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 atomcounting diagnosed by combining a thorough statistical method and detailed image simulations.

Abstract: Since its discovery 20 years ago, many studies have been performed to gain insight into the functional role of cytoglobin (Cygb). However, Cygb has been proven to be a promiscuous protein. Yet, there is a consensus that Cygb is a cytoprotective protein involved in redox homeostasis. CYGB is a ubiquitously expressed hexacoordinated globin that is highly expressed in melanocytes and is often found to be downregulated during melanocyte-to-melanoma transition. In Chapter III, we investigated the molecular mechanism through which CYGB could be involved in redox regulation. Here, we showed that CYGB contains two redox-sensitive cysteine residues and that the formation of an intramolecular disulfide bridge resulted in the heme group becoming more accessible to external ligands. This supports the hypothesis that Cys38 and Cys83 serve as sensitive redox sensors. In Chapter IV we showed that CYGB mRNA and protein levels were elevated upon exposure to hypoxia. Interestingly, this upregulation was most likely HIF-2α-dependent. We propose that in melanoma, HIF-2α, rather than HIF-1α, positively regulates CYGB under hypoxic conditions in a cell type specific way. In Chapter V, the cytotoxic effect of indirect NTP treatment in two melanoma cell lines with divergent endogenous CYGB expression levels was investigated. We confirmed that NTP endows cytotoxicity that induces cell death through apoptosis and that this was mediated through the production of ROS. Moreover, we showed that CYGB protects melanoma cells from ROS-induced apoptosis by the scavenging of ROS. Interestingly, CYGB expression influenced the expression of NRF2 and HO-1. We identified the lncRNA MEG3 as a possible mechanism through which NRF2 expression and its downstream target HO-1 can be regulated by CYGB. In chapter VI, increased basal ROS levels and higher degree of lipid peroxidation upon RSL3 treatment contributed to the increased sensitivity of CYGB knockdown G361 cells to ferroptosis. Furthermore, transcriptome analysis demonstrates the enrichment of multiple cancer malignancy pathways upon CYGB knockdown, supporting a tumor-suppressive role for CYGB. Remarkably, CYGB expression regulation was identified as a critical determinant of the ferroptosis–pyroptosis therapy response. This suggests that CYGB is involved in the regulation of multiple modes of programmed cell death. FInally, we sought to delineate the RONS that are responsible for plasma-induced ICD. Our results highlight the importance of the short-lived species. Furthermore, we are first to demonstrate that NTP-created vaccine is safely prepared and offers complete protection. Moreover, we provide conclusive evidence that direct application of NTP induces ICD in melanoma.

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: We propose a new method to measure atomic scale dynamics of nanoparticles from experimental high-resolution annular dark field scanning transmission electron microscopy images. By using the so-called hidden Markov model, which explicitly models the possibility of structural changes, the number of atoms in each atomic column can be quantified over time. This newly proposed method outperforms the current atom-counting procedure and enables the determination of the probabilities and cross sections for surface diffusion. This method is therefore of great importance for revealing and quantifying the atomic structure when it evolves over time via adatom dynamics, surface diffusion, beam effects, or during in situ experiments.

Abstract: We present a quantitative method which allows us to reliably measure dynamic changes in the atomic structure of monatomic crystalline nanomaterials from a time series of atomic resolution annular dark field scanning transmission electron microscopy images. The approach is based on the so-called hidden Markov model and estimates the number of atoms in each atomic column of the nanomaterial in each frame of the time series. We discuss the origin of the improved performance for time series atom-counting as compared to the current state-of-the-art atom-counting procedures, and show that the so-called transition probabilities that describe the probability for an atomic column to lose or gain one or more atoms from frame to frame are particularly important. Using these transition probabilities, we show that the method can also be used to estimate the probability and cross section related to structural changes. Furthermore, we explore the possibilities for applying the method to time series recorded under variable environmental conditions. The method is shown to be promising for a reliable quantitative analysis of dynamic processes such as surface diffusion, adatom dynamics, beam effects, or in situ experiments.

Abstract: Bacterial and mammalian proteins, such as lysozyme, are gaining increasing interest as anticancer drugs. This study aims to modify the lysozyme structure using cold atmospheric plasma to boost its cancer cell killing effect. We investigated the structure at acidic and neutral pH using various experimental techniques (circular dichroism, fluorescence, and mass spectrometry) and molecular dynamics simulations. The controlled structural modification of lysozyme at neutral pH enhances its activity, while the activity was lost at acidic pH at the same treatment conditions. Indeed, a larger number of amino acids were oxidized at acidic pH after plasma treatment, which results in a greater distortion of the lysozyme structure, whereas only limited structural changes were observed in lysozyme after plasma treatment at neutral pH. We found that the plasma-treated lysozyme significantly induced apoptosis to the cancer cells. Our results reveal that plasma-treated lysozyme could have potential as a new cancer cell killing drug.

Abstract: By combining statistical parameter estimation and model-order selection using a Bayesian framework, the maximum a posteriori (MAP) probability rule is proposed in this chapter as an objective and quantitative method to detect atom columns from high-resolution scanning transmission electron microscopy (HRSTEM) images. The validity and usefulness of this approach is demonstrated to both simulated and experimental annular dark-field (ADF) STEM images, but also to simultaneously acquired annular bright-field (ABF) and ADF STEM image data.

Abstract: An efficient model-based estimation algorithm is introduced to quantify the atomic column positions and intensities from atomic-resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting for overlap between neighboring columns, enabling the analysis of a large field of view. To provide end-users with this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license. In this chapter, this efficient algorithm is applied to three different nanostructures for which the analysis of a large field of view is required.

Abstract: The maximum a posteriori (MAP) probability rule for atom column detection can also be used as a tool to evaluate the relation between scanning transmission electron microscopy (STEM) image quality and atom detectability. In this chapter, a new image-quality measure is proposed that correlates well with atom detectability, namely the integrated contrast-to-noise ratio (ICNR). Furthermore, the working principle of the MAP probability rule is described in detail showing a close relation to the principles of model-selection methods.

Abstract: In this chapter, the principles of detection theory are used to quantify the probability of error for atom counting from high-resolution scanning transmission electron microscopy (HRSTEM) images. Binary and multiple hypothesis testing have been investigated in order to determine the limits to the precision with which the number of atoms in a projected atomic column can be estimated. The probability of error has been calculated when using STEM images, scattering cross-sections or peak intensities as a criterion to count atoms. Based on this analysis, we conclude that scattering cross-sections perform almost equally well as images and perform better than peak intensities. Furthermore, the optimal STEM detector design can be derived for atom counting using the expression of the probability of error. We show that for very thin objects the low-angle annular dark-field (LAADF) regime is optimal and that for thicker objects the optimal inner detector angle increases.

Abstract: A small sample tilt away from a main zone axis orientation results in an elongation of the atomic columns in ADF STEM images. An often posed research question is therefore whether the ADF STEM image intensities of tilted nanomaterials should be quantified using a parametric imaging model consisting of elliptical rather than the currently used symmetrical peaks. To this purpose, simulated ADF STEM images corresponding to different amounts of sample tilt are studied using a parametric imaging model that consists of superimposed 2D elliptical Gaussian peaks on the one hand and symmetrical Gaussian peaks on the other hand. We investigate the quantification of structural parameters such as atomic column positions and scattering cross sections using both parametric imaging models. In this manner, we quantitatively study what can be gained from this elliptical model for quantitative ADF STEM, despite the increased parameter space and computational effort. Although a qualitative improvement can be achieved, no significant quantitative improvement in the estimated structure parameters is achieved by the elliptical model as compared to the symmetrical model. The decrease in scattering cross sections with increasing sample tilt is even identical for both types of parametric imaging models. This impedes direct comparison with zone axis image simulations. Nonetheless, we demonstrate how reliable atom-counting can still be achieved in the presence of small sample tilt.

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: 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.