An exemplary embodiment of the present disclosure provides a system for detecting antimicrobial resistance of a bacteria in a biological sample. In some embodiments, the system can include a plurality of containers, a detecting agent in each of the plurality of containers, and an antimicrobial agent in at least a portion of the plurality of containers. The antimicrobial agent is disposed in at least one of the plurality of containers. Each of the containers can contain at least a portion of the biological sample. The detecting agent can be configured to produce optically detectable changes responsive to bacterial respiration or growth, directly from patient samples of from patient sample cultures.

The invention relates in a first aspect to an improved fluidic device for determining a property of a microbe. The device comprising a bottom layer comprising a plurality of light-transmissive wells; and a top layer comprising an injection opening and a fluid distribution system. Each of said plurality of distribution channels has: essentially the same channel length between the inlet end and the outlet end; and essentially the same channel volume. The invention relates in a second aspect to a use of the device for determining a susceptibility of a microbe, preferably a bacterium, to an antimicrobial drug.

The invention relates in a first aspect to an improved fluidic device for determining a property of a microbe. The device comprising a bottom layer comprising a plurality of light-transmissive wells; and a top layer comprising an injection opening and a fluid distribution system. Each of said plurality of distribution channels has: essentially the same channel length between the inlet end and the outlet end; and essentially the same channel volume. The invention relates in a second aspect to a use of the device for determining a susceptibility of a microbe, preferably a bacterium, to an antimicrobial drug.

The present invention relates to a method of interpreting different antibiogram images in which it is possible to recognize a phenotype of bacterial resistance relative to antibiotics by comparing photographs using a photographic image bank of the reference antibiogram without any need to interpret them using the EUCAST or CA-SFM interpretation data; providing that for a given phenotype, there is available a collection of photographs of a plurality of bacteria of the same species and of the same phenotype.

The present invention relates to a method of interpreting different antibiogram images in which it is possible to recognize a phenotype of bacterial resistance relative to antibiotics by comparing photographs using a photographic image bank of the reference antibiogram without any need to interpret them using the EUCAST or CA-SFM interpretation data; providing that for a given phenotype, there is available a collection of photographs of a plurality of bacteria of the same species and of the same phenotype.

The invention provides a version of fluorescent in situ hybridization (FISH) in which all the steps are performed at physiological temperatures, i.e., body temperature, to detect and identify pathogenic bacteria in clinical samples. Methods of the invention use species-specific fluorescent probes to label clinically important infectious bacteria. A sample such as a urine sample is loaded into a cartridge, fluorescently labeled, and imaged with a microscope. Labelled bacteria are pulled down onto an imaging surface and a dye cushion is used to keep unbound probes off of the imaging surface. A microscopic image of the surface shows whether and in what quantities the infectious bacteria are present in the clinical sample.

The invention provides a version of fluorescent in situ hybridization (FISH) in which all the steps are performed at physiological temperatures, i.e., body temperature, to detect and identify pathogenic bacteria in clinical samples. Methods of the invention use species-specific fluorescent probes to label clinically important infectious bacteria. A sample such as a urine sample is loaded into a cartridge, fluorescently labeled, and imaged with a microscope. Labelled bacteria are pulled down onto an imaging surface and a dye cushion is used to keep unbound probes off of the imaging surface. A microscopic image of the surface shows whether and in what quantities the infectious bacteria are present in the clinical sample.

Methods and systems are for identifying the cell type of an unknown microorganism. The device includes: an apparatus for culturing unknown organism(s), a diagnostic data acquisition tool and a computer program. The method includes: incubation of the sample with a growth medium (with or without toxins), and an analysis of the metabolites detected in the sample. The computer system compares the results collected from the device to reference metabolite profiles.

Methods and systems are for identifying the cell type of an unknown microorganism. The device includes: an apparatus for culturing unknown organism(s), a diagnostic data acquisition tool and a computer program. The method includes: incubation of the sample with a growth medium (with or without toxins), and an analysis of the metabolites detected in the sample. The computer system compares the results collected from the device to reference metabolite profiles.

An imaging system and method provides automated microbial growth detection for antibiotic sensitivity testing. A processing system having an image sensor for capturing images of an inoculated culture plate having antibiotic disks disposed on the culture media captures images of the plate at separate times (e.g., first and second images). The system generates pixel characteristic data for pixels of the second image from a comparison of the first image and second image. The pixel characteristic data may be indicative of plate growth. The system may access growth modeling data concerning the antibiotic disk(s) and generate simulated image data with a growth model function. The growth model function uses the growth modeling data. The simulated image data simulates growth on the plate relative to the disk(s). The system compares the simulated image and the pixel characteristic data to identify pixel region(s) of the second image that differ from the simulated image.