Synthesis of 4-Deoxy-4-Fluoro-d-Sedoheptulose: A Promising New Sugar to Apply the Principle of Metabolic Trapping.

Fluorinated carbohydrates are important tools for understanding the deregulation of metabolic fluxes and pathways. Fluorinating specific positions within the sugar scaffold can lead to enhanced metabolic stability and subsequent metabolic trapping in cells. This principle has, however, never been applied to study the metabolism of the rare sugars of the pentose phosphate pathway (PPP). In this study, two fluorinated derivatives of d-sedoheptulose were designed and synthesized: 4-deoxy-4-fluoro-d-sedoheptulose (4DFS) and 3-deoxy-3-fluoro-d-sedoheptulose (3DFS). Both sugars are taken up by human fibroblasts but only 4DFS is phosphorylated. Fluorination of d-sedoheptulose at C-4 effectively halts the enzymatic degradation by transaldolase and transketolase. 4DFS thus has a high potential as a new PPP imaging probe based on the principle of metabolic trapping. Therefore, the synthesis of potential radiolabeling precursors for 4DFS for future radiofluorinations with fluorine-18 is presented.

Hyperspectral Imaging as a Tool for Viability Assessment During Normothermic Machine Perfusion of Human Livers: A Proof of Concept Pilot Study.

Normothermic machine perfusion (NMP) allows for ex vivo viability and functional assessment prior to liver transplantation (LT). Hyperspectral imaging represents a suitable, non-invasive method to evaluate tissue morphology and organ perfusion during NMP. Liver allografts were subjected to NMP prior to LT. Serial image acquisition of oxygen saturation levels (StO2), organ hemoglobin (THI), near-infrared perfusion (NIR) and tissue water indices (TWI) through hyperspectral imaging was performed during static cold storage, at 1h, 6h, 12h and at the end of NMP. The readouts were correlated with perfusate parameters at equivalent time points. Twenty-one deceased donor livers were included in the study. Seven (33.0%) were discarded due to poor organ function during NMP. StO2 (p < 0.001), THI (p < 0.001) and NIR (p = 0.002) significantly augmented, from static cold storage (pre-NMP) to NMP end, while TWI dropped (p = 0.005) during the observational period. At 12-24h, a significantly higher hemoglobin concentration (THI) in the superficial tissue layers was seen in discarded, compared to transplanted livers (p = 0.036). Lactate values at 12h NMP correlated negatively with NIR perfusion index between 12 and 24h NMP and with the delta NIR perfusion index between 1 and 24h (rs = -0.883, p = 0.008 for both). Furthermore, NIR and TWI correlated with lactate clearance and pH. This study provides first evidence of feasibility of hyperspectral imaging as a potentially helpful contact-free organ viability assessment tool during liver NMP.

Prediction of Biliary Complications After Human Liver Transplantation Using Hyperspectral Imaging and Convolutional Neural Networks: A Proof-of-concept Study.

BACKGROUND: Biliary complications (BCs) negatively impact the outcome after liver transplantation. We herein tested whether hyperspectral imaging (HSI) generated data from bile ducts (BD) on reperfusion and machine learning techniques for data readout may serve as a novel approach for predicting BC. METHODS: Tissue-specific data from 136 HSI liver images were integrated into a convolutional neural network (CNN). Fourteen patients undergoing liver transplantation after normothermic machine preservation served as a validation cohort. Assessment of oxygen saturation, organ hemoglobin, and tissue water levels through HSI was performed after completing the biliary anastomosis. Resected BD segments were analyzed by immunohistochemistry and real-time confocal microscopy. RESULTS: Immunohistochemistry and real-time confocal microscopy revealed mild (grade I: 1%-40%) BD damage in 8 patients and moderate (grade II: 40%-80%) injury in 1 patient. Donor and recipient data alone had no predictive capacity toward BC. Deep learning-based analysis of HSI data resulted in >90% accuracy of automated detection of BD. The CNN-based analysis yielded a correct classification in 72% and 69% for BC/no BC. The combination of HSI with donor and recipient factors showed 94% accuracy in predicting BC. CONCLUSIONS: Deep learning-based modeling using CNN of HSI-based tissue property data represents a noninvasive technique for predicting postoperative BC.

Novel, Innovative Models to Study Ischemia/Reperfusion-Related Redox Damage in Organ Transplantation.

The implementation of ex vivo organ machine perfusion (MP) into clinical routine undoubtedly helped to increase the donor pool. It enables not just organ assessment, but potentially regeneration and treatment of marginal organs in the future. During organ procurement, redox-stress triggered ischemia-reperfusion injury (IRI) is inevitable, which in addition to pre-existing damage negatively affects such organs. Ex vivo MP enables to study IRI-associated tissue damage and its underlying mechanisms in a near to physiological setting. However, research using whole organs is limited and associated with high costs. Here, in vitro models well suited for early stage research or for studying particular disease mechanisms come into play. While cell lines convince with simplicity, they do not exert all organ-specific functions. Tissue slice cultures retain the three-dimensional anatomical architecture and cells remain within their naïve tissue-matrix configuration. Organoids may provide an even closer modelling of physiologic organ function and spatial orientation. In this review, we discuss the role of oxidative stress during ex vivo MP and the suitability of currently available in vitro models to further study the underlying mechanisms and to pretest potential treatment strategies.

Hyperspectral Imaging and Machine Perfusion in Solid Organ Transplantation: Clinical Potentials of Combining Two Novel Technologies.

Organ transplantation survival rates have continued to improve over the last decades, mostly due to reduction of mortality early after transplantation. The advancement of the field is facilitating a liberalization of the access to organ transplantation with more patients with higher risk profile being added to the waiting list. At the same time, the persisting organ shortage fosters strategies to rescue organs of marginal donors. In this regard, hypothermic and normothermic machine perfusion are recognized as one of the most important developments in the modern era. Owing to these developments, novel non-invasive tools for the assessment of organ quality are on the horizon. Hyperspectral imaging represents a potentially suitable method capable of evaluating tissue morphology and organ perfusion prior to transplantation. Considering the changing environment, we here discuss the hypothetical combination of organ machine perfusion and hyperspectral imaging as a prospective feasibility concept in organ transplantation.

The PI3K pathway preserves metabolic health through MARCO-dependent lipid uptake by adipose tissue macrophages.

Adipose tissue macrophages (ATMs) display tremendous heterogeneity depending on signals in their local microenvironment and contribute to the pathogenesis of obesity. The phosphoinositide 3-kinase (PI3K) signalling pathway, antagonized by the phosphatase and tensin homologue (PTEN), is important for metabolic responses to obesity. We hypothesized that fluctuations in macrophage-intrinsic PI3K activity via PTEN could alter the trajectory of metabolic disease by driving distinct ATM populations. Using mice harbouring macrophage-specific PTEN deletion or bone marrow chimeras carrying additional PTEN copies, we demonstrate that sustained PI3K activity in macrophages preserves metabolic health in obesity by preventing lipotoxicity. Myeloid PI3K signalling promotes a beneficial ATM population characterized by lipid uptake, catabolism and high expression of the scavenger macrophage receptor with collagenous structure (MARCO). Dual MARCO and myeloid PTEN deficiencies prevent the generation of lipid-buffering ATMs, reversing the beneficial actions of elevated myeloid PI3K activity in metabolic disease. Thus, macrophage-intrinsic PI3K signalling boosts metabolic health by driving ATM programmes associated with MARCO-dependent lipid uptake.

PI3K activity in dendritic cells exerts paradoxical effects during autoimmune inflammation.

The peripheral activation of autoreactive T cells and subsequent central nervous system (CNS) immune cell infiltration are key events relevant for experimental autoimmune encephalomyelitis (EAE), a commonly employed multiple sclerosis (MS) model, influenced by TH1 and TH17 mediated immunity. The phosphoinositide-3-kinase (PI3K)-AKT kinase pathway modulates outcome during EAE, with direct actions of PI3K on adaptive immunity implicated in deleterious and effects on antigen presenting cells involved in beneficial responses during EAE. Here, by genetically deleting the regulatory subunit of Class Ia PI3K, p85α, in selective myeloid cells, we aimed to resolve the impact of PI3K in EAE. While genetically deleting PI3K in LysM expressing cells exerted unremarkable effects, attenuating PI3K function in CD11c+ dendritic cells (DCs), promoted secretion of pathogenic EAE promoting cytokines, particularly skewing TH1 and TH17 immunity, while notably, improving health in EAE. Neutralizing IFN-γ activity using blocking antibodies revealed a prolonged TH1 response was critical for the decreased disease of these animals. Thus, PI3K-AKT signaling in DCs acts in a paradoxical manner. While attenuating EAE associated TH1 and TH17 responses, it impairs health during autoimmune inflammation.