and based on aberration corrected HR(S)TEM images. Depending on the case studied, picometer range precisions for individual distances can be obtained, boundary widths at the unit cell level determined or statistical evolutions of fractions of the ordered areas calculated. In all of these cases, these quantitative measures imply new routes for the applications of the respective materials.

Abstract: High angle annular dark field scanning transmission electron microscopy (HAADF STEM) images provide sample information which is sensitive to the chemical composition. The image intensities indeed scale with the mean atomic number Z. To some extent, chemically different atomic column types can therefore be visually distinguished. However, in order to quantify the atomic column composition with high accuracy and precision, model-based methods are necessary. Therefore, an empirical incoherent parametric imaging model can be used of which the unknown parameters are determined using statistical parameter estimation theory (Van Aert et al., 2009, [1]). In this paper, it will be shown how this method can be combined with frozen lattice multislice simulations in order to evolve from a relative toward an absolute quantification of the composition of single atomic columns with mixed atom types. Furthermore, the validity of the model assumptions are explored and discussed.

Abstract: Quantitative structural and chemical information can be obtained from high angle annular dark field scanning transmission electron microscopy (HAADF STEM) images when using statistical parameter estimation theory. In this approach, we assume an empirical parameterized imaging model for which the total scattered intensities of the atomic columns are estimated. These intensities can be related to the material structure or composition. Since the experimental probe profile is assumed to be known in the description of the imaging model, we will explore how the uncertainties in the probe profile affect the estimation of the total scattered intensities. Using multislice image simulations, we analyze this effect for Cs corrected and non-Cs corrected microscopes as a function of inaccuracies in cylindrically symmetric aberrations, such as defocus and spherical aberration of third and fifth order, and non-cylindrically symmetric aberrations, such as 2-fold and 3-fold astigmatism and coma.

Abstract: Au nanoparticles (NPs) deposited on CeO2 are extensively used as thermal catalysts since the morphology of the NPs is expected to be stable at elevated temperatures. Although it is well known that the activity of Au NPs depends on their size and surface structure, their three-dimensional (3D) structure at the atomic scale has not been completely characterized as a function of temperature. In this paper, we overcome the limitations of conventional electron tomography by combining atom counting applied to aberration-corrected scanning transmission electron microscopy images and molecular dynamics relaxation. In this manner, we are able to perform an atomic resolution 3D investigation of supported Au NPs. Our results enable us to characterize the 3D equilibrium structure of single NPs as a function of temperature. Moreover, the dynamic 3D structural evolution of the NPs at high temperatures, including surface layer jumping and crystalline transformations, has been studied.