Abstract: Quantitative atomic resolution annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique for nanoparticle atom-counting. However, a lot of nanoparticles provide a severe characterisation challenge because of their limited size and beam sensitivity. Therefore, quantitative ADF STEM may greatly benefit from statistical detection theory in order to optimise the instrumental microscope settings such that the incoming electron dose can be kept as low as possible whilst still retaining single-atom precision. The principles of detection theory are used to quantify the probability of error for atom-counting. This enables us to decide between different image performance measures and to optimise the experimental detector settings for atom-counting in ADF STEM in an objective manner. To demonstrate this, ADF STEM imaging of an industrial catalyst has been conducted using the near-optimal detector settings. For this experiment, we discussed the limits for atom-counting diagnosed by combining a thorough statistical method and detailed image simulations.

Abstract: Quantification of annular dark field (ADF) scanning transmission electron microscopy (STEM) images in terms
of composition or thickness often relies on probe-position integrated scattering cross sections (PPISCS). In
order to compare experimental PPISCS with theoretically predicted ones, expensive simulations are needed for
a given specimen, zone axis orientation, and a variety of microscope settings. The computation time of such
simulations can be in the order of hours using a single GPU card. ADF STEM simulations can be efficiently
parallelized using multiple GPUs, as the calculation of each pixel is independent of other pixels. However, most
research groups do not have the necessary hardware, and, in the best-case scenario, the simulation time will
only be reduced proportionally to the number of GPUs used. In this manuscript, we use a learning approach and
present a densely connected neural network that is able to perform real-time ADF STEM PPISCS predictions as
a function of atomic column thickness for most common face-centered cubic (fcc) crystals (i.e., Al, Cu, Pd, Ag,
Pt, Au and Pb) along [100] and [111] zone axis orientations, root-mean-square displacements, and microscope
parameters. The proposed architecture is parameter efficient and yields accurate predictions for the PPISCS
values for a wide range of input parameters that are commonly used for aberration-corrected transmission
electron microscopes.

Abstract: Pt nanoparticles play an essential role in a wide variety of catalytic reactions. The activity of the particles strongly depends on their three-dimensional (3D) structure and exposed facets, as well as on the reactive environment. High-resolution electron microscopy has often been used to characterize nanoparticle catalysts but unfortunately most observations so far have been either performed in vacuum and/or using conventional (2D) in situ microscopy. The latter however does not provide direct 3D morphological information. We have implemented a quantitative methodology to measure variations of the 3D atomic structure of nanoparticles under the flow of a selected gas. We were thereby able to quantify refaceting of Pt nanoparticles with atomic resolution during various oxidation−reduction cycles. In a H2 environment, a more faceted surface morphology of the particles was observed with {100} and {111} planes being dominant. On the other hand, in O2 the percentage of {100} and {111} facets decreased and a significant increase of higher order facets was found, resulting in a more rounded morphology. This methodology opens up new opportunities toward in situ characterization of catalytic nanoparticles because for the first time it enables one to directly measure 3D morphology variations at the atomic scale in a specific gaseous reaction environment.

Abstract: Over the last two decades, three-dimensional (3D) imaging by transmission electron microscopy or “electron tomography” has evolved into a powerful tool to investigate a variety of nanomaterials in different fields, such as life sciences, chemistry, solid-state physics, and materials science. Most of these results were obtained with nanometer-scale resolution, but different approaches have recently pushed the resolution to the atomic level. Such information is a prerequisite to understand the specific relationship between the atomic structure and the physicochemical properties of (nano) materials. We provide an overview of the latest progress in the field of atomic-resolution electron tomography. Different imaging and reconstruction approaches are presented, and state-of-the-art results are discussed. This article demonstrates the power and importance of electron tomography with atomic-scale resolution.

Abstract: Oriented attachment of PbSe nanocubes can result in the formation of two-dimensional (2D) superstructures with long-range nanoscale and atomic order. This questions the applicability of classic models in which the superlattice grows by first forming a nucleus, followed by sequential irreversible attachment of nanocrystals, as one misaligned attachment would disrupt the 2D order beyond repair. Here, we demonstrate the formation mechanism of 2D PbSe superstructures with square geometry by using in situ grazing-incidence X-ray scattering (small angle and wide angle), ex situ electron microscopy, and Monte Carlo simulations. We observed nanocrystal adsorption at the liquid/gas interface, followed by the formation of a hexagonal nanocrystal monolayer. The hexagonal geometry transforms gradually through a pseudo-hexagonal phase into a phase with square order, driven by attractive interactions between the {100} planes perpendicular to the liquid substrate, which maximize facet-to-facet overlap. The nanocrystals then attach atomically via a necking process, resulting in 2D square superlattices.

Abstract: Non-thermal plasma (NTP) therapy has been emerging as a promising cancer treatment strategy, and recently, its ability to locally induce immunogenic cancer cell death is being unraveled. We hypothesized that the chemical species produced by NTP reduce immunosuppressive surface proteins and checkpoints that are overexpressed on cancerous cells. Here, 3D in vitro tumor models, an in vivo mouse model, and molecular dynamics simulations are used to investigate the effect of NTP on CD47, a key innate immune checkpoint. CD47 is immediately modulated after NTP treatment and simulations reveal the potential oxidized salt-bridges responsible for conformational changes. Umbrella sampling simulations of CD47 with its receptor, signal-regulatory protein alpha (SIRPα), demonstrate that the induced-conformational changes reduce its binding affinity. Taken together, this work provides new insight into fundamental, chemical NTP-cancer cell interaction mechanisms and a previously overlooked advantage of present NTP cancer therapy: reducing immunosuppressive signals on the surface of cancer cells.

Abstract: NADPH oxidases 1 (NOX1) derived reactive oxygen species (ROS) play an important role in the progression of cancer through signaling pathways. Therefore, in this paper, we demonstrate the effect of cold atmospheric plasma (CAP) on the structural changes of Noxa1 SH3 protein, one of the regulatory subunits of NOX1. For this purpose, firstly we purified the Noxa1 SH3 protein and analyzed the structure using X-ray crystallography, and subsequently, we treated the protein with two types of CAP reactors such as pulsed dielectric barrier discharge (DBD) and Soft Jet for different time intervals. The structural deformation of Noxa1 SH3 protein was analyzed by various experimental methods (circular dichroism, fluorescence, and NMR spectroscopy) and by MD simulations. Additionally, we demonstrate the effect of CAP (DBD and Soft Jet) on the viability and expression of NOX1 in A375 cancer cells. Our results are useful to understand the structural modification/oxidation occur in protein due to reactive oxygen and nitrogen (RONS) species generated by CAP.

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: Introduction: Noninvasive ventilation (NIV) is a well-established treatment for acute-on-chronic respiratory failure in hypercapnic COPD patients. Less is known about the effects of a long-term treatment with NIV in hypercapnic COPD patients and about the factors that may predict response in terms of improved oxygenation and lowered CO2 retention.Methods: In this study, we randomized 15 patients to a routine pharmacological treatment (n = 5, age 66 [standard deviation ± 6] years, FEV1 30.5 [±5.1] %pred, PaO2 65 [±6] mmHg, PaCO2 52.4 [±6.0] mmHg) or to a routine treatment and NIV (using the Synchrony BiPAP device [Respironics, Inc, Murrsville, PA]) (n = 10, age 65 [±7] years, FEV1 29.5 [±9.0] %pred, PaO2 59 [±13] mmHg, PaCO2 55.4 [±7.7] mmHg) for 6 months. We looked at arterial blood gasses, lung function parameters and performed a low-dose computed tomography of the thorax, which was later used for segmentation (providing lobe and airway volumes, iVlobe and iVaw) and post-processing with computer methods (providing airway resistance, iRaw) giving overall a functional image of the separate airways and lobes.Results: In both groups there was a nonsignificant change in FEV1 (NIV group 29.5 [9.0] to 38.5 [14.6] %pred, control group 30.5 [5.1] to 36.8 [8.7] mmHg). PaCO2 dropped significantly only in the NIV group (NIV: 55.4 [7.7] → 44.5 [4.70], P = 0.0076; control: 52.4 [6.0] → 47.6 [8.2], NS). Patients actively treated with NIV developed a more inhomogeneous redistribution of mass flow than control patients. Subsequent analysis indicated that in NIV-treated patients that improve their blood gases, mass flow was also redistributed towards areas with higher vessel density and less emphysema, indicating that flow was redistributed towards areas with better perfusion. There was a highly significant correlation between the % increase in mass flow towards lobes with a blood vessel density of >9% and the increase in PaO2. Improved ventilation–perfusion match and recruitment of previously occluded small airways can explain the improvement in blood gases.Conclusion: We can conclude that in hypercapnic COPD patients treated with long-term NIV over 6 months, a mass flow redistribution occurs, providing a better ventilation–perfusion match and hence better blood gases and lung function. Control patients improve homogeneously in iVaw and iRaw, without improvement in gas exchange since there is no improved ventilation/perfusion ratio or increased alveolar ventilation. These differences in response can be detected through functional imaging, which gives a more detailed report on regional lung volumes and resistances than classical lung function tests do. Possibly only patients with localized small airway disease are good candidates for long-term NIV treatment. To confirm this and to see if better arterial blood gases also lead to better health related quality of life and longer survival, we have to study a larger population.

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: In this paper, we investigate how precise atoms of a small nanocluster can ultimately be located in three dimensions (3D) from a tilt series of images acquired using annular dark field (ADF) scanning transmission electron microscopy (STEM). Therefore, we derive an expression for the statistical precision with which the 3D atomic position coordinates can be estimated in a quantitative analysis. Evaluating this statistical precision as a function of the microscope settings also allows us to derive the optimal experimental design. In this manner, the optimal angular tilt range, required electron dose, optimal detector angles, and number of projection images can be determined.

Abstract: In this paper, it has been investigated how to measure atom column positions as accurately and precisely as possible using a focal series of images. In theory, it is expected that the precision would considerably improve using a maximum likelihood estimator based on the full series of focal images. As such, the theoretical lower bound on the variances of the unknown atom column positions can be attained. However, this approach is numerically demanding. Therefore, maximum likelihood estimation has been compared with the results obtained by fitting a model to a reconstructed exit wave rather than to the full series of focal images. Hence, a real space model-based exit wave reconstruction technique based on the channelling theory is introduced. Simulations show that the reconstructed complex exit wave contains the same amount of information concerning the atom column positions as the full series of focal images. Only for thin samples, which act as weak phase objects, this information can be retrieved from the phase of the reconstructed complex exit wave.

Abstract: In this chapter, the principles of statistical parameter estimation theory for a quantitative analysis of atomic-resolution electron microscopy images are introduced. Within this framework, electron microscopy images are described by a parametric statistical model. Here, parametric models are introduced for different types of electron microscopy images: reconstructed exit waves, annular dark-field (ADF) scanning transmission electron microscopy (STEM) images, and simultaneously acquired ADF and annular bright-field (ABF) STEM images. Furthermore, the Cramér-Rao lower bound (CRLB) is introduced, i.e. a theoretical lower bound on the variance of any unbiased estimator. This CRLB is used to quantify the precision of the structure parameters of interest, such as the atomic column positions and the integrated atomic column intensities.

Abstract: In this chapter, a statistical model-based method to count the number of atoms of monotype crystalline nanostructures from high-resolution annular dark-field (ADF) scanning transmission electron microscopy (STEM) images is discussed in detail together with a thorough study on the possibilities and inherent limitations. We show that this method can be applied to nanocrystals of arbitrary shape, size, and atom type. The validity of the atom-counting results is confirmed by means of detailed image simulations and it is shown that the high sensitivity of our method enables us to count atoms with single atom sensitivity.

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.