Bioorthogonal nanozymes for breast cancer imaging and therapy.

Bioorthogonal catalysis via transition metal catalysts (TMCs) enables the generation of therapeutics locally through chemical reactions not accessible by biological systems. This localization can enhance the efficacy of anticancer treatment while minimizing off-target effects. The encapsulation of TMCs into nanomaterials generates "nanozymes" to activate imaging and therapeutic agents.

LA-ICP-MS and MALDI-MS image registration for correlating nanomaterial biodistributions and their biochemical effects.

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.

Nanodelivery vehicles induce remote biochemical changes in vivo.

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.

Reconstruction, analysis, and segmentation of LA-ICP-MS imaging data using Python for the identification of sub-organ regions in tissues.

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.

Dual Mass Spectrometric Tissue Imaging of Nanocarrier Distributions and Their Biochemical Effects.

Nanomaterial-based drug delivery vehicles are able to deliver therapeutics in a controlled, targeted manner. Currently, however, there are limited analytical methods that can detect both nanomaterial distributions and their biochemical effects concurrently. In this study, we demonstrate that matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and laser ablation inductively coupled plasma mass spectrometry imaging (LA-ICP-MSI) can be used together to obtain nanomaterial distributions and biochemical consequences.

Oligo p-Phenylenevinylene Derivatives as Electron Transfer Matrices for UV-MALDI.

Phenylenevinylene oligomers (PVs) have outstanding photophysical characteristics for applications in the growing field of organic electronics. Yet, PVs are also versatile molecules, the optical and physicochemical properties of which can be tuned by manipulation of their structure. We report the synthesis, photophysical, and MS characterization of eight PV derivatives with potential value as electron transfer (ET) matrices for UV-MALDI.