Abstract: In the present paper, a statistical model-based method to count the number of atoms of monotype crystalline nanostructures from high resolution high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) images is discussed in detail together with a thorough study on the possibilities and inherent limitations. In order to count the number of atoms, it is assumed that the total scattered intensity scales with the number of atoms per atom column. These intensities are quantitatively determined using model-based statistical parameter estimation theory. The distribution describing the probability that intensity values are generated by atomic columns containing a specific number of atoms is inferred on the basis of the experimental scattered intensities. Finally, the number of atoms per atom column is quantified using this estimated probability distribution. The number of atom columns available in the observed STEM image, the number of components in the estimated probability distribution, the width of the components of the probability distribution, and the typical shape of a criterion to assess the number of components in the probability distribution directly affect the accuracy and precision with which the number of atoms in a particular atom column can be estimated. It is shown that single atom sensitivity is feasible taking the latter aspects into consideration.

Abstract: Many current anti-cancer therapies rely on increasing the intracellular reactive oxygen and nitrogen species (RONS) contents with the aim to induce irreparable damage, which subsequently results in tumor cell death. A novel tool in cancer therapy is the use of cold atmospheric plasma (CAP), which has been found to be very effective in the treatment of many different cancer cell types in vitro as well as in vivo, mainly through the vast generation of RONS. One of the key determinants of the cell's fate will be the interaction of RONS, generated by CAP, with important proteins, i.e. redox-regulatory proteins. One such protein is cytoglobin (CYGB), a recently discovered globin proposed to be involved in the protection of the cell against oxidative stress. In this study, the effect of plasma-produced RONS on CYGB was investigated through the treatment of CYGB with CAP for different treatment times. Spectroscopic analysis of CYGB showed that although chemical modifications occur, its secondary structure remains intact. Mass spectrometry experiments identified these modifications as oxidations of mainly sulfur-containing and aromatic amino acids. With longer treatment time, the treatment was also found to induce nitration of the heme. Furthermore, the two surface-exposed cysteine residues of CYGB were oxidized upon treatment, leading to the formation of intermolecular disulfide bridges, and potentially also intramolecular disulfide bridges. In addition, molecular dynamics and docking simulations confirmed, and further show, that the formation of an intramolecular disulfide bond, due to oxidative conditions, affects the CYGB 3D structure, thereby opening the access to the heme group, through gate functioning of His117. Altogether, the results obtained in this study (1) show that plasma-produced RONS can extensively oxidize proteins and (2) that the oxidation status of two redox-active cysteines lead to different conformations of CYGB.

Abstract: A decade ago, a statistics-based method was introduced to count the number of atoms from annular dark-field scanning transmission electron microscopy (ADF STEM) images. In the past years, this method was successfully applied to nanocrystals of arbitrary shape, size, and composition (and its high accuracy and precision has been demonstrated). However, the counting results obtained from this statistical framework are so far presented without a visualization of the actual uncertainty about this estimate. In this paper, we present three approaches that can be used to represent counting results together with their statistical error, and discuss which approach is most suited for further use based on simulations and an experimental ADF STEM image.

Abstract: Melanoma remains a deadly cancer despite significant advances in immune checkpoint blockade and targeted therapies. The incidence of melanoma is also growing worldwide, which highlights the need for novel treatment options and strategic combination of therapies. Here, we investigate non-thermal plasma (NTP), an ionized gas, as a promising, therapeutic option. In a melanoma mouse model, direct treatment of tumors with NTP results in reduced tumor burden and prolonged survival. Physical characterization of NTP treatment in situ reveals the deposited NTP energy and temperature associated with therapy response, and whole transcriptome analysis of the tumor identified several modulated pathways. NTP treatment also enhances the cancer-immunity cycle, as immune cells in both the tumor and tumor-draining lymph nodes appear more stimulated to perform their anti-cancer functions. Thus, our data suggest that local NTP therapy stimulates systemic, anti-cancer immunity. We discuss, in detail, how these fundamental insights will help direct the translation of NTP technology into the clinic and inform rational combination strategies to address the challenges in melanoma therapy.