Jimmy Larsson

This paper develops a method to rapidly detect bacteria in blood using smart centrifugation, microfluidic trapping, and deep learning for sepsis diagnostics.

This study uses single-cell imaging and a deep neural network to rapidly assess drug susceptibility in Mycobacterium tuberculosis variant bovis BCG, achieving results in under 12 hours.

This study evaluates if phenotypic antibiotic susceptibility testing can be performed on single bacterial cells by monitoring phenotypic changes over time, finding that single-cell responses are heterogeneous and require sequential antibiotic exposure for accurate resistance classification.

This study uses live-cell imaging of fluorescently labeled loci in E. coli to inform a dynamic polymer model of chromosome organization across the cell cycle, revealing global reorganization of the chromosome structure.

The paper demonstrates in situ genotyping of pooled strain libraries by combining single molecule fluorescence imaging with barcoded plasmids to identify individual cell genotypes after phenotype characterization.