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Faradays legendary Molecules of Gold have stimulated intense interest (over 165 years) but have only recently begun to yield their secrets to modern methods of chemical analysis. Here(in), we demonstrate how striking charging patterns emerge directly from native electrospray of large, gold-rich molecules that were generated by reduction of various (8) small gold(I)thiolate complexes [-RS-Au(I)-SR-], followed by extensive thermochemical processing to enrich the most robust forms. In each case (R), electrospray ionization of a picomolar solution yields a characteristic series of abundant, highly resolved peaks at related (m/z)-ratios, that can be used to deduce charges {z e+} and hence a distinct molecular mass, {MR}. A plot of {MR} versus thiolate-mass {mL} yields a straight line with slope 60.0 (the ligand count) and an intercept of 28,364-Da, the mass of 144 Au-atoms. i.e., a unique molecular composition {197Au144(SR)60}. This formula agrees with the unique chiral-icosahedral structure-model, c@12@42@60@(30,60), the Pd145(CO)60-structure, that features a massively-compact globular Au114-core (~1.6-nm) and an intrinsically chiral (I) outer shell (~2.0-nm) with 12 distinct ligand types of 5-fold equivalence], denoted by Martin et al. as virus-like on the basis of its resemblance of icosahedral-virus capsids. 

Laser ablation inductively-coupled plasma mass spectrometry (LA-ICP-MS) imaging and matrix assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) are complementary methods that measure distributions of elements and biomolecules in tissue sections. Quantitative correlations of the information provided by these two imaging modalities requires that the datasets be registered in the same coordinate system, allowing for pixel-by-pixel comparisons. We describe here a computational workflow written in Python that accomplishes this registration, even for adjacent tissue sections, with accuracies within ±50 μm. The value of this registration process is demonstrated by correlating images of tissue sections from mice injected with gold nanomaterial drug delivery systems. Quantitative correlations of the nanomaterial delivery vehicle, as detected by LA-ICP-MS imaging, with biochemical changes, as detected by MALDI-MSI, provide deeper insight into how nanomaterial delivery systems influence lipid biochemistry in tissues. Moreover, the registration process allows the more precise images associated with LA-ICP-MS imaging to be leveraged to achieve improved segmentation in MALDI-MS images, resulting in the identification of lipids that are most associated with different sub-organ regions in tissues. 

Nanomaterial-based platforms are promising vehicles for the controlled delivery of therapeutics. For these systems to be both efficacious and safe, it is essential to understand where the carriers accumulate and to reveal the site-specific biochemical effects they produce in vivo . Here, a dual-mode mass spectrometry imaging (MSI) method is used to evaluate the distributions and biochemical effects of anti-TNF-α nanoparticle stabilized capsules (NPSCs) in mice. It is found that most of the anticipated biochemical changes occur in sub-organ regions that are separate from where the nanomaterials accumulate. In particular, TNF-α-specific lipid biomarker levels change in immune cell-rich regions of organs, while the NPSCs accumulate in spatially isolated filtration regions. Biochemical changes that are associated with the nanomaterials themselves are also observed, demonstrating the power of matrix-assisted laser desorption/ionization (MALDI) MSI to reveal markers indicating possible off-target effects of the delivery agent. This comprehensive assessment using MSI provides spatial context of nanomaterial distributions and efficacy that cannot be easily achieved with other imaging methods, demonstrating the power of MSI to evaluate both expected and unexpected outcomes associated with complex therapeutic delivery systems. 

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) imaging has been extensively used to determine the distributions of metals in biological tissues for a wide variety of applications. To be useful for identifying metal biodistributions, the acquired raw data needs to be reconstructed into a two-dimensional image. Several approaches have been developed for LA-ICP-MS image reconstruction, but less focus has been placed on software for more in-depth statistical processing of the imaging data. Yet, improved image processing can allow the biological ramifications of metal distributions in tissues to be better understood. In this work, we describe software written in Python that automatically reconstructs, analyzes, and segments images from LA-ICP-MS imaging data. Image segmentation is achieved using LA-ICP-MS signals from the biological metals Fe and Zn together with k -means clustering to automatically identify sub-organ regions in different tissues. Spatial awareness also can be incorporated into the images through a neighboring pixel evaluation that allows regions of interest to be identified that are at the limit of the LA-ICP-MS imaging resolution. The value of the described algorithms is demonstrated for LA-ICP-MS images of nanomaterial biodistributions. The developed image reconstruction and processing approach reveals that nanomaterials distribute in different sub-organ regions based on their chemical and physical properties, opening new possibilities for understanding the impact of such nanomaterials in vivo . 

Developing an engineerable chemical reaction that is triggerable for simultaneous chemical bond formation and cleavage by external cues offers tunability and orthogonality which is highly desired in many biological and materials applications. Here, we present a chemical switch that concurrently captures these features in response to chemically and biologically abundant and important cues, viz. , thiols and amines. This thiol/amine-triggerable chemical switch is based on a Triggerable Michael Acceptor (TMAc) which bears good leaving groups at its β-position. The acceptor undergoes a “trigger-to-release” process where thiol/amine addition triggers cascaded release of leaving groups and generates a less activated acceptor. The newly generated TMAc can be further reversed to liberate the original thiol/amine by a second nucleophile trigger through a “trigger-to-reverse” process. Within the small molecular volume of the switch, we have shown five locations that can be engineered to achieve tunable “trigger-to-release” kinetics and tailored reversibility. The potential of the engineerable bonding/debonding capability of the chemical switch is demonstrated by applications in cysteine-selective and reversible protein modification, universal self-immolative linkers, and orthogonally addressable hydrogels.