A method of analysis using mass spectrometry and/or ion mobility spectrometry is disclosed comprising: (a) using a first device to generate smoke, aerosol or vapour from a target in vitro or ex vivo cell population; (b) mass analysing and/or ion mobility analysing said smoke, aerosol or vapour, or ions derived therefrom, in order to obtain spectrometric data; and (c) analysing said spectrometric data in order to identify and/or characterise said target cell population or one or more cells and/or compounds present in said target cell population.

In a method for spatially localizing mass-spectrometry analysis of an analyte derived from an energy event, an electrical device is used to deliver an energy event to a substrate, and the analyte produced is analyzed using mass spectrometry. Electrical signals sent to and received from the electrical device under different modes of operation are sensed and classified according to each different mode of operation. A location of the electrical device is tracked in three dimensions during the energy event, and a processor is used to perform spatial-temporal alignment of the mass-spectrometry, the determined modes of operation of the electrical device, and the tracked location of the electrical device, wherein mass spectrometry data corresponding to the determined modes of the electrical device are identified and localized within the site of the energy event. The substrate may be tissue in a surgical site, and the electrical device may be an electrocautery device.

After a sample such as a biomedical tissue section is attached to an electrically-conductive slide glass (S1), the film layer of a matrix substance is appropriately formed by vapor deposition so as to cover the sample (S2). The crystal of the matrix substance in the film layer is very fine and uniform. Subsequently, the slide glass on which the matrix film layer is formed is placed in a vaporized solvent atmosphere, and the solvent infiltrates into the matrix film layer (S3). When the solvent sufficiently infiltrated is vaporized, a substance to be measured in the sample takes in the matrix and re-crystallized. Furthermore, the matrix film layer is formed again on the surface by the vapor deposition (S4). The added matrix film layer absorbs excessive energy of a laser beam during MALDI, which suppresses the denaturation of the substance to be measured and the like, so that high detection sensitivity can be achieved while high spatial resolution is maintained.

Disclosed embodiments include a time-of-flight mass spectrometer with a straight ion optical axis comprising: an ion gate is electrically insolated electrode on which applied voltages to reject/pass ions through ion gate, entrance module and exit module set in focus/mirror modes, and create ion optical image on image plane located in field view aperture, electrostatic object lens, entrance module in focus mode and, transport electrostatic lens, exit module in focus mode and projection lens focused and map ions from image plane of field view aperture to image plane of ion detector, projection lens configured to form ion optical image of sample holder on image plane of ion detector and ion optical components with corrected geometrical, chromatic and timed aberrations configured to compensate time arriving disturbance in image plane of ion detector and improve mass and spatial resolution of image on image plane of ion detector.

Systems and methods are provided for maximizing the data acquired from a sample in a mass spectrometry imaging experiment. An ion source device is instructed to produce and transmit to a tandem mass spectrometer a plurality of ions for each location of two or more locations of a sample. A mass range is divided into two or more mass window widths. For each location of the two or more locations, the tandem mass spectrometer is instructed to fragment the plurality of ions received for each location using each mass window width of the two or more mass window widths and to analyze resulting product ions. A product ion spectrum is produced for each mass window width, and a plurality of product ion spectra are produced for each location of the two or more locations.

When a user designates a region of interest for a plurality of groups targeted for difference analysis in a microscopic observation image of a sample, an m/z candidate search unit (32) searches for candidates for m/z presumed to differ, based on collected mass spectral data. An intensity histogram creation unit processing unit (33) creates and displays a graph showing a frequency distribution of peak intensities at measurement points included in the region of interest of the groups for each of the m/z candidates. If this graph exhibits multimodality, the data distribution is not suitable for a statistical hypothesis test. Thus, an intensity range determination unit (34) limits an intensity range in accordance with a user's instruction. Then, an ROI correction unit (35) corrects the ROI so as to include only measurement points with peak intensities within the limited intensity range. After that, a test processing unit (36) performs a statistical hypothesis test by using the data corresponding to the corrected ROI. In this way, even if first user's setting of a region of interest is improperly made, it is possible to perform highly reliable difference analysis.

An imaging mass spectrometry unit (1) executes predetermined analysis on each of a plurality of micro areas set in a two-dimensional measurement region on a sample or a three-dimensional measurement region in a sample to acquire spectrum data. A clustering execution section (21) classifies spectrum data for a plurality of measurement points obtained for a reference sample into any of a plurality of clusters. A clustering model information storage section (22) stores a clustering model obtained by clustering processing. A segmentation execution section (23) classifies respective spectral data for a plurality of measurement points obtained for a sample other than a reference sample using a clustering model, and a spatial distribution image creation section (24) creates a segmentation image obtained by partitioning a two-dimensional or three-dimensional image into a plurality of small regions on the basis of a result of the classification.

The invention generally relates to methods for analyzing a metabolite level in a sample. In certain embodiments, methods of the invention may involve obtaining a sample, analyzing the sample using a mass spectrometry technique to determine a level of at least one metabolite in the sample, and correlating the metabolite level with an originating source of the sample, thereby analyzing the sample.

The disclosure features systems and methods that include: exposing a biological sample to an ion beam that is incident on the sample at a first angle to a plane of the sample by translating a position of the ion beam on the sample in a first direction relative to a projection of a direction of incidence of the ion beam on the sample; after each translation of the ion beam in the first direction, adjusting a focal length of an ion source that generates the ion beam; and measuring and analyzing secondary ions generated from the sample by the ion beam after adjustment of the focal length to determine mass spectral information for the sample, where the sample is labeled with one or more mass tags and the mass spectral information includes populations of the mass tags at locations of the sample.

A peak-waveform conversion processor detects a peak in a profile spectrum created based on data obtained at each measurement point in a sample's measurement area, and acquires a rod-like peak by performing centroid conversion processing on a waveform of the peak having a mountain shape. When an operator specifies a target compound to be observed, a mass difference calculation unit calculates a mass difference between a precise m/z of the target compound and an m/z of a rod-like peak at a position close to the precise m/z for each measurement point. A mass difference image creator creates an image showing a distribution of mass differences based on the calculated mass differences. A mass difference related information calculation unit acquires an index value such as an average value of a plurality of mass differences for each mass difference image, and creates a graph showing a frequency distribution of the mass differences.