A novel in vivo Cerenkov luminescence image‐guided surgery on primary and metastatic colorectal cancer

Intraoperative Cerenkov luminescence imaging (CLI) can effectively improve the performance of tumor surgery. Nevertheless, the existing approaches are still unsatisfying to the clinical demands of open surgery. This study develops a novel intraoperative in vivo CLI approach to investigate the potential and value of Cerenkov luminescence (CL) image‐guided surgery. A system characterized with high sensitivity (19.61 kBq mL^{?1 18}F‐FDG) and desirable spatial resolution (88.34 μm) is developed. CL image‐guided surgery is performed on colorectal cancer (CRC) models of mice and swine. Tumor surgery is guided by the static CL images, and the resection quality is evaluated quantitatively and contrasted with other imaging modalities exemplified by bioluminescence imaging (BLI). The in vivo results demonstrated the effectiveness of the proposed intraoperative CLI approach for removing primary and metastatic CRC. Safety of performing in vivo CL image‐guided surgery is verified as well through radiation measurements of related staffs. Overall, the developed intraoperative in vivo CLI approach can efficiently improve the cancer treatment.     

Subnetwork identification and chemical modulation for neural regeneration: A study combining network guided forest and heat diffusion model

Background: The induction of neural regeneration is vital to the repair of spinal cord injury (SCI). While compared with peripheral nervous system (PNS), the regenerative capacity of the central nervous system (CNS) is extremely limited. This indicates that modulating the molecular pathways underlying PNS repair may lead to the discovery of potential treatment for CNS injury.Methods: Based on the gene expression profiles of dorsal root ganglion (DRG) after a sciatic nerve injury, we utilized network guided forest (NGF) to rank genes in terms of their capacity of distinguishing injured DRG from sham-operated controls. Gene importance scores deriving from NGF were used as initial heat in a heat diffusion model (HotNet2) to infer the subnetworks underlying neural regeneration in the DRG. After potential regulators of the subnetworks were found through Connectivity Map (cMap), candidate compounds were experimentally evaluated for their capacity to regenerate the damaged neurons.Results: Gene ontology analysis of the subnetworks revealed ubiquinone biosynthetic process is crucial for neural regeneration. Moreover, almost half of the genes in these subnetworks are found to be related to neural regeneration via text mining. After screening compounds that are likely to modulate gene expressions of the subnetworks, three compounds were selected for the experiment. Of them, trichostatin A, a histone deacetylase inhibitor, was validated to enhance neurite outgrowth in vivo via an optic nerve crush mouse model.Conclusions: Our study identified subnetworks underlying neural regeneration, and validated a compound can promote neurite outgrowth by modulating these subnetworks. This work also suggests an alternative approach for drug repositioning that can be easily extended to other disease phenotypes.