Related Experiment Video
Updated: Feb 9, 2026

Nanosensors to Detect Protease Activity In Vivo for Noninvasive Diagnostics
Published on: July 16, 2018
Siderophore-based biosensors and nanosensors; new approach on the development of diagnostic systems
Rahim Nosrati1, Sadegh Dehghani2, Bahareh Karimi3
1Department of Pharmaceutical Biotechnology, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran; Molecular Microbiology Research Center (MMRC), Faculty of Medicine, Shahed University, Tehran, Iran.
Abstract:
Siderophores are small organic compounds secreted by microorganisms under iron-depleted conditions which enhance the uptake of iron. Siderophores can play vital roles in ecology, agriculture, bioremediation, biosensor, and medicine. In recent years, the concept of siderophore-based biosensing devices has opened new horizons in high precision detection of various metal ions especially the iron, microorganisms, phosphopeptides, antibiotics as well pesticides. Once combined with nanomaterials, nano-scale siderophore systems provide powerful analytical platforms for detection of low concentration of metal ions and numerous pathogens. In this article, a brief overview of general aspects of siderophore is firstly discussed. In addition, a clear and concise review of recent advances of siderophore-based biosensors (siderosensor) and nanosensors are mainly discussed herein. Subsequently, future perspectives and challenges of siderophore-based sensors are discussed briefly.
Related Concept Videos
Second Order systems II
First Order Systems
When a first-order system is subjected to a unit-step input, its response is characterized by its transfer function. By applying the Laplace transform of the unit-step input to the transfer function, expanding the...
Second Order systems I
By reinterpreting the system, one can derive the closed-loop transfer function, which...
Thermodynamic Systems
Consider an example of tea boiling in a kettle. The...
Classification of Systems-I
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Classification of Systems-II

