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We present an optimization of the toroidal self-organizing map (SOM) algorithm for the accurate visualization of hyperspectral data. This represents a significant advancement on our previous work, in which we demonstrated the use of toroidal SOMs for the visualization of time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging data. We have previously shown that the toroidal SOM can be used, unsupervised, to produce a multicolor similarity map of the analysis area, in which pixels with similar mass spectra are assigned a similar color. Here, we use an additional algorithm, relational perspective mapping (RPM), to produce more accurate visualizations of hyperspectral data. The SOM output is used as an input for the RPM algorithm, which is a nonlinear dimensionality reduction technique designed to produce a two-dimensional map of high-dimensional data. Using the topological information provided by the SOM, RPM provides complementary distance information. The result is a color scheme that more accurately reflects the local spectral distances between pixels in the data. We exemplify SOM-RPM using ToF-SIMS imaging data from a mouse tumor tissue section. The similarity maps produced are compared with those produced by two leading hyperspectral visualization techniques in the field of mass spectrometry imaging: t-distributed stochastic neighborhood embedding (t-SNE) and uniform manifold approximation and projection (UMAP). We evaluate the performance of each technique both qualitatively and quantitatively, investigating the correlations between distances in the models and distances in the data. SOM-RPM is demonstrably highly competitive with t-SNE and UMAP, according to our evaluations. Furthermore, the use of a neural network offers distinct advantages in data characterization, which we discuss. We also show how spectra extracted from regions of interest identified by SOM-RPM can be further analyzed using linear discriminant analysis for the validation and charac

Combinatorial approaches to materials discovery offer promising potential for the rapid development of novel polymer systems. Polymer microarrays enable the high-throughput comparison of material physical and chemical properties-such as surface chemistry and properties like cell attachment or protein adsorption-in order to identify correlations that can progress materials development. A challenge for this approach is to accurately discriminate between highly similar polymer chemistries or identify heterogeneities within individual polymer spots. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) offers unique potential in this regard, capable of describing the chemistry associated with the outermost layer of a sample with high spatial resolution and chemical sensitivity. However, this comes at the cost of generating large scale, complex hyperspectral imaging data sets. We have demonstrated previously that machine learning is a powerful tool for interpreting ToF-SIMS images, describing a method for color-tagging the output of a self-organizing map (SOM). This reduces the entire hyperspectral data set to a single reconstructed color similarity map, in which the spectral similarity between pixels is represented by color similarity in the map. Here, we apply the same methodology to a ToF-SIMS image of a printed polymer microarray for the first time. We report complete, single-pixel molecular discrimination of the 70 unique homopolymer spots on the array while also identifying intraspot heterogeneities thought to be related to intermixing of the polymer and the pHEMA coating. In this way, we show that the SOM can identify layers of similarity and clusters in the data, both with respect to polymer backbone structures and their individual side groups. Finally, we relate the output of the SOM analysis with fluorescence data from polymer-protein adsorption studies, highlighting how polymer performance can be visualized within the context of the global topology of the

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful surface characterization technique capable of producing high spatial resolution hyperspectral images, in which each pixel comprises an entire mass spectrum. Such images can provide insight into the chemical composition across a surface. However, issues arise due to the size and complexity of the data produced. Data are particularly complicated for biological samples, primarily due to overlapping spectra produced by similar components. The traditional approach of selecting individual ion peaks as representative of particular components is insufficient for such complex data sets. Multivariate analysis (MVA) can help to overcome this significant hurdle. We demonstrate that Kohonen self-organizing maps (SOMs) with a toroidal topology can be used to analyze a ToF-SIMS hyperspectral imaging data set and identify spectral similarities between pixels. We present a method for color-tagging the toroidal SOM output, which reduces the entire data set to a single RGB image in which similar pixels - based on their associated mass spectra - are assigned a similar color. This method was exemplified using a ToF-SIMS image of dried large multilamellar vesicles (LMVs), loaded with the antibiotic cefditoren pivoxil (CP). We successfully identified CP-loaded and empty LMVs without the need for any prior knowledge of the sample, despite their highly similar spectra. We also identified which specific ion peaks were most important in differentiating the two LMV populations. This approach is entirely unsupervised and requires minimal experimenter input. It was developed with the aim of providing a user-friendly yet sophisticated workflow for understanding complex biological samples using ToF-SIMS images.

2019 Elsevier Ltd Mitoxantrone is an anticancer anthracenedione that can be activated by formaldehyde to generate covalent drug-DNA adducts. Despite their covalent nature, these DNA lesions are relatively labile. It was recently established that analogues of mitoxantrone featuring extended side-chains terminating in primary amino groups typically yielded high levels of stable DNA adducts following their activation by formaldehyde. In this study we describe the DNA sequence-specific binding properties of the mitoxantrone analogue WEHI-150 which is the first anthracenedione to form apparent DNA crosslinks mediated by formaldehyde. The utility of this compound lies in the versatility of the covalent binding modes displayed. Unlike other anthracenediones described to date, WEHI-150 can mediate covalent adducts that are independent of interactions with the N-2 of guanine and is capable of adduct formation at novel DNA sequences. Moreover, these covalent adducts incorporate more than one formaldehyde-mediated bond with DNA, thus facilitating the formation of highly lethal DNA crosslinks. The versatility of binding observed is anticipated to allow the next generation of anthracenediones to interact with a broader spectrum of nucleic acid species than previously demonstrated by the parent compounds, thus allowing for more diverse biological activities.

The major covalent adduct formed between a 13C-labelled formaldehyde activated bis-amino mitoxantrone analogue (WEHI-150) and the hexanucleotide d(CG5MeCGCG)2 has been isolated by HPLC chromatography and the structure determined by NMR spectroscopy. The results indicate that WEHI-150 forms one covalent bond through a primary amine to the N-2 of the G2 residue, with the polycyclic ring structure intercalated at the 5MeC3pG4/G10p5MeC9 site. Furthermore, the WEHI-150 aromatic ring system is oriented approximately parallel to the long axis of the base pairs, with one aliphatic side-chain in the major groove and the other side-chain in the minor groove. This study indicates that mitoxantrone derivatives like WEHI-150 should be capable of forming major-minor groove cross-linked adducts that will likely produce considerably different intracellular biological properties compared to known anthracycline and anthracenedione anticancer drugs.

The ability of a bis-amino mitoxantrone anticancer drug (named WEHI-150) to form covalent adducts with DNA, after activation by formaldehyde, has been studied by electrospray ionisation mass spectrometry and HPLC. Mass spectrometry results showed that WEHI-150 could form covalent adducts with d(ACGCGCGT)2 that contained one, two or three covalent links to the octanucleotide, whereas the control drugs (daunorubicin and the anthracenediones mitoxantrone and pixantrone) only formed adducts with one covalent link to the octanucleotide. HPLC was used to examine the extent of covalent bond formation of WEHI-150 with d(CGCGCG)2 and d(CG5MeCGCG)2. Incubation of WEHI-150 with d(CG5MeCGCG)2 in the presence of formaldehyde resulted in the formation of significantly greater amounts of covalent adducts than was observed with d(CGCGCG)2. In order to understand the observed increase of covalent adducts with d(CG5MeCGCG)2, an NMR study of the reversible interaction of WEHI-150 at both CpG and 5MeCpG sites was undertaken. Intermolecular NOEs were observed in the NOESY spectra of d(ACGGCCGT)2 with added WEHI-150 that indicated that the drug selectively intercalated at the CpG sites and from the major groove. In particular, NOEs were observed from the WEHI-150 H2,3 protons to the H1′ protons of G3 and G7 and from the H6,7 protons to the H5 protons of C2 and C6. By contrast, intermolecular NOEs were observed between the WEHI-150 H2,3 protons to the H2′′ proton of the 5MeC3 in d(CG5MeCGCG)2, and between the drug aliphatic protons and the H1′ proton of G4. This demonstrated that WEHI-150 preferentially intercalates at 5MeCpG sites, compared to CpG sequences, and predominantly via the minor groove at the 5MeCpG site. The results of this study demonstrate that WEHI-150 is likely to form interstrand DNA cross-links, upon activation by formaldehyde, and consequently exhibit greater cytotoxicity than other current anthracenedione drugs.

Mas Jaffri Masarudin,1 Suzanne M Cutts,2 Benny J Evison,3 Don R Phillips,2 Paul J Pigram4 1Department of Cell and Molecular Biology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, Serdang, Malaysia; 2Department of Biochemistry, La Trobe University, Melbourne, Victoria, Australia; 3Department of Chemical Biology and Therapeutics, St Jude Children's Hospital, Memphis, TN, USA; 4Department of Physics, La Trobe University, Melbourne, Victoria, Australia Abstract: Development of parameters for the fabrication of nanosized vectors is pivotal for its successful administration in therapeutic applications. In this study, homogeneously distributed chitosan nanoparticles (CNPs) with diameters as small as 62 nm and a polydispersity index (PDI) of 0.15 were synthesized and purified using a simple, robust method that was highly reproducible. Nanoparticles were synthesized using modified ionic gelation of the chitosan polymer with sodium tripolyphosphate. Using this method, larger aggregates were mechanically isolated from single particles in the nanoparticle population by selective efficient centrifugation. The presence of disaggregated monodisperse nanoparticles was confirmed using atomic force microscopy. Factors such as anions, pH, and concentration were found to affect the size and stability of nanoparticles directly. The smallest nanoparticle population was ~62 nm in hydrodynamic size, with a low PDI of 0.15, indicating high particle homogeneity. CNPs were highly stable and retained their monodisperse morphology in serum-supplemented media in cell culture conditions for up to 72 hours, before slowly degrading over 6 days. Cell viability assays demonstrated that cells remained viable following a 72-hour exposure to 1 mg/mL CNPs, suggesting that the nanoparticles are well tolerated and highly suited for biomedical applications. Cellular uptake studies using fluorescein isothiocyanate-labeled CNPs showed that cancer cells readily accumula