Abstract:
A method for deep learning video microscopy-based antimicrobial susceptibility testing of a bacterial strain in a sample by acquiring image sequences of individual bacterial cells of the bacterial strain in a subject sample before, during, and after exposure to each antibiotic at different concentrations. The image sequences are compressed into static images while preserving essential phenotypic features. Data representing the static images is input into a pre-trained deep learning (DL) model which generates output data; and antimicrobial susceptibility for the bacterial strain is determined from the output data.
Abstract:
Provided herein are methods of assessing the presence of microbes in a liquid sample that include assessing an initial integrated scattering intensity of objects (IC0) in the sample and an integrated scattering intensity of the objects at a time t (ICt) from modified images of the liquid sample, and identifying the sample as comprising microbes for (ICt)/(IC0) above a predefined infection threshold TI. Related systems and other aspects are also provided.
Abstract:
Method and system to remove background noise with a differential approach in optical imaging is disclosed. The differential approach moves the sample position laterally over a small distance, and a differential image is generated from the images recorded before and after the lateral translation. This approach can significantly improve the image quality of objects, including single DNA molecules, for label-free optical imaging techniques, such as surface plasmon resonance imaging. Disclosed imaging technique provides high-resolution genome-wide restriction maps of single DNA molecules.
Abstract:
Provided herein are systems for the label-free detection of target molecules in samples. The systems include a sensor probe positioned in a sensing region and configured to bind to receptors for the target molecules. The systems also include electrodes configured to expose the sensor probe to an alternating electric field, and a light source optically coupled to the sensor probe and configured to provide light along a length of the sensor probe. In addition, the systems also include a position sensitive photodetector configured to detect a position of light exiting the sensor probe, and a processor configured to assess, based at least in part on the position of the light exiting the sensor probe, an amplitude of oscillation of the sensor at a frequency of the alternating electric field and a direction of a displacement of the sensor. Additional systems and related methods are also provided.
Abstract:
A method for deep learning video microscopy-based antimicrobial susceptibility testing of a bacterial strain in a sample by acquiring image sequences of individual bacterial cells of the bacterial strain in a subject sample before, during, and after exposure to each antibiotic at different concentrations. The image sequences are compressed into static images while preserving essential phenotypic features. Data representing the static images is input into a pre-trained deep learning (DL) model which generates output data; and antimicrobial susceptibility for the bacterial strain is determined from the output data.
Abstract:
Provided herein are systems for the label-free detection of target molecules in samples. The systems include a sensor probe positioned in a sensing region and configured to bind to receptors for the target molecules. The systems also include electrodes configured to expose the sensor probe to an alternating electric field, and a light source optically coupled to the sensor probe and configured to provide light along a length of the sensor probe. In addition, the systems also include a position sensitive photodetector configured to detect a position of light exiting the sensor probe, and a processor configured to assess, based at least in part on the position of the light exiting the sensor probe, an amplitude of oscillation of the sensor at a frequency of the alternating electric field and a direction of a displacement of the sensor. Additional systems and related methods are also provided.
Abstract:
Provided herein are methods of detecting single molecules that include binding single molecules in a sample solution to a first surface of an optically transparent substrate include the optically transparent substrate is free of a metallic coating. In some embodiments, the methods include irradiating the first surface of the substrate with an incident light having an incident angle selected to achieve total internal reflection of the incident light, thereby scattering light from the first surface and from the single molecules bound to the surface in which a wavelength of the incident light is between 10 nm and 350 μm and the optically transparent substrate has a refractive index at the wavelength of the incident light exceeding that of the sample solution, and collecting an image that captures interference between evanescent light scattered from the single molecules and the first surface. Systems and additional methods are also provided.
Abstract:
A method for deep learning video microscopy-based antimicrobial susceptibility testing of a bacterial strain in a sample by acquiring image sequences of individual bacterial cells of the bacterial strain in a subject sample before, during, and after exposure to each antibiotic at different concentrations. The image sequences are compressed into static images while preserving essential phenotypic features. Data representing the static images are input into a pre-trained deep learning (DL) model which generates output data; and antimicrobial susceptibility for the bacterial strain is determined from the output data.
Abstract:
Method and system to remove background noise with a differential approach in optical imaging is disclosed. The differential approach moves the sample position laterally over a small distance, and a differential image is generated from the images recorded before and after the lateral translation. This approach can significantly improve the image quality of objects, including single DNA molecules, for label-free optical imaging techniques, such as surface plasmon resonance imaging. Disclosed imaging technique provides high-resolution genome-wide restriction maps of single DNA molecules.