Tumor cells have an increased nutritional demand for amino acids (AAs) to satisfy their rapid proliferation. Positron-emitting nuclide labeled AAs are interesting probes and are of great importance ...for imaging tumors using positron emission tomography (PET). Carbon-11 and fluorine-18 labeled AAs include the 1-
C AAs, labeling alpha-C- AAs, the branched-chain of AAs and
-substituted carbon-11 labeled AAs. These tracers target protein synthesis or amino acid (AA) transport, and their uptake mechanism mainly involves AA transport. AA PET tracers have been widely used in clinical settings to image brain tumors, neuroendocrine tumors, prostate cancer, breast cancer, non-small cell lung cancer (NSCLC) and hepatocellular carcinoma. This review focuses on the fundamental concepts and the uptake mechanism of AAs, AA PET tracers and their clinical applications.
Stem cell-derived islet organoids constitute a promising treatment of type 1 diabetes. A major hurdle in the field is the lack of appropriate
method to determine graft outcome. Here, we investigate ...the feasibility of
tracking of transplanted stem cell-derived islet organoids using magnetic particle imaging (MPI) in a mouse model. Human induced pluripotent stem cells-L1 were differentiated to islet organoids and labeled with superparamagnetic iron oxide nanoparticles. The phantoms comprising of different numbers of labeled islet organoids were imaged using an MPI system. Labeled islet organoids were transplanted into NOD/scid mice under the left kidney capsule and were then scanned using 3D MPI at 1, 7, and 28 days post transplantation. Quantitative assessment of the islet organoids was performed using the
++ algorithm analysis of 3D MPI. The left kidney was collected and processed for immunofluorescence staining of C-peptide and dextran. Islet organoids expressed islet cell markers including insulin and glucagon. Image analysis of labeled islet organoids phantoms revealed a direct linear correlation between the iron content and the number of islet organoids. The
++ algorithm showed that during the course of the study the signal from labeled islet organoids under the left kidney capsule decreased. Immunofluorescence staining of the kidney sections showed the presence of islet organoid grafts as confirmed by double staining for dextran and C-peptide. This study demonstrates that MPI with machine learning algorithm analysis can monitor islet organoids grafts labeled with super-paramagnetic iron oxide nanoparticles and provide quantitative information of their presence
.
Objective:
To investigate the value of 2-(3-18Ffluoropropyl)-2-methyl-malonic acid (18FML-8) positron emission tomography (PET) imaging of rat pulmonary fibrosis.
Methods:
Male Sprague-Dawley rats ...were divided into 2 groups, including pulmonary fibrosis model group and control group. The rat model was established by an intratracheal instillation of bleomycin (BLM). Control rats were treated with saline. Positron emission tomography/computed tomography (CT) with 18FML-8 or 18F-fluorodeoxyglucose (18FFDG) was performed on 2 groups. After PET/CT imaging, lung tissues were collected for histologic examination. Data were analyzed and comparisons between 2 groups were performed using Student t test.
Results:
Bleomycin-treated rats showed a higher lung uptake of 18FML-8 than control rats (P < .05). In BLM-treated rats, the lung to muscle relative uptake ratio of 18FML-8 was also higher than that of 18FFDG (P < .05). Pathological examination showed overproliferation of fibroblasts and deposition of collagen in lungs from BLM-treated rats. Compared to control rats, BLM-treated rats had higher lung hydroxyproline content (P < .05). Immunofluorescence staining indicated more apoptotic cells in BLM-treated rats than those in control rats. Moreover, the apoptosis rate of lung tissues obtained from BLM-treated rats was higher than that from control rats (P < .05).
Conclusions:
2-(3-18Ffluoropropyl)-2-methyl-malonic acid PET/CT could be used for noninvasive diagnosis of pulmonary fibrosis in a rat model.
Although significant advances have been made in understanding the mechanisms of macrophage response to
infection, the molecular details are still elusive. Identification of the essential genes and ...biological processes of macrophages that are specifically changed at different durations of
exposure is of great clinical significance.
We aimed to identify the significantly changed genes and biological processes of
-exposed macrophages. We systematically analyzed the macrophage gene expression profile GSE 13670 database with 8 h, 24 h or 48 h
infection. The results were further confirmed by western blot and quantitative polymerase chain reaction (qPCR) analyses.
After 8 h of
infection, the expression of 624 genes was significantly changed. Six hundred thirteen differentially expressed genes (DEGs) were identified after 24 h of
infection. Two hundred fifty-three genes were significantly changed after 48 h of
infection. STAT1 was consistently up-regulated in these three treatments.
,
,
,
,
,
and
were only identified in the 8 h or 24 h
infection groups.
and
were for the first time identified as potential essential genes in
infection of macrophages. In the Gene Ontology (GO) term analysis, the defense response was shown to be the most significantly changed biological process among all processes; KEGG pathway analysis identified the JAK-STAT signaling pathway involved in early infection.
Our systematic analysis identified unique gene expression profiles and specifically changed biological processes of the macrophage response to different
exposure times.
Islet transplantation has great potential as a cure for type 1 diabetes. At present; the lack of a clinically validated non-invasive imaging method to track islet grafts limits the success of this ...treatment. Some major clinical imaging modalities and various molecular probes, which have been studied for non-invasive monitoring of transplanted islets, could potentially fulfill the goal of understanding pathophysiology of the functional status and viability of the islet grafts. In this current review, we summarize the recent clinical studies of a variety of imaging modalities and molecular probes for non-invasive imaging of transplanted beta cell mass. This review also includes discussions on in vivo detection of endogenous beta cell mass using clinical imaging modalities and various molecular probes, which will be useful for longitudinally detecting the status of islet transplantation in Type 1 diabetic patients. For the conclusion and perspectives, we highlight the applications of multimodality and novel imaging methods in islet transplantation.
Background. Transplantation of human-induced pluripotent stem cell (hiPSC)-derived islet organoids is a promising cell replacement therapy for type 1 diabetes (T1D). It is important to improve the ...efficacy of islet organoids transplantation by identifying new transplantation sites with high vascularization and sufficient accommodation to support graft survival with a high capacity for oxygen delivery. Methods. A human-induced pluripotent stem cell line (hiPSCs-L1) was generated constitutively expressing luciferase. Luciferase-expressing hiPSCs were differentiated into islet organoids. The islet organoids were transplanted into the scapular brown adipose tissue (BAT) of nonobese diabetic/severe combined immunodeficiency disease (NOD/SCID) mice as the BAT group and under the left kidney capsule (KC) of NOD/SCID mice as a control group, respectively. Bioluminescence imaging (BLI) of the organoid grafts was performed on days 1, 7, 14, 28, 35, 42, 49, 56, and 63 posttransplantation. Results. BLI signals were detected in all recipients, including both the BAT and control groups. The BLI signal gradually decreased in both BAT and KC groups. However, the graft BLI signal intensity under the left KC decreased substantially faster than that of the BAT. Furthermore, our data show that islet organoids transplanted into streptozotocin-induced diabetic mice restored normoglycemia. Positron emission tomography/MRI verified that the islet organoids were transplanted at the intended location in these diabetic mice. Immunofluorescence staining revealed the presence of functional organoid grafts, as confirmed by insulin and glucagon staining. Conclusions. Our results demonstrate that BAT is a potentially desirable site for islet organoid transplantation for T1D therapy.
Current methods of in vivo imaging islet cell transplants for diabetes using magnetic resonance imaging (MRI) are limited by their low sensitivity. Simultaneous positron emission tomography (PET)/MRI ...has greater sensitivity and ability to visualize cell metabolism. However, this dual-modality tool currently faces two major challenges for monitoring cells. Primarily, the dynamic conditions of PET such as signal decay and spatiotemporal change in radioactivity prevent accurate quantification of the transplanted cell number. In addition, selection bias from different radiologists renders human error in segmentation. This calls for the development of artificial intelligence algorithms for the automated analysis of PET/MRI of cell transplantations. Here, we combined K-means++ for segmentation with a convolutional neural network to predict radioactivity in cell-transplanted mouse models. This study provides a tool combining machine learning with a deep learning algorithm for monitoring islet cell transplantation through PET/MRI. It also unlocks a dynamic approach to automated segmentation and quantification of radioactivity in PET/MRI.
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•Algorithms were developed for the analysis of PET/MRI of transplanted cell•Three algorithms were trained and tested with in vitro and in vivo datasets•3D CNN predicts actual transplanted cell numbers in cell-transplanted mouse models•We provide a novel tool for monitoring islet transplantation through PET/MRI
Cell biology; Artificial intelligence applications
Human islet transplantation is a promising therapy to restore normoglycemia for type 1 diabetes (T1D). Despite recent advances, human islet transplantation remains suboptimal due to significant islet ...graft loss after transplantation. Various immunological and nonimmunological factors contribute to this loss therefore signifying a need for strategies and approaches for visualizing and monitoring transplanted human islet grafts. One such imaging approach is magnetic particle imaging (MPI), an emerging imaging modality that detects the magnetization of iron oxide nanoparticles. MPI is known for its specificity due to its high image contrast and sensitivity. MPI through its noninvasive nature provides the means for monitoring transplanted human islets in real time. Here we summarize an approach to track transplanted human islets using MPI. We label human islet from donors with dextran-coated ferucarbotran iron oxide nanoparticles, transplant the labeled human islet into under the left kidney capsule, and image graft cells using an MPI scanner. We engineer a K-means++, clustering-based unsupervised machine learning algorithm for standardized image segmentation and iron quantification of the MPI, which solves problems with selection bias and indiscriminate signal boundary that accompanies this newer imaging modality. In this chapter, we summarize the methods of this emerging imaging modality of MPI in conjunction with unsupervised machine learning to monitor and visualize islets after transplantation.
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