Polycomb group (PcG) proteins maintain cell identity by repressing gene expression during development. Surprisingly, emerging studies have recently reported that a number of PcG proteins directly activate gene expression during cell fate determination process. However, the mechanisms by which they direct gene activation in pluripotency remain poorly understood. Here, we show that Phc1, a subunit of canonical polycomb repressive complex 1 (cPRC1), can exert its function in pluripotency maintenance via a PRC1-independent activation of Nanog. Ablation of Phc1 reduces the expression of Nanog and overexpression of Nanog partially rescues impaired pluripotency caused by Phc1 depletion. We find that Phc1 interacts with Nanog and activates Nanog transcription by stabilizing the genome-wide chromatin interactions of the Nanog locus. This adds to the already known canonical function of PRC1 in pluripotency maintenance via a PRC1-dependent repression of differentiation genes. Overall, our study reveals a function of Phc1 to activate Nanog transcription through regulating chromatin architecture and proposes a paradigm for PcG proteins to maintain pluripotency.

With the rapid growth of express delivery industry, service failure has become an increasingly pressing issue. However, there is a lack of research on express service failure risk assessment within the Failure Mode and Effects Analysis (FMEA) framework. To address the research gap, we propose an improved FMEA approach based on integrating the uncertainty reasoning cloud model and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The cloud model describing randomness and fuzziness in uncertainty environment is adopted to achieve the transformation between the qualitative semantic evaluation of occurrence (O), severity (S), and detection (D) risk factors of FMEA and the quantitative instantiation and set up the comprehensive cloud of risk assessment matrix for express delivery service failure (EDSF). The TOPSIS method calculates and ranks the relative closeness coefficients of EDSF mode. Finally, the rationality and applicability of the proposed method are demonstrated by an empirical study for the express delivery service in China. It is found that among 18 express delivery service failure modes, six service failure modes with high risk are mainly located in the processing and delivery stages, while six service failures with the relatively low risk are involved in the picking-up and transportation stages. This study provides insight on how to explore the risk evaluation of express delivery service failure, and it helps express delivery firms to identify the key service failure points, develop the corresponding service remedy measures, reduce the loss from service failures, and improve the service quality.

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