Increased throughput and ultra-high mass resolution in DESI FT-ICR MS imaging through new-generation external data acquisition system and advanced data processing approaches

Fabrication and Advanced Imaging Characterization of Magnetic Aerogel-Based Thin Films for Water Decontamination

Aerogels have emerged as appealing materials for various applications due to their unique features, such as low density, high porosity, high surface area, and low thermal conductivity. Aiming to bring the advantages of these materials to the environmental field, this study focuses on synthesizing magnetic silica aerogel-based films suitable for water decontamination. In this respect, a novel microfluidic platform was created to obtain core-shell iron oxide nanoparticles that were further incorporated into gel-forming precursor solutions. Afterward, dip-coating deposition was utilized to create thin layers of silica-based gels, which were further processed by 15-hour gelation time, solvent transfer, and further CO2 desiccation. A series of physicochemical analyses (XRD, HR-MS FT-ICR, FT-IR, TEM, SEM, and EDS) were performed to characterize the final films and intermediate products. The proposed advanced imaging experimental model for film homogeneity and adsorption characteristics confirmed uniform aerogel film deposition, nanostructured surface, and ability to remove pesticides from contaminated water samples. Based on thorough investigations, it was concluded that the fabricated magnetic aerogel-based thin films are promising candidates for water decontamination and novel solid-phase extraction sample preparation.

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.

Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications

Osteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.

Ultrahigh-Mass Resolution Mass Spectrometry Imaging with an Orbitrap Externally Coupled to a High-Performance Data Acquisition System

Matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging (MSI) is a powerful analytical tool that enables molecular sample analysis while simultaneously providing the spatial context of hundreds or even thousands of analytes. However, because of the lack of a separation step prior to ionization and the immense diversity of biomolecules, such as lipids, including numerous isobaric species, the coupling of ultrahigh mass resolution (UHR) with MSI presents one way in which this complexity can be resolved at the spectrum level. Until now, UHR MSI platforms have been restricted to Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometers. Here, we demonstrate the capabilities of an Orbitrap-based UHR MSI platform to reach over 1,000,000 mass resolution in a lipid mass range (600-950 Da). Externally coupling the Orbitrap Q Exactive HF with the high-performance data acquisition system FTMS Booster X2 provided access to the unreduced data in the form of full-profile absorption-mode FT mass spectra. In addition, it allowed us to increase the time-domain transient length from 0.5 to 10 s, providing improvement in the mass resolution, signal-to-noise ratio, and mass accuracy. The resulting UHR performance generates high-quality MALDI MSI images and simplifies the identification of lipids. Collectively, these improvements resulted in a 1.5-fold increase in annotations, demonstrating the advantages of this UHR imaging platform for spatial lipidomics using MALDI-MSI.

FT-ICR MS Spectral Improvement of Dissolved Organic Matter by the Absorption Mode: A Comparison of the Electrospray Ionization in Positive-Ion and Negative-Ion Modes

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) in the absorption mode has a superior performance over the conventional magnitude mode. However, this improved performance for the analysis of dissolved organic matter (DOM) in negative-ion and positive-ion modes of electrospray ionization [ESI(-) and ESI(+), respectively] remains unknown. This study systemically compared the improved performance by the absorption mode for DOM FT-ICR MS spectra acquired with the low-field and high-field magnet instruments between two charge modes. The absorption mode enhanced the resolution and signal-to-noise ratio values of DOM peaks with factors of 1.88-1.94 and 1.60-1.72, respectively. The significantly higher improvement of mass resolution for the ESI(+) mode than that for the ESI(-) mode could resolve the extensive occurrence of mass doublets in the ESI(+) mode, yielding some formulas exclusively identified in the ESI(+) mode. The findings of this study have systemically demonstrated the superiority of the absorption mode in improving the spectra quality during the routine FT-ICR MS postdata analysis and highlighted its great potential in characterizing the molecular composition of DOM using the FT-ICR MS technique in both ESI(-) and ESI(+) modes.

Unlocking the Hidden Depths: Multi-Modal Integration of Imaging Mass Spectrometry-Based and Molecular Imaging Techniques

Multimodal imaging (MMI) has emerged as a powerful tool in clinical research, combining different imaging modes to acquire comprehensive information and enabling scientists and surgeons to study tissue identification, localization, metabolic activity, and molecular discovery, thus aiding in disease progression analysis. While multimodal instruments are gaining popularity, challenges such as non-standardized characteristics, custom software, inadequate commercial support, and integration issues with other instruments need to be addressed. The field of multimodal imaging or multiplexed imaging allows for simultaneous signal reproduction from multiple imaging strategies. Intraoperatively, MMI can be integrated into frameless stereotactic surgery. Recent developments in medical imaging modalities such as magnetic resonance imaging (MRI), and Positron Emission Topography (PET) have brought new perspectives to multimodal imaging, enabling early cancer detection, molecular tracking, and real-time progression monitoring. Despite the evidence supporting the role of MMI in surgical decision-making, there is a need for comprehensive studies to validate and perform integration at the intersection of multiple imaging technologies. They were integrating mass spectrometry-based technologies (e.g., imaging mass spectrometry (IMS), imaging mass cytometry (IMC), and Ion mobility mass spectrometry ((IM-IM) with medical imaging modalities, offering promising avenues for molecular discovery and clinical applications. This review emphasizes the potential of multi-omics approaches in tissue mapping using MMI integrated into desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI), allowing for sequential analyses of the same section. By addressing existing knowledge gaps, this review encourages future research endeavors toward multi-omics approaches, providing a roadmap for future research and enhancing the value of MMI in molecular pathology for diagnosis.

A new dual-ligand DUT-52-type metal-organic framework for ratiometric luminescence detection of aqueous-phase Cu2+ and Cr2O72

Metal-organic frameworks (MOFs) are a unique class of multifunctional hybrid crystals that have been successfully utilized in diverse ranges of applications. However, since MOFs are prone to aqueous degradation, the development of stable luminescent MOF platforms in aqueous media is still a huge challenge. Here, a novel dual-ligand Eu³⁺/DUT-52-COOH composite is prepared based on the luminescent DUT-52 prototype structure via a dual-ligand strategy and a post-synthetic modification (PSM) method. The functionalized Eu³⁺/DUT-52-COOH material exhibits dual emission and good photothermal stability in aqueous media. Thus, Eu³⁺/DUT-52-COOH is developed as a ratiometric luminescent sensor to achieve highly selective and sensitive detection of Cu²⁺ and Cr₂O₇^2- in aqueous solutions and has a low detection limit of 3.43 μM and 25.7 nM, respectively. This work is one of the few cases of detecting Cu²⁺ and Cr₂O₇^2- in aqueous media based on a DUT-52, and the detection signals can be observed by the bare eye without using sophisticated analytical instruments. The possible sensing mechanism is discussed in detail. The results obtained in this project may provide broad prospects for developing smart sensing systems to accomplish highly efficient, easily operable and quantitative intelligent recognition of Cu²⁺ and Cr₂O₇^2-.

High-Throughput Mass Spectrometry Imaging of Biological Systems: Current Approaches and Future Directions

In the past two decades, the power of mass spectrometry imaging (MSI) for the label free spatial mapping of molecules in biological systems has been substantially enhanced by the development of approaches for imaging with high spatial resolution. With the increase in the spatial resolution, the experimental throughput has become a limiting factor for imaging of large samples with high spatial resolution and 3D imaging of tissues. Several experimental and computational approaches have been recently developed to enhance the throughput of MSI. In this critical review, we provide a succinct summary of the current approaches used to improve the throughput of MSI experiments. These approaches are focused on speeding up sampling, reducing the mass spectrometer acquisition time, and reducing the number of sampling locations. We discuss the rate-determining steps for different MSI methods and future directions in the development of high-throughput MSI techniques.

Novel Hybrid Quadrupole-Multireflecting Time-of-Flight Mass Spectrometry System

A novel mass spectrometry system is described here comprising a quadrupole-multireflecting time-of-flight design. The new multireflecting time-of-flight analyzer has an effective path length of 48 m and employs planar, gridless ion mirrors providing fourth-order energy focusing resulting in resolving power over 200 000 fwhm and sub-ppm mass accuracy. We show how these attributes are maintained with relatively fast acquisition speeds, setting the system apart from other high resolution mass spectrometers. We have integrated this new system into both liquid chromatography-mass spectrometry and mass spectrometry imaging workflows to demonstrate how the instrument characteristics are of benefit to these applications.

Emerging Computational Methods in Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds of molecules in biological samples with high sensitivity and molecular specificity. Advanced MSI platforms with capability of high-spatial resolution and high-throughput acquisition generate vast amount of data, which necessitates the development of computational tools for MSI data analysis. In addition, computation-driven MSI experiments have recently emerged as enabling technologies for further improving the MSI capabilities with little or no hardware modification. This review provides a critical summary of computational methods and resources developed for MSI data analysis and interpretation along with computational approaches for improving throughput and molecular coverage in MSI experiments. This review is focused on the recently developed artificial intelligence methods and provides an outlook for a future paradigm shift in MSI with transformative computational methods.

Temporal chemical composition changes in water below a crude oil slick irradiated with natural sunlight

Photooxidation can alter the environmental fate and effects of spilled oil. To better understand this process, oil slicks were generated on seawater mesocosms and exposed to sunlight for 8 days. The molecular composition of seawater under irradiated and non-irradiated oil slicks was characterized using ion mobility spectrometry-mass spectrometry and polyaromatic hydrocarbons analyses. Biomimetic extraction was performed to quantify neutral and ionized constituents. Results show that seawater underneath irradiated oil showed significantly higher amounts of hydrocarbons with oxygen- and sulfur-containing by-products peaking by day 4-6; however, concentrations of dissolved organic carbon were similar. Biomimetic extraction indicated toxic units in irradiated mesocosms increased, mainly due to ionized components, but remained <1, suggesting limited potential for ecotoxicity. Because the experimental design mimicked important aspects of natural conditions (freshly collected seawater, natural sunlight, and relevant oil thickness and concentrations), this study improves our understanding of the effects of photooxidation during a marine oil spill.

High-Throughput Mass Spectrometry Imaging with Dynamic Sparse Sampling

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.

Square wave voltammetric approach to leptin immunosensing and optimization of driving parameters with chemometrics

Square wave voltammetry serves as an effective analytical means to evaluate antigen-antibody coupling at the solid-liquid interface. Herein, we describe 3-aminopropyltrimethoxysilane (APTMS) induced irreversible immobilization of anti-leptin to micellar gold nanoparticles (AuNPs). Antibodies (Abs) were orthogonally loaded on micellized AuNP assemblies via amino residual groups. The ratio of bound Ab molecules was determined by the Bradford assay. The AuNP/Ab layer modified electrodes with variable antibody surface coverage (∼400 ± 55-200 ± 30 Ab/NP) were analyzed in terms of change in backward, net current (Ip) components. The rate of antigen coupling was found to be consistent with the variation in antibody density as well as the binding affinity. The lowest detection limit was observed at the femtomolar level (0.25 fM/mL) over a wide range of antigen concentration (6.2 ng/mL to 0.12 fg/mL). The variables affecting the epitope-paratope interaction were further optimized using a chemometric approach and a response surface methodology (RSM).

Comparing DESI-MSI and MALDI-MSI Mediated Spatial Metabolomics and Their Applications in Cancer Studies

Metabolic heterogeneity of cancer contributes significantly to its poor treatment outcomes and prognosis. As a result, studies continue to focus on identifying new biomarkers and metabolic vulnerabilities, both of which depend on the understanding of altered metabolism in cancer. In the recent decades, the rise of mass spectrometry imaging (MSI) enables the in situ detection of large numbers of small molecules in tissues. Therefore, researchers look to using MSI-mediated spatial metabolomics to further study the altered metabolites in cancer patients. In this review, we examined the two most commonly used spatial metabolomics techniques, MALDI-MSI and DESI-MSI, and some recent highlights of their applications in cancer studies. We also described AFADESI-MSI as a recent variation from the DESI-MSI and compare it with the two major techniques. Specifically, we discussed spatial metabolomics results in four types of heterogeneous malignancies, including breast cancer, esophageal cancer, glioblastoma and lung cancer. Multiple studies have effectively classified cancer tissue subtypes using altered metabolites information. In addition, distribution trends of key metabolites such as fatty acids, high-energy phosphate compounds, and antioxidants were identified. Therefore, while the visualization of finer distribution details requires further improvement of MSI techniques, past studies have suggested spatial metabolomics to be a promising direction to study the complexity of cancer pathophysiology.

Enhancing the Throughput of FT Mass Spectrometry Imaging Using Joint Compressed Sensing and Subspace Modeling

Mass spectrometry imaging (MSI) allows for untargeted mapping of the chemical composition of tissues with attomole detection limits. MSI using Fourier transform (FT)-based mass spectrometers, such as FT-ion cyclotron resonance (FT-ICR), grants the ability to examine the chemical space with unmatched mass resolution and mass accuracy. However, direct imaging of large tissue samples using FT-ICR is slow. In this work, we present an approach that combines the subspace modeling of ICR temporal signals with compressed sensing to accelerate high-resolution FT-ICR MSI. A joint subspace and spatial sparsity constrained model computationally reconstructs high-resolution MSI data from the sparsely sampled transients with reduced duration, allowing a significant reduction in imaging time. Simulation studies and experimental implementation of the proposed method in investigation of brain tissues demonstrate a 10-fold enhancement in throughput of FT-ICR MSI, without the need for instrumental or hardware modifications.

Applications and advancements of FT-ICR-MS for interactome studies

The set of all intra- and intermolecular interactions, collectively known as the interactome, is currently an unmet challenge for any analytical method, but if measured, could provide unparalleled insight on molecular function in living systems. Developments and applications of chemical cross-linking and high-performance mass spectrometry technologies are beginning to reveal details on how proteins interact in cells and how protein conformations and interactions inside cells change with phenotype or during drug treatment or other perturbations. A major contributor to these advances is Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) technology and its implementation with accurate mass measurements on cross-linked peptide-pair precursor and fragment ions to enable improved identification methods. However, these applications place increased demands on mass spectrometer performance in terms of high-resolution spectral acquisition rates for on-line MSⁿ experiments. Moreover, FT-ICR-MS also offers unique opportunities to develop and implement parallel ICR cells for multiplexed signal acquisition and the potential to greatly advance accurate mass acquisition rates for interactome studies. This review highlights our efforts to exploit accurate mass FT-ICR-MS technologies with chemical cross-linking and developments being pursued to realize parallel MS array capabilities that will further advance visualization of the interactome.

Fourier transform ion cyclotron resonance mass spectrometry at the true cyclotron frequency

Ion cyclotron resonance (ICR) cells provide stability and coherence of ion oscillations in crossed electric and magnetic fields over extended periods of time. Using the Fourier transform enables precise measurements of ion oscillation frequencies. These precisely measured frequencies are converted into highly accurate mass-to-charge ratios of the analyte ions by calibration procedures. In terms of resolution and mass accuracy, Fourier transform ICR mass spectrometry (FT-ICR MS) offers the highest performance of any MS technology. This is reflected in its wide range of applications. However, in the most challenging MS application, for example, imaging, enhancements in the mass accuracy of fluctuating ion fluxes are required to continue advancing the field. One approach is to shift the ion signal power into the peak corresponding to the true cyclotron frequency instead of the reduced cyclotron frequency peak. The benefits of measuring the true cyclotron frequency include increased tolerance to electric fields within the ICR cell, which enhances frequency measurement precision. As a result, many attempts to implement this mode of FT-ICR MS operation have occurred. Examples of true cyclotron frequency measurements include detection of magnetron inter-harmonics of the reduced cyclotron frequency (i.e., the sidebands), trapping field-free (i.e., screened) ICR cells, and hyperbolic ICR cells with quadrupolar ion detection. More recently, ICR cells with spatially distributed ion clouds have demonstrated attractive performance characteristics for true cyclotron frequency ion detection. Here, we review the corresponding developments in FT-ICR MS over the past 40 years.

Imaging and Direct Sampling Capabilities of Nanospray Desorption Electrospray Ionization with Absorption-Mode 21 Tesla Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

Nanospray desorption electrospray ionization mass spectrometry, a powerful ambient sampling and imaging technique, is herein coupled as an isolated source with 21 Tesla (21T) Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS). Absorption-mode data, enabled by an external data acquisition system, is applied for improved mass resolution, accuracy, and dynamic range without compromising spectral acquisition rates. Isotopic fine structure (IFS) information is obtained from the ambient sampling of living Bacillus and Fusarium species, allowing for high confidence in molecular annotations with a resolution >830 k (at m/z 825). Tandem mass spectrometry experiments for biological samples are shown to retain the IFS in addition to gained fragmentation information, providing a further degree of annotation confidence from ambient analyses. Rat brain was imaged by nanospray desorption electrospray ionization (nano-DESI) 21T FTICR MS in ∼5 h using 768 ms transients, producing over 800 molecular annotations using the METASPACE platform and low-parts-per-billion mass accuracy at a spatial resolution of ∼25 × 180 μm. Finally, nano-DESI 21T FTICR MS imaging is demonstrated to reveal images corresponding to the IFS, as well as hundreds of additional molecular features (including demonstrated differences as low as 8.96 mDa) that are otherwise undetected by a more conventional imaging methodology.

Adapting a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer for Gas-Phase Fluorescence Spectroscopy Measurement of Trapped Biomolecular Ions

Gas-phase fluorescence spectroscopy is still in its infancy, which demands further instrumental developments. In this study, a Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR MS), equipped with a lab-developed data acquisition system, was coupled to a tunable femtosecond laser and a state-of-the-art optical system for fluorescence studies of mass-selected ions. For excitation, a laser beam was focused (beam size < 1.0 mm) into the cylindrical ICR cell. A wire mesh replaced the back trapping plate, allowing ∼10% of the fluorescence emitted from trapped ions to be collected by a lens installed beside the wire mesh. The collected fluorescence light was then transmitted outside of the mass spectrometer via fiber optics. A novel accumulation during detection (ADD) scheme was developed to increase the duty cycle of gas-phase fluorescence spectroscopy experiments. With ADD, >90% duty cycle for mass spectrometry and fluorescence experiments could be achieved. This instrument was able to perform fluorescence experiments on various ions, from simple rhodamine dyes to large biomolecules (i.e., peptides and proteins) labeled with dyes of various optical properties. A fluorescence lifetime measurement of trapped rhodamine 6G cations was also performed, yielding a value of 5.97 ± 0.23 ns. This setup has a broad mass range and decent fluorescence spectroscopy performance (i.e., the emission spectrum of rhodamine 6G can be acquired with good S/N in a minute). Finally, this setup also allows more challenging gas-phase fluorescence spectroscopy experiments, for example, of low quantum yield fluorophores and large biomolecules in their native state that appear at high m/z, which may not be doable with quadrupole ion traps (QIT).

Integrative Metabolomics Reveals Deep Tissue and Systemic Metabolic Remodeling in Glioblastoma

(1) Background: Glioblastoma is the most common malignant brain tumor in adults. Its etiology remains unknown in most cases. Glioblastoma pathogenesis consists of a progressive infiltration of the white matter by tumoral cells leading to progressive neurological deficit, epilepsy, and/or intracranial hypertension. The mean survival is between 15 to 17 months. Given this aggressive prognosis, there is an urgent need for a better understanding of the underlying mechanisms of glioblastoma to unveil new diagnostic strategies and therapeutic targets through a deeper understanding of its biology. (2) Methods: To systematically address this issue, we performed targeted and untargeted metabolomics-based investigations on both tissue and plasma samples from patients with glioblastoma. (3) Results: This study revealed 176 differentially expressed lipids and metabolites, 148 in plasma and 28 in tissue samples. Main biochemical classes include phospholipids, acylcarnitines, sphingomyelins, and triacylglycerols. Functional analyses revealed deep metabolic remodeling in glioblastoma lipids and energy substrates, which unveils the major role of lipids in tumor progression by modulating its own environment. (4) Conclusions: Overall, our study demonstrates in situ and systemic metabolic rewiring in glioblastoma that could shed light on its underlying biological plasticity and progression to inform diagnosis and/or therapeutic strategies.

New Advances in Tissue Metabolomics: A Review

Metabolomics offers a hypothesis-generating approach for biomarker discovery in clinical medicine while also providing better understanding of the underlying mechanisms of chronic diseases. Clinical metabolomic studies largely rely on human biofluids (e.g., plasma, urine) as a more convenient specimen type for investigation. However, biofluids are non-organ specific reflecting complex biochemical processes throughout the body, which may complicate biochemical interpretations. For these reasons, tissue metabolomic studies enable deeper insights into aberrant metabolism occurring at the direct site of disease pathogenesis. This review highlights new advances in metabolomics for ex vivo analysis, as well as in situ imaging of tissue specimens, including diverse tissue types from animal models and human participants. Moreover, we discuss key pre-analytical and post-analytical challenges in tissue metabolomics for robust biomarker discovery with a focus on new methodological advances introduced over the past six years, including innovative clinical applications for improved screening, diagnostic testing, and therapeutic interventions for cancer.

Drug-to-Antibody Ratio Estimation via Proteoform Peak Integration in the Analysis of Antibody-Oligonucleotide Conjugates with Orbitrap Fourier Transform Mass Spectrometry

The therapeutic efficacy and pharmacokinetics of antibody-drug conjugates (ADCs) in general, and antibody-oligonucleotide conjugates (AOCs) in particular, depend on the drug-to-antibody ratio (DAR) distribution and average value. The DAR is considered a critical quality attribute, and information pertaining to it needs to be gathered during ADC/AOC development, production, and storage. However, because of the high structural complexity of ADC/AOC samples, particularly in the initial drug-development stages, the application of the current state-of-the-art mass spectrometric approaches can be limited for DAR analysis. Here, we demonstrate a novel approach for the analysis of complex ADC/AOC samples, following native size-exclusion chromatography Orbitrap Fourier transform mass spectrometry (FTMS). The approach is based on the integration of the proteoform-level mass spectral peaks in order to provide an estimate of the DAR distribution and its average value with less than 10% error. The peak integration is performed via a truncation of the Orbitrap's unreduced time-domain ion signals (transients) before mass spectra generation via FT processing. Transient recording and processing are undertaken using an external data acquisition system, FTMS Booster X2, coupled to a Q Exactive HF Orbitrap FTMS instrument. This approach has been applied to the analysis of whole and subunit-level trastuzumab conjugates with oligonucleotides. The obtained results indicate that ADC/AOC sample purification or simplification procedures, for example, deglycosylation, could be omitted or minimized prior to the DAR analysis, streamlining the drug-development process.

Radiomics feature stability of open-source software evaluated on apparent diffusion coefficient maps in head and neck cancer

Radiomics is a promising technique for discovering image based biomarkers of therapy response in cancer. Reproducibility of radiomics features is a known issue that is addressed by the image biomarker standardisation initiative (IBSI), but it remains challenging to interpret previously published radiomics signatures. This study investigates the reproducibility of radiomics features calculated with two widely used radiomics software packages (IBEX, MaZda) in comparison to an IBSI compliant software package (PyRadiomics). Intensity histogram, shape and textural features were extracted from 334 diffusion weighted magnetic resonance images of 59 head and neck cancer (HNC) patients from the PREDICT-HN observational radiotherapy study. Based on name and linear correlation, PyRadiomics shares 83 features with IBEX and 49 features with MaZda, a sub-set of well correlated features are considered reproducible (IBEX: 15 features, MaZda: 18 features). We explore the impact of including non-reproducible radiomics features in a HNC radiotherapy response model. It is possible to classify equivalent patient groups using radiomic features from either software, but only when restricting the model to reliable features using a correlation threshold method. This is relevant for clinical biomarker validation trials as it provides a framework to assess the reproducibility of reported radiomic signatures from existing trials.

Facilitating Imaging Mass Spectrometry of Microbial Specialized Metabolites with METASPACE

Metabolite annotation from imaging mass spectrometry (imaging MS) data is a difficult undertaking that is extremely resource intensive. Here, we adapted METASPACE, cloud software for imaging MS metabolite annotation and data interpretation, to quickly annotate microbial specialized metabolites from high-resolution and high-mass accuracy imaging MS data. Compared with manual ion image and MS1 annotation, METASPACE is faster and, with the appropriate database, more accurate. We applied it to data from microbial colonies grown on agar containing 10 diverse bacterial species and showed that METASPACE was able to annotate 53 ions corresponding to 32 different microbial metabolites. This demonstrates METASPACE to be a useful tool to annotate the chemistry and metabolic exchange factors found in microbial interactions, thereby elucidating the functions of these molecules.

Intraoperative Mass Spectrometry Platform for IDH Mutation Status Prediction, Glioma Diagnosis, and Estimation of Tumor Cell Infiltration

BACKGROUND

Surgical tumor resection is the primary treatment option for diffuse glioma, the most common malignant brain cancer. The intraoperative diagnosis of gliomas from tumor core samples can be improved by use of molecular diagnostics. Further, residual tumor at surgical margins is a primary cause of tumor recurrence and malignant progression. This study evaluates a desorption electrospray ionization mass spectrometry (DESI-MS) system for intraoperative isocitrate dehydrogenase (IDH) mutation assessment, estimation of tumor cell infiltration as tumor cell percentage (TCP), and disease status. This information could be used to enhance the extent of safe resection and so potentially improve patient outcomes.

METHODS

A mobile DESI-MS instrument was modified and used in neurosurgical operating rooms (ORs) on a cohort of 49 human subjects undergoing craniotomy with tumor resection for suspected diffuse glioma. Small tissue biopsies (ntotal = 203) from the tumor core and surgical margins were analyzed by DESI-MS in the OR and classified using univariate and multivariate statistical methods.

RESULTS

Assessment of IDH mutation status using DESI-MS/MS to measure 2-hydroxyglutarate (2-HG) ion intensities from tumor cores yielded a sensitivity, specificity, and overall diagnostic accuracy of 89, 100, and 94%, respectively (ncore = 71). Assessment of TCP (categorized as low or high) in tumor margin and core biopsies using N-acetyl-aspartic acid (NAA) intensity provided a sensitivity, specificity, and accuracy of 91, 76, and 83%, respectively (ntotal = 203). TCP assessment using lipid profile deconvolution provided sensitivity, specificity, and accuracy of 76, 85, and 81%, respectively (ntotal = 203). Combining the experimental data and using PCA-LDA predictions of disease status, the sensitivity, specificity, and accuracy in predicting disease status are 63%, 83%, and 74%, respectively (ntotal = 203).

CONCLUSIONS

The DESI-MS system allowed for identification of IDH mutation status, glioma diagnosis, and estimation of tumor cell infiltration intraoperatively in a large human glioma cohort. This methodology should be further refined for clinical diagnostic applications.

Improved Uranium Isotope Ratio Analysis in Liquid Sampling-Atmospheric Pressure Glow Discharge/Orbitrap FTMS Coupling through the Use of an External Data Acquisition System

Isotope ratio (IR) analysis of natural abundance uranium presents a formidable challenge for mass spectrometry (MS): the required spectral dynamic range needs to enable the quantitatively accurate measurement of the ²³⁴UO₂ species present at ∼0.0053% isotopic abundance. We address this by empowering a benchtop Orbitrap Fourier transform mass spectrometer (FTMS) coupled with the liquid sampling-atmospheric pressure glow discharge (LS-APGD) ion source and an external high-performance data acquisition system, FTMS Booster X2. The LS-APGD microplasma has demonstrated impressive capabilities regarding elemental and IR analysis when coupled with Orbitrap FTMS. Despite successes, there are limitations regarding the dynamic range and mass resolution that stem from space charge effects and data acquisition and processing restrictions. To overcome these limitations, the FTMS Booster was externally interfaced to an LS-APGD Q Exactive Focus Orbitrap FTMS to obtain time-domain signals (transients) and to process unreduced data. The unreduced time-domain data acquisition with user-controlled processing permit the evaluation of the effects of in-hardware transient phasing, increased transient lengths, advanced transient coadding, varying the length of a transient to be processed with a user-defined time increment, and the use of absorption-mode FT (aFT) processing methods on IR analysis. The added capabilities extend the spectral dynamic range of the instrument to at least 4-5 orders of magnitude and provide a resolution improvement from ∼70k to 900k m/Δm at 200 m/z. The empowered LS-APGD Orbitrap platform allows for the simultaneous measurement of ²³⁴UO₂ and the prominent ²³⁵UO₂ and ²³⁸UO₂ isotopic species at their natural abundances, ultimately yielding improvements in performance when compared to previous uranium IR results on this same Q Exactive Focus instrument.

Streamlined Multimodal DESI and MALDI Mass Spectrometry Imaging on a Singular Dual-Source FT-ICR Mass Spectrometer

The study of biological specimens by mass spectrometry imaging (MSI) has had a profound influence in the various forms of spatial-omics over the past two decades including applications for the identification of clinical biomarker analysis; the metabolic fingerprinting of disease states; treatment with therapeutics; and the profiling of lipids, peptides and proteins. No singular approach is able to globally map all biomolecular classes simultaneously. This led to the development of many complementary multimodal imaging approaches to solve analytical problems: fusing multiple ionization techniques, imaging microscopy or spectroscopy, or local extractions into robust multimodal imaging methods. However, each fusion typically requires the melding of analytical information from multiple commercial platforms, and the tandem utilization of multiple commercial or third-party software platforms—even in some cases requiring computer coding. Herein, we report the use of matrix-assisted laser desorption/ionization (MALDI) in tandem with desorption electrospray ionization (DESI) imaging in the positive ion mode on a singular commercial orthogonal dual-source Fourier transform ion cyclotron resonance (FT-ICR) instrument for the complementary detection of multiple analyte classes by MSI from tissue. The DESI source was 3D printed and the commercial Bruker Daltonics software suite was used to generate mass spectrometry images in tandem with the commercial MALDI source. This approach allows for the generation of multiple modes of mass spectrometry images without the need for third-party software and a customizable platform for ambient ionization imaging. Highlighted is the streamlined workflow needed to obtain phospholipid profiles, as well as increased depth of coverage of both annotated phospholipid, cardiolipin, and ganglioside species from rat brain with both high spatial and mass resolution.

Adaptive Pixel Mass Recalibration for Mass Spectrometry Imaging Based on Locally Endogenous Biological Signals

Mass spectrometry imaging (MSI) is a powerful and convenient method for revealing the spatial chemical composition of different biological samples. Molecular annotation of the detected signals is only possible if a high mass accuracy is maintained over the entire image and the m/z range. However, the change in the number of ions from pixel-to-pixel of the biological samples could lead to small fluctuations in the detected m/z-values, called mass shift. The use of internal calibration is known to offer the best solution to avoid, or at least to reduce, mass shifts. Their "a priori" selection for a global MSI acquisition is prone to false positive detection and therefore to poor recalibration. To fill this gap, this work describes an algorithm that recalibrates each spectrum individually by estimating its mass shift with the help of a list of pixel-specific internal calibrating ions, automatically generated in a data-adaptive manner (https://github.com/LaRoccaRaphael/MSI_recalibration). Through a practical example, we applied the methodology to a zebrafish whole-body section acquired at a high mass resolution to demonstrate the impact of mass shift on data analysis and the capability of our algorithm to recalibrate MSI data. In addition, we illustrate the broad applicability of the method by recalibrating 31 different public MSI data sets from METASPACE from various samples and types of MSI and show that our recalibration significantly increases the numbers of METASPACE annotations (gaining from 20 up to 400 additional annotations), particularly the high-confidence annotations with a low false discovery rate.

Muscle metabolic remodelling patterns in Duchenne muscular dystrophy revealed by ultra-high-resolution mass spectrometry imaging

Duchenne muscular dystrophy (DMD) is a common and severe X-linked myopathy, characterized by muscle degeneration due to altered or absent dystrophin. DMD has no effective cure, and the underlying molecular mechanisms remain incompletely understood. The aim of this study is to investigate the metabolic changes in DMD using mass spectrometry-based imaging. Nine human muscle biopsies from DMD patients and nine muscle biopsies from control individuals were subjected to untargeted MSI using matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry. Both univariate and pattern recognition techniques have been used for data analysis. This study revealed significant changes in 34 keys metabolites. Seven metabolites were decreased in the Duchenne biopsies compared to control biopsies including adenosine triphosphate, and glycerophosphocholine. The other 27 metabolites were increased in the Duchenne biopsies, including sphingomyelin, phosphatidylcholines, phosphatidic acids and phosphatidylserines. Most of these dysregulated metabolites are tightly related to energy and phospholipid metabolism. This study revealed a deep metabolic remodelling in phospholipids and energy metabolism in DMD. This systems-based approach enabled exploring the metabolism in DMD in an unprecedented holistic and unbiased manner with hypothesis-free strategies.

Monitoring glycation levels of a bispecific monoclonal antibody at subunit level by ultrahigh-resolution MALDI FT-ICR mass spectrometry

Bispecific monoclonal antibodies (BsAbs) are engineered proteins with multiple functionalities and properties. The "bi-specificity" of these complex biopharmaceuticals is a key characteristic for the development of novel and more effective therapeutic strategies. The high structural complexity of BsAbs poses a challenge to the analytical methods needed for their characterization. Modifications of the BsAb structure, resulting from enzymatic and non-enzymatic processes, further complicate the analysis. An important example of the latter type of modification is glycation, which can occur in the manufacturing process, during storage in the formulation or in vivo after application of the drug. Glycation affects the structure, function, and stability of monoclonal antibodies, and consequently, a detailed analysis of glycation levels is required. Mass spectrometry (MS) plays a key role in the structural characterization of monoclonal antibodies and top-down, middle-up and middle-down MS approaches are increasingly used for the analysis of modifications. Here, we apply a novel middle-up strategy, based on IdeS digestion and matrix-assisted laser desorption ionization (MALDI) Fourier transform ion cyclotron resonance (FT-ICR) MS, to analyze all six different BsAb subunits in a single high-resolution mass spectrum, namely two light chains, two half fragment crystallizable regions and two Fd' regions, thus avoiding upfront chromatography. This method was used to monitor glycation changes during a 168 h forced-glycation experiment. In addition, hot spot glycation sites were localized using top-down and middle-down MALDI-in-source decay FT-ICR MS, which provided complementary information compared to standard bottom-up MS.

Accelerating Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry Imaging Using a Subspace Approach

We present a subspace method that accelerates data acquisition using Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometry imaging (MSI). For MSI of biological tissue samples, there is a finite number of heterogeneous tissue types with distinct chemical profiles that introduce redundancy in the high-dimensional measurements. Our subspace model exploits the redundancy in data measured from whole-slice tissue samples by decomposing the transient signals into linear combinations of a set of basis transients with the desired spectral resolution. This decomposition allowed us to design a strategy that acquires a subset of long transients for basis determination and short transients for the remaining pixels, drastically reducing the acquisition time. The computational reconstruction strategy can maintain high-mass-resolution and spatial-resolution MSI while providing a 10-fold improvement in throughput. We validated the capability of the subspace model using a rat sagittal brain slice imaging data set. Comprehensive evaluation of the quality of the mass spectral and ion images demonstrated that the reconstructed data produced by the reported method required only 15% of the typical acquisition time and exhibited both qualitative and quantitative consistency when compared to the original data. Our method enables either higher sample throughput or higher-resolution images at similar acquisition lengths, providing greater flexibility in obtaining FT-ICR MSI measurements.

Narrow Aperture Detection Electrodes ICR Cell with Quadrupolar Ion Detection for FT-ICR MS at the Cyclotron Frequency

Ion signal detection at the true (unperturbed) cyclotron frequency instead of the conventional reduced cyclotron frequency has remained a formidable challenge since the inception of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Recently, routine FT-ICR MS at the true cyclotron frequency has become a reality with the implementation of ICR cells with narrow aperture detection electrodes (NADEL). Here, we describe the development and implementation of the next generation of these cells, namely, a 2xNADEL ICR cell, which comprises four flat detect and four ∼45° cylindrical excite electrodes, enabling independent ion excitation and quadrupolar ion detection. The performance of the 2xNADEL ICR cell was evaluated on two commercial FT-ICR MS platforms, 10 T LTQ FT from Thermo Scientific and 9.4 T SolariX XR from Bruker Daltonics. The cells provided accurate mass measurements in the analyses of singly and multiply charged peptides (root-mean-square, RMS, mass error Δm/m of 90 ppb), proteins (Δm/m = 200 ppb), and petroleum fractions (Δm/m < 200 ppb). Due to the reduced influence of measured frequency on the space charge and external (trapping) electric fields, the 2xNADEL ICR cells exhibited stable performance in a wide range of trapping potentials (1-20 V). Similarly, in a 13 h rat brain MALDI imaging experiment, the RMS mass error did not exceed 600 ppb even for low signal-to-noise ratio analyte peaks. Notably, the same set of calibration constants was applicable to Fourier spectra in all pixels, reducing the need for recalibration at the individual pixel level. Overall, these results support further experimental development and fundamentals investigation of this promising technology.

Transient-Mediated Simulations of FTMS Isotopic Distributions and Mass Spectra to Guide Experiment Design and Data Analysis

Fourier transform mass spectrometry (FTMS) applications require accurate analysis of extremely complex mixtures of species in wide mass and charge state ranges. To optimize the related FTMS data analysis accuracy, parameters for data acquisition and the allied data processing should be selected rationally, and their influence on the data analysis outcome is to be understood. To facilitate this selection process and to guide the experiment design and data processing workflows, we implemented the underlying algorithms in a software tool with a graphical user interface, FTMS Isotopic Simulator. This tool computes FTMS data via time-domain data (transient) simulations for user-defined molecular species of interest and FTMS instruments, including diverse Orbitrap FTMS models, followed by user-specified FT processing steps. Herein, we describe implementation and benchmarking of this tool for analysis of a wide range of compounds as well as compare simulated and experimentally generated FTMS data. In particular, we discuss the use of this simulation tool for narrowband, broadband, and low- and high-resolution analysis of small molecules, peptides, and proteins, up to the level of their isotopic fine structures. By demonstrating the allied FT processing artifacts, we raise awareness of a proper selection of FT processing parameters for modern applications of FTMS, including intact mass analysis of proteoforms and top-down proteomics. Overall, the described transient-mediated approach to simulate FTMS data has proven useful for supporting contemporary FTMS applications. We also find its utility in fundamental FTMS studies and creating didactic materials for FTMS teaching.

Mass spectrometry imaging as a potential technique for diagnostic of Huanglongbing disease using fast and simple sample preparation

Huanglongbing (HLB) is a disease of worldwide incidence that affects orange trees, among other commercial varieties, implicating in great losses to the citrus industry. The disease is transmitted through Diaphorina citri vector, which inoculates Candidatus Liberibacter spp. in the plant sap. HLB disease lead to blotchy mottle and fruit deformation, among other characteristic symptoms, which induce fruit drop and affect negatively the juice quality. Nowadays, the disease is controlled by eradication of sick, symptomatic plants, coupled with psyllid control. Polymerase chain reaction (PCR) is the technique most used to diagnose the disease; however, this methodology involves high cost and extensive sample preparation. Mass spectrometry imaging (MSI) technique is a fast and easily handled sample analysis that, in the case of Huanglongbing allows the detection of increased concentration of metabolites associated to the disease, including quinic acid, phenylalanine, nobiletin and sucrose. The metabolites abieta-8,11,13-trien-18-oic acid, suggested by global natural product social molecular networking (GNPS) analysis, and 4-acetyl-1-methylcyclohexene showed a higher distribution in symptomatic leaves and have been directly associated to HLB disease. Desorption electrospray ionization coupled to mass spectrometry imaging (DESI-MSI) allows the rapid and efficient detection of biomarkers in sweet oranges infected with Candidatus Liberibacter asiaticus and can be developed into a real-time, fast-diagnostic technique.

A Further Study on Multiperiod Health Diagnostics Methodology under a Single-Valued Neutrosophic Set

Employing the concept and function of tangency with similarity measures and counterpart distances for reliable medical consultations has been extensively studied in the past decades and results in lots of isomorphic measures for application. We compared the majority of such isomorphic measures proposed by various researchers and classified them into (a) maximum norm and (b) one-norm categories. Moreover, we found that previous researchers used monotonic functions to transform an identity function and resulted in complicated expressions. In this study, we provide a theoretical foundation to explain the isomorphic nature of a newer measure proposed by the following research paper against its studied existing one in deriving the same pattern recognition results. Specifically, this study initially proposes two similarity measures using maximum norm, arithmetic mean, and aggregation operators and followed by a detailed discussion on their mathematical characteristics. Subsequently, a simplified version of such measures is presented for easy application. This study completely covers two previous methods to point out that the complex approaches used were unnecessary. The findings will help physicians, patients, and their family members to obtain a proper medical diagnosis during multiple examinations.

Parallel Detection of Fundamental and Sixth Harmonic Signals Using an ICR Cell with Dipole and Sixth Harmonic Detectors

Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) is a powerful instrument for high-resolution analysis of biomolecules. However, relatively long signal acquisition periods are needed to achieve mass spectra with high resolution. The use of multiple detector electrodes for detection of harmonic frequencies has been introduced as one approach to increase scan rate for a given resolving power or to obtain increased resolving power for a given detection period. The achieved resolving power and scan rate increase linearly with the order of detected harmonic signals. In recent years, ICR cell geometries have been investigated to increase the order of the harmonic frequencies and enhance harmonic signal intensities. In this study, we demonstrated PCB-based ICR cell designs with dipole and sixth harmonic detectors for parallel detection of fundamental and harmonic (6f) signals. The sixth harmonic signals from the sixth harmonic detector showed an expected 6 times higher resolving power with (M + 3H)3+ charge state insulin ions as compared with that from fundamental signals from the dipole detector. Moreover, the insulin isotopic peaks with sixth harmonic frequency signals acquired with the sixth harmonic detector were resolved for a 40 ms data acquisition period but unresolved with the same duration dipole detector signals, corresponding to a 6-fold improvement in achievable spectral acquisition rates for a given resolving power.

Trace-Level Persistent Organic Pollutant Analysis with Gas-Chromatography Orbitrap Mass Spectrometry-Enhanced Performance by Complementary Acquisition and Processing of Time-Domain Data

The range of commercial techniques for high-resolution gas-chromatography-mass spectrometry (GC-MS) has been recently extended with the introduction of GC Orbitrap Fourier transform mass spectrometry (FTMS). We report on progress with quantitation performance in the analysis of persistent organic pollutants (POP), by averaging of time-domain signals (transients), from a number of GC-FTMS experiment replicates. Compared to a standard GC-FTMS measurement (a single GC-FTMS experiment replicate, mass spectra representation in reduced profile mode), for the 10 GC-FTMS technical replicates of ultratrace POP analysis, sensitivity improvement of up to 1 order of magnitude is demonstrated. The accumulation method was implemented with an external high-performance data acquisition system and dedicated data processing software to acquire the time-domain data for each GC-FTMS replicate and to average the acquired GC-FTMS data sets. Concomitantly, the increased flexibility in ion signal detection allowed the attainment of ultrahigh-mass resolution (UHR), approaching R = 700 000 at m/z = 200.

Ultra-High Mass Resolving Power, Mass Accuracy, and Dynamic Range MALDI Mass Spectrometry Imaging by 21-T FT-ICR MS

Detailed characterization of complex biological surfaces by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) requires instrumentation that is capable of high mass resolving power, mass accuracy, and dynamic range. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) offers the highest mass spectral performance for MALDI MSI experiments, and often reveals molecular features that are unresolved on lower performance instrumentation. Higher magnetic field strength improves all performance characteristics of FT-ICR; mass resolving power improves linearly, while mass accuracy and dynamic range improve quadratically with magnetic field strength. Here, MALDI MSI at 21T is demonstrated for the first time: mass resolving power in excess of 1 600 000 (at m/z 400), root-mean-square mass measurement accuracy below 100 ppb, and dynamic range per pixel over 500:1 were obtained from the direct analysis of biological tissue sections. Molecular features with m/z differences as small as 1.79 mDa were resolved and identified with high mass accuracy. These features allow for the separation and identification of lipids to the underlying structures of tissues. The unique molecular detail, accuracy, sensitivity, and dynamic range combined in a 21T MALDI FT-ICR MSI experiment enable researchers to visualize molecular structures in complex tissues that have remained hidden until now. The instrument described allows for future innovative, such as high-end studies to unravel the complexity of biological, geological, and engineered organic material surfaces with an unsurpassed detail.

Imaging and quantifying drug delivery in skin - Part 1: Autoradiography and mass spectrometry imaging

In this two-part review we present an up-to-date description of different imaging methods available to map the localization of drugs on skin as a complement of established ex-vivo absorption studies. This first part deals with invasive methods which are grouped in two classes according to their underlying principles: i) methods using radioactivity such as autoradiography and ii) mass spectrometry methods such as MALDI and SIMS. For each method, a description of the principle is given along with example applications of imaging and quantifying drug delivery in human skin. Thanks to these techniques a better assessment of the fate of drugs is obtained: its localization on a particular skin structure, its potential accumulation, etc. A critical comparison in terms of capabilities, sensitivity and practical applicability is included that will help the reader to select the most appropriate technique depending on the particular problem to be solved.