The invention relates to a device and method for reducing the reduction in intensity of a fluorescence dye by laser light when determining fluorescence and the number of antibodies on exosomes, comprising means for storing different measurement points of various differently coloured lasers in a measuring cell at certain measurement positions, the focusing of the laser beam interacting with the sample being recorded in a video camera as the centre of a convergent beam bundle.

The disclosure relates to growing cells, directing cells to grow into specified cell types, genetically and physically manipulating cells, and addressing one or more individual cells within a mixed cell population. Aspects of the disclosure relate to vectors useful to induce developmental changes in cells, in which those vectors have a temporal component. Vectors of the disclosure encode a controllable, temporal series of events. Once the vectors are delivered into target cells, a series of discrete and different genetic events may be induced. The disclosed methods generally provide for the temporal encoding of multiplex genetic effectors in vector format for cell state transitions.

In one aspect, the present teachings provide a system for performing cytometry that can be operated in three operational modes. In one operational mode, a fluorescence image of a sample is obtained by exciting one or more fluorophore(s) present in the sample by an excitation beam formed as a superposition of a top-hat-shaped beam with a plurality of beams that are radiofrequency shifted relative to one another. In another operational mode, a sample can be illuminated successively over a time interval by a laser beam at a plurality of excitation frequencies in a scanning fashion. In yet another operational mode, the system can be operated to illuminate a plurality of locations of a sample concurrently by a single excitation frequency, which can be generated, e.g., by shifting the central frequency of a laser beam by a radiofrequency. The detected fluorescence radiation can be used to analyze the fluorescence content of the sample, e.g., a cell/particle.

An analyzer of a component in a sample fluid includes an optical source and an optical detector defining a beam path of a beam, wherein the optical source emits the beam and the optical detector measures the beam after partial absorption by the sample fluid, a fluid flow cell disposed on the beam path defining an interrogation region in the fluid flow cell in which the optical beam interacts with the sample fluid and a reference fluid; and wherein the sample fluid and the reference fluid are in laminar flow, and a scanning system that scans the beam relative to the laminar flow within the fluid flow cell, wherein the scanning system scans the beam relative to both the sample fluid and the reference fluid.

An analyzer of a component in a sample fluid includes an optical source and an optical detector defining a beam path of a beam, wherein the optical source emits the beam and the optical detector measures the beam after partial absorption by the sample fluid, a fluid flow cell disposed on the beam path defining an interrogation region in the a fluid flow cell in which the optical beam interacts with the sample fluid and a reference fluid; and wherein the sample fluid and the reference fluid are in laminar flow, and a scanning system that scans the beam relative to the laminar flow within the fluid flow cell, wherein the scanning system scans the beam relative to both the sample fluid and the reference fluid.

A lens-free microscope system for automatically analyzing yeast cell viability in a stained sample includes a portable, lens-free microscopy device that includes a housing containing a light source coupled to an optical fiber, the optical fiber spaced away several centimeters from an image sensor disposed at one end of the housing, wherein the stained sample is disposed on the image sensor or a sample holder adjacent to the image sensor. Hologram images are transferred to a computing device having image processing software contained therein, the image processing software identifying yeast cell candidates of interest from back-propagated images of the stained sample, whereby a plurality of spatial features are extracted from the yeast cell candidates of interest and subject to a trained machine learning model to classify the yeast cell candidates of interest as live or dead.

A mask structure optimization device includes a classification target image size acquisition unit that is configured to acquire a size of a classification target image which is an image including a classification target, a mask size setting unit that is configured to set a size of a mask applied to the classification target image, a brightness detection unit that is configured to detect a brightness of each pixel within the classification target image at a position on an opposite side of the mask from the classification target image, a sum total brightness calculation unit that is configured to calculate the sum total brightness of the each pixel within the classification target image detected by the brightness detection unit, an initial value setting unit that is configured to set an initial value for a mask pattern of the mask, and a movement unit that is configured to relatively move the mask with respect to the classification target image. The sum total brightness calculation unit is configured to calculate the sum total brightness of the each pixel within the classification target image every time the movement unit relatively moves the mask by a predetermined movement amount. The mask structure optimization device further includes a mask pattern optimization unit that is configured to optimize the mask pattern of the mask on the basis of the sum total brightness.

A system for dissociating cells from a cell culture vessel. The system comprises an imaging system configured to image a plurality of cells in a cell culture vessel being dissociated from at least one surface of the cell culture vessel by at least one cell dissociation agent; and at least one controller coupled to the imaging system and configured to: control the imaging system to capture a sequence of images of at least some cells in the plurality of cells during dissociation; and identify when to neutralize the at least one cell dissociation agent using the sequence of images.

A particulate matter (PM) sensor comprises a substrate forming a cavity (5), the substrate comprising a semiconductor chip (4), and a light source (1) arranged in the cavity (5). The light source (1) is adapted to emit a light beam (7). The light beam (7) forms a detection volume (8) for particulate matter (9) outside the cavity (5). Optionally, the particulate matter sensor comprises an optical element (2) delimiting the cavity (5) at one end. The optical element (2) is configured to shape the light beam (7). Further, the particulate matter sensor comprises at least one photodetector (3) that is integrated into a surface of the semiconductor chip (4). The surface into which the at least one photodetector (3) is integrated faces the detection volume (8). The at least one photodetector (3) is adapted to detect light (10) scattered by particulate matter (9) in the detection volume (8).

A laser sensor for detecting a particle density includes: a laser configured to emit a measurement beam, an optical arrangement being arranged to focus the measurement beam to a measurement volume, the optical arrangement having a numerical aperture with respect to the measurement beam, a detector configured to determine a self-mixing interference signal of a optical wave within a laser cavity of the laser, and an evaluator. The evaluator is configured to: receive detection signals generated by the detector in reaction to the determined self-mixing interference signal, determine an average transition time of particles passing the measurement volume in a predetermined time period based on a duration of the self-mixing interference signals generated by the particles, determine a number of particles based on the self-mixing interference signals in the predetermined time period, and determine the particle density based on the average transition time and the number of particles.