Glycosylation reactions mainly catalyzed by glycosyltransferases (Gts) occur almost everywhere in the biosphere, and always play crucial roles in vital processes. In order to understand the full potential of Gts, the chemical and structural glycosylation mechanisms are systematically summarized in this review, including some new outlooks in inverting/retaining mechanisms and the overview of GT-C superfamily proteins as a novel Gt fold. Some special features of glycosylation and the evolutionary studies on Gts are also discussed to help us better understand the function and application potential of Gts. Natural product (NP) glycosylation and related Gts which play important roles in new drug development are emphasized in this paper. The recent advances in the glycosylation pattern (particularly the rare C- and S-glycosylation), reversibility, iterative catalysis and protein auxiliary of NP Gts are all summed up comprehensively. This review also presents the application of NP Gts and associated studies on synthetic biology, which may further broaden the mind and bring wider application prospects.

Most teacher-student frameworks based on knowledge distillation (KD) depend on a strong congruent constraint on instance level. However, they usually ignore the correlation between multiple instances, which is also valuable for knowledge transfer. In this work, we propose a new framework named correlation congruence for knowledge distillation (CCKD), which transfers not only the instance-level information, but also the correlation between instances. Furthermore, a generalized kernel method based on Taylor series expansion is proposed to better capture the correlation between instances. Empirical experiments and ablation studies on image classification tasks (including CIFAR-100, ImageNet-1K) and metric learning tasks (including ReID and Face Recognition) show that the proposed CCKD substantially outperforms the original KD and achieves stateof-the-art accuracy compared with other SOTA KD-based methods. The CCKD can be easily deployed in the majority of the teacher-student framework such as KD and hintbased learning methods. Our code will be released, hoping to nourish our idea to other domains.

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