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- Raccosta, L, et al.
(författare)
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The oxysterol-CXCR2 axis plays a key role in the recruitment of tumor-promoting neutrophils
- 2013
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Ingår i: The Journal of experimental medicine. - : Rockefeller University Press. - 1540-9538 .- 0022-1007. ; 210:9, s. 1711-1728
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Tidskriftsartikel (refereegranskat)abstract
- Tumor-infiltrating immune cells can be conditioned by molecules released within the microenvironment to thwart antitumor immune responses, thereby facilitating tumor growth. Among immune cells, neutrophils play an important protumorigenic role by favoring neoangiogenesis and/or by suppressing antitumor immune responses. Tumor-derived oxysterols have recently been shown to favor tumor growth by inhibiting dendritic cell migration toward lymphoid organs. We report that tumor-derived oxysterols recruit protumor neutrophils in a liver X receptor (LXR)–independent, CXCR2-dependent manner, thus favoring tumor growth by promoting neoangiogenesis and immunosuppression. We demonstrate that interfering with the oxysterol–CXCR2 axis delays tumor growth and prolongs the overall survival of tumor-bearing mice. These results identify an unanticipated protumor function of the oxysterol–CXCR2 axis and a possible target for cancer therapy.
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- Strong, Giles C, et al.
(författare)
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TomOpt: differential optimisation for task- and constraint-aware design of particle detectors in the context of muon tomography
- 2024
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Ingår i: Machine Learning. - : Institute of Physics (IOP). - 2632-2153. ; 5:3
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Tidskriftsartikel (refereegranskat)abstract
- We describe a software package, TomOpt, developed to optimise the geometrical layout and specifications of detectors designed for tomography by scattering of cosmic-ray muons. The software exploits differentiable programming for the modeling of muon interactions with detectors and scanned volumes, the inference of volume properties, and the optimisation cycle performing the loss minimisation. In doing so, we provide the first demonstration of end-to-end-differentiable and inference-aware optimisation of particle physics instruments. We study the performance of the software on a relevant benchmark scenario and discuss its potential applications. Our code is available on Github (Strong et al 2024 available at: https://github.com/GilesStrong/tomopt).
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