TBME presents

An Automated Microrobotic Platform for Rapid Detection of C. diff Toxins

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Clostridium difficile (C. diff) is a gastrointestinal pathogen and the leading cause of healthcare associated infection (e. g. diarrhoea and pseudomembranous colitis) in the USA and developed countries. Therefore, early diagnosis of this toxin-mediated disease is important. This paper aims to develop a microrobotic system and related methods that enable the automated and rapid detection of toxins secreted by C. diff that exist in patient’s stool.

We utilize the fluorescent magnetic spore-based microrobot (FMSM), a microscale mobile sensing tool, to efficiently detect C. diff toxins by utilizing its property of selective fluorescence responses to C. diff toxins. A plug-and-play (PnP) electromagnetic coil system integrated with fluorescence microscopy is developed for actuation, control and observation of FMSMs. In order to track in real time and accurately obtain the fluorescence parameters of a FMSM under varied background noise in fluorescence signal, an image gradient-based method is proposed. For accelerating the FMSM-toxin interaction in different samples, an automated navigation control scheme for the FMSM is proposed and implemented. Moreover, data post-processing methods that can optimally extract the fluorescence decay trend from the dense and fluctuated fluorescence data are developed.

This automated mobile detection process finishes within only 20 minutes, and the toxin detection result is immediately given by adopting the proposed system and methods. Experimental results on different biological samples confirm the qualitative detection capability. And, C. diff toxins are automatically detected from the clinical stool of infectious patients and the relationship between the fluorescence decay and the toxin concentration is calibrated for semi-quantitative detection purpose. The proposed automated microrobotic platform provides a rapid and low-cost detection technique for C. diff toxins, and it has good competency for future clinical use.

Read the full paper on IEEE Explore

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