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A multimodal approach that integrates IF and high resolution nano-DESI MSI using image registration and segmentation tools to characterize the chemical composition of skeletal fibers.

Mass spectrometry imaging (MSI) enables label-free mapping of hundreds of molecules in biological samples with high sensitivity and unprecedented specificity. Conventional MSI experiments are relatively slow, limiting their utility for applications requiring rapid data acquisition, such as intraoperative tissue analysis or 3D imaging. Recent advances in MSI technology focus on improving the spatial resolution and molecular coverage, further increasing the acquisition time. Herein, a deep learning approach for dynamic sampling (DLADS) was employed to reduce the number of required measurements, thereby improving the throughput of MSI experiments in comparison with conventional methods. DLADS trains a deep learning model to dynamically predict molecularly informative tissue locations for active mass spectra sampling and reconstructs high-fidelity molecular images using only the sparsely sampled information. Experimental hardware and software integration of DLADS with nanospray desorption electrospray ionization (nano-DESI) MSI is reported for the first time, which demonstrates a 2.3-fold improvement in throughput for a linewise acquisition mode. Meanwhile, simulations indicate that a 5-10-fold throughput improvement may be achieved using the pointwise acquisition mode.

Imaging of proteoforms in human tissues is hindered by low molecular specificity and limited proteome coverage. Here, we introduce proteoform imaging mass spectrometry (PiMS), which increases the size limit for proteoform detection and identification by fourfold compared to reported methods and reveals tissue localization of proteoforms at

Unraveling the complexity of biological systems relies on the development of new approaches for spatially resolved proteoform-specific analysis of the proteome. Top-down proteomics is a powerful tool, which has been used for the identification of thousands of proteoforms in biological samples. Herein, we present a first spatially resolved top-down proteomics analysis of biological tissues using nanospray desorption electrospray ionization mass spectrometry imaging (nano-DESI MSI). Nano-DESI generates multiply charged protein ions, which is advantageous for their structural characterization using tandem mass spectrometry (MS/MS). Proof-of-concept experiments demonstrate that the nano-DESI MSI combined with on-tissue top-down proteomics is ideally suited for the proteoform-selective imaging of thin tissue sections. Using rat brain tissue as a model system, we provide the first evidence of the differential proteoform expression in different regions of the brain.

Imaging of proteoforms in human tissues is hindered by low molecular specificity and limited proteome coverage. Here, we introduce proteoform imaging mass spectrometry (PiMS), which increases the size limit for proteoform detection and identification by 4-fold compared to reported methods, and reveals tissue localization of proteoforms at 2MS). We demonstrate the first proteoform imaging of human kidney, identifying 169 of 400 proteoforms TeaserNano-DESI combined with individual ion mass spectrometry generates images of proteoforms up to 70 kDa.

People with arthritis, a leading cause of disability, may be prescribed long-term opioid therapy to manage chronic pain. Regular use of opioids can increase risk of overdose and opioid use disorder (OUD).The purpose of our research was to validate an instrument to screen for harmful opioid use in people with disability and chronic pain due to arthritis (PWDA).We tested the Current Opioid MisuseOf the 17 items on the original COMM, we found that 11 items measured the intended construct-opioid use in a way that causes harm in PWDA. Once limiting the instrument to these 11 items (The COMM 11-PWDA), the items had excellent internal consistency and validity with the DSM-V measure. Reasonable sensitivity and specificity were established.The COMM 11-PWDA is a valid instrument for screening for and monitoring harmful opioid use in PWDA.