Optimal sampling policies in a centralised supply chain with demands affected by product quality

We address a quality control problem frequently encountered in multi-stage pharmaceutical supply chains transporting drugs from a producer to a wholesaler and eventually to retailers (pharmacies). Depending on the transportation modes and storage methods used, the stages may expose the drugs to hostile environments, such as extreme temperatures, which may impact the quality. To study the performance of such a supply chain, we incorporate the effect of quality on demand with the Neyman–Pearson statistical framework. We show that in a centralised supply chain the optimal inspection strategies for the parties depend on parameters, which signify the relative importance of price and the impact of quality on demand. In particular, we find that the ratio between the customer demand under perfect product quality and the customer sensitivity to quality plays a critical role in selecting optimal inspection policies.supply chain management; SCM; quality control; sampling strategy; game theory; optimal sampling policies; product quality; pharmaceutical supply chains; centralised supply chains; inspection strategies.

Systematic proximal mapping of the classical RAD51 paralogs unravel functionally and clinically relevant interactors for genome stability.

Homologous recombination (HR) plays an essential role in the maintenance of genome stability by promoting the repair of cytotoxic DNA double strand breaks (DSBs). More recently, the HR pathway has emerged as a core component of the response to replication stress, in part by protecting stalled replication forks from nucleolytic degradation. In that regard, the mammalian RAD51 paralogs (RAD51B, RAD51C, RAD51D, XRCC2, and XRCC3) have been involved in both HR-mediated DNA repair and collapsed replication fork resolution. Still, it remains largely obscure how they participate in both processes, thereby maintaining genome stability and preventing cancer development. To gain better insight into their contribution in cellulo, we mapped the proximal interactome of the classical RAD51 paralogs using the BioID approach. Aside from identifying the well-established BCDX2 and CX3 sub-complexes, the spliceosome machinery emerged as an integral component of our proximal mapping, suggesting a crosstalk between this pathway and the RAD51 paralogs. Furthermore, we noticed that factors involved RNA metabolic pathways are significantly modulated within the BioID of the classical RAD51 paralogs upon exposure to hydroxyurea (HU), pointing towards a direct contribution of RNA processing during replication stress. Importantly, several members of these pathways have prognostic potential in breast cancer (BC), where their RNA expression correlates with poorer patient outcome. Collectively, this study uncovers novel functionally relevant partners of the different RAD51 paralogs in the maintenance of genome stability that could be used as biomarkers for the prognosis of BC