Abstract: Objective: We aim to investigate if anatomical and functional properties of the upper airway using computerized 3D models derived from computed tomography (CT) scans better predict obstructive sleep apnea (OSA) severity than standard clinical markers. Methods: Consecutive children with suspected OSA underwent polysomnography, clinical assessment of upper airway patency, and a CT scan while awake. A three-dimensional (3D) reconstruction of the pharyngeal airway was built from these images, and computational fluid dynamics modeling of low inspiratory flow was performed using open-source software. Results: Thirty-three children were included (23 boys; mean age, was 6.0 +/- 3.2 y). OSA was diagnosed in 23 patients. Children with OSA had a significantly lower volume of the overlap region between tonsils and the adenoids (median volume, 1408 mm compared to 2173 mm; p = 0.04), a lower mean cross-sectional area at this location (median volume, 69.3 mm(2) compared to 114.3 mm(2); p = 0.04), and a lower minimal cross-sectional area (median volume, 17.9 mm(2) compared to 25.9 mm(2); p = 0.05). Various significant correlations were found between several imaging parameters and the severity of OSA, most pronounced for upper airway conductance (r = -0.46) (p < 0.01) for correlation between upper airway conductance and the apnea-hypopnea index. No differences or significant correlations were observed with clinical parameters of upper airway patency. Preliminary data after treatment showed that none of the patients with residual OSA had their smallest cross-sectional area located in segment 3, and this frequency was significantly lower than in their peers whose sleep study normalized (64%; p = 0.05). Conclusion: Functional imaging parameters are highly correlated with OSA severity and are a more powerful correlate than clinical scores of upper airway patency. Preliminary data also showed that we could identify differences in the upper airway of those subjects who did not benefit from a local upper airway treatment. (c) 2013 Elsevier B.V. All rights reserved.

Abstract: Computational fluid dynamics (CFD) is increasingly applied in the respiratory domain. The ability to simulate the flow through a bifurcating tubular system has increased the insight into the internal flow dynamics and the particular characteristics of respiratory flows such as secondary motions and inertial effects. The next step in the evolution is to apply the technique to patient-specific cases, in order to provide more information about pathological airways. This study presents a patient-specific approach where both the geometry and the boundary conditions (BC) are based on individual imaging methods using computed tomography (CT). The internal flow distribution of a 73-year-old female suffering from chronic obstructive pulmonary disease (COPD) is assessed. The validation is performed through the comparison of lung ventilation with gamma scintigraphy. The results show that in order to obtain agreement within the accuracy limits of the gamma scintigraphy scan, both the patient-specific geometry and the BC (driving pressure) play a crucial role. A minimal invasive test (CT scan) supplied enough information to perform an accurate CFD analysis. In the end it was possible to capture the pathological features of the respiratory system using the imaging and computational fluid dynamics techniques. This brings the introduction of this new technique in the clinical practice one step closer.

Abstract: We introduce a Bayesian genetic algorithm for reconstructing atomic models of monotype crystalline nanoparticles from a single projection using Z-contrast imaging. The number of atoms in a projected atomic column obtained from annular dark field scanning transmission electron microscopy images serves as an input for the initial three-dimensional model. The algorithm minimizes the energy of the structure while utilizing a priori information about the finite precision of the atom-counting results and neighbor-mass relations. The results show promising prospects for obtaining reliable reconstructions of beam-sensitive nanoparticles during dynamical processes from images acquired with sufficiently low incident electron doses.

Abstract: Statistical parameter estimation theory is proposed as a quantitative method to measure unknown structure parameters from electron microscopy images. Images are then purely considered as data planes from which structure parameters have to be determined as accurately and precisely as possible using a parametric statistical model of the observations. For this purpose, an efficient algorithm is proposed for the estimation of atomic column positions and intensities from high angle annular dark field (HAADF) scanning transmission electron microscopy (STEM) images. Furthermore, the so-called CramérRao lower bound (CRLB) is reviewed to determine the limits to the precision with which continuous parameters such as atomic column positions and intensities can be estimated. Since this lower bound can only be derived for continuous parameters, alternative measures using the principles of detection theory are introduced for problems concerning the estimation of discrete parameters such as atomic numbers. An experimental case study is presented to show the practical use of these measures for the optimization of the experiment design if the purpose is to decide between the presence of specific atom types using STEM images.

Abstract: A new methodology is presented to count the number of atoms in multimetallic nanocrystals by combining energy dispersive X-ray spectroscopy (EDX) and high angle annular dark field scanning transmission electron microscopy (HAADF STEM). For this purpose, the existence of a linear relationship between the incoherent HAADF STEM and EDX images is exploited. Next to the number of atoms for each element in the atomic columns, the method also allows quantification of the error in the obtained number of atoms, which is of importance given the noisy nature of the acquired EDX signals. Using experimental images of an Au@Ag core–shell nanorod, it is demonstrated that 3D structural information can be extracted at the atomic scale. Furthermore, simulated data of an Au@Pt core–shell nanorod show the prospect to characterize heterogeneous nanostructures with adjacent atomic numbers.

Abstract: Background: Previous studies have demonstrated the potential beneficial effect of N-acetylcysteine (NAC) in chronic obstructive pulmonary disease (COPD). However, the required dose and responder phenotype remain unclear. The current study investigated the effect of high-dose NAC on airway geometry, inflammation, and oxidative stress in COPD patients. Novel functional respiratory imaging methods combining multislice computed tomography images and computer-based flow simulations were used with high sensitivity for detecting changes induced by the therapy. Methods: Twelve patients with Global Initiative for Chronic Obstructive Lung Disease stage II COPD were randomized to receive NAC 1800 mg or placebo daily for 3 months and were then crossed over to the alternative treatment for a further 3 months. Results: Significant correlations were found between image-based resistance values and glutathione levels after treatment with NAC (P = 0.011) and glutathione peroxidase at baseline (P = 0.036). Image-based resistance values appeared to be a good predictor for glutathione peroxidase levels after NAC (P = 0.02), changes in glutathione peroxidase levels (P = 0.035), and reduction in lobar functional residual capacity levels (P = 0.00084). In the limited set of responders to NAC therapy, the changes in airway resistance were in the same order as changes induced by budesonide/formoterol. Conclusion: A combination of glutathione, glutathione peroxidase, and imaging parameters could potentially be used to phenotype COPD patients who would benefit from addition of NAC to their current therapy. The findings of this small pilot study need to be confirmed in a larger pivotal trial.

Abstract: In the present paper, the optimal detector design is investigated for both detecting and locating light atoms from high resolution scanning transmission electron microscopy (HR STEM) images. The principles of detection theory are used to quantify the probability of error for the detection of light atoms from HR STEM images. To determine the optimal experiment design for locating light atoms, use is made of the so-called Cramer-Rao Lower Bound (CRLB). It is investigated if a single optimal design can be found for both the detection and location problem of light atoms. Furthermore, the incoming electron dose is optimised for both research goals and it is shown that picometre range precision is feasible for the estimation of the atom positions when using an appropriate incoming electron dose under the optimal detector settings to detect light atoms.

Abstract: Aberration correction in scanning transmission electron microscopy (STEM) has greatly improved the lateral and depth resolution. When using depth sectioning, a technique during which a series of images is recorded at different defocus values, single impurity atoms can be visualised in three dimensions. In this paper, we investigate new possibilities emerging when combining depth sectioning and precise atom-counting in order to reconstruct nanosized particles in three dimensions. Although the depth resolution does not allow one to precisely locate each atom within an atomic column, it will be shown that the depth location of an atomic column as a whole can be measured precisely. In this manner, the morphology of a nanoparticle can be reconstructed in three dimensions. This will be demonstrated using simulations and experimental data of a gold nanorod.

Abstract: Melanoma arises from pigment-producing cells called melanocytes located in the basal layers of the epidermis of the skin. Cytoglobin (CYGB) is a ubiquitously expressed hexacoordinated globin that is highly enriched in me­lanocytes and frequently downregulated during melanomagenesis. Previously, we showed that non-thermal plasma (NTP)-produced reactive oxygen and nitrogen species (RONS) lead to the formation of an intra­ molecular disulfide bridge that would allow CYGB to function as a redox-sensitive protein. Here, we investigate the cytotoxic effect of indirect NTP treatment in two melanoma cell lines with divergent endogenous CYGB expression levels, and we explore the role of CYGB in determining treatment outcome. Our findings are consistent with previous studies supporting that NTP cytotoxicity is mediated through the production of RONS and leads to apoptotic cell death in melanoma cells. Furthermore, we show that NTP-treated solutions elicit an antioxidant response through the activation of nuclear factor erythroid 2–related factor 2 (NRF2). The knock­ down and overexpression of CYGB respectively sensitizes and protects melanoma cells from RONS-induced apoptotic cell death. The presence of CYGB enhances heme-oxygenase 1 (HO-1) and NRF2 protein expression levels, whereas the absence impairs their expression. Moreover, analysis of the CYGB-dependent transcriptome demonstrates the tumor suppressor long non-coding RNA maternally expressed 3 (MEG3) as a hitherto unde­ scribed link between CYGB and NRF2. Thus, the presence of CYGB, at least in melanoma cells, seems to play a central role in determining the therapeutic outcome of RONS-inducing anticancer therapies, like NTP-treated solutions, possessing both tumor-suppressive and oncogenic features. Hence, CYGB expression could be of in­ terest either as a biomarker or as a candidate for future targeted therapies in melanoma.

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, 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: In this work, a recently developed quantitative approach based on the principles of detection theory is used in order to determine the possibilities and limitations of High Resolution Scanning Transmission Electron Microscopy (HR STEM) and HR TEM for atom-counting. So far, HR STEM has been shown to be an appropriate imaging mode to count the number of atoms in a projected atomic column. Recently, it has been demonstrated that HR TEM, when using negative spherical aberration imaging, is suitable for atom-counting as well. The capabilities of both imaging techniques are investigated and compared using the probability of error as a criterion. It is shown that for the same incoming electron dose, HR STEM outperforms HR TEM under common practice standards, i.e. when the decision is based on the probability function of the peak intensities in HR TEM and of the scattering cross-sections in HR STEM. If the atom-counting decision is based on the joint probability function of the image pixel values, the dependence of all image pixel intensities as a function of thickness should be known accurately. Under this assumption, the probability of error may decrease significantly for atom-counting in HR TEM and may, in theory, become lower as compared to HR STEM under the predicted optimal experimental settings. However, the commonly used standard for atom-counting in HR STEM leads to a high performance and has been shown to work in practice.

Abstract: To understand the structure–property relationship of nanostructures, reliably quantifying parameters, such as the number of atoms along the projection direction, is important. Advanced statistical methodologies have made it possible to count the number of atoms for monotype crystalline nanoparticles from a single ADF STEM image. Recent developments enable one to simultaneously acquire multiple ADF STEM images. Here, we present an extended statistics-based method for atom counting from a combination of multiple statistically independent ADF STEM images reconstructed from non-overlapping annular detector collection regions which improves the accuracy and allows one to retrieve precise atom-counts, especially for images acquired with low electron doses and multiple element structures.