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The lack of standardization in antibody validation remains a major contributor to irreproducibility of human research. To address this, we have applied a standardized approach to validate a panel of antibodies to identify 18 major cell types and 5 extracellular matrix compartments in the human kidney by immunofluorescence (IF) microscopy. We have used these to generate an organ mapping antibody panel for two-dimensional (2-D) and three-dimensional (3-D) cyclical IF (CyCIF) to provide a more detailed method for evaluating tissue segmentation and volumes using a larger panel of markers than would normally be possible using standard fluorescence microscopy. CyCIF also makes it possible to perform multiplexed IF microscopy of whole slide images, which is a distinct advantage over other multiplexed imaging technologies that are applicable to limited fields of view. This enables a broader view of cell distributions across larger anatomical regions, allowing a better chance to capture localized regions of dysfunction in diseased tissues. These methods are broadly accessible to any laboratory with a fluorescence microscope, enabling spatial cellular phenotyping in normal and disease states. We also provide a detailed solution for image alignment between CyCIF cycles that can be used by investigators to perform these studies without programming experience using open-sourced software. This ability to perform multiplexed imaging without specialized instrumentation or computational skills opens the door to integration with more highly dimensional molecular imaging modalities such as spatial transcriptomics and imaging mass spectrometry, enabling the discovery of molecular markers of specific cell types, and how these are altered in disease. NEW & NOTEWORTHY We describe here validation criteria used to define on organ mapping panel of antibodies that can be used to define 18 cell types and five extracellular matrix compartments using cyclical immunofluorescence (CyCIF) microscopy. As CyCIF does not require specialized instrumentation, and image registration required to assemble CyCIF images can be performed by any laboratory without specialized computational skills, this technology is accessible to any laboratory with access to a fluorescence microscope and digital scanner.

Introduction: Autism is a common neurodevelopmental condition with a complex genetic aetiology that includes contributions from monogenic and polygenic factors. Many autistic people have unmet healthcare needs that could be served by genomics-informed research and clinical trials. The primary aim of the European Autism GEnomics Registry (EAGER) is to establish a registry of participants with a diagnosis of autism or an associated rare genetic condition who have undergone whole-genome sequencing. The registry can facilitate recruitment for future clinical trials and research studies, based on genetic, clinical and phenotypic profiles, as well as participant preferences. The secondary aim of EAGER is to investigate the association between mental and physical health characteristics and participants' genetic profiles., Methods and Analysis: EAGER is a European multisite cohort study and registry and is part of the AIMS-2-TRIALS consortium. EAGER was developed with input from the AIMS-2-TRIALS Autism Representatives and representatives from the rare genetic conditions community. 1500 participants with a diagnosis of autism or an associated rare genetic condition will be recruited at 13 sites across 8 countries. Participants will be given a blood or saliva sample for whole-genome sequencing and answer a series of online questionnaires. Participants may also consent to the study to access pre-existing clinical data. Participants will be added to the EAGER registry and data will be shared externally through established AIMS-2-TRIALS mechanisms., Ethics and Dissemination: To date, EAGER has received full ethical approval for 11 out of the 13 sites in the UK (REC 23/SC/0022), Germany (S-375/2023), Portugal (CE-085/2023), Spain (HCB/2023/0038, PIC-164-22), Sweden (Dnr 2023-06737-01), Ireland (230907) and Italy (CET_62/2023, CEL-IRCCS OASI/24-01-2024/EM01, EM 2024-13/1032 EAGER). Findings will be disseminated via scientific publications and conferences but also beyond to participants and the wider community (eg, the AIMS-2-TRIALS website, stakeholder meetings, newsletters)., Competing Interests: Competing interests: In the past 3 years, TC has served as a paid consultant to F. Hoffmann-La Roche and Servier and has received royalties from Sage Publications and Guilford Publications. DGMM has received funding for a PhD studentship from Compass, and for consulting from Jaguar Therapeutics and Hoffman Le Roche. GM receives funding for an investigator-initiated study from Compass Pathways; no financial or other conflict of interest with the present study. SB discloses that he has in the last 3 years acted as an author, consultant, or lecturer for Medice, Roche and Linus Biotechnology. SB receives royalties for textbooks and diagnostic tools from Hogrefe, UTB, Ernst Reinhardt, Kohlhammer, and Liber, and is a partner at NeuroSupportSolutions International AB. CC is a full-time employee of Genentech and owns stocks or RSUs in Roche Holdings. MA is the UK chief investigator for a trial sponsored by Roche (a phase II, randomised, double-blind, placebo-controlled, parallel group study to evaluate the safety, efficacy and pharmacodynamics of 52 weeks of treatment with basmasanil in participants aged 2–14 years old with dup15q syndrome followed by a 2-year optional open-label extension). LB served on an advisory board to Kingdom therapeutics in 2022., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

While probabilistic constellation shaping (PCS) enables rate and reach adaption with finer granularity [1], it imposes signal processing challenges at the receiver. Since the distribution of PCS-quadrature amplitude modulation (QAM) signals tends to be Gaussian, conventional blind polarization demultiplexing algorithms are not suitable for them [2]. It is known that independently and identically distributed (iid) Gaussian signals, when mixed, cannot be recovered/separated from their mixture. For PCS-QAM signals, there are algorithms such as [3], [4] which are designed by extending conventional blind algorithms used for uniform QAM signals. In these algorithms, an initialization point is obtained by processing only a part of the mixed signal, which have non-Gaussian statistics. In this paper, we propose an alternative method wherein we add temporal correlations at the transmitter, which are subsequently exploited at the receiver in order to separate the polarizations. We will refer to the proposed method as frequency domain (FD) joint diagonalization (JD) probability aware-multi modulus algorithm (pr-MMA), and it is suited to channels with moderate polarization mode dispersion (PMD) effects. Furthermore, we extend our previously proposed JD-MMA [5] by replacing the standard MMA with a pr-MMA, improving its performance. Both FDJD-pr-MMA and JD-pr-MMA are evaluated for a diverse range of PCS (entropy 𝓗 ) over a first-order PMD channel that is simulated in a proof-of-concept setup. A MMA initialized with a memoryless constant modulus algorithm (CMA) is used as a benchmark. We show that at a differential group delay (DGD) of 10% of symbol period T symb and 18 dB SNR/pol., JD-pr-MMA successfully demultiplexes the PCS signals, while CMA-MMA fails drastically. Furthermore, we demonstrate that the newly proposed FDJD-pr-MMA is robust against moderate PMD effects by evaluating it over a DGD of up to 40% of T symb . Our results show that the proposed FDJD-pr-MMA successfully equalizes PMD channels with a DGD up to 20% of T symb .

The Human BioMolecular Atlas Program (HuBMAP) aims to create a multi-scale spatial atlas of the healthy human body at single-cell resolution by applying advanced technologies and disseminating resources to the community. As the HuBMAP moves past its first phase, creating ontologies, protocols and pipelines, this Perspective introduces the production phase: the generation of reference spatial maps of functional tissue units across many organs from diverse populations and the creation of mapping tools and infrastructure to advance biomedical research., (© 2023. Springer Nature Limited.)

The glomerulus is a multicellular functional tissue unit (FTU) of the nephron that is responsible for blood filtration. Each glomerulus contains multiple substructures and cell types that are crucial for their function. To understand normal aging and disease in kidneys, methods for high spatial resolution molecular imaging within these FTUs across whole slide images is required. Here we demonstrate a workflow using microscopy-driven selected sampling to enable 5 μm pixel size matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) of all glomeruli within whole slide human kidney tissues. Such high spatial resolution imaging entails large numbers of pixels, increasing the data acquisition times. Automating FTU-specific tissue sampling enables high-resolution analysis of critical tissue structures, while concurrently maintaining throughput. Glomeruli were automatically segmented using coregistered autofluorescence microscopy data, and these segmentations were translated into MALDI IMS measurement regions. This allowed high-throughput acquisition of 268 glomeruli from a single whole slide human kidney tissue section. Unsupervised machine learning methods were used to discover molecular profiles of glomerular subregions and differentiate between healthy and diseased glomeruli. Average spectra for each glomerulus were analyzed using Uniform Manifold Approximation and Projection (UMAP) and k -means clustering, yielding 7 distinct groups of differentiated healthy and diseased glomeruli. Pixel-wise k -means clustering was applied to all glomeruli, showing unique molecular profiles localized to subregions within each glomerulus. Automated microscopy-driven, FTU-targeted acquisition for high spatial resolution molecular imaging maintains high-throughput and enables rapid assessment of whole slide images at cellular resolution and identification of tissue features associated with normal aging and disease.

Spatially targeted proteomics analyzes the proteome of specific cell types and functional regions within tissue. While spatial context is often essential to understanding biological processes, interpreting sub-region-specific protein profiles can pose a challenge due to the high-dimensional nature of the data. Here, we develop a multivariate approach for rapid exploration of differential protein profiles acquired from distinct tissue regions and apply it to analyze a published spatially targeted proteomics data set collected from Staphylococcus aureus -infected murine kidney, 4 and 10 days postinfection. The data analysis process rapidly filters high-dimensional proteomic data to reveal relevant differentiating species among hundreds to thousands of measured molecules. We employ principal component analysis (PCA) for dimensionality reduction of protein profiles measured by microliquid extraction surface analysis mass spectrometry. Subsequently, k -means clustering of the PCA-processed data groups samples by chemical similarity. Cluster center interpretation revealed a subset of proteins that differentiate between spatial regions of infection over two time points. These proteins appear involved in tricarboxylic acid metabolomic pathways, calcium-dependent processes, and cytoskeletal organization. Gene ontology analysis further uncovered relationships to tissue damage/repair and calcium-related defense mechanisms. Applying our analysis in infectious disease highlighted differential proteomic changes across abscess regions over time, reflecting the dynamic nature of host-pathogen interactions.

Imaging mass spectrometry (IMS) provides untargeted, highly multiplexed maps of molecular distributions in tissue. Ion images are routinely presented as heatmaps and can be overlaid onto complementary microscopy images that provide greater context. However, heatmaps use transparency blending to visualize both images, obscuring subtle quantitative differences and distribution gradients. Here, we developed a contour mapping approach that combines information from IMS ion intensity distributions with that of stained microscopy. As a case study, we applied this approach to imaging data from Staphylococcus aureus -infected murine kidney. In a univariate, or single molecular species, use-case of the contour map representation of IMS data, certain lipids colocalizing with regions of infection were selected using Pearson's correlation coefficient. Contour maps of these lipids overlaid with stained microscopy showed enhanced visualization of lipid distributions and spatial gradients in and around the bacterial abscess as compared to traditional heatmaps. The full IMS data set comprising hundreds of individual ion images was then grouped into a smaller subset of representative patterns using non-negative matrix factorization (NMF). Contour maps of these multivariate NMF images revealed distinct molecular profiles of the major abscesses and surrounding immune response. This contour mapping workflow also enabled a molecular visualization of the transition zone at the host-pathogen interface, providing potential clues about the spatial molecular dynamics beyond what histological staining alone provides. In summary, we developed a new IMS-based contour mapping approach to augment classical stained microscopy images, providing an enhanced and more interpretable visualization of IMS-microscopy multimodal molecular imaging data sets.

Gangliosides are acidic glycosphingolipids, containing ceramide moieties and oligosaccharide chains with one or more sialic acid residue(s) and are highly diverse isomeric structures with distinct biological roles. Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) enables the untargeted spatial analysis of gangliosides, among other biomolecules, directly from tissue sections. Integrating trapped ion mobility spectrometry with MALDI IMS allows for the analysis of isomeric lipid structures in situ. Here, we demonstrate the gas-phase separation and identification of disialoganglioside isomers GD1a and GD1b that differ in the position of a sialic acid residue, in multiple samples, including a standard mixture of both isomers, a biological extract, and directly from thin tissue sections. The unique spatial distributions of GD1a/b (d36:1) and GD1a/b (d38:1) isomers were determined in rat hippocampus and spinal cord tissue sections, demonstrating the ability to structurally characterize and spatially map gangliosides based on both the carbohydrate chain and ceramide moieties.

Introduction: Age related macular degeneration (AMD) causes legal blindness worldwide, with few therapeutic targets in early disease and no treatments for 80% of cases. Extracellular deposits, including drusen and subretinal drusenoid deposits (SDD; also called reticular pseudodrusen), disrupt cone and rod photoreceptor functions and strongly confer risk for advanced disease. Due to the differential cholesterol composition of drusen and SDD, lipid transfer and cycling between photoreceptors and support cells are candidate dysregulated pathways leading to deposit formation. The current study explores this hypothesis through a comprehensive lipid compositional analysis of SDD., Methods: Histology and transmission electron microscopy were used to characterize the morphology of SDD. Highly sensitive tools of imaging mass spectrometry (IMS) and nano liquid chromatography tandem mass spectrometry (nLC-MS/MS) in positive and negative ion modes were used to spatially map and identify SDD lipids, respectively. An interpretable supervised machine learning approach was utilized to compare the lipid composition of SDD to regions of uninvolved retina across 1873 IMS features and to automatically discern candidate markers for SDD. Immunohistochemistry (IHC) was used to localize secretory phospholipase A2 group 5 (PLA2G5)., Results: Among the 1873 detected features in IMS data, three lipid classes, including lysophosphatidylcholine (LysoPC), lysophosphatidylethanolamine (LysoPE) and lysophosphatidic acid (LysoPA) were observed nearly exclusively in SDD while presumed precursors, including phosphatidylcholine (PC), phosphatidylethanolamine (PE) and phosphatidic acid (PA) lipids were detected in SDD and adjacent photoreceptor outer segments. Molecular signals specific to SDD were found in central retina and elsewhere. IHC results indicated abundant PLA2G5 in photoreceptors and retinal pigment epithelium (RPE)., Discussion: The abundance of lysolipids in SDD implicates lipid remodeling or degradation in deposit formation, consistent with ultrastructural evidence of electron dense lipid-containing structures distinct from photoreceptor outer segment disks and immunolocalization of secretory PLA2G5 in photoreceptors and RPE. Further studies are required to understand the role of lipid signals observed in and around SDD., Competing Interests: TA has the following disclosures: Consultant for Roche, Novartis, Novartis, Bayer, Apellis Pharmaceutical Research support from Nidek outside this project. CC receives research funds from Genentech/Hoffman LaRoche and Heidelberg Engineering and consults for Apellis, Astellas, Boehringer Ingelheim, Character Biosciences, Osanni, and Annexon outside this project. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

The total uptake of prenatal aneuploidy screening for Down syndrome (DS) is increasing worldwide. As a result of increasing prenatal diagnosis of DS and subsequent termination of pregnancy, livebirth prevalence of DS is decreasing. The aim of this study is to explore the impact of an increasing uptake of prenatal aneuploidy screening on the neonatal mortality and morbidity in DS. This is a retrospective cohort study of 253 neonates with DS born between 2012 and 2018 that were seen at the outpatient clinic of five hospitals in the Netherlands. The medical files were reviewed for maternal and neonatal characteristics and neonatal morbidities. The Dutch national birth registry (Perined) provided mortality numbers of neonates with DS. The results were interpreted in the context of other published studies. Neonatal mortality in DS remained stable, ranging from 1.4 to 3.6%. A congenital heart defect (CHD) was found in 138 of the 251 neonates (55.0%) with atrial septal defect, atrioventricular septal defect, and ventricular septal defect being the most common. The type of CHD in DS did not change over time. Gastro-intestinal defects were present in 22 of the 252 neonates with DS (8.7%), with duodenal atresia as the most reported anomaly. Persistent pulmonary hypertension of the neonate (PPHN) was found in 31 of the 251 infants (12.4%).  Conclusions: Although uptake of prenatal aneuploidy screening increased, neonatal mortality and morbidity in DS appears to be stable. An increased incidence of PPHN was found. What is Known: • The total uptake of prenatal aneuploidy screening for Down syndrome is increasing worldwide. • As a result of increasing prenatal diagnosis of Down syndrome and subsequent termination of pregnancy, the livebirth prevalence of Down syndrome is decreasing. What is New: • Although uptake of prenatal aneuploidy screening increased, neonatal mortality and morbidity in Down syndrome appears to be stable. • An increased incidence of persistent pulmonary hypertension of the neonate was found., (© 2022. The Author(s).)

Introduction: Although Staphylococcus aureus is the leading cause of biofilm-related infections, the lipidomic distributions within these biofilms is poorly understood. Here, lipidomic mapping of S. aureus biofilm cross-sections was performed to investigate heterogeneity between horizontal biofilm layers., Methods: S. aureus biofilms were grown statically, embedded in a mixture of carboxymethylcellulose/gelatin, and prepared for downstream matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS). Trapped ion mobility spectrometry (TIMS) was also applied prior to mass analysis., Results: Implementation of TIMS led to a ∼ threefold increase in the number of lipid species detected. Washing biofilm samples with ammonium formate (150 mM) increased signal intensity for some bacterial lipids by as much as tenfold, with minimal disruption of the biofilm structure. MALDI TIMS IMS revealed that most lipids localize primarily to a single biofilm layer, and species from the same lipid class such as cardiolipins CL(57:0) - CL(66:0) display starkly different localizations, exhibiting between 1.5 and 6.3-fold intensity differences between layers (n = 3, p < 0.03). No horizontal layers were observed within biofilms grown anaerobically, and lipids were distributed homogenously., Conclusions: High spatial resolution analysis of S. aureus biofilm cross-sections by MALDI TIMS IMS revealed stark lipidomic heterogeneity between horizontal S. aureus biofilm layers demonstrating that each layer was molecularly distinct. Finally, this workflow uncovered an absence of layers in biofilms grown under anaerobic conditions, possibly indicating that oxygen contributes to the observed heterogeneity under aerobic conditions. Future applications of this workflow to study spatially localized molecular responses to antimicrobials could provide new therapeutic strategies., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 THE AUTHORS. Publishing services by ELSEVIER B.V. on behalf of MSACL.)

Bacterial pathogens have evolved virulence factors to colonize, replicate, and disseminate within the vertebrate host. Although there is an expanding body of literature describing how bacterial pathogens regulate their virulence repertoire in response to environmental signals, it is challenging to directly visualize virulence response within the host tissue microenvironment. Multimodal imaging approaches enable visualization of host-pathogen molecular interactions. Here we demonstrate multimodal integration of high spatial resolution imaging mass spectrometry and microscopy to visualize Staphylococcus aureus envelope modifications within infected murine and human tissues. Data-driven image fusion of fluorescent bacterial reporters and matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance imaging mass spectrometry uncovered S. aureus lysyl-phosphatidylglycerol lipids, localizing to select bacterial communities within infected tissue. Absence of lysyl-phosphatidylglycerols is associated with decreased pathogenicity during vertebrate colonization as these lipids provide protection against the innate immune system. The presence of distinct staphylococcal lysyl-phosphatidylglycerol distributions within murine and human infections suggests a heterogeneous, spatially oriented microbial response to host defenses., Competing Interests: Declaration of interests The authors declare no interests., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Objective: To evaluate the desire for parenthood and reproductive outcomes of young cervical cancer survivors who underwent fertility-sparing surgery or fertility preservation procedures for invasive cervical cancer., Methods: All women <45 years who underwent fertility-sparing treatment for invasive cervical cancer in a tertiary referral center in the Netherlands between January 2009 and January 2020 were identified. Fertility-sparing treatment options included Vaginal Radical Trachelectomy (VRT) for patients with early-stage disease and fertility preservation techniques (FP) when requiring Radical Hysterectomy (RH) or chemoradiotherapy. Data on reproductive intentions - and outcomes were retrieved from medical files and questionnaires., Results: 75 patients were identified of whom 34 underwent VRT, 9 RH and 32 had (chemo)radiotherapy. 26 patients started FP of whom 23 (88.5%) successfully preserved fertility through cryopreservation of embryos, oocytes and ovarian tissue. After a median follow-up of 49 months, 5 patients developed recurrent disease and died. Reproductive outcomes were retrieved in 58 patients. 89.6% maintained their desire for parenthood after cancer treatment. Following VRT, we report a pregnancy rate of 61.9% among the patients attempting conception (n = 24). 15 patients conceived 21 pregnancies which resulted in 15 live-births, yielding a live-birth rate of 75.0%. Following RH or (chemo)radiotherapy, 3 surrogate pregnancies were established (21.4%) using frozen-thawed material with good neonatal outcomes., Conclusion: Many cervical cancer survivors maintain the desire to become parents eventually. In early-stage disease, VRT shows good reproductive outcomes without compromising oncological safety. For those requiring gonadotoxic treatment fertility preservation and gestational surrogacy provides a promising alternative for achieving a biological offspring., Competing Interests: Declaration of Competing Interest All authors declare that they have no conflict of interest [31]., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

We demonstrate the utility of combining silicon nanopost arrays (NAPA) and trapped ion mobility imaging mass spectrometry (TIMS IMS) for high spatial resolution and specificity mapping of neutral lipid classes in tissue. Ionization of neutral lipid species such as triglycerides (TGs), cholestryl esters (CEs), and hexosylceramides (HexCers) from biological tissues has remained a challenge for imaging applications. NAPA, a matrix-free laser desorption ionization substrate, provides enhanced ionization efficiency for the above-mentioned neutral lipid species, providing complementary lipid coverage to matrix-assisted laser desorption ionization (MALDI). The combination of NAPA and TIMS IMS enables imaging of neutral lipid species at 20 μm spatial resolution while also increasing molecular coverage greater than 2-fold using gas-phase ion mobility separations. This is a significant improvement with respect to sensitivity, specificity, and spatial resolution compared to previously reported imaging studies using NAPA alone. Improved specificity for neutral lipid analysis using TIMS IMS was shown using rat kidney tissue to separate TGs, CEs, HexCers, and phospholipids into distinct ion mobility trendlines. Further, this technology allowed for the separation of isomeric species, including mobility resolved isomers of Cer(d42:2) ( m / z 686.585) with distinct spatial localizations measured in rat kidney tissue section.

The search for molecular species that are differentially expressed between biological states is an important step towards discovering promising biomarker candidates. In imaging mass spectrometry (IMS), performing this search manually is often impractical due to the large size and high-dimensionality of IMS datasets. Instead, we propose an interpretable machine learning workflow that automatically identifies biomarker candidates by their mass-to-charge ratios, and that quantitatively estimates their relevance to recognizing a given biological class using Shapley additive explanations (SHAP). The task of biomarker candidate discovery is translated into a feature ranking problem: given a classification model that assigns pixels to different biological classes on the basis of their mass spectra, the molecular species that the model uses as features are ranked in descending order of relative predictive importance such that the top-ranking features have a higher likelihood of being useful biomarkers. Besides providing the user with an experiment-wide measure of a molecular species' biomarker potential, our workflow delivers spatially localized explanations of the classification model's decision-making process in the form of a novel representation called SHAP maps. SHAP maps deliver insight into the spatial specificity of biomarker candidates by highlighting in which regions of the tissue sample each feature provides discriminative information and in which regions it does not. SHAP maps also enable one to determine whether the relationship between a biomarker candidate and a biological state of interest is correlative or anticorrelative. Our automated approach to estimating a molecular species' potential for characterizing a user-provided biological class, combined with the untargeted and multiplexed nature of IMS, allows for the rapid screening of thousands of molecular species and the obtention of a broader biomarker candidate shortlist than would be possible through targeted manual assessment. Our biomarker candidate discovery workflow is demonstrated on mouse-pup and rat kidney case studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

Here, we describe the preservation and preparation of human kidney tissue for interrogation by histopathology, imaging mass spectrometry, and multiplexed immunofluorescence. Custom image registration and integration techniques are used to create cellular and molecular atlases of this organ system. Through careful optimization, we ensure high-quality and reproducible datasets suitable for cross-patient comparisons that are essential to understanding human health and disease. Moreover, each of these steps can be adapted to other organ systems or diseases, enabling additional atlas efforts., Competing Interests: The authors declare no competing interests., (© 2021.)

Low molecular weight metabolites are essential for defining the molecular phenotypes of cells. However, spatial metabolomics tools often lack the sensitivity, specify, and spatial resolution to provide comprehensive descriptions of these species in tissue. MALDI imaging mass spectrometry (IMS) of low molecular weight ions is particularly challenging as MALDI matrix clusters are often nominally isobaric with multiple metabolite ions, requiring high resolving power instrumentation or derivatization to circumvent this issue. An alternative to this is to perform ion mobility separation before ion detection, enabling the visualization of metabolites without the interference of matrix ions. Additional difficulties surrounding low weight metabolite visualization include high resolution imaging, while maintaining sufficient ion numbers for broad and representative analysis of the tissue chemical complement. Here, we use MALDI timsTOF IMS to image low molecular weight metabolites at higher spatial resolution than most metabolite MALDI IMS experiments (20 μm) while maintaining broad coverage within the human kidney. We demonstrate that trapped ion mobility spectrometry (TIMS) can resolve matrix peaks from metabolite signal and separate both isobaric and isomeric metabolites with different distributions within the kidney. The added ion mobility data dimension dramatically increased the peak capacity for spatial metabolomics experiments. Through this improved sensitivity, we have found >40 low molecular weight metabolites in human kidney tissue, such as argininic acid, acetylcarnitine, and choline that localize to the cortex, medulla, and renal pelvis, respectively. Future work will involve further exploring metabolomic profiles of human kidneys as a function of age, sex, and race.

Lipids are a structurally diverse class of molecules with important biological functions including cellular signaling and energy storage. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) allows for direct mapping of biomolecules in tissues. Fully characterizing the structural diversity of lipids remains a challenge due to the presence of isobaric and isomeric species, which greatly complicates data interpretation when only m / z information is available. Integrating ion mobility separations aids in deconvoluting these complex mixtures and addressing the challenges of lipid IMS. Here, we demonstrate that a MALDI quadrupole time-of-flight (Q-TOF) mass spectrometer with trapped ion mobility spectrometry (TIMS) enables a >250% increase in the peak capacity during IMS experiments. MALDI TIMS-MS separation of lipid isomer standards, including sn backbone isomers, acyl chain isomers, and double-bond position and stereoisomers, is demonstrated. As a proof of concept, in situ separation and imaging of lipid isomers with distinct spatial distributions were performed using tissue sections from a whole-body mouse pup.

Identifying the spatial distributions of biomolecules in tissue is crucial for understanding integrated function. Imaging mass spectrometry (IMS) allows simultaneous mapping of thousands of biosynthetic products such as lipids but has needed a means of identifying specific cell-types or functional states to correlate with molecular localization. We report, here, advances starting from identity marking with a genetically encoded fluorophore. The fluorescence emission data were integrated with IMS data through multimodal image processing with advanced registration techniques and data-driven image fusion. In an unbiased analysis of spleens, this integrated technology enabled identification of ether lipid species preferentially enriched in germinal centers. We propose that this use of genetic marking for microanatomical regions of interest can be paired with molecular information from IMS for any tissue, cell-type, or activity state for which fluorescence is driven by a gene-tracking allele and ultimately with outputs of other means of spatial mapping.

Imaging mass spectrometry (IMS) is a rapidly advancing molecular imaging modality that can map the spatial distribution of molecules with high chemical specificity. IMS does not require prior tagging of molecular targets and is able to measure a large number of ions concurrently in a single experiment. While this makes it particularly suited for exploratory analysis, the large amount and high-dimensional nature of data generated by IMS techniques make automated computational analysis indispensable. Research into computational methods for IMS data has touched upon different aspects, including spectral preprocessing, data formats, dimensionality reduction, spatial registration, sample classification, differential analysis between IMS experiments, and data-driven fusion methods to extract patterns corroborated by both IMS and other imaging modalities. In this work, we review unsupervised machine learning methods for exploratory analysis of IMS data, with particular focus on (a) factorization, (b) clustering, and (c) manifold learning. To provide a view across the various IMS modalities, we have attempted to include examples from a range of approaches including matrix assisted laser desorption/ionization, desorption electrospray ionization, and secondary ion mass spectrometry-based IMS. This review aims to be an entry point for both (i) analytical chemists and mass spectrometry experts who want to explore computational techniques; and (ii) computer scientists and data mining specialists who want to enter the IMS field. © 2019 The Authors. Mass Spectrometry Reviews published by Wiley Periodicals, Inc. Mass SpecRev 00:1-47, 2019., (© 2019 The Authors. Mass Spectrometry Reviews published by Wiley Periodicals, Inc.)

Metals play an essential role in biological systems and are required as structural or catalytic co-factors in many proteins. Disruption of the homeostatic control and/or spatial distributions of metals can lead to disease. Imaging technologies have been developed to visualize elemental distributions across a biological sample. Measurement of elemental distributions by imaging mass spectrometry and imaging X-ray fluorescence are increasingly employed with technologies that can assess histological features and molecular compositions. Data from several modalities can be interrogated as multimodal images to correlate morphological, elemental, and molecular properties. Elemental and molecular distributions have also been axially resolved to achieve three-dimensional volumes, dramatically increasing the biological information. In this review, we provide an overview of recent developments in the field of metal imaging with an emphasis on multimodal studies in two and three dimensions. We specifically highlight studies that present technological advancements and biological applications of how metal homeostasis affects human health., Competing Interests: Conflict of interest statement Nothing declared., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Comparability is a key concept in the evaluation of both manufacturing changes and biosimilars. It constitutes a pragmatic and flexible approach which recognises that biologicals are inherently variable and that minor variations in quality attributes are often clinically irrelevant. In this discussion paper, we argue that comparability exercises rely on a number of pragmatic criteria. These criteria have been remarkably robust for 20 years of comparability exercises; however, the increased scrutiny of biosimilar applications provides an impetus for both codification and improvement of criteria for establishing comparability. Such a more rigorous, methodologically sound, approach towards comparability seems both feasible and beneficial., (Copyright © 2019 International Alliance for Biological Standardization. Published by Elsevier Ltd. All rights reserved.)

Imaging mass spectrometry (IMS) enables the spatially targeted molecular assessment of biological tissues at cellular resolutions. New developments and technologies are essential for uncovering the molecular drivers of native physiological function and disease. Instrumentation must maximize spatial resolution, throughput, sensitivity, and specificity, because tissue imaging experiments consist of thousands to millions of pixels. Here, we report the development and application of a matrix-assisted laser desorption/ionization (MALDI) trapped ion-mobility spectrometry (TIMS) imaging platform. This prototype MALDI timsTOF instrument is capable of 10 μm spatial resolutions and 20 pixels/s throughput molecular imaging. The MALDI source utilizes a Bruker SmartBeam 3-D laser system that can generate a square burn pattern of <10 × 10 μm at the sample surface. General image performance was assessed using murine kidney and brain tissues and demonstrate that high-spatial-resolution imaging data can be generated rapidly with mass measurement errors <5 ppm and ∼40 000 resolving power. Initial TIMS-based imaging experiments were performed on whole-body mouse pup tissue demonstrating the separation of closely isobaric [PC(32:0) + Na] + and [PC(34:3) + H] + (3 mDa mass difference) in the gas phase. We have shown that the MALDI timsTOF platform can maintain reasonable data acquisition rates (>2 pixels/s) while providing the specificity necessary to differentiate components in complex mixtures of lipid adducts. The combination of high-spatial-resolution and throughput imaging capabilities with high-performance TIMS separations provides a uniquely tunable platform to address many challenges associated with advanced molecular imaging applications.

Cancer-induced cachexia has a negative impact on quality of life and adversely affects therapeutic outcomes and survival rates. It is characterized by, often severe, loss of muscle, with or without loss of fat mass. Insight in the pathophysiology of this complex metabolic syndrome and direct treatment options are still limited, which creates a research demand. Results from recent studies point towards a significant involvement of muscle mitochondrial networks. However, data are scattered and a comprehensive overview is lacking. This paper aims to fill existing knowledge gaps by integrating published data sets on muscle protein or gene expression from cancer-induced cachexia animal models. To this end, a database was compiled from 94 research papers, comprising 11 different rodent models. This was combined with four genome-wide transcriptome datasets of cancer-induced cachexia rodent models. Analysis showed that the expression of genes involved in mitochondrial fusion, fission, ATP production and mitochondrial density is decreased, while that of genes involved ROS detoxification and mitophagy is increased. Our results underline the relevance of including post-translational modifications of key proteins involved in mitochondrial functioning in future studies on cancer-induced cachexia., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

Histology-directed imaging mass spectrometry (IMS) is a spatially targeted IMS acquisition method informed by expert annotation that provides rapid molecular characterization of select tissue structures. The expert annotations are usually determined on digital whole slide images of histological stains where the staining preparation is incompatible with optimal IMS preparation, necessitating serial sections: one for annotation, one for IMS. Registration is then used to align staining annotations onto the IMS tissue section. Herein, we report a next-generation histology-directed platform implementing IMS-compatible autofluorescence (AF) microscopy taken prior to any staining or IMS. The platform enables two histology-directed workflows, one that improves the registration process between two separate tissue sections using automated, computational monomodal AF-to-AF microscopy image registration, and a registration-free approach that utilizes AF directly to identify ROIs and acquire IMS on the same section. The registration approach is fully automated and delivers state of the art accuracy in histology-directed workflows for transfer of annotations (∼3-10 μm based on 4 organs from 2 species) while the direct AF approach is registration-free, allowing targeting of the finest structures visible by AF microscopy. We demonstrate the platform in biologically relevant case studies of liver stage malaria and human kidney disease with spatially targeted acquisition of sparsely distributed (composing less than one tenth of 1% of the tissue section area) malaria infected mouse hepatocytes and glomeruli in the human kidney case study.

The correlation of imaging mass spectrometry (IMS) with histopathology can help relate novel molecular findings obtained through IMS to the well-characterized and validated histopathology knowledge base. The quality of correlation between these two modalities is limited by the quality of the spatial mapping that is obtained by registration of the two image types. In this work, we develop novel workflows for MALDI IMS-to-microscopy data registration and analysis using nondestructive IMS-compatible wide field autofluorescence (AF) microscopy combined with computational image registration. First, a substantially automated procedure for high-accuracy registration between IMS and microscopy data of the same section is described that explicitly links the MALDI laser ablation pattern imaged by microscopy to its corresponding IMS pixel. Subsequent examination of the registered data allows for high-confidence colocalization of image features between the two modalities, down to single-cell scales within tissue. Building on this IMS-microscopy spatial mapping, we furthermore demonstrate the automated spatial correlation between IMS measurements from serial sections. This AF-registration-driven inter-section analysis, using a combination of nonlinear AF-to-AF and IMS-to-AF image registrations, can be applied to tissue sections that are prepared and imaged with different sample preparations (e.g., lipids vs proteins) and/or that are measured using different spatial resolutions. Importantly, all registrations, whether within a single section or across serial sections, are entirely independent of the IMS intensity signal content and thus unbiased by it.

The molecular identification of species of interest is an important part of an imaging mass spectrometry (IMS) experiment. The high resolution accurate mass capabilities of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) have recently been shown to facilitate the identification of proteins in matrix-assisted laser desorption/ionization (MALDI) IMS. However, these experiments are typically limited to proteins giving rise to ions of relatively low m/ z due to difficulties transmitting and measuring large molecular weight ions of low charge states. Herein we have modified the source gas manifold of a commercial MALDI FT-ICR MS to regulate the gas flow and pressure to maximize the transmission of large m/ z protein ions through the ion funnel region of the instrument. By minimizing the contribution of off-axis gas disruption to ion focusing and maximizing the effective potential wall confining the ions through pressure optimization, the signal-to-noise ratios (S/N) of most protein species were improved by roughly 1 order of magnitude compared to normal source conditions. These modifications enabled the detection of protein standards up to m/ z 24 000 and the detection of proteins from tissue up to m/ z 22 000 with good S/N, roughly doubling the mass range for which high quality protein ion images from rat brain and kidney tissue could be produced. Due to the long time-domain transients (>4 s) required to isotopically resolve high m/ z proteins, we have used these data as part of an FT-ICR IMS-microscopy data-driven image fusion workflow to produce estimated protein images with both high mass and high spatial resolutions.

Diseases are characterized by distinct changes in tissue molecular distribution. Molecular analysis of intact tissues traditionally requires preexisting knowledge of, and reagents for, the targets of interest. Conversely, label-free discovery of disease-associated tissue analytes requires destructive processing for downstream identification platforms. Tissue-based analyses therefore sacrifice discovery to gain spatial distribution of known targets or sacrifice tissue architecture for discovery of unknown targets. To overcome these obstacles, we developed a multimodality imaging platform for discovery-based molecular histology. We apply this platform to a model of disseminated infection triggered by the pathogen Staphylococcus aureus , leading to the discovery of infection-associated alterations in the distribution and abundance of proteins and elements in tissue in mice. These data provide an unbiased, three-dimensional analysis of how disease affects the molecular architecture of complex tissues, enable culture-free diagnosis of infection through imaging-based detection of bacterial and host analytes, and reveal molecular heterogeneity at the host-pathogen interface., (Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Imaging mass spectrometry (IMS) is a molecular imaging technology that can measure thousands of biomolecules concurrently without prior tagging, making it particularly suitable for exploratory research. However, the data size and dimensionality often makes thorough extraction of relevant information impractical. To help guide and accelerate IMS data analysis, we recently developed a framework that integrates IMS measurements with anatomical atlases, opening up opportunities for anatomy-driven exploration of IMS data. One example is the automated anatomical interpretation of ion images, where empirically measured ion distributions are automatically decomposed into their underlying anatomical structures. While offering significant potential, IMS-atlas integration has thus far been restricted to the Allen Mouse Brain Atlas (AMBA) and mouse brain samples. Here, we expand the applicability of this framework by extending towards new animal species and a new set of anatomical atlases retrieved from the Scalable Brain Atlas (SBA). Furthermore, as many SBA atlases are based on magnetic resonance imaging (MRI) data, a new registration pipeline was developed that enables direct non-rigid IMS-to-MRI registration. These developments are demonstrated on protein-focused FTICR IMS measurements from coronal brain sections of a Parkinson's disease (PD) rat model. The measurements are integrated with an MRI-based rat brain atlas from the SBA. The new rat-focused IMS-atlas integration is used to perform automated anatomical interpretation and to find differential ions between healthy and diseased tissue. IMS-atlas integration can serve as an important accelerator in IMS data exploration, and with these new developments it can now be applied to a wider variety of animal species and modalities. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann., (Copyright © 2017. Published by Elsevier B.V.)

An understanding of how cells respond to perturbation is essential for biological applications; however, most approaches for profiling cellular response are limited in scope to pre-established targets. Global analysis of molecular mechanism will advance our understanding of the complex networks constituting cellular perturbation and lead to advancements in areas, such as infectious disease pathogenesis, developmental biology, pathophysiology, pharmacology, and toxicology. We have developed a high-throughput multiomics platform for comprehensive, de novo characterization of cellular mechanisms of action. Platform validation using cisplatin as a test compound demonstrates quantification of over 10 000 unique, significant molecular changes in less than 30 days. These data provide excellent coverage of known cisplatin-induced molecular changes and previously unrecognized insights into cisplatin resistance. This proof-of-principle study demonstrates the value of this platform as a resource to understand complex cellular responses in a high-throughput manner.

Neurofibromatosis type 1 (NF1) is a common neurogenetic disorder, in which affected individuals develop tumors of the nervous system. Children with NF1 are particularly prone to brain tumors (gliomas) involving the optic pathway that can result in impaired vision. Since tumor formation and expansion requires a cooperative tumor microenvironment, it is important to identify the cellular and acellular components associated with glioma development and growth. In this study, we used 3-D matrix assisted laser desorption ionization imaging mass spectrometry (MALDI IMS) to measure the distributions of multiple molecular species throughout optic nerve tissue in mice with and without glioma, and to explore their spatial relationships within the 3-D volume of the optic nerve and chiasm. 3-D IMS studies often involve extensive workflows due to the high volume of sections required to generate high quality 3-D images. Herein, we present a workflow for 3-D data acquisition and volume reconstruction using mouse optic nerve tissue. The resulting 3-D IMS data yield both molecular similarities and differences between glioma-bearing and wild-type (WT) tissues, including protein distributions localizing to different anatomical subregions., Biological Significance: The current work addresses a number of challenges in 3-D MALDI IMS, driven by the small size of the mouse optic nerve and the need to maintain consistency across multiple 2-D IMS experiments. The 3-D IMS data yield both molecular similarities and differences between glioma-bearing and wild-type (WT) tissues, including protein distributions localizing to different anatomical subregions, which could then be targeted for identification and related back to the biology observed in gliomas of the optic nerve., Competing Interests: The authors have declared no conflict of interest., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Lung cancer is the leading cause of cancer death. Beyond first line treatment, few therapeutic options are available, particularly for squamous cell carcinoma (SCC). Here, we have explored the phospholipidomes of 30 human SCCs and found that they almost invariably (in 96.7% of cases) contain phospholipids with longer acyl chains compared to matched normal tissues. This trait was confirmed using in situ 2D-imaging MS on tissue sections and by phospholipidomics of tumor and normal lung tissue of the L-IkkαKA/KA mouse model of lung SCC. In both human and mouse, the increase in acyl chain length in cancer tissue was accompanied by significant changes in the expression of acyl chain elongases (ELOVLs). Functional screening of differentially expressed ELOVLs by selective gene knockdown in SCC cell lines followed by phospholipidomics revealed ELOVL6 as the main elongation enzyme responsible for acyl chain elongation in cancer cells. Interestingly, inhibition of ELOVL6 drastically reduced colony formation of multiple SCC cell lines in vitro and significantly attenuated their growth as xenografts in vivo in mouse models. These findings identify acyl chain elongation as one of the most common traits of lung SCC discovered so far and pinpoint ELOVL6 as a novel potential target for cancer intervention.

Non-small cell lung cancer (NSCLC) is the leading cause of cancer death globally. To develop better diagnostics and more effective treatments, research in the past decades has focused on identification of molecular changes in the genome, transcriptome, proteome, and more recently also the metabolome. Phospholipids, which nevertheless play a central role in cell functioning, remain poorly explored. Here, using a mass spectrometry (MS)-based phospholipidomics approach, we profiled 179 phospholipid species in malignant and matched non-malignant lung tissue of 162 NSCLC patients (73 in a discovery cohort and 89 in a validation cohort). We identified 91 phospholipid species that were differentially expressed in cancer versus non-malignant tissues. Most prominent changes included a decrease in sphingomyelins (SMs) and an increase in specific phosphatidylinositols (PIs). Also a decrease in multiple phosphatidylserines (PSs) was observed, along with an increase in several phosphatidylethanolamine (PE) and phosphatidylcholine (PC) species, particularly those with 40 or 42 carbon atoms in both fatty acyl chains together. 2D-imaging MS of the most differentially expressed phospholipids confirmed their differential abundance in cancer cells. We identified lipid markers that can discriminate tumor versus normal tissue and different NSCLC subtypes with an AUC (area under the ROC curve) of 0.999 and 0.885, respectively. In conclusion, using both shotgun and 2D-imaging lipidomics analysis, we uncovered a hitherto unrecognized alteration in phospholipid profiles in NSCLC. These changes may have important biological implications and may have significant potential for biomarker development., (© 2015 The Authors. Published by Wiley Periodicals, Inc. on behalf of UICC.)

We describe a predictive imaging modality created by 'fusing' two distinct technologies: imaging mass spectrometry (IMS) and microscopy. IMS-generated molecular maps, rich in chemical information but having coarse spatial resolution, are combined with optical microscopy maps, which have relatively low chemical specificity but high spatial information. The resulting images combine the advantages of both technologies, enabling prediction of a molecular distribution both at high spatial resolution and with high chemical specificity. Multivariate regression is used to model variables in one technology, using variables from the other technology. We demonstrate the potential of image fusion through several applications: (i) 'sharpening' of IMS images, which uses microscopy measurements to predict ion distributions at a spatial resolution that exceeds that of measured ion images by ten times or more; (ii) prediction of ion distributions in tissue areas that were not measured by IMS; and (iii) enrichment of biological signals and attenuation of instrumental artifacts, revealing insights not easily extracted from either microscopy or IMS individually.

Imaging mass spectrometry (IMS) has become a prime tool for studying the distribution of biomolecules in tissue. Although IMS data sets can become very large, computational methods have made it practically feasible to search these experiments for relevant findings. However, these methods lack access to an important source of information that many human interpretations rely upon: anatomical insight. In this work, we address this need by (1) integrating a curated anatomical data source with an empirically acquired IMS data source, establishing an algorithm-accessible link between them and (2) demonstrating the potential of such an IMS-anatomical atlas link by applying it toward automated anatomical interpretation of ion distributions in tissue. The concept is demonstrated in mouse brain tissue, using the Allen Mouse Brain Atlas as the curated anatomical data source that is linked to MALDI-based IMS experiments. We first develop a method to spatially map the anatomical atlas to the IMS data sets using nonrigid registration techniques. Once a mapping is established, a second computational method, called correlation-based querying, gives an elementary demonstration of the link by delivering basic insight into relationships between ion images and anatomical structures. Finally, a third algorithm moves further beyond both registration and correlation by providing automated anatomical interpretation of ion images. This task is approached as an optimization problem that deconstructs ion distributions as combinations of known anatomical structures. We demonstrate that establishing a link between an IMS experiment and an anatomical atlas enables automated anatomical annotation, which can serve as an important accelerator both for human and machine-guided exploration of IMS experiments.

Although physicochemical fractionation techniques play a crucial role in the analysis of complex mixtures, they are not necessarily the best solution to separate specific molecular classes, such as lipids and peptides. Any physical fractionation step such as, for example, those based on liquid chromatography, will introduce its own variation and noise. In this paper we investigate to what extent the high sensitivity and resolution of contemporary mass spectrometers offers viable opportunities for computational separation of signals in full scan spectra. We introduce an automatic method that can discriminate peptide from lipid peaks in full scan mass spectra, based on their isotopic properties. We systematically evaluate which features maximally contribute to a peptide versus lipid classification. The selected features are subsequently used to build a random forest classifier that enables almost perfect separation between lipid and peptide signals without requiring ion fragmentation and classical tandem MS-based identification approaches. The classifier is trained on in silico data, but is also capable of discriminating signals in real world experiments. We evaluate the influence of typical data inaccuracies of common classes of mass spectrometry instruments on the optimal set of discriminant features. Finally, the method is successfully extended towards the classification of individual lipid classes from full scan mass spectral features, based on input data defined by the Lipid Maps Consortium.

Background: An early semi-invasive diagnosis of endometriosis has the potential to allow early treatment and minimize disease progression but no such test is available at present. Our aim was to perform a combined mRNA microarray and proteomic analysis on the same eutopic endometrium sample obtained from patients with and without endometriosis., Methods: mRNA and protein fractions were extracted from 49 endometrial biopsies obtained from women with laparoscopically proven presence (n= 31) or absence (n= 18) of endometriosis during the early luteal (n= 27) or menstrual phase (n= 22) and analyzed using microarray and proteomic surface enhanced laser desorption ionization-time of flight mass spectrometry, respectively. Proteomic data were analyzed using a least squares-support vector machines (LS-SVM) model built on 70% (training set) and 30% of the samples (test set)., Results: mRNA analysis of eutopic endometrium did not show any differentially expressed genes in women with endometriosis when compared with controls, regardless of endometriosis stage or cycle phase. mRNA was differentially expressed (P< 0.05) in women with (925 genes) and without endometriosis (1087 genes) during the menstrual phase when compared with the early luteal phase. Proteomic analysis based on five peptide peaks [2072 mass/charge (m/z); 2973 m/z; 3623 m/z; 3680 m/z and 21133 m/z] using an LS-SVM model applied on the luteal phase endometrium training set allowed the diagnosis of endometriosis (sensitivity, 91; 95% confidence interval (CI): 74-98; specificity, 80; 95% CI: 66-97 and positive predictive value, 87.9%; negative predictive value, 84.8%) in the test set., Conclusion: mRNA expression of eutopic endometrium was comparable in women with and without endometriosis but different in menstrual endometrium when compared with luteal endometrium in women with endometriosis. Proteomic analysis of luteal phase endometrium allowed the diagnosis of endometriosis with high sensitivity and specificity in training and test sets. A potential limitation of our study is the fact that our control group included women with a normal pelvis as well as women with concurrent pelvic disease (e.g. fibroids, benign ovarian cysts, hydrosalpinges), which may have contributed to the comparable mRNA expression profile in the eutopic endometrium of women with endometriosis and controls.

Objective: To test the hypothesis that differential surface-enhanced laser desorption/ionization time-of-flight mass spectrometry protein or peptide expression in plasma can be used in infertile women with or without pelvic pain to predict the presence of laparoscopically and histologically confirmed endometriosis, especially in the subpopulation with a normal preoperative gynecologic ultrasound examination., Methods: Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry analysis was performed on 254 plasma samples obtained from 89 women without endometriosis and 165 women with endometriosis (histologically confirmed) undergoing laparoscopies for infertility with or without pelvic pain. Data were analyzed using least squares support vector machines and were divided randomly (100 times) into a training data set (70%) and a test data set (30%)., Results: Minimal-to-mild endometriosis was best predicted (sensitivity 75%, 95% confidence interval [CI] 63-89; specificity 86%, 95% CI 71-94; positive predictive value 83.6%, negative predictive value 78.3%) using a model based on five peptide and protein peaks (range 4.898-14.698 m/z) in menstrual phase samples. Moderate-to-severe endometriosis was best predicted (sensitivity 98%, 95% CI 84-100; specificity 81%, 95% CI 67-92; positive predictive value 74.4%, negative predictive value 98.6%) using a model based on five other peptide and protein peaks (range 2.189-7.457 m/z) in luteal phase samples. The peak with the highest intensity (2.189 m/z) was identified as a fibrinogen β-chain peptide. Ultrasonography-negative endometriosis was best predicted (sensitivity 88%, 95% CI 73-100; specificity 84%, 95% CI 71-96) using a model based on five peptide peaks (range 2.058-42.065 m/z) in menstrual phase samples., Conclusion: A noninvasive test using proteomic analysis of plasma samples obtained during the menstrual phase enabled the diagnosis of endometriosis undetectable by ultrasonography with high sensitivity and specificity., Level of Evidence: II.

Objective: To test the hypothesis that specific proteins and peptides are expressed differentially in eutopic endometrium of women with and without endometriosis and at specific stages of the disease (minimal, mild, moderate, or severe) during the secretory phase., Design: Patients with endometriosis were compared with controls., Setting: University hospital., Patient(s): A total of 29 patients during the secretory phase were selected for this study on the basis of cycle phase and presence or absence of endometriosis., Intervention(s): Endometriosis was confirmed laparoscopically and histologically in 19 patients with endometriosis of revised American Society for Reproductive Medicine stages (9 minimal-mild and 10 moderate-severe), and the presence of a normal pelvis was documented by laparoscopy in 10 controls., Main Outcome Measure(s): Protein expression of endometrium was evaluated with use of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. The differential expression of protein mass peaks was analyzed with use of support vector machine algorithms and logistic regression models., Result(s): Data preprocessing resulted in differential expression of 73, 30, and 131 mass peaks between controls and patients with endometriosis (all stages), with minimal-mild endometriosis, and with moderate-severe endometriosis, respectively. Endometriosis was diagnosed with high sensitivity (89.5%) and specificity (90%) with use of five down-regulated mass peaks (1.949 kDa, 5.183 kDa, 8.650 kDa, 8.659 kDa, and 13.910 kDa) obtained after support vector machine ranking and logistic regression classification. With use of a similar analysis, minimal-mild endometriosis was diagnosed with four mass peaks (two up-regulated: 35.956 kDa and 90.675 kDa and two down-regulated: 1.924 kDa and 2.504 kDa) with maximal sensitivity (100%) and specificity (100%). The 90.675-kDa and 35.956-kDa mass peaks were identified as T-plastin and annexin V, respectively., Conclusion(s): Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry analysis of secretory phase endometrium combined with bioinformatics puts forward a prospective panel of potential biomarkers with sensitivity of 100% and specificity of 100% for the diagnosis of minimal to mild endometriosis., (Copyright © 2011 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.)

We describe a 15-year-old patient with X-linked agammaglobulinemia who developed malabsorption and bacteremia due to infection of Helicobacter pylori and Campylobacter jejuni. The Campylobacter bacteremia was only recognized after subculturing of blood culture bottles that failed to signal in the automated system. After 2 weeks of treatment with meropenem and erythromycin for 4 weeks, the patient developed a relapse of bacteremia 10 months later with a high level erythromycin resistant C. jejuni. Sequencing revealed an A2058C mutation in the 23 S rRNA gene associated with this resistance. Treatment with doxycycline for 4 weeks finally resulted in complete eradication. This case report illustrates the importance for physicians to use adapted culture methods and adequate prolonged therapy in patients with an immunodeficiency. A summary of published case reports and series of patients with hypogammaglobulinemia or agammaglobulinemia with Campylobacter or Helicobacter bacteremia is given.

Background: According to mRNA microarray, proteomics and other studies, biological abnormalities of eutopic endometrium (EM) are involved in the pathogenesis of endometriosis, but the relationship between mRNA and protein expression in EM is not clear. We tested for the first time the hypothesis that EM TRIzol extraction allows proteomic Surface Enhanced Laser Desorption/Ionisation Time-of-Flight Mass Spectrometry (SELDI-TOF MS) analysis and that these proteomic data can be related to mRNA (microarray) data obtained from the same EM sample from women with and without endometriosis., Methods: Proteomic analysis was performed using SELDI-TOF-MS of TRIzol-extracted EM obtained during secretory phase from patients without endometriosis (n = 6), patients with minimal-mild (n = 5) and with moderate-severe endometriosis (n = 5), classified according to the system of the American Society of Reproductive Medicine. Proteomic data were compared to mRNA microarray data obtained from the same EM samples., Results: In our SELDI-TOF MS study 32 peaks were differentially expressed in endometrium of all women with endometriosis (stages I-IV) compared with all controls during the secretory phase. Comparison of proteomic results with those from microarray revealed no corresponding genes/proteins., Conclusion: TRIzol treatment of secretory phase EM allows combined proteomic and mRNA microarray analysis of the same sample, but comparison between proteomic and microarray data was not evident, probably due to post-translational modifications.

This tutorial provides a concise overview of support vector machines and different closely related techniques for pattern classification. The tutorial starts with the formulation of support vector machines for classification. The method of least squares support vector machines is explained. Approaches to retrieve a probabilistic interpretation are covered and it is explained how the binary classification techniques can be extended to multi-class methods. Kernel logistic regression, which is closely related to iteratively weighted least squares support vector machines, is discussed. Different practical aspects of these methods are addressed: the issue of feature selection, parameter tuning, unbalanced data sets, model evaluation and statistical comparison. The different concepts are illustrated on three real-life applications in the field of metabolomics, genetics and proteomics., (Copyright 2010 Elsevier B.V. All rights reserved.)

Zinc co-crystallizes with insulin in dense core secretory granules, but its role in insulin biosynthesis, storage and secretion is unknown. In this study we assessed the role of the zinc transporter ZnT8 using ZnT8-knockout (ZnT8(-/-)) mice. Absence of ZnT8 expression caused loss of zinc release upon stimulation of exocytosis, but normal rates of insulin biosynthesis, normal insulin content and preserved glucose-induced insulin release. Ultrastructurally, mature dense core insulin granules were rare in ZnT8(-/-) beta cells and were replaced by immature, pale insulin "progranules," which were larger than in ZnT8(+/+) islets. When mice were fed a control diet, glucose tolerance and insulin sensitivity were normal. However, after high-fat diet feeding, the ZnT8(-/-) mice became glucose intolerant or diabetic, and islets became less responsive to glucose. Our data show that the ZnT8 transporter is essential for the formation of insulin crystals in beta cells, contributing to the packaging efficiency of stored insulin. Interaction between the ZnT8(-/-) genotype and diet to induce diabetes is a model for further studies of the mechanism of disease of human ZNT8 gene mutations.

Background: There is a strong need for prognostic biomarkers in ovarian cancer patients due to the heterogeneous responses on current treatment modalities., Materials and Methods: This study investigates the feasibility of combining laser microdissection (LMD) and surface enhanced laser desorption ionization-time of flight mass spectrometry (SELDI-TOF MS) in ovarian cancer tissue to obtain protein profiles., Results: Ideal conditions for preparing a protein lysate were determined and subsequently analysed on SELDI-TOF MS. Applying these protocols on tissue of 9 ovarian cancer patients showed different protein profiles between platinum sensitive and resistant patients., Conclusion: This shows that combining optimised protocols for LMD with SELDI-TOF MS can be used to obtain discriminatory protein profiles. However, studies with large patient numbers and validation sets are essential to identify reliable biomarkers using this approach.

MALDI-based Imaging Mass Spectrometry (IMS) is an analytical technique that provides the opportunity to study the spatial distribution of biomolecules including proteins and peptides in organic tissue. IMS measures a large collection of mass spectra spread out over an organic tissue section and retains the absolute spatial location of these measurements for analysis and imaging. The classical approach to IMS imaging, producing univariate ion images, is not well suited as a first step in a prospective study where no a priori molecular target mass can be formulated. The main reasons for this are the size and the multivariate nature of IMS data. In this paper we describe the use of principal component analysis as a multivariate pre-analysis tool, to identify the major spatial and mass-related trends in the data and to guide further analysis downstream. First, a conceptual overview of principal component analysis for IMS is given. Then, we demonstrate the approach on an IMS data set collected from a transversal section of the spinal cord of a standard control rat.

Microbiological tests for diagnosis of acute meningococcal disease are important for the clinical management of patients with this often-fatal illness, but cultures are frequently negative after antibiotics have been administered. Retrospective studies suggest that examination of skin biopsies may aid a rapid diagnosis and that cultures of skin biopsies are often positive even after antimicrobial treatment has commenced. This prospective controlled study aimed to assess the diagnostic value of skin biopsy compared with investigations of blood and cerebrospinal fluid (CSF) in patients with skin lesions and presumed meningococcal disease. A total of 43 patients, 31 with suspected acute meningococcal infection and 12 controls, were included. All skin biopsies were investigated by Gram stain and routine microbiological culture. In 25 patients, meningococcal infection was diagnosed microbiologically. The clinical diagnosis was meningococcal meningitis in 8 patients, meningococcal sepsis in 11 patients, and a combination of both in 6 patients. The sensitivity of cultures of blood, CSF, and skin biopsies was 56%, 50%, and 36%, respectively. When culture and Gram stain were combined, positive results were obtained in 56%, 64%, and 56%, respectively. There was no correlation between the diagnostic yield of skin biopsies and previous antibiotic treatment. In 14 patients, the diagnosis was based exclusively on one positive sample: CSF in 7 (28%) patients, blood in 4 (16%) patients, and skin biopsy in 3 (12%) patients. The sensitivity of skin biopsies was highest in patients with the least extensive skin lesions. Specificity was 100%. Microbiological investigation of skin biopsies increased the diagnostic yield and could be considered a component of the routine diagnostic work-up in patients with suspected meningococcal infection, even after the initiation of antimicrobial treatment.

During the last thirty years of the nineteenth century in France, a psychology calling itself "positive," "experimental," or "physiological" was developing in opposition to the official philosophy, eclectic spiritualism. Its bases were set forth by Hippolyte Taine and Théodule Ribot, who popularised foreign models among the academic and scientific public, opposing spiritualism on the one hand, and Auguste Comte's positivism on the other. At the end of the century, Pierre Janet put into practice Ribot's programme for psychology, while differentiating himself from Ribot on the question of the relationship between psychology and physiology. Meanwhile, Alfred Binet, influenced by Taine in the first part of his work, went on to develop "individual psychology," and Gabriel Tarde tried to establish "interpsychology," which never managed to become recognised as a discipline in its own right. We intend to reposition these "scientific" psychologists and their works in that intellectual, institutional, and political context existing in late-nineteenth-century France. We aim to show that "scientific" psychology was able to find its place in that context only within philosophy, by means of a strategy of co-existing insertion and differentiation. If a new discipline did emerge, it was only after compromise, and with limited institutionalisation.

Objective: Approximately 50% of constipated children contract rather than relax the external sphincter complex during a defecation attempt. Although biofeedback training (BF) is able to change this defecation behavior, there is no additional effect of BF to conventional treatment (CT) on clinical outcome compared with CT alone. It has been postulated that the absence of a significant difference between these 2 treatment options might be because of a therapeutic, "demystifying" effect of performing anorectal manometry in conventionally treated children, necessary to obtain basal manometric data. The objective of this prospective, controlled, randomized study was to evaluate the effect of CT with 2 anorectal manometry sessions compared with CT alone (dietary advice, diary, toilet training, oral laxatives, and enemas) on clinical outcome., Methods: A total of 212 constipated children (143 boys) who were visiting a referral pediatric gastroenterologic practice were randomized prospectively to CT alone (115 patients) or to CT combined with 2 manometry sessions (CTM; 97 patients). Patients were included in the study when they fulfilled at least 2 of the 4 following criteria: stool frequency fewer than 3 per week, 2 or more soiling and/or encopresis episodes per week, periodic passage of very large amounts of stool every 7 to 30 days, or a palpable rectal or abdominal fecal mass. CT comprises dietary advice, a daily diary, toilet training, and oral laxative treatment preceded by rectal disimpaction with enemas on 3 consecutive days. During both manometries, the child and the parent could watch the tracing on the computer screen. No explanation was given to either the child or the parents during the procedure. When the procedure was finished, the tracings were clarified. Successful treatment was defined as a defecation frequency of 3 or more per week and fewer than 1 soiling/encopresis episode per 2 weeks and no use of laxatives., Results: Only 4 and 2 children from the CT and CTM groups showed no soiling and/or encopresis, whereas 76% and 65%, respectively, reported the periodic passage of large stools. In 26% and 30% of the patients, a rectal scybalum was found on physical examination. The success rates at 6, 26, 52, and 104 weeks' follow-up were 4%, 24%, 32%, and 43% and 7%, 22%, 30%, and 35% in the CT and CTM group, respectively. No significant difference in success percentage was observed between the 2 groups at any time of follow-up with relative risks (CT/CTM) and 95% confidence intervals, respectively, of 0.55 (0.16-1.89), 1.13 (0.67-1.89), 1.07 (0.69-1.65), and 1.23 (0.81-1.85). A significant increase in defecation frequency was observed between the first (intake) and second visits, which was sustained at all subsequent visits and stages of follow-up in both groups (not significant). Also in relation to the first visit, a significant decrease in encopresis episodes was shown and a further slow but significant decrease at 52 weeks of follow-up in both groups. The manometric data obtained from the CTM group showed a low percentage of children with normal defecation dynamics, namely 28%, which (significantly) increased to 38% at the last manometry., Conclusions: Anorectal manometry combined with CT compared with CT alone did not result in higher success rates in chronically constipated children. Therefore, anorectal manometry has no additional demystifying or educational effect on clinical outcome in chronically constipated children. This observation together with the observation in the current and previous studies that no correlation was found between (achievement of) normal defecation dynamics and success and that no relation was observed between volume of urge or critical volume and success leaves no diagnostic or therapeutic role for anorectal manometry in chronic constipated children, except its use as a diagnostic test to exclude Hirschsprung's disease. A simple CT is successful in 30% of severely constipated children who are referred to a tertiary hospital, underscoring the importance of long-lasting and adequate laxative treatment.