In the past decades, matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has been applied to a broad range of biological samples, e.g., forensics and preclinical samples. The use of MALDI-MSI for the analysis of bone tissue has been limited due to the insulating properties of the material but more importantly the absence of a proper sample preparation protocol for undecalcified bone tissue. Undecalcified sections are preferred to retain sample integrity as much as possible or to study the tissue-bone bio interface in particular. Here, we optimized the sample preparation protocol of undecalcified bone samples, aimed at both targeted and untargeted applications for forensic and preclinical applications, respectively. Different concentrations of gelatin and carboxymethyl cellulose (CMC) were tested as embedding materials. The composition of 20% gelatin and 7.5% CMC showed to support the tissue best while sectioning. Bone tissue has to be sectioned with a tungsten carbide knife in a longitudinal fashion, while the sections need to be supported with double-sided tapes to maintain the morphology of the tissue. The developed sectioning method was shown to be applicable on rat and mouse as well as human bone samples. Targeted (methadone and EDDP) as well as untargeted (unknown lipids) detection was demonstrated. DHB proved to be the most suitable matrix for the detection of methadone and EDDP in positive ion mode. The limit of detection (LOD) is estimated to approximately 50 pg/spot on bone tissue. The protocol was successfully applied to detect the presence of methadone and EDDP in a dosed rat femur and a dosed human clavicle. The best matrices for the untargeted detection of unknown lipids in mouse hind legs in positive ion mode were CHCA and DHB based on the number of tissue-specific peaks and signal-to-noise ratios. The developed and optimized sample preparation method, applicable on animal and human bones, opens the door for future forensic and (pre)clinical investigations.

The analysis of samples with large height variations remains a challenge for mass spectrometry imaging (MSI), despite many technological advantages. Ambient sampling and ionization MS techniques allow for the molecular analysis of sample surfaces with height variations, but most techniques lack MSI capabilities. We developed a 3D MS scanner for the automated sampling and imaging of a 3D surface with laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS). The sample is moved automatically with a constant distance between the laser probe and sample surface in the 3D MS Scanner. The topography of the surface was scanned with a laser point distance sensor to define the MS measurement points. MS acquisition was performed with LA-REIMS using a surgical CO 2 laser coupled to a qTOF instrument. The topographical scan and MS acquisition can be completed within 1 h using the 3D MS scanner for 300 measurement points on uneven samples with a spatial resolution of 2 mm in the top view, corresponding to 22.04 cm 2 . Comparison between the automated acquisition with the 3D MS scanner and manual acquisition by hand showed that the automation resulted in increased reproducibility between the measurement points. 3D visualizations of molecular distributions related to structural differences were shown for an apple, a marrowbone, and a human femoral head to demonstrate the imaging feasibility of the system. The developed 3D MS scanner allows for the automated sampling of surfaces with uneven topographies with LA-REIMS, which can be used for the 3D visualization of molecular distributions of these surfaces.

Background: Fracture healing is a complex process, involving cell-cell interactions, various cytokines, and growth factors. Although fracture treatment improved over the last decades, a substantial part of all fractures shows delayed or absent healing. The fracture hematoma (fxh) is known to have a relevant role in this process, while the exact mechanisms by which it influences fracture healing are poorly understood. To improve strategies in fracture treatment, regulatory pathways in fracture healing need to be investigated. Lipids are important molecules in cellular signaling, inflammation, and metabolism, as well as key structural components of the cell. Analysis of the lipid spectrum in fxh may therefore reflect important events during the early healing phase. This study aims to develop a protocol for the determination of lipid signals over time, and the identification of lipids that contribute to these signals, with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) in fxh in healthy fracture healing.Methods: Twelve fxh samples (6 porcine; 6 human) were surgically removed, snap frozen, sectioned, washed, and analyzed using MALDI-MSI in positive and negative ion mode at different time points after fracture (porcine: 72 h; human samples: range 1–19 days). A tissue preparation protocol for lipid analysis in fxh has been developed with both porcine and human fxh. Data were analyzed through principal component- and linear discriminant analyses.Results: A protocol for the preparation of fxh sections was developed and optimized. Although hematoma is a heterogeneous tissue, the intra-variability within fxh was smaller than the inter-variability between fxh. Distinctive m/z values were detected that contributed to the separation of three different fxh age groups: early (1–3 days), middle (6–10 days), and late (12–19 days). Identification of the distinctive m/z values provided a panel of specific lipids that showed a time dependent expression within fxh.Conclusion: This study shows that MALDI-MSI is a suitable analytical tool for lipid analysis in fxh and that lipid patterns within fxh are time-dependent. These lipid patterns within fxh may serve as a future diagnostic tool. These findings warrant further research into fxh analysis using MALDI-MSI and its possible clinical implications in fracture treatment.

AbstractCommon traumas to the skeletal system are bone fractures and injury-related articular cartilage damage. The healing process can be impaired resulting in non-unions in 5–10% of the bone fractures and in post-traumatic osteoarthritis (PTOA) in up to 75% of the cases of cartilage damage. Despite the amount of research performed in the areas of fracture healing and cartilage repair as well as non-unions and PTOA, still, the outcome of a bone fracture or articular cartilage damage cannot be predicted. Here, we discuss known risk factors and key molecules involved in the repair process, together with the main challenges associated with the prediction of outcome of these injuries. Furthermore, we review and discuss the opportunities for mass spectrometry (MS) – an analytical tool capable of detecting a wide variety of molecules in tissues – to contribute to extending molecular understanding of impaired healing and the discovery of predictive biomarkers. Therefore, the current knowledge and challenges concerning MS imaging of bone and cartilage tissue as well as in vivo MS are discussed. Finally, we explore the possibilities of in situ, real-time MS for the prediction of outcome during surgery of bone fractures and injury-related articular cartilage damage.

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