PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 24, 2026Journal of Ovarian Research0 citationsOpen Access

Development of a surface plasmon resonance sensor for assessing infertility based on Anti-Mullerian hormone levels

HMHamed MirshekariFSFatemeh SabzalizadehRTRamezan Ali Taheri

Key Points

  • To create a cost-effective and sensitive biosensor for measuring anti-Müllerian hormone (AMH) levels in serum.
  • Developed a surface plasmon resonance (SPR) sensor using a gold chip.
  • Used Protein G to immobilize anti-AMH antibodies for detection.
  • Conducted comparisons with ELISA and localized surface plasmon resonance assays.
  • Achieved limits of detection (LOD) of 0.6 ng/mL and quantification (LOQ) of 1.78 ng/mL for AMH.
  • The biosensor showed high sensitivity with results comparable to ELISA.
  • It significantly reduces costs and time required for AMH testing.

Abstract

Anti-Müllerian hormone (AMH) is a key biomarker for fertility assessment, but current diagnostic methods lack cost-effectiveness. Plasmonic biosensors can effectively detect low-concentration protein interactions. This study developed a sensitive, label-free surface plasmon resonance (SPR) sensor for AMH detection. Protein G was used to bind anti-AMH antibodies onto a gold chip coated with 11-MUA. Various AMH concentrations were measured to create a standardized graph, establishing limits of detection (LOD) and quantification (LOQ). The biosensor also tested patient serum samples for AMH detection, comparing the results with those obtained from enzyme-linked immunosorbent assay (ELISA) and localized surface plasmon resonance (LSPR) using silica@Au-NRs with anti-AMH antibodies. The detection results indicated a high sensitivity of the nanobiosensors, with LOD and LOQ for the gold chip at 0.6 ng/mL and 1.78 ng/mL, respectively, closely matching those of ELISA and silica@Au-NRs. Additionally, SPR-based biosensors reduce detection costs and measurement time, making them strong candidates for integration into diagnostic kits.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Mirshekari et al. (2026) studied this question.

synapsesocial.com/papers/69eb0ac4553a5433e34b4b89https://doi.org/10.1186/s13048-026-02096-9
Ask AI
Helpful
Bookmark
Share
View Full Paper