No-Regret Learning in Two-Echelon Supply Chain with Unknown Demand Distribution

Supply chain management (SCM) has been recognized as an important discipline with applications to many industries, where the two-echelon stochastic inventory model, involving one downstream retailer and one upstream supplier, plays a fundamental role for developing firms' SCM strategies. In this work, we aim at designing online learning algorithms for this problem with an unknown demand distribution, which brings distinct features as compared to classic online optimization problems. Specifically, we consider the two-echelon supply chain model introduced in [Cachon and Zipkin, 1999] under two different settings: the centralized setting, where a planner decides both agents' strategy simultaneously, and the decentralized setting, where two agents decide their strategy independently and selfishly. We design algorithms that achieve favorable guarantees for both regret and convergence to the optimal inventory decision in both settings, and additionally for individual regret in the decentralized setting. Our algorithms are based on Online Gradient Descent and Online Newton Step, together with several new ingredients specifically designed for our problem. We also implement our algorithms and show their empirical effectiveness

Dual-Drug Loaded Separable Microneedles for Efficient Rheumatoid Arthritis Therapy

Although the inhibitors of the interleukin-6 receptor (IL-6R) and tumor necrosis factor-α (TNF-α) have achieved a certain success in the clinical treatment of rheumatoid arthritis (RA), great effort should be made to overcome side effects and to improve patient compliance. The present research aimed to address these problems by the co-delivery of tocilizumab (TCZ)—an inhibitor of IL-6R—and an aptamer Apt1-67, which specifically inhibits TNF receptor 1 via separable microneedles (MN). MN were featured with a sustained release of TCZ from needle tips and a rapid release of Apt1-67 from needle bodies by using methacrylate groups grafted hyaluronic acid as the fillings of needle tips and polyvinyl alcohol/polyvinyl pyrrolidone as the fillings of needle bodies. Our results demonstrated that TCZ and Apt1-67 were distributed in MN as expected, and they could be released to the surroundings in the skin. In vivo studies revealed that combined medication via MN (TCZ/Apt1-67@MN) was superior to MN loaded with a single drug. Compared with subcutaneous injection, TCZ/Apt1-67@MN was of great advantage in inhibiting bone erosion and alleviating symptoms of CIA mice. This study not only provides a novel approach for combined medication with different release properties but also supplies a strategy for improving drug efficacy

Discovery of benzisoxazoles as potent inhibitors of chaperone heat shock protein 90.

Heat shock protein 90 (Hsp90) is a molecular chaperone that is responsible for activating many signaling proteins and is a promising target in tumor biology. We have identified small-molecule benzisoxazole derivatives as Hsp90 inhibitors. Crystallographic studies show that these compounds bind in the ATP binding pocket interacting with the Asp93. Structure based optimization led to the identification of potent analogues, such as 13, with good biochemical profiles