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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.

Simultaneous spatial localization and structural characterization of molecules in complex biological samples currently represents an analytical challenge for mass spectrometry imaging (MSI) techniques. In this study, we describe a novel experimental platform, which substantially expands the capabilities and enhances the depth of chemical information obtained in high spatial resolution MSI experiments performed using nanospray desorption electrospray ionization (nano-DESI). Specifically, we designed and constructed a portable nano-DESI MSI platform and coupled it with a drift tube ion mobility (IM) spectrometer-mass spectrometer. We demonstrate imaging of drift time-separated ions with a high spatial resolution of better than ∼25 μm using uterine tissues on day 4 of pregnancy in mice. Collision cross-section measurements provide unique molecular descriptors of molecules observed in nano-DESI-IM-MSI necessary for their unambiguous identification by comparison with databases. Meanwhile, isomer-specific imaging reveals variations in the isomeric composition across the tissue. Furthermore, IM separation efficiently eliminates isobaric and isomeric interferences originating from solvent peaks, overlapping isotopic peaks of endogenous molecules extracted from the tissue, and products of in-source fragmentation, which is critical to obtaining accurate concentration gradients in the sample using MSI. The structural information provided by the IM separation substantially expands the molecular specificity of high-resolution MSI necessary for unraveling the complexity of biological systems.

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.

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.

Scope: Acquire imaging mass spectrometry (IMS) datasets of proteins on human kidney tissue with ~12μm spatial resolution. Expected Outcome: Visualize the proteins distribution localizing to physiological regions within the human kidney by generating ion images of multiply charged protein peaks.

Scope: Acquire imaging mass spectrometry (IMS) datasets of lipids and metabolites on human kidney tissue with ~12μm spatial resolution. Expected Outcome: Visualize the lipids distribution localizing to physiological regions within the human kidney by generating ion images of lipids precursor ions.

Aging of transformer oils could shorten the life of a transformer. Electrochemical behavior of the antioxidant 2,6-di-tert-butyl-4-methylphenol (BHT) in an electrolyte containing transformer oils was investigated. Cyclic voltammograms were obtained from electrochemical tests under different temperatures, and the quasi-reversible behavior for BHT on glassy carbon electrode was confirmed by the characteristics of the peak currents. The diffusion coefficients of BHT under different temperatures were evaluated from the dependence of the peak current density on the potential scan rates in the cyclic voltammograms, and it was found that the diffusion coefficient increases with increasing temperature. Diffusion activation energy of BHT was also calculated to be 29.29 kJ mol−1, according to the relationship between the diffusion coefficient and temperature. Determination of the antioxidant content in transformer oils by electrochemical techniques and appropriate addition of the antioxidant, which can effectively ...

Background With an epidemic of traffic injuries affecting children worldwide, a better understanding of the data, including parent attitudes and behaviours, is essential. Methods A survey was conducted among a diverse group of 6000 parents in six nations in 2014. In Brazil, China and South Africa, the survey was fielded by phone; in Qatar and India, by interviews; and in the United States, online. To assess the burden of road traffic deaths and injuries on children worldwide, data from the Global Burden of Diseases Study was analysed. Results More than 90 percent of parents in Brazil, China, India, Qatar and South Africa said more needs to be done to improve road safety for children. More than half of parents in five out of six countries said they are concerned about their child’s safety on the way to school. In India, 66 percent of parents expect their child to be seriously hurt in a crash in the next year. In the United States, more than 70 percent of parents worry about their child being hit by a distracted or speeding driver on the way to school. Analysis of GBD data showed that, in 2010, road crashes were the leading cause of death among children ages 5 to 19, with teenagers accounting for nearly half of deaths. More than 90 percent of road deaths among children occurred in low- and middle-income countries. Conclusions Parents around the world are highly concerned about the safety of their children on the roads. These concerns are justified since road crashes are the leading cause of death for children ages 5 to 19. A strong focus on building awareness, expanding prevention programs, advocating for laws, and enhancing enforcement, consistent with the pillars of the UN Decade of Action on Road Safety, is needed.