ILC2-driven innate immune checkpoint mechanism antagonizes NK cell antimetastatic function in the lung.

Metastasis constitutes the primary cause of cancer-related deaths, with the lung being a commonly affected organ. We found that activation of lung-resident group 2 innate lymphoid cells (ILC2s) orchestrated suppression of natural killer (NK) cell-mediated innate antitumor immunity, leading to increased lung metastases and mortality. Using multiple models of lung metastasis, we show that interleukin (IL)-33-dependent ILC2 activation in the lung is involved centrally in promoting tumor burden. ILC2-driven innate type 2 inflammation is accompanied by profound local suppression of interferon-γ production and cytotoxic function of lung NK cells. ILC2-dependent suppression of NK cells is elaborated via an innate regulatory mechanism, which is reliant on IL-5-induced lung eosinophilia, ultimately limiting the metabolic fitness of NK cells. Therapeutic targeting of IL-33 or IL-5 reversed NK cell suppression and alleviated cancer burden. Thus, we reveal an important function of IL-33 and ILC2s in promoting tumor metastasis via their capacity to suppress innate type 1 immunity.

Imaging tumor lactate is feasible for identifying intermediate-risk prostate cancer patients with postsurgical biochemical recurrence.

While radical prostatectomy remains the mainstay of prostate cancer (PCa) treatment, 20 to 40% of patients develop postsurgical biochemical recurrence (BCR). A particularly challenging clinical cohort includes patients with intermediate-risk disease whose risk stratification would benefit from advanced approaches that complement standard-of-care diagnostic tools. Here, we show that imaging tumor lactate using hyperpolarized 13C MRI and spatial metabolomics identifies BCR-positive patients in two prospective intermediate-risk surgical cohorts. Supported by spatially resolved tissue analysis of established glycolytic biomarkers, this study provides the rationale for multicenter trials of tumor metabolic imaging as an auxiliary tool to support PCa treatment decision-making.

Ischemia-Selective Cardioprotection by Malonate for Ischemia/Reperfusion Injury.

BACKGROUND: Inhibiting SDH (succinate dehydrogenase), with the competitive inhibitor malonate, has shown promise in ameliorating ischemia/reperfusion injury. However, key for translation to the clinic is understanding the mechanism of malonate entry into cells to enable inhibition of SDH, its mitochondrial target, as malonate itself poorly permeates cellular membranes. The possibility of malonate selectively entering the at-risk heart tissue on reperfusion, however, remains unexplored. METHODS: C57BL/6J mice, C2C12 and H9c2 myoblasts, and HeLa cells were used to elucidate the mechanism of selective malonate uptake into the ischemic heart upon reperfusion. Cells were treated with malonate while varying pH or together with transport inhibitors. Mouse hearts were either perfused ex vivo (Langendorff) or subjected to in vivo left anterior descending coronary artery ligation as models of ischemia/reperfusion injury. Succinate and malonate levels were assessed by liquid chromatography-tandem mass spectrometry LC-MS/MS, in vivo by mass spectrometry imaging, and infarct size by TTC (2,3,5-triphenyl-2H-tetrazolium chloride) staining. RESULTS: Malonate was robustly protective against cardiac ischemia/reperfusion injury, but only if administered at reperfusion and not when infused before ischemia. The extent of malonate uptake into the heart was proportional to the duration of ischemia. Malonate entry into cardiomyocytes in vivo and in vitro was dramatically increased at the low pH (≈6.5) associated with ischemia. This increased uptake of malonate was blocked by selective inhibition of MCT1 (monocarboxylate transporter 1). Reperfusion of the ischemic heart region with malonate led to selective SDH inhibition in the at-risk region. Acid-formulation greatly enhances the cardioprotective potency of malonate. CONCLUSIONS: Cardioprotection by malonate is dependent on its entry into cardiomyocytes. This is facilitated by the local decrease in pH that occurs during ischemia, leading to its selective uptake upon reperfusion into the at-risk tissue, via MCT1. Thus, malonate's preferential uptake in reperfused tissue means it is an at-risk tissue-selective drug that protects against cardiac ischemia/reperfusion injury.

Comorbidities in patients with vascular dementia and Alzheimer's disease with Neuropsychiatric symptoms.

INTRODUCTION: This study aimed to examine baseline risk factors in Alzheimer's Disease (AD) and Vascular dementia (VaD) patients with neuropsychiatry symptoms (NPS), and determine whether specific risk factors differ by subtypes of dementia for AD and VaD patients with NPS. METHODS: A retrospective data analysis was conducted to evaluate similarities and differences in the risk factors for AD and VaD with NPS. The analysis included 2949 patients with VaD and 6341 patients with clinical confirmation of AD and VaD with or without NPS collected between February 2016 and August 2021. The multivariate logistic regression analysis was used to determine the risk factors associated with AD and VaD with NPS, by predicting the increasing odds (odds ratios (ORs) of an association of a specific baseline risk factor with AD or VaD with NPS. The validity of the regression models was tested using a Hosmer-Lemeshow test, while the Receiver Operating Curve (ROC) was used to test the sensitivity of the models. RESULTS: In the adjusted analysis TSH (OR = 1.781, 95 % CI, p = 0.0025) and CHF (OR = 1.620, 95 %, p = 0.016) were associated with VaD with NPS, while a history of emergency department(ED) admission (OR = 0.277, 95 % CI, p = 0.003) likely to be associated with VaD patients without NPS. For AD patients, a history of CVA (OR = 1.395, 95 % CI, p = 0.032) and cancer (OR = 1.485, 95 % CI, p = 0.013) were associated with AD patients with NPS. DISCUSSION: The findings of this study indicate that an abnormal thyroid gland and CHF were linked to VaD patients with behavioral disturbances, while CVA and cancer were linked to AD patients with behavioral disturbances. These findings suggest the need to develop management strategies for the care of patients with AD and VaD with NPS.

Obstetric Neuropathy in Diabetic Patients: The "Double Hit Hypothesis".

The two-hit model has been proposed to explain the effects of diabetes on mothers who are already in a putative subclinical damaged state and then undergo neuronal damage during the delivery process. However, the anatomical and pathophysiological mechanisms are not well understood. Our overarching hypothesis in this review paper is that pregnant women who are diabetic have a damaged peripheral nervous system, constituting the "first hit" hypothesis. The delivery process itself-the "second hit"-can produce neurological damage to the mother. Women with diabetes mellitus (DM) are at risk for neurological damage during both hits, but the cumulative effects of both "hits" pose a greater risk of neurological damage and pathophysiological changes during delivery. In our analysis, we introduce the different steps of our concept paper. Subsequently, we describe each of the topics. First, we outline the mechanisms by which diabetes acts as a detrimental variable in neuropathy by focusing on the most common form of diabetic neuropathy, diabetic distal symmetrical polyneuropathy, also known as distal sensorimotor neuropathy. The possible role of macrosomia in causing diabetic neuropathy and obstetric neurological injury is discussed. Second, we describe how vaginal delivery can cause various obstetrical neurological syndromes and pathophysiological changes. Third, we highlight the risk of obstetric neuropathy and discuss anatomical sites at which lesions may occur, including lesions during delivery. Fourth, we characterize the pathophysiological pathways involved in the causation of diabetic neuropathy. Finally, we highlight diabetic damage to sensory vs. motor nerves, including how hyperglycemia causes different types of damage depending on the location of nerve cell bodies.

Research Education Program for Underrepresented Minority Students: Students' Perception of Academic Enrichment and Research Activities.

The Research Education Program (REP) is an NIH R25-funded training grant designed to increase the pipeline of underrepresented minority (URM) students entering graduate programs and pursuing biomedical research and health care careers. Each week, students participated in different academic enrichment activities during morning sessions. Research activities were during afternoon sessions. URM students presented their research findings in a local poster session with their peers, graduate medical students, and faculty members. They also attended national conferences to gain experience and expand their professional networks. Our participants included 14.3% rural, 42.85% suburban, and 42.85% urban students. Of this, 83.33% were females, while 16.67% were males. In addition, 100% of students indicated exceptional satisfaction in 64.0% of the academic enrichment activities offered by the REP, and 100% indicated exceptional satisfaction in 63.0% of the research activities. Future research will investigate the long-term effects of REP and graduate enrollments.

Atmospheric-Pressure Infrared Laser-Ablation Plasma-Postionization Mass Spectrometry Imaging of Formalin-Fixed Paraffin-Embedded (FFPE) and Fresh-Frozen Tissue Sections with No Sample Preparation.

Mass spectrometry imaging (MSI) encompasses a powerful suit of techniques which provide spatially resolved atomic and molecular information from almost any sample type. MSI is now widely used in preclinical research to provide insight into metabolic phenotypes of disease. Typically, fresh-frozen tissue preparations are considered optimal for biological MSI and other traditional preservation methods such as formalin fixation, alone or with paraffin embedding (FFPE), are considered less optimal or even incompatible. Due to the prevalence of FFPE tissue storage, particularly for rare and therefore high-value tissue samples, there is substantial motivation for optimizing MSI methods for analysis of FFPE tissue. Here, we present a novel modality, atmospheric-pressure infrared laser-ablation plasma postionization (AP-IR-LA-PPI), with the first proof-of-concept examples of MSI for FFPE and fresh-frozen tissues, with no post-sectioning sample preparation. We present ion images from FFPE and fresh tissues in positive and negative ion modes. Molecular annotations (via the Metaspace annotation engine) and on-tissue MS/MS provide additional confidence that the detected ions arise from a broad range of metabolite and lipid classes from both FFPE and fresh-frozen tissues.

Method To Visualize the Intratumor Distribution and Impact of Gemcitabine in Pancreatic Ductal Adenocarcinoma by Multimodal Imaging.

Gemcitabine (dFdC) is a common treatment for pancreatic cancer; however, it is thought that treatment may fail because tumor stroma prevents drug distribution to tumor cells. Gemcitabine is a pro-drug with active metabolites generated intracellularly; therefore, visualizing the distribution of parent drug as well as its metabolites is important. A multimodal imaging approach was developed using spatially coregistered mass spectrometry imaging (MSI), imaging mass cytometry (IMC), multiplex immunofluorescence microscopy (mIF), and hematoxylin and eosin (H&E) staining to assess the local distribution and metabolism of gemcitabine in tumors from a genetically engineered mouse model of pancreatic cancer (KPC) allowing for comparisons between effects in the tumor tissue and its microenvironment. Mass spectrometry imaging (MSI) enabled the visualization of the distribution of gemcitabine (100 mg/kg), its phosphorylated metabolites dFdCMP, dFdCDP and dFdCTP, and the inactive metabolite dFdU. Distribution was compared to small-molecule ATR inhibitor AZD6738 (25 mg/kg), which was codosed. Gemcitabine metabolites showed heterogeneous distribution within the tumor, which was different from the parent compound. The highest abundance of dFdCMP, dFdCDP, and dFdCTP correlated with distribution of endogenous AMP, ADP, and ATP in viable tumor cell regions, showing that gemcitabine active metabolites are reaching the tumor cell compartment, while AZD6738 was located to nonviable tumor regions. The method revealed that the generation of active, phosphorylated dFdC metabolites as well as treatment-induced DNA damage primarily correlated with sites of high proliferation in KPC PDAC tumor tissue, rather than sites of high parent drug abundance.

Epidermolysis bullosa acquisita: a case series of three paediatric patients.

Epidermolysis bullosa acquisita is a highly uncommon condition in the paediatric population. This article describes three children with this disease, different clinical presentation and management. It also reviews the most relevant articles on this topic.

Structural and Ultrastructural Analysis of the Multiple Myeloma Cell Niche and a Patient-Specific Model of Plasma Cell Dysfunction.

Multiple myeloma (MM) is a deadly, incurable malignancy in which antibody-secreting plasma cells (PCs) become neoplastic. Previous studies have shown that the PC niche plays a role cancer progression. Bone marrow (BM) cores from MM and a premalignant condition known as monoclonal gammopathy of unknown significance (MGUS) patients were analyzed with confocal and transmission electron microscopy. The BM aspirates from these patients were used to generate 3D PC cultures. These in vitro cultures were then assayed for the molecular, cellular, and ultrastructural hallmarks of dysfunctional PC at days 1 and 5. In vivo, evidence of PC endoplasmic reticulum stress was found in both MM and MGUS BM; however, evidence of PC autophagy was found only in MM BM. Analysis of in vitro cultures found that MM PC can survive and maintain a differentiated phenotype over an unprecedented 5 days, had higher levels of paraprotein production when compared to MGUS-derived cultures, and showed evidence of PC autophagy as well. Increased fibronectin deposition around PC associated with disease severity and autophagy dysregulation was also observed. 3D cultures constructed from BM aspirates from MGUS and MM patients allow for long-term culture of functional PC while maintaining their distinct morphological phenotypes.

Fifteen-minute consultation: How to manage eczema in children.

Atopic eczema is common and has a major impact on quality of life. Paediatricians and general practitioners play a key role in the non-specialist treatment of atopic eczema. However, the clinical nature of the diagnosis, multitude of topical therapies and sometimes complicated treatment strategies can leave both clinicians and families feeling bewildered. This article aims to provide a concise, patient-focused summary of the assessment and management of childhood atopic eczema.

Mass Spectrometry Detection and Imaging of a Non-Covalent Protein-Drug Complex in Tissue from Orally Dosed Rats.

Here, we demonstrate detection by mass spectrometry of an intact protein-drug complex directly from liver tissue from rats that had been orally dosed with the drug. The protein-drug complex comprised fatty acid binding protein 1, FABP1, non-covalently bound to the small molecule therapeutic bezafibrate. Moreover, we demonstrate spatial mapping of the [FABP1+bezafibrate] complex across a thin section of liver by targeted mass spectrometry imaging. This work is the first demonstration of in situ mass spectrometry analysis of a non-covalent protein-drug complex formed in vivo and has implications for early stage drug discovery by providing a route to target-drug characterization directly from the physiological environment.

A SERS-Active Electrospun Polymer Mesh for Spatially Localized pH Measurements of the Cellular Microenvironment.

Extracellular pH (pHe) is an important chemical factor in many cellular processes and disease pathologies. The routine sampling of pHe in vitro could lead to innovative advances in therapeutics. To this end, we have fabricated a novel gold-coated polymer mesh, which facilitates the real-time measurement of pHe via surface-enhanced Raman scattering (SERS). In this proof of concept study, we apply our SERS sensor to measure metabolically induced changes in the pHe of carcinoma-derived cell line HepG2/C3A. We demonstrate that gold-coated polyurethane electrospun nanofibers (AuNF) have strong and reproducible SERS spectra of surface-adsorbed analytes. By functionalizing AuNF with pH-responsive reporter 4-mercaptobenzoic acid (MBA), we have developed an accurate pH SERS sensor for the extracellular microenvironment. We cultured HepG2/C3A on the surface of MBA-AuNF and measured an acidic shift in pHe at the cell-fiber interface. Following exposure to staurosporine, an apoptosis-inducing drug, we observed changes in the HepG2/C3A cellular morphology indicative of controlled cell death, and detected an increase in the pHe of HepG2/C3A. These results demonstrate how subtle changes in pHe, induced by the metabolic activity of cells, can be measured with our novel SERS sensor MBA-AuNF. The excellent pH measurement performance of MBA-AuNF provides a unique platform to study extracellular pH on the microscale and will help to deepen our understanding of pHe in disease pathology.

Evaluation of UV-C Decontamination of Clinical Tissue Sections for Spatially Resolved Analysis by Mass Spectrometry Imaging (MSI).

Clinical tissue specimens are often unscreened, and preparation of tissue sections for analysis by mass spectrometry imaging (MSI) can cause aerosolization of particles potentially carrying an infectious load. We here present a decontamination approach based on ultraviolet-C (UV-C) light to inactivate clinically relevant pathogens such as herpesviridae, papovaviridae human immunodeficiency virus, or SARS-CoV-2, which may be present in human tissue samples while preserving the biodistributions of analytes within the tissue. High doses of UV-C required for high-level disinfection were found to cause oxidation and photodegradation of endogenous species. Lower UV-C doses maintaining inactivation of clinically relevant pathogens to a level of increased operator safety were found to be less destructive to the tissue metabolome and xenobiotics. These doses caused less alterations of the tissue metabolome and allowed elucidation of the biodistribution of the endogenous metabolites. Additionally, we were able to determine the spatially integrated abundances of the ATR inhibitor ceralasertib from decontaminated human biopsies using desorption electrospray ionization-MSI (DESI-MSI).

Deep Learning-Based Annotation Transfer between Molecular Imaging Modalities: An Automated Workflow for Multimodal Data Integration.

An ever-increasing array of imaging technologies are being used in the study of complex biological samples, each of which provides complementary, occasionally overlapping information at different length scales and spatial resolutions. It is important to understand the information provided by one technique in the context of the other to achieve a more holistic overview of such complex samples. One way to achieve this is to use annotations from one modality to investigate additional modalities. For microscopy-based techniques, these annotations could be manually generated using digital pathology software or automatically generated by machine learning (including deep learning) methods. Here, we present a generic method for using annotations from one microscopy modality to extract information from complementary modalities. We also present a fast, general, multimodal registration workflow [evaluated on multiple mass spectrometry imaging (MSI) modalities, matrix-assisted laser desorption/ionization, desorption electrospray ionization, and rapid evaporative ionization mass spectrometry] for automatic alignment of complex data sets, demonstrating an order of magnitude speed-up compared to previously published work. To demonstrate the power of the annotation transfer and multimodal registration workflows, we combine MSI, histological staining (such as hematoxylin and eosin), and deep learning (automatic annotation of histology images) to investigate a pancreatic cancer mouse model. Neoplastic pancreatic tissue regions, which were histologically indistinguishable from one another, were observed to be metabolically different. We demonstrate the use of the proposed methods to better understand tumor heterogeneity and the tumor microenvironment by transferring machine learning results freely between the two modalities.

Correlative Imaging of Trace Elements and Intact Molecular Species in a Single-Tissue Sample at the 50 µm Scale.

Elemental and molecular imaging play a crucial role in understanding disease pathogenesis. To accurately correlate elemental and molecular markers, it is desirable to perform sequential elemental and molecular imaging on a single-tissue section. However, very little is known about the impact of performing these measurements in sequence. In this work, we highlight some of the challenges and successes associated with performing elemental mapping in sequence with mass spectrometry imaging. Specifically, the feasibility of molecular mapping using the mass spectrometry imaging (MSI) techniques matrix-assisted laser desorption ionization (MALDI) and desorption electrospray ionization (DESI) in sequence with the elemental mapping technique particle-induced X-ray emission (PIXE) is explored. Challenges for integration include substrate compatibility, as well as delocalization and spectral changes. We demonstrate that while sequential imaging comes with some compromises, sequential DESI-PIXE imaging is sufficient to correlate sulfur, iron, and lipid markers in a single tissue section at the 50 µm scale.

Implications of Peak Selection in the Interpretation of Unsupervised Mass Spectrometry Imaging Data Analyses.

Mass spectrometry imaging can produce large amounts of complex spectral and spatial data. Such data sets are often analyzed with unsupervised machine learning approaches, which aim at reducing their complexity and facilitating their interpretation. However, choices made during data processing can impact the overall interpretation of these analyses. This work investigates the impact of the choices made at the peak selection step, which often occurs early in the data processing pipeline. The discussion is done in terms of visualization and interpretation of the results of two commonly used unsupervised approaches: t-distributed stochastic neighbor embedding and k-means clustering, which differ in nature and complexity. Criteria considered for peak selection include those based on hypotheses (exemplified herein in the analysis of metabolic alterations in genetically engineered mouse models of human colorectal cancer), particular molecular classes, and ion intensity. The results suggest that the choices made at the peak selection step have a significant impact in the visual interpretation of the results of either dimensionality reduction or clustering techniques and consequently in any downstream analysis that relies on these. Of particular significance, the results of this work show that while using the most abundant ions can result in interesting structure-related segmentation patterns that correlate well with histological features, using a smaller number of ions specifically selected based on prior knowledge about the biochemistry of the tissues under investigation can result in an easier-to-interpret, potentially more valuable, hypothesis-confirming result. Findings presented will help researchers understand and better utilize unsupervised machine learning approaches to mine high-dimensionality data.

Method to Investigate the Distribution of Water-Soluble Drug-Delivery Systems in Fresh Frozen Tissues Using Imaging Mass Cytometry.

Imaging mass cytometry (IMC) offers the opportunity to image metal- and heavy halogen-containing xenobiotics in a highly multiplexed experiment with other immunochemistry-based reagents to distinguish uptake into different tissue structures or cell types. However, in practice, many xenobiotics are not amenable to this analysis, as any compound which is not bound to the tissue matrix will delocalize during aqueous sample-processing steps required for IMC analysis. Here, we present a strategy to perform IMC experiments on a water-soluble polysarcosine-modified dendrimer drug-delivery system (S-Dends). This strategy involves two consecutive imaging acquisitions on the same tissue section using the same instrumental platform, an initial laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MSI) experiment followed by tissue staining and a standard IMC experiment. We demonstrated that settings can be found for the initial ablation step that leave sufficient residual tissue for subsequent antibody staining and visualization. This workflow results in lateral resolution for the S-Dends of 2 µm followed by imaging of metal-tagged antibodies at 1 µm.

Comparison of 13 C MRI of hyperpolarized [1-13 C]pyruvate and lactate with the corresponding mass spectrometry images in a murine lymphoma model.

PURPOSE: To compare carbon-13 (13 C) MRSI of hyperpolarized [1-13 C]pyruvate metabolism in a murine tumor model with mass spectrometric (MS) imaging of the corresponding tumor sections in order to cross validate these metabolic imaging techniques and to investigate the effects of pyruvate delivery and tumor lactate concentration on lactate labeling. METHODS: [1-13 C]lactate images were obtained from tumor-bearing mice, following injection of hyperpolarized [1-13 C]pyruvate, using a single-shot 3D 13 C spectroscopic imaging sequence in vivo and using desorption electrospray ionization MS imaging of the corresponding rapidly frozen tumor sections ex vivo. The images were coregistered, and levels of association were determined by means of Spearman rank correlation and Cohen kappa coefficients as well as linear mixed models. The correlation between [1-13 C]pyruvate and [1-13 C]lactate in the MRS images and between [12 C] and [1-13 C]lactate in the MS images were determined by means of Pearson correlation coefficients. RESULTS: [1-13 C]lactate images generated by MS imaging were significantly correlated with the corresponding MRS images. The correlation coefficient between [1-13 C]lactate and [1-13 C]pyruvate in the MRS images was higher than between [1-13 C]lactate and [12 C]lactate in the MS images. CONCLUSION: The inhomogeneous distribution of labeled lactate observed in the MRS images was confirmed by MS imaging of the corresponding tumor sections. The images acquired using both techniques show that the rate of 13 C label exchange between the injected pyruvate and endogenous tumor lactate pool is more correlated with the rate of pyruvate delivery to the tumor cells and is less affected by the endogenous lactate concentration.

Characterization of an Aggregated Three-Dimensional Cell Culture Model by Multimodal Mass Spectrometry Imaging.

Mass spectrometry imaging (MSI) is an established analytical tool capable of defining and understanding complex tissues by determining the spatial distribution of biological molecules. Three-dimensional (3D) cell culture models mimic the pathophysiological environment of in vivo tumors and are rapidly emerging as a valuable research tool. Here, multimodal MSI techniques were employed to characterize a novel aggregated 3D lung adenocarcinoma model, developed by the group to mimic the in vivo tissue. Regions of tumor heterogeneity and the hypoxic microenvironment were observed based on the spatial distribution of a variety of endogenous molecules. Desorption electrospray ionization (DESI)-MSI defined regions of a hypoxic core and a proliferative outer layer from metabolite distribution. Targeted metabolites (e.g., lactate, glutamine, and citrate) were mapped to pathways of glycolysis and the TCA cycle demonstrating tumor metabolic behavior. The first application of imaging mass cytometry (IMC) with 3D cell culture enabled single-cell phenotyping at 1 µm spatial resolution. Protein markers of proliferation (Ki-67) and hypoxia (glucose transporter 1) defined metabolic signaling in the aggregoid model, which complemented the metabolite data. Laser ablation inductively coupled plasma (LA-ICP)-MSI analysis localized endogenous elements including magnesium and copper, further differentiating the hypoxia gradient and validating the protein expression. Obtaining a large amount of molecular information on a complementary nature enabled an in-depth understanding of the biological processes within the novel tumor model. Combining powerful imaging techniques to characterize the aggregated 3D culture highlighted a future methodology with potential applications in cancer research and drug development.