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Interaction of a subduction zone with an oceanic plateau has implications for plate tectonics. However, the geodynamic processes and petrological responses to oceanic plateau–arc interactions remain enigmatic. The southwestern Mariana and Yap arcs have experienced interactions with the Caroline Plateau, which have affected the regional tectonism. In this study, tholeiitic basalts and metamorphosed volcanic rocks (i.e., greenstones) were recovered from the southwestern Mariana forearc. The protoliths of the metamorphosed volcanic rocks have geochemical affinities to low-silica boninites. These boninitic rocks have similar K–Ar and apatite U–Pb ages of ca. 24 Ma, which record the timing of collision between the southwestern Mariana arc and the Caroline Plateau. 40Ar/39Ar dating of plagioclase in the tholeiitic basalts dates post-collisional magmatism to ca. 18 Ma. The tholeiites have geochemical signatures of fore-arc basalts (e.g., low Ti/V ratios and light rare earth element-depleted patterns) and high Th/Yb ratios, which reflect a depleted mantle source with a subduction component inherited from a pre-collisional subduction event. We suggest that the southwestern Mariana arc is an intra-oceanic arc that underwent plateau–arc collisions. These plateau–arc interactions affected the tectonic and magmatic evolution of the southwestern Mariana arc and nearby western Pacific basins. 

Abstract This paper develops a New Keynesian model featuring financial intermediation, short- and long-term bonds, credit shocks, and scope for unconventional monetary policy. The log-linearized model reduces to four equations: Phillips and IS curves, as well as policy rules for the short-term interest rate and the central bank's long-bond portfolio (QE). Credit shocks and QE appear in both the IS and Phillips curves. In equilibrium, optimal monetary policy entails adjusting the short-term interest rate to offset natural rate shocks but using QE to offset credit market disruptions. Use of QE significantly mitigates the costs of a binding zero lower bound. 

Unraveling molecular regulatory networks underlying disease progression is critically important for understanding disease mechanisms and identifying drug targets. The existing methods for inferring gene regulatory networks (GRNs) rely mainly on time-course gene expression data. However, most available omics data from cross-sectional studies of cancer patients often lack sufficient temporal information, leading to a key challenge for GRN inference. Through quantifying the latent progression using random walks-based manifold distance, we propose a latent-temporal progression-based Bayesian method, PROB, for inferring GRNs from the cross-sectional transcriptomic data of tumor samples. The robustness of PROB to the measurement variabilities in the data is mathematically proved and numerically verified. Performance evaluation on real data indicates that PROB outperforms other methods in both pseudotime inference and GRN inference. Applications to bladder cancer and breast cancer demonstrate that our method is effective to identify key regulators of cancer progression or drug targets. The identified ACSS1 is experimentally validated to promote epithelial-to-mesenchymal transition of bladder cancer cells, and the predicted FOXM1-targets interactions are verified and are predictive of relapse in breast cancer. Our study suggests new effective ways to clinical transcriptomic data modeling for characterizing cancer progression and facilitates the translation of regulatory network-based approaches into precision medicine. 

Arabidopsis RESISTANCE TO POWDERY MILDEW 8.2 (RPW8.2) is specifically induced by the powdery mildew (PM) fungus (Golovinomyces cichoracearum) in the infected epidermal cells to activate immunity. However, the mechanism of RPW8.2-induction is not well understood. Here, we identify a G. cichoracearum effector that interacts with RPW8.2, named Gc-RPW8.2 interacting protein 1 (GcR8IP1), by a yeast two-hybrid screen of an Arabidopsis cDNA library. GcR8IP1 physically associated with RPW8.2 with its RING finger domain that is essential and sufficient for the association. GcR8IP1 was secreted and translocated into the nucleus of host cell infected with PM. Association of GcR8IP1 with RPW8.2 led to an increase of RPW8.2 in the nucleus. In turn, the nucleus-localised RPW8.2 promoted the activity of the RPW8.2 promoter, resulting in transcriptional self-amplification of RPW8.2 to boost immunity at infection sites. Additionally, ectopic expression or host-induced gene silencing of GcR8IP1 supported its role as a virulence factor in PM. Altogether, our results reveal a mechanism of RPW8.2-dependent defense strengthening via altered partitioning of RPW8.2 and transcriptional self-amplification triggered by a PM fungal effector, which exemplifies an atypical form of effector-triggered immunity.