Evidence map›Paper›PMID 38781346›Full record

ArticleScience advances2024

A pattern recognition artificial olfactory system based on human olfactory receptors and organic synaptic devices.

Hyun Woo Song, Dongseok Moon, Yousang Won, Yeon Kyung Cha, Jin Yoo, Tai Hyun Park, Joon Hak Oh

Abstract read
In one paragraph

Article in Science advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. Review
  8. Organic Electrochemical Transistors in Tissue-Interfaced Bioelectronics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  9. Review
  10. Review
  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Hyun Woo SongSchool of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of Korea.ORCID 0009-0002-1637-6953
Dongseok MoonSchool of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of Korea.ORCID 0000-0001-7474-7252
Yousang WonSchool of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of Korea.ORCID 0009-0003-7125-7858
Yeon Kyung ChaInterdisciplinary Program in Bioengineering, Seoul National University, Seoul 08826, Republic of Korea.ORCID 0000-0001-9932-7553
Jin YooSchool of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of Korea.ORCID 0000-0002-7738-8424
Tai Hyun ParkSchool of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of Korea.ORCID 0000-0003-4254-0657
Joon Hak OhSchool of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of Korea.ORCID 0000-0003-0481-6069

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neuromorphic sensors, designed to emulate natural sensory systems, hold the promise of revolutionizing data extraction by facilitating rapid and energy-efficient analysis of extensive datasets. However, a challenge lies in accurately distinguishing specific analytes within mixtures of chemically similar compounds using existing neuromorphic chemical sensors. In this study, we present an artificial olfactory system (AOS), developed through the integration of human olfactory receptors (hORs) and artificial synapses. This AOS is engineered by interfacing an hOR-functionalized extended gate with an organic synaptic device. The AOS generates distinct patterns for odorants and mixtures thereof, at the molecular chain length level, attributed to specific hOR-odorant binding affinities. This approach enables precise pattern recognition via training and inference simulations. These findings establish a foundation for the development of high-performance sensor platforms and artificial sensory systems, which are ideal for applications in wearable and implantable devices.

Indexed as

OdorantsReceptors, OdorantBiosensing TechniquesHumansOlfactory Receptor NeuronsPattern Recognition, AutomatedSmellSynapsesReceptors, Odorant

Identifiers

PMID38781346
PMCPMC11114221

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.