Fingerprints of Element Concentrations in Infective Endocarditis Obtained by Mass Spectrometric Imaging and t-Distributed Stochastic Neighbor Embedding

Advances in mass spectrometry imaging for spatial cancer metabolomics

Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.

Tandem Mass Spectrometry Imaging Enables High Definition for Mapping Lipids in Tissues

Mass spectrometry imaging (MSI) of lipids in biological tissues is useful for correlating molecular distribution with pathological results, which could provide useful information for both biological research and disease diagnosis. It is well understood that the lipidome could not be clearly deciphered without tandem mass spectrometry analysis, but this is challenging to achieve in MSI due to the limitation in sample amount at each image spot. Here we develop a multiplexed MS² imaging (MS² I) method that can provide MS² images for 10 lipid species or more for each sampling spot, providing spatial structural lipidomic information. Coupling with on-tissue photochemical derivatization, imaging of 20 phospholipid C=C location isomers is also realized, showing enhanced molecular images with high definition in structure for mouse brain and human liver cancer tissue sections. Spatially mapped t-distributed stochastic neighbor embedding has also been adopted to visualize the tumor margin with enhancement by structural lipidomic information.

Native valve, prosthetic valve, and cardiac device-related infective endocarditis: A review and update on current innovative diagnostic and therapeutic strategies

Infective endocarditis (IE) is a life-threatening microbial infection of native and prosthetic heart valves, endocardial surface, and/or indwelling cardiac device. Prevalence of IE is increasing and mortality has not significantly improved despite technological advances. This review provides an updated overview using recent literature on the clinical presentation, diagnosis, imaging, causative pathogens, treatment, and outcomes in native valve, prosthetic valve, and cardiac device-related IE. In addition, the experimental approaches used in IE research to improve the understanding of disease mechanisms and the current diagnostic pipelines are discussed, as well as potential innovative diagnostic and therapeutic strategies. This will ultimately help towards deriving better diagnostic tools and treatments to improve IE patient outcomes.