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Accurate and rapid antibiotic susceptibility testing using a machine learning assisted nanomotion technology platform

Fig. 1 from Alexander Sturm et al. “Accurate and rapid antibiotic susceptibility testing using a machine learning-assisted nanomotion technology platform”: Nanomotion detection and recording platform. a Representation of the components of the nanomotion technology platform. b A representation of the nanomotion measurement setup with the (1) bacteria-loaded cantilever, (2) superluminescent light emitting diode (SLED) = light source, and (3) photodetector. c Schematic illustrating Gram-negative bacteria attached to the cantilever. Prior to attachment, bacteria are dispersed in gelling agarose while the cantilever surface is functionalized using positively charged poly-D-lysine. The gelling agent proved beneficial for an even distribution and stability of the bacterial attachment. d Representative standard 4-h nanomotion recordings with a 2-h medium phase (50% LB medium) followed by a 2-h drug phase with 32 µg/ml CRO for the E. coli reference strains ATCC-25922 (S, susceptible) and BAA-2452 (R, resistant). These recordings form the basis for using nanomotion to conduct AST. This study contains 219 recordings of ATCC-25922 and 225 recordings of BAA-2452 exposed to 32 µg/ml CRO with similar results. Data are available in the source data file. NANOSENSORSTM tipless uniqprobe AFM cantilevers SD-qp-CONT-TL from the NANOSENSORS Special Developments List were used.

Antimicrobial resistance (AMR) has become a significant threat to public health worldwide. * AMR diagnostic strategies such as antibiotic susceptibility testing (AST) help provide clinicians… Read More »Accurate and rapid antibiotic susceptibility testing using a machine learning assisted nanomotion technology platform