71 results about "Cell number" patented technology

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 discloses a preparation method and application of a photo-thermal biosensor for tumor cell quantification and vitality dual-index liquid biopsy. Phosphatidylserine (PS) is exposed by enriching and cracking tumor cells, is identified and combined by an aptamer Apt2, and is driven to be separated from Apt2-Cu2-xTe NSs; after magnetic separation, separated supernatant is subjected to photo-thermal detection; the photo-thermal signal intensity is positively correlated with the number of cells, so that quantitative detection is realized; during cell apoptosis, PS is turned out of the membrane, Apt2-Cu2-xTe NSs is combined with the surface of the membrane, separated supernatant is subjected to photo-thermal detection after magnetic separation, and the photo-thermal signal enhancement amplitude is in negative correlation with cell activity. The platform has the advantages of POCT characteristics, low cost and portability, and a new tool is provided for precise tumor diagnosis and treatment.

The invention relates to the technical field of lithium ion battery safety monitoring, and discloses a method and a device for early warning and positioning thermal runaway of a lithium ion battery pack in advance. The method comprises the following steps: firstly, collecting real-time voltage, temperature, current and serial number data of each battery cell, and constructing a battery cell state observation tensor with a time-space label; running a battery cell thermoelectric state extended Kalman estimation algorithm based on the tensor to generate a battery cell health state partial sequence lattice; and then constructing a thermal runaway risk propagation phase space grid, finally executing manifold analysis-based local attractor region identification and early warning decision under the constraint of the grid, and outputting a high-risk source cell number and an early warning level. According to the invention, the problems of early warning lag, lack of cell group state consistency dynamic evaluation and incapability of accurately positioning fault cells caused by dependence on later physical symptoms in the prior art are solved, and the thermal runaway early warning timeliness and positioning accuracy are improved.

In a bioprinting system and method, a bioprinter may include one or more reservoirs, a printhead, and a print surface on which the bioprinting is dispensed. An optical system may collect imaging data of a plurality of cells within a cross-linkable material during and / or after passage of the plurality of cells through the bioprinting system. A computing system may generate, via a machine learning algorithm executing on the image data, a plurality of segmented regions in the image data, wherein each segmented region in the plurality of segmented region defines a boundary around a different set of cell aggregates in the plurality of cells, identify a first segmented region in the plurality of segmented regions that defines a boundary around at least a visible portion of a first cell aggregate, wherein the first cell aggregate includes an occluded portion, determine, based on an estimated shape of the first cell aggregate, an extrapolated boundary around at least some of the visible portion of the first cell aggregate and at least some of the occluded portion of the first cell aggregate, compute a quantity of cells within the first cell aggregate based on an area surrounded by the extrapolated boundary, and determine one or more parameters associated with the plurality of cells, the material flow, or the bioprinting system based on the quantity of cells.

The present invention discloses a method for simulating the tumor blood vessel growth process, comprising constructing a two-dimensional discrete coordinate system based on a two-dimensional tumor model and defining a blood vessel index function that describes the cell grid properties of the cell grid; updating the cell number, oxygen concentration, fibronectin concentration, and growth factor concentration of each cell grid at preset intervals t; predicting the movement direction of the blood vessel tip within the current time period t based on the fibronectin concentration and growth factor concentration; calculating a first predicted extension distance and a second predicted extension distance based on the movement direction within the current time period t and the movement direction within the previous time period t; and updating the cell grid properties of each cell grid in the two-dimensional discrete coordinate system based on the movement direction within the current time period t, the vessel tip's existence time, and the movement extension distance calculated from the vessel tip. The present invention incorporates oxygen concentration and cell number into the tumor blood vessel growth model to achieve accurate simulation and prediction of the tumor blood vessel growth process.

Embodiments of the disclosure provide bandwidth adjustment method applicable to sending end, the sending end periodically sends cells to receiving end, and a number of cells sent in each period is n, where n is an integer greater than or equal to 2; in each period, the sending end occupies a cell having a number that is within a bearer cell group of the sending end, the occupied cell is capable of carrying service information, and the method includes: sending adjustment information including adjustment operation to the receiving end, with the adjustment operation being adding a cell number to be adjusted to the bearer cell group of the sending end, or deleting the cell number to be adjusted from the bearer cell group of the sending end; and receiving confirmation information sent by the receiving end, and performing the adjustment operation. Embodiments of the disclosure further provide a terminal.

A method, apparatus, and system for calculating cell concentration are disclosed. The method includes: determining an effective measurement region of a cell container, the cell container including a first encapsulation layer, a second encapsulation layer, and a solution cavity disposed between the first and second encapsulation layers; a first positioning mark is disposed on one side of the first encapsulation layer facing the solution cavity, and a second positioning mark is disposed on one side of the second encapsulation layer facing the solution cavity; dividing the effective measurement region into multiple sub-regions; focusing and acquiring an image of each sub-region; detecting the number of cells in each image and summing the number of cells in multiple images to obtain the total number of cells in the effective measurement region; focusing on the first and second positioning marks to obtain a first original cavity thickness; multiplying the first original cavity thickness by a preset adjustment coefficient to obtain an adjusted cavity thickness; calculating the volume of the effective measurement region based on the adjusted cavity thickness; and calculating the cell concentration based on the total number of cells and the volume of the effective measurement region.

This invention discloses a single-cell spatial annotation method that integrates image and sequencing data. It obtains candidate cue point locations, cell nucleus instance segmentation masks, and cell nucleus type probability vectors by processing full-field H&E stained tissue images. It also obtains a preprocessed spatial transcriptome raw sequencing matrix and corresponding cell type labels by processing the raw spatial transcriptome sequencing matrix. Each capture site and its corresponding integrated data structure are constructed. Based on rigid constraints on the number of cells allocated to each type within each capture site and main type quota constraints, the main type annotation is written. For cells in the intercapture zone, one or more neighboring capture sites with existing annotation results are found. The main type and cell subtype of the intercapture zone cells are inferred through morphological feature similarity calculation, thus obtaining the annotation result. This solves the problem that existing technologies cannot determine the exact type of each cell in ST-sequencing tissue.

A method of using the relaxation rate (R1 and / or R2) of solvent NMR signal to non-invasively estimate cell counts in cell cultures prepared under similar conditions as well as to use wNMR to measure cell viability. The methods can simply, rapidly, and non-invasively monitor the growth, health, and aging status of a cell culture, without any sample preparation or reagent (e.g., a dye) addition.

An automatic liquid handling device comprises: a deck, located at the bottom, for accommodating one or more racks; a pipetting device, placed above the deck, capable of three-dimensional movement by an actuator, for aspirating and dispensing samples by coupling pipette tips to a probe; a tip optical system, mounted on the deck, for imaging a cell mixture aspirated into the pipette tip from a sample container at the counting position; a cooling module that holds a sample container accommodating a cell mixture containing cells or cell clusters, to keep the cell mixture cool; and a control module for calculating the number of cells based on the taken image of the cell mixture aspirated into the pipette tip and controlling the operation of the pipetting device according to a pre-programmed method, wherein the control module calculates the number of cells on the basis of the taken image of the pipette tip.

The invention provides a battery cell installation detection method, system and device and a storage medium, and relates to the technical field of battery manufacturing, and the method comprises the steps: obtaining a detection signal triggered by a to-be-detected battery cell module at a detection station, and recognizing the key features of the to-be-detected battery cell module; based on the key features, obtaining the cell number, the cell polarity arrangement sequence and the cell placement angle of the to-be-detected cell module, and judging the installation result of the to-be-detected cell module according to the cell number, the cell polarity arrangement sequence and the cell placement angle; if the installation is qualified, conveying the current battery cell module to the next process; if the installation is not qualified, conveying the current cell module to a manual detection station, and generating an abnormal installation picture; and conveying the battery cell module processed at the manual detection station to the detection station for re-detection. In this way, the battery cell modules which are recognized to be abnormal are conveyed to the manual detection station, the mounting abnormity picture is displayed for troubleshooting, meanwhile, the next group of battery cell modules continues to be detected at the detection station, and automatic and efficient mounting detection of batched battery cells is achieved.

1. Name of the product in this design: Cell Measurement Plate. 2. Purpose of this design: This design is used to hold cell fluid for calculating cell count. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D rendering 1. 5. Other situations requiring explanation: The entire product of this design is made of transparent material.

The present invention relates to a sampling chamber measurement method, device, computer equipment and storage medium. The measurement device includes a chamber body and a sampling needle with a part disposed in the chamber body; it also includes a light source and a detector. The present invention also provides a sampling chamber measurement method, including steps: calculating the initial sample volume; calculating the sample volume at the current moment; calculating the current sample running speed; calculating the number of cells that can be sorted; calculating the total number of cells to be sorted theoretically. By setting the light source and the detector, the detection light emitted by the light source undergoes refraction or scattering after passing through the container and the sample. According to the state of the sample, detection light with different signal intensities can be obtained. Based on the data such as the detection light with different signal intensities, the number of detectors, and the container volume, the initial sample volume, the sample volume at the current moment, the current sample running speed, the remaining sample running time, the number of cells that can be sorted, and the total number of cells to be sorted theoretically can be calculated in sequence.

The invention provides a single cell ATAC sequencing library construction method and a kit, the construction method comprises the following steps: (1) subpackaging a cell sample into a porous plate, adding a mixed solution containing a first transposon and a second transposon into each pore, and co-incubating to obtain a cell containing fragmented DNA; (2) carrying out splitting decomposition on the cells containing the fragmented DNA, and retaining the fragmented DNA; and (3) amplifying the fragmented DNA to obtain the sequencing library. The construction method is high in transposition efficiency, not limited by a microfluidic or microwell plate platform, appropriate in label combination information amount, low in requirements for the cell number, the cell type and the tissue state, suitable for a conventional double-end sequencing platform, high in sequencing data quality and high in application value.

The invention discloses a cell voice mode switching method and device and computer equipment. The method comprises the following steps: respectively acquiring packet loss rate data and measurement report data of a plurality of users in a network slice; associating the packet loss rate data with the cell number and the measurement report data to obtain an initial data set; deleting data in the initial data set in the cell switching time period to obtain a processed data set; screening users with unchanged positions in a preset time period in each cell from the processed data set, and determining the users as target users; determining a reference signal receiving power fluctuation curve of the target user of each cell according to the reference signal receiving power of the target user, and determining a reference signal receiving power threshold value of each cell based on the reference signal receiving power fluctuation curve of each cell; and switching the voice mode of each cell according to the reference signal receiving power threshold value of each cell.

The embodiment of the invention provides a communication method and device, relates to the field of communication, and is used for reducing the situation that CSI-RS measurement resources of different network devices conflict and improving the accuracy of a CSI-RS measurement result. In the method, a first network device can determine a resource of a reference signal of a first cell according to a first cell number uniquely identifying the first cell of the first network device, and send the reference signal to a terminal device in the first cell according to the resource of the reference signal of the first cell. The first cell belongs to one of the plurality of cells, and the resource of the reference signal of each cell in the plurality of cells can be determined according to the respective cell number of each cell, and based on the unique cell number corresponding to each cell in the plurality of cells, the resource of the reference signal of each cell in the plurality of cells can be determined. According to the embodiment of the invention, the resources of the reference signal corresponding to each cell in the plurality of cells are different, and the condition that the reference signal measurement resources of different network devices and different cells of the same network device conflict is reduced.

The invention discloses an entry mode determination method and device and electronic equipment. The method comprises: obtaining a network element group table corresponding to a plurality of traffic modes, the network element group table comprising at least one of the following: a base station cell number, a cell name and a scene name corresponding to the traffic mode; base station cells occupied by foreign entry tourists in a preset entry time period are determined from mobile depth data packet detection (DPI), a tourist entry time trajectory table is obtained, and the tourist entry time trajectory table at least comprises the base station cells occupied by the foreign entry tourists and geographical location information corresponding to the base station cells occupied by the foreign entry tourists; and according to the geographical location information in the tourist entry time trajectory table and the geographical location information corresponding to each cell name in the network element group table, determining the traffic mode used by the foreign entry tourists during entry. According to the invention, the technical problem of misjudgment of an entry mode caused by incomplete base station network element group information of a traffic scene in related technologies is solved.

The invention discloses an influence parameter optimization method and device for a cascaded SOFC system, the method is applied to the cascaded SOFC system, and the method comprises the steps: obtaining influence parameters of the cascaded SOFC system, the influence parameters at least comprising a battery number ratio and a shunt ratio of a first-stage electric pile and a second-stage electric pile; the influence parameters are sequentially changed, a pre-established target system model is utilized, the system electric efficiency and the average net power under the condition that the influence parameters are changed are calculated, the target system model is established according to the net alternating current power of the system, and the net alternating current power of the system is determined at least according to the total power generation power of the first-stage electric pile and the second-stage electric pile; and screening a target influence parameter from the changed influence parameters according to the calculated system electrical efficiency and the calculated on-chip net power. According to the method, the influence parameters of the cascaded SOFC system can be optimized, so that the requirements of different application scenes can be met, the electric efficiency of the cascaded SOFC system is effectively improved, and the operation cost is reduced.

The present invention relates to the field of biomedicine and particularly provides a method for identifying a target. The method specifically comprises determining the number of target-adjusting systems of a plurality of cells to be tested to determine the influence of adjusting a candidate target on cell function; and before and / or during the determination, adjusting the expression or activity of the candidate target in said plurality of cells by means of the plurality of target-adjusting systems, wherein each of the target-adjusting systems targets a different candidate target site, and during the determination, the number of said cells is at least 5 times the number of the target-adjusting systems. Further provided is a system for identifying a target.

The application relates to the technical field of biochemistry, and provides a cell counting method and a cell counting device of a micro-fluidic chip. The cell counting method of the micro-fluidic chip comprises the following steps: controlling a cell solution to fill a plurality of flow channels with height differences; collecting a target image corresponding to a set region in each flow channel, obtaining a cell clumping rate corresponding to each flow channel based on the target image, and determining a flow channel with the lowest cell clumping rate as a calculation flow channel; wherein the cell clumping rate is the ratio of the number of cell groups in the set region to the total number of cells; obtaining a calculation cell number in a target region of the calculation flow channel; obtaining a preset volume corresponding to the target region based on the area of the target region and the height of the calculation flow channel, and determining the ratio of the calculation cell number to the preset volume as the concentration of the cell solution. The cell counting method of the micro-fluidic chip provided by the application provides the cell solution with a flow channel with a suitable height, so that the cell solution is uniformly distributed in the flow channel as much as possible, and the cell counting accuracy is higher.

The tumor cell migration characteristic analysis method, device, storage medium and related equipment provided in the present application can, when analyzing the migration characteristics of tumor cells, first obtain the fluorescent microscopic image corresponding to the tumor cells in the migration channel at each preset acquisition time, so that the number of cells on each sensing electrode in each fluorescent microscopic image can be counted and the statistical results can be obtained; then, the present application can also collect the electrophysiological signals generated by the tumor cells during the migration process captured by each sensing electrode on the microfluidic electrode array chip within the preset acquisition period, and use fast Fourier transform to obtain the power spectral density distribution corresponding to the electrophysiological signal. Based on the statistical results and the power spectral density distribution, the spike signal corresponding to each sensing electrode is extracted from the electrophysiological signal, and the spike occurrence frequency of each sensing electrode is determined; then, based on the statistical results and the spike occurrence frequency of each sensing electrode, the migration characteristics of the tumor cells are determined.

The application relates to a single-cell Hi-C clustering method and system based on contact number weight smoothing and feature fusion, which comprises the following steps: (1) data preprocessing; (2) contact number weight-based smoothing; using a weight matrix to quantify the influence of different neighbor fragments on a target chromosome fragment; (3) restart random walk smoothing; using a restart random walk algorithm to perform smoothing processing on the chromosome contact matrix after the contact number weight-based smoothing processing; (4) contact binarization; (5) principal component extraction; using KPCA to perform dimension reduction and generate cell embedding; (6) feature fusion; (7) spectral clustering; using a spectral clustering algorithm to realize cell clustering. The single-cell Hi-C clustering method provided by the application is obviously superior to existing clustering methods, greatly improves the clustering effect when a large-scale single-cell Hi-C data set is processed, and can identify cell types with a small number of cells in the data set.

The present invention provides methods for collecting desired cells from a sample using countercurrent centrifugal elutriation. The method of the present invention provides a continuous elutriation workflow with optimized conditions, which improves cell purity and retention during the elutriation process. In particular, the methods of the invention use a continuous counter-current centrifugal elutriation process which does not require harvesting cells between elutriation cycles or removal of cells from the separation chamber. The method of the present invention increases the purity, cell number yield, cell recovery, and cell viability of a desired cell population to improve downstream processing. The method of the invention also reduces the volume of buffers and reagents required for the treatment and accelerates the elutriation process, thereby achieving a cost-effective and more efficient cell manufacturing workflow.

A method of grouping certain cell densities to establish the number and volume of cells appearing in an image input the image into a self-encoder having a preset number of a density grouping models to obtain a preset number of reconstructed images. The image and each reconstructed image are input into a twin network model of the density grouping model corresponding to each reconstructed image, and a first error value is calculated between the image and each reconstructed image. A minimum first error value in the first error value set is determined, and a density range corresponding to the density grouping model corresponding to minimum first error value is taken as the density range. An electronic device and a non-volatile storage medium performing the above-described method are also disclosed.

Disclosed herein are methods to assess off-target sites resulting from CRISPR Cas nuclease systems wherein the methods require fewer cells than conventional strategies and can provide robust signal reads over noise. Also provided are methods of identifying Cas nuclease off-target cut-sites from the resulting reads using a computational pipeline including an artificial neural network model trained on known on-target and off-target cut-sites for the Cas nuclease.

The application relates to the technical field of culture medium prediction, and discloses a serum-free culture medium component prediction method based on artificial intelligence. The method comprises the following steps: constructing a phenotype condition vector according to a cell type identifier and a cell phenotype specification parameter, constructing a phenotype-formulation pairing data set according to historical culture batch data, training a conditional variational autoencoder with the phenotype condition vector as a conditional constraint, sampling a latent variable from a standard normal distribution, decoding the latent variable through a decoder to obtain a candidate culture medium formulation set, screening a candidate formulation with the minimum Euclidean distance through a forward verifier, and obtaining a recommended culture medium formulation. The application solves the problem that an existing serum-free culture medium component prediction method based on artificial intelligence cannot generate a culture medium formulation in reverse according to a clinical phenotype quality specification because the number of cells is taken as an optimization target.

The invention belongs to the technical field of image recognition, and provides a cell counting method and system based on a multi-modal image. The method comprises the following steps: shooting an RGB optical image and a fluorescence image of a blood cell culture sample to be identified, and converting the RGB optical image into an HSV optical image to form a multi-modal image; performing cell recognition processing on the fluorescence image, marking cell monomers and cell clusters in the fluorescence image, and counting each cell monomer to obtain a first cell number; extracting a multi-modal feature corresponding to the cell cluster based on the multi-modal image, and analyzing and processing the multi-modal feature by using a composite counting model constructed based on a plurality of graph variational auto-encoders to obtain a second cell number; and summing the first cell number and each second cell number to complete cell counting. According to the method, the complementary information of different modal images is fully utilized, and the cell number is obtained by analyzing the multi-modal characteristics of the cell cluster by using the composite counting model, so that the accuracy of cell counting is effectively improved.

The phagocytic cell AI identification training, detection and proportion detection analysis method comprises the following steps: preprocessing a sample to obtain a microscopic sample; shooting a microscopic examination sample to obtain a microscopic examination sample image; identifying and labeling phagocytic cells in the microscopic examination sample image to obtain a phagocytic cell labeling picture; and AI training is carried out by using the labeled picture to obtain an AI identification feature data set A, and the AI identification feature data set A comprises phagocytic cell AI identification feature data. Identifying the microscopic examination sample image by using an AI identification algorithm, identifying phagocytic cells in hydrothorax and ascites in a selected area S1 of the image, obtaining the number NUM1 of the phagocytic cells, and obtaining the number NUM2 of phagocytic cells; in a microscopic examination sample, the content of phagocytic cells in unit volume is equal to NUM1 / V1. The ratio of phagocytic cells is equal to NUM1 / NUM2.

The present application relates to the technical field of lithium ion battery safety monitoring, and discloses a method and device for early warning and positioning thermal runaway of lithium ion battery pack; first, real-time voltage, temperature, current and number data of each cell are collected to construct a cell state observation tensor with a space-time label; then, a cell thermal-electric state extended Kalman estimation algorithm is run based on the tensor to generate a cell health state partial order lattice; then, a thermal runaway risk propagation phase space grid is constructed, and finally, local attractor region identification and early warning decision based on manifold analysis are executed under grid constraints to output high-risk source cell number and early warning level. The present application solves the problems of existing technology, such as lagging early warning caused by dependence on late physical signs, lack of dynamic evaluation of cell group state consistency, and inability to accurately locate faulty cells, and improves the timeliness and positioning accuracy of thermal runaway early warning.

The present application provides a service scenario recognition method, an electronic device, and a storage medium, relating to the field of terminal technologies. The method includes: upon detecting a scenario recognition request for a target service, obtaining base station information of the base station to which the electronic device is currently connected and the scenario recognition accuracy of the target service, where the scenario recognition accuracy includes high accuracy; detecting that the base station information matches the operator identifier, cell number, and base station number in a base station fence snapshot; determining a target scenario fence snapshot according to the scenario fence identifier in the base station fence snapshot that matches the base station information; determining the fence area corresponding to the target scenario fence snapshot; obtaining the current location of the electronic device; detecting that the current location is within the fence area; obtaining the WiFi list of the electronic device; detecting that the WiFi list matches the WiFi features; and determining that the electronic device is located in the target scenario. This method can achieve low-power service scenario recognition and effectively improve the real-time performance of service scenario recognition.