The 5‐HT3 receptor is a member of the ‘Cys‐loop’ family of ligand‐gated ion channels that mediate fast excitatory and inhibitory transmission in the nervous system. Current evidence points towards native 5‐HT3 receptors originating from homomeric assemblies of 5‐HT3A or heteromeric assembly of 5‐HT3A and 5‐HT3B. Novel genes encoding 5‐HT3C, 5‐HT3D, and 5‐HT3E have recently been described but the functional importance of these proteins is unknown. In the present study, in silico analysis (confirmed by partial cloning) indicated that 5‐HT3C, 5‐HT3D, and 5‐HT3E are not human–specific as previously reported: they are conserved in multiple mammalian species but are absent in rodents. Expression profiles of the novel human genes indicated high levels in the gastrointestinal tract but also in the brain, Dorsal Root Ganglion (DRG) and other tissues. Following the demonstration that these subunits are expressed at the cell membrane, the functional properties of the recombinant human subunits were investigated using patch clamp electrophysiology. 5‐HT3C, 5‐HT3D, and 5‐HT3E were all non‐functional when expressed alone. Co‐transfection studies to determine potential novel heteromeric receptor interactions with 5‐HT3A demonstrated that the expression or function of the receptor was modified by 5‐HT3C and 5‐HT3E, but not 5‐HT3D. The lack of distinct effects on current rectification, kinetics or pharmacology of 5‐HT3A receptors does not however provide unequivocal evidence to support a direct contribution of 5‐HT3C or 5‐HT3E to the lining of the ion channel pore of novel heteromeric receptors. The functional and pharmacological contributions of these novel subunits to human biology and diseases such as irritable bowel syndrome for which 5‐HT3 receptor antagonists have major clinical usage, therefore remains to be fully determined.

Abstract:The metabotropic glutamate receptor mGluR1␣ in membranes isolated both from rat brain and from cell lines transfected with cDNA coding for the receptor migrates as a disulphide-bonded dimer on sodium dodecyl sulphate-polyacrylamide gels. Dimerization of mGluR1␣ takes place in the endoplasmic reticulum because it is not prevented by exposing transfected human embryonic kidney (HEK) 293 cells to the drug brefeldin A, a drug that prevents egress of proteins from the endoplasmic reticulum. Dimerization was also not dependent on protein glycosylation as it was not prevented by treatment of the cells with tunicamycin. Using a mammalian expression vector containing the N-terminal domain of mGluR1␣, truncated just before the first transmembrane domain (NT-mGluR1␣), we show that the N-terminal domain is secreted as a soluble disulphide-bonded dimeric protein. In addition, the truncated N-terminal domain can form heterodimers with mGluR1␣ when both proteins are cotransfected into HEK 293 cells. However, mGluR1␣ and its splice variant mGluR1␤ did not form heterodimers in doubly transfected HEK 293 cells. These results show that although the N-terminal domain of mGluR1␣ is sufficient for dimer formation, other domains in the molecule must regulate the process. Key Words: Metabotropic glutamate receptors-Dimerization-Brefeldin A-Endoplasmic reticulum-N-terminal domain.

Using both economic theory and Artificial Intelligence (AI) pricing algorithms, we investigate the ability of a platform to design its marketplace to promote competition, improve consumer surplus, and even raise its own profits. We allow sellers to use Q-learning algorithms (a common reinforcement-learning technique from the computer-science literature) to devise pricing strategies in a setting with repeated interactions, and consider the effect of steering policies that reward firms that cut prices with additional exposure to consumers. Overall, the evidence from our experiments suggests that platform design decisions can meaningfully benefit consumers even when algorithmic collusion might otherwise emerge but that achieving these gains may require more than the simplest steering policies when algorithms value the future highly. We also find that policies that raise consumer surplus can raise the profits of the platform, depending on the platform's revenue model. Finally, we document several learning challenges faced by the algorithms. We thank Emilio Calvano, Timo Klein, Scott Duke Kominers, and participants at the University of California (Berkeley) and the 2020 Econometric Society Meetings (San Diego).

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