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Background: As a critical driving power to promote health care, the health care-related artificial intelligence (AI) literature is growing rapidly. Objective: The purpose of this analysis is to provide a dynamic and longitudinal bibliometric analysis of health care-related AI publications. Methods: The Web of Science (Clarivate PLC) was searched to retrieve all existing and highly cited AI-related health care research papers published in English up to December 2019. Based on bibliometric indicators, a search strategy was developed to screen the title for eligibility, using the abstract and full text where needed. The growth rate of publications, characteristics of research activities, publication patterns, and research hotspot tendencies were computed using the HistCite software. Results: The search identified 5235 hits, of which 1473 publications were included in the analyses. Publication output increased an average of 17.02% per year since 1995, but the growth rate of research papers significantly increased to 45.15% from 2014 to 2019. The major health problems studied in AI research are cancer, depression, Alzheimer disease, heart failure, and diabetes. Artificial neural networks, support vector machines, and convolutional neural networks have the highest impact on health care. Nucleosides, convolutional neural networks, and tumor markers have remained research hotspots through 2019. Conclusions: This analysis provides a comprehensive overview of the AI-related research conducted in the field of health care, which helps researchers, policy makers, and practitioners better understand the development of health care-related AI research and possible practice implications. Future AI research should be dedicated to filling in the gaps between AI health care research and clinical applications.

Apelin receptor (APJ) and bradykinin B2 receptor (B2R) play an important role in many physiological processes and share multiple similar characteristics in distribution and functions in the cardiovascular system. We first identified the endogenous expression of APJ and B2R in human umbilical vein endothelial cells (HUVECs) and their co-localization on human embryonic kidney (HEK) 293 cells membrane. A suite of bioluminescence and fluorescence resonance energy transfer (BRET and FRET), proximity ligation assay (PLA), and co-immunoprecipitation (Co-IP) was exploited to demonstrate formation of functional APJ and B2R heterodimer in HUVECs and transfected cells. Stimulation with apelin-13 and bradykinin (BK) increased the phosphorylation of the endothelial nitric oxide synthase (eNOS) in HUVECs, which could be inhibited by the silencing of APJ or B2R, indicating the APJ-B2R dimer is critical for eNOS phosphorylation in HUVECs. Furthermore, the increase of NOS and extracellular signal regulated kinases1/2 (ERK1/2) phosphorylation mediated by APJ/B2R dimer can be inhibited by U0126 and U73122, respectively, suggesting that the heterodimer might activate the PLC/ERK1/2/eNOS signaling pathway, and finally leading to a significant increase in cell proliferation. Thus, we uncovered for the first time the existence of APJ-B2R heterodimer and provided a promising new target in cardiovascular therapeutics.