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Mol Pharm ; 2019 Nov 12.
Artigo em Inglês | MEDLINE | ID: mdl-31670970


Similar to glycolysis, glutaminolysis acts as a vital energy source in tumor cells, providing building blocks for the metabolic needs of tumor cells. To capture glutaminolysis in tumors, 18F-(2S,4R)4-fluoroglutamine ([18F]FGln) and 18F-fluoroboronoglutamine ([18F]FBQ) have been successfully developed for positron emission tomography (PET) imaging, but these two molecules lack stability, resulting in undesired yet significant bone uptake. In this study, we found that [18F]FBQ-C2 is a stable Gln PET tracer by adding two more methylene groups to the side chain of [18F]FBQ. [18F]FBQ-C2 was synthesized with a good radiochemical yield of 35% and over 98% radiochemical purity. [18F]FBQ-C2 showed extreme stability in vitro, and no defluorination was observed after 2 h in phosphate buffered saline at 37 °C. The competitive inhibition assay results indicated that [18F]FBQ-C2 enters cells via the system ASC and N, similar to natural glutamine, and can be transported by tumor-overexpressed ASCT2. PET imaging and biodistribution results indicated that [18F]FBQ-C2 is stable in vivo with low bone uptake (0.81 ± 0.20% ID/g) and can be cleared rapidly from most tissues. Dynamic scan and pharmacokinetic studies using BGC823-xenograft-bearing mice revealed that [18F]FBQ-C2 accumulates specifically in tumors, with a longer half-life (101.18 ± 6.50 min) in tumor tissues than in other tissues (52.70 ± 12.44 min in muscle). Biodistribution exhibits a high tumor-to-normal tissue ratio (4.8 ± 1.7 for the muscle, 2.5 ± 1.0 for the stomach, 2.2 ± 0.9 for the liver, and 17.8 ± 8.4 for the brain). In conclusion, [18F]FBQ-C2 can be used to perform high-contrast Gln imaging of tumors and can serve as a PET tracer for clinical research.

J Opt Soc Am A Opt Image Sci Vis ; 36(9): 1566-1572, 2019 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-31503851


Sparse representation is commonly used in correction models to reduce thermal radiation effects. If the correction problem is restricted to a sparse representation problem, residual aero-optic thermal radiation effects will appear in the corrected results. To accurately estimate the thermal radiation bias field, the low-frequency information of the thermal radiation bias field is explored. We propose a correction model to integrate the low-frequency constraint on the thermal bias field and gradient sparse constraint on the latent clear image. A split Bregman alternating iterative algorithm is used to solve the minimization problem of the correction model. The experimental results show that the proposed method can effectively remove thermal radiation effects and greatly improve image quality for infrared focal plane detection.