It has been reported that TNFR2 is involved in regulatory T cell induction and myeloid-derived suppressor cell (MDSC) accumulation, two kinds of immunosuppressive cells contributing to tumor immune evasion. Because transmembrane TNF-α (tmTNF-α) is the primary ligand for TNFR2, we hypothesized that tmTNF-α is mainly responsible for the activation of MDSCs. Indeed, we found that tmTNF-α, rather than secretory TNF-α (sTNF-α), activated MDSCs with enhanced suppressive activities, including upregulating arginase-1 and inducible NO synthase transcription, promoting secretion of NO, reactive oxygen species, IL-10, and TGF-β, and enhancing inhibition of lymphocyte proliferation. This effect of tmTNF-α was mediated by TNFR2, as TNFR2 deficiency significantly impaired tmTNF-α–induced release of IL-10 and NO and inhibition of T cell proliferation by MDSC supernatant. Furthermore, tmTNF-α caused p38 phosphorylation and NF-κB activation, whereas inhibition of NF-κB or p38 with an inhibitor pyrrolidine dithiocarbamate or SB203580 abrogated tmTNF-α–mediated increased suppression of lymphocyte proliferation by MDSCs. Consistently, our in vivo study showed that ectopic expression of uncleavable tmTNF-α mutant by 4T1 cells significantly promoted tumor progression and angiogenesis, accompanied with more accumulation of MDSCs and regulatory T cells in the tumor site, increased production of NO, IL-10, and TGF-β, as well as poor lymphocyte infiltration. In contrast, enforced expression of sTNF-α mutant by 4T1 cells that only released sTNF-α without expression of surface tmTNF-α markedly reduced MDSC accumulation and induced more lymphocyte infiltration instead, showing obvious tumor regression. Our data suggest that tmTNF-α acts as a potent activator of MDSCs via TNFR2 and reveals another novel immunosuppressive effect of this membrane molecule that promotes tumor immune escape.
Key Points
tmTNF-α expressed on LSC and leukemia cells correlates with poor risk stratification and adverse clinical parameters. Targeting tmTNF-α by monoclonal antibody eradicates LSC and blasts, preventing leukemia regeneration in secondary transplant in NOD-SCID mice.
Wrinkles play an important role in the face-based analysis. They have been widely used in applications, such as facial retouching, facial expression recognition, and face age estimation. Although a few techniques for a wrinkle analysis have been explored in the literature, poor detection limits the accuracy and reliability of wrinkle segmentation. Therefore, an automated wrinkle detection method is crucial to maintain consistency and reduce human error. In this paper, we propose Hessian line tracking (HLT) to overcome the detection problem. HLT is composed of Hessian seeding and directional line tracking. It is an extension of a Hessian filter; however, it significantly increases the accuracy of wrinkle localization when compared with existing methods. In the experimental phase, three coders were instructed to annotate wrinkles manually. To assess the manual annotation, both intrareliability and interreliability were measured, with an accuracy of 94% or above. The experimental results show that the proposed method is capable of tracking hidden pixels; thus, it increases connectivity of detection between wrinkles, allowing some fine wrinkles to be detected. In comparison to the state-of-the-art methods such as the Cula Method, Frangi Filter, and Hybrid Hessian Filter, the proposed HLT yields better results, with an accuracy of 84%. This paper demonstrates that the HLT is a remarkably strong detector of forehead wrinkles in 2-D images.INDEX TERMS Wrinkle detection, Hessian filter, line tracking, Bosphorus dataset, Jaccard similarity index.
We address the problem of tracking in vivo muscle fascicle shape and length changes using ultrasound video sequences. Quantifying fascicle behaviour is required to improve understanding of the functional significance of a muscle's geometric properties. Ultrasound imaging provides a non-invasive means of capturing information on fascicle behaviour during dynamic movements, to date however computational approaches to assess such images are limited. Our approach to the problem is novel because we permit fascicles to take up non-linear shape configurations. We achieve this using a Bayesian tracking framework that is: i) robust, conditioning shape estimates on the entire history of image observations; and ii) flexible, enforcing only a very weak Gaussian Process shape prior that requires fascicles to be locally smooth. The method allows us to track and quantify fascicle behaviour in vivo during a range of movements, providing insight into dynamic changes in muscle geometric properties which may be linked to patterns of activation and intramuscular forces and pressures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.