Development of a mycolic acid-graphene quantum dot probe as a potential tuberculosis biosensor.

The development of amine-functionalized graphene quantum dots (GQDs) linked to mycolic acids (MAs) as a potential fluorescent biosensor to detect tuberculosis (TB) biomarkers is described. GQDs have attractive properties: high fluorescence, excellent biocompatibility, good water solubility, and low toxicity. MAs are lipids that are found in the cell wall of Mycobacterium tuberculosis that are antigenic, however, they are soluble only in chloroform and hexane.

Synthesis and characterisation of quantum dots coupled to mycolic acids as a water-soluble fluorescent probe for potential lateral flow detection of antibodies and diagnosis of tuberculosis.

This work explores the potential use of cadmium-based quantum dots (QDs) coupled to mycolic acids (MAs) as a fluorescent probe to detect anti-MA antibodies which are biomarkers for tuberculosis (TB). The use of free MAs as antigens for the serodiagnosis of TB is known but has not been developed into a point of care test. This study focuses on the synthesis, solubility, and lateral flow of QDs coupled to MAs.

Development of a quantum dot molecularly imprinted polymer sensor for fluorescence detection of atrazine.

Atrazine is a common agricultural pesticide which has been reported to occur widely in surface drinking water, making it an environmental pollutant of concern. In the quest for developing sensitive detection methods for pesticides, the use of quantum dots (QDs) as sensitive fluorescence probes has gained momentum in recent years. QDs have attractive and unique optical properties whilst coupling of QDs to molecularly imprinted polymers (MIPs) has been shown to offer excellent selectivity.

Validation of the AGDISP model for predicting airborne atrazine spray drift: A South African ground application case study.

Air dispersion software models for evaluating pesticide spray drift during application have been developed that can potentially serve as a cheaper convenient alternative to field monitoring campaigns. Such models require validation against field monitoring data in order for them to be employed with confidence, especially when they are used to implement regulatory measures or to evaluate potential human exposure levels. In this case study, off-target pesticide drift was monitored during ground application of a pesticide mixture to a sorghum field in South Africa.