Skip to main navigation Skip to search Skip to main content

A memristor-based method for discriminating tuberculous and malignant pleural effusions

  • Miaomiao Liu
  • , Jian Wang
  • , Zelin Cao
  • , Bai Sun
  • , Song Ling Wang
  • , Juan Wang
  • , Tao Xin
  • , Ruina Ma
  • , Junxiang Gu
  • , Ping He
  • , Jinbo Zhao
  • , Yu Cui
  • , Teng Wu
  • , Jianqiang Qu
  • , Xiaojun Li
  • , Yandong Nan
  • , Xianxia Yan
  • The Second Affiliated Hospital of Xi'an Jiaotong University
  • Tangdu Hospital, Fourth Military Medical University
  • 94750th Hospital of Chinese People's Liberation Army
  • Air Force Medical University
  • Frontier Institute of Science and Technology
  • CAS - Fujian Institute of Research on the Structure of Matter

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Distinguishing malignant pleural effusion (MPE) from tuberculous pleural effusion (TPE) is important, as the underlying diseases (tuberculosis and advanced malignancies) are major public health concerns. However, an efficient method for differentiating these two effusions is still lacking. In this work, we fabricated an Ag/SiO2/Fe2O3/ITO memristor and demonstrated its ability to reliably distinguish MPE from TPE by exploiting its unique resistive switching behavior. Mechanistic analysis reveals that subtle compositional differences between MPE and TPE can be transduced into distinct, measurable electrical signals. Furthermore, the memristor achieves effective identification of MPE and TPE through characteristic electrochemical responses, most notably polarity-dependent variations in the high-resistance-state/low-resistance-state (Roff/Ron) ratio and peak current. This work introduces a memristor-based approach for discriminating MPE and TPE, providing a potential tool for clinical practice.

Original languageEnglish
Article number103273
JournalMaterials Today Bio
Volume38
DOIs
StatePublished - Jun 2026
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Malignant pleural effusion
  • Memristor
  • Smart medicine
  • Tuberculous pleural effusion

Fingerprint

Dive into the research topics of 'A memristor-based method for discriminating tuberculous and malignant pleural effusions'. Together they form a unique fingerprint.

Cite this