ReviewACS applied materials & interfaces2026
Janus Synapses as Modular Neurointerfaces.
Review in ACS applied materials & interfaces, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The nervous system processes information by translating chemical signals into electrical and biochemical responses, ultimately driving biological adaptation and computation. Chemical synapses are the primary communication channels between neurons, operating with remarkable speed and precision to enable complex neural information processing. In this perspective, we focus on these native signaling principles and explore the potential of synaptic structures as neurointerface modules. Building on this view, we argue that electrodes can be engineered to function as complementary synaptic terminals, enabling neuron-device communication that directly leverages the chemical, electrical, and biological logic of neural systems. In particular, we discuss whether synaptic cell adhesion molecules can be harnessed as synaptogenic cues to redefine electrode surfaces as functional synaptic counterparts of neuronal terminals, and we examine the distinctive properties and emerging applications of such interfaces.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.