The present disclosure relates to systems and methods for cell recognition. At least one embodiment relates to a method for recognizing cell. The method includes receiving an image of the cell. The method also includes performing edge detection on the image of the cell. Further, the method includes detecting ridges within the image of the cell. In addition, the method includes quantifying an internal complexity of the cell by gauging a contrast of the ridges with an average of a Laplacian on the detected ridges.

Provided are a medical analysis device and a cell analysis method which can capture many cancer cells, including cancer cells not expressing EpCAM. A medical analysis device including a flow channel zone that includes a chamber zone, the inner surface of the flow channel zone being at least partially provided with a layer of a hydrophilic polymer having a thickness of 2 to 200 nm.

According to one embodiment, an optical sensor includes a plurality of sensing parts two-dimensionally arranged in a matrix to form a sensor surface, and a phototransmissive sample-supporting plate arranged to be opposed to the sensing parts.

Implementations described and claimed herein provide systems and methods for sampling particles from air. In one implementation, an inlet opening is defined in a proximal end of a cassette top, and the inlet opening has an inlet diameter. An internal surface extends along an airflow curve from the inlet opening to an internal cavity. A sampling substrate is formed by at least one grid attached to a filter. The sampling substrate is disposed in the internal cavity at an internal distance from the inlet opening. The inlet opening and the airflow curve of the internal surface generate an airflow of the air to the sampling substrate. The sampling substrate collects a set of the particles from the air, and the inlet diameter, the airflow, and the internal distance dictate a cutoff diameter of the set of particles collected from the air by the sampling substrate.

A cell suction support system includes: an image acquisition unit that acquires a microscopic image of a group of cells in a cell container; an image processor that uses the microscopic image to calculate a characteristic amount of each cell, and detects a cell having a characteristic amount that satisfies a predetermined condition; a display that displays information concerning the group of cells so that the detected cell is distinguishable; and a movement controller that moves the cell container so that a designated specific cell is placed at a predetermined suction position, while moving a suction tip to the suction position.

The invention relates to a liquid cell (1) for the microscopic image capture and Raman spectroscopic material analysis of a particle suspension in a reflected light microscope, having at least the following components: a measuring chamber (2) which has a base (3), a measuring window (5) opposite the base (3), and a seal (6), wherein the base (3) has a planar design at least in one region of the support of the seal (6), and the base (3) has a reflective surface (4) which is provided such that Raman excitation light incident through the measuring window (5) is reflected on the reflective surface (4) in a directed manner such that the background signal in a Raman measurement is reduced and the Raman signal of a particle in a suspension is increased. The invention further relates to a microscope which has such a liquid cell.

A method for aggregating a cluster of particles having a target cluster constitution in a channel comprising a retention section comprises the steps of establishing a fluid stream comprising a fluid carrier medium and particles of at least one type through said channel; controlling a supply of said particles of at least one type into the fluid stream; operating a retention mechanism to aggregate at least part of said particles in an aggregation region within said retention section, to thereby form said cluster of particles; monitoring, while operating said retention mechanism, the particles in at least part of said channel for obtaining a monitoring signal associated with the cluster and/or with the particles moving in the fluid stream; determining a current cluster constitution from the monitoring signal; comparing said current cluster constitution with said target cluster constitution; and controlling at least one of said particle retention mechanism and said supply of said particles of at least one type, such that said current cluster constitution approaches said target cluster constitution.

The present invention relates to the field of genetic engineering, particularly to a recombinant expression vector for rapidly screening the high expression strains and a method for rapidly screening high expression strains. In the invention, an exogenous red fluorescent protein and Aspergillus fumigatus cell surface protein localization signal are fused and expressed, and the fusion gene (DsRed-AfMP1) is integrated into the genome of Trichoderma reesei, so as to construct a strain displaying red fluorescent protein on the surface of Trichoderma reesei. By sorting Trichoderma reesei strains with red fluorescent protein on the surface by flow cytometry, genes beneficial to the improvement of cellulase activity can be quickly isolated.

A method for parallel determination of contrasting particles on a membrane when analyzing an accumulation of particles on the same membrane using an optical microscope is provided. The method involves increasing the transparency of the membrane to light radiation before analyzing particle accumulation.

An optical method of characterizing an object comprises providing an object to be characterized, the object having at least one nanoscale feature; illuminating the object with coherent plane wave optical radiation having a wavelength larger than the nanoscale feature; capturing a diffraction intensity pattern of the radiation which is scattered by the object; supplying the diffraction intensity pattern to a neural network trained with a training set of diffraction intensity patterns corresponding to other objects with a same nanoscale feature as the object to be characterized, the neural network configured to recover information about the object from the diffraction intensity pattern; and making a characterization of the object based on the recovered information.