Click-aware purchase prediction with push at the top

Eliciting user preferences from purchase records for performing purchase prediction is challenging because negative feedback is not explicitly observed, and because treating all non-purchased items equally as negative feedback is unrealistic. Therefore, in this study, we present a framework that leverages the past click records of users to compensate for the missing user-item interactions of purchase records, i.e., non-purchased items. We begin by formulating various model assumptions, each one assuming a different order of user preferences among purchased, clicked-but-not-purchased, and non-clicked items, to study the usefulness of leveraging click records. We implement the model assumptions using the Bayesian personalized ranking model, which maximizes the area under the curve for bipartite ranking. However, we argue that using click records for bipartite ranking needs a meticulously designed model because of the relative unreliableness of click records compared with that of purchase records. Therefore, we ultimately propose a novel learning-to-rank method, called P3Stop, for performing purchase prediction. The proposed model is customized to be robust to relatively unreliable click records by particularly focusing on the accuracy of top-ranked items. Experimental results on two real-world e-commerce datasets demonstrate that P3STop considerably outperforms the state-of-the-art implicit-feedback-based recommendation methods, especially for top-ranked items.Comment: For the final published journal version, see https://doi.org/10.1016/j.ins.2020.02.06

Cdk5 Phosphorylates Dopamine D2 Receptor and Attenuates Downstream Signaling

The dopamine D2 receptor (DRD2) is a key receptor that mediates dopamine-associated brain functions such as mood, reward, and emotion. Cyclin-dependent kinase 5 (Cdk5) is a proline-directed serine/threonine kinase whose function has been implicated in the brain reward circuit. In this study, we revealed that the serine 321 residue (S321) in the third intracellular loop of DRD2 (D2i3) is a novel regulatory site of Cdk5. Cdk5-dependent phosphorylation of S321 in the D2i3 was observed in in vitro and cell culture systems. We further observed that the phosphorylation of S321 impaired the agonist-stimulated surface expression of DRD2 and decreased G protein coupling to DRD2. Moreover, the downstream cAMP pathway was affected in the heterologous system and in primary neuronal cultures from p35 knockout embryos likely due to the reduced inhibitory activity of DRD2. These results indicate that Cdk5-mediated phosphorylation of S321 inhibits DRD2 function, providing a novel regulatory mechanism for dopamine signaling.X111111sciescopu

Gating of memory encoding of time-delayed cross-frequency MEG networks revealed by graph filtration based on persistent homology

To explain gating of memory encoding, magnetoencephalography (MEG) was analyzed over multi-regional network of negative correlations between alpha band power during cue (cue-alpha) and gamma band power during item presentation (item-gamma) in Remember (R) and No-remember (NR) condition. Persistent homology with graph filtration on alpha-gamma correlation disclosed topological invariants to explain memory gating. Instruction compliance (R-hits minus NR-hits) was significantly related to negative coupling between the left superior occipital (cue-alpha) and the left dorsolateral superior frontal gyri (item-gamma) on permutation test, where the coupling was stronger in R than NR. In good memory performers (R-hits minus false alarm), the coupling was stronger in R than NR between the right posterior cingulate (cue-alpha) and the left fusiform gyri (item-gamma). Gating of memory encoding was dictated by inter-regional negative alpha-gamma coupling. Our graph filtration over MEG network revealed these inter-regional time-delayed cross-frequency connectivity serve gating of memory encoding