321 results about "Cell counting" patented technology

The invention relates to the technical field of biological information, in particular to a stem cell culture information management method and system. The method comprises the following steps: collecting culture process basic data in a stem cell culture process, wherein the culture process basic data comprises cell counting data, culture condition parameter data and pollution condition data; performing growth kinetic analysis on the basic data in the culture process to obtain cell growth characteristic data; establishing a cell growth prediction model based on the cell growth characteristic data, and generating cell growth early warning data; and monitoring the culture process in real time according to the cell growth early warning data, triggering an early warning signal when abnormal fluctuation is detected, and generating a culture abnormality processing scheme. The growth prediction model is established based on the cell growth characteristic data, the culture dynamic state can be monitored in real time, an early warning signal is provided, the detection and response speed of abnormal fluctuation is remarkably improved, and culture failure is avoided.

The present disclosure provides systems and methods for analyzing a mixed population of cells. In particular, the present disclosure provides systems and methods for digital cytometry of a biological sample, digital analysis of a biological sample, digital purification of a biological sample, evaluation of a disease in an individual, and prediction of a clinical outcome of a disease therapy.

The invention discloses an inertial micro-fluidic chip integrating cell focusing and sorting and a preparation method thereof. The inertial micro-fluidic chip comprises a cover plate layer, a runner layer and a substrate layer, a chip inlet, a first chip outlet and a second chip outlet are formed in the cover plate layer; the flow channel layer is provided with a sample liquid flow channel inlet, a first flow channel outlet and a second flow channel outlet, the chip inlet is communicated with the sample liquid flow channel inlet, the first chip outlet is communicated with the first flow channel outlet, and the second chip outlet is communicated with the second flow channel outlet. The flow channel layer is provided with a spiral cell sorting flow channel and a cell focusing flow channel, the front end of the spiral cell sorting flow channel is communicated with a sample liquid flow channel inlet, the tail end of the spiral cell sorting flow channel is communicated with the cell focusing flow channel and a first flow channel outlet, and the tail end of the cell focusing flow channel is communicated with a second flow channel outlet. Through a microfluid vortex focusing technology and a spiral flow channel inertia sorting technology, accurate sorting and focusing of cells are realized, and the problems that the focusing state of the sorted cells is influenced and the cell counting detection precision is low are effectively solved.

Methods, systems, and devices for enumerating the number of cells present in each event for cell-secretion based sorting applications are described herein. The cell secretion applications use carrier to encapsulate cells and collect the biomolecules they secrete. The carriers are then sorted using flow based particle sorting. The total number of cells present in a carrier is very important for several applications. A convolutional neural network is used to count the number of cells present from a brightfield image, and outputs the information to be used as part of the sort logic.

The invention relates to the technical field of medical informatics and artificial intelligence technology cross application, in particular to a dynamic intelligent prediction system for HIV infected person immune reconstruction insufficiency. Comprising a data acquisition and management module, a data preprocessing and feature engineering module, a Bayesian joint modeling core module, a dynamic prediction calculation module, a multi-dimensional verification and evaluation module and a clinical application service module. According to the method, on the basis of large-sample multi-center longitudinal follow-up visit data, a Bayesian shared parameter dynamic joint model is adopted, the dependency relationship between dynamic trajectories of immune indexes such as cell counting and the like and IIR occurrence time is captured, real-time risk prediction is achieved through a sequential Bayesian updating mechanism, and through multi-dimensional verification, the risk prediction accuracy is improved. The method has the advantages that the performance is better than that of an expert-driven model, expert experience pre-judgment and 19 mainstream machine learning algorithms, an individualized conclusion with a confidence interval can be output, clinical decision is assisted, prediction is promoted to be clinical from scientific research, and the method has important application value and popularization prospect.

The embodiment of the invention is suitable for the technical field of biomedicine and image processing, and provides a cell counting method and device and computer equipment, and the method comprises the steps: collecting an adherent stem cell image; segmenting the adherent stem cell image by using a detection segmentation model obtained by training to obtain a plurality of stem cell masks; determining the number of stem cells contained in the adherent stem cell image according to the plurality of stem cell masks; wherein the detection segmentation model comprises a backbone network structure, a convolution layer in the backbone network structure is a multi-layer pyramid convolution, and the multi-layer pyramid convolution is used for extracting multi-scale feature information in the adherent stem cell image. By adopting the method, the adherent stem cells can be rapidly and accurately counted.

The invention relates to the technical field of medical treatment, and particularly discloses a compound prognosis model for cancer prognosis evaluation, a prognosis evaluation method and a calculator. The compound prognosis model is constructed based on inflammation burden related prognosis indexes ALNCR and TNM by stage combination; the creation method comprises the following steps: step 1, collecting albumin concentration, lymphocyte count, neutrophil count and C-reactive protein concentration data of a cancer patient; 2, calculating an ALNCR index according to a formula; 3, according to a clinical classic TNM staging system, the patients are divided into a TNM staging stage I, a TNM staging stage II, a TNM staging stage III or a TNM staging stage IV; 4, the ALNCR index obtained in the step 2 and the TNM staging result obtained in the step 3 are associated and integrated, and the individualized prognosis score of the ALNCR.TNM composite prognosis model is obtained through calculation. The method is suitable for clinical rapid application; high-risk patients can be accurately distinguished, a quantitative basis is provided for individualized treatment and follow-up visit strategy formulation, and excessive medical treatment or insufficient treatment is reduced.

The present disclosure relates generally to an autonomous cell imaging and modeling platform, and more specifically to machine-learning techniques for using microscopy imaging data to continuously study live biological cells. The autonomous cell imaging and modeling platform can be applied to evaluate various cellular processes, such as cellular differentiation, optimization of cell culture (e.g., in-plate cytometry), disease modeling, histopathology imaging, and genetic and chemical screening, using a dynamic universal imaging system. In some embodiments, the platform comprises a set of label-free computational imaging techniques, self-supervised learning models, and robotic devices configured in an autonomous imaging system to study positional and morphological characteristics in particular cellular substructures of a cell culture in an efficient and non-destructive manner over time.

According to the cell fixing liquid, phenol oxidase is used for catalyzing phenol to be oxidized into a quinone structure, the quinone structure reacts with protein amido to form light covalent immobilization, cell immobilization is achieved, a stable hydration environment and membrane protection are provided through the ionic liquid solvent choline dihydrogen phosphate, a phosphate-free buffer system is provided, and cell immobilization is achieved. Therefore, a novel cell fixing liquid is obtained, the cell structure integrity required by cell imaging analysis is effectively reserved, meanwhile, cell staining fluorescence signal interference is avoided, and therefore the accuracy of cell counting and cell imaging analysis is ensured.

The invention discloses a phycomycete composite biological fertilizer for an arid loess area as well as a preparation method and application of the phycomycete composite biological fertilizer, and belongs to the technical field of biological fertilizers. The phycomycete composite biological fertilizer is prepared from nitrogen-fixing anabaena and acinetobacter, counted by a single cell, the total viable count of the anabaena azotica is greater than or equal to 1.0 * 10 < 6 > CFU / mL, and the total viable count of the acinetobacter is greater than or equal to 1.0 * 10 < 7 > CFU / mL. Experiments prove that the phycomycete composite biological fertilizer can significantly improve the germination potential and germination rate of crop seeds, promote seedling growth, improve the nutritional quality of crops and reduce the death rate of seedlings, is suitable for various crops such as wheat, Shanghai Qing and peas, and has important application value in agricultural production in arid regions.

Various examples relate to determining a number and / or a confluency of cells in a microscopy image. To that end, the microscopy image is firstly rescaled and then processed.

The invention belongs to the field of deep learning and medical image analysis, provides a glioma stem cell image segmentation method and system, and aims to solve the problems that glioma stem cells are high in morphological heterogeneity, fuzzy in boundary and prone to missing detection of tiny targets. On the basis of a deep learning network model framework, three-stage improvement is carried out: in a preprocessing stage, a dynamic data enhancement strategy is introduced, and image enhancement is carried out on a pathological image through combination of CLAHE and a Gaussian filtering algorithm; in the feature extraction stage, a bidirectional feature pyramid network (BiFPN) and a BiFPN module are adopted to realize efficient fusion of cross-scale features, and more accurate cell image segmentation and cell counting are realized.

The invention provides a micro-fluidic biosensor array, and relates to the technical field of sewage detection, the micro-fluidic biosensor array comprises a flow channel layer, a first detection layer and a second detection layer which are sequentially stacked from top to bottom; a flow channel structure is arranged in the flow channel layer, a micro-column array is arranged in the flow channel structure, and the micro-column array is used for generating a gradient resistance field for flowing liquid; the first detection layer is provided with a liquid inlet, the liquid inlet is used for receiving liquid discharged from the flow channel layer, the first detection layer comprises a three-dimensional interdigital electrode array and a micropore array modified by a quantum dot labeled antibody probe, and the three-dimensional interdigital electrode array is used for capturing and dissolving organic matter molecules; the second detection layer comprises a fluorescence detection module and an electrochemical detection module, the fluorescence detection module is used for carrying out cell counting and fluorescence signal acquisition on target microorganisms captured by the micropore array, and the electrochemical detection module is used for realizing directional enrichment and concentration detection of heavy metal ions. By means of the micro-fluidic biosensor array, sewage detection of multiple types of parameters can be achieved.

The invention discloses a method for obtaining a sorted and purified autoimmune vaccine, which comprises the following steps: S1, extracting 30ml of autologous blood sample of a patient, and sorting to obtain CD34 + cells; s2, carrying out flow analysis on the CD34 + cells to ensure that CD34 + is greater than or equal to 90%, counting by using a counting instrument, and adjusting the concentration of the CD34 + cells to be 1 * 106 / mL; s3, the extracted cells are placed in a 42 DEG C constant-temperature water bath kettle for heat shock treatment, and the heat shock treatment lasts for two hours; s4, collecting the cells obtained in the step S3, transferring the cells into liquid nitrogen at-196 DEG C and a water bath kettle at 37 DEG C, and repeatedly freezing and thawing for multiple times; s5, collecting after detecting that no living cells exist by using a cell counter, and centrifuging for 10 minutes at the rotating speed of 6000 r / min under the centrifugal condition of 4 DEG C; s6, after the centrifugation is finished, discarding the supernatant and leaving the precipitate, and resuspending by using normal saline; and S7, irradiating 200 GY through gamma rays for 60 minutes, collecting the sample, sending the sample, and inspecting the sample for later use after the sample is qualified.

The present invention provides an online purification and sampling and visualized automatic enrichment apparatus and method for deep-sea microorganisms. Through online sample pretreatment during microorganism sampling, automatic biological concentration and purification, online monitoring of environmental indicators during biological enrichment, online observation of biomass, and automatic enrichment and transfer of high-purity enriched materials, the present invention overcomes the shortcomings of the prior art, such as difficulties in purifying deep-sea microorganism samples under high-pressure environments, complex manual operations for enrichment and observation, low timeliness of biomass observation, and difficulties in real-time cell counting of the enriched materials. This effectively increases the enrichment rate and acquisition efficiency of difficult-to-culture deep-sea microorganisms, providing a fundamental way for enhancing deep-sea biological research and bioresource development efficiency.

The invention relates to the technical field of thallus quantity detection, in particular to a primer pair and a kit for detecting the number of lactobacillus brevis thalli in a postbiotic preparation and application of the primer pair and the kit. The primer pair provided by the invention has the advantages of strong specificity and high amplification efficiency, and can be used for carrying out qPCR quantitative detection on the quantity of lactobacillus brevis in the metastatic preparation. As the traditional flow cytometry and the plate cell counting method are not suitable for detecting the number of thalli in the metagen preparation, the qPCR quantitative method provided by the invention can be used for rapidly and accurately carrying out quantitative analysis on the number of lactobacillus brevis thalli in the metagen in a relatively short time, and the result is compared with a plate counting result; compared with the prior art, the qPCR counting method has the advantages that the detection result difference does not exceed one order of magnitude, counting does not distinguish viable bacteria and dead bacteria, and the qPCR counting method has the advantages of high specificity and high speed and can make up the limitation that a plate counting method is suitable for viable bacteria counting, so that the qPCR counting method provided by the invention has more advantages in the application of metagen counting.

The invention belongs to the field of pesticide poisoning prognosis, and particularly discloses a method for establishing an acute diquat pesticide poisoning prediction death risk index, which comprises the following steps: collecting data; establishing a death risk index model based on demographic characteristics and blood routine test results; and carrying out model training, internal verification and external verification. The death risk index provided by the invention comprehensively considers age, diquat blood concentration, leukocyte count and glutamic oxalacetic transaminase concentration, and aims to accurately evaluate the death risk of acute diquat pesticide poisoning patients in an index form. Through deep analysis of large-scale clinical data, the death risk index of the invention not only has scientificity and accuracy on the data level, but also can play an important role in clinical practice, can be applied to construction of acute diquat pesticide poisoning death risk prediction terminal equipment, helps medical teams to distribute medical resources more reasonably, and has a good application prospect. High-risk patients are preferentially processed, so that the overall treatment effect and the survival opportunity of the patients are improved.

The invention discloses a urine detection method based on lensless microscopic lamination imaging, which comprises the following steps of: acquiring a low-resolution image of a urine sample by using a lensless microscopic lamination imaging device, calculating an incident wave vector to obtain a light field, and performing Fourier transform on the light field; smooth processing is carried out through Gaussian filtering, and image enhancement is carried out through Laplacian sharpening; using the low-resolution image to obtain a final large-view-field high-resolution image through iterative updating; adaptive threshold segmentation is carried out on the image, and then cells and a background are separated to obtain a segmented image; performing edge detection on the image by using a Canny operator to output the image; carrying out edge detection on each pixel point by using a non-maximum suppression method, and segmenting by using double thresholds; and performing cell counting on the image after edge detection, calculating the cell density, and finally outputting the identified and calculated information. The improvement of the method is expected to promote wide application of lensless microscopic lamination imaging in urine detection.

This disclosure concerns a cytometry system including a handling system that enables presentation of single cells to at least one laser source. The laser source is configured to deliver light to a cell within the cells in order to induce bond vibrations in the cellular DNA. The system further includes a detection facility that detects the signature of the bond vibrations, wherein the bond vibration signature is used to determine the folding or packing of the DNA.

The described invention is a cell counting device for counting target cells within a fluid, the device comprising: a microfluidic channel configured to receive a flow of a cell-containing fluid through an inlet and conduct the flow of the cell-containing fluid along the channel, the microfluidic channel sized such that target cells within the cell-containing fluid flow consecutively through the microfluidic channel; a first photodetector arranged to receive light that has passed through the microfluidic channel at a first measurement point, such that signal from the photodetector varies due to the received light being restricted by the passage of cells across the first measurement point in the microfluidic channel; a processing unit configured to receive a signal from the photodetector and distinguish the size of a cell passing the first measurement point based on an interruption time during which the signal intensity received from the photodetector is reduced, thereby determining the presence of a target cell type. Using an optical interruption signal in this way, provides a low cost device that does not require fluorescent dyes to label the cells nor does it require lasers, microscopes or other specialist equipment such that the device is suitable for point-of-care and at-home use and does not require the direction of a trained specialist operator.

The present invention belongs to the technical field of counting devices, specifically an organic photovoltaic cell counting device and method thereof, which solves the problem of error defects in counting through photoelectric sensors. The device comprises a feed conveyor and a discharge conveyor, wherein a transfer counting component is provided between the feed conveyor and the discharge conveyor, and the transfer counting component comprises a supporting circular table provided between the feed conveyor and the discharge conveyor, and a rotating transfer member for cell transfer is provided on the outer side of the supporting circular table. When the supporting circular table moves downward, the baffle plate moves downward to close the end of the feed conveyor, thereby preventing subsequent organic photovoltaic cells from continuing to move, ensuring that the organic photovoltaic cells can be transferred and counted in sequence, and improving counting accuracy.

We provide a system and method for autofocus and automated cell counting. [Solution] A system and method for autofocus using artificial intelligence includes (i) capturing multiple monochrome images over a nominal focal range, (ii) identifying one or more connected components within each monochrome image, (iii) sorting the identified connected components based on the number of pixels associated with each connected component, (iv) generating focus quality estimates for at least some of the sorted connected components using a machine learning module, and (iv) calculating a target focal position based on the focus quality estimates of the evaluated connected components. The target focal position can be used to perform cell counting using artificial intelligence, for example, by (i) generating seed likelihood images and whole cell likelihood images based on the output of a convolutional neural network, and (ii) generating a mask indicating the quantity and / or pixel location of objects based on the seed likelihood image.

The invention discloses a blood cell counting device. The blood cell counting device comprises a front tank, a rear tank, a counting hole, at least one detection assembly and a control assembly, wherein the front tank is communicated with the rear tank through the counting hole; the at least one detection assembly is adjacent to the front tank and / or the rear tank; the control assembly is connected with the detection assembly. When blood cell counting is carried out on a to-be-detected sample, the control assembly is used for controlling the detection assembly to detect the liquid level position of the to-be-detected sample and controlling the blood cell counting device to stop blood cell counting when the liquid level position reaches a preset position. Through the blood cell counting device, blood cell counting can be carried out on the to-be-detected sample, and when the liquid level position of the to-be-detected sample in the front pool and / or the rear pool reaches the preset position, it can be determined that the to-be-detected sample with the fixed volume flows through the counting hole, and due to the fact that the to-be-detected sample with the fixed volume contains cells with the fixed particle number, the counting accuracy is improved. The influence on the counting result caused by factors such as the blockage of the counting hole and the size of the counting hole can be avoided, and the counting result is relatively accurate.

Systems and methods for autofocus using artificial intelligence include (i) capturing a plurality of monochrome images over a nominal focus range, (ii) identifying one or more connected components within each monochrome image, (iii) sorting the identified connected components based on a number of pixels associated with each connected component, (iv) generating a focus quality estimate of at least a portion of the sorted connected components using a machine learning module, and (iv) calculating a target focus position based on the focus quality estimate of the evaluated connected components. The calculated target focus position can be used to perform cell counting using artificial intelligence, such as by (i) generating a seed likelihood image and a whole cell likelihood image based on output—a convolutional neural network and (ii) generating a mask indicative quantity and / or pixel locations of objects based on the seed likelihood image.

An analytical method of and system for monitoring cell status whereby excitation energy is focused to an excitation cytometry volume in a cell sample to fluoresce first and second fluorophores of a cell. Fluorescence signals from the first and second fluorescing cell fluorophores are directed to a detection subsystem. A first peak in fluorescence intensity for the first fluorophore is detected as is a second peak in fluorescence intensity for the second fluorophore. The fluorescence signals are processed to identify when the first and second peaks occur substantially simultaneously indicating the presence of a cell at the excitation cytometry volume instead of background fluorescence and in response, the cellular status of the cell is measured using the intensity of the levels of the first and second peaks.

1. Name of the product of this design: Electronic device with a graphical user interface for a cell counter operating program. 2. Purpose of the product of this design: an electronic device used for a cell counter. 3. The design highlights of this design product are the graphical user interface of the cell counter operating program. The hardware design part and the rest are conventional designs. 4. The picture or photo that best illustrates the design points: Interface change state diagram 3. 5.Purpose of Graphical User Interface: It is the interactive interface when operating the cell counter. 6. Description of the changing states of the graphical user interface: The main view shows the main interface, which displays all the functions of the software; Interface change state Figure 1 is the graphical user interface after clicking the "Cell Count" option in the main view, which is the insert sample bar prompt interface, prompting the user to insert a sample bar; Interface change state Figure 2 is the graphical user interface after clicking the "OK" option in interface change state Figure 1, which is the new program interface for setting program parameters; Interface change state Figure 3 is the graphical user interface after clicking the "Start" option in interface change state Figure 2, which is the result interface, displaying the test results; Interface change state Figure 4 is the graphical user interface after clicking the "Dia graph" option in interface change state Figure 3, which is the diameter graph interface, displaying the diameter histogram.

A non-transitory, processor-readable medium stores instructions that, when executed by a processor, cause the processor to receive, at a first time, a first data array associated with a first cytometric instrument. The first data array includes a set of scatter signal datapoints that includes data representing: at least one low forward scatter signal output, at least one high forward scatter signal output, at least one low side scatter signal output, and at least one high side scatter signal output. At a second time subsequent to the first time, a cytometric instrument parameter is adjusted based on the first data array, and / or a first cytometric measurement of the first cytometric instrument is reconciled with a second cytometric measurement of a second cytometric instrument different from the first cytometric instrument, based on at least one of the first data array or a second data array associated with the second cytometric instrument.

The application discloses an automatic cell counter and belongs to the technical field of cell counters. The automatic cell counter comprises a cell counter body, a lifting assembly, an assembly plate and a transverse position adjusting assembly. The bottom of the cell counter body is provided with an assembly groove. The lifting assembly is installed in the assembly groove and drives the assembly plate to move up and down. The automatic cell counter drives two middle plates to linearly move in opposite directions along guide frames through the transverse position adjusting assembly, so that the distance between the two middle plates is adjusted to adapt to cell culture dishes with different diameters. The first tooth plate is driven to move along the first guide rod through power. When the first tooth plate moves, the first tooth plate is engaged with the gear, and then the second tooth plate is synchronously driven to move, so that the two clamping rollers are synchronously moved to the cell culture dish, the clamping of the cell culture dishes with different diameters is completed, the clamping components need not be replaced, and the operation complexity and the workload of users are reduced.

This application relates to a storage device, a memory device, and a method of operating the memory device. A memory device includes a plurality of memory cells, peripheral circuitry, and control logic. The peripheral circuitry performs a first read operation on a selected memory cell using a plurality of read voltages. In the first read operation, the control logic controls the peripheral circuitry to perform a cell counting operation, adjusting the remaining read voltage among the plurality of read voltages based on a read offset table and a cell count as a result of the cell counting operation, and performing the first read operation on the selected memory cell using the remaining read voltage. The control logic executes, in parallel among a plurality of consecutively executed read operations, a read data output operation of a second read operation performed prior to the first read operation and a cell counting operation corresponding to the first read operation.

The invention relates to the technical field of image processing, and discloses a cell counting method, device and equipment, a storage medium and a program product, the method comprises the following steps: acquiring cell images and cell marking information corresponding to the cell images one by one; inputting the cell image into a pre-constructed cell prediction model to obtain cell prediction point information corresponding to the cell image; the cell prediction point information comprises cell prediction point position information and confidence values in one-to-one correspondence with cell prediction points; based on the cell marking information and the cell prediction point information, performing one-to-one matching on the reference points corresponding to the cell image and the cell prediction points to obtain a matching result; and adjusting a cell prediction model based on the matching result, wherein the cell prediction model is used for predicting the cell position and the cell number. The cell prediction model is obtained through training, counting and positioning of the cells can be achieved at the same time, and the positioning precision and counting performance of the cells are effectively improved.