Abstract:
This disclosure provides a method for detecting and/or identifying uncultured bacteria. The sample is an aerosol sample selected from a group consisting of cough, sneeze, saliva, mucus, bile, urine, vaginal secretions, middle ear aspirate, pus, pleural effusions, synovial fluid, abscesses, cavity swabs, serum, blood and spinal fluid. The method comprises obtaining absorption spectra (AS) of the sample, extracting and processing the acquired data, thereby detecting and/or identifying the bacteria.
Abstract:
The present invention provides a method for detecting and/or identifying specific bacteria within an uncultured sample, comprising steps of: a. obtaining an absorption spectrum (AS) of said uncultured sample; b. acquiring the n dimensional volume boundaries for said specific bacteria; c. data processing said AS; i. noise reducing; ii. extracting m features from said entire AS; iii. dividing said AS into several segments according to said m features; iv. calculating m 1 features of each of said segment; and, d. detecting and/or identifying said specific bacteria if said m 1 features and/or said m features are within said n dimensional volume; wherein said bacteria is a antibiotics resistance bacteria.
Abstract:
The present invention provides a method for detecting and/or identifying specific bacteria within an uncultured sample, comprising steps of: a. obtaining an absorption spectrum (AS) of said uncultured sample; b. acquiring the n dimensional volume boundaries for said specific bacteria; c. data processing said AS; i. noise reducing; ii. extracting m features from said entire AS; iii. dividing said AS into several segments according to said m features; iv. calculating m 1 features of each of said segment; and, d. detecting and/or identifying said specific bacteria if said m 1 features and/or said m features are within said n dimensional volume; wherein said bacteria is a antibiotics resistance bacteria.
Abstract:
The present invention provides a method for detecting and/or identifying specific bacteria within an uncultured sample. The method comprises steps se lected inter alia from (a) obtaining an absorption spectrum (AS) of said unc ultured sample; (b) acquiring the n dimensional volume boundaries for said s pecific bacteria; (c) data processing said AS; and, (d) detecting and/or ide ntifying said specific bacteria if said m1 statistical correlation and/or sa id m features are within said n dimensional volume.
Abstract:
A spectroscopic method for spectroscopic detection and identification of bacteria in culture is disclosed. The method incorporates construction of at least one data set, which may be a spectrum, interference pattern, or scattering pattern, from a cultured sample suspected of containing said bacteria. The data set is corrected for the presence of water in the sample, spectral features are extracted using a principal components analysis, and the features are classified using a learning algorithm. In some embodiments of the invention, for example, to differentiate MRS A from MSSA, a multimodal analysis is performed in which identification of the bacteria is made based on a spectrum of the sample, an interference pattern used to determine cell wall thickness, and a scattering pattern used to determine cell wall roughness. An apparatus for performing the method is also disclosed, one embodiment of which incorporates a multiple sample analyzer.