The adaptor protein CARD9 links detection of fungi by surface receptors to the activation of the NF-κB pathway. Mice deficient in CARD9 exhibit dysbiosis and are more susceptible to colitis. Here we examined the impact of Card9 deficiency in the development of colitis-associated colon cancer (CAC). Treatment of Card9 mice with AOM-DSS resulted in increased tumor loads as compared to WT mice and in the accumulation of myeloid-derived suppressor cells (MDSCs) in tumor tissue. The impaired fungicidal functions of Card9 macrophages led to increased fungal loads and variation in the overall composition of the intestinal mycobiota, with a notable increase in C. tropicalis. Bone marrow cells incubated with C. tropicalis exhibited MDSC features and suppressive functions. Fluconazole treatment suppressed CAC in Card9 mice and was associated with decreased MDSC accumulation. The frequency of MDSCs in tumor tissues of colon cancer patients correlated positively with fungal burden, pointing to the relevance of this regulatory axis in human disease.

In this study, a novel Al 18 F-NOTA-FAPI probe was developed for fibroblast activation protein (FAP) targeted tumour imaging, which was available to achieve curie level radioactivity by automatic synthesizer. The tumour detection efficacy of Al 18 F-NOTA-FAPI was further validated both in preclinical and clinical translational studies. MethodsThe radiolabeling procedure of Al 18 F-NOTA-FAPI was optimized. Cell uptake and competitive binding assay were completed with U87MG and A549 cell lines, to evaluate the affinity and specificity of Al 18 F-NOTA-FAPI probe. The biodistribution, pharmacokinetics, radiation dosimetry and tumour imaging efficacy of Al 18 F-NOTA-FAPI probe were researched with healthy Kunming (KM) and/or U87MG model mice.After the approval of ethical committee, Al 18 F-NOTA-FAPI probe was translated into clinical for the PET/CT imaging of first 10 cancer patients. ResultsThe radiolabeling yield of Al 18 F-NOTA-FAPI was 33.8 ± 3.2% through manually operation (n = 10), with the radiochemical purity over than 99% and the specific activity of 9.3-55.5 MBq/nmol. Whole body effective dose of Al 18 F-NOTA-FAPI was estimated to be 1.24E-02 mSv/MBq, lower than several other FAPI probes ( 68 Ga-FAPI-04, 68 Ga-FAPI-46 and 68 Ga-FAPI-74). In U87MG tumour bearing mice, Al 18 F-NOTA-FAPI showed good tumor detection efficacy from the results of micro PET/CT imaging and biodistribution studies. In organ biodistribution study of human patients, Al 18 F-NOTA-FAPI showed lower SUVmean than 2-[ 18 F]FDG in most organs, especially in liver (1.1 ± 0.2 vs. 2.0 ± 0.9), brain (0.1 ± 0.0 vs. 5.9 ± 1.3), and bone marrow (0.9 ± 0.1 vs. 1.7 ± 0.4). Meanwhile, Al 18 F-NOTA-FAPI do not show extensive bone uptakes, and was able to find out more tumour lesions than 2-[ 18 F]FDG in the PET/CT imaging of several patients. ConclusionAl 18 F-NOTA-FAPI probe was successfully fabricated and applied in fibroblast activation protein targeted tumour PET/CT imaging, which showed excellent imaging quality and tumour detection efficacy in U87MG tumour bearing mice as well as in human cancer patients.

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The transformation from traditional manufacturing to intelligent manufacturing intrigues the profound and lasting effect on the future manufacturing worldwide. Industry 4.0 was proposed for advancing manufacturing to realize short product life cycles and extreme mass customization in a cost‐efficient way. As the heart of Industry 4.0, smart factory integrates physical technologies and cyber technologies and makes the involved technologies more complex and precise in order to improve performance, quality, controllability, management, and transparency of manufacturing processes. So far, leading manufacturers have begun the journey toward implementing smart factory. However, most firms still lack insight into the challenges and resources for implementing smart factory. As such, this paper identifies the requirements and key challenges, investigates available new technologies, reviews existing studies that have been done for smart factory, and further provides guidance for manufacturers to implementing smart factory in the context of Industry 4.0.

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