Microscopic examination of spatial transcriptome using Seq-Scope.

Spatial barcoding technologies have the potential to reveal histological details of transcriptomic profiles; however, they are currently limited by their low resolution. Here, we report Seq-Scope, a spatial barcoding technology with a resolution comparable to an optical microscope. Seq-Scope is based on a solid-phase amplification of randomly barcoded single-molecule oligonucleotides using an Illumina sequencing platform. The resulting clusters annotated with spatial coordinates are processed to expose RNA-capture moiety. These RNA-capturing barcoded clusters define the pixels of Seq-Scope that are ∼0.5-0.8 µm apart from each other. From tissue sections, Seq-Scope visualizes spatial transcriptome heterogeneity at multiple histological scales, including tissue zonation according to the portal-central (liver), crypt-surface (colon) and inflammation-fibrosis (injured liver) axes, cellular components including single-cell types and subtypes, and subcellular architectures of nucleus and cytoplasm. Seq-Scope is quick, straightforward, precise, and easy-to-implement and makes spatial single-cell analysis accessible to a wide group of biomedical researchers.

Human Cerebellar Development and Transcriptomics: Implications for Neurodevelopmental Disorders.

Developmental abnormalities of the cerebellum are among the most recognized structural brain malformations in human prenatal imaging. Yet reliable information regarding their cause in humans is sparse, and few outcome studies are available to inform prognosis. We know very little about human cerebellar development, in stark contrast to the wealth of knowledge from decades of research on cerebellar developmental biology of model organisms, especially mice. Recent studies show that multiple aspects of human cerebellar development significantly differ from mice and even rhesus macaques, a nonhuman primate. These discoveries challenge many current mouse-centric models of normal human cerebellar development and models regarding the pathogenesis of several neurodevelopmental phenotypes affecting the cerebellum, including Dandy-Walker malformation and medulloblastoma. Since we cannot model what we do not know, additional normative and pathological human developmental data are essential, and new models are needed.

Antibody-drug conjugates: Smart chemotherapy delivery across tumor histologies.

As distinct cancer biomarkers have been discovered in recent years, a need to reclassify tumors by more than their histology has been proposed, and therapies are now tailored to treat cancers based on specific molecular aberrations and immunologic markers. In fact, multiple histology-agnostic therapies are currently adopted in clinical practice for treating patients regardless of their tumor site of origin. In parallel with this new model for drug development, in the past few years, several novel antibody-drug conjugates (ADCs) have been approved to treat solid tumors, benefiting from engineering improvements in the conjugation process and the introduction of novel linkers and payloads. With the recognition that numerous surface targets are expressed across various cancer histologies, alongside the remarkable activity of modern ADCs, this drug class has been increasingly evaluated as suitable for a histology-agnostic expansion of indication. For illustration, the anti-HER2 ADC trastuzumab deruxtecan has demonstrated compelling activity in HER2-overexpressing breast, gastric, colorectal, and lung cancer. Examples of additional novel and potentially histology-agnostic ADC targets include trophoblast cell-surface antigen 2 (Trop-2) and nectin-4, among others. In the current review article, the authors summarize the current approvals of ADCs by the US Food and Drug Administration focusing on solid tumors and discuss the challenges and opportunities posed by the multihistological expansion of ADCs.

Deep learning in spatially resolved transcriptfomics: a comprehensive technical view

Spatially resolved transcriptomics (SRT) is a pioneering method for simultaneously studying morphological contexts and gene expression at single-cell precision. Data emerging from SRT are multifaceted, presenting researchers with intricate gene expression matrices, precise spatial details and comprehensive histology visuals. Such rich and intricate datasets, unfortunately, render many conventional methods like traditional machine learning and statistical models ineffective. The unique challenges posed by the specialized nature of SRT data have led the scientific community to explore more sophisticated analytical avenues. Recent trends indicate an increasing reliance on deep learning algorithms, especially in areas such as spatial clustering, identification of spatially variable genes and data alignment tasks. In this manuscript, we provide a rigorous critique of these advanced deep learning methodologies, probing into their merits, limitations and avenues for further refinement. Our in-depth analysis underscores that while the recent innovations in deep learning tailored for SRT have been promising, there remains a substantial potential for enhancement. A crucial area that demands attention is the development of models that can incorporate intricate biological nuances, such as phylogeny-aware processing or in-depth analysis of minuscule histology image segments. Furthermore, addressing challenges like the elimination of batch effects, perfecting data normalization techniques and countering the overdispersion and zero inflation patterns seen in gene expression is pivotal. To support the broader scientific community in their SRT endeavors, we have meticulously assembled a comprehensive directory of readily accessible SRT databases, hoping to serve as a foundation for future research initiatives.

Merged magnetic resonance and light sheet microscopy of the whole mouse brain.

We have developed workflows to align 3D magnetic resonance histology (MRH) of the mouse brain with light sheet microscopy (LSM) and 3D delineations of the same specimen. We start with MRH of the brain in the skull with gradient echo and diffusion tensor imaging (DTI) at 15 µm isotropic resolution which is ~ 1,000 times higher than that of most preclinical MRI. Connectomes are generated with superresolution tract density images of ~5 µm. Brains are cleared, stained for selected proteins, and imaged by LSM at 1.8 µm/pixel. LSM data are registered into the reference MRH space with labels derived from the ABA common coordinate framework. The result is a high-dimensional integrated volume with registration (HiDiver) with alignment precision better than 50 µm. Throughput is sufficiently high that HiDiver is being used in quantitative studies of the impact of gene variants and aging on mouse brain cytoarchitecture and connectomics.

Diffusion MRI of the Hippocampus.

The hippocampus is a brain structure that plays key roles in a variety of cognitive processes. Critically, a wide range of neurological disorders are associated with degeneration of the hippocampal microstructure, defined as neurons, dendrites, glial cells, and more. Thus, the hippocampus is a key target for methods that are sensitive to these microscale properties. Diffusion MRI is one such method, which can noninvasively probe neural architecture. Here we review the extensive use of diffusion MRI to capture hippocampal microstructure in both health and disease. The results of these studies indicate that (1) diffusion tensor imaging is sensitive but not specific to the hippocampal microstructure; (2) biophysical modeling of diffusion MRI signals is a promising avenue to capture more specific aspects of the hippocampal microstructure; (3) use of ultra-short diffusion times have shown unique laminar-specific microstructure and response to hippocampal injury; (4) dispersion of microstructure is likely abundant in the hippocampus; and (5) the angular richness of the diffusion MRI signal can be leveraged to improve delineation of the internal hippocampal circuitry. Overall, extant findings suggest that diffusion MRI offers a promising avenue for characterizing hippocampal microstructure.

Cardiovascular Magnetic Resonance Radiomics to Identify Components of the Extracellular Matrix in Dilated Cardiomyopathy.

BACKGROUND: Current cardiovascular magnetic resonance sequences cannot discriminate between different myocardial extracellular space (ECSs), including collagen, noncollagen, and inflammation. We sought to investigate whether cardiovascular magnetic resonance radiomics analysis can distinguish between noncollagen and inflammation from collagen in dilated cardiomyopathy. METHODS: We identified data from 132 patients with dilated cardiomyopathy scheduled for an invasive septal biopsy who underwent cardiovascular magnetic resonance at 3 T. Cardiovascular magnetic resonance imaging protocol included native and postcontrast T1 mapping and late gadolinium enhancement (LGE). Radiomic features were computed from the midseptal myocardium, near the biopsy region, on native T1, extracellular volume (ECV) map, and LGE images. Principal component analysis was used to reduce the number of radiomic features to 5 principal radiomics. Moreover, a correlation analysis was conducted to identify radiomic features exhibiting a strong correlation (r>0.9) with the 5 principal radiomics. Biopsy samples were used to quantify ECS, myocardial fibrosis, and inflammation. RESULTS: Four histopathological phenotypes were identified: low collagen (n=20), noncollagenous ECS expansion (n=49), mild to moderate collagenous ECS expansion (n=42), and severe collagenous ECS expansion (n=21). Noncollagenous expansion was associated with the highest risk of myocardial inflammation (65%). Although native T1 and ECV provided high diagnostic performance in differentiating severe fibrosis (C statistic, 0.90 and 0.90, respectively), their performance in differentiating between noncollagen and mild to moderate collagenous expansion decreased (C statistic: 0.59 and 0.55, respectively). Integration of ECV principal radiomics provided better discrimination and reclassification between noncollagen and mild to moderate collagen (C statistic, 0.79; net reclassification index, 0.83 [95% CI, 0.45-1.22]; P<0.001). There was a similar trend in the addition of native T1 principal radiomics (C statistic, 0.75; net reclassification index, 0.93 [95% CI, 0.56-1.29]; P<0.001) and LGE principal radiomics (C statistic, 0.74; net reclassification index, 0.59 [95% CI, 0.19-0.98]; P=0.004). Five radiomic features per sequence were identified with correlation analysis. They showed a similar improvement in performance for differentiating between noncollagen and mild to moderate collagen (native T1, ECV, LGE C statistic, 0.75, 0.77, and 0.71, respectively). These improvements remained significant when confined to a single radiomic feature (native T1, ECV, LGE C statistic, 0.71, 0.70, and 0.64, respectively). CONCLUSIONS: Radiomic features extracted from native T1, ECV, and LGE provide incremental information that improves our capability to discriminate noncollagenous expansion from mild to moderate collagen and could be useful for detecting subtle chronic inflammation in patients with dilated cardiomyopathy.

Histologic Remission in Inflammatory Bowel Disease and Female Fertility: A Nationwide Study.

BACKGROUND & AIMS: Inflammatory bowel disease (IBD) is linked to reduced female fertility, but it is unclear how fertility rates vary by histologic disease activity. METHODS: Nationwide IBD cohort of Swedish women aged 15 to 44 years. We examined fertility rates during periods with vs without histologic inflammation (n = 21,046; follow-up, 1990-2016) and during periods with vs without clinical activity (IBD-related hospitalization, surgery, or treatment escalation) (n = 24,995; follow-up, 2006-2020). Accounting for sociodemographics and comorbidities, we used Poisson regression to estimate adjusted fertility rate ratios (aFRRs) for live births conceived during 12-month periods of histologic inflammation (vs histologic remission) and 3-month periods of clinically active IBD (vs quiescent IBD). RESULTS: During periods with vs without histologic inflammation, there were 6.35 (95% confidence interval [CI], 5.98-6.73) and 7.09 (95% CI, 6.48-7.70) live births conceived per 100 person-years of follow-up, respectively, or 1 fewer child per 14 women with 10 years of histologic inflammation (aFRR, 0.90; 95% CI, 0.81-1.00). In women with histologic inflammation, fertility was similarly reduced in ulcerative colitis (UC) (aFRR, 0.89 [95% CI, 0.78-1.02]) and Crohn's disease (CD) (aFRR, 0.86 [95% CI, 0.72-1.04]). Clinical IBD activity was associated with an aFRR of 0.76 (95% CI, 0.72-0.79) or 1 fewer child per 6 women with 10 years of clinical activity. Fertility was reduced in clinically active UC (aFRR, 0.75 [95% CI, 0.70-0.81]) and CD (aFRR, 0.76 [95% CI, 0.70-0.82]). Finally, among women with clinically quiescent IBD, histologic inflammation (vs histologic remission) was associated with reduced fertility (aFRR, 0.85 [95% CI, 0.73-0.98]). CONCLUSIONS: An association between histologic and clinical activity and reduced female fertility in CD and UC was found. Notably, histologic inflammation was also linked to reduced fertility in women with clinically quiescent IBD.

Standardizing Randomized Controlled Trials in Celiac Disease: An International Multidisciplinary Appropriateness Study.

BACKGROUND & AIMS: There is a need to develop safe and effective pharmacologic options for the treatment of celiac disease (CeD); however, consensus on the appropriate design and configuration of randomized controlled trials (RCTs) in this population is lacking. METHODS: A 2-round modified Research and Development/University of California Los Angeles Appropriateness Method study was conducted. Eighteen gastroenterologists (adult and pediatric) and gastrointestinal pathologists voted on statements pertaining to the configuration of CeD RCTs, inclusion and exclusion criteria, gluten challenge, and trial outcomes. Two RCT designs were considered, representing the following distinct clinical scenarios for which pharmacotherapy may be used: trials incorporating a gluten challenge to simulate exposure; and trials evaluating reversal of histologic changes, despite attempted adherence to a gluten-free diet. Each statement was rated as appropriate, uncertain, or inappropriate, using a 9-point Likert scale. RESULTS: For trials evaluating prevention of relapse after gluten challenge, participants adherent to a gluten-free diet for 12 months or more with normal or near-normal-sized villi should be enrolled. Gluten challenge should be FODMAPS (fermentable oligosaccharides, disaccharides, monosaccharides, and polyols) free, and efficacy evaluated using histology with a secondary patient-reported outcome measure. For trials evaluating reversal of villus atrophy, the panel voted it appropriate to enroll participants with a baseline villus height to crypt depth ratio ≤2 and measure efficacy using a primary histologic end point. Guidance for measuring histologic, endoscopic, and patient-reported outcomes in adult and pediatric patients with CeD are provided, along with recommendations regarding the merits and limitations of different end points. CONCLUSIONS: We developed standardized recommendations for clinical trial design, eligibility criteria, outcome measures, gluten challenge, and disease evaluations for RCTs in patients with CeD.

Biopsy Proteome Scoring to Determine Mucosal Remodeling in Celiac Disease.

BACKGROUND & AIMS: Histologic evaluation of gut biopsies is a cornerstone for diagnosis and management of celiac disease (CeD). Despite its wide use, the method depends on proper biopsy orientation, and it suffers from interobserver variability. Biopsy proteome measurement reporting on the tissue state can be obtained by mass spectrometry analysis of formalin-fixed paraffin-embedded tissue. Here we aimed to transform biopsy proteome data into numerical scores that give observer-independent measures of mucosal remodeling in CeD. METHODS: A pipeline using glass-mounted formalin-fixed paraffin-embedded sections for mass spectrometry-based proteome analysis was established. Proteome data were converted to numerical scores using 2 complementary approaches: a rank-based enrichment score and a score based on machine learning using logistic regression. The 2 scoring approaches were compared with each other and with histology analyzing 18 patients with CeD with biopsies collected before and after treatment with a gluten-free diet as well as biopsies from patients with CeD with varying degree of remission (n = 22). Biopsies from individuals without CeD (n = 32) were also analyzed. RESULTS: The method yielded reliable proteome scoring of both unstained and H&E-stained glass-mounted sections. The scores of the 2 approaches were highly correlated, reflecting that both approaches pick up proteome changes in the same biological pathways. The proteome scores correlated with villus height-to-crypt depth ratio. Thus, the method is able to score biopsies with poor orientation. CONCLUSIONS: Biopsy proteome scores give reliable observer and orientation-independent measures of mucosal remodeling in CeD. The proteomic method can readily be implemented by nonexpert laboratories in parallel to histology assessment and easily scaled for clinical trial settings.

Tissue niches and immunopathology through the lens of spatial tissue profiling techniques.

Spatial organization plays a fundamental role in biology, influencing the function of biological structures at various levels. The immune system, in particular, relies on the orchestrated interactions of immune cells with their microenvironment to mount protective or pathogenic immune responses. The COVID-19 pandemic has underscored the significance of studying immunity within target organs to understand disease progression and severity. To achieve this, multiplex histology and spatial transcriptomics have proven indispensable in providing a spatial context to protein and gene expression patterns. By combining these techniques, researchers gain a more comprehensive understanding of the complex interactions at the cellular and molecular level in distinct tissue niches, key functional units modulating health and disease. In this review, we discuss recent advances in spatial tissue profiling techniques, highlighting their advantages over traditional histopathology studies. The insights gained from these approaches have the potential to revolutionize the diagnosis and treatment of various diseases including cancer, autoimmune disorders, and infectious diseases. However, we also acknowledge their challenges and limitations. Despite these, spatial tissue profiling offers promising opportunities to improve our understanding of how tissue niches direct regional immunity, and their relevance in tissue immunopathology, as a basis for novel therapeutic strategies and personalized medicine.

Distinct virtual histology of grey matter atrophy in four neuroinflammatory diseases.

Gray matter (GM) atrophies were observed in multiple sclerosis, neuromyelitis optica spectrum disorders (both anti-aquaporin-4 antibody-positive [AQP4+], and -negative [AQP4-] subtypes NMOSD), and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Revealing the pathogenesis of brain atrophy in these disorders would help their differential diagnosis and guide therapeutic strategies. To determine the neurobiological underpinnings of GM atrophies in multiple sclerosis, AQP4+ NMOSD, AQP4- NMOSD, and MOGAD, we conducted a virtual histology analysis that links T1-weighted image derived GM atrophy and gene expression using a multicenter cohort of 324 patients with multiple sclerosis, 197 patients with AQP4+ NMOSD, 75 patients with AQP4- NMOSD, 47 patients with MOGAD, and 2,169 healthy controls (HCs). First, interregional GM atrophy profiles across the cortical and subcortical regions were determined by Cohen's d between patients with multiple sclerosis, AQP4+ NMOSD, AQP4- NMOSD, MOGAD and HCs. Then, the GM atrophy profiles were spatially correlated with the gene expressions extracted from the Allen Human Brain Atlas, respectively. Finally, we explored the virtual histology of clinical feature relevant GM atrophy by subgroup analysis that stratified by physical disability, disease duration, number of relapses, lesion burden, and cognitive function. Multiple sclerosis showed severe widespread GM atrophy pattern, mainly involving subcortical nuclei and brainstem. AQP4+ NMOSD showed obvious widespread GM atrophy pattern, predominately located in occipital cortex as well as cerebellum. AQP4- NMOSD showed mild widespread GM atrophy pattern, mainly located in frontal and parietal cortices. MOGAD showed GM atrophy mainly involving the frontal and temporal cortices. High expression of genes specific to microglia, astrocytes, oligodendrocytes, and endothelial cells in multiple sclerosis, S1 pyramidal cells in AQP4+ NMOSD, as well as S1 and CA1 pyramidal cells in MOGAD had spatial correlations with GM atrophy profiles were observed, while no atrophy profile related gene expression was found in AQP4- NMOSD. Virtual histology of clinical feature relevant GM atrophy mainly pointed to the shared neuronal and endothelial cells among the four neuroinflammatory diseases. The unique underlying virtual histology patterns were microglia, astrocytes, and oligodendrocytes for multiple sclerosis; astrocytes for AQP4+ NMOSD; and oligodendrocytes for MOGAD. Neuronal and endothelial cells were shared potential targets across these neuroinflammatory diseases. These findings might help their differential diagnosis and optimal therapeutic strategies.

The Subcortical Atlas of the Marmoset ("SAM") monkey based on high-resolution MRI and histology.

A comprehensive three-dimensional digital brain atlas of cortical and subcortical regions based on MRI and histology has a broad array of applications in anatomical, functional, and clinical studies. We first generated a Subcortical Atlas of the Marmoset, called the "SAM," from 251 delineated subcortical regions (e.g. thalamic subregions, etc.) derived from high-resolution Mean Apparent Propagator-MRI, T2W, and magnetization transfer ratio images ex vivo. We then confirmed the location and borders of these segmented regions in the MRI data using matched histological sections with multiple stains obtained from the same specimen. Finally, we estimated and confirmed the atlas-based areal boundaries of subcortical regions by registering this ex vivo atlas template to in vivo T1- or T2W MRI datasets of different age groups (single vs. multisubject population-based marmoset control adults) using a novel pipeline developed within Analysis of Functional NeuroImages software. Tracing and validating these important deep brain structures in 3D will improve neurosurgical planning, anatomical tract tracer injections, navigation of deep brain stimulation probes, functional MRI and brain connectivity studies, and our understanding of brain structure-function relationships. This new ex vivo template and atlas are available as volumes in standard NIFTI and GIFTI file formats and are intended for use as a reference standard for marmoset brain research.

USP28 promotes tumorigenesis and cisplatin resistance by deubiquitinating MAST1 protein in cancer cells.

Cisplatin is a chemotherapy drug that causes a plethora of DNA lesions and inhibits DNA transcription and replication, resulting in the induction of apoptosis in cancer cells. However, over time, patients develop resistance to cisplatin due to repeated treatment and thus the treatment efficacy is limited. Therefore, identifying an alternative therapeutic strategy combining cisplatin treatment along with targeting factors that drive cisplatin resistance is needed. CRISPR/Cas9 system-based genome-wide screening for the deubiquitinating enzyme (DUB) subfamily identified USP28 as a potential DUB that governs cisplatin resistance. USP28 regulates the protein level of microtubule-associated serine/threonine kinase 1 (MAST1), a common kinase whose expression is elevated in several cisplatin-resistant cancer cells. The expression level and protein turnover of MAST1 is a major factor driving cisplatin resistance in many cancer types. Here we report that the USP28 interacts and extends the half-life of MAST1 protein by its deubiquitinating activity. The expression pattern of USP28 and MAST1 showed a positive correlation across a panel of tested cancer cell lines and human clinical tissues. Additionally, CRISPR/Cas9-mediated gene knockout of USP28 in A549 and NCI-H1299 cells blocked MAST1-driven cisplatin resistance, resulting in suppressed cell proliferation, colony formation ability, migration and invasion in vitro. Finally, loss of USP28 destabilized MAST1 protein and attenuated tumor growth by sensitizing cells to cisplatin treatment in mouse xenograft model. We envision that targeting the USP28-MAST1 axis along with cisplatin treatment might be an alternative therapeutic strategy to overcome cisplatin resistance in cancer patients.

A Standardized and Reproducible Workflow for Membrane Glass Slides in Routine Histology and Spatial Proteomics.

Defining the molecular phenotype of single cells in situ is key for understanding tissue architecture in health and disease. Advanced imaging platforms have recently been joined by spatial omics technologies, promising unparalleled insights into the molecular landscape of biological samples. Furthermore, high-precision laser microdissection (LMD) of tissue on membrane glass slides is a powerful method for spatial omics technologies and single-cell type spatial proteomics in particular. However, current histology protocols have not been compatible with glass membrane slides and LMD for automated staining platforms and routine histology procedures. This has prevented the combination of advanced staining procedures with LMD. In this study, we describe a novel method for handling glass membrane slides that enables automated eight-color multiplexed immunofluorescence staining and high-quality imaging followed by precise laser-guided extraction of single cells. The key advance is the glycerol-based modification of heat-induced epitope retrieval protocols, termed "G-HIER." We find that this altered antigen-retrieval solution prevents membrane distortion. Importantly, G-HIER is fully compatible with current antigen retrieval workflows and mass spectrometry-based proteomics and does not affect proteome depth or quality. To demonstrate the versatility of G-HIER for spatial proteomics, we apply the recently introduced deep visual proteomics technology to perform single-cell type analysis of adjacent suprabasal and basal keratinocytes of human skin. G-HIER overcomes previous incompatibility of standard and advanced staining protocols with membrane glass slides and enables robust integration with routine histology procedures, high-throughput multiplexed imaging, and sophisticated downstream spatial omics technologies.

Local, Quantitative Morphometry of Fibroproliferative Lung Injury Using Laminin.

Investigations into the mechanisms of injury and repair in fibroproliferative disease require consideration of the spatial heterogeneity inherent in the disease. Most scoring of fibrotic remodeling in preclinical animal models relies on the modified Ashcroft score, which is an ordinal rubric of macroscopic resolution. The obvious limitations of manual histopathologic scoring have generated an unmet need for unbiased, repeatable scoring of fibroproliferative burden in tissue. Using computer vision approaches on immunofluorescence imaging of the extracellular matrix component laminin, we generated a robust and repeatable quantitative remodeling scorer. In the bleomycin lung injury model, the quantitative remodeling scorer shows significant agreement with the modified Ashcroft scale. This antibody-based approach is easily integrated into larger multiplex immunofluorescence experiments, which we demonstrate by testing the spatial apposition of tertiary lymphoid structures to fibroproliferative tissue, a poorly characterized phenomenon observed in both human interstitial lung diseases and preclinical models of lung fibrosis. The tool reported in this article is available as a stand-alone application that is usable without programming knowledge.

Exploring contrast-enhancing staining agents for studying adipose tissue through contrast-enhanced computed tomography.

Contrast-enhanced computed tomography offers a nondestructive approach to studying adipose tissue in 3D. Several contrast-enhancing staining agents (CESAs) have been explored, whereof osmium tetroxide (OsO4) is the most popular nowadays. However, due to the toxicity and volatility of the conventional OsO4, alternative CESAs with similar staining properties were desired. Hf-WD 1:2 POM and Hexabrix have proven effective for structural analysis of adipocytes using contrast-enhanced computed tomography but fail to provide chemical information. This study introduces isotonic Lugol's iodine (IL) as an alternative CESA for adipose tissue analysis, comparing its staining potential with Hf-WD 1:2 POM and Hexabrix in murine caudal vertebrae and bovine muscle tissue strips. Single and sequential staining protocols were compared to assess the maximization of information extraction from each sample. The study investigated interactions, distribution, and reactivity of iodine species towards biomolecules using simplified model systems and assesses the potential of the CESA to provide chemical information. (Bio)chemical analyses on whole tissues revealed that differences in adipocyte gray values post-IL staining were associated with chemical distinctions between bovine muscle tissue and murine caudal vertebrae. More specific, a difference in the degree of unsaturation of fatty acids was identified as a likely contributor, though not the sole determinant of gray value differences. This research sheds light on the potential of IL as a CESA, offering both structural and chemical insights into adipose tissue composition.

Spatial lipidomics of coronary atherosclerotic plaque development in a familial hypercholesterolemia swine model.

Coronary atherosclerosis is caused by plaque build-up, with lipids playing a pivotal role in its progression. However, lipid composition and distribution within coronary atherosclerosis remain unknown. This study aims to characterize lipids and investigate differences in lipid composition across disease stages to aid in the understanding of disease progression. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) was used to visualize lipid distributions in coronary artery sections (n = 17) from hypercholesterolemic swine. We performed histology on consecutive sections to classify the artery segments and to investigate colocalization between lipids and histological regions of interest in advanced plaque, including necrotic core and inflammatory cells. Segments were classified as healthy (n = 6), mild (n = 6), and advanced disease (n = 5) artery segments. Multivariate data analysis was employed to find differences in lipid composition between the segment types, and the lipids' spatial distribution was investigated using non-negative matrix factorization (NMF). Through this process, MALDI-MSI detected 473 lipid-related features. NMF clustering described three components in positive ionization mode: triacylglycerides (TAG), phosphatidylcholines (PC), and cholesterol species. In negative ionization mode, two components were identified: one driven by phosphatidylinositol(PI)(38:4), and one driven by ceramide-phosphoethanolamine(36:1). Multivariate data analysis showed the association between advanced disease and specific lipid signatures like PC(O-40:5) and cholesterylester(CE)(18:2). Ether-linked phospholipids and LysoPC species were found to colocalize with necrotic core, and mostly CE, ceramide, and PI species colocalized with inflammatory cells. This study, therefore, uncovers distinct lipid signatures correlated with plaque development and their colocalization with necrotic core and inflammatory cells, enhancing our understanding of coronary atherosclerosis progression.

A method to image brain tissue frozen at autopsy.

Magnetic Resonance Imaging (MRI) can provide the location and signal characteristics of pathological regions within a postmortem tissue block, thereby improving the efficiency of histopathological studies. However, such postmortem-MRI guided histopathological studies have so far only been performed on fixed samples as imaging tissue frozen at the time of extraction, while preserving its integrity, is significantly more challenging. Here we describe the development of cold-postmortem-MRI, which can preserve tissue integrity and help target techniques such as transcriptomics. As a first step, RNA integrity number (RIN) was used to determine the rate of tissue biomolecular degradation in mouse brains placed at various temperatures between -20 °C and +20 °C for up to 24 h. Then, human tissue frozen at the time of autopsy was immersed in 2-methylbutane, sealed in a bio-safe tissue chamber, and cooled in the MRI using a recirculating chiller to determine MRI signal characteristics. The optimal imaging temperature, which did not show significant RIN deterioration for over 12 h, at the same time giving robust MRI signal and contrast between brain tissue types was deemed to be -7 °C. Finally, MRI was performed on human tissue blocks at this optimal imaging temperatures using a magnetization-prepared rapid gradient echo (MPRAGE, isotropic resolution between 0.3-0.4 mm) revealing good gray-white matter contrast and revealing subpial, subcortical, and deep white matter lesions. RINs measured before and after imaging revealed no significant changes (n = 3, p = 0.18, paired t-test). In addition to improving efficiency of downstream processes, imaging tissue at sub-zero temperatures may also improve our understanding of compartment specificity of MRI signal.

A toolkit for stroke infarct volume estimation in rodents.

Stroke volume is a key determinant of infarct severity and an important metric for evaluating treatments. However, accurate estimation of stroke volume can be challenging, due to the often confined 2-dimensional nature of available data. Here, we introduce a comprehensive semi-automated toolkit to reliably estimate stroke volumes based on (1) whole brains ex-vivo magnetic resonance imaging (MRI) and (2) brain sections that underwent immunofluorescence staining. We located and quantified infarct areas from MRI three days (acute) and 28 days (chronic) after photothrombotic stroke induction in whole mouse brains. MRI results were compared with measures obtained from immunofluorescent histologic sections of the same brains. We found that infarct volume determined by post-mortem MRI was highly correlated with a deviation of only 6.6 % (acute) and 4.9 % (chronic) to the measurements as determined in the histological brain sections indicating that both methods are capable of accurately assessing brain tissue damage (Pearson r > 0.9, p < 0.001). The Dice similarity coefficient (DC) showed a high degree of coherence (DC > 0.8) between MRI-delineated regions of interest (ROIs) and ROIs obtained from histologic sections at four to six pre-defined landmarks, with histology-based delineation demonstrating higher inter-operator similarity compared to MR images. We further investigated stroke-related scarring and post-ischemic angiogenesis in cortical peri­infarct regions and described a negative correlation between GFAP+fluorescence intensity and MRI-obtained lesion size.