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Cross-reactivity

Cross-reactivity

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Related Experiment Video

Updated: Apr 16, 2026

Snap Chip for Cross-reactivity-free and Spotter-free Multiplexed Sandwich Immunoassays

Snap Chip for Cross-reactivity-free and Spotter-free Multiplexed Sandwich Immunoassays

Published on: November 13, 2017

Multidimensional mapping method using an arrayed sensing system for cross-reactivity screening.

Sheryl E Chocron¹, Bryce M Weisberger¹, Hadar Ben-Yoav²

¹MEMS Sensors and Actuators Laboratory (MSAL), University of Maryland, College Park, Maryland, United States of America; Fischell Department of Bioengineering, University of Maryland, College Park, Maryland, United States of America.

|March 20, 2015

Summary

This summary is machine-generated.

This study introduces a new method to investigate cross-reactions in biological fluids for sensor design. It helps create more accurate chemical sensing systems by understanding how different substances interfere with measurements.

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Area of Science:

Analytical Chemistry
Biomedical Engineering
Chemical Sensing

Background:

Cross-reactivity poses a significant challenge in chemical sensing within biological fluids, particularly when biological recognition elements are absent.
Understanding these cross-reactions is crucial for developing effective sensing systems for complex matrices.

Purpose of the Study:

To present a novel methodology for systematically investigating cross-reactions in complex biological fluids.
To guide the design of robust sensing systems capable of accurate chemical measurements in vivo.

Main Methods:

Systematic screening of matrix components in buffer solutions.
Characterization of simulated mixtures using an arrayed electrochemical sensing system.
Mapping sensor array responses onto multidimensional heat maps to identify characteristic signatures.

Main Results:

Demonstrated differential responses from an electrochemical sensor array, providing synergistic sample information.
Successfully mapped and compared characteristic signatures across sensors and different matrices.
Applied the methodology to biological samples, matching simulated mixture signatures with complex sample responses.

Conclusions:

The proposed methodology offers an investigational tool for multi-analyte sensor design and chemometric modeling.
This approach aids in biomarker discovery by enabling the discernment of specific chemical signatures in complex biological samples.
The study highlights the application in schizophrenia management, correlating clozapine and antioxidant levels with therapeutic efficacy.