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 MRSA 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.

Abstract: The present invention provides a method for detecting and/or identifying specific bacteria within an uncultured sample. The method comprises steps selected inter alia from (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; and, (d) detecting and/or identifying said specific bacteria if said m1 statistical correlation and/or said 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 MRSA 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.

Abstract: The present invention provides an optical unit (320) adapted to accommodate a sample and to enable optical detection of infection within said sample; said optical unit comprising a body (100); said body is characterized by a distal end and a proximal end interconnected via a main longitudinal axis; said body (100) comprising at least one mirror (50) coupled to said distal end; wherein said mirror (50) having a proximal and distal surfaces; said proximal surface faces said mask; said proximal surface is adapted to accommodate said sample.

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 m1 features of each of said segment; and, d. detecting and/or identifying said specific bacteria if said m1 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 selected inter alia from (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; and, (d) detecting and/or identifying said specific bacteria if said m1 statistical correlation and/or said m features are within said n dimensional volume.

Abstract: A method and composition for the identification of biomolecule in a sample are disclosed. The method comprises obtaining a coated capture membrane stack comprising a plurality of capture membranes with each capture membrane coated with a different peptide. The membrane stack is exposed to a sample, and, after a given amount of time for the sample to permeate the membrane stack, the membrane stack is removed from the sample carrier and the capture membrane to which the biomolecule adheres is identified.

Abstract: A method and composition for the identification of biomolecule in a sample are disclosed. The method comprises obtaining a coated capture membrane stack comprising a plurality of capture membranes with each capture membrane coated with a different peptide. The membrane stack is exposed to a sample, and, after a given amount of time for the sample to permeate the membrane stack, the membrane stack is removed from the sample carrier and the capture membrane to which the biomolecule adheres is identified.